### ALTERNATIVE INTAKE TECHNOLOGIES

AT INDIAN POINT UNITS 2 & 3

Attachment 6

Attachment 6

Biological Assessment

Biological Effectiveness of Alternative Intake Technologies for Indian Point Units 2 and 3 [LWB/AKRF/Normandeau/ASA]

Appendix A: Biological Analysis of Selected Cooling System Al ternatives for Indian Point Energy Center [ASA]

Appendix B: Biological Evaluation of Intake Screen Alternatives to Reduce Impingement and Entrainment Losses at Indian Point Energy Center [Normandeau]

Appendix C: Empirical Assessmen t of Expected Population-Level Effects of Reductions in Entrainment Losses at Entergy Nuclear Indian Point Units 2 and 3 [AKRF]

Appendix D: Responses to Issues Rais ed in NYSDEC’s FEIS [LWB/AKRF]

# Biological Effectiveness of Alternative Intake Technologies for Indian Point Units 2 and 3

Lawrence W. Barnthouse, Ph. D. LWB Environmental Services, Inc.

Douglas G. Heimbuch, Ph. D. AKRF, Inc.

Mark Mattson, Ph. D. Normandeau Associates, Inc.

John R. Young. Ph. D. ASA Analysis and Communications, Inc.



## February 2010

### i 

## Executive Summary

Entergy Nuclear Indian Point 2, LLC and Entergy Nuclear Indian Point 3, LLC (collectively, “Entergy”) have submitted a timely and complete renewal application for a State Pollutant Discharge Elimination Syst em (“SPDES”) permit for the Indian Point Entergy Center (“IPEC”) nuclear powered electric generating stations 2 and 3 (individually, “Unit 2” and “Unit 3,” and co llectively, the “Stations”). Counsel for Entergy informed Lawrence W. Barnthous e of LWB Environmental Services, Inc., Douglas G. Heimbuch of AKRF, Inc., Mark T. Mattson of Normandeau Associates, Inc., and John R. Young of ASA Analysis & Communication, Inc. (collectively the “Biological Experts”) that the New York State Department of Environmental Conservation (“NYSDEC” or “Department”) staff has proposed modifications in the Stations’ draft SPDES permit, including possible construction and operation of two large counter-flow, forced draft, plume abated hybr id cooling towers to be located on the

eastern shoreline of the Hudson River at the IPEC site in Westchester County, New York (the “NYSDEC Proposed Project”). Counsel for Entergy also informed the Biological Experts that consideration of the NYSDEC Propos ed Project is subject to an alternative technologies assessment, as directed by the NYSDEC Assistant Commissioner’s August 13, 2008 Interim Decision. Accordingly, th e Department may revisit its proposed modifications to the draft SPDES permit for the Stations and change them pursuant to Entergy’s alternative technologies assessment. 1



### This report supports the “Evaluation of A lternative Intake Technologies at Indian Point Units 2 & 3” prepared by Enercon Serv ices, Inc (“ENERCON”). Entergy retained ENERCON and the Biological Experts to de termine whether an alternative technology

exists that “will minimize adverse environmenta l impact to a level equivalent to that which can be achieved by closed cycle coolin g.” Interim Decision, at 25. According to the Interim Decision, this assessment must in clude “aquatic impact information, relevant cost information (for example, cost of c onstruction, installation, and operation), and the proposed location of the technology at the site.” Id. at 26. The In terim Decision allows Entergy to provide “further info rmation . . . with respect to the numbers of fish that are entrained and impinged at the Stations as part of the evaluation of alternative technologies.” Id. at 26, n.18. This s upporting report provides evaluations of the “biological effectiveness” (dis cussed below) of the Stations’ existing intake technology, the NYSDEC Proposed Project, and of various alternative intake t echnologies identified by ENERCON.

Biological effectiveness has two key aspects. The fi rst aspect of biological effectiveness is the degree to which a tec hnology can be expected to reduce the number of eggs, larvae, and older life stages of fi sh lost due to entrainment and impingement (“I&E losses”). The second aspe ct is the degree to which reductions in entrainment and impingement losses can be expected to result in measurable increases in the abundance of potentially affected fish populations.

1 The Interim Decision provides th at the Department must evaluate Entergy’s alternative technology assessment and “[i]f it determines that the proposed alternative may be substituted for closed cycle cooling . . . commence a proceeding to modify th e permit accordingly.” Id. at 25.

### ii In this report, reductions in I&E losses were evaluated using a combination of laboratory studies, field studies, and theoretical models that a ddress the potential fate of fish exposed to cooling water intake st ructures. This evaluation found that two technologies may potentially provide reductions comparable to the reduction achievable through closed cycle cooling. These technolo gies, cylindrical we dgewire screens and aquatic filter barriers, have operating characteristics that enhance the ability of small fish, including larvae, to avoid contact with the in take structure, there by preventing injury.

In addition, a cumulative benefits an alysis was performed to determine the

reductions in I&E losses associated with cylindrical wedgewire screens versus the NYSDEC Proposed Project over the projected operating life times of Units 2 and 3.

ENERCON 2 

### determined that construction and operation of two large counter-flow, forced draft, plume abated hybr id cooling towers to be located on the eas tern shoreline of

the Hudson River at the IPEC site in We stchester County, New York, as proposed NYSDEC would not be complete until 2029 due to the technical complexity of the project, to permitting requirements, and to likely litigation relating to local zoning ordinances. Cylindrical wedge wire screens, by contrast, are a proven technology that could be installed at both Unit 2 and Unit 3 by 2013 and 2015, respectively. Immediate installation of cylindrical wedgewire screens would result in cumulative reductions in I&E losses over the remaining lifetimes of Un it 2 and Unit 3 that are more than two times greater than those associated w ith the NYSDEC Propos ed Project.

The second aspect of biol ogical effectiveness was eval uated using analyses of data on fish populations of the Hudson Rive r collected during more than 30 years of operation of Indian Point Units 2 and 3. Th is evaluation indicates that none of the technologies evaluated, includi ng the NYSDEC Proposed Project , is likely to measurably increase the abundance of any Hudson River fish population as comp ared to the existing technology.

2 Engineering Feasibility and Costs of Conversion of Indian Point Units 2 and 3 to a Closed-Loop Condenser Cooling Water Configuration, Enercon Services, Inc., 2010.

### iii 

## Table of Contents

Executive Summary...................................................................................i

1. Introduction .............................................................................................................. ...... 1

2. Approach to biological evaluation of alternative technologies ..................................... 3 2.1 Technology descriptions .......................................................................................... 3 2.1.1 The existing technology at the Stations ............................................................ 3 2.1.2 Alternative technologies iden tified in the ENERCON report ........................... 4 2.1.3 Closed-cycle cooling .......................................................................................... 6 2.2 Interactions of fish with cooling water intake systems ............................................ 6 2.3 Fish species and metrics used to evalua te the biological effe ctiveness of intake technologies .................................................................................................................. .. 9 2.4 Overview of assessment approach ......................................................................... 10

2.4.1 Baseline definition .......................................................................................... 11

2.4.2 Estimation of baseline I&E losses .................................................................. 12 2.4.3 Development of exclusion factors, we dgewire screen avoidance factors, and entrainment and impingement survival factors ......................................................... 13 2.4.4 Conversion of entrainment and impingeme nt losses to equivalent age-1 fish 13 2.5 Computer code verification .................................................................................... 14 3. Results of technology evaluations ............................................................................... 15

4. Cumulative benefits of I&E reductions ...................................................................... 31 4.1 Comparison of immediate installation of cylindrical wedgewire screens to delayed installation of the NYSDEC Proposed Project ............................................................ 31 4.2 Sensitivity analysis ................................................................................................. 35 5. Potential I&E impacts of IPEC operati ons on Hudson River fish populations, with and without alternative technologies ................................................................................. 37 5.1 Entergy’s AEI report .............................................................................................. 37 5.2 Empirical assessment of expected popul ation-level effects of reductions in

entrainment losses due to a lternative technologies ....................................................... 38

5.2.1 Methods............................................................................................................ 39

5.2.2 Results ............................................................................................................. 40

6. Conclusions ................................................................................................................. 4 7

7. References ................................................................................................................... 49

### iv 

## List of Tables

Table 1. Definitions of cases evaluated..........................................................18

Table 2. Entrainment losses, equivalent ag e 1 losses, mean percent reductions from regulatory baseline, and incremental re ductions from alternative baseline for alternative intake technologies examined for Units 2 and 3........................19

Table 3. Impingement losses, equivalent ag e 1 losses, mean percent reductions from regulatory baseline, and incremental reduc tions from the current technology for alternative intake technologies examined for Units 2 and 3........................20

Table 4. Monthly and annual total percent reduction in age 1 equivalent entrainment losses of RIS associated with certain alternative intake technologies for Units 2

and 3. Reduction calculated from regulatory baseline..............................21

Table 5. Monthly and annual total percen t reduction in equivalent age 1 losses of impinged RIS Associated with certain alte rnative intake technologies for Units

2 and 3. Reduction calculated from regulatory baseline............................22

Table 6. Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due to entrainm ent and impingement for alternative intake technology for Units 2 and 3....................................................23

Table 7. Cumulative I&E losses, percent reduc tions in losses, and savings ratios for alternative intake technologies at Indian Point Units 2 and 3.......................33

Table 8. Cumulative I&E losses, percent reduc tions in losses, and savings ratios for alternative intake technologies at In dian Point Units 2 and 3, with post-2013 reductions discounted at 3% per year..................................................34

Table 9. Projected annual increases in ag e-1 equivalents due to eliminating current

entrainment losses at Units 2 and 3....................................................42

### v 

## List of Figures

Figure 1. Potential fates of organisms expos ed to a cooling wate r intake structure.........7

Figure 2. Sensitivity of cumulative percent reduction estimates for cylindrical wedgewire screens to alternative length-specifi c avoidance curves and assumptions concerning the survival of impinged larvae and juveniles.........................36

Figure 3. Observed year-to-year changes in riverwide juvenile abundance of American shad in response to observed year-to-y ear increases in riverwide post yolk-sac

larval abundance.........................................................................43

Figure 4. Observed year-to-year changes in riverwide juvenile abundance of river herring in response to observed year-to-year incr eases in riverwide po st yolk-sac larval

abundance.................................................................................44

Figure 5. Observed year-to-year changes in riverwide juvenile abundance of striped bass in response to observed year-to-year incr eases in riverwide po st yolk-sac larval

abundance.................................................................................45

Figure 6. Observed year-to-year changes in riverwide juvenile abundance of white perch in response to observed year-to-year incr eases in riverwide po st yolk-sac larval

abundance.................................................................................46

Figure 7. Percent reductions in age-1 equi valent entrainment and impingement losses compared to the regulatory baseline , for technologies evaluated in this report.....................................................................................48

### 1 

## 1. Introduction

This report supports the “Evaluation of A lternative Intake Technologies at Indian Point Units 2 & 3” (“ENERCON Report”) prep ared in response to the Interim Decision

of the NYSDEC Assistant Commissioner requiring Entergy to produce a report addressing the feasibility of alternative c ooling water intake t echnologies that will minimize adverse environmental impact to a level equivalent to that which can be achieved by closed cycle cooling, albeit at a lo wer cost. In this report, we evaluate the “biological effectiveness” of the Stati ons’ existing technology, the NYSDEC Proposed Project, and various alternative intake technologies evaluated by ENERCON.

ENERCON investigated the feasibility of installing the following alternative intake technologies at the Stations:

- Upgrade of the existing fish handling and return systems; - Modification of the existing Ristroph-t ype traveling water screens (“Ristroph screens”) to incorporate fine mesh screens;

- Traveling screen technologi es other than Ristroph scre ens, including dual flow traveling water screens, angled traveling screens, WIP screens, and MultiDisc ®



### screens;

- Passive intake systems, incl uding cylindrical wedgewire screens, perforated pipe inlets, and porous dikes/leaky dams;

- Barrier technologies, including aq uatic filter barriers, fish net barriers, behavioral barriers, and louver systems;

- Alternate intake location;

- Various types of flow reductions, incl uding via the existing dual/variable speed pumps, use of recycled wastewater as cooling water, outage timing, and radial wells; and

- Alternative heat rejectio n and recirculation, includi ng evaporative ponds, spray ponds, cooling canals, and in -river heat exchangers.

These technologies are described in detail in the ENERCON Report.

Biological effectiveness has two key aspects. The fi rst aspect of biological effectiveness is the degree to which a tec hnology can be expected to reduce the number of I&E losses, as compared to closed-cycle cooling. The second aspe ct is the degree to which reductions in I&E losses can be expected to result in measurable increases in the abundance of potentially aff ected fish populations.

We addressed the first aspect of biologi cal effectiveness using a combination of laboratory studies, field studies, and theoretical models that a ddress the potential fate of

fish that encounter the Stations’ existin g intake technology, th e NYSDEC Proposed Project, and various alternative intake tec hnologies identified by ENERCON. To address the second aspect of biologica l effectiveness, we assessed the long-term impacts of the operation of the Stations with and without th e existing technology, the alternative intake

### 2 technologies, and the NYSDEC Proposed Pr oject on representative important species (“RIS”) 3 

### and the Hudson River ecosystem as a whole. This assessment relied on the analyses and conclusions provided in Ente rgy’s Adverse Environmental Impact Report (Barnthouse et al. 2008) (“AEI Report”), as su pplemented by new analyses performed to support the evaluation of the alte rnative intake technologies.

Section 2 of this report provides an overview of how Hudson River fish populations come into contact with the St ations’ existing intake structure, brief descriptions of the al ternative intake technologies we ev aluated, and an explanation of the methods used to perform the technology comparisons to determine which alternative intake technologies results in I&E losses co mparable to the NYSDEC Proposed Project. Section 3 presents the results of the techno logy comparisons. S ection 4 evaluates the

benefits that could be achieve d through immediate installati on of cylindrical wedgewire screens as compared to c onstruction of the NYSDEC Proposed Project following the schedule developed by ENERC ON, which concluded that construction would not be complete until 2029. Section 5 discusses th e long-term impacts of the Stations’ operations, with and without modifications to the Stations’ existing intake technologies, on Hudson River fish populations . Section 6 summarizes the c onclusions from all of the above analyses. Detailed documentation of al l calculations is prov ided in Appendices Athrough C. Appendix D provides additional material supporting the evaluation of longterm impacts in Section 4 of this report.

3 As discussed in further detail in Entergy’s AEI Report, the original National Pollutant Discharge Elimination System (“NPDES”) permit hearings for the Stations identified eight fish species as RIS: striped bass, white perch, American shad, Atlantic tomcod, spottail shiner, bay anchovy, alewife, and blueback herring. These species were selected beca use of their recreational, commercial, and ecological

value.

### 3 

## 2. Approach to biological evaluation of alternative technologies

This section describes the technologies evaluated and explains the methods used to perform the technology comparisons. For purposes of introduction, Units 2 and 3 each have cooling water intake structures (“CW IS”) located on the eastern shore of the

Hudson River. These CWIS c onsist of water intake bays and pumps that provide river water to cool the steam condensers (see Section 2.2 of the ENERCON Report). Traveling screens 4 

### located within the intake bays pr event debris from entering the pumps and condensers. Eggs, larvae, juveniles, and older fish present in the cooling water may come into contact with these screens (a process termed “impingement”), or, if small enough to fit through openings in the traveling screens, ma y be drawn through them and pass through the condensers with the cooling water (a process termed “entrainment”). As discussed in the following section, a variety of cooling water inta ke technologies are available to reduce I&E losses at power plants.



## 2.1 Technology descriptions

This section describes the existing intake technology at Units 2 and 3, which includes many features specifically intended for reducing I&E lo sses. The existing traveling screens and fish return system, portions of which were designed by Dr. Ian Fletcher, a consultant to th e Hudson River Fisherman’s A ssociation (the “HRFA,” now Riverkeeper, Inc.) and subjected to a full-scale field test prio r to installation, is described below. The description of the existing inta ke technology is followed by descriptions of the alternatives evaluated by ENERCON for feasibility, including the NYSDEC Proposed Project.



### 2.1.1 The existing technology at the Stations

The Stations’ existing CWIS already incl ude a number of feat ures that reduce

I&E losses. These features include:

- Modified Ristroph-type tr aveling water screens,

- Fish handling and return systems,

- Low pressure screenwash systems,

- Low temperature increase across the c ondensers and rapid transit through the cooling system,

- Seasonal flow reductions due to dual/ variable speed pump operations, and

- Flow reductions due to maintenance/refueling outages.

4 These screens are called traveling screens because th ey are linked to form a vertically-oriented endless belt so that they can be rotated and washed to remove trapped debris. See Section 4.1 of the ENERCON Report for a detailed description of the traveling screens installed at Units 2 and 3.

### 4 The Stations’ modified vertical Ristroph screens were installed in 1990 following a collaborative research effort among the form er owners of the Sta tions and Dr. Fletcher, a consultant to Riverkeeper’s predecessor (as noted above). 5 

### The current Ristroph screens were specifically designed to gently re move fish from the cooling water flow and

return them live to the Hudson River. The St ations’ traveling water screens consist of a

continuous series of wire me sh panels and curved fish handling buckets attached to

frames and attached to two matched strands of roller chains. These panels and buckets are commonly referred to as Ristroph Screens.

In addition to the Ristroph screens, the fish handling and return systems and low pressure screenwash systems were specifica lly designed to minimize impingement losses. The low through-screen and approach velo cities (approximately 1 foot per second (“fps”)) when all pumps are operating at full flow) increases the likelihood that impingeable sizes of fish may escape the intake flow. The screens are rotated continuously, and any fish in proximity to the screens are lifted up in fish collection troughs that were specially designed to mini mize stress on fish. The screenwash system further minimizes stress on fish as they are washed out of the bucke ts and into the fish return system. This system was designed to minimize stress on captured fish, following

extensive field-scale studi es conducted under the revi ew of NYSDEC staff and Riverkeeper experts. The discharge points fo r the Unit 2 and Unit 3 fish return pipes were selected after conducting dye and fish release studies to find locations that would minimize reimpingement.

The comparatively low Δ T (temperature increase as water passes through the condenser tubes) of about 10°C, and short transit times (average 9.7 min for Unit 2 and 5.6 min for Unit 3 at full flow) reduce therma l stress and permit significant entrainment survival for some species.

Flow reductions have the potential to reduce both impingement and entrainment

at Unit 2 and Unit 3. 6 

### Both units are equipped with dua l or variable speed pumps that permit intake flows to be reduced during cert ain seasons (primarily late October until early May). In addition, maintenance outages are scheduled, when reasonably practical, during seasons when entrainable life stages, i.e. eggs and larvae, are present in the river. Typically, these outages occur during the late spring entrainment period, with the result that only one unit is operati ng during the approximately 25- day outage period each year.



### 2.1.2 Alternative technologies id entified in the ENERCON report

In addition to the existing technology, ENERCON evaluated a wide variety of alternative intake technologies that could potentially furthe r reduce I&E losses in order to determine the feasibility of installing such technologies at the Stations. ENERCON’s

5 Flow Dynamics and Fish Recovery Experiments: Water Intake Systems , Transactions of the American Fisheries Society, Vol. 119, No. 3, pp. 393-415 (R. Ian Fletcher).

6 At a given level of generation, reducing the cooling water flow increases the Δ T and transit time, potentially increasing the mortality rate of entrained organisms. To accura tely evaluate the benefit of flow reductions, the reduced number entrained must be weighed against the potentially higher mortality rate.

### 5 evaluations emphasized technologies capable of reducing entrainment, because as discussed in Section 4.1 of the ENERCON report, the existing “fish return systems at

Units 2 and 3 are considered to be state-of-the-art” and that “upgrades to the current fish return systems are not expected to provide appreciable biological benefits.” The principal technologies evaluated include modi fication of the existing Ristroph screens to incorporate fine mesh screens (Section 4.2.1 of the ENERCON report), cylindrical wedgewire screens (Section 4.3.1 of the ENERC ON report), aquatic f ilter barrier systems (Section 4.4.1 of the ENERCON report), and oper ational changes such as flow reductions and changes in the timing of maintenan ce/refueling outages (Section 4.6 of the ENERCON report). Technologies that would provide little or no di rect reductions in entrainment losses (i.e., upgrades to the exis ting fish handling and return systems, fish barrier nets, behavioral barrier s, louver systems, additional flow reductions, etc.) were not

considered as viable alternatives to the current screening systems at the Stations.

As discussed in Section 4.2.1 of ENERC ON’s report, the fi ne mesh screen alternative involves replacing the current 1⁄4” x 1⁄2” mesh sc reen panels used in the Stations’ existing Ristroph screen s with panels with smaller mesh sizes are intended to screen out fish, small juveniles, larvae, a nd eggs that pass through the existing screens, and thereby reduce entrainment. The eggs, larvae, and early juveniles excluded by the fine mesh screen panels would be washed o ff the screens into the Stations’ fish return systems and returned to the River. En trainment would be reduced because these organisms would be impinged rather than entrai ned. Fish eggs are very fragile and it is therefore assumed here that eggs impinged on fine-mesh screens would be unlikely to survive. Since it is also assumed that entrained eggs do not survive, fine mesh screens would provide no net benefit with respect to eggs. However, larv ae and small juvenile fish may survive impingement. If the surviv al rates of larvae and small juveniles is higher than the survival rate of entrained la rvae and juveniles, then fine mesh screens could reduce I&E losses for these life stages . Species-specific entrainment survival estimates are discussed in Appendix A to this report; survival estimates for larvae and juveniles impinged on fine mesh screens are discussed in Appendix B.

We evaluated the reduction in I&E losses a ssociated with fine mesh screens with mesh sizes ranging from 1-9 mm in this report . Since no changes w ould be made to the fish buckets, the spray wash system, or the fish return system, the survival of older impinged fish was expected to be the same as with the existing t echnology. Fine mesh screens with mesh sizes ranging from 1-9 mm are evaluated in this report.

As discussed in Section 4.3.1 of ENER CON’s report, cylindrical wedgewire screens are designed to reduce I&E losses in two ways. Like the Stations’ existing Ristroph screen technology, they prevent aquatic organisms larger than the screen slot width from entering the intake and becoming entrained. In addition, because cylindrical wedgewire screens are typically deployed directly in the source waterbody rather than being housed within an intake bay, flows within the source water body (e.g., the tidal flows in the Hudson River) create hydrodynamic forces that can sweep organisms past the cylindrical wedgewire screens without comi ng into physical contact with the screen. Thus, even organisms that are smaller in diameter than the screen slot width can be swept passed the intake. Because of the very lo w through-screen curren t velocity and the

### 6 sweeping currents that m ove organisms past the intake st ructure, cylindrical wedgewire screens are expected to eliminate impingeme nt and greatly reduce entrainment. We evaluated the biological effectiveness of we dgewire screens with sl ot widths from 1-9 mm in this report.

As discussed in Section 4.4.1 of ENERC ON’s report, aquatic filter barriers represent a relatively new fish protection tec hnology. The filter barrier is a fabric curtain, completely surrounding the intake structure, which allows water to pass through while excluding fish, larvae and eggs. Because of th e very low through-screen current velocity most organisms, specifically fish of all ag es and larvae, should be able to avoid the curtain rather than be physically excluded. Thus, this technology is expected to greatly reduce or eliminate both entrainment and impi ngement. The evaluation of aquatic filter barriers in this report includes an estimation of the fraction of fish, eggs, and larvae in the vicinity of the intake that pass under, over, or through gaps in the barrier and subsequently are entrained or impinged.

As discussed in Section 4.6 of ENERCON’ s report, reducing intake flows would

also reduce I&E losses. Flow reductions resu lt in reductions in the power output of the

Stations. Several alternative flow and power reduction scenario s were evaluated by ENERCON. The analysis of I&E losses includes changes to both the numbers entrained or impinged and their mortality rates. In addition, ENERCON evaluated the benefits of changing the timing of maintenance/refueli ng outages to occur during the month for which outages would provide the greatest percent reduction in age-1 equivalent entrainment losses compared to the existi ng technology, while avoiding outages during peak-demand summer months.



### 2.1.3 Closed-cycle cooling

In the draft SPDES permit NYSDEC issued in 2003, NYSDEC proposed the NYSDEC Proposed Project. 7 

### Pursuant to the Interi m Decision, NYSDEC may revisit this proposal and change it pur suant to Entergy’s alternativ e technologies assessment



## 2.2 Interactions of fish with cooling water intake systems

Four life stages of fish are relevant to evaluating cooling water intake technologies: eggs, larvae, juvenile fish (a lso called “young-of-the-y ear” or “YOY”), and older fish. An egg, larva, juvenile, or olde r fish approaching the Stations has 3 possible fates, as illustrated in Figure 1. First, if it is able to swim, it may avoid contact with the screen by swimming or moving away. This fa te is termed “avoida nce.” Second, it may come into contact with the screen but be excluded from the intake because it is too large to pass through the screen. This fate is term ed “impingement.” Im pinged fish, larvae, and eggs are washed off the screen and returned to the river via the Stations’ fish return system. Third, it may pass through the scre en, be entrained through the plant, and discharged back into the River. Th is fate is termed “entrainment.”

7 Discussed in ENERCON’s report entitled “Engineerin g Feasibility and Costs of Conversion of Indian Point Units 2 and 3 to a Closed-Loop Condenser Cooling Water Configuration”

### 7 Figure 1 Potential fates of organisms exposed to a cooling water intake structure. Only organisms in the shaded compartments in Figure 1 are included in the loss

estimates. 

## Organisms approaching CWIS

Avoidance

Exclusion Avoid-live

Impinged-live

Impinged-dead

Entrained-live

Entrained-dead Survive?

Survive? No contact with

screen

Pass through

screen 

## Yes

Yes No

No 

# Fate

Entrainment Excluded By screen 

## Organisms approaching CWIS

Avoidance

Exclusion Avoid-live

Impinged-live

Impinged-dead

Entrained-live

Entrained-dead Survive?

Survive? No contact with

screen

Pass through

screen 

## Yes

Yes No

No 

# Fate

Entrainment Excluded By screen

### 8 The relative probability of each of these even ts events set out in Figure 1 occurring differs on the life stage of the fish and the type of technolog y installed. With respect to avoidance, fish eggs have no swimming ab ility, so they cannot avoid the intake. Depending on the dimensions of the screen mesh, they may be excluded. If they are small enough to pass through the mesh, they are entrained. Larvae have a weak swimming ability that increases as they gr ow. Some technologies, and in particular cylindrical wedgewire screen technology, take advantage of “sweeping” currents in the source water body to move organisms past the intake structure without being excluded or entrained. Experimental studi es appear to show that la rvae can detect the currents drawing water through the screen, move awa y, be drawn into the sweeping current, and avoid impingement and entrainment (see discu ssion in Appendix B). These same studies

have shown that the avoidance ab ility of larvae is a function of length, i.e., larger larvae have much more avoidance ability than smalle r larvae. It is gene rally accepted that, for any screening technology, if inta ke flow velocities are at or below 0.5 fps, juvenile and older fish can avoid impingement. Fish that do not avoid the intake structure are either impinged or entrained. Juvenile and older fish large enough to be excluded with the Stations’ existing technology will also be excluded by all of the other technologies evaluated in this report.

Entrainment – the third possible fate of an organism approach ing an intake – occurs when eggs, larvae, and very small juvenile fish pass through the mesh in the Stations’ existing technology. Traveling screens w ith finer mesh sizes – one of the alternat ives discussed in

Section 2.1.2 above – will exclude some of thes e fish, so that they are impinged rather

than entrained. The avoidance factors and exclusion factors used in this report are documented in Appendix B. Survival rates of fish impinged with the existing technology are discussed in Appendix A.

The probability that an egg, larva, juvenile, or older fish will survive its encounter with the Stations depends on its age and size and whether it avoids the intake, or is entrained or impinged. For this assessment, because fish eggs are very fragile it is assumed that all eggs that encounter the in take structure do not survive. This is a conservative assumption that is made b ecause no species-specific estimates of impingement or entrainment survival of eggs are available. However, species-specific survival studies performed at the Stations ha ve shown that larvae a nd small juveniles may survive entrainment. Many studies of entrai nment and impingement survival at Units 2 and 3 have been performed. Results of th ese studies have recently been summarized by Young et al. (2009) for striped ba ss. Site-specific entrainment survival values for all RIS species are documented in Appendix A. Larv ae, juveniles, and older fish may survive impingement and subsequently return to the river, with the proba bility of survival depending on the species and size of the fis h. Estimates of impingement survival for small fish impinged on fine mesh screens ar e documented in Attachment B. Larvae, juveniles, and older fish are assumed to surv ive if they successfully avoid contact with the intake (Appendix B).

### 9 

## 2.3 Fish species and metrics used to evaluate the biological effectiveness of intake technologies

Eight species commonly entrained or impi nged at Unit 2 and Unit 3 are addressed in this report: striped bass, white perch, American shad, Atlantic tomcod, spottail shiner, bay anchovy, and two species collectively k nown as “river herring” (alewife and blueback herring). These species were identified by NYSDEC as RIS for the original NPDES permit hearings for the Stations. In addition to being considered important due to their recreational, commercial, and ecologi cal value, these species have historically

accounted for more than 98% of fish larvae and 92% and of juven ile fish (YOY) fish captured, respectively, in the utilities’ LRS and Beach Survey (CHGE 1999, Tables V-45 and V-46). A detailed discussion of the biol ogical attributes of each RIS species is provided in the Section V of Draft Environmental Impact St atement (“DEIS”) prepared by the Hudson River utility companies (CHGE 1999).

As discussed in Entergy’s AEI Report (B arnthouse et al. 2008) , natural mortality of early life stages of fish is very high. For example, according to Secor and Houde (1995), more than 99.99% of newly-spawned st riped bass eggs die from natural causes within 60 days. Only about one striped ba ss egg in 100,000 is lik ely to survive to become a one-year-old fish. As young fish de velop and grow, mortal ity rates decline. According to Secor and Houde (1995), 97% of the youngest and smallest striped bass larvae can be expected to die each day. Of those that survive to reach the next stage of development, approximately 15% can be expect ed to die each day until they transform into juvenile fish. Approximate ly 4% of striped bass that su rvive until the juvenile stage would be expected to survive to become one-y ear-old fish. Because their probabilities of survival are so low, fish eggs and larvae make much smaller contributions to the adult populations of fish than do juvenile and olde r fish. For this reason, the total number of eggs, larvae, juvenile, and older fish entr ained or impinged provides an inaccurate and potentially misleading metric for evaluating the benefits of alternative intake technologies.

EPA recognized this problem in performi ng its case study re ports supporting the Phase II rulemaking (EPA 2002, 2004). Rather than basing the case studies on total

numbers of fish entrained or impinged, EPA converted the nu mbers of fish entrained or impinged at different ages to equivalent one-year-old fish using estimates of the probabilities that fish entrained or impinged at various ages would survive to age 1. Conversion to equivalent age-1 fi sh allows I&E losses that occu r at different life stages to be combined into a single metric that wei ghts the losses according to the number that could, on average, have survived to age 1. The biological effectiveness of each alternative, using this approach, reflects th e net effectiveness of that alternative at reducing losses of young fish, including both en trainment and impingement losses. More

detailed discussions of the conversion methodology can be found in the EPA case study reports (EPA 2002, 2004) and in guidance ma nuals prepared for the Electric Power Research Institute (EPRI 2004, 2005).

### 10 

## 2.4 Overview of assessment approach

The approach used to evaluate the biologi cal effectiveness of alternative intake technologies, as compared to closed-cyc le cooling, involves the following steps:

- Definition of baseline impingement and entrainment losses,

- estimation of the reduction in impingement and entrainment losses, expressed as equivalent age-1 fish, that could be achieved using each technology alternative,

and

- comparison of all alternatives to closed-cycle cooling.

As discussed below, two different concep tual definitions of baseline losses are used in this report: a “re gulatory baseline” that has recen tly been used by NYSDEC in SPDES permit proceedings for other New Yo rk power plants, an d an “alternative baseline” intended to more closely approxi mate actual impingement and entrainment losses that would occur at Unit 2 and Unit 3, if the existing intake technology had not been installed. For both definitions, estimation of baseline impingement and entrainment losses requires the use of historical data to estimate impingement and entrainment losses

under current conditions. Data from laborator y experiments, field tests, and full-scale operation of the alternatives are then used to estimate the reductions in impingement and

entrainment at Unit 2 and Unit 3 that would be expected, if these technologies were deployed.

This section summarizes all of the above procedures. In addition, it summarizes the steps performed to ensure that the com puter programs used to process the data and perform the calculations were free from errors that could compromise the validity of the

assessment. Detailed documentation of all of these procedures is provided in Appendices

A and B.

### 11 

### 2.4.1 Baseline definition

In recent regulatory prac tice under 6 NYCRR 704.5 (the New York statutory equivalent of §316(b) of the Clean Water Ac t), NYSDEC has evaluated the effectiveness of proposed intake technologies at reduci ng I&E losses by comparing the estimated I&E losses for the proposed technology to the lo sses that would occur under a “baseline”

condition. The baseline losses are those that would occur if the station were built and operated according to the following conditions:

- Shoreline intake structure w ithdrawing from surface waters,

- 3/8” mesh traveling screens operate d as needed for debris removal,

- Full flow operation 365 days per year, and

- No survival of impinged or entrained fish

This baseline is a regulatory construct th at assumes that no entrained or impinged fish survive, regardless of the effectivene ss of existing technologi es. In reality, field

studies conducted at the Stations have demonstr ated that for some species the survival of entrained organisms is high, even in the abse nce of technologies spec ifically employed to reduce entrainment mortality (See Appendix A). 8 

### Hence, the regulat ory baseline is not

intended to and does not descri be historical I&E losses at Unit 2 and Unit 3. The failure of the regulatory baseline to consider entrai nment survival does not affect the technology evaluations presented in this report, because the percent reductions in entrainment losses for the alternative technologies (which include site-specific estimates of entrainment and impingement survival) are compared to percen t reductions associated with closed-cycle cooling, relative to the same baseline.

The failure of the baseline to consider entrainment survival would, however, be important if the economic benefits of the alternatives were being evaluated. An economic benefits analysis is different from regulatory analysis focused on determining compliance with a performance standard. An economic benefits analysis involves assigning monetary valu es to the numbers of fish save d by each technol ogy. For species such as striped bass, which have shown relati vely high rates of entrainment survival in site-specific studies, the use of the regulator y baseline would substant ially bias benefits

estimates because much of the calculated re duction in entrainment losses would reflect the zero survival assumption used in the ba seline, not the actual performance of the technologies.

For this reason, an alterna tive baseline was developed using the configuration and flow assumptions used in the regulatory base line, but using site-spe cific estimates of the entrainment survival that would be expected to occur under those assumptions. This baseline is still conservative because it assumes that both Unit 2 and Unit 3 operate at full flow for 365 days per year, with no mainte nance outages. Increm ental reductions in

8 This inconsistency does not aff ect comparative estimates of impingement losses, because Unit 2 and Unit 3 were originally built without fish return systems, so that survival of impinged fish would have been zero, as assumed in the regulatory baseline.

### 12 losses for the existing technology are comp ared to the alternative baseline, and

incremental reductions for all other tec hnologies were compared to the existing technology. In addition, the al ternative baseline is used to calculate the fishery yield and foregone fish production (i.e., biomass of prey fish such as bay anchovy available for consumption by predators such as striped ba ss) represented by these fish. The methods

used for these calculations are the same me thods used in the EPA regional case studies (EPA 2002, 2004) and recommended in EPRI guidance (EPRI 2004).



### 2.4.2 Estimation of baseline I&E losses

The most recent information on species-sp ecific entrainment densities (number of organisms per volume of water withdrawn) at Units 2 and 3 are fo r the years 1983-1987. As discussed in Entergy’s AEI Report, the rela tive abundances of the eight RIS present in the river have changed since the 1980s, a nd these changes in abundance likely would have also changed the numbers of each sp ecies entrained at Unit 2 and Unit 3. To

estimate levels of entrainment that would ha ve been expected in more recent years, estimates of the numbers of each species in the vicinity of IPEC during the years 1983- 1987, as measured in the LRS, were compared to estimates of the density of that species in entrainment samples. These comparisons were used to calculate “conversion factors”

that relate the abundance of each species in the river to its density in entrainment samples. These conversion factors were then applied to river abundance estimates for the years 2001-2007 to produce estimates of the dens ity of each species th at would have been expected in entrainment samples during thos e years. The years 2001-2007 are the most recent years for which data from the LRS are av ailable, therefore, they provide the best available information concerning the abundance of RIS species curren tly present in the vicinity of Unit 2 and Unit 3. Because pr obabilities of exclusion, avoidance, and survival of potentially entrained larvae differ depending on length (see section 2.2 above), length distribution data for larv ae entrained during 1983- 1987 were used to estimate the length distributions of larvae that would have been entrained during 2001- 2007. Appendix A provides a detailed explanati on of the procedures used to perform all

of the above calculations.

A similar procedure was used to estimate expected impingement of each RIS for the years 2001-2007. Impingement sampli ng at IPEC was conducted from 1972 through 1990. The most recent seven years of impinge ment sampling (1984-1990) were selected for use in estimating recent impingement rates, because a consistent, statistically-based sampling design was used to estimate impi ngement during these years (Mattson et al. 1988). Because impingement data were collect ed and analyzed in exactly the same way during each of these years, we can be confident that the results are not biased due to changes in sampling design. Quarterly impinge ment densities, by species, for each year during this period were related to the abundance of each species in the river during that month, as estimated from Beach Seine Surv ey (“BSS”) and Fall Shoals Survey (“FSS”) data. These two programs sampled fish within the size range that are impinged at Unit 2 and Unit 3. Conversion factors analogous to those developed for entrainment were applied to river abundance data for 2001 -2007 to obtain monthly estimates of

### 13 impingement, by species for these years. A ppendix A provides a detailed explanation of the procedures used to perform all of the above calculations.

Operational measures (flow reductions and outages) and the NYSDEC Proposed Project reduce the number of organisms s ubject to impingement and entrainment by reducing the volume of water withdrawn from the Hudson River for condenser cooling. Entrainment and impingement estimates fo r these technologies were obtained by reducing the entrainment and impingement estimates proportionate to the estimated

reductions in intake flows.



### 2.4.3 Development of exclusion fa ctors, wedgewire screen avoidance factors, and entrainment and impingement survival factors

Most of the technology altern atives evaluated in this report reduce I&E losses by increasing the exclusion of eggs, larvae, and sm all juveniles from the intake structure, by permitting some larvae and juveniles to avoid p hysical contact with the intake structure, or by increasing the survival rate of fish that encounter the intake structure. Estimates of species and length-specific exclusion, avoida nce, and survival factors are needed to quantify the biological benefits of these altern atives. Estimates of species-specific and size-specific exclusion and avoidance factors were developed for each RIS and are documented in Appendix B. These factor s permit length-specific evaluations of the effect of wedgewire screen slot width on the fraction of fish larvae and small juveniles

that avoid contact with the in take structure. They also permit size and species-specific evaluation of the effect of wedgewire screen slot width and fine mesh screen mesh size on the fraction of fish larvae and small juveni les that are impinged versus entrained.

Estimates of impingement survival rates for very small fish impinged on fine mesh screens are documented in Appendix B. Estimates of entrainment survival rates and impingement survival for fish impi nged on the existing in take technology, specifically the Ristroph screens at Unit 2 a nd Unit 3 are documented in Appendix A. In the case of entrainment, survival rates for flow reduction scenarios were adjusted, where necessary, to account for the effects of increa sed discharge temperatures on survival rates of entrained larvae (i.e., when flow is re duced, the discharge temperature increases, which results in less survival).



### 2.4.4 Conversion of entrainmen t and impingement losses to equivalent age-1 fish

As discussed in Section 2.3 above, convers ion of I&E losses to age-1 equivalents

allows I&E losses that occur at different life st ages to be combined into a single metric that weights the losses according to the numbe r that could, on average, have survived to age 1. After adjusting the en trainment estimates to account for avoidance and survival, life-stage-specific estimates of entrainment losses for each species were converted to equivalent age-1 fish and then summed. Larv ae that would have been entrained using the

Stations’ current inta ke technology but would instead be impinged on m odified Ristroph screens (i.e., fine mesh screens) are includ ed in the entrainment totals, but with the

### 14 survival factors for impingement rather th an entrainment applied. Similarly, after adjustments for avoidance and survival, estimates of impingement losses for each species were converted to equivalent age-1 fish. Th e parameter values used for these calculations are documented in Appendix A.



## 2.5 Computer code verification

Hudson River data sets, collected over more than 35 years by multiple contractors, constitute the most comprehensive data set available for any estuarine fish community in North America. However, b ecause sampling protocol s and data recording methods have changed with time, these data sets are very complex, and the computer programs (termed “codes” by program writers) needed to access these data and convert them to a form that can be used to implement the models used in this report are similarly very complex. The codes used here for this purpose are all written in the SAS programming language. To verify that SAS codes used in this evaluation are accurate, one of the contractors (Normandeau Associates ) performed an independent verification of the codes developed by another contractor (ASA). The step s involved in the verification process are documented in Appendix B.

### 15 

## 3. Results of technology evaluations

Table 1 summarizes the “cases” included in th e alternatives anal ysis. Cases 0 and 0.5 represent, respectively, the regulatory baseli ne and the alternative baseline used in the calculations. Case 1 represents the existi ng intake technology at the Units 2 and 3, including the fish return system and the Ristroph screens. Cases 1.001 through 1.204 represent the existing intake technology, supplemented with several combinations of flow reductions and power reductions. Case 1.5 represents a one-month, one-unit outage scheduled during the month (September) that would provided the greatest estimated reduction in total age-1 equivalent entrai nment losses compared to the existing technology, while avoiding outages duri ng high-demand summer months (Enercon, Section 4.6). Cases 2 through 7 represent cylindrical wedgewire screens with slot widths ranging from 1 mm to 9 mm. Cases 8 through 13 represent fine mesh screens with mesh sizes ranging from 1-9 mm. Case 14 represents the aquatic filter barrier, and cases 15 and 15.5 represent closed-cycle cooling scenar ios using alternative assumptions about the magnitude of service water flows used for make-up water.

Tables 2 and 3 summarize, respectively, entrainment and impingement outputs for each case, including annual mean total losses ov er all species, annual mean total age-1 equivalent losses over all species, mean per cent reductions in losses and age-1 equivalent losses compared to the regulatory baseline, and incremental reductions compared to the alternative baseline (for th e existing technology) or compar ed to the existing technology (all other technologies). To calculate the m ean percent reductions, percent reductions in losses were calculated for each RIS, for each year from 2001-2007. These annual values were averaged across all species, and then the yearly across-species averages were averaged to obtain a mean percent reduction over all years. The reason for averaging across species is that a truer measure of tec hnology effectiveness for all of the RIS can be obtained. If percent reductions were to be calculated on the total losses, then the

effectiveness measures would be dominated by the most abundant taxa, bay anchovy, and to a lesser extent striped bass. Averaging percent reductions across species provides a better discrimination between technologies becau se it gives equal weight to species such as Atlantic tomcod and white perch, which w ould receive little weight if metrics were

based on abundance.

Table 4 provides estimates of the percen t reduction in equivale nt age-1 losses due to entrainment, by month, as calculated usi ng the regulatory baseline. These values quantify the contribution of each month to the total percent reduction in age-1 equivalent losses. Apportioning the total percent reducti on by month permits evaluation of seasonal

variations in effectiveness. For example, technologies such as wedgewire screens and filter barriers that reduce entrainment provide nearly all their benefits between May and October, because these are the months in whic h entrainable life stages are most abundant in the river. If, for oper ational reasons, it proved to be impractical to deploy these technologies during the winter, there would be little or no reduction in the effectiveness of these technologies with respect to entrainm ent. Table 5 provides similar estimates of monthly percent reductions for impingement.

### 16 Table 6 provides estimates of total age-1 equivalent losses, equivalent yield to fisheries, and production foregone for each technology alternative for each RIS. These estimates are for entrainment and impingement combined. Equivalent yield, as discussed by EPRI (2004) refers to the reduction in harvest of recreationally or commercially important species due to entrainment and impingement. Production foregone, as discussed by EPRI (2004), refers to the reduct ion in prey biomass available to predators due to entrainment and impingement of prey species. These values are not used in the technology comparisons, but would be used in economic benefits analyses such as those performed in EPA’s case studies (EPA 2002, 2004).

Table 2 shows that, compared to the regul atory baseline, all of the technologies, including the current technology, provide a 30% or greate r reduction in age-1 equivalent losses, as compared to the regulatory baseli ne. However, wedgewire screens and aquatic filter barriers provide reductions in age-1 e quivalent losses of approximately 90%, only slightly lower than the reduction calculated for the NYSDEC Proposed Project (96.3% to 97.6%). Flow reductions, combined with va rious levels of reduction in power output, provide reductions in age-1 equivalent losses between 35% and 50%. Shutdown of one unit during September of each year reduces age-1 equivalent losses by 36.3% compared to the regulatory baseline. Table 2 also shows that the estimated incremental reduction in losses (comparisons to the alternative baseli ne or current technol ogy) is negative for some fine mesh alternatives. A negative value for the incremental reduction indicates the estimated losses for the alternative technology are greater than the estimated losses for the current technology.

Modification of the existing Ristroph scr eens to incorporate fine-mesh screens, regardless of mesh size, provides no additional benefits over the Stations’ current technology and, depending on the assumptions made concerning th e survival of fish that are impinged rather than entrained, may act ually be more harmful than the current technology. The reason for this result is that, for some species and length classes, entrainment survival rates are higher than corresponding impingement survival rates (See section 2.1.2 above).

Results of this evaluation indicate that cy lindrical wedgewire screens and aquatic filter barriers are nearly as effective as closed-cycle cooling at reducing entrainment mortality.

The reason for the effectiveness of these technologies is that larvae have a high probability of avoiding direct contact with the screen. In the case of wedgewire screens, as discussed in Appendix B, the sweeping flow of the Hudson River appears to act together with the limited avoidance abilities of fish larvae to allow larvae to be diverted around the screen rather than being impinged on the screen or passing through the screen. Eggs and very small larvae are unable to avoid the screen, but high percentages of larger larvae appear to avoid entrainment and im pingement (see Section 2.2 above). Available data indicate that the avoidance phenomenon is only slightly affected by slot width. Aquatic filter barriers also appear to be highly effective at reducing entrainment of species and sizes of eggs and larvae. The pore dimensions of these barriers are small enough to exclude all life stages of fish, and the through-barrier velocity is low enough to

### 17 prevent impingement. However, aquatic filter barriers deployed at the Lovett Generating Station (discussed in Attachment B) have at best about 90% effective, because under some conditions unfiltered water can pass over the barrier, under the barrier, or through gaps or holes in the barrier.

Table 3 shows that, regardless of which baseline is used, the existing intake technology provides approximately an 80% re duction in impingement mortality. Flow reductions and modified outage schedules provide incremen tal reductions in impingement losses due to reduced intake fl ows. Modification of the existing Ristroph screens to incorporate fine mesh screens, regardless of mesh size, provide no additional protection. Cylindrical wedgewire screens a nd aquatic filter barri ers provide reductions in age-1 equivalent losses due to impingeme nt that are equal to or greater than the reduction provided by closed-cycle cooling. In the case of wedgewire screens, the cylindrical design, the low intake veloc ity, and the sweeping flow permit actively swimming fish to avoid contact with the screen and move with the sweeping flow. In the case of aquatic filter barriers , the through-barr ier velocity is too low to trap fish.

Table 4 shows that, for all technologies, most of the reducti ons in entrainment mortality compared to th e regulatory baseline occurs in June, July and August. These are the months in which entrainable life stages are most abundant, because spawning of all RIS species except Atlantic tomcod occurs dur ing the spring and summer. In contrast, Table 5 shows that reductions in impingement mortality are spread much more evenly throughout the year, with the highest values occurring in January, February, and March. The reason for this is that impingeable sizes of white perch and, to a lesser extent, striped bass, are abundant in the vicinity of Unit 2 and Un it 3 during the winter.

Table 6 shows that, for all species a nd technologies, entrainment accounts for most of the losses of equivalent age-1 fis h, equivalent yield, and production foregone. Bay anchovy accounts for most of the equiva lent age-1 fish and production foregone lost due to entrainment and impingement and stri ped bass accounts for most of the foregone equivalent yield to fisheries. Cylindrical wedgewire screens and aquatic filter barriers provide biological effectiveness benefits – as measured in re ductions in impingement and entrainment losses – that are comparable to those provided by the NYSDEC Proposed Project.

### 18 Table 1. Definitions of cases evaluated

Case no. Technology Source 0 Regulatory baseline This report, section 2.2.1 0.5 Alternative baseline This report, section 2.2.1 1 Existing intake technology 9 ENERCON report, section 3 1.001 Flow reduction, 0 MW loss ENERCON report, section 4.6.1 1.101 Flow reduction, 10 MW loss ENERCON report, section 4.6.1 1.202 Flow reduction, 20 MW loss ENERCON report, section 4.6.1 1.203 Flow reduction, 20-30 MW loss ENERCON report, section 4.6.1 1.204 Flow reduction, 20-40 MW loss ENERCON report, section 4.6.1 1.5 One-unit maintenance outage in September each

year ENERCON report, section 4.6.3

2 1-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 3 1.5-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 4 2-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 5 3-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 6 6-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 7 9-mm cylindrical wedgewire screen ENERCON report, section 4.3.1 8 1-mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 9 1.5 mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 10 2-mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 11 3-mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 12 6-mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 13 9-mm mesh alternative Ristroph screen ENERCON report, section 4.2.1 14 Aquatic filter barrier ENERCON report, section 4.4.1 15 NYSDEC Proposed Project min SW (Closed-cycle cooling with minimum service water use) ENERCON cooling tower report 10

15.5 NYSDEC Proposed Project max SW (Closedcycle cooling with maximum service water use) ENERCON cooling tower report

9 Ristroph screens with 6 mm x 12 mm mesh panels, as described in Section 4.1 of the ENERCON alternatives report.

10 “Engineering Feasibility and Costs of Conversion of Indian Point Units 2 and 3 to a Closed-Loop Condenser Cooling Water Configuration”

### 19 Table 2. Entrainment losses, equivalent ag e 1 losses, mean percent reductions from regulatory baseline, and incremental reductions from alternative baseline for alternative intake technologies examined for Units 2 and 3.

Case Alternative Losses Equivalent age 1

Mean (millions) %

reduction

from regulatory

baseline Incremental

reduction 11 Mean (millions) %

reduction from regulatory

baseline Incremental

reduction

0 Regulatory Baseline 1,224 0.0 3.270 0.0

0.5 Alternative Baseline 687 23.7 0 2.834 17.2 0.000

1 Existing intake technology 646 34.7 42 2.637 33.8 0.197

1.001 Flow Reduction 0MW Loss 632 35.9 14 2.597 35.7 0.040

1.101 Flow Reduction 10MW

Loss 587 45.1 58 2.174 44.7 0.462

1.202 Flow Reduction 20MW

Loss 578 47.4 68 1.997 47.8 0.640

1.203 Flow Reduction 20-30MW

Loss 567 48.6 78 1.895 49.6 0.742

1.204 Flow Reduction 20-40MW

Loss 565 48.8 80 1.881 49.9 0.756

1.5 September maintenance
outage 631 35.5 15 2.610 36.3 0.198

2 1-mm wedgewire screen 316 79.0 329 0.301 88.8 2.335
3 1.5-mm wedgewire screen 268 80.2 378 0.278 89.7 2.359
4 2-mm wedgewire screen 262 80.3 384 0.275 89.8 2.362
5 3-mm wedgewire screen 262 80.2 383 0.277 89.7 2.360
6 6-mm wedgewire screen 262 80.2 383 0.279 89.6 2.358
7 9-mm wedgewire screen 262 80.2 383 0.279 89.6 2.358

8 1-mm mesh alternative Ristroph screen 898 25.2 -252 2.656 28.0 -0.019

9 1.5mmmesh alternative Ristroph screen 731 30.2 -85 2.562 31.5 0.075

10 2-mm mesh alternative Ristroph screen 672 33.1 -26 2.520 33.5 0.117

11 3-mm mesh alternative Ristroph screen 646 35.0 0 2.499 34.9 0.138

12 6-mm mesh alternative Ristroph screen 646 34.7 0 2.637 33.8 0.000

13 9-mm mesh alternative Ristroph screen 647 33.0 -1 2.690 31.5 -0.053

14 Aquatic Filter Barrier 134 88.0 511 0.474 90.4 2.162
15 NYSDEC Proposed Project

min SW 35 97.4 611 0.095 97.6 2.542

15.5 NYSDEC Proposed Project

max SW 54 96.0 591 0.141 96.3 2.495

11 For the current technology (case 1) the incremental reduction is the re duction compared to the alternative baseline. For all other technologies, the incremental reduction is the reduction compared to the current technology.

### 20 Table 3. Impingement losses, equivalent ag e 1 losses, mean percent reductions from regulatory baseline, and incremental reduc tions from the current technology for alternative intake technologies examined for Units 2 and 3.

Case Alternative Losses Equivalent Age 1

Mean %

reduction

from regulatory

baseline Incremental

reduction 12

Mean %

reduction

from regulatory

baseline Incremental

reduction

0 Baseline 669,465 0.0 484,294 0.0
1 Existing technology 70,415 79.9 0 49,926 80.2 0

1.001 Flow Reduction 0 MW Loss 66, 914 80.8 3,501 47,703 80.8 2,223

1.101 Flow Reduction 10 MW Loss 61, 518 83.6 8,897 43,760 83.9 6,166

1.202 Flow Reduction 20 MW Loss 60, 843 84.2 9,572 43,081 84.7 6,846

1.203 Flow Reduction 20-30 MW

Loss 60,619 84.5 9,795 42,776 85.0 7,149

1.204 Flow Reduction 20-40 MW

Loss 60,598 84.5 9,817 46,077 85.1 7,181

1.5 September maintenance outa ge 69,859 80.8 555 49,118 81.3 809

2 1-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102
3 1.5-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102
4 2-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102
5 3-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102
6 6-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102
7 9-mm wedgewire screen 2,598 99.3 67,816 1,824 99.4 48,102

8 1-mm mesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

9 1.5mmmesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

10 2-mm mesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

11 3-mm mesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

12 6-mm mesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

13 9-mm mesh alternative Ristroph screen 70,415 79.9 0 49,926 80.2 0

14 Aquatic Filter Barrier 16,840 95.3 53,575 11,926 95.3 38,000
15 NYSDEC Proposed Project –

min SW 2,817 99.3 67,598 1,979 99.3 47,948

15.5 NYSDEC Proposed Project –

Max SW 4,277 98.9 66,137 3,034 98.9 46,892

12 For the current technology (case 1) the incremental reduction is the re duction compared to the alternative baseline. For all other technologies, the incremental reduction is the reduction compared to the current technology.

### 21 Table 4. Monthly and annual total percent reduction in age 1 equivalent entrainment

losses of RIS associated with certain alternat ive intake technologies for Units 2 and 3.

Reduction calculated from regulatory baseline.

Case Alternative Jan Feb Mar Apr Ma y Jun Jul Aug Sep Oct Nov Dec Total

0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.5 Alternative Baseline 0.0 0.0 0.0 0.2 4.8 9.0 1.2 0.5 0.7 0.7 0.0 0.0 17.2

1 Existing technology 0.0 0.0 0.0 0.4 6.1 14.3 6.4 4.1 1.3 1.1 0.0 0.0 33.8

1.001 Flow Reduction

0MW Loss 0.0 0.0 0.0 0.4 6.3 14.9 7.3 4.2 1.4 1.2 0.0 0.0 35.7

1.101 Flow Reduction

10MW Loss 0.0 0.0 0.0 0.4 6.5 17.1 10.2 6.0 2.3 2.1 0.0 0.0 44.7

1.202 Flow Reduction

20MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 11.8 7.0 2.7 2.2 0.0 0.0 47.8

1.203 Flow Reduction 20-

30MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 12.9 7.5 2.9 2.2 0.0 0.0 49.6

1.204 Flow Reduction 20-

40MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 13.0 7.6 2.9 2.2 0.0 0.0 49.9

1.5 September maintenance outages 0.0 0.0 0.0 0.4 6.1 14.3 6.4 4.1 3.9 1.1 0.0 0.0 36.3

2 1-mm wedgewire

screen 0.0 0.0 0.0 0.5 7.9 27.7 26.6 14.8 6.4 4.9 0.0 0.0 88.8

3 1.5-mm wedgewire

screen 0.0 0.0 0.0 0.5 8.3 28.2 26.6 14.8 6.4 4.9 0.0 0.0 89.7

4 2-mm wedgewire

screen 0.0 0.0 0.0 0.5 8.3 28.3 26.5 14.8 6.4 4.9 0.0 0.0 89.8

5 3-mm wedgewire

screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.7

6 6-mm wedgewire

screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.6

7 9-mm wedgewire

screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.6

8 1-mm mesh

Ristroph screen 0.0 0.0 0.0 0.4 4.8 8.7 6.9 4.8 1.5 1.0 0.0 0.0 27.9

9 1.5mm mesh

Ristroph screen 0.0 0.0 0.0 0.4 5.9 11.0 6.9 4.8 1.5 1.0 0.0 0.0 31.5

10 2-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.1 12.8 7.0 4.8 1.5 1.0 0.0 0.0 33.5

11 3-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.2 14.1 7.0 4.8 1.5 1.0 0.0 0.0 34.9

12 6-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.1 14.3 6.4 4.1 1.3 1.1 0.0 0.0 33.8

13 9-mm mesh Ristroph screen 0.0 0.0 0.0 0.3 5.9 13.6 5.8 3.4 1.3 1.2 0.0 0.0 31.5

14 Aquatic Filter Barrier 0.0 0.0 0.0 0.5 9.9 30.2 25. 1 13.8 6.0 4.8 0.0 0.0 90.4

15 NYSDEC Proposed Project – min SW 0.0 0.0 0.0 0.5 10.6 33.3 27.1 14.8 6.3 4.8 0.0 0.0 97.6

15.5 NYSDEC Proposed Project – max SW 0.0 0.0 0.0 0.5 10.4 32.8 26.8 14.6 6.3 4.8 0.0 0.0 96.2

### 22 Table 5. Monthly and annual total percen t reduction in equivale nt age 1 losses of impinged RIS Associated with certain alternat ive intake technologies for Units 2 and 3.

Reduction calculated from regulatory baseline.

Case Alternative Jan Feb Mar Apr Ma y Jun Jul Aug Sep Oct Nov Dec Total

0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1 Current technology

6x12mm 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

1.001 Flow Reduction

0MW Loss 8.8 9.6 12.0 6.7 7.4 8.5 4.0 4.2 4.4 3.9 4.7 6.5 80.7

1.101 Flow Reduction

10MW Loss 8.8 9.6 12.0 6.7 7.9 9.7 4.3 4.4 4.7 4.4 5.0 6.5 84.0

1.202 Flow Reduction

20MW Loss 8.8 9.6 12.0 6.7 7.9 9.9 4.4 4.5 4.8 4.4 5.0 6.5 84.7

1.203 Flow Reduction 20-

30MW Loss 8.8 9.6 12.0 6.7 7.9 10.0 4.5 4.6 4.9 4.4 5.0 6.5 85.0

1.204 Flow Reduction 20-

40MW Loss 8.8 9.6 12.0 6.7 7.9 10.0 4.5 4.7 4.9 4.4 5.0 6.5 85.0

1.5 September maintenance outages 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 5.6 3.8 4.6 6.3 81.3

2 1-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

3 1.5-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

4 2-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

5 3-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

6 6-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

7 9-mm wedgewire

screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.9

8 1-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

9 1.5mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

10 2-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

11 3-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

12 6-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

13 9-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.2

14 Aquatic Filter Barrier 9.4 10.3 12.9 8.0 9.5 11.7 5. 3 5.5 5.7 4.9 5.5 7.6 96.1

15 NYSDEC Proposed Project –low SW

flow 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99,8

15.5 NYSDEC Proposed Project – high SW

flow 9.6 10.5 13.1 8.2 9.9 12.6 5.5 5.7 6.0 5.0 5.7 7.7 99.523Table 6. Average annual losses of age-1equivalent fish (millions) lost yield (kg), andproduction forgone (kg) due to entrainment andimpingement for alternative intake technology for Units 2 and 3.Case Taxon Equivalent Age 1 (millions) Equivalent Yield(kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp TotalRegulatory Baseline0 Bay anchovy 2.332 0.014 2.346 0 0 0 5,628 2 5,6300 American shad 0.000 0.000 0.000 14 9 23 368 38 4050 Striped bass 0.571 0.048 0.619 213,460 25,942 239,402 660,935 50,960 711,8950 Atlantic tomcod 0.046 0.002 0.047 0 0 0 12,656 47 12,7040 White perch 0.279 0.399 0.678 153 322 475 12,301 13,048 25,3490 Alosa sp 0.042 0.021 0.062 135 32 167 8,318 621 8,9390 Total 3.270 0.484 3.754 213,762 26,306 240,068 700,206 64,716 764,922Alternative Baseline0.5 Bay anchovy 2.332 0.484 2.817 0 26,306 26,306 5,628 64,716 70,3440.5 American shad 0.000 0.003 0.003 14 13 27 368 237 6050.5 Striped bass 0.247 0.000 0.247 102,547 1 102,549 285,377 25 285,4030.5 Atlantic tomcod 0.042 0.001 0.043 0 0 0 10,510 0 10,5100.5 White perch 0.171 0.003 0.174 97 1,526 1,623 7,548 2,997 10,5460.5 Alosa sp 0.042 0.402 0.444 135 325 459 8,318 13,059 21,3770.5 Total 2.834 0.894 3.728 102,793 28,171 130,964 317,749 81,035 398,785Existing technology1 Bay anchovy 2.223 0.000 2.223 0 0 0 5,373 7 5,3801 American shad 0.000 0.039 0.039 12 32 44 340 1,277 1,6161 Striped bass 0.214 0.003 0.217 88,821 0 88,821 247,082 0 247,0831 Atlantic tomcod 0.011 0.000 0.011 0 3 3 2,963 10 2,9741 White perch 0.151 0.000 0.151 83 1 85 6,649 24 6,6731 Alosa sp 0.039 0.056 0.094 125 3,114 3,239 7,761 7,783 15,5441 Total 2.637 0.098 2.735 89,042 3,149 92,191 270,168 9,102 279,27024Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.Flow Reduction 0MW Loss1.001 Bay anchovy 2.220 0.001 2.222 0 0 0 5,369 0 5,3691.001 American shad 0.000 0.003 0.003 12 1,457 1,469 339 2,859 3,1991.001 Striped bass 0.189 0.048 0.236 77,014 1,503 78,517 217,685 4,345 222,0301.001 Atlantic tomcod 0.011 0.002 0.013 0 10 10 2,938 188 3,1261.001 White perch 0.139 0.002 0.142 76 0 76 6,145 0 6,1451.001 Alosa sp 0.038 0.038 0.076 125 31 156 7,729 1,244 8,9731.001 Total 2.597 0.094 2.691 77,227 3,001 80,228 240,205 8,636 248,841Flow Reduction 10MW Loss1.101 Bay anchovy 1.770 0.000 1.770 0 2 2 4,287 9 4,2951.101 American shad 0.000 0.000 0.000 10 1 11 263 20 2831.101 Striped bass 0.224 0.000 0.225 90,338 0 90,338 259,234 6 259,2391.101 Atlantic tomcod 0.009 0.035 0.044 0 28 28 2,571 1,137 3,7081.101 White perch 0.142 0.044 0.185 79 1,452 1,531 6,235 4,133 10,3681.101 Alosa sp 0.030 0.006 0.036 96 1,411 1,507 5,952 2,774 8,7261.101 Total 2.175 0.085 2.260 90,522 2,895 93,417 278,542 8,077 286,619Flow Reduction 20MW Loss1.202 Bay anchovy 1.589 0.002 1.591 0 10 10 3,844 179 4,0241.202 American shad 0.000 0.002 0.002 9 0 9 239 0 2391.202 Striped bass 0.229 0.001 0.231 90,633 0 90,633 265,119 0 265,1191.202 Atlantic tomcod 0.008 0.003 0.011 0 1,404 1,404 2,443 2,761 5,2041.202 White perch 0.143 0.000 0.143 79 0 79 6,316 6 6,3211.202 Alosa sp 0.027 0.044 0.071 88 1,455 1,544 5,482 4,160 9,6411.202 Total 1.997 0.052 2.049 90,809 2,869 93,678 283,443 7,106 290,54925Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.Flow Reduction 20-30MW Loss1.203 Bay anchovy 1.493 0.035 1.527 0 28 28 3,608 1,129 4,7371.203 American shad 0.000 0.043 0.043 8 1,444 1,453 228 4,103 4,3311.203 Striped bass 0.227 0.000 0.227 88,682 2 88,684 261,962 8 261,9701.203 Atlantic tomcod 0.008 0.000 0.008 0 1 1 2,394 19 2,4121.203 White perch 0.142 0.001 0.143 77 0 77 6,250 0 6,2501.203 Alosa sp 0.026 0.004 0.030 85 9 94 5,287 181 5,4691.203 Total 1.895 0.083 1.978 88,853 1,485 90,337 279,729 5,440 285,169Flow Reduction 20-40MW Loss1.204 Bay anchovy 1.480 0.003 1.482 0 1,402 1,402 3,576 2,757 6,3331.204 American shad 0.000 0.000 0.000 8 0 8 227 5 2321.204 Striped bass 0.226 0.002 0.228 88,330 9 88,340 261,118 175 261,2931.204 Atlantic tomcod 0.008 0.002 0.010 0 0 0 2,389 0 2,3901.204 White perch 0.141 0.000 0.141 77 2 79 6,232 8 6,2401.204 Alosa sp 0.026 0.079 0.105 85 1,469 1,554 5,271 5,220 10,4911.204 Total 1.881 0.085 1.966 88,501 2,882 91,383 278,814 8,166 286,97926Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.1-mm wedgewire screen2 Bay anchovy 0.145 0.001 0.146 0 0 0 395 0 3962 American shad 0.000 0.000 0.000 0 1 2 11 6 162 Striped bass 0.071 0.002 0.073 21,359 1,154 22,513 82,075 2,282 84,3572 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 6 532 White perch 0.081 0.030 0.111 36 24 60 3,629 994 4,6232 Alosa sp 0.005 0.003 0.007 14 6 20 1,105 116 1,2212 Total 0.301 0.036 0.337 21,408 1,186 22,594 87,262 3,404 90,6661.5-mm wedgewire screen3 Bay anchovy 0.148 0.036 0.184 0 1,186 1,186 406 3,404 3,8093 American shad 0.000 0.000 0.000 0 0 1 11 7 183 Striped bass 0.047 0.000 0.047 14,385 0 14,385 54,238 1 54,2393 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 0 483 White perch 0.078 0.000 0.078 34 59 93 3,460 116 3,5763 Alosa sp 0.005 0.030 0.035 14 24 38 1,145 995 2,1403 Total 0.278 0.066 0.344 14,434 1,270 15,704 59,308 4,522 63,8302-mm wedgewire screen4 Bay anchovy 0.150 0.000 0.150 0 0 0 410 0 4104 American shad 0.000 0.001 0.001 0 1 1 11 48 594 Striped bass 0.043 0.000 0.043 13,360 0 13,360 50,146 0 50,1464 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 0 494 White perch 0.077 0.000 0.077 34 0 34 3,437 1 3,4384 Alosa sp 0.005 0.002 0.007 14 120 135 1,162 297 1,4584 Total 0.275 0.004 0.279 13,409 122 13,531 55,214 346 55,56027Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.3-mm wedgewire screen4 Bay anchovy 0.150 0.000 0.150 0 0 0 412 0 4125 American shad 0.000 0.000 0.000 0 59 59 12 116 1285 Striped bass 0.043 0.002 0.045 13,449 61 13,510 50,344 173 50,5175 Atlantic tomcod 0.000 0.000 0.000 0 0 0 49 7 565 White perch 0.078 0.000 0.078 35 0 35 3,479 0 3,4795 Alosa sp 0.005 0.001 0.007 14 1 16 1,165 49 1,2145 Total 0.277 0.004 0.280 13,499 122 13,620 55,460 346 55,8056-mm wedgewire screen6 Bay anchovy 0.152 0.000 0.152 0 0 0 415 0 4156 American shad 0.000 0.000 0.000 0 0 0 12 1 126 Striped bass 0.044 0.000 0.044 13,654 0 13,654 50,801 0 50,8016 Atlantic tomcod 0.000 0.001 0.002 0 1 1 50 48 996 White perch 0.078 0.002 0.080 35 61 96 3,489 173 3,6626 Alosa sp 0.005 0.000 0.005 14 59 74 1,165 116 1,2816 Total 0.279 0.004 0.282 13,704 121 13,825 55,932 339 56,2729-mm wedgewire screen7 Bay anchovy 0.152 0.000 0.152 0 0 0 415 7 4227 American shad 0.000 0.000 0.000 0 0 0 12 0 127 Striped bass 0.044 0.000 0.044 13,666 0 13,666 50,831 0 50,8317 Atlantic tomcod 0.000 0.000 0.000 0 59 59 51 116 1677 White perch 0.078 0.000 0.078 35 0 35 3,489 0 3,4907 Alosa sp 0.005 0.002 0.007 14 61 75 1,165 174 1,3397 Total 0.279 0.002 0.281 13,716 120 13,836 55,962 298 56,26028Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.1-mm alternative Ristroph screen8 Bay anchovy 2.069 0.001 2.071 0 1 1 5,015 48 5,0638 American shad 0.000 0.002 0.002 12 61 73 336 173 5098 Striped bass 0.331 0.000 0.331 122,560 0 122,560 383,052 0 383,0538 Atlantic tomcod 0.010 0.000 0.010 0 0 0 2,888 1 2,8898 White perch 0.207 0.000 0.207 110 0 110 9,138 0 9,1388 Alosa sp 0.039 0.000 0.039 125 0 125 7,748 7 7,7558 Total 2.656 0.004 2.659 122,807 63 122,870 408,177 230 408,4071.5mm alternative Ristroph screen9 Bay anchovy 2.072 0.000 2.072 0 0 0 5,022 1 5,0239 American shad 0.000 0.000 0.000 12 0 12 336 0 3369 Striped bass 0.252 0.001 0.254 99,631 1 99,632 291,515 48 291,5649 Atlantic tomcod 0.010 0.002 0.012 0 61 61 2,886 173 3,0599 White perch 0.189 0.003 0.192 102 13 115 8,351 237 8,5889 Alosa sp 0.039 0.000 0.039 125 59 184 7,752 117 7,8699 Total 2.562 0.006 2.568 99,870 134 100,004 315,862 577 316,4382-mm alternative Ristroph screen10 Bay anchovy 2.074 0.050 2.124 0 1,575 1,575 5,029 4,555 9,58410 American shad 0.000 0.003 0.003 12 13 25 336 237 57310 Striped bass 0.225 0.000 0.225 91,561 1 91,562 259,298 25 259,32310 Atlantic tomcod 0.010 0.001 0.012 0 0 0 2,882 0 2,88210 White perch 0.173 0.003 0.175 95 1,526 1,621 7,603 2,997 10,60010 Alosa sp 0.039 0.042 0.081 125 34 159 7,757 1,288 9,04510 Total 2.520 0.100 2.620 91,793 3,149 94,943 282,904 9,103 292,00829Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.3-mm alternative Ristroph screen11 Bay anchovy 2.081 0.001 2.082 0 0 0 5,045 0 5,04511 American shad 0.000 0.003 0.003 12 1,526 1,539 338 2,997 3,33511 Striped bass 0.212 0.050 0.262 87,815 1,575 89,389 244,813 4,555 249,36811 Atlantic tomcod 0.010 0.003 0.013 0 13 13 2,876 237 3,11311 White perch 0.157 0.003 0.160 88 0 88 6,896 0 6,89611 Alosa sp 0.039 0.040 0.078 125 33 158 7,760 1,309 9,06911 Total 2.499 0.100 2.598 88,040 3,147 91,186 267,727 9,100 276,8266-mm alternative Ristroph screen12 Bay anchovy 2.223 0.003 2.226 0 13 13 5,373 237 5,61012 American shad 0.000 0.003 0.003 12 0 12 340 0 34012 Striped bass 0.214 0.001 0.216 88,821 0 88,821 247,082 0 247,08312 Atlantic tomcod 0.011 0.003 0.013 0 1,526 1,526 2,963 2,997 5,96112 White perch 0.151 0.000 0.151 83 0 83 6,649 7 6,65612 Alosa sp 0.039 0.050 0.089 125 1,579 1,704 7,761 4,591 12,35212 Total 2.637 0.061 2.697 89,042 3,118 92,160 270,168 7,834 278,0029-mm alternative Ristroph screen13 Bay anchovy 2.254 0.003 2.257 0 1,526 1,526 5,443 2,997 8,44113 American shad 0.000 0.000 0.000 13 0 13 342 7 34913 Striped bass 0.229 0.001 0.230 95,992 3 95,995 264,220 55 264,27513 Atlantic tomcod 0.014 0.001 0.014 0 0 0 4,083 0 4,08313 White perch 0.155 0.000 0.155 86 1 87 6,818 3 6,82113 Alosa sp 0.039 0.091 0.129 125 1,606 1,731 7,765 5,832 13,59713 Total 2.690 0.095 2.785 96,217 3,136 99,353 288,671 8,894 297,56630Table 6 (continued). Average annual losses of age-1 equivalent fish (millions) lost yield (kg), and production forgone (kg) due toentrainment and impingement for alternative intake technology for Units 2 and 3.Aquatic Filter Barrier14 Bay anchovy 0.405 0.001 0.406 0 0 0 989 0 98914 American shad 0.000 0.000 0.000 1 0 1 37 2 3814 Striped bass 0.034 0.002 0.036 13,570 1,042 14,611 39,598 2,049 41,64814 Atlantic tomcod 0.001 0.000 0.001 0 0 0 173 2 17614 White perch 0.030 0.016 0.046 16 13 29 1,310 538 1,84814 Alosa sp 0.005 0.001 0.006 14 1 15 1,103 23 1,12614 Total 0.474 0.020 0.494 13,600 1,056 14,657 43,210 2,614 45,824NYSDEC Proposed Project – min SW15 Bay anchovy 0.108 0.020 0.128 0 1,056 1,056 261 2,614 2,87515 American shad 0.000 0.000 0.000 1 0 1 17 8 2415 Striped bass 0.025 0.000 0.025 9,337 0 9,337 28,624 1 28,62415 Atlantic tomcod 0.002 0.000 0.002 0 0 0 553 0 55315 White perch 0.012 0.000 0.012 7 65 72 518 129 64615 Alosa sp 0.002 0.017 0.018 6 13 19 362 538 90115 Total 0.149 0.037 0.185 9,350 1,135 10,486 30,334 3,289 33,623NYSDEC Proposed Project - max SW15.5 Bay anchovy 0.105 0.000 0.105 0 0 0 253 0 25315.5 American shad 0.000 0.002 0.002 1 2 3 16 80 9615.5 Striped bass 0.023 0.000 0.023 8,254 2 8,256 26,307 0 26,30715.5 Atlantic tomcod 0.001 0.000 0.001 0 38 38 183 0 18315.5 White perch 0.012 0.000 0.012 6 128 134 517 0 51715.5 Alosa sp 0.002 0.003 0.005 6 696 702 370 494 86315.5 Total 0.141 0.006 0.147 8,267 866 9,133 27,646 574 28,219

### 31 

## 4. Cumulative benefits of I&E reductions

This section provides an evaluation of th e cumulative benefits of I&E reductions over the expected lifetimes of Units 2 and 3 associat ed with the immediate installation of cylindrical wedgewire screens versus the 2029 completion date for construction of the NYSDEC Proposed Project. 13 

### This evaluation account s for both expected annual

reductions in I&E losses and for the time required to install alternative intake technologies. The schedule for the NYSDEC Proposed Project was derived by ENERCON with input from Enter gy’s counsel and Spectra Energy 14 

### . Key factors influencing this schedule include the techni cal complexity of the project, permitting requirements, and to likely litigation relating to local zoning ordinances.

Cylindrical wedgewire screens, which ar e nearly as effective as the NYSDEC Proposed Project at reducing I&E losses (as dem onstrated in Section 3) could be installed relatively quickly. This bene fits analysis assumes, cons istent with a proposal from Entergy, that cylindrical wedgewire screens could be installed at Unit 2 by 2013 and at Unit 3 by 2015. Because they can be insta lled much sooner, reductions in I&E losses could begin immediately rather than be ing deferred for an extended period while technical feasibility and permitting issues as sociated with the NYSDEC Proposed Project

are resolved. Because of the earlier instal lation date, cumulative reductions in I&E losses

over the lifetimes of Units 2 and 3 associat ed with cylindrical wedgewire screens are estimated to be more than two times greater than reductions that could be achieved with the NYSDEC Proposed Project. Detailed documentation of methods and results is provided in Appendix A.



## 4.1 Comparison of immediate installation of cylindrical wedgewire screens to delayed installation of the NYSDEC Proposed Project

The construction schedule was provide d by counsel to Entergy and by ENERCON. It was assumed for this analysis that cylindrical wedgewi re screens could be installed and operating at Unit 2 in 2013 and at Unit 3 in 2015. It was assumed that the NYSDEC Proposed Project would become ope rational at both units in 2029. It was assumed that Unit 2 would be retired in 2033 and Unit 3 would be retired in 2035, consistent with their respective NRC licenses.

Table 7 shows the cumulative estimated total I&E losses and age-1 equivalent losses from 2013 through 2035, for Unit 2 and Unit 3, for the regulatory baseline, for the existing technology, for the 6 cylindrical wedgewi re screen scenarios evaluated in this report, and for the NYSDEC Proposed Project. Table 7 also shows, for each scenario, the

13 Aquatic filter barriers were not included in this analysis because, as discussed by ENERCON (section 5.4.1), significant operational and nuclear safety/licensing issues associated with this technology would have to be resolved prior to installation.

14 Counsel informed us that Spectra Energy is the parent company of Algonquin Gas Transmission, LLC, the owner of the natural gas pipeline syst em that traverses the IPEC property.

### 32 percent reduction in cumulative estimated to tal I&E losses and ag e-1 equivalent losses compared to the regulatory baseline. Finally, Table 7 shows the “savi ngs ratio” for each scenario. As discussed in Appendix A, the savings ratio measures the relative

incremental reduction in cumulative losses for each technology, as compared to the existing technology at Units 2 and 3.

Table 7 shows that, because of the time re quired to resolve technical feasibility and permitting issues associated with the NYSDEC Proposed Project, implementing this project would result in only a 55% reduction in estimated entrainment losses and age-1 equivalent losses compared to the regulatory ba seline. The reason for this is because for most of the years between 2013 and 2029 th e existing technology would still be operating. In contrast, for all of the wedgewi re screen scenarios, estimated cumulative total entrainment losses would be reduced by 78% and estimated cumulative age-1 equivalent losses due to entrainment w ould be reduced by 88% . Reductions in impingement would also be much greater (99% for both losses and age-equivalents) for wedgewire screens than for the NYSDEC Propos ed Project (88% for losses and 87% for age-1 equivalents). The savings ratios for th e 6 cylindrical wedgewire screens scenarios are all greater than 2.5 for entrainment and eq ual to 3.0 for impingement, indicating that

these screens would be more than twice as effective as the NYSDEC Proposed Project at reducing entrainment losses and three times as effective at reducing impingement losses compared to the losses associat ed with the existing technology.

One of the fundamental principles of natu ral resource restorati on is that resources that are provided in the future are less valu able than resources th at are provided in the present (NOAA 1997, French McCay and Rowe 2003) . For example, a given quantity of

restored habitat is considered to be less valuab le if it is provided 10 years in the future than if it is provided 2 years in the future. To compare ecol ogical benefits of alternative restoration projects that ma y be completed at different times in the future, trustee agencies use a discount rate of 3% to convert the future values of all of the alternatives to their present value. This is the same proce dure that is used in ec onomics to calculate the present value of investments or costs that will occur in the future (NOAA 1997).

Both cylindrical wedgewire screens and the NYSDEC Proposed Project will provide potential ecological benefits related to reductions in I&E losses. However, the benefits accruing from the NYSDEC Proposed Project would occur mu ch later than the benefits accruing from immediate installation of cylindrical wedgewire screens. Table 8 presents the same comparisons as Table 7, but with values for future I&E losses and

reductions in losses discounted by 3% per year. With discounting, the comparative benefits of immediate installation of cylindric al wedgewire screens ar e even greater than

the undiscounted benefits. The discounted re ductions in entrainment and impingement losses for wedgewire screens are, respectivel y, 77% and 98%, compared to 50% and 86% for the NYSDEC Proposed Project. The di scounted reduction in age-1 equivalent entrainment for wedgewire screens is 87% for entrainment and 98% for impingement, compared to 50% and 86% for the NYSDEC Proposed Project. The discounted savings ratios for cylindrical wedgewire screens ar e 2.7 for total entrainment losses, 3.3 for equivalent age-1 entrainment losses, and 3.8 for both total impingement losses and equivalent age-1 impingement losses.33Table 7. Cumulative I&E losses, percent reductions in losses, and savings ratios for alternative intake technologies at IndianPointUnits 2 and 3.ScenarioUndiscountedYearTechnologyOperationalaTotal Losses (millions) Equivalent Age 1 Losses(millions)Number%ReductionSavingsRatioNumber%ReductionSavingsRatioUnit 2 Unit 3EntrainmentRegulatory Baseline 26,931 0 71.914 0Existing Technology 2013 2013 14,183 35 0 57.969 34 0.01-mm wedgewire screen 2013 2015 7,264 77 1.9 8.926 87 2.51.5-mm wedgewire screen 2013 2015 6,255 78 2.1 8.424 88 2.62-mm wedgewire screen 2013 2015 6,127 78 2.1 8.371 88 2.63-mm wedgewire screen 2013 2015 6,136 78 2.1 8.408 88 2.66-mm wedgewire screen 2013 2015 6,137 78 2.1 8.448 88 2.69-mm wedgewire screen 2013 2015 6,137 78 2.1 8.449 88 2.6NYSDEC Proposed Project 2029 2029 9,885 55 1.0 40.1 55 1.0ImpingementRegulatory Baseline 14.728 0 10.654 0Existing Technology 2013 2013 1.549 82 0.0 1.098 81 0.01-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.01.5-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.02-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.03-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.06-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.09-mm wedgewire screen 2013 2015 0.125 99 3.0 0.088 99 3.0NYSDEC Proposed Project 2029 2029 1.073 88 1.0 0.761 87 1.0aConstruction schedules provided byENERCON and counsel to Entergy34Table 8. Cumulative I&E losses, percent reductions in losses, and savings ratios for alternative intake technologies at IndianPointUnits 2 and 3, with post-2013 reductions discounted at 3% per year.ScenarioDiscounted 3% per yearYearTechnologyOperationalaTotal Losses (millions) Equivalent Age 1 Losses(millions)Number%ReductionSavingsRatioNumber%ReductionSavingsRatioUnit 2 Unit 3EntrainmentRegulatory Baseline 19,919 0 53.189 0Existing Technology 2013 2013 10,494 35 0.0 42.881 34 0.01-mm wedgewire screen 2013 2015 5,456 76 2.4 7.176 86 3.21.5-mm wedgewire screen 2013 2015 4,721 77 2.6 6.81 87 3.32-mm wedgewire screen 2013 2015 4,627 77 2.7 6.771 87 3.33-mm wedgewire screen 2013 2015 4,634 77 2.7 6.798 87 3.36-mm wedgewire screen 2013 2015 4,635 77 2.7 6.827 87 3.39-mm wedgewire screen 2013 2015 4,635 77 2.7 6.828 87 3.3NYSDEC Proposed Project 2029 2029 8,007 50 1.0 32.547 50 1.0ImpingementRegulatory Baseline 10.892 0 7.88 0Existing Technology 2013 2013 1.146 82 0.0 0.812 81 0.01-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.81.5-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.82-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.83-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.86-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.89-mm wedgewire screen 2013 2015 0.109 98 3.8 0.077 98 3.8NYSDEC Proposed Project 2029 2029 0.87 86 1.0 0.617 86 1.0aConstruction schedule provided by ENERCON and counsel to Entergy.

### 35 

## 4.2 Sensitivity analysis

A sensitivity analysis was performed to determine the level of confidence in the cumulative biological benef its associated with cylindrical wedgewire screens as compared to the NYSDEC Proposed Project. This analysis focused on entrainment, because all wedgewire screen configurations evaluated in this report should reduce impingement to very low levels (Section 3 and Table 3). The avoidance and survival factors used to estimate potential entrainment loss reductions for cylindrical wedgewire screens are well-supported by laboratory studi es, and are also supported by a full-scale field study performed at the Eddystone Gene rating Station on the Delaware River (see Appendix B). However, cylindr ical wedgewire screens have not been field-tested at Indian Point. To assess the level of confidence in the relative biological benefits calculations presented in Tables 7 and 8, a dditional calculations were performed using

alternative avoidance and surv ival factors. These altern ative avoidance and survival factors produce a lower entrainment loss percen tages than the curves used to generate tables 7 and 8. As a result, they provide a conservative, lower range of entrainment loss percentages that nevertheless highlights the su perior cumulative benefits of cylindrical wedgewire screens as compared to the NYSDEC Proposed Project.

As discussed in Appendix A, the sensitiv ity analysis documented in this section utilized 8 alternative length-specific avoi dance curves and 3 alternative assumptions about the survival rates of excluded (i.e., impinged) larvae. The most extreme set of alternative assumptions assumes that there is no avoidance of the screen by larvae or juveniles, and no survival of impinged larvae and juveniles. Four slot widths ranging

from 1 mm to 9 mm were selected for analysis.

Results of the sensitivity analysis are shown in Figure 2. In Figure 2, discounted percent reductions in cumulative age-1 equivalent losses for each combination of avoidance and survival assumptions are co mpared to the corresponding reduction for the NYSDEC Proposed Project. The percent reduc tions for cylindrical wedgewire screens fall below the value for the NYSDEC Propose d Project only for avoidance curve 8,

which assumes no avoidance of th e screen by larvae or juveniles of a ny length class. Since data from studies of cylindrical wedgewi re screens have consis tently demonstrated that avoidance occurs (see Appendix B), curve 8 is not realistic. For all other avoidance curves and exclusion survival assumptions, cu mulative percent reductions in entrainment losses are greater for cylindrical wedgewi re screens than for the NYSDEC Proposed Project. Hence, the sensitivity analysis provides confidence that even using very

conservative survival and avoidance factor s, immediate installation of cylindrical wedgewire screens would provide greater reduct ions in I&E losses than later installation of the NYSDEC Proposed Project.36Figure 2. Sensitivity of cumulative percent reduction estimates for cylindrical wedgewire screens to alternative length-specificavoidance curves and assumptions concerningthe survival of impinged larvae and juveniles. Avoidance curve 1 is the baseline curvedeveloped in Appendix B. Curve 8 is the worst-case assumptionthat no avoidance occurs. The alternative impingement survivalassumptions are 100% survival (Sx=100%), survival equal to the survival of small fishimpinged on fine mesh screens (Sx = FMscreen), and 0% survival (Sx=0).1‐mmSlot020406080100CumulativeDiscountedEntrainment%ReductionEquivAge1Sx=100%86.4 84.2 81.9 79.2 77.4 76.7 76.4 75.8Sx=FMscreen85.2 82.5 79.4 75.3 71.4 67.9 63.5 29.2Sx=084.7 82.0 78.8 74.6 70.4 66.6 61.5 10.7ClosedCycle50.1 50.1 50.1 50.1 50.1 50.1 50.1 50.1123456783‐mmSlot020406080100CumulativeDiscountedEntrainment%ReductionEquivAge1Sx=100%87.2 85.2 83.2 80.7 78.5 76.4 74.0 70.3Sx=FMscreen86.5 84.4 82.2 79.5 76.7 73.8 69.5 35.2Sx=086.0 83.9 81.7 78.9 75.9 72.7 67.8 17.0ClosedCycle50.1 50.1 50.1 50.1 50.1 50.1 50.1 50.1123456786‐mmSlot020406080100CumulativeDiscountedEntrainment%ReductionEquivAge1Sx=100%87.2 85.1 82.9 80.3 77.5 74.7 70.8 55.2Sx=FMscreen86.5 84.5 82.3 79.5 76.7 73.8 69.5 34.3Sx=086.0 84.0 81.8 79.1 76.2 73.2 68.7 19.6ClosedCycle50.1 50.1 50.1 50.1 50.1 50.1 50.1 50.1123456789‐mmSlot020406080100CumulativeDiscountedEntrainment%ReductionEquivAge1Sx=100%87.2 85.1 82.9 80.2 77.4 74.5 70.3 48.3Sx=FMscreen86.5 84.5 82.2 79.5 76.7 73.7 69.4 32.3Sx=086.0 84.0 81.8 79.1 76.2 73.3 68.9 21.4ClosedCycle50.1 50.1 50.1 50.1 50.1 50.1 50.1 50.112345678

### 37 

## 5. Potential I&E impacts of IPEC operations on Hudson River

fish populations, with and without alternative technologies

All of the calculations discussed in the previous section assume that I&E losses are directly proportional to reductions in th e subsequent abundance of older fish. For example, if on average 1% of la rvae lost due to entrainment would be expected to survive to age 1, then the loss of 100,000 larvae is as sumed to reduce the number of 1-year-old fish present in the river by 1000. Empl oying an intake technology that reduces entrainment losses to 10,000 larvae is assumed to save 900 future one-year-old fish (i.e., the survivors among the 90,000 larvae that were not entrained due to the new technology)

that would have been lost without the new technology.

These are hypothetical calculations that fail to account for environmental and biological variability, density-d ependent mortality, and othe r factors that disrupt the presumed relationship between the losses of early life stages and subsequent abundance of older fish. Many of these factors are di scussed in Entergy’s Adverse Environmental Impact (“AEI”) Report (Barnthouse et al. 200 8). The AEI report analyzed 30 years of data relating the abundance of the eight RIS species discussed in this report to the operations of Units 2 and 3, and found no eviden ce that entrainment at these stations had any measurable effect on the abundance of a ny species. If existing levels of I&E losses

have not caused a measurable decline in th e abundance of any RIS, then reducing those losses through installa tion of new technologies would not be expected to cause a measurable increase in the abundance of any species.

Section 5.1 provides a summary of the AE I report. Section 5.2 discusses a new analysis (documented in Appendix C to this report) that supports th e conclusions of the AEI report by demonstrating, using data from the Hudson River surveys, that increasing

the abundance of larvae in the Hudson River by eliminating all entrainment losses at Units 2 and 3 would not produce a measurable in crease in the abundance of juvenile fish. Appendix D provides additional supporting inform ation that addresses issues raised in NYSDEC’s Final Environmental Impact Statement (“FEIS”).

As set forth below, no appreciable populat ion-level impacts would be achieved by implementing any of the technology alternatives considered in this report, including the NYSDEC Proposed Project.



## 5.1 Entergy’s AEI report

Entergy’s AEI report evaluated whether entrainment and impingement caused by the operation of Units 2 and 3 resulted in AEI, on Hudson River fish populations and communities. The report used biologically-based definitions of AEI that are consistent

with established definitions and standards of ecological risk assessment and fisheries
management.

### 38 The approach involved three elements. First, the extensive Hudson River

fisheries data-sets were evalua ted to determine: (1) whether changes in the status of species of interest identified by NYSDEC have occurred since Units 2 and 3 began commercial operation, (2) whether cooling-wa ter withdrawals by Units 2 and 3 during this period could have been responsible for a ny such changes, or (3 ) whether alternative stressors including striped ba ss predation, zebra mussels, a nd harvesting are the more probable cause of perceived changes.

Second, a widely-accepted method for quantifying the impacts of harvesting on the sustainability of fish populations, term ed the Spawning Stock Biomass per Recruit (SSBPR) model, was used to determine whet her entrainment and impingement caused by the operation of Units 2 and 3 could have ad versely affected the sustainability of the Hudson River striped bass and American shad populations.

Third, long-term trends in the abundan ce of all Hudson River fish species for which adequate data were available were examined to determine whether species with high susceptibility to entrainment at Units 2 and 3 are more likely to have declined in abundance over the past 30 years than are specie s with low susceptibility to entrainment.

All three elements of the assessment supported a conclusion that Units 2 and 3

have not caused an AEI. Evaluation of alternative hypotheses c oncerning the causes of changes in abundance of Hudson River fish populations found no evidence supporting the hypothesis that Units 2 and 3 contributed to th ese changes. Instead, the evaluation shows that overharvesting is the most likely cause of recent declines in abundance of American shad, with striped bass preda tion being a potentially signifi cant contributing factor. Increased predation by the rapidly growing Hudson River striped ba ss population is the most likely cause of recent declines in the abundance of Atlantic tomcod, river herring and bay anchovy. Striped bass predation pr obably contributed to the decline in abundance of white perch, although other unknown causes were also involved.



## 5.2 Empirical assessment of expected population-level effects

of reductions in entrainment losses due to alternative technologies

As noted above, estimates of losses of age-1 equivalent fish are theoretical calculations based on estimates of the average fraction of entrained fi sh that would have survived to an age of 1 year. However, as shown in Entergy’s AEI Report, as summarized in Section 5.1, survival rates of ear ly life stages of fish in the Hudson River are highly variable, and correlations between abundance indices for larvae and juveniles are often low. Hence, increasing the a bundance of larvae th rough reductions in entrainment losses may lead to little or no increase in the abundance of older fish. To fully assess the relationship between estimated increases in larval abundance (expressed as equivalent age-1 fish) and actual increase s in the abundance of one-year old fish, it would be necessary to obtain field measuremen ts of increased larval abundance, together with estimates of the resulting change in abundance of one-year-old fish.

### 39 For large natural ecosystems like the Hudson River estuary, it is not possible to experimentally increase the abundance of larvae and then observe the resulting increase in abundance of 1-year-old fish. However, the 30 years of historical data document naturally-occurring “experiments” in which the effects of increases in riverwide larval abundance (expressed in terms of age-1 equiva lents) on changes in riverwide juvenile

abundance can be measured. Increases and de creases in the abundance of larvae from one year to the next commonly occur, due to natural variability. Since the abundances of both larvae and juveniles of all RIS species are measured annua lly, these data can be used to determine whether, when the abundance of larvae increases from one year to the next, the abundance of juveniles also increases. These naturally-occurring experiments can be used to address the question of whether meas urable changes in the abundance of juvenile and older fish can be expected from reducing entrainment losses of larvae at Units 2 and

3.

Specifically, year-to-year increases in the a bundance of larval fish, as measured in the Long River Survey (“LRS”), 15 

### can be compared to corresponding changes in juvenile abundance, as measured in “BSS”, a nd Fall Juvenile Survey (“FJS”). 16 

### These surveys provide comprehensive and consistent estimate s of long-term trends in the abundance of multiple life stages of important Hudson Ri ver fish populations, from 1974 through the present. Detailed descriptions of th ese surveys are provided in ASA (2007).

If increases in larval abundance as measur ed in the LRS were regularly associated with increases in juvenile abundance as meas ured in the FSS and FJS, then it could be concluded that saving fish larvae by reducin g entrainment could increase the subsequent abundance of juvenile and older fish. If, howev er, there is no relati onship between larval abundance and subsequent juvenile abundance, then it is unlikely that increasing the number of larval fish present in the river will lead to an incr ease in the abundance of juvenile and older fish.



### 5.2.1 Methods

The relationship between in creases in larval abundan ce and changes in abundance of older fish was investigated for American shad, river herring, st riped bass, and white perch. Data for the remaining RIS were judged to be insufficient for this analysis. For each of the species addressed, the annual ri verwide abundance of post yolk-sac larvae (“PYSL”), expressed in terms of age-1 equi valents, was calculated for the years 1974 through 2005. The abundance of PYSL in e ach year was then compared to PYSL abundance in every other year. For example, PYSL abundance in 1974 was compared to

PYSL abundance in all other years. Instances in which PYSL abundance in these years was greater than PYSL abundance in 1974 were identified. The same procedure was applied to all other years, e.g., PYSL abundance in 1984 was compared to PYSL

15 The LRS samples eggs, larvae, and juvenile fish, weekly from April through July. The region between the George Washington Bridge and the Federal Dam at Troy has been sampled since 1974. In 1988, the LRS was extended to sample the region between the Battery and the George Washington Bridge.

16 The BSS and FSS sample juvenile fish, during altern ate weeks from June through October. Sampling is conducted from the George Washington Bridge to the Federal Dam.

### 40 abundance in the years 1974-1983 a nd 1985-2005. Evaluating all pairs of years, rather than only adjacent years, eliminates any pos sible influence of long-term trends in

abundance or survival of larvae on the outcome of the analysis.

The difference in PYSL abundance between the higher and lower of each pair was calculated and used as a measure of increasing larval abundance, analogo us to an increase that could occur due to implementation of an alternative intake technology at Units 2 and 3. For each pair of years with an increas e in PYSL abundance, the corresponding change in observed juvenile abundance between thos e years was calculated. Estimates of changes in juvenile abundance were based on the annual juvenile index of abundance from Entergy’s AEI report.

The estimates of increases in PYSL abunda nce were converted to equivalent age1 fish using the same methods used in th e technology evaluations (Section 2; Appendix A). Hence, the estimates of increases in PYSL abundance used in this analysis are directly comparable to the pr ojections of potential increases in age-1 equivalents due to reduced entrainment losses. Table 9 shows, for each taxon, the maximum and minimum

entrainment losses under the “existing technology” scen ario, for the years 2001-2007. This range represents the maximum increas e in age-1 equivalents that could have occurred, if no entrainment caused by operati on of the Stations ha d occurred during this period. For those year-to-year in creases in riverwide age-1 equi valents that fell within the range of potential annual increas es in age-1 equivalents due to eliminating current IPEC entrainment losses, the corresponding changes in juvenile abundance were summarized. The changes in juvenile abundance for those pair s of years indicate the change in juvenile abundance that could be expected if current entrainment losses at Units 1 and 2 were

eliminated.



### 5.2.2 Results

Figures 3 through 6 show, for each of the four taxa evaluated, the range of yearto-year increases in riverwide PYSL abundanc e calculated from historical data and the relative change in juve nile abundance associated with each increase. These figures also show the range of increases that would be expected to occur if current levels of

entrainment losses at IPEC were eliminated. For all taxa, the range of projected increases in numbers of age-1 equivalent s due to eliminating entrainment is very small compared to the range of year-to-year increases calculated from historical data. Within this small

range, decreases in corresponding abundance of juveniles have occurred as frequently as increases. The estimated probability of obs erving an increase in juvenile abundance,

when the increase in PYSL abundance is within the range that would be projected due to elimination of entrainment, is not significan tly different than 50:50 for any of the four taxa evaluated (Appendix C).

None of the technology altern atives evaluated in this report would completely eliminate entrainment. If reducing entrai nment to zero would not produce a measurable increase in the actual abundance of juven ile or one-year-old fish, then reducing entrainment by a lesser amount would simila rly produce no measurable increases in

### 41 abundance. This result implies that none of th e technology alternatives evaluated in this report would be expected to result in a demonstrable incr ease in juvenile abundance of American shad, river herring, striped bass or white perch.

### 42 Table 9. Projected annual increases in ag e-1 equivalents due to eliminating current entrainment losses at Units 2 and 3 (Source: Appendix A to this report).

Taxon Projected Range of Potential Annual Increases in Age-1 Equivalents Due to Eliminating

Current Entrainment Losses at

Units 2 and 3

Minimum Projected

Annual

Increase in Age-1 Equivalents Maximum Projected

Annual Increase in Age-1 Equivalents

River Herring 12,100 86,900

American Shad 0 200 Striped Bass 76,300 561,400 White Perch 54,100 347,200

### 43 -3 -2 -1 0 1 2 3

0 2, 500 5,000

7 , 50

0 10, 000 12,500 15, 000 17,500

2 0, 000 22,500 Projected Range of Potential Annual Increase in Age-1 Equivalents Due to Eliminating Current IPEC Entrainment Losses

Observed Year-to-Year Increase in PYSL Abundance (Expressed as Increase in Equivalent Age-1 Abundance) O b s e r v e d C h a n g e i n J u v e n i l e A b u n d a n c e

(

E x p r e s s e d a s a M u l t i p l e o f A v e r a g e J u v e n i l e A b u n d a n c e ) American Shad



### Figure 3. Observed year-to-year changes in riverwide juvenile abundance of American shad in response to observed year-to-y ear increases in riverwide post yolk-sac larval (PYSL) abundance. Based on all pa irs of years (1985-2005) with observed positive change in abundance of PYSL.

### 44 -4 -3 -2 -1 0 1 2 3 4

0 200,000 40 0

, 0 00 60 0

, 0 00
80 0

, 0 00

1 , 0 0 0,00

0 1,20 0

, 0 00 1,40 0

, 0 00 1,60 0

, 0 00 1,80 0

, 0 00 2,00 0

, 0 00

2,200,000 2,40

0

, 0 00 2,60 0

, 0 00

2,800,000 3,000,000 Projected Range of Potential Annual Increase in Age-1 Equivalents Due to Eliminating Current IPEC Entrainment Losses

Observed Year-to-Year Increase in PYSL Abundance (Expressed as Increase in Equivalent Age-1 Abundance) O b s e r v e d C h a n g e i n J u v e n i l e A b u n d a n c e

(

E x p r e s s e d a s a M u l t i p l e o f A v e r a g e J u v e n i l e A b u n d a n c e ) River Herring



### Figure 4. Observed year-to-year changes in riverwide juvenile abundance of river herring in response to observed year-to-year incr eases in riverwide po st yolk-sac larval (PYSL) abundance. Based on all pair s of years (1974-2005) with observed positive change in PYSL abundance.

### 45 -2 -1.5

-1 -0.5

0 0.5

1 1.5

2

0

1 , 0 0 0

, 0 0 0 2,00 0 ,00

0 3,000,000 4,0 0 0,000

5 , 0 0 0,000 6,00 0 ,00

0 7,000,00 0 8,0 0 0,000

9 ,00

0

, 0 0 0

10 , 0 0 0

, 0 0 0 Projected Range of Potential Annual Increase in Age-1 Equivalents Due to Eliminating Current IPEC Entrainment Losses

Observed Year-to-Year Increase in PYSL Abundance (Expressed as Increase in Equivalent Age-1 Abundance) O b s e r v e d C h a n g e i n J u v e n i l e A b u n d a n c e

(

E x p r e s s e d a s a M u l t i p l e o f A v e r a g e J u v e n i l e A b u n d a n c e ) Striped Bass



### Figure 5. Observed year-to-year changes in riverwide juvenile abundance of striped bass in response to observed year-to-year increases in riverwide post yol k-sac larval (PYSL) abundance. Based on all pairs of years ( 1974-2005) with observed positive change in

PYSL abundance.

### 46 -3 -2 -1 0 1 2 3

0

5, 0 00

, 00

0

1 0

, 00

0 ,0

0 0

15, 0 00,000

2 0

, 00

0 ,0

0 0

25, 0 00,000

3 0 ,0

0 0 ,0

0 0 35,000,000

4 0 ,0

0 0 ,0

0 0 Projected Range of Potential Annual Increase in Age-1 Equivalents Due to Eliminating Current IPEC Entrainment Losses

Observed Year-to-Year Increase in PYSL Abundance (Expressed as Increase in Equivalent Age-1 Abundance) O b s e r v e d C h a n g e i n J u v e n i l e A b u n d a n c e

( E x p r e s s e d a s a M u l t i p l e o f A v e r a g e J u v e n i l e A b u n d a n c e ) 

### White Perch



### Figure 6. Observed year-to-ye ar changes in riverwide juve nile abundance of white perch in response to observed year-t o-year increases in riverwid e post yolk-sac larval (PYSL) abundance. Based on all pair s of years (1974-2005) with observed positive change in

PYSL abundance.

### 47 

## 6. Conclusions

The technology evaluations documented in this report and supporting appendices show that, of the alternative technologi es examined by ENERCON, two have the potential to reduce I&E losses to levels comparable to the reduction that could be achieved through installation of the NYSEC Proposed Project: cylindrical wedgewire screens and aquatic filter barriers (Figur e 7). Both of thes e technologies possess

characteristics that minimize or eliminate th e physical contact of organisms with intake screens, thereby reducing or eliminating the potential for injury. The other screening technologies evaluated would pr ovide fish protection comparab le to, or worse than, the protection provided by the Stations’ existing intake technology. Operational changes such as flow reductions, power reductions, a nd scheduled maintenance/refueling outages could reduce I&E losses to a gr eater extent than the existin g intake technology, but would still not approach the reductions possible w ith cylindrical wedgewire screens, aquatic filter barriers, and the NYSDEC Proposed Project.

Installation of the NYSDEC Proposed Proj ect would involve extended delays due to the technical complexity of the project, to permitting requirements, and to likely litigation relating to local zoning ordinances. The feasibility of installing an aquatic filter

barrier at the Stations is still uncertai n, because significant operational and nuclear safety/licensing issues associated with this technology would ha ve to be resolved prior to installation. However, it is assumed that cylindrical we dgewire screens could be installed at both Units 2 and 3 within approximately 5 years. If these screens were installed according to the schedule assumed in Section 4 of this report, the cumulative reductions in I&E losses over the remaining lifetimes of Units 2 and 3 would be far greater than the reduction that could be achieved through c onstruction of the NYS DEC Proposed Project.

It is questionable, however, whether a ny modifications of the existing intake technology would provide real and measurable increases in the abundance of any Hudson River fish populations. Entergy’s AEI report had previously concluded that historical operations of Units 2 and 3 have had no me asurable effect on fish populations and communities in the Hudson River. Additional analyses documented in this report show

that even if entrainment of fish larvae at Units 2 and 3 were completely eliminated, no measurable changes in the abundance of older, juvenile fish are li kely to occur.

### 48 Figure 7. Percent reductions in age-1 equi valent entrainment and impingement losses compared to the regulatory baseline, fo r technologies evaluated in this report. 0 10 20 30 40 50 60 70 80 90 100111.11.21.21.21.52345678910111213141515.5

Case Number% reduction in Age-1 Equivalents Compared toRegulatory Baseline

Operational changes Wedgewire Screens

Existing technology Alternative Ristroph

screens

Aquatic filter

barrier Closed-cycle cooling 

### Entrainment

0 10 20 30 40 50 60 70 80 90 100111.11.21.21.21.52345678910111213141515.5

Case Number% reduction in Age-1 Equivalents Compared toRegulatory Baseline

Operational changes Wedgewire Screens

Existing technology Alternative Ristroph

screens

Aquatic filter

barrier Closed-cycle cooling 

### Impingement

### 49 

## 7. References

ASA. 2007. 2005 Year Class Report for the Hu dson River Estuary monitoring program. ASA Analysis and Communica tion, Washingtonville, NY.

Barnthouse, L. W., D. G. Heimbuch, W. Van Winkle, and J. R. Young. 2008. Entrainment and and Impingement at IP2 and IP3: A Biological Assessment.

Central Hudson Gas and Electr ic (“CHGE”), et al. 1999. Dr aft Environmental Impact Statement Concerning the Applications to Renew New York State Pollutant Discharge Elimination System (“SPDES”) Permits for the Roseton 1 & 2, Bowline 1 & 2, and

Indian Point 2 & 3 Steam Electric Gene rating Stations, Orange, Rockland, and

Westchester Counties.

U.S. Environmental Protection Agency (EPA ). 2002. §316b Existing Facilities Benefits Case Studies, Part A: Evaluation Methods, Ch. 5.

EPA. 2004. §316b Phase II Final Rule – Regi onal Case Studies, Part A: Evaluation Methods, Ch. 5.

Electric Power Research Institute (“EPRI”) . July 2004. Extrapolating impingement and entrainment losses to equivalent adults and production foregone. EPRI Report 1008471.

EPRI. December 2005. Parameter developmen t for equivalent adult and production foregone models. EPRI Report 1008832.

French McCay, D. P., and J. J. Rowe. 2003. Habitat restoration as mitigation for lost production at multiple trophic levels. Ma rine Ecology Progress Series 264:233-247.

Mattson, M. T., J. B. Waxman, and D. A ., Watson. 1988. Reliability of impingement sampling designs: An example from the Indian Point Station. American Fisheries Society Monographs 4 :161-169.

National Oceanic and Atmospheric Admi nistration (NOAA). 1997. Natural resource damage assessment guidance document: scali ng compensatory restoration actions. Damage Assessment and Restoration Progr am, National Oceanic and Atmospheric Administration, Silver Spring, MD.

Secor, D.H., and E.D. Houde. 1995. Temperat ure effects on the timing of striped bass egg production, larval viabil ity, and recruitment potentia l in the Patuxent River (Chesapeake Bay). Estuaries 18 :527-544.

### 50 Young, J. R., W. P. Dey, S. M. Jinks, and D. T. Mosier. 2009. Survival of striped bass entrained into the cooling system of two Hudson River power plants. North American Journal of Fisheries Management

. 29 :1015-1034.

### ASA Analysis & Communication, Inc.



### 1 

## APPENDIX A

BIOLOGICAL ANALYSIS OF SELECTED

COOLING SYSTEM ALTERNATIVES FOR

INDIAN POINT ENERGY CENTER

John R. Young
ASA Analysis & Communication, Inc.



### February 2010

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### 2 

## LIST OF TABLES ................................................................. 4

Introduction ......................................................................... 6

Methodology ........................................................................ 8

Species selection .......................................................................... 8

Entrainment and impingement densities .................................. 11

Entrainment Density ( D Esw 

### ) .............................................................. 12

Impingement Density ( D Ism 

### ) ............................................................. 14



## Modes of Action of Alternatives................................................. 15

Avoidance probability ( A ) ................................................................ 16

Exclusion probability ( X ).................................................................. 18

Survival probabilit y if excluded ( S X



### ) ............................................... 18

Survival probability if not excluded ( S nX 

### ) ....................................... 21



## Calculation of losses and loss reduction .................................. 23



## Results ............................................................................... 29

References ......................................................................... 60

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### 3 

## LIST OF FIGURES

Figure 1 Calculations to estimate regu latory compliance (% loss reduction) and alternative performance (incremental loss reduction) for technology alternatives. .. 10 Figure 2 Potential fates of organisms exposed to a cooling water intake structure. A = probability of avoiding the intake, X = probability of exclusion by the intake if encountered, S X



### = probability of surviving if excluded by the intake, S

nx 

### = probability of surviving if not excluded ...................................................................................... 17 Figure 3 Estimated fraction of Atlantic to mcod excluded by screens as a function of opening size and fish length (mm). ........................................................................... 19 Figure 4 Estimated fraction of striped bass excluded by screens as a function of opening size and fish length (mm). ......................................................................................... 19 Figure 5 Estimated fraction of white perch excluded by screens as a function of opening size and fish length (mm). ......................................................................................... 19 Figure 6 Estimated fraction of river herring excluded by screens as a function of opening size and fish length (mm). ......................................................................................... 20 Figure 7 Estimated fraction of bay anchovy excluded by screens as a function of opening size and fish length (mm). ......................................................................................... 20

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### 4 

## LIST OF TABLES

Table 1 Size, habitat, and exploitation of Representative Important Species (RIS) for Indian Point Energy Center. ...................................................................................... 11 Table 2 Conversion factor (Psl) to estimate entrainment density from river standing crop. Life stages are egg, yolk-sac larva (YSL), post yolk-sac larva (P YSL), and juvenile.

............................................................................................................................... .... 13 Table 3 Correlations among BSS and FSS a nnual abundance in rm 34-55 across ages and surveys, and selected adjustment ratio for impingement analysis. ........................... 15 Table 4 Exclusion survival parameters us ed for IPEC alternatives analysis. A = asymptotic maximum survival, B = parameter for length, C = length below which survival is 0, D = latent survival rate ........................................................................ 21 Table 5 Impingement survival on current Ri stroph screens at IPEC (from Fletcher 1990)

............................................................................................................................... .... 21 Table 6 Entrainment survival paramete rs for species entrained at IPEC. M E0 

### = initial instantaneous mortality rate, M EL 

### = latent mortality rate, λ = latent mortality change
parameter, α = parameter for length, β = parameter for temperature, γ = parameter for salinity, T crit 

### = temperature at which thermal effects begin. ............................... 23 Table 7 Entrainment avoidance, exclusion, and survival parameters used for IPEC alternative technologies. ........................................................................................... 24 Table 8 Impingement avoidance, exclusion, and survival parameters used for IPEC alternative technologies. ........................................................................................... 24 Table 9 Intake technologies in place each year for cumulative analysis. ........................ 28 Table 10 Numbers entrained, entrainment losse s, and equivalent age 1 losses, and mean

percent loss reduction from regulatory baseline (
E 

### LR % 

### ) and mean incremental loss

reduction ( E 

### ILR ) for alternatives examined for IPEC Units 2 and 3. ...................... 32
Table 11 Numbers impinged, impingement losses, and equivalent age 1 losses, and mean

percent loss reduction from regulatory baseline (
I 

### LR % ) and mean incremental loss

reduction (
I 

### ILR ) for alternatives examined for IPEC. ............................................. 33
Table 12 Monthly and annual total number of RIS entrained (millions) under intake technology alternatives for Indi an Point Energy Center. .......................................... 34 Table 13 Monthly and annual total percent reduction in number of RIS entrained under intake technology alternatives for Indian Point Energy Center. Reduction calculated from regulatory baseline. .......................................................................................... 35 Table 14 Monthly and annual total number entrainment losses (millions) of RIS under intake technology alternatives fo r Indian Point Energy Center. ............................... 36 Table 15 Monthly and annual total percent re duction in entrainment losses of RIS under intake technology alternatives for Indian Point Energy Center. Reduction calculated from regulatory baseline. .......................................................................................... 37 Table 16 Monthly and annual total equivalent age 1 losses (millions) of RIS under intake technology alternatives for Indi an Point Energy Center. .......................................... 38

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### 5 Table 17 Monthly and annual total percent re duction in equivalent age 1 losses of RIS under intake technology altern atives for Indian Point Energy Center. Reduction calculated from regulat ory baseline. ......................................................................... 39 Table 18 Monthly and annual total number of RIS impinged under intake technology alternatives for Indian Point Energy Center. ............................................................. 40 Table 19 Monthly and annual total percent reduction in number of RIS impinged under intake technology alternatives for Indian Point Energy Center. Reduction calculated from regulatory baseline. .......................................................................................... 41 Table 20 Monthly and annual total impingeme nt losses of RIS under intake technology alternatives for Indian Point Energy Center. ............................................................. 42 Table 21 Monthly and annual total percen t reduction in impingement losses RIS under intake technology alternatives for Indian Point Energy Center. Reduction calculated from regulatory baseline. .......................................................................................... 43 Table 22 Monthly and annual total equivale nt age 1 impingement losses of RIS under intake technology alternatives fo r Indian Point Energy Center. ............................... 44 Table 23 Monthly and annual total percent reduction in equivalent age 1 losses of impinged RIS under intake technology alternat ives for Indian Point Energy Center.

Reduction calculated from regulatory baseline. ........................................................ 45 Table 24 Average annual RIS equivalent age 1 loss (millions) lost yield (kg), and production forgone (kg) due to entrainmen t and impingement for intake technology alternatives for Indian Point Energy Center. ............................................................. 46 Table 25 Lost yield (kg) due to entrainment and impingement and combined for intake

alternatives at IPEC. Dir ect lost yield represents co mmercial and recreational catch of exploited species. Convert ed lost yield calculated fr om production forgone of all RIS except striped bass converted to st riped bass yield by EPA Phase III rule methodology. ............................................................................................................ 55

Table 26 Cumulative end of life estimates of undiscounted entrainment and impingement total losses, equivalent age 1 losses, and lost yield for RIS at IPEC units 2 and 3, 2013 through 2035. Percent reduction relative to Baseline value. Savings ratio relative to Closed Cycle. Percent reducti on and savings ratio av eraged over species.

............................................................................................................................... .... 56

Table 27 Cumulative end of life estimates of discounted (3% per year) entrainment and impingement total losses, equivalent age 1 losses, and lost yield for RIS at IPEC units 2 and 3, 2013 through 2035. Percent reduc tion relative to Baseline value. Savings ratio relative to Clos ed Cycle. Percent reduction and savings ratio averaged over species. .............................................................................................................. 57 Table 28 Annual equivalent age 1 entrainment losses (millions) for RIS with existing technology at IPEC units 2 and 3. ............................................................................. 59

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### 6 

## Introduction

Entergy Nuclear Indian Point 2, LLC a nd Entergy Nuclear Indian Point 3, LLC (“Entergy”) retained ASA Analysis & Comm unications, Inc. (“ASA”) to determine the biological effectiveness, measured in reducti ons in entrainment and impingement losses, associated with potential alte rnative intake technologies c onsidered for the Indian Point Entergy Center (“IPEC”) nuclear powered electric generating stations 2 and 3 (individually, “Unit 2” and “Unit 3,” and coll ectively, the “Stations”). This evaluation was undertaken as part of Entergy’s a lternative technology a ssessment performed pursuant to the New York State Depart ment of Environmental Conservation (“NYSDEC”) Assistant Commissione r’s August 13, 2008 Interim Decision. 1 

### This report supports the “Biological Effec tiveness of Alternat ive Intake Technologies for Indian Point Units 2 and 3” (the “Biological Repor t”) prepared by Lawrence W. Barnthouse of LWB Environmental Services, Inc., Douglas G. Heimbuch of AKRF, Inc., Mark T. Mattson of Normandeau Associates, Inc., and John R. Young of ASA Analysis & Communication, Inc.

A suite of potential alternative technologies considered at IPEC was first evaluated by the engineering consultant, Ener con Services, Inc. (“ENERCO N”) for technological and engineering feasibility. The alternative tec hnologies further eval uated for biological

effectiveness at IPEC were:

 wedgewire screens with slot wi dths ranging from 1mm to 9 mm

 Ristroph-type traveling screens with mesh sizes ranging from 1mm to 9mm

 aquatic filter barriers (“AFB” ) in front of the intakes

In addition to these alternative technol ogies, the biological evaluation includes a comparison to the existing technologies (6mm x 12mm Ristroph screens operated continuously, with fish return systems; mu lti speed pumps operated to minimize cooling water use; and a cooling system design that pe rmits entrainment survival) and to a closed cycle cooling system.

Two separate biological eval uations of the technology alte rnatives are provided: an evaluation of regulatory complian ce with performance standards 2 

### and an analysis of alternative technology performance (incre mental reduction in entrainment and impingement losses) that would be expected for each alternative (Figure 1). For the regulatory compliance analysis (Figure 1 t op), entrainment and impingement losses are compared to those that would occur if the station were built and operated according to

defined baseline conditions:

1 As noted in Biological Effectiveness of Alternativ e Intake Technologies for Indian Point Units 2 and 3 (Barnthouse et al. 2010), a 2003 draft permit issued by NYSDEC Staff proposed modifications to the cooling water intake structure at the Stations. These modifications include possible construction and operation of two large counter-flow, forced draft, plume abated hybrid cooling towers (the “NYSDEC Proposed Project”).

2 Typically NYSDEC issues renewed SPDES permits containing specified numerical performance standards for entrainment and impingement reductions. The minimum requirements are generally at or above the minimums in the now-suspended EPA Phase II §316(b) rule: 60% for entrainment and 80% for impingement. However, for the Stations, no numerical standards were specified.

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### 7  Shoreline intake structure w ithdrawing from surface waters

 3/8” mesh traveling screens operate d as needed for debris removal

 Full flow operation 365 days per year

 No survival of impinged or entrained fish

The regulatory compliance baseline loss is a hypothetical level of entrainment and impingement loss that does not, in most cases, describe actual historic al losses. Usually generating stations do not operate at full flow on all days of the year, and often at least one plant design feature differs from the baseline condition.

The alternative baseline was intended to mo re closely approximate actual impingement and entrainment losses that would occur at Unit 2 and Unit 3, if the existing intake technology had not been installed. For the a lternative comparison (F igure 1 bottom), the

alternative baseline assumes the same intake configuration and flow assumptions as the compliance baseline, but also incorporates esti mates of the actual survival of entrained

fish.

For the regulatory baseline, losses are determined as:

mBaseline Ism

m sBaseline I wBaseline Esw

w sBaseline E



### F D Loss F D Loss



#  

 

where Loss EsBaseline 

### = annual entrainment loss of species s under baseline conditions, D Esw 

### = expected density (number of organisms per unit volume of water withdrawn) of entrainable stages of species s in week w , F wBaseline 

### = baseline (full flow) water withdrawal during week w , Loss IsBaseline 

### = annual impingement loss of species s under baseline conditions, D Ism 

### = density of impingeable stages of species s in month m , and

F

mBaseline 

### = baseline (full flow) wa ter withdrawal during month m. It is assumed that all organisms will die as a result of entrainm ent or impingement, therefore no explicit adjustment for survival is required. The tim e intervals for entrainment and impingement differ because the study designs to measure th e densities were based on weekly sampling for entrainment, but quarterly sampling for impingement.

Losses for the alternative baselines for en trainment and impingement at IPEC are

calculated as:

mBaseline IsBaseline Ism

m sBaseline I wBaseline EsBaseline Esw

w sBaseline E



### F S D Loss F S D Loss

) 1 ( )

1 (

* *



### 

  


# 



S

EsBaseline 

### = entrainment survival of species s under baseline conditions, S IsBaseline 

### = impingement survival of species s under baseline conditions. Survival estimates reflect operation of the facility under baseline conditions. For entrai nment, some survival would be expected at times when thermal stress wa s not severe and bioc ides were not being used. For impingement, long wash-to-wash dura tions and lack of a fish return system

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### 8 would preclude any significant level of survival, therefore the regulatory baseline and alternative baseline are equivalent.

Losses under current technology ar e calculated similarly, with appropriate changes for

current flows and survival:

mCurrent IsCurrent Ism

m sCurrent I wCurrent EsCurrent Esw

w sCurrent E



### F S D Loss F S D Loss

) 1 ( )

1 (

   


# 



For the current technology and all technol ogy alternatives, percent loss reductions ( %LR )

are calculated as:

% 100% Baseline Tech

Tech

Baseline 

### Loss Loss LR Loss   



### where Loss Baseline 

### = baseline loss 3 

### , and Loss Tech 

### = estimated losses for the technology being evaluated.

The incremental loss reduction ( ILR ) is the additional reduct ion in losses beyond that already achieved with a less protective t echnology. For curren t technology, the less protective alternative for calculating ILR is the alternative baseline, i.e. losses that would

occur under baseline conditions af ter adjusting for any survival that would have occurred. For other technologies, the loss with th e current technology is the appropriate comparison:

e Alternativ Current e Alternativ Current Baseline Current


### Loss Loss ILR Loss Loss ILR

    *



### where Loss Baseline* 

### = baseline losses after adjustment for survival (alternative baseline)



## Methodology

Species selection

The biological analysis of alternatives is pe rformed for the eight species determined in the original National Pollution Discharge Elimination System (“NPDES”) permit hearings for the Hudson River stations as Representative Important Species (“RIS”): striped bass, white perch, American shad, Atlantic tomcod, spottail shiner, bay anchovy, and two species collectively known as “river he rring” (alewife and blueback herring). Species may be put in the designated RIS group due to a high degree of involvement with the intake structure or sensitivity to thermal discharges, high ecological or societal value, or as surrogates for other species for whic h impacts may be similar. Several of the designated RIS (alewife, blueback herring, bay anchovy, spottail shiner) are small

3 For comparison to performance standards, the regu latory baseline would typically be used. Percent reductions from the alternative baseline are also provided for information purposes.

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### 9 (typically no more than 6-7”), even as adults, and serve an ecological function as prey for larger fish species. The river herrings use the estuary as a spawning and nursery area, but spend their adult lives in the ocean.ASAAnalysis & Communication, Inc.10Figure 1 Calculations to estimate regulatory compliance (% loss reduction) and alternative performance (incremental loss reduction) for technologyalternatives.Regulatory Compliance(% Loss Reduction)Alternative Tech & FlowAlternative SurvivalClosed Cycle FlowAlternative SurvivalBaseline Tech & FlowNo SurvivalBaseline Tech & FlowActual SurvivalCurrent Tech & FlowActual SurvivalLossBaselineClosed Cycle Technology(LossBaseline–LossClosed Cycle) /LossBaselinex 100%Alternative Performance(Incremental Loss Reduction)0LossScaleLossBaseline*LossCurrentLossAlternativeLossClosed CycleAlternative Technology(LossBaseline–LossAlternative) /LossBaselinex 100%Current Technology(LossBaseline–LossCurrent) /LossBaselinex 100%Current TechnologyLossBaseline* –LossCurrentAlternative TechnologyLossCurrent–LossAlternativeClosed Cycle TechnologyLossCurrent–LossClosed CycleRegulatory BaselineAlternative Baseline

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### 11 They are fished in the river primarily for use as bait. Bay anchovy, which consist of a single large coastal stock, inha bit only the brackish portions of the estuary during the warmer months. Spottail shiner is a sma ll year-round resident species that inhabits primarily the freshwater portion of the estuar y. White perch is a medium-sized (adults are up to about 12”) fish that is resident throughout the estuary, although it may undergo seasonal migrations within the estuary. Atlantic tomcod are another medium-sized estuarine resident species (a lthough some venture out side the mouth of the estuary), but are near the southern end of their range in the Hudson. Tomcod spawn in the Hudson in midwinter, with the young becoming mature ad ults by the following winter. Both species undergo light recreational fishing pressure.

Striped bass are a large (up to about 36” or larger), highly pr ized recreational species that enters the river to spawn during the spring. Young fish leave the estuary after 1 to 2 years, although some fish remain resident in the river. Prior to the discovery of high PCB concentrations, adult striped bass were harves ted from the Hudson commercially as a bycatch of the American shad fishery. Th e species is exploited commercially and recreationally in marine waters.

American shad, a large (up to 30” or more) me mber of the herring family, also return to the river to spawn. Shad formerly supporte d a large commercial fishery on the Hudson, but overexploitation in marine waters has driven the stock to very lo w levels. Shad, like the river herrings, spawn near the upper end of the estuary.

Table 1 Size, habitat, and exploi tation of Representative Importan t Species (RIS) for Indian Point Energy Center. 

### Species Size Habitat Exploitation Bay anchovy Small Marine/brackish No Spottail shiner Small Freshwater No Blueback herring Small Anad romous Primarily as bait Alewife Small Anadromous Primarily as bait White perch Medium Estuarine Light recreational

Atlantic tomcod Medium Es tuarine Light recreational American shad Large Anadromous Commercial Striped bass Large Anadromous Commercial & Recreational



## Entrainment and impingement densities

The owners of the Hudson River generating stations have conducte d biological studies

since the 1970s to assess the status the estuary’s fish populations and measure involvement of the populations with the power stations 4 

### . The Long River Survey

4 The survey descriptions provided are typical of the sampling, however, study designs have undergone change over the years. The actual study design for any particular year is provided in annual study reports.

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### 12 (“LRS”) measures the abundance and distribution of eggs, larv ae, and early juvenile fish in the shoal, bottom and channel strata from the Battery (river miles (“rm”) 0) to Albany (rm 152). Sampling is conducted weekly in the spring and early summer, and bi-weekly from July through October, or later in some years. The Fall Shoal Survey (“FSS”, “Fall Juvenile Survey” or “FJS”) measures the a bundance and distribution of juvenile and older fish in the same strata and regions. Th e FSS is conducted on alternate weeks from LRS sampling, beginning in July and extending thro ugh October. The Beach Seine Survey (“BSS”) samples beach areas along the entire estuary from July through November on alternate weeks. Annual reports on the result s of these studies are produced and provided to NYSDEC, the most recent currently av ailable being for the 2007 program (ASA 2009).

Entrainment abundance sampling to estimate the density (number per unit volume) of entrained organisms, was conducted at IPEC beginning in the early 1970s. However the most intense, and most recent, sampli ng was conducted from 1983-1987. Sampling was conducted nearly continuously from early May to early August in those years by pumping water from the discharge canal into ne ts suspended in a barrel of water. To assess involvement of Atlantic tomcod, samp ling was conducted one day per week from January through April in 1987. Numerous ancillary studies were also conducted to provide additional information on sampling effi ciency and distribution of organisms (EA 1984, EA 1985, NAI 1987a, NAI 1987b, NAI 1988).

Studies to estimate the fraction of organisms that survive entrainment were conducted at IPEC during the 1970s and 1980s. At the time the studies were begun, the methodology for entrainment survival was undergoing a rapi d evolution but stabi lized by the late 1970s. The results of the 1979, 1980, and 1988 programs were reanalyzed and summarized by Young et al. (2009).

Impingement at IPEC was sampled daily from 1973 through mid-1981, and according to a stratified random sampling design (Mattson et al. 1988) until the end of 1990 when the Ristroph screen installation was completed. No impingement sampling has been conducted recently. Entrainment survival on the Ristroph screens was estimated from on-site studies (Fletcher 1990).

Data from these river and in-plant samp ling programs were used to estimate the entrainment and impingement effects that would have been expected for various technology alternatives, had they been in place during 2001-2007.



### Entrainment Density ( D Esw 

### )

The week-specific entrainment densities ( D Esw 

### ), number of organisms per million m 3 

### of water withdrawn, were estimated by estab lishing the relationship between average weekly entrainment density in 1983-1987 (the most recent in-plant sampling data available) and standing crop (num ber of individuals) of the species in the vicinity of

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### 13 IPEC, between rm 34 and 55, in the same week s based on LRS data from the same set of years. Because both the entrai nment densities and river stan ding crops are measured with sampling error, a geometric mean regressi on (Ricker 1975) through the origin was used to estimate the relationship betw een river abundance and entrainment:

" ' " '



### / sl sl sl Eslw sl Rslw Rslw sl Eslw



### P P P D P C C P D

  



### where D Eslw 

### = entrainment density (# per million m 3 

### ) of life stage l of species s in week

w , C Rslw 

### = standing crop (millions) of life stage l of species s in the river (rm 34-55) in

week w, P’ sl



### = regression coefficient for de nsity regressed on standing crop, P” sl 

### = regression coefficient for stan ding crop regressed on density; P sl



### = conversion factor for life stage l of species s

.

This technique did not work for bay anchovy juveniles and American shad eggs because, due to low densities and sampling variation, they were not found in both entrainment and river sampling in the same week. For bay anchovy juveniles, FSS data were substituted for LRS data. For American shad eggs, P sl



### was defined as the ratio of mean entrainment density and mean river standing crop.

Table 2 Conversion factor (Psl) to estimate entr ainment density from riv er standing crop. Life stages are egg, yolk-sac larva (YSL), post yolk-sac larva (PYSL), and juvenile.



### Species P sl 

### Egg YSL PYSL Juvenile Bay anchovy 382 35,422 759 112 American shad 11,651 58 4,501 423

Striped bass 91 264 1,257 3,407

Atlantic tomcod No data No data 4.2 383

White perch 495 86 643 4,356 River herrings

(alewife & blueback herring) 5,572 8,976 1,557 2,224

The conversion factors (Table 2) were then applied to the weekly LRS standing crops (FSS standing crops for bay anchovy juveni les) observed in 2001-2007 sampling to

estimate 2001-2007 entrainment densities. Us ing this method, entrainment density can be estimated for any week in which there was river sampling between rm 34 and 55. For weeks between the beginning and end of the sampling program, standing crops in weeks that were not sampled were estimated by linear interpolation.

Swimming and physiological capabilities incr ease as fish develop from the newly hatched prolarvae to juvenile and older stag es (Beamish 1978, Yin and Blaxter 1987). In addition, development is a continual process and classification into life stage may be somewhat subjective (Lagler et al. 1962). Ther efore the changes that occur in avoidance,

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### 14 exclusion, and survival probabilities may be more closely related to size than to the developmental stage. To account more accurately for these size-related effects, the life stage densities were converted to length-spe cific densities based on length frequencies of entrained individuals during 1983-1987:



# 



l Eslw swlL EslLw 

### D f D

where D EsLw 

### = density (# per million m 3 

### ) of species s life stage l of length L in week w , f

swlL 

### = fraction of species s , life stage l that are length L in week w

.



### Impingement Density ( D Ism 

### )

Impingement sampling at IPEC was conducted from 1972 through 1990, when the modified Ristroph screen installation was completed. Because impingement estimates are desired for the most recent seven years (2001-2207), the most recent seven years of impingement sampling (1984-1990) were selected as a basis for making the estimates. During those years sampling was conducted a ccording to a stratified random sampling design (Mattson et al. 1988). In order to estimate recent impingement densities, it is necessary to use the historical impingement data, adjusted for changes in abundance from

the time those data were collected to the re cent period using data collected in the Hudson River Estuary Monitoring Program:

) 1990 1984 ( ) 2007 2001 (
) 1990 1984 (

 

 

### 

Rs Rs

Ism Ism 

### A A D D



### where ) 1990 1984 (

 Ism 

### D 

### = mean impingement density in month m of species s during 1984-

1990, adjusted for collection efficiency; ) 1990 1984 (

 Rs A 

### = mean standing crop in rm 34-55 of

species s during weeks 33-40 of 1984-1990; ) 2007 2001 (

 Rs A 

### = mean standing crop in rm 34-

55 of species s during weeks 33-40 of 2001-2007.

) 1990 1984 (

 Ism 

### D is calculated from the seasonal mean density in each year adjusted for

collection efficiency, averaged over the years 1984-1990, and applied to each month

within a season.

Both the FSS and BSS data were examined as potential sources of the values of Ā Rs



### . Mean annual standing crops in rm 33-55 ove r weeks 33-40 were calculated for young-ofyear and yearling fish for each survey. Correlations across age classes and surveys (and yearlings with young-of-year during the previ ous year) were examined to validate the mean standing crops as actual measures of abundance and choose the appropriate metric for adjustment of the historical impingement density (Table 3).

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### 15 Table 3 Correlations among BSS and FSS annual abundance in rm 34-55 across ages and surveys, and selected adjustment rati o for impingement analysis.

Species Abundance Correlations Selected Adjustment YOY BSS with YOY FSS with

YRL BSS YRL BSS

(t+1) YOY FSS YRL FSS YRL FSS

(t+1) Data set

) 1990 1984 ( ) 2007 2001 (

 

Rs Rs



### A A

Alewife -0.027 0.629* 0.221 0.092 -0.262 YOY BSS 3.341

Bay anchovy -0.225 0.224 0.070 0.566* 0.149 YOY FSS YRL FSS 0.395

0.109

American

shad - - 0.698* 0.042 0.596* YOY FSS 0.108

Blueback

herring -0.201 0.194 0.640** -0.179 0.558* YOY FSS 0.286

Spottail

shiner 0.009 0.158 - - - YOY BSS YRL BSS 0.629

0.484

Striped bass -0.361 0.369 0.018 0.894** 0.248 YOY BSS YRL BSS 1.141

1.757

Atlantic

tomcod 0.215 0.528 0.601* 0.471 0.658* YOY FSS 0.091

White perch 0.317 0.532 0.623** 0.770** 0.333 YOY BSS YRL BSS 0.630

0.389 

### * indicates p < 0.05 ** indicates p < 0.01



## Modes of Action of Alternatives

Alternatives technologie s considered for cooling water in takes generally can be separated into four modes of action. Technologies may i nduce fish to avoid the intake structure, for instance by providing a flight-i nducing stimulus such as flashing lights or sound. If intake velocities are low enough, normal beha vioral responses may be sufficient to produce avoidance. Other technologies may phys ically exclude fish from the intake by drawing water through a straining system with openings smaller than the organisms to be excluded. Exclusion systems may be placed aw ay from the actual intake structure, e.g. wedgewire screens or barrier nets, or within the intake, e.g. fine-mesh traveling screens. If the “strainer” is placed within the intake a collection and return system need to be incorporated to achieve any reductions in lo sses. Other technologies may increase the survival of fish that encounter the intake, in contrast to a baseline of 100% mortality for impinged or entrained fish.

For all three of these modes of action, it is assumed that the actual number of fish encountering the intake is di rectly proportional to the amoun t of cooling water flow. Thus, the fourth mode of action is to reduce the amount of water drawn into the intake. There may be interactions among these modes. For instance reduced flow rates, which reduce numbers of organisms impinged and pot entially increase avoidance and survival of impinged fish, may decrease the survival of entrained fish due to higher exposure
temperatures.

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### 16 These four modes of action produce five possi ble fates of the organisms exposed to the intake. They may be (1) able to avoid the intake, (2) be physically excluded (impinged)

at or within the intake and be returned to the source water alive, (3) be physically excluded (impinged) at or with in the intake but not surviv e, (4) pass through the cooling system and survive, or (5) pa ss through the cooling system but not survive (Figure 2).

The efficacy of the alternative technologies considered for the Stations can be divided into components due to avoidance, exclusi on, and survival, whether excluded or not excluded (Figure 2): A sLAlt 

### = probability that length L of species s can avoid the intake for the technology; X sLAlt 

### = probability that length L of species s will be excluded from the intake for the technology; and S XsLAlt 

### = probability that excluded length L of species s will survive. The following sections descri be the calculations for the avoidance and exclusion probabilities ( A EsAlt 

### , A IsAlt 

### , X EsAlt 

### , X IsAlt 

### ) and the survival probabilities ( S EsAlt 

### , S

IsAlt 

### ).



### Avoidance probability ( A )

Avoidance of an intake requires that an or ganism has a capability of swimming faster than the velocity of flow into the intake, is ab le to perceive some s timulus that triggers a response, and has a behavioral response appropr iate to result in escape. Fish eggs have none of these requirements, but as newly hatched larvae develop, they increase the capability for all three requirements. Due to the low design through-slot velocities (0.16 m/sec), and ambient currents that will occu r at times of tidal flow in the estuary, entrainable stages should be capable of some avoidance of the wedgewire screens. As documented in Appendix B, an avoidance pr obability was calculated from previous studies of wedgewire screen performance (Heuer and Tomaljanovich 1978, Weisberg et al. 1987, EPRI 2003). Avoidance pr obability was estimated by:

A sLAlt 

### = 1 – exp(-0.275[L-4])

where L = length in mm.

This function predicts no avoidance for larvae 4 mm or less, 24% avoidance for 5-mm larvae, 50% avoidance by 6.5 mm, and 95% avoidance at 15 mm fish.

The AFB being considered will have enough f iltering area that through -fabric velocities will be low enough that larval life stages s hould be able to avoid impingement, and even eggs and larvae that may contact the barrier s hould not be harmed. However, in practice it is difficult to maintain a perfect seal around the intake so that all water withdrawn must pass through the barrier (Appendix B). It wa s assumed that the barrier would be 79% effective in straining the water withdrawn, and that only 21% of the water would be

unfiltered.

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### 17 Figure 2 Potential fates of organisms exposed to a cooling water intake structure. Only organisms in

the Excluded-Dead and Passed-Dead fates are included in the loss estimates.

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### 18 Due to the designs considered for wedgewi re screens and AFBs, the water velocity through the intake filtering surface will be less than 0.5 feet per second (“fps”), a velocity which is considered slow enough that “impi ngeable” sized fish can avoid impingement. For the AFB, it is assumed that 21% of th e water withdrawn will not pass through the barrier but will somehow bypass it. Thus a voidance probability is 1.0 for wedgewire screens, 0 for fine-mesh screens, and 0.79 for AFB.



### Exclusion probability ( X )

Exclusion of organisms at the in take structure is a function of size of the mesh or slot width and the dimensions of the organism, which change as the organism grows. Exclusion probabilities for entrainment as a function of size were determined by measuring the body depth and width of specimens of the RIS over the range of sizes that are subject to entrainment (See Appendix B) . The exclusion probabilities described approximate sigmoid curves with no exclusion at the smallest sizes, and 100% exclusion for larger sizes. The lengths at which exclus ion occurs shift upward as slot size or mesh size increases (Figures 3 to 7).

The exclusion probabilities for wedgewire screens and fine-mesh screens are considered to be 1.0 for impingeable size fish, i.e. thos e that would be excl uded by the conventional 3/8” mesh traveling screen. However, for AFB, not all of the water will be filtered,

therefore exclusion of the fish will be 1.0 in filtered water but 0 in unfiltered water.



### Survival probability if excluded ( S X



### )

Survival of small fish that would have been entrained under the current technology but are excluded from the intake by fine-mesh sc reens was estimated from studies conducted at the Danskammer Point facility in 1986 and 1988 (NAI 1988b, NAI 1989). Fine-mesh (3 mm) screens were installed at the Dans kammer Point Unit 3 intake, and there were

standard 3/8” mesh at Danskammer Point Unit 4. Although differences in survival between the two units were inconsistent, there was a clear length-related pattern to

survival. The statistical model fit to the Danskammer data from both intakes was:

D C Length B A S IsL 

### })] { exp( 1 [



 

where S IsL 

### = impingement survival probability for species s of length L , A = asymptotic maximum survival, B = parameter for length, C = length below which survival is 0, D =

latent survival rate.

### ASA Analysis & Communication, Inc.



### 19 Atlantic tomcod

0 0.2 0.4 0.6 0.8

1

0 20 40 60 80
LengthFraction Excluded 1 mm

1.5 mm

2 mm

3 mm

6 mm

9 mm

Figure 3 Estimated fraction of Atlantic tomcod exclud ed by screens as a functi on of openin g size and fish length (mm).

Striped bass

0 0.2 0.4 0.6 0.8

1

0 20 40 60 80
LengthFraction Excluded 1 mm

1.5 mm

2 mm

3 mm

6 mm

9 mm

Figure 4 Estimated fraction of striped bass excluded by screens as a function of opening size and fish length (mm).

White perch

0 0.2 0.4 0.6 0.8

1

0 20 40 60 80
LengthFraction Excluded 1 mm

1.5 mm

2 mm

3 mm

6 mm

9 mm

Figure 5 Estimated fraction of white perch excluded by screens as a function of opening size and fish length (mm).

### ASA Analysis & Communication, Inc.



### 20 River herring

0 0.2 0.4 0.6 0.8

1

0 20 40 60 80
LengthFraction Excluded 1 mm

1.5 mm

2 mm

3 mm

6 mm

9 mm

Figure 6 Estimated fraction of river herring excl uded by screens as a function of opening size and fish length (mm).

Bay anchovy

0 0.2 0.4 0.6 0.8

1

0 20 40 60 80
LengthFraction Excluded 1 mm

1.5 mm

2 mm

3 mm

6 mm

9 mm

Figure 7 Estimated fraction of bay anchovy excluded by screens as a function of opening size and fish length (mm).



### To combine the length-specific survival model with the Stations-speci fic data, the 8-hour survival values (1 – mortality) from Fletcher (1990) were substituted for the A parameter estimated from the Danskammer data. For the current Ristroph screens, the latent

survival rate was excluded from calculations because Fletcher’s estimates included data up to 8 hours after collection. Very little additional morta lity occurred after 8 hours. However, for the fine-mesh screen evaluations , survival was estimated both without and with the D parameter (Table 4) to provide upper and lower bounds on survival of small fish that may be retained on the finer mesh.

### ASA Analysis & Communication, Inc.



### 21 Table 4 Exclusion survival parameters used for IPEC alternatives analysis. A = asymptotic maximum survival, B = parameter for length, C = le ngth below which survival is 0, D = latent

survival rate 

### Species A a 

### B C D Striped bass 0.91 0.0392 11.96 0.2677 White perch 0.86 0.0374 10.70 0.2292

Atlantic tomcod 0.83 0.0664 5 0.6797

American shad 0.65 0.0044 13.76 0 Bay anchovy 0.77 0.0059 8 0

Alewife 0.38 0.0044 13.76 0 Blueback herring 0.74 0.0044 13.76 0 Spottail shiner b 

### 0.91 0.0645 5 0.6797 a Fletcher (1990) survival value substituted for estimate from Danskammer data

b Substituted data for Atlantic tomcod

Studies to estimate impingement survival on the current Ristroph screens were conducted in 1986-1987 (Fletcher 1990). These studies pr ovided empirical estimates of the fraction of many of the RIS that surv ive the experience undamaged, a nd can then be returned to the river. (Table 5).

Table 5 Impingement survival on current Ristroph screens at the Stations (from Fletcher 1990) 

### Species S I s 

### Striped bass 0.91 White perch 0.86

Atlantic tomcod 0.83

American shad 0.65 Bay anchovy 0.77

Alewife 0.38 Blueback herring 0.74 Spottail shiner b 

### 0.91

Survival of fish impinged is assumed to be 1.0 for wedgewire screens and AFB since impingeable fish can either avoid impingement altogether, or should be able to easily escape from the mesh due to the low velocitie s at the face of the screens and sweeping flows. Impingement survival on fine-mesh sc reens should be equal t o, or possibly better than, survival on the current screens.



### Survival probability if not excluded ( S nX 

### )

Organisms that do not avoid the intake, and are not excluded, are entrained into the cooling system. Entrainment survival, for simplicity denoted as S E



### rather than S nX



### , is considered to be the product of the indepe ndent probabilities of surviving mechanical (physical contact with cooling system equi pment, shear, turbulence), thermal, and

### ASA Analysis & Communication, Inc.



### 22 chemical stress (USEPA 2006). However, chlo rination of the condenser cooling system at the Stations is limited by permit conditi ons to a maximum of 2 hours per unit per day, and 9 hours total per week, and actual chlorina tion is significantly less than permitted. Therefore, entrainment survival can be esti mated as functions of only mechanical and

thermal stresses:

S

EsLw 

### = S msLw 

### S Tsw



### where S EsLw 

### = probability of surviving entrainment for species s, length L in week w , S

msLw 

### = probability of surviving mechanical stresses for species s, length L in week w , and

S Tsw 

### = probability of surviving thermal stresses for species s in week w

.

The probability of surviving mechanical st ress was estimated from survival studies conducted at IPEC in 1979 (EA 1980), 1980 (EA 1981), and 1988 (EA 1989). Years of

intensive research at IPEC and other Hudson River stations (cite i ndividual studies and ESEERCO work) produced many improvements in the equipment and protocols used to measure entrainment survival (O’Connor and Shaffer 1977, McGroddy and Wyman 1977, Jinks et al. 1981, Muessig et al. 1988). The results of this research were incorporated into the 1979, 1980, and 1988 st udies. The mechanical component of entrainment survival for striped bass, based on the 1979, 1980, and 1988 data, was determined to be a function of organism le ngth and salinity, using failure time analysis (Young et al. 2009), which is an improved method of estimation over the methods previously used (Young 2009):

) } 1 ) exp( { exp( 0   

###  

w EL E msLw 

### H L t M M S  

 



### where S msLw 

### = probability of surviving the mechan ical stress of entrainment for length L of species s in week w , M E0 

### = initial instantaneous mortality rate, M EL 

### = latent mortality

rate, λ = latent mortality change parameter, t = time in days since entrainment, L = length in mm, H

w 

### = salinity in ppt in week w , α = parameter for length, γ = parameter for salinity.

Probability of surviving thermal stress, ba sed on the field data from the same 1979, 1980, and 1988 studies, was estimated by Young et al. (2009) with a logistic model as:

)]} ( ) 99 exp[log( 1 /{ 1
crit Ed Tsd 

### T T S

     for T Ed 

### ≥ T crit


### S Tsd 

### = 1 for T Ed



### < T crit



### where S Tsd 

### = probability of surviving the thermal stress of entrainment for species s on day d

, β = thermal parameter, T Ed



### = exposure temperature in the discharge (°C) on day d

, and T crit 

### = temperature (°C) at which therma l effects begin. Daily values of S msLw 

### S Tsd 

### were averaged for each week.

Parameters for striped bass were estimated by Young et al. (2009). Their analysis of the 1979, 1980, and 1988 data was repeated for the other RIS species, however only white

### ASA Analysis & Communication, Inc.



### 23 perch and Atlantic tomcod had sufficient data demonstrating survival substantially above zero. Therefore, for species other than these three, parameter values were set to indicate

no entrainment survival..

Table 6 Entrainment surv ival parameters for species entrained at IPEC. M E0 = initial instantaneous mortality rate, M EL = latent mortality rate, λ = latent mortality change parameter, α = parameter for length, β = parameter for temperature, γ = parameter for salinity, T crit = temperature at which thermal effects begin. 

### Species M E0 

### M EL 

### λ α β γ T cri t 

### Striped bass 8.27 0.02 1.54 -1.75 -1.16 -0.20 30 White perch 38.21 208.62 -3.82 -2.76 -1.10 -0.41 30

Atlantic tomcod 0.506 0.677 -1.090 -0.343 -2.376 -0.22 25.1

Others 5 

### 50 0 0 0 0 0 30

For fish entrained into the service water system 6 

### , which provides up to 16,000 gallons per minute (“gpm”) at Unit 1, 30,000 gpm at Un it 2 and 36,000 gpm at Unit 3 for cooling equipment other than the condensers and for othe r uses, entrainment survival was set to 0. Mechanical stresses, thermal exposures and tr ansit times in the serv ice water system may be greater than in the cooli ng water system, and survival of organisms entrained into the service water system has not been studied.



## Calculation of losses and loss reduction

If A = probability of avoiding the intake, X = probability of exclusion by the intake if it is encountered, S X



### = probability of surviving if excluded by the intake, S

nx 

### = probability of surviving if not excluded, and all probabilities are independen t, then the probabilities of the five distinct fates are the products of the individual probabilitie s along each pathway:

Fate Intake Structure Excluded Survive Probability

1 Avoid intake - Yes A 2 Encounter intake Yes Yes (1- A ) XS X 

### 3 Encounter intake Yes No (1- A ) X

(1- S X



### ) 4 Encounter intake No Yes (1- A )(1- X

) S

nx 

### 5 Encounter intake No No (1- A )(1- X

)(1- S

nx 

### )

For any particular alternativ e technology, losses are calcul ated from the sum of the probabilities of fates 3 and 5:

mAlt IsAlt sAlt XsAlt sAlt sAlt Ism

m ve sAlternati I wAlt EsAlt sAlt XsAlt sAlt sAlt Esw

w ve sAlternati E



### F S X S X A D Loss F S X S X A D Loss

)] 1 )( 1 ( ) 1 ( )[ 1 ( )] 1 )( 1 ( ) 1 ( )[ 1 (

  

     

  


# 



5 Survival estimates were ve ry low, therefore parameter values that estimate survival as 0 were substituted.

6 Service water is used for cooling auxiliary equipment, screen wash water, and uses other than condenser cooling. Typically service water withdrawals ar e a small fraction of cooling water withdrawals.

### ASA Analysis & Communication, Inc.



### 24 where A sAlt 

### = probability of species s avoiding the intake under the technology alternative,

X

sAlt 

### = probability of species s being excluded from pa ssing through the technology alternative, S XsAlt 

### = probability of species s surviving exclusion by the technology alternative, S EsAlt 

### = probability of species s surviving entrainment if not excluded by the technology alternative, S IsAlt 

### = probability of species s surviving impingement on the current screen system if not excl uded by the technology alternative, F wAlt 

### and F mAlt 

### = weekly or monthly flow under the alternativ e technology. The avoidance, exclusion, and survival probabilities will differ for entrainabl e size, i.e. pass through 3/8” mesh (Table 7) and impingeable size, i.e. excluded by 3/8” mesh (Table 8). Some technologies may not

have avoidance or exclusion fates.

Table 7 Entrainment avoidance, exclusion, and survival paramet ers used for IPEC alternative technologies.



### Technology

Alternative Avoidance

A sLAlt 

### Exclusion

X

sLAlt 

### Survival if

Excluded

S

XsLAl t 

### Survival if not

Excluded

S

Es

L

Al t



### Wedgewire

screens Increasing

function of length Based on body

dimensions

and slot width 1 Species and sizedependent

Fine-mesh

screens 0 Based on body

dimensions

and mesh size Increasing

function of length (w/wo latent effects) Species and sizedependent

Aquatic filter

barrier 0.82 0 0 Species and sizedependent Closed cycle cooling 0 0 0 0

Table 8 Impingement avoidance, exclusion, and survival parameters used for IPEC alternative technologies.



### Technology Alternative Avoidance

A

s LAl t 

### Exclusion

X

s LAl t 

### Survival

S

XsLAl t 

### Wedgewire screens 1 1 1

Fine-mesh screens 0 1 S I sCurren t 

### Aquatic filter barrier 0.82 0 0 Closed cycle cooling 0 0 0

The percentage reduction in entrainment and impingement losses ( %LR ) for each species

are calculated as:

% 100 % % 100 %

 

  



IsBaseline ive IsAlternat IsBaseline

ve sAlternati I EsBaseline ive EsAlternat EsBaseline

ve sAlternati E



### Loss Loss Loss LR Loss Loss Loss LR

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### 25 Incremental loss reduction ( ILR ) of an alternative technology is based on the reduction in entrainment and impingement losses from those occurring under a less protective technology alternative, usually the currently employed technology, and is expressed as an absolute number of organisms:

ive IsAlternat IsCurrent ve sAlternati I IsCurrent IsBaseline IsCurrent ive EsAlternat EsCurrent ve sAkternati E EsCurrent EsBaseline EsCurrent



### Loss Loss ILR Loss Loss ILR Loss Loss ILR Loss Loss ILR

       

* *



### where Loss EsBaseline* 

### and Loss IsBaseline* 

### are entrainment and impingement losses using the baseline technology and operating practices, with any entrainment or impingement survival that would actually occur under this condition (alt ernative baseline). At IPEC,

non-zero entrainment survival has been demons trated, but impingement survival was not

so Loss IsBaseline* = 

### Loss IsBaseline.



### .

Percent loss reductions ( %LR EsAlternative 

### , %LR IsAlternative 

### ), and incremental loss reductions ( ILR EsAlternative 

### , ILR IsAlternative 

### ) can be calculated for each year in which plant flow and organism densities are available. For pur poses of estimating the average reductions toward compliance of a technology alternat ive, the percentage loss reductions are calculated for each of the taxa in a particular year and then averaged to produce an annual average percent reduction in year y :



#  

 

s s ive IsAlternat ive IyAlternat s s ive EsAlternat ive EyAlternat



### n LR LR n LR LR

/ % % / % %



### where n s 

### = number of species. For entrainment, only 6 taxa are involved because spottail shiner are distributed upriver from IPEC a nd seldom entrained, a nd larval stages of blueback herring and alewife ar e indistinguishable and are co mbined into a single river herring taxon.

The annual average percent re ductions are averaged ove r the years 2001-2007 to obtain the expected average performance of the technolo gy alternative:



#  

 

y y ive IyAlternat ve IAlternati y y ive EyAlternat ve EAlternati



### n LR LR n LR LR

/ % % / % %



### where n y 

### = number of years.

Summary of the incremental loss reductions was done by first averaging the ILR values for a species across the years, then summing over species.

### ASA Analysis & Communication, Inc.



### 26 

#  

 

y y ive IsAlternat ive IsAlternat y y ive EsAlternat ive EsAlternat



### n ILR ILR n ILR ILR

/ /



#  

 

s ive IsAlternat ve IAlternati s ive EsAlternat ve EAlternati



### ILR ILR ILR ILR

For a fish, involvement with a cooling water intake structure coul d happen at any life stage, i. e. egg, yolk-sac larva, post yolk-sac larva, juvenile, sub-adult, adult, although as fish grow their ability to avoid cooling wa ter intakes increases. As an annual cohort (group of fish spawned in the same year) progresses through these stages, it becomes less

numerous due to natural mort ality from causes such as pred ation, disease, and starvation, but the individual surviving fish become la rger in size and more valuable to the population because their probability of reproducing increases. Thus, the loss of a single egg is of less consequence to a population of fish than loss of a la rva, and similarly the loss of a larva is of less consequence than loss of a juvenile, and so forth. Although the average probability of survival for any life stag e varies with species, cohorts of fish often decline by one or more orders of magnitude from one stage to the next due solely to natural mortality.

The actual metrics for entrainment and impingement losses, Loss Es 

### and Loss Is 

### , are often expressed as raw numbers of organisms su mmed over all life stages, but due to the different life stages’ wide variation in probability of surviving to reproduce, the significance of these totals is difficult to in terpret. To facilitate an understanding of the significance of the losses, they can also be expressed as losses at some common age or stage which has a more obvious ecological or so cietal meaning, such as age 1, age at first reproduction, or age of entry into a fish ery (Horst 1975, Rago 1984, EPRI 2004). This conversion to a common stage or age is particularly important when comparing alternative technologies that may have different effectiveness for different life stages. A technology that would save 50% of a million entrained eggs, could be less effective ecologically than a technology that save d 25% of a thousand impinged juveniles. 7



### For comparing among the various alternativ e technologies, it is unimportant which common life stage the lo sses are converted to as long as the losses are converted to an equivalent life stage that is used for all alternatives. The life stage selected for conversion in this analysis is age 1, i.e. 12 months old. C onversion to equivalent age-1

fish allows I&E losses that occur at different life stages to be combined into a single metric that weights the losses according to the number that could, on average, have survived to age 1. The biologi cal effectiveness of each altern ative, using this approach,

7 Consider two brothers who each receive $1in change (25 pennies, 6 nickels, 2 dimes, and 1 quarter) to spend at the store. Due to holes in their pockets, when they get to the store some of their money has been lost. One brother has lost 8 coins, but the other brother has lost only 4. Which brother suffered the greater loss cannot be determined without knowing the number of each type of coin lost and their values. The conversion of entrainment and impingement losses to a common life stage is analogous.

### ASA Analysis & Communication, Inc.



### 27 reflects the net effectiveness of that alternative at reduci ng losses of young fish, including both entrainment and impingement losses. While this conversion is effective at equilibrating losses at different life stages within a single species, it may still encompass wide ecological differences when losses are summed across species. Age 1 bay anchovy and Atlantic tomcod are full-grown mature adults, but age 1 st riped bass are only a fraction of their adult size and still 3-6 year s from spawning. Comparing the effects of technologies across species that differ greatly in size, life history, and ecological niche, particularly if some of the species have recreational or co mmercial value, can be done by converting the losses to lost yield and produc tion forgone. The losses of harvestable species are translated directly into weight of harvest the losses woul d have been expected to produce, and forage species are converted to additional lost ha rvest through the amount of biomass they would have been expected to produce, that would then be consumed by harvestable species, converted to harvestable biomass, and subsequently harvested (EPA 2006, EPRI 2004, Rago 1984)



## Cumulative Analysis

The effects of whatever technol ogy is in place at the Stati ons will be realized over the course of the remaining life of the facility. Although Unit 2's operating license expires in 2013, and Unit 3's license in 2015, Entergy has a pplied for 20-year license extensions for both units. If the license extensions are granted, the units will operate from present until

end of life with a combination of the cu rrent technology, and any potential replacement technology installed at some time in the future . A cumulative analysis was performed to examine the possible cumulative effects of the current technology, wedgewire screens, and closed cycle alternatives using a realistic timeline fo r implementation over the time of the extended operating licenses. The technology implementation proposal for wedgewire screens (i.e., Unit 2 installed by 2013 and Unit 3 installed by 2015) is based on studies of this technology. The implementation schedule for the NYSDEC Proposed Project (i.e. construction complete by 2029) was derived by ENERCON, with input from counsel and Spectra Energy Transmission, LLC (owner of the gas pipeline that would require relocation to complete the project).

For this analysis, th ree indicators, mean annual losses, mean annual equivalent age 1 losses, and mean annual lost yield for each RIS taxon for entrainment and impingement, were applied to a 23-year time frame from 2013 to 2035, the year th at a 20 -year license

extension for Unit 3 would end.

Three separate scenarios were considered : 1) Existing technology remains in place throughout the 23 year period; 2) Wedgewire sc reens are installed at both units, with Unit 2 screens operational in 2013, and Unit 3 screens in 2015; 3) Existing technology remains in place until closed cycle cooling is eventua lly installed. The initial year of operation for closed cycle is assumed to be 2029 at both units. It is also assumed that a 1-year outage is required in 2028 to comp lete tie-in for both units.

The three loss metrics, for the appropriate technologies for each scenario (Table 9) were summed over the 23 year period on an undiscounte d, and discounted (3% pe r year) basis.

### ASA Analysis & Communication, Inc.



### 28 Table 9 Intake technologies in place each year for cumulative analysis.



### Year Technologies in place for scenario Existing Technology Wedgewire Screens Closed Cycle

Unit 2 Unit 3 Unit 2 Unit 3 Unit 2 Unit 3 2013 Existing Existing Wedgwire Existing Existing Existing 2014 Existing Existing Wedgwire Existing Existing Existing 2015 Existing Existing Wedgwire Wedgwire Existing Existing 2016 Existing Existing Wedgwire Wedgwire Existing Existing 2017 Existing Existing Wedgwire Wedgwire Existing Existing 2018 Existing Existing Wedgwire Wedgwire Existing Existing 2019 Existing Existing Wedgwire Wedgwire Existing Existing 2020 Existing Existing Wedgwire Wedgwire Existing Existing 2021 Existing Existing Wedgwire Wedgwire Existing Existing 2022 Existing Existing Wedgwire Wedgwire Existing Existing 2023 Existing Existing Wedgwire Wedgwire Existing Existing 2024 Existing Existing Wedgwire Wedgwire Existing Existing 2025 Existing Existing Wedgwire Wedgwire Existing Existing 2026 Existing Existing Wedgwire Wedgwire Existing Existing 2027 Existing Existing Wedgwire Wedgwire Existing Existing 2028 Existing Existing Wedgwire Wedgwire Not online Not online 2029 Existing Existing Wedgwire Wedgwire Closed Cycle Closed Cycle 2030 Existing Existing Wedgwire Wedgwire Closed Cycle Closed Cycle 2031 Existing Existing Wedgwire Wedgwire Closed Cycle Closed Cycle 2032 Existing Existing Wedgwire Wedgwire Closed Cycle Closed Cycle 2033 Existing Existing Wedgwire Wedgwire Closed Cycle Closed Cycle 2034 Not online Existing Not online Wedgwire Not online Closed Cycle 2035 Not online Existing Not online Wedgwire Not online Closed Cycle

The percent reduction in cumulative losses fr om the regulatory baseline was calculated for each scenario. In addition, the ratio of reduced losses, from those for existing technology, due to wedgewire scr een alternatives were compar ed to the reduced losses of the closed cycle alternative.

### ASA Analysis & Communication, Inc.



### 29 The percent reduction and savings ratio we re averaged over the RIS taxa for each

scenario.

As a final step for the cumulative analysis, the sensitivity of the entrainment cumulative result to the wedgewire screen avoidance function and exclusion survival rate was examined. These two factors could potentially be highly determinative of the comparison between wedgewire screens and closed cycle cooling. For the sens itivity analysis, a series of reduced avoidance capability curves was developed (Figure 8).

Figure 8 Avoidance capability curves used for sensit ivity analysis. Curve 1 is based on the function derived from experimental data Avoidance = 1 - exp(-0 .275[Length-4]). Curves 2 through 8 represent alternative assumptions of lesser avoidance capability.



### Three alternative assumptions were used for survival of organisms excluded by the wedgewire screens: 1) the assumption of 100% used in analysis of alternatives, 2) survival equivalent to the fine-mesh screen impingement survival curves estimated from the studies at Danskammer Point(Figure 9), and 3) zero survival of physically excluded organisms.

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### 30 Figure 9 Exclusion survival assumed for wedgewi re screens for sensitivity analysis. Curves are based on parameters A, B, and C from Table 4.



### The combination of eight different assump tions about avoidance and three different exclusion survival assumption resulted in 24 alternative estimates of cumulative

entrainment results.



## Results

Main output summaries are provided in Tables 10 (entrainment) and 11 (impingement).

Tables 12-17 contain the average monthl y numbers entrained (12), % reduction of numbers (13), monthly entrainment losses (1 4) , % reduction of losses (15), monthly equivalent age 1 losses (16), and % reduction of losses (17).

Tables 18-23 contain the average monthl y numbers impinged (18), % reduction of numbers (19), monthly impingement losses ( 20) , % reduction of losses (21), monthly equivalent age 1 losses (22), and % reduction of losses (23).

Table 24 presents equivalent age 1 losses, lost yield, and production forgone by for entrainment and impingement by species for each alternative.

Table 25 presents lost yield estimates for each alternative.

Table 26 presents the cumulative analysis for entrainment and impingement, using

undiscounted totals.

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### 31 Table 27 presents the cumulative analysis for entrainment and impingement, using

discounted totals.

Figure 10 presents results of the sensitivity analysis for percent reduction of cumulative 2013-2035 equivalent age 1 losses of wedgewire screen alternatives and closed cycle cooling.

Table 28 presents the estimated annual 2001-2007 equivalent age 1 entrainment losses for the RIS with existing technology.ASAAnalysis & Communication, Inc.32Table 10 Numbers entrained, entrainment losses, and equivalentage 1 losses, and mean percent loss reduction from regulatory baseline (ELR%)and meanincremental loss reduction (EILR) for alternatives examinedfor IPEC Units 2 and 3.Case AlternativeNumbers (millions) Losses (millions) Equivalent Age 1 (millions) IncrementalReductionaofLost Yield(kg)MeanMean %ReducedMeanIncrementalReduction MeanELR%EILRMeanELR%EILRAltELR_%0 Regulatory Baseline 1,219 0 01,224 0 0 3.270 0 0.000 0.00 00.5 Alternative Baseline 1,219 0 0 68723.67 0 2.834 17.19 0.000 0.00 01 Existing Technology 1,139 17.38 79 64634.74 42 2.637 33.770.197 19.21 14,0391.0000 Flow Reduction 0MW Loss 1,128 18.04 11632 35.88 14 2.597 35.68 0.040 22.94 11,8341.1010 Flow Reduction 10MW Loss 861 37.33 278 58745.07 58 2.174 44.720.462 29.50 -1,3561.2020 Flow Reduction 20MW Loss 805 41.68 334578 47.36 68 1.997 47.8 0.640 31.94 -1,6111.2030 Flow Reduction 20-30MW Loss 783 43.31 356567 48.63 78 1.89549.63 0.742 33.83 3631.2040 Flow Reduction 20-40MW Loss 781 43.42 358565 48.77 80 1.88149.85 0.756 34.10 7181.5 One-unit outage 604 56.33 535 340 66.13 306 1.36066.15 1.277 59.13 46,8242 1-mm wedgewire screen 315 78.05 824 316 78.99329 0.301 88.84 2.335 81.90 68,2173 1.5-mm wedgewire screen 424 74.22 715 26880.15 378 0.27889.68 2.35984.01 75,1954 2-mm wedgewire screen 43873.5 701 262 80.27384 0.275 89.77 2.362 84.30 76,2205 3-mm wedgewire screen 444 73.07 695 262 80.17383 0.277 89.67 2.360 84.16 76,1296 6-mm wedgewire screen 446 72.82 693 262 80.16383 0.279 89.64 2.358 84.10 75,9237 9-mm wedgewire screen 446 72.82 693 262 80.16383 0.279 89.64 2.358 84.10 75,9118 1-mm mesh Ristroph screen 618 57.89 521 89825.18 -252 2.656 27.95-0.019 5.02 -33,8348.5 1-mm mesh Ristroph screena618 57.89 521 908 20.69 -262 2.974 18.12 -0.338 -8.06 -69,8629 1.5mm mesh Ristroph screen 938 42.74 201 73130.23 -85 2.562 31.460.075 13.06 -10,8719.5 1.5mm mesh Ristroph screena938 42.74 201 739 25.86 -93 2.878 21.66 -0.241 0.01 -46,89310 2-mm mesh Ristroph screen 1,057 34.18 82 67233.08 -26 2.520 33.490.117 17.32 -2,77010.5 2-mm mesh Ristroph screena1,057 34.18 82 678 28.83 -33 2.833 23.76 -0.196 4.37 -38,77311 3-mm mesh Ristroph screen 1,122 25.14 17646 34.99 0 2.499 34.930.138 20.25 1,00711.5 3-mm mesh Ristroph screena1,122 25.14 17 650 31.06 -42.802 25.5 -0.165 7.74 -34,683126-mm mesh Ristroph screen1,139 17.38 0 646 34.74 02.637 33.77 0.000 19.21 012.56-mm mesh Ristroph screena1,139 17.38 0 647 31.56 -2 2.75626.94 -0.119 10.62 -20,67713 9-mm mesh Ristroph screen 1,143 7.55 -4 64732.95 -1 2.690 31.5-0.053 16.25 -7,21713.5 9-mm mesh Ristroph screena1,143 7.55 -4 647 31.06 -2 2.734 26.82 -0.097 11.05 -10,16114 Aquatic Filter Barrier 239 82.64 900 13488.02 511 0.474 90.392.162 87.75 76,07915 Closed Cycle 35 97.53 1,104 35 97.44 611 0.095 97.562.542 96.65 84,40515.5 Closed Cycleb54 96.12 1,085 54 96.01 5910.141 96.25 2.495 94.80 81,487aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.33Table 11 Numbers impinged, impingement losses,and equivalent age 1 losses, and mean percent loss reduction from regulatory baseline (ILR%)and meanincremental loss reduction (IILR) for alternatives examined for IPEC.Case AlternativeNumbers Losses Equivalent Age 1 IncrementalReductionaof Lost Yield(kg)MeanMean %ReducedMeanIncrementalReduction MeanELR%EILRMeanELR%EILR0 Regulatory Baseline 669,465 0.000 669,465 0.00 0 484,294 0.00 0 00.5 Regulatory Baseline 669,465 0.000 669,465 0.00 0 484,294 0.00 0 01 Existing Technology 474,429 22.02 195,036 70,415 79.89 599,050 49,926 80.15 434,368 25,3481.0000 Flow Reduction 0MW Loss 450,654 25.41 23,775 66,914 80.78 3,50147,703 80.76 2,223 751.1010 Flow Reduction 10MW Loss 419,016 35.05 55,413 61,518 83.63 8,89743,760 83.93 6,166 1331.2020 Flow Reduction 20MW Loss 415,620 36.96 58,809 60,843 84.20 9,57243,081 84.68 6,846 1411.2030 Flow Reduction 20-30MW Loss 414,674 37.8159,755 60,619 84.47 9,79542,776 85.04 7,149 1441.2040 Flow Reduction 20-40MW Loss 414,595 37.9159,834 60,598 84.50 9,81742,746 85.08 7,181 1451.5 One-unit outage 366,79348.68 107,635 52,915 87.85 17,499 35,790 90.05 14,136 4112 1-mm wedgewire screen 17,829 97.35 456,600 2,598 99.34 67,816 1,82499.39 48,102 1,5903 1.5-mm wedgewire screen 17,829 97.35 456,6002,598 99.34 67,816 1,82499.39 48,102 1,5904 2-mm wedgewire screen 17,829 97.35 456,600 2,598 99.34 67,816 1,82499.39 48,102 1,5905 3-mm wedgewire screen 17,829 97.35 456,600 2,598 99.34 67,816 1,82499.39 48,102 1,5906 6-mm wedgewire screen 17,829 97.35 456,600 2,598 99.34 67,816 1,82499.39 48,102 1,5907 9-mm wedgewire screen 17,829 97.35 456,600 2,598 99.34 67,816 1,82499.39 48,102 1,5908 1- mm mesh Ristroph screen 474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 08.5 1- mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 09 1. 5mm mesh Ristroph screen 474,42922.02 0 70,415 79.890 49,926 80.15 0 09.5 1. 5mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 010 2- mm mesh Ristroph screen 474,42922.02 0 70,415 79.890 49,926 80.15 0 010.5 2- mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 011 3- mm mesh Ristroph screen 474,42922.02 0 70,415 79.890 49,926 80.15 0 011.5 3- mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 012 6- mm mesh Ristroph screen 474,42922.02 0 70,415 79.890 49,926 80.15 0 012.5 6- mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 013 9- mm mesh Ristroph screen 474,42922.02 0 70,415 79.890 49,926 80.15 0 013.5 9- mm mesh Ristroph screena474,429 22.02 0 70,415 79.89 0 49,926 80.15 0 014 Aquatic Filter Barrier 113,715 81.54 360,713 16,840 95.26 53,575 11,926 95.34 38,000 1,25615 Closed Cycle 19,317 97.14 455,111 2,81799.29 67,598 1,97999.33 47,948 1,58415.5 Closed Cycleb29,287 95.64 445,142 4,277 98.9266,137 3,034 98.93 46,892 1,545aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.34Table 12 Monthly and annual total numberof RIS entrained (millions) under intake technology alternatives for Indian Point Energy Center.Number Entrained (millions)Case Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.1 0.5 385.6 492.0 224.0 83.8 30.0 2.5 0.0 0.0 1,218.50.5 Alternative Baseline 0.0 0.0 0.1 0.5 385.6 492.0 224.0 83.8 30.0 2.5 0.0 0.0 1,218.51 Existing Technology 0.0 0.0 0.0 0.3 336.1 472.5 218.1 80.8 28.9 2.3 0.0 0.0 1,139.11.0000 Flow Reduction 0MW Loss 0.0 0.0 0.0 0.3 325.2 472.3 218.1 80.8 28.9 2.2 0.0 0.0 1,127.81.1010 Flow Reduction 10MW Loss 0.0 0.0 0.0 0.3 244.5 350.9 175.2 65.8 22.7 1.6 0.0 0.0 861.11.2020 Flow Reduction 20MW Loss 0.0 0.0 0.0 0.3 243.5 324.4 156.5 58.7 20.4 1.5 0.0 0.0 805.31.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.0 0.3 243.5 317.9 145.8 54.9 19.2 1.5 0.0 0.0 783.11.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.0 0.3 243.5 317.9 144.9 53.9 19.2 1.5 0.0 0.0 781.21.5 One-unit outage 0.0 0.0 0.0 0.2 186.6 246.1 112.6 42.0 14.9 1.2 0.0 0.0 603.62 1-mm wedgewire screen 0.0 0.0 0.0 0.1 118.6 121.1 49.5 17.4 8.2 0.6 0.0 0.0 315.43 1.5-mm wedgewire screen 0.0 0.0 0.0 0.1 151.4 162.9 76.9 24.0 8.5 0.6 0.0 0.0 424.44 2-mm wedgewire screen 0.0 0.0 0.0 0.1 154.2 172.1 77.9 24.3 8.6 0.6 0.0 0.0 437.85 3-mm wedgewire screen 0.0 0.0 0.0 0.1 156.6 174.9 78.4 24.4 8.7 0.6 0.0 0.0 443.66 6-mm wedgewire screen 0.0 0.0 0.0 0.1 158.5 175.1 78.4 24.4 8.7 0.6 0.0 0.0 445.87 9-mm wedgewire screen 0.0 0.0 0.0 0.1 158.5 175.1 78.4 24.4 8.7 0.6 0.0 0.0 445.88 1-mm mesh Ristroph screen 0.0 0.0 0.0 0.1 216.2 226.8 112.6 43.2 17.7 1.3 0.0 0.0 617.88.5 1-mm mesh Ristroph screena0.0 0.0 0.0 0.1 216.2 226.8 112.6 43.2 17.7 1.3 0.0 0.0 617.89 1.5mm mesh Ristroph screen 0.0 0.0 0.0 0.1 312.7 368.5 169.3 63.0 22.9 1.6 0.0 0.0 938.29.5 1.5mm mesh Ristroph screena0.0 0.0 0.0 0.1 312.7 368.5 169.3 63.0 22.9 1.6 0.0 0.0 938.210 2-mm mesh Ristroph screen 0.0 0.0 0.0 0.1 327.9 435.1 193.2 72.4 26.3 1.9 0.0 0.0 1,057.010.5 2-mm mesh Ristroph screena0.0 0.0 0.0 0.1 327.9 435.1 193.2 72.4 26.3 1.9 0.0 0.0 1,057.011 3-mm mesh Ristroph screen 0.0 0.0 0.0 0.1 333.5 469.6 210.6 78.0 27.8 2.0 0.0 0.0 1,121.711.5 3-mm mesh Ristroph screena0.0 0.0 0.0 0.1 333.5 469.6 210.6 78.0 27.8 2.0 0.0 0.0 1,121.712 6-mm mesh Ristroph screen 0.0 0.0 0.0 0.3 336.1 472.5 218.1 80.8 28.9 2.3 0.0 0.0 1,139.112.5 6-mm mesh Ristroph screena0.0 0.0 0.0 0.3 336.1 472.5 218.1 80.8 28.9 2.3 0.0 0.0 1,139.113 9-mm mesh Ristroph screen 0.0 0.0 0.0 0.3 337.5 472.7 218.8 81.8 29.5 2.4 0.0 0.0 1,143.113.5 9-mm mesh Ristroph screena0.0 0.0 0.0 0.3 337.5 472.7 218.8 81.8 29.5 2.4 0.0 0.0 1,143.114 Aquatic Filter Barrier 0.0 0.0 0.0 0.1 70.6 99.2 45.8 17.0 6.1 0.5 0.0 0.0 239.215 Closed Cycle 0.0 0.0 0.0 0.0 10.6 13.7 6.7 2.7 0.9 0.1 0.0 0.0 34.615.5 Closed Cycleb0.0 0.0 0.0 0.0 16.5 22.0 10.3 3.8 1.4 0.1 0.0 0.0 54.1aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.35Table 13 Monthly and annual total percent reduction in numberof RIS entrained under intake technology alternatives for IndianPoint Energy Center.Reduction calculated from regulatory baseline.% Reduction of Number EntrainedCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00.5 Alternative Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.01 Existing Technology 0.0 0.0 0.2 1.1 10.8 2.7 1.8 0.2 0.0 0.0 0.0 0.0 16.91.0000 Flow Reduction 0MW Loss 0.0 0.0 0.3 1.3 11.3 2.7 1.8 0.2 0.0 0.0 0.0 0.0 17.61.1010 Flow Reduction 10MW Loss 0.0 0.0 0.3 1.3 14.7 13.8 4.9 1.0 0.3 0.1 0.0 0.0 36.41.2020 Flow Reduction 20MW Loss 0.0 0.0 0.3 1.3 14.7 16.2 6.2 1.3 0.4 0.1 0.0 0.0 40.61.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.3 1.3 14.7 16.8 7.0 1.6 0.5 0.1 0.0 0.0 42.21.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.3 1.3 14.7 16.8 7.1 1.6 0.5 0.1 0.0 0.0 42.31.5 One-unit outage 0.0 0.0 0.3 1.7 17.4 23.2 9.4 2.2 0.7 0.1 0.0 0.0 54.92 1-mm wedgewire screen 0.0 0.0 0.5 2.6 20.1 33.7 14.6 3.6 1.0 0.1 0.0 0.0 76.23 1.5-mm wedgewire screen 0.0 0.0 0.5 2.6 19.3 32.0 13.6 3.3 1.0 0.1 0.0 0.0 72.54 2-mm wedgewire screen 0.0 0.0 0.5 2.6 19.3 31.5 13.5 3.3 1.0 0.1 0.0 0.0 71.85 3-mm wedgewire screen 0.0 0.0 0.5 2.6 19.2 31.3 13.4 3.3 1.0 0.1 0.0 0.0 71.36 6-mm wedgewire screen 0.0 0.0 0.5 2.4 19.2 31.2 13.4 3.3 1.0 0.1 0.0 0.0 71.17 9-mm wedgewire screen 0.0 0.0 0.5 2.4 19.2 31.2 13.4 3.3 1.0 0.1 0.0 0.0 71.18 1-mm mesh Ristroph screen 0.0 0.0 0.5 2.6 16.4 23.0 11.3 2.2 0.6 0.1 0.0 0.0 56.68.5 1-mm mesh Ristroph screena0.0 0.0 0.5 2.6 16.4 23.0 11.3 2.2 0.6 0.1 0.0 0.0 56.69 1.5mm mesh Ristroph screen 0.0 0.0 0.4 2.6 14.2 14.7 8.3 1.2 0.3 0.1 0.0 0.0 41.89.5 1.5mm mesh Ristroph screena0.0 0.0 0.4 2.6 14.2 14.7 8.3 1.2 0.3 0.1 0.0 0.0 41.810 2-mm mesh Ristroph screen 0.0 0.0 0.3 2.5 13.8 9.8 6.2 0.6 0.2 0.0 0.0 0.0 33.510.5 2-mm mesh Ristroph screena0.0 0.0 0.3 2.5 13.8 9.8 6.2 0.6 0.2 0.0 0.0 0.0 33.511 3-mm mesh Ristroph screen 0.0 0.0 0.3 2.4 13.6 4.4 3.5 0.3 0.1 0.0 0.0 0.0 24.611.5 3-mm mesh Ristroph screena0.0 0.0 0.3 2.4 13.6 4.4 3.5 0.3 0.1 0.0 0.0 0.0 24.612 6-mm mesh Ristroph screen 0.0 0.0 0.2 1.1 10.8 2.7 1.8 0.2 0.0 0.0 0.0 0.0 16.912.5 6-mm mesh Ristroph screena0.0 0.0 0.2 1.1 10.8 2.7 1.8 0.2 0.0 0.0 0.0 0.0 16.913 9-mm mesh Ristroph screen 0.0 0.0 0.2 0.8 4.3 1.5 0.4 0.1 0.0 0.0 0.0 0.0 7.413.5 9-mm mesh Ristroph screena0.0 0.0 0.2 0.8 4.3 1.5 0.4 0.1 0.0 0.0 0.0 0.0 7.414 Aquatic Filter Barrier 0.0 0.0 0.4 2.4 22.6 36.3 14.2 3.6 1.1 0.1 0.0 0.0 80.715 Closed Cycle 0.0 0.0 0.5 2.6 25.2 44.0 17.0 4.3 1.3 0.2 0.0 0.0 95.215.5 Closed Cycleb0.0 0.0 0.5 2.6 25.0 43.3 16.7 4.3 1.3 0.2 0.0 0.0 93.8aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.36Table 14 Monthly and annual total number entrainment losses (millions) of RIS under intake technology alternatives for Indian Point Energy Center.Entrainment Losses (millions)Case Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.1 0.5 385.9 492.9 226.0 85.2 30.9 3.0 0.0 0.0 1,224.50.5 Alternative Baseline 0.0 0.0 0.0 0.3 119.1 230.3 219.2 85.0 30.6 2.9 0.0 0.0 687.31 Existing Technology 0.0 0.0 0.0 0.2 99.2 217.3 213.8 82.4 29.9 2.7 0.0 0.0 645.61.0000 Flow Reduction 0MW Loss 0.0 0.0 0.0 0.2 96.8 209.0 211.0 82.4 29.9 2.7 0.0 0.0 632.01.1010 Flow Reduction 10MW Loss 0.0 0.0 0.0 0.2 109.6 210.4 174.4 67.1 23.6 1.9 0.0 0.0 587.31.2020 Flow Reduction 20MW Loss 0.0 0.0 0.0 0.2 110.8 226.6 157.3 59.9 21.2 1.9 0.0 0.0 577.91.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.0 0.2 110.8 231.6 146.8 56.0 20.0 1.9 0.0 0.0 567.31.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.0 0.2 110.8 231.6 146.0 55.0 19.9 1.9 0.0 0.0 565.41.5 One-unit outage 0.0 0.0 0.0 0.1 58.4 112.5 109.2 42.8 15.4 1.4 0.0 0.0 339.92 1-mm wedgewire screen 0.0 0.0 0.0 0.1 85.6 123.4 74.9 23.3 8.3 0.6 0.0 0.0 316.13 1.5-mm wedgewire screen 0.0 0.0 0.0 0.1 59.6 99.4 75.9 24.0 8.5 0.6 0.0 0.0 268.14 2-mm wedgewire screen 0.0 0.0 0.0 0.1 57.6 94.3 76.5 24.3 8.6 0.6 0.0 0.0 262.05 3-mm wedgewire screen 0.0 0.0 0.0 0.1 57.5 94.4 76.8 24.4 8.7 0.6 0.0 0.0 262.46 6-mm wedgewire screen 0.0 0.0 0.0 0.1 57.5 94.4 76.8 24.4 8.7 0.6 0.0 0.0 262.57 9-mm wedgewire screen 0.0 0.0 0.0 0.1 57.5 94.4 76.8 24.4 8.7 0.6 0.0 0.0 262.58 1-mm mesh Ristroph screen 0.0 0.0 0.0 0.2 193.4 375.9 215.1 81.0 29.5 2.7 0.0 0.0 897.88.5 1-mm mesh Ristroph screena0.0 0.0 0.0 0.3 194.0 378.6 218.8 82.9 30.3 2.8 0.0 0.0 907.79 1.5mm mesh Ristroph screen 0.0 0.0 0.0 0.2 115.5 287.1 214.3 81.4 29.7 2.7 0.0 0.0 730.99.5 1.5mm mesh Ristroph screena0.0 0.0 0.0 0.2 116.1 289.4 217.1 82.9 30.3 2.8 0.0 0.0 738.810 2-mm mesh Ristroph screen 0.0 0.0 0.0 0.2 102.3 241.6 213.6 81.8 29.8 2.7 0.0 0.0 672.010.5 2-mm mesh Ristroph screena0.0 0.0 0.0 0.2 102.9 243.4 215.6 82.9 30.3 2.8 0.0 0.0 678.211 3-mm mesh Ristroph screen 0.0 0.0 0.0 0.2 99.1 218.6 213.2 82.1 29.9 2.7 0.0 0.0 645.911.5 3-mm mesh Ristroph screena0.0 0.0 0.0 0.2 99.7 219.2 214.5 82.9 30.3 2.8 0.0 0.0 649.612 6-mm mesh Ristroph screen 0.0 0.0 0.0 0.2 99.2 217.3 213.8 82.4 29.9 2.7 0.0 0.0 645.612.5 6-mm mesh Ristroph screena0.0 0.0 0.0 0.2 99.6 217.6 214.2 82.8 30.2 2.8 0.0 0.0 647.413 9-mm mesh Ristroph screen 0.0 0.0 0.0 0.2 99.5 217.4 213.9 82.7 30.0 2.7 0.0 0.0 646.513.5 9-mm mesh Ristroph screena0.0 0.0 0.0 0.2 99.6 217.7 214.2 82.8 30.1 2.8 0.0 0.0 647.314 Aquatic Filter Barrier 0.0 0.0 0.0 0.0 20.7 45.6 44.5 17.0 6.1 0.5 0.0 0.0 134.315 Closed Cycle 0.0 0.0 0.0 0.0 10.6 13.7 6.7 2.7 1.0 0.1 0.0 0.0 34.815.5 Closed Cycleb0.0 0.0 0.0 0.0 16.5 22.0 10.4 3.9 1.4 0.1 0.0 0.0 54.4aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.37Table 15 Monthly and annualtotal percent reduction in entrainment losses of RIS under intake technologyalternatives for Indian Point Energy Center.Reduction calculated from regulatory baseline.% Reduction of Entrainment LossesCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00.5 Alternative Baseline 0.0 0.0 0.2 0.9 9.7 12.2 0.6 0.0 0.0 0.0 0.0 0.0 23.71 Existing Technology 0.0 0.0 0.3 1.4 13.8 15.8 2.8 0.6 0.1 0.0 0.0 0.0 34.71.0000 Flow Reduction 0MW Loss 0.0 0.0 0.3 1.4 14.1 16.4 3.1 0.6 0.1 0.0 0.0 0.0 35.91.1010 Flow Reduction 10MW Loss 0.0 0.0 0.3 1.4 14.4 20.7 6.3 1.5 0.4 0.1 0.0 0.0 45.11.2020 Flow Reduction 20MW Loss 0.0 0.0 0.3 1.4 14.4 20.9 7.8 1.9 0.6 0.1 0.0 0.0 47.41.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.3 1.4 14.4 21.0 8.7 2.2 0.6 0.1 0.0 0.0 48.61.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.3 1.4 14.4 21.0 8.8 2.2 0.6 0.1 0.0 0.0 48.81.5 One-unit outage 0.0 0.0 0.3 1.8 17.7 30.3 12.0 3.0 0.9 0.2 0.0 0.0 66.12 1-mm wedgewire screen 0.0 0.0 0.3 2.0 17.9 34.7 17.9 4.5 1.3 0.3 0.0 0.0 79.03 1.5-mm wedgewire screen 0.0 0.0 0.3 2.0 18.5 35.4 17.9 4.4 1.3 0.3 0.0 0.0 80.24 2-mm wedgewire screen 0.0 0.0 0.3 2.0 18.5 35.6 17.8 4.4 1.3 0.3 0.0 0.0 80.35 3-mm wedgewire screen 0.0 0.0 0.3 2.0 18.5 35.5 17.8 4.4 1.3 0.3 0.0 0.0 80.26 6-mm wedgewire screen 0.0 0.0 0.3 2.0 18.5 35.5 17.8 4.4 1.3 0.3 0.0 0.0 80.27 9-mm wedgewire screen 0.0 0.0 0.3 2.0 18.5 35.5 17.8 4.4 1.3 0.3 0.0 0.0 80.28 1-mm mesh Ristroph screen 0.0 0.0 0.2 1.4 12.0 8.1 2.7 0.6 0.1 0.0 0.0 0.0 25.28.5 1-mm mesh Ristroph screena0.0 0.0 0.2 1.2 10.4 7.0 1.5 0.4 0.0 0.0 0.0 0.0 20.79 1.5mm mesh Ristroph screen 0.0 0.0 0.2 1.4 13.6 11.5 2.7 0.6 0.1 0.0 0.0 0.0 30.29.5 1.5mm mesh Ristroph screena0.0 0.0 0.2 1.2 12.0 10.4 1.6 0.4 0.0 0.0 0.0 0.0 25.910 2-mm mesh Ristroph screen 0.0 0.0 0.3 1.4 14.0 13.9 2.8 0.6 0.1 0.0 0.0 0.0 33.110.5 2-mm mesh Ristroph screena0.0 0.0 0.2 1.2 12.4 12.9 1.7 0.4 0.0 0.0 0.0 0.0 28.811 3-mm mesh Ristroph screen 0.0 0.0 0.3 1.4 14.0 15.7 2.9 0.6 0.1 0.0 0.0 0.0 35.011.5 3-mm mesh Ristroph screena0.0 0.0 0.3 1.2 12.4 14.8 1.9 0.4 0.0 0.0 0.0 0.0 31.112 6-mm mesh Ristroph screen 0.0 0.0 0.3 1.4 13.8 15.8 2.8 0.6 0.1 0.0 0.0 0.0 34.712.5 6-mm mesh Ristroph screena0.0 0.0 0.3 1.4 12.6 15.0 1.9 0.4 0.1 0.0 0.0 0.0 31.613 9-mm mesh Ristroph screen 0.0 0.0 0.3 1.4 12.6 15.4 2.7 0.5 0.1 0.0 0.0 0.0 33.013.5 9-mm mesh Ristroph screena0.0 0.0 0.3 1.4 12.4 14.7 1.8 0.4 0.1 0.0 0.0 0.0 31.114 Aquatic Filter Barrier 0.0 0.0 0.3 2.0 21.0 39.5 18.7 4.7 1.4 0.3 0.0 0.0 88.015 Closed Cycle 0.0 0.0 0.3 2.1 22.1 44.5 21.0 5.4 1.6 0.4 0.0 0.0 97.415.5 Closed Cycleb0.0 0.0 0.3 2.1 21.8 43.7 20.7 5.3 1.6 0.3 0.0 0.0 96.0aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.38Table 16 Monthly and annual total equivalent age 1 losses (millions) of RIS underintake technology alternatives for Indian Point Energy Center.Equivalent Age 1 Losses (millions)Case Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.2 0.4 1.2 0.8 0.5 0.2 0.0 0.0 3.30.5 Alternative Baseline 0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.8 0.4 0.1 0.0 0.0 2.81 Existing Technology 0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.7 0.4 0.1 0.0 0.0 2.61.0000 Flow Reduction 0MW Loss 0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.7 0.4 0.1 0.0 0.0 2.61.1010 Flow Reduction 10MW Loss 0.0 0.0 0.0 0.0 0.1 0.2 0.9 0.6 0.3 0.1 0.0 0.0 2.21.2020 Flow Reduction 20MW Loss 0.0 0.0 0.0 0.0 0.1 0.2 0.8 0.5 0.3 0.1 0.0 0.0 2.01.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.0 0.0 0.1 0.2 0.7 0.5 0.3 0.1 0.0 0.0 1.91.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.0 0.0 0.1 0.2 0.7 0.5 0.3 0.1 0.0 0.0 1.91.5 One-unit outage 0.0 0.0 0.0 0.0 0.0 0.1 0.5 0.4 0.2 0.1 0.0 0.0 1.42 1-mm wedgewire screen 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.33 1.5-mm wedgewire screen 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.34 2-mm wedgewire screen 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.35 3-mm wedgewire screen 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.36 6-mm wedgewire screen 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.37 9-mm wedgewire screen 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.38 1-mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.3 1.0 0.7 0.4 0.1 0.0 0.0 2.78.5 1-mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.3 1.1 0.8 0.4 0.2 0.0 0.0 3.09 1.5mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.3 1.0 0.7 0.4 0.1 0.0 0.0 2.69.5 1.5mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.3 1.1 0.8 0.4 0.2 0.0 0.0 2.910 2-mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.2 1.0 0.7 0.4 0.1 0.0 0.0 2.510.5 2-mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.3 1.1 0.8 0.4 0.2 0.0 0.0 2.811 3-mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.2 1.0 0.7 0.4 0.1 0.0 0.0 2.511.5 3-mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.8 0.4 0.2 0.0 0.0 2.812 6-mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.7 0.4 0.1 0.0 0.0 2.612.5 6-mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.8 0.4 0.1 0.0 0.0 2.813 9-mm mesh Ristroph screen 0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.8 0.4 0.1 0.0 0.0 2.713.5 9-mm mesh Ristroph screena0.0 0.0 0.0 0.0 0.1 0.2 1.1 0.8 0.4 0.1 0.0 0.0 2.714 Aquatic Filter Barrier 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.1 0.1 0.0 0.0 0.0 0.515 Closed Cycle 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.115.5 Closed Cycleb0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.1aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.39Table 17 Monthly and annualtotal percent reduction inequivalent age 1 losses of RIS underintake technologyalternatives forIndian Point Energy Center.Reduction calculated from regulatory baseline.% Reduction of Equivalent Age 1 LossesCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00.5 Alternative Baseline 0.0 0.0 0.0 0.2 4.8 9.0 1.2 0.5 0.7 0.7 0.0 0.0 17.21 Existing Technology 0.0 0.0 0.0 0.4 6.1 14.3 6.4 4.1 1.3 1.1 0.0 0.0 33.81.0000 Flow Reduction 0MW Loss 0.0 0.0 0.0 0.4 6.3 14.9 7.3 4.2 1.4 1.2 0.0 0.0 35.71.1010 Flow Reduction 10MW Loss 0.0 0.0 0.0 0.4 6.5 17.1 10.2 6.0 2.3 2.1 0.0 0.0 44.71.2020 Flow Reduction 20MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 11.8 7.0 2.7 2.2 0.0 0.0 47.81.2030 Flow Reduction 20-30MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 12.9 7.5 2.9 2.2 0.0 0.0 49.61.2040 Flow Reduction 20-40MW Loss 0.0 0.0 0.0 0.4 6.5 17.2 13.0 7.6 2.9 2.2 0.0 0.0 49.91.5 One-unit outage 0.0 0.0 0.0 0.5 8.3 24.0 17.1 9.4 3.9 3.0 0.0 0.0 66.22 1-mm wedgewire screen 0.0 0.0 0.0 0.5 7.9 27.7 26.6 14.8 6.4 4.9 0.0 0.0 88.83 1.5-mm wedgewire screen 0.0 0.0 0.0 0.5 8.3 28.2 26.6 14.8 6.4 4.9 0.0 0.0 89.74 2-mm wedgewire screen 0.0 0.0 0.0 0.5 8.3 28.3 26.5 14.8 6.4 4.9 0.0 0.0 89.85 3-mm wedgewire screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.76 6-mm wedgewire screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.67 9-mm wedgewire screen 0.0 0.0 0.0 0.5 8.3 28.2 26.5 14.8 6.4 4.9 0.0 0.0 89.68 1-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 4.8 8.7 6.9 4.8 1.5 1.0 0.0 0.0 27.98.5 1-mm mesh Ristroph screena0.0 0.0 0.0 0.3 4.4 6.9 3.5 2.3 0.5 0.3 0.0 0.0 18.19 1.5mm mesh Ristroph screen 0.0 0.0 0.0 0.4 5.9 11.0 6.9 4.8 1.5 1.0 0.0 0.0 31.59.5 1.5mm mesh Ristroph screena0.0 0.0 0.0 0.3 5.5 9.2 3.6 2.3 0.5 0.3 0.0 0.0 21.710 2-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.1 12.8 7.0 4.8 1.5 1.0 0.0 0.0 33.510.5 2-mm mesh Ristroph screena0.0 0.0 0.0 0.3 5.8 11.0 3.6 2.3 0.5 0.3 0.0 0.0 23.811 3-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.2 14.1 7.0 4.8 1.5 1.0 0.0 0.0 34.911.5 3-mm mesh Ristroph screena0.0 0.0 0.0 0.3 5.8 12.4 3.8 2.3 0.5 0.3 0.0 0.0 25.512 6-mm mesh Ristroph screen 0.0 0.0 0.0 0.4 6.1 14.3 6.4 4.1 1.3 1.1 0.0 0.0 33.812.5 6-mm mesh Ristroph screena0.0 0.0 0.0 0.3 5.9 12.8 4.1 2.3 0.7 0.7 0.0 0.0 26.913 9-mm mesh Ristroph screen 0.0 0.0 0.0 0.3 5.9 13.6 5.8 3.4 1.3 1.2 0.0 0.0 31.513.5 9-mm mesh Ristroph screena0.0 0.0 0.0 0.3 5.8 12.4 4.0 2.3 1.0 0.9 0.0 0.0 26.814 Aquatic Filter Barrier 0.0 0.0 0.0 0.5 9.9 30.2 25.1 13.8 6.0 4.8 0.0 0.0 90.415 Closed Cycle 0.0 0.0 0.0 0.5 10.6 33.3 27.1 14.8 6.4 4.8 0.0 0.0 97.615.5 Closed Cycleb0.0 0.0 0.0 0.5 10.4 32.8 26.8 14.6 6.3 4.8 0.0 0.0 96.2aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.40Table 18 Monthly and annual total number ofRIS impinged under intake technology alternatives for Indian Point Energy Center.Number ImpingedCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 139,769 130,752 139,769 19,179 19,818 19,171 5,256 5,248 5,078 62,483 60,467 62,483 669,4731 Existing Technology 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,4251.0000 Flow Reduction 0MW Loss 88,291 76,826 82,108 11,291 15,151 18,468 5,124 5,108 4,986 58,345 41,546 43,408 450,6511.1010 Flow Reduction 10MW Loss 88,291 76,826 82,108 10,878 11,890 13,685 4,136 4,174 3,939 44,259 36,306 42,524 419,0151.2020 Flow Reduction 20MW Loss 88,291 76,826 82,108 10,878 11,840 12,670 3,717 3,746 3,554 43,159 36,306 42,524 415,6181.2030 Flow Reduction 20-30MW Loss 88,291 76,826 82,108 10,878 11,840 12,425 3,500 3,540 3,386 43,050 36,306 42,524 414,6721.2040 Flow Reduction 20-40MW Loss 88,291 76,826 82,108 10,878 11,840 12,425 3,482 3,487 3,377 43,050 36,306 42,524 414,5931.5 One-unit outage 73,388 61,527 69,460 8,225 9,409 9,810 3,009 3,017 2,912 45,810 37,460 42,767 366,7932 1-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8283 1.5-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8284 2-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8285 3-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8286 6-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8287 9-mm wedgewire screen 3,530 3,282 3,587 437 492 504 162 174 161 1,984 1,730 1,785 17,8288 1-mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,4259 1.5mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,42510 2-mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,42511 3-mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,42512 6-mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,42513 9-mm mesh Ristroph screen 94,241 79,238 85,543 12,141 15,461 18,478 5,124 5,108 4,986 58,834 44,939 50,333 474,42514 Aquatic Filter Barrier 22,579 19,233 20,798 2,895 3,635 4,279 1,205 1,211 1,175 13,922 10,804 11,980 113,71615 Closed Cycle 3,930 3,643 3,917 497 530 528 163 174 162 2,025 1,823 1,925 19,31715.5 Closed Cycleb6,259 5,710 5,973 755 813 848 241 243 238 2,829 2,427 2,948 29,283aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.41Table 19 Monthly and annualtotal percent reduction in number ofRIS impinged under intake technology alternatives for Indian Point Energy Center.Reduction calculated from regulatory baseline.% Reduction in Number ImpingedCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.01 Existing Technology 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.11.0000 Flow Reduction 0MW Loss 3.7 3.9 4.1 2.0 1.2 0.2 0.2 0.2 0.1 1.0 4.4 4.7 25.51.1010 Flow Reduction 10MW Loss 3.7 3.9 4.1 2.2 2.1 1.4 1.1 1.1 1.2 4.2 5.4 4.8 35.11.2020 Flow Reduction 20MW Loss 3.7 3.9 4.1 2.2 2.1 1.7 1.6 1.5 1.6 4.6 5.4 4.8 37.11.2030 Flow Reduction 20-30MW Loss 3.7 3.9 4.1 2.2 2.1 1.8 1.9 1.8 1.8 4.6 5.4 4.8 37.91.2040 Flow Reduction 20-40MW Loss 3.7 3.9 4.1 2.2 2.1 1.8 1.9 1.9 1.8 4.6 5.4 4.8 38.01.5 One-unit outage 4.8 5.0 5.1 2.6 2.5 2.1 2.9 2.8 2.7 5.6 6.4 6.3 48.72 1-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.43 1.5-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.44 2-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.45 3-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.46 6-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.47 9-mm wedgewire screen 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.1 97.48 1-mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.19 1.5mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.110 2-mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.111 3-mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.112 6-mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.113 9-mm mesh Ristroph screen 3.3 3.7 3.9 1.8 1.1 0.2 0.2 0.2 0.1 0.8 3.6 3.3 22.114 Aquatic Filter Barrier 8.3 7.9 8.4 4.5 4.5 4.1 4.0 4.0 3.8 10.5 10.8 11.0 81.615 Closed Cycle 9.6 9.0 9.6 5.2 5.4 5.2 5.0 5.0 4.8 13.0 12.6 13.0 97.215.5 Closed Cycleb9.4 8.8 9.4 5.1 5.3 5.1 4.9 4.9 4.7 12.8 12.4 12.8 95.8aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.42Table 20 Monthly and annual total impingement losses of RIS under intake technology alternatives for Indian Point Energy Center.Impingement LossCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 139,769 130,752 139,769 19,179 19,818 19,171 5,256 5,248 5,078 62,483 60,467 62,483 669,4731 Existing Technology 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,4141.0000 Flow Reduction 0MW Loss 11,741 10,217 10,916 1,898 2,569 3,150 1,171 1,165 1,140 9,385 6,646 6,917 66,9151.1010 Flow Reduction 10MW Loss 11,741 10,217 10,916 1,831 2,010 2,325 941 950 896 7,086 5,823 6,780 61,5151.2020 Flow Reduction 20MW Loss 11,741 10,217 10,916 1,831 2,002 2,147 841 848 801 6,895 5,823 6,780 60,8411.2030 Flow Reduction 20-30MW Loss 11,741 10,217 10,916 1,831 2,002 2,101 783 793 758 6,874 5,823 6,780 60,6191.2040 Flow Reduction 20-40MW Loss 11,741 10,217 10,916 1,831 2,002 2,101 779 779 755 6,874 5,823 6,780 60,5981.5 One-unit outage 9,740 8,166 9,218 1,334 1,531 1,583 601 604 584 7,107 5,841 6,606 52,9162 1-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5963 1.5-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5964 2-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5965 3-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5966 6-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5967 9-mm wedgewire screen 469 436 476 73 82 84 35 39 34 314 273 281 2,5968 1-mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,4149 1.5mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,41410 2-mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,41411 3-mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,41412 6-mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,41413 9-mm mesh Ristroph screen 12,531 10,537 11,372 2,041 2,623 3,152 1,171 1,165 1,140 9,472 7,198 8,012 70,41414 Aquatic Filter Barrier 3,002 2,558 2,765 486 615 729 274 275 267 2,237 1,727 1,904 16,83915 Closed Cycle 522 484 521 83 89 89 35 39 35 321 290 305 2,81315.5 Closed Cycleb833 759 794 127 138 144 55 55 52 454 391 472 4,275aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.43Table 21 Monthly and annual total percentreduction in impingement losses RIS under intake technology alternatives for IndianPoint Energy Center. Reductioncalculated from regulatory baseline.% Reduction in Impingement LossCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.01 Existing Technology 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.01.0000 Flow Reduction 0MW Loss 9.0 8.5 9.0 4.5 4.4 3.9 3.7 3.7 3.5 9.7 10.4 10.8 80.81.1010 Flow Reduction 10MW Loss 9.0 8.5 9.0 4.5 4.6 4.3 4.0 3.9 3.8 10.6 10.7 10.8 83.71.2020 Flow Reduction 20MW Loss 9.0 8.5 9.0 4.5 4.6 4.3 4.1 4.1 4.0 10.7 10.7 10.8 84.31.2030 Flow Reduction 20-30MW Loss 9.0 8.5 9.0 4.5 4.6 4.4 4.2 4.1 4.0 10.8 10.7 10.8 84.51.2040 Flow Reduction 20-40MW Loss 9.0 8.5 9.0 4.5 4.6 4.4 4.2 4.2 4.0 10.8 10.7 10.8 84.51.5 One-unit outage 9.2 8.6 9.2 4.7 4.8 4.6 4.5 4.5 4.3 11.1 11.0 11.4 87.92 1-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.43 1.5-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.44 2-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.45 3-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.46 6-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.47 9-mm wedgewire screen 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.48 1-mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.09 1.5mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.010 2-mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.011 3-mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.012 6-mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.013 9-mm mesh Ristroph screen 8.9 8.4 9.0 4.4 4.3 3.9 3.7 3.7 3.5 9.6 10.2 10.4 80.014 Aquatic Filter Barrier 9.6 9.0 9.7 5.1 5.2 5.0 4.8 4.8 4.6 12.5 12.3 12.7 95.315 Closed Cycle 9.8 9.2 9.8 5.3 5.5 5.3 5.1 5.1 4.9 13.3 12.9 13.3 99.415.5 Closed Cycleb9.8 9.2 9.8 5.3 5.4 5.3 5.1 5.1 4.9 13.2 12.8 13.2 99.1aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.44Table 22 Monthly and annual total equivalent age 1 impingement losses of RIS under intake technology alternatives for Indian Point Energy Center.Equivalent Age 1 LossesCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 92,716 96,598 115,086 19,524 22,096 26,718 5,625 5,682 5,690 27,740 30,836 35,982 484,2931 Existing Technology 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,9271.0000 Flow Reduction 0MW Loss 7,905 7,645 9,092 1,861 2,806 4,404 1,153 1,166 1,173 3,784 3,083 3,632 47,7041.1010 Flow Reduction 10MW Loss 7,905 7,645 9,092 1,800 2,189 3,234 918 944 909 2,878 2,691 3,557 43,7601.2020 Flow Reduction 20MW Loss 7,905 7,645 9,092 1,800 2,178 2,973 806 830 798 2,809 2,691 3,557 43,0821.2030 Flow Reduction 20-30MW Loss 7,905 7,645 9,092 1,800 2,178 2,905 721 750 732 2,802 2,691 3,557 42,7771.2040 Flow Reduction 20-40MW Loss 7,905 7,645 9,092 1,800 2,178 2,905 714 728 727 2,802 2,691 3,557 42,7441.5 One-unit outage 6,575 6,126 7,693 1,244 1,579 2,040 333 353 364 3,028 2,818 3,635 35,7872 1-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8213 1.5-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8214 2-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8215 3-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8216 6-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8217 9-mm wedgewire screen 316 327 397 70 88 116 31 35 33 129 130 150 1,8218 1-mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,9279 1.5mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,92710 2-mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,92711 3-mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,92712 6-mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,92713 9-mm mesh Ristroph screen 8,438 7,886 9,472 2,002 2,870 4,406 1,153 1,166 1,173 3,815 3,333 4,213 49,92714 Aquatic Filter Barrier 2,022 1,914 2,303 476 673 1,017 267 273 273 903 802 1,003 11,92615 Closed Cycle 352 362 434 82 97 122 31 35 33 132 136 162 1,97715.5 Closed Cycleb561 568 661 127 152 201 52 52 53 184 180 245 3,035aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.45Table 23 Monthly and annualtotal percent reduction inequivalent age 1 losses of impingedRIS under intake technology alternatives for Indian Point EnergyCenter. Reduction calculated from regulatory baseline.% Reduction in Equivalent Age 1 LossesCase Alternative Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total0 Regulatory Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.01 Existing Technology 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.21.0000 Flow Reduction 0MW Loss 8.8 9.6 12.0 6.7 7.4 8.5 4.0 4.2 4.4 3.9 4.7 6.5 80.71.1010 Flow Reduction 10MW Loss 8.8 9.6 12.0 6.7 7.9 9.7 4.3 4.4 4.7 4.4 5.0 6.5 84.01.2020 Flow Reduction 20MW Loss 8.8 9.6 12.0 6.7 7.9 9.9 4.4 4.5 4.8 4.4 5.0 6.5 84.71.2030 Flow Reduction 20-30MW Loss 8.8 9.6 12.0 6.7 7.9 10.0 4.5 4.6 4.9 4.4 5.0 6.5 85.01.2040 Flow Reduction 20-40MW Loss 8.8 9.6 12.0 6.7 7.9 10.0 4.5 4.7 4.9 4.4 5.0 6.5 85.01.5 One-unit outage 9.0 9.8 12.2 7.6 8.8 11.3 5.2 5.1 5.6 4.4 5.1 6.7 90.92 1-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.93 1.5-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.94 2-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.95 3-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.96 6-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.97 9-mm wedgewire screen 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.98 1-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.29 1.5mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.210 2-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.211 3-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.212 6-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.213 9-mm mesh Ristroph screen 8.7 9.6 12.0 6.6 7.4 8.5 4.0 4.2 4.4 3.8 4.6 6.3 80.214 Aquatic Filter Barrier 9.4 10.3 12.9 8.0 9.5 11.7 5.3 5.5 5.7 4.9 5.5 7.6 96.115 Closed Cycle 9.6 10.5 13.1 8.2 10.0 12.7 5.5 5.7 6.0 5.1 5.7 7.8 99.815.5 Closed Cycleb9.6 10.5 13.1 8.2 9.9 12.6 5.5 5.7 6.0 5.0 5.7 7.7 99.5aLower bound including latent impingement survival;,bAssumes maximum service water useASAAnalysis & Communication, Inc.46Table 24 Average annual RIS equivalent age 1 loss (millions) lostyield (kg), and production forgone (kg) due to entrainment and impingement forintake technology alternativesfor Indian Point Energy Center.Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp TotalRegulatory Baseline0 Bay anchovy 2.332 0.014 2.346 0 0 0 5,628 2 5,6300 American shad 0.000 0.000 0.000 14 9 23 368 38 4050 Striped bass 0.571 0.048 0.619 213,460 25,942 239,402 660,935 50,960 711,8950 Atlantic tomcod 0.046 0.002 0.047 0 0 0 12,656 47 12,7040 White perch 0.279 0.3990.678 153 322 475 12,301 13,048 25,3490 Alosa sp 0.042 0.021 0.062 135 32 167 8,318 621 8,9390 Total 3.270 0.484 3.754 213,76226,306 240,068 700,206 64,716 764,922Alternative Baseline0.5 Bay anchovy 2.332 0.484 2.817 0 26,306 26,306 5,628 64,716 70,3440.5 American shad 0.000 0.003 0.003 14 13 27 368 237 6050.5 Striped bass 0.247 0.000 0.247102,547 1 102,549 285,377 25 285,4030.5 Atlantic tomcod 0.0420.001 0.043 0 0 0 10,510 0 10,5100.5 White perch 0.171 0.0030.174 97 1,526 1,623 7,548 2,997 10,5460.5 Alosa sp 0.042 0.402 0.444 135 325 459 8,318 13,059 21,3770.5 Total 2.834 0.894 3.728 102,793 28,171 130,964 317,749 81,035 398,785Existing Technology1 Bay anchovy 2.223 0.000 2.223 0 0 0 5,373 7 5,3801 American shad 0.000 0.039 0.039 12 32 44 340 1,277 1,6161 Striped bass 0.214 0.003 0.217 88,821 0 88,821 247,082 0 247,0831 Atlantic tomcod 0.011 0.000 0.011 0 3 3 2,963 10 2,9741 White perch 0.151 0.000 0.151 83 1 85 6,649 24 6,6731 Alosa sp 0.039 0.056 0.094 125 3,114 3,239 7,761 7,783 15,5441 Total 2.637 0.098 2.735 89,0423,149 92,191 270,168 9,102 279,270Flow Reduction 0MW Loss1.0000 Bay anchovy 2.220 0.001 2.222 0 0 0 5,369 0 5,3691.0000 American shad 0.000 0.003 0.003 12 1,457 1,469 339 2,859 3,199ASAAnalysis & Communication, Inc.47Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total1.0000 Striped bass 0.189 0.048 0.23677,014 1,503 78,517 217,685 4,345 222,0301.0000 Atlantic tomcod 0.0110.002 0.013 0 10 10 2,938 188 3,1261.0000 White perch 0.1390.002 0.142 76 0 76 6,145 0 6,1451.0000 Alosa sp 0.038 0.038 0.076 125 31 156 7,729 1,244 8,9731.0000 Total 2.597 0.094 2.691 77,227 3,001 80,228 240,205 8,636 248,841Flow Reduction 10MW Loss1.1010 Bay anchovy 1.770 0.000 1.770 0 2 2 4,287 9 4,2951.1010 American shad 0.000 0.000 0.000 10 1 11 263 20 2831.1010 Striped bass 0.224 0.0000.225 90,338 0 90,338 259,234 6 259,2391.1010 Atlantic tomcod 0.0090.035 0.044 0 28 28 2,571 1,137 3,7081.1010 White perch 0.142 0.0440.185 79 1,452 1,531 6,235 4,133 10,3681.1010 Alosa sp 0.030 0.0060.036 96 1,411 1,507 5,952 2,774 8,7261.1010 Total 2.175 0.085 2.260 90,522 2,895 93,417 278,542 8,077 286,619Flow Reduction 20MW Loss1.2020 Bay anchovy 1.589 0.002 1.591 0 10 10 3,844 179 4,0241.2020 American shad 0.000 0.002 0.002 9 0 9 239 0 2391.2020 Striped bass 0.229 0.0010.231 90,633 0 90,633 265,119 0 265,1191.2020 Atlantic tomcod 0.0080.003 0.011 0 1,404 1,404 2,443 2,761 5,2041.2020 White perch 0.1430.000 0.143 79 0 79 6,316 6 6,3211.2020 Alosa sp 0.027 0.0440.071 88 1,455 1,544 5,482 4,160 9,6411.2020 Total 1.997 0.052 2.049 90,809 2,869 93,678 283,443 7,106 290,549Flow Reduction 20-30MW Loss1.2030 Bay anchovy 1.493 0.035 1.527 0 28 28 3,608 1,129 4,7371.2030 American shad 0.000 0.043 0.043 8 1,444 1,453 228 4,103 4,3311.2030 Striped bass 0.227 0.0000.227 88,682 2 88,684 261,962 8 261,9701.2030 Atlantic tomcod 0.008 0.000 0.008 0 1 1 2,394 19 2,4121.2030 White perch 0.1420.001 0.143 77 0 77 6,250 0 6,2501.2030 Alosa sp 0.026 0.004 0.030 85 9 94 5,287 181 5,469ASAAnalysis & Communication, Inc.48Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total1.2030 Total 1.895 0.083 1.978 88,853 1,485 90,337 279,729 5,440 285,169Flow Reduction 20-40MW Loss1.2040 Bay anchovy 1.480 0.0031.482 0 1,402 1,402 3,576 2,757 6,3331.2040 American shad 0.000 0.000 0.000 8 0 8 227 5 2321.2040 Striped bass 0.226 0.002 0.228 88,330 9 88,340 261,118 175 261,2931.2040 Atlantic tomcod 0.008 0.002 0.010 0 0 0 2,389 0 2,3901.2040 White perch 0.1410.000 0.141 77 2 79 6,232 8 6,2401.2040 Alosa sp 0.026 0.0790.105 85 1,469 1,554 5,271 5,220 10,4911.2040 Total 1.881 0.085 1.966 88,501 2,882 91,383 278,814 8,166 286,979One-unit outage1.5 Bay anchovy 1.152 0.000 1.152 0 1 1 2,784 19 2,8031.5 American shad 0.000 0.001 0.001 6 0 6 176 0 1771.5 Striped bass 0.105 0.034 0.13942,467 28 42,494 121,296 1,128 122,4241.5 Atlantic tomcod 0.006 0.043 0.048 0 1,441 1,441 1,576 4,092 5,6681.5 White perch 0.077 0.001 0.078 42 6 48 3,386 106 3,4921.5 Alosa sp 0.020 0.003 0.023 66 1,403 1,469 4,073 2,769 6,8431.5 Total 1.360 0.083 1.442 42,581 2,879 45,460 133,292 8,114 141,4061-mm wedgewire screen2 Bay anchovy 0.145 0.001 0.146 0 0 0 395 0 3962 American shad 0.000 0.000 0.000 0 1 2 11 6 162 Striped bass 0.071 0.002 0.07321,359 1,154 22,513 82,075 2,282 84,3572 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 6 532 White perch 0.081 0.030 0.111 36 24 60 3,629 994 4,6232 Alosa sp 0.005 0.003 0.007 14 6 20 1,105 116 1,2212 Total 0.301 0.036 0.337 21,408 1,186 22,594 87,262 3,404 90,6661.5-mm wedgewire screen3 Bay anchovy 0.148 0.036 0.184 0 1,186 1,186 406 3,404 3,8093 American shad 0.000 0.000 0.000 0 0 1 11 7 18ASAAnalysis & Communication, Inc.49Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total3 Striped bass 0.047 0.000 0.047 14,385 0 14,385 54,238 1 54,2393 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 0 483 White perch 0.078 0.000 0.078 34 59 93 3,460 116 3,5763 Alosa sp 0.005 0.030 0.035 14 24 38 1,145 995 2,1403 Total 0.278 0.066 0.344 14,434 1,270 15,704 59,308 4,522 63,8302-mm wedgewire screen4 Bay anchovy 0.150 0.000 0.150 0 0 0 410 0 4104 American shad 0.000 0.001 0.001 0 1 1 11 48 594 Striped bass 0.043 0.000 0.043 13,360 0 13,360 50,146 0 50,1464 Atlantic tomcod 0.000 0.000 0.000 0 0 0 48 0 494 White perch 0.077 0.000 0.077 34 0 34 3,437 1 3,4384 Alosa sp 0.005 0.002 0.007 14 120 135 1,162 297 1,4584 Total 0.275 0.004 0.279 13,409 122 13,531 55,214 346 55,5603-mm wedgewire screen4 Bay anchovy 0.150 0.000 0.150 0 0 0 412 0 4125 American shad 0.000 0.000 0.000 0 59 59 12 116 1285 Striped bass 0.043 0.002 0.045 13,449 61 13,510 50,344 173 50,5175 Atlantic tomcod 0.000 0.000 0.000 0 0 0 49 7 565 White perch 0.078 0.000 0.078 35 0 35 3,479 0 3,4795 Alosa sp 0.005 0.001 0.007 14 1 16 1,165 49 1,2145 Total 0.277 0.004 0.280 13,499 122 13,620 55,460 346 55,8056-mm wedgewire screen6 Bay anchovy 0.152 0.000 0.152 0 0 0 415 0 4156 American shad 0.000 0.000 0.000 0 0 0 12 1 126 Striped bass 0.044 0.000 0.044 13,654 0 13,654 50,801 0 50,8016 Atlantic tomcod 0.000 0.001 0.002 0 1 1 50 48 996 White perch 0.078 0.002 0.080 35 61 96 3,489 173 3,6626 Alosa sp 0.005 0.000 0.005 14 59 74 1,165 116 1,281ASAAnalysis & Communication, Inc.50Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total6 Total 0.279 0.004 0.282 13,704 121 13,825 55,932 339 56,2729-mm wedgewire screen7 Bay anchovy 0.152 0.000 0.152 0 0 0 415 7 4227 American shad 0.000 0.000 0.000 0 0 0 12 0 127 Striped bass 0.044 0.000 0.044 13,666 0 13,666 50,831 0 50,8317 Atlantic tomcod 0.000 0.000 0.000 0 59 59 51 116 1677 White perch 0.078 0.000 0.078 35 0 35 3,489 0 3,4907 Alosa sp 0.005 0.002 0.007 14 61 75 1,165 174 1,3397 Total 0.279 0.002 0.281 13,716 120 13,836 55,962 298 56,2601-mm mesh Ristroph screen8 Bay anchovy 2.069 0.001 2.071 0 1 1 5,015 48 5,0638 American shad 0.000 0.002 0.002 12 61 73 336 173 5098 Striped bass 0.331 0.000 0.331 122,560 0 122,560 383,052 0 383,0538 Atlantic tomcod 0.010 0.000 0.010 0 0 0 2,888 1 2,8898 White perch 0.207 0.000 0.207 110 0 110 9,138 0 9,1388 Alosa sp 0.039 0.000 0.039 125 0 125 7,748 7 7,7558 Total 2.656 0.004 2.659 122,807 63 122,870 408,177 230 408,4071-mm mesh Ristroph screen*8.5 Bay anchovy 2.278 0.000 2.278 0 59 59 5,499 116 5,6158.5 American shad 0.000 0.000 0.000 13 0 13 357 0 3578.5 Striped bass 0.405 0.000 0.405 158,424 0 158,424 468,593 7 468,6008.5 Atlantic tomcod 0.0210.000 0.021 0 0 0 5,654 0 5,6548.5 White perch 0.231 0.000 0.231 128 0 128 10,154 0 10,1558.5 Alosa sp 0.040 0.003 0.043 129 62 191 7,913 222 8,1358.5 Total 2.975 0.004 2.978 158,694 122 158,815 498,171 346 498,5161.5mm fine-mesh screen9 Bay anchovy 2.072 0.000 2.072 0 0 0 5,022 1 5,0239 American shad 0.000 0.000 0.000 12 0 12 336 0 336ASAAnalysis & Communication, Inc.51Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total9 Striped bass 0.252 0.001 0.254 99,631 1 99,632 291,515 48 291,5649 Atlantic tomcod 0.010 0.002 0.012 0 61 61 2,886 173 3,0599 White perch 0.189 0.003 0.192 102 13 115 8,351 237 8,5889 Alosa sp 0.039 0.000 0.039 125 59 184 7,752 117 7,8699 Total 2.562 0.006 2.568 99,870 134 100,004 315,862 577 316,4381.5mm mesh Ristroph screen*9.5 Bay anchovy 2.278 0.003 2.281 0 0 0 5,499 0 5,4999.5 American shad 0.000 0.000 0.000 13 3 16 357 11 3679.5 Striped bass 0.327 0.003 0.330 135,489 1,526 137,015 377,035 2,997 380,0329.5 Atlantic tomcod 0.0210.000 0.021 0 0 0 5,652 7 5,6599.5 White perch 0.213 0.039 0.252 120 32 152 9,363 1,277 10,6409.5 Alosa sp 0.040 0.005 0.044 129 14 143 7,913 263 8,1779.5 Total 2.878 0.050 2.928 135,751 1,575 137,326 405,819 4,555 410,3742-mm mesh Ristroph screen10 Bay anchovy 2.074 0.050 2.124 0 1,575 1,575 5,029 4,555 9,58410 American shad 0.000 0.003 0.003 12 13 25 336 237 57310 Striped bass 0.225 0.000 0.225 91,561 1 91,562 259,298 25 259,32310 Atlantic tomcod 0.010 0.001 0.012 0 0 0 2,882 0 2,88210 White perch 0.173 0.0030.175 95 1,526 1,621 7,603 2,997 10,60010 Alosa sp 0.039 0.042 0.081 125 34 159 7,757 1,288 9,04510 Total 2.520 0.100 2.620 91,793 3,149 94,943 282,904 9,103 292,0082-mm mesh Ristroph screen*10.5 Bay anchovy 2.278 0.000 2.278 0 0 0 5,499 7 5,50610.5 American shad 0.000 0.039 0.039 13 32 45 357 1,277 1,63310.5 Striped bass 0.299 0.003 0.302 127,402 0 127,402 344,748 0 344,74810.5 Atlantic tomcod 0.0210.000 0.021 0 3 3 5,646 11 5,65710.5 White perch 0.196 0.000 0.196 113 1 114 8,593 25 8,61810.5 Alosa sp 0.040 0.056 0.095 129 3,114 3,243 7,913 7,790 15,703ASAAnalysis & Communication, Inc.52Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total10.5 Total 2.833 0.098 2.932 127,657 3,149 130,806 372,756 9,110 381,8663-mm mesh Ristroph screen11 Bay anchovy 2.081 0.001 2.082 0 0 0 5,045 0 5,04511 American shad 0.000 0.003 0.003 12 1,526 1,539 338 2,997 3,33511 Striped bass 0.212 0.050 0.26287,815 1,575 89,389 244,813 4,555 249,36811 Atlantic tomcod 0.010 0.003 0.013 0 13 13 2,876 237 3,11311 White perch 0.157 0.003 0.160 88 0 88 6,896 0 6,89611 Alosa sp 0.039 0.040 0.078 125 33 158 7,760 1,309 9,06911 Total 2.499 0.100 2.598 88,040 3,147 91,186 267,727 9,100 276,8263-mm mesh Ristroph screen*11.5 Bay anchovy 2.278 0.000 2.278 0 3 3 5,499 11 5,50911.5 American shad 0.000 0.000 0.000 13 1 15 357 25 38211.5 Striped bass 0.286 0.000 0.286 123,348 0 123,348 329,348 7 329,35511.5 Atlantic tomcod 0.0210.039 0.060 0 32 32 5,636 1,277 6,91211.5 White perch 0.177 0.0500.227 104 1,575 1,679 7,774 4,555 12,32911.5 Alosa sp 0.040 0.007 0.047 129 1,526 1,655 7,913 2,998 10,91111.5 Total 2.802 0.097 2.899 123,594 3,137 126,731 356,526 8,873 365,3996-mm mesh Ristroph screen12 Bay anchovy 2.223 0.003 2.226 0 13 13 5,373 237 5,61012 American shad 0.000 0.003 0.003 12 0 12 340 0 34012 Striped bass 0.214 0.001 0.216 88,821 0 88,821 247,082 0 247,08312 Atlantic tomcod 0.011 0.003 0.013 0 1,526 1,526 2,963 2,997 5,96112 White perch 0.151 0.000 0.151 83 0 83 6,649 7 6,65612 Alosa sp 0.039 0.050 0.089 125 1,579 1,704 7,761 4,591 12,35212 Total 2.637 0.061 2.697 89,042 3,118 92,160 270,168 7,834 278,0026-mm mesh Ristroph screen*12.5 Bay anchovy 2.278 0.039 2.317 0 32 32 5,499 1,277 6,77512.5 American shad 0.000 0.050 0.050 13 1,575 1,588 357 4,555 4,912ASAAnalysis & Communication, Inc.53Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total12.5 Striped bass 0.258 0.000 0.258109,384 3 109,387 296,822 11 296,83312.5 Atlantic tomcod 0.0210.000 0.021 0 1 1 5,513 25 5,53812.5 White perch 0.160 0.001 0.162 91 0 91 7,060 0 7,06112.5 Alosa sp 0.040 0.006 0.046 129 13 142 7,913 245 8,15812.5 Total 2.756 0.097 2.853 109,617 1,623 111,240 323,164 6,113 329,2779-mm mesh Ristroph screen13 Bay anchovy 2.254 0.003 2.257 0 1,526 1,526 5,443 2,997 8,44113 American shad 0.000 0.000 0.000 13 0 13 342 7 34913 Striped bass 0.229 0.001 0.230 95,992 3 95,995 264,220 55 264,27513 Atlantic tomcod 0.014 0.001 0.014 0 0 0 4,083 0 4,08313 White perch 0.155 0.000 0.155 86 1 87 6,818 3 6,82113 Alosa sp 0.039 0.091 0.129 125 1,606 1,731 7,765 5,832 13,59713 Total 2.690 0.095 2.785 96,217 3,136 99,353 288,671 8,894 297,5669-mm mesh Ristroph screen*13.5 Bay anchovy 2.278 0.000 2.278 0 0 0 5,499 6 5,50513.5 American shad 0.000 0.000 0.000 13 0 13 357 0 35713.5 Striped bass 0.235 0.009 0.244 98,858 8 98,866 271,104 306 271,41013.5 Atlantic tomcod 0.0220.012 0.034 0 379 379 5,957 1,093 7,05013.5 White perch 0.159 0.000 0.159 90 0 90 7,002 8 7,01013.5 Alosa sp 0.040 0.001 0.040 129 368 497 7,913 726 8,63913.5 Total 2.734 0.023 2.756 99,090 755 99,845 297,832 2,139 299,971Aquatic Filter Barrier14 Bay anchovy 0.405 0.000 0.405 0 0 0 989 0 98914 American shad 0.000 0.000 0.000 1 0 1 37 0 3714 Striped bass 0.034 0.000 0.034 13,570 65 13,635 39,598 129 39,72714 Atlantic tomcod 0.001 0.000 0.001 0 0 0 173 0 17414 White perch 0.030 0.002 0.031 16 1 17 1,310 53 1,36214 Alosa sp 0.005 0.000 0.005 14 0 14 1,103 9 1,112ASAAnalysis & Communication, Inc.54Case TaxonEquivalent Age 1(millions) Lost Yield (kg)Production Forgone (kg)Ent Imp Total Ent Imp Total Ent Imp Total14 Total 0.474 0.002 0.476 13,600 67 13,667 43,210 190 43,401Closed Cycle15 Bay anchovy 0.071 0.002 0.073 0 67 67 171 190 36215 American shad 0.000 0.000 0.000 0 1 1 10 13 2315 Striped bass 0.015 0.000 0.015 5,355 0 5,356 16,974 1 16,97515 Atlantic tomcod 0.000 0.000 0.000 0 0 0 120 0 12015 White perch 0.008 0.000 0.008 4 101 105 329 199 52815 Alosa sp 0.001 0.002 0.003 4 1 5 239 53 29215 Total 0.095 0.004 0.099 5,364 171 5,534 17,843 457 18,300Closed Cycle**15.5 Bay anchovy 0.105 0.000 0.105 0 0 0 253 0 25315.5 American shad 0.000 0.002 0.002 1 2 3 16 80 9615.5 Striped bass 0.023 0.0000.023 8,254 2 8,256 26,307 0 26,30715.5 Atlantic tomcod 0.001 0.000 0.001 0 38 38 183 0 18315.5 White perch 0.012 0.000 0.012 6 128 134 517 0 51715.5 Alosa sp 0.002 0.003 0.005 6 696 702 370 494 86315.5 Total 0.141 0.006 0.147 8,267 866 9,133 27,646 574 28,219* Includes latent mortality on Ristroph screens** Assumes full use of service waterASAAnalysis & Communication, Inc.55Table 25 Lost yield(kg) due to entrainment and impingement and combined for intake alternatives at IPEC. Direct lost yield represents commercialand recreational catch of exploited species.Converted lost yield calculated from production forgone of all RIS except stripedbass converted to stripedbass yield by EPA Phase III rule methodology.Case Alternative BaselineEntrainment Impingement CombinedDirect Converted TotalIncrementalReductionDirect Converted TotalIncrementalReductionTotalIncrementalReduction0 Regulatory Baseline 213,762 1,268 215,030 0 26,306 700 27,006 0 242,037 00.5 Alternative Baseline 102,793 1,046 103,838 111,192 26,306 700 27,006 0 130,845 111,1921 Current technology 6x12mm 89,042 746 89,788 125,242 1,575 79 1,65425,352 91,442 150,5951.0001 Flow Reduction 0MW Loss 77,227 72777,954 11,834 1,503 761,579 75 79,533 11,9091.1010 Flow Reduction 10MW Loss 90,522624 91,146 -1,358 1,45269 1,522 132 92,667 -1,2251.2020 Flow Reduction 20MW Loss 90,809592 91,400 -1,612 1,44468 1,513 141 92,913 -1,4711.2030 Flow Reduction 20-30MW Loss 88,853 574 89,427 361 1,442 68 1,510 144 90,936 5061.2040 Flow Reduction 20-40MW Loss 88,501 572 89,072 716 1,441 68 1,509 145 90,581 8611.5 One-unit outage 42,581 387 42,968 46,820 1,18657 1,243 411 44,211 47,2312 1-mm wedgewire screen 21,408 168 21,576 68,212 61 3 64 1,590 21,640 69,8023 1.5-mm wedgewire screen 14,434 164 14,598 75,190 61 3 64 1,590 14,662 76,7804 2-mm wedgewire screen 13,409 164 13,573 76,215 61 3 64 1,590 13,636 77,8065 3-mm wedgewire screen 13,499 165 13,664 76,124 61 3 64 1,590 13,728 77,7146 6-mm wedgewire screen 13,704 166 13,869 75,919 61 3 64 1,590 13,933 77,5097 9-mm wedgewire screen 13,716 166 13,882 75,906 61 3 64 1,590 13,945 77,4978 1-mm fine-mesh screen 122,807 811 123,618 -33,830 1,575 79 1,654 0 125,272 -33,8308.5 1-mm fine-mesh screen_LB 158,694 955 159,649 -69,861 1,575 79 1,654 0 161,303 -69,8619 1.5mm fine-mesh screen 99,870 786 100,656 -10,868 1,575 79 1,654 0 102,310 -10,8689.5 1.5mm fine-mesh screen_LB 135,751 930 136,681 -46,893 1,575 79 1,654 0 138,335 -46,89310 2-mm fine-mesh screen 91,793 762 92,556 -2,768 1,575 791,654 0 94,210 -2,76810.5 2-mm fine-mesh screen_LB 127,657 905 128,561 -38,773 1,575 79 1,654 0 130,215 -38,77311 3-mm fine-mesh screen 88,040 740 88,780 1,008 1,575 791,654 0 90,434 1,00811.5 3-mm fine-mesh screen_LB 123,594 878 124,472 -34,684 1,575 79 1,654 0 126,126 -34,68412 6-mm fine-mesh screen 89,042746 89,788 0 1,57579 1,654 0 91,442 012.5 6-mm fine-mesh screen_LB 109,617 851 110,468 -20,680 1,575 79 1,654 0 112,122 -20,68013 9-mm fine-mesh screen 96,217 790 97,006 -7,218 1,575 791,654 0 98,660 -7,21813.5 9-mm fine-mesh screen_LB 99,090 863 99,953 -10,165 1,575 791,654 0 101,607 -10,16514 Aquatic Filter Barrier 13,600 11713,717 76,071 379 19398 1,256 14,115 77,32715 Closed Cycle 5,364 28 5,39284,396 67 3 70 1,584 5,462 85,98015.5 Closed Cycle - Max SW 8,267 438,310 81,478 104 5109 1,545 8,420 83,022ASAAnalysis & Communication, Inc.56Table 26 Cumulative end of life estimates of undiscounted entrainment and impingement total losses, equivalent age 1 losses, and lost yield for RIS atIPEC units 2 and 3, 2013through 2035. Percent reduction relative to Baseline value. Savingsratio relative to Closed Cycle.Percent reduction andsavings ratio averaged over species.UndiscountedScenarioYearTechnologyOperationalTotalLosses(M)EquivalentAge1Losses(M)LostYield(kg)Number%ReductionSavingsRatioNumber%ReductionSavingsRatioNumber%ReductionSavingsRatioUnit2Unit3

EntrainmentRegulatoryBaseline26,931071.91404,729,1890ExistingTechnologies2013201314,18334.87057.96934.3601,972,41333.5301‐mmwedgewirescreen201320157,26476.581.938.92687.252.54540,07587.522.591.5‐mmwedgewirescreen201320156,25577.752.098.42488.032.61393,53588.142.642‐mmwedgewirescreen201320156,12777.852.118.37188.112.62372,00888.22.653‐mmwedgewirescreen201320156,13677.752.18.40888.032.62373,92588.112.646‐mmwedgewirescreen201320156,13777.742.18.44887.992.61378,23788.072.649‐mmwedgewirescreen201320156,13777.742.18.44987.992.61378,49388.062.64ClosedCycle202920299,88554.85140.154.5511,377,75853.981

ImpingementRegulatoryBaseline14.728010.6540594,1690ExistingTechnologies201320131.54982.1101.09880.98036,39181.0201‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.991.5‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.992‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.993‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.996‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.999‐mmwedgewirescreen201320150.12598.622.990.08898.562.992,99198.552.99ClosedCycle202920291.07387.6210.76186.85125,23486.881ASAAnalysis & Communication, Inc.57Table 27 Cumulative end of life estimates of discounted (3% per year) entrainmentand impingement total losses, equivalent age1 losses, and lost yieldfor RIS at IPEC units 2 and 3, 2013 through 2035. Percent reduction relative to Baseline value.Savings ratio relative to Closed Cycle. Percentreduction and savings ratio averaged over species.Discounted3%peryearScenarioYearTechnologyOperationalTotalLosses(M)EquivalentAge1Losses(M)LostYield(kg)Number%ReductionSavingsRatioNumber%ReductionSavingsRatioNumber%ReductionSavingsRatioUnit2Unit3

EntrainmentRegulatoryBaseline19,919053.18903,497,7650ExistingTechnologies2013201310,49434.84042.88134.3401,459,31833.5101‐mmwedgewirescreen201320155,45675.912.437.17686.413.2416,42186.683.271.5‐mmwedgewirescreen201320154,72177.072.636.8187.193.29309,59087.283.332‐mmwedgewirescreen201320154,62777.172.656.77187.273.3293,90687.343.343‐mmwedgewirescreen201320154,63477.072.656.79887.193.3295,30187.253.336‐mmwedgewirescreen201320154,63577.062.656.82787.153.29298,43987.213.339‐mmwedgewirescreen201320154,63577.062.656.82887.153.29298,62687.213.33ClosedCycle202920298,00750.47132.54750.1311,115,28649.51

ImpingementRegulatoryBaseline10.89207.880439,4210ExistingTechnologies201320131.14682.1100.81280.98026,91381.0201‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.771.5‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.772‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.773‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.776‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.779‐mmwedgewirescreen201320150.10998.363.770.07798.293.772,60298.283.77ClosedCycle202920290.8786.4210.61785.57120,46185.61ASAAnalysis & Communication, Inc.58Figure 10 Result of sensitivity analysis for % reduction of equivalent age 1 losses for wedgewirescreen slot widths of 1, 3,6, and 9 mm under differentassumptions about avoidance and exclusion survival.ASAAnalysis & Communication, Inc.59Table 28 Annual equivalent age 1 entrainment losses (millions) for RIS with existing technology at IPEC units 2 and 3.2001 2002 2003 2004 2005 2006 2007Bay anchovy 0.8289 1.9145 1.7301 2.1453 2.5029 1.7236 4.715American shad 0.0002 0.0001 0.0001 0 0 0 0Striped bass 0.2952 0.1081 0.5614 0.1542 0.1478 0.0763 0.1555Atlantic tomcod 0.0295 0.0016 0.0069 0.0186 0.0118 0.0033 0.002White perch 0.0576 0.2415 0.3472 0.134 0.0897 0.1307 0.0541Alosa sp 0.0359 0.0581 0.0869 0.0191 0.0327 0.0121 0.0256

### ASA Analysis & Communication, Inc.



### 60 

## References

ASA. 2009. 2007 Year Class Report for the H udson River Estuary Monitoring Program. Report prepared for Dynegy Roseton L.L.C., Entergy Nuclear Indian Point 2 L.L.C., Entergy Nuclear Indian Point 3 L. L.C., and Mirant Bowline L.L.C.

Beamish, F.W.H. 1978. Swimming capaci ty. Fish Physiology, Vol. VII:101-187.

EA. 1981. Indian Point Genera tion Station entrainment surv ival and related studies. 1979 annual report prepared for Consolidated Edison Company of New York, Inc. and Power Authority of the State of New York.

EA. 1982. Indian Point Genera tion Station entrainment surv ival and related studies. 1980 annual report prepared for Consolidated Edison Company of New York, Inc. and Power Authority of the State of New York.

EA. 1984. Indian Point Generating Sta tion entrainment abundance and outage evaluation. 1983 annual report to Consolidat ed Edison Company of New York and New York Power Authority. Ecol ogical Analysts. New York

EA. 1985. Indian Point Generating Sta tion entrainment abundance and outage evaluation. 1984 annual report to Consolidat ed Edison Company of New York and New York Power Authority. Ecol ogical Analysts. New York.

EA. 1989. Indian Point Generating Station 1988 entrainment survival study. Report to Consolidated Edison Company of New York and New York Power Authority. EA Engineering, Science and Technology, Inc. New York.

EPRI (Electric Power Research Institute) . 2003. Laboratory eval uation of wedgewire screens for protecting early life stages of fi sh at cooling water intakes. Report 1005339.

EPRI. 2004. Extrapolating Impingement and En trainment Losses to Equivalent Adults and Production Foregone. Report 1008471.

Fletcher, R. I. 1990. Flow dynamics and fi sh recovery experiments: water intake systems. Transactions of the Amer ican Fisheries Society. 119:393-415.

Heuer, J.H., and D.A. Tomljanovich. 1978. A study on the protection of fish larvae at water intakes using wedge-wire scre ening. TVA Tech. Note B26. 60 p.

Horst, T. J. 1975. The assessment of impact due to entrainment of ichthyoplankton. P.

107-118 in S. B. Saila (ed.) Fisheries and energy production. D. C. Heath and Company, Lexington, MA. 300p.

Jinks S.M., G. Lauer, and M. Loftus. 1981. Advances in Techniques for Assessment of Ichthyoplankton Entrainment Survival. Pp 91- 110 in: Issues Associ ated with Impact Assessment: Proceedings of the Fifth National Workshop on Entrainment and Impingement (L. Jensen, ed.) Ec ological Analysts. Sparks, MD.

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McGroddy, P. M., and R. L. Wyman. 1977. E fficiency of nets and a new device for sampling living fish larvae. Journal Fisheries Research Board Canada 34: 571-574.

Muessig, P. H., J. R. Young, D. S. Vaughan, and B. A. Smith. 1988. Advances in field and analytical methods for estimating entr ainment mortality factors. Pages 124-132 in Barnthouse, L. W., R. J. Klauda, D. S. Va ughan, and R. L. Kendall, editors. Science law and Hudson River power plants. American Fisheries Society, Monograph 4. Bethesda, Maryland.

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to Central Hudson Gas & Electric Cor poration.. Normandeau Associates, New Hampshire.

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USEPA 2006. Regional Benefits Analysis for the Final Section 316(b) Phase III Rule for Existing Facilities. EPA-821-R-04-007. http://www.epa.gov/waterscience/316b/ phase3/ph3docs/p3-rb a-final-part1.pdf

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### 62 Weisberg, S.B., W.H. Burton, F. Jacobs, and E.A. Ross. 1987. Reductions in ichthyoplankton entrainment with fine-mesh, wedge-wire screens. N. Amer. J. Fish. Manag. 7:386-393.

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# Appendix B

B IOLOGICAL 

# E VALUATION OF 

# I NTAKE 

# S CREEN


# A LTERNATIVES TO 

# R EDUCE 

# I MPINGEMENT AND 

# E NTRAINMENT 

# L OSSES AT 

# I NDIAN 

# P OINT 

# E NERGY 

# C ENTER

Prepared for ENTERGY SERVICES, INC. 1340 Echelon Parkway Jackson, Mississippi 39213

Prepared by NORMANDEAU ASSOCIATES, INC.

25 Nashua Road Bedford, New Hampshire 03110

R-19998.001

February 2010IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 ii Normandeau Associates, Inc. 

# Table of Contents

Page

1.0 INTRODUCTION .................................................................................................................. ................ 1

2.0 MESH SELEC TIVITY .............................................................................................................. ........... 1

2.1 P HYSICAL E XCLUSION F ACTORS .................................................................................................... 2

2.1.1 Larvae ........................................................................................................................ ...... 2

2.1.2 Eggs .......................................................................................................................... ....... 5

2.2 W EDGEWIRE A VOIDANCE F ACTORS ............................................................................................... 5

2.3 R EFERENCES

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

3.0 IMPINGEMENT MORTALITY OF SMALL FISH ON FINE-MESH INTAKE

SCREENS AT DANSKAMMER POINT STATION ....................................................................... 19

3.1 A PPROACH

.............................................................................................................................. ..... 19

3.2 R ESULTS

.............................................................................................................................. ........ 21

3.2.1 Bay Anchovy ................................................................................................................. 2 1

3.2.2 Striped Bass .................................................................................................................. . 22

3.2.3 White Perch ................................................................................................................... 22

3.2.4 Clupeids ...................................................................................................................... ... 23

3.2.5 All Other Fish Taxa ....................................................................................................... 23

3.2.6 All Fish Taxa Combined ................................................................................................ 24

3.3 R EFERENCES

.............................................................................................................................. .. 25

4.0 LOVETT GUNDERBOOM EFFECTIVENESS AND MESH SELECTIVITY

ANALYSIS ...................................................................................................................... ..................... 36

4.1 A PPROACH

.............................................................................................................................. ..... 36

4.2 R ESULTS

.............................................................................................................................. ........ 37

4.3 R EFERENCES

.............................................................................................................................. .. 39

5.0 VERIFICATION OF COMPUTER CODE ...................................................................................... 42

5.1 A PPROACH

.............................................................................................................................. ..... 42

5.2 P ROGRAM 1 H

. SAS (22S EP 09 R EVISION ) ....................................................................................... 43

5.2.1 Entrainment Section 1—Estimate River Standing Crops for 1983-1987 and

2000-2007 ..................................................................................................................... . 43

5.2.2 Entrainment Section 2—Estimate En trainment Densities for 1983- 1987 ...................... 44

5.2.3 Entrainment Section 3—Relationship of En trainment Density to Standing Crop ......... 45

5.2.4 Entrainment Section 4—Predict 20 00-2007 Entrainm ent Densities .............................. 45

5.2.5 Entrainment Section 5—Estimate 2000-2007 Entrainment Length-Frequencies .......... 45

5.2.6 Entrainment Section 6—Crea te Flow Data Sets ............................................................ 46

5.2.7 Entrainment Section 7—Survival an d Exclusion Parameter Values.............................. 46

5.2.8 Entrainment Section 8—Calculate Numbers and Losse s by Case ................................. 46

5.2.9 Entrainment Section 9—Calculate Eq uivalent Life Stage Values ................................. 48

5.2.10 Entrainment Section 10—Convert Entrai nment Loss to Equivalent Loss ..................... 49

5.2.11 Entrainment Section 11—Pro duce Output Tables ......................................................... 50

5.2.12 Impingement Sections 1 and 2—River Abundance in 1983-1987 and 2000- 2007; Correlation of Standing Crops ............................................................................. 51

5.2.13 Impingement Section 3—Merge Abundance Ratios with Densities and Estimate Impingement .................................................................................................................. 51

5.2.14 Impingement Section 4—Conver t to Equivalent Losses ............................................... 52

5.2.15 Outstanding Cons ideration ............................................................................................ 52

5.3 P ROGRAM IP-C OLL E FF 1981

- 1990. SAS (22S EP 09 R EVISION ) ..................................................... 52IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 iii Normandeau Associates, Inc. 5.3.1 Step 1—Calculate Collection E fficiency Coe fficients ................................................... 52

5.4 P ROGRAM IP-S TRATA I MP B Y L ENGTH C LASS 1981

- 1990. SAS (22S EP 09 R EVISION ) ..................... 53

5.4.1 Step 2—Join Catch Data to the Collec tion Efficiency Data from Step 1 ....................... 53

5.4.2 Step 3—Calculate St rata Numbers ................................................................................ 53

5.4.3 Step 4—Bring in Plan t Operation Data ......................................................................... 54

5.5 V ERIFICATION OF S ENSITIVITY A NALYSIS AND C UMULATIVE A NALYSIS .................................... 54IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 iv Normandeau Associates, Inc. 

# List of Figures

Page

Figure 2-1. Observed wedgewire avoidance factors by le ngth, species, and slot width, with a generalized relationship between larval le ngth and wedgewire avoidance factor. ........... 11

Figure 3-1. Adjusted (for differences in volume samp led) length frequenc y distributions for fish impinged on the 3.2 mm fine me sh conventional traveling screens at

Danskammer Unit 3 and the 9.5 mm stan dard mesh conventional traveling screens at Unit 4, 1 May through 23 August 1988. ............................................................ 26

Figure 3-2. Relative (percent) adjusted length freque ncy distributions for fish impinged on

the 3.2 mm fine mesh conventional trav eling screens at Danskammer Unit 3 and

the 9.5 mm standard mesh conventiona l traveling screens at Unit 4, 1 May through 23 Augus t 1988. ..................................................................................................... 2 7

Figure 3-3. Cumulative relative length frequency distributions for fish impinged on the 3.2 mm fine mesh conventional traveling sc reens at Danskammer Unit 3 and the 9.5

mm standard mesh conventional trave ling screens at Unit 4, 1 May through 23 August 1988. .................................................................................................................. ..... 28

Figure 4-1. Length Frequency (one mm length groups) of all larval fish taxa combined collected by simultaneous pairs of samples taken inside (test) or outside (control) of a deployed AFB at Lovett Station on the Hudson River, New York, from May through October 2004, 2005 and 2007 (2006 length data not available). ......................... 40IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 v Normandeau Associates, Inc. 

# List of Tables

Page

Table 2-1. Physical exclusion factors for Atlantic tomcod. ................................................................. 12

Table 2-2. Physical exclusion factors for striped bass. ........................................................................ 13

Table 2-3. Physical exclusion factor s for white perch. ........................................................................ 14

Table 2-4. Physical exclusion factors for rive r herring and American shad. ...................................... 15

Table 2-5. Physical exclusion factors for bay anchovy. ...................................................................... 16

Table 2-6. Physical exclusion factors for eggs. .................................................................................... 17

Table 2-7. Data used to fit a generalized curve for estimating wedgewire avoidance as a function of length. ........................................................................................................... .... 18

Table 3-1. Results of the Danskammer fine mesh traveling screen impingement survival study, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ............................................................................................................... ..... 29

Table 3-2. Number and percent of fish collected in Length Class 1 (representing the fraction

of small fish retained on the fine mesh screen of Unit 3 but not on the standard mesh screen of Unit 4) and Length Class 2 (representing the frac tion of large fish

retained on both the fine mesh and stan dard mesh screens) for which length was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ............................................................................. 30

Table 3-3. Number and percent of fish collected in Length Class 1 (representing the fraction

of small fish retained on the fine mesh screen of Unit 3 but not on the standard mesh screen of Unit 4) that contributed to the combined impingement collection from both Units, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ............................................................................. 31

Table 3-4. Number of fish and percent impingement survival for all fish for which length was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ............................................................................. 32

Table 3-5. Number of fish and percent imping ement survival for Length Class 1 representing the fraction of sm all fish retained on the fine mesh screen (Unit 3) but not on the standard mesh screen (U nit 4) for which le ngth was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ...................................................................................................... 3 3

Table 3-6. Number of fish and percent imping ement survival for Length Class 2 representing the fraction of large fish reta ined on both the fine mesh and standard mesh screens for which length was determin ed, adjusted for differences in intake flow between Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh). ..................................................................... 34

Table 3-7. Comparison of 8-hour survival (percent alive) and the tota l number of fish collected (N Total) for common fish im pinged on the Danskammer Point StationIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 vi Normandeau Associates, Inc. fine mesh conventional traveling screens at Unit 3 (3.2 mm), the standard mesh traveling screens at Unit 4 (9.5 mm) tested between 1 May and 23 August 1988, and the Ristroph screen vers ion 2 installed and tested at Indian Point Unit 2, screen well 26 during 16 Septem ber through 24 October 1986. ........................................ 35

Table 4-1. Summary of annual percent exclusion effec tiveness for fish larvae collected by simultaneous pairs of samples taken insi de and outside of a deployed AFB at Lovett Station on the Hudson River, New York, from May through October 2004, 2005, 2006 and 2007. ................................................................................................ 41IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 1 Normandeau Associates, Inc. 

## 1.0 I NTRODUCTION

Entergy Nuclear Indian Point 2, LLC and Entergy Nu clear Indian Point 3, LLC (“Entergy”) retained Normandeau Associates, Inc. (“Normandeau”) to provide biological support for its assessment of potential alternative intake technologies for the I ndian Point Entergy Center (“IPEC”) nuclear powered electric generating stations 2 and 3 (individ ually, “Unit 2” and “Unit 3,” and collectively, the “Stations”). This evaluation was undertaken as pa rt of Entergy’s alternative technology assessment performed pursuant to the New York State Depart ment of Environmental Conservation (“NYSDEC”) Assistant Commissioner’s August 13, 2008 Interim Decision. 1 Normandeau’s contributions to the alternatives analysis presented in this report are an evaluation of the potential for narrow slot width wedgewire screens or fine-mesh intake screens to reduce rates of entrainment (Section 2.0), analysis of impingement mortality of small fish on fine-m esh intake screens (Section 3.0), analysis of the potential for a fine-mesh aquatic filter barrier (“AFB”) to reduce rates of entrainment and impingement (Section 4.0), and qua lity control verification of the computer programs projecting entrainment and impingement losses under the various alternatives (Section 5.0). 2



## 2.0 M ESH 

## S ELECTIVITY

The IPEC analysis uses Normandeau’s estimates of the exclusion potential of various mesh sizes as part of the evaluation of the biological effec tiveness of wedgewire screens and fine-mesh intake screens. The exclusion estimates represent two di stinct processes. One process, which applies to both wedgewire screens and fine mesh intake screens, is the physical exclusion of eggs and larvae by withdrawing cooling water through openings that are too small for the eggs and larvae to pass through. This process is represented by the “phy sical exclusion factor,” which represents the proportion of the organisms that would have been entrained through the existing screens that are excluded from the facility’s cooling water by the finer mesh alternative. The purpose of the physical

exclusion factor is to enable estimation of the reduced number that would be entrained through the fine-mesh alternative technology:

E f

= ( E ) ( 1–P
e ) (Equation 1)

where E f = number entrained through fine-mesh intake screens,

E = number entrained through existing intake screens, and

P e = proportion of the currently entrained organisms that would be excluded by a finer mesh alternative screening technology (physical exclusion factor).

The second process, which applies only to wedgewire scr eens, is the ability of larvae to actively avoid being entrained through wedgewire screens. Th is is represented by the “wedgewire avoidance factor,” which is the proportion of organisms of a size vulnerable to entrainment that actively avoid

1 As noted in Biological Effectiveness of Alternativ e Intake Technologies for Indian Point Units 2 and 3 (Barnthouse et al. 2010), a 2003 draft permit issued by NYSDEC Staff proposed modifications to the cooling water intake structure at the Stations. These modifications include possible construction and operation of two large counter-flow, forced draft, plume abated hybrid cooling towers.

2 This report supports the report en titled “Biological Effectiveness of Altern ative Intake Technologies for Indian Point Units 2 and 3” prepared by Lawrence W. Barnthou se of LWB Environmental Services, Inc., Douglas G. Heimbuch of AKRF, Inc., Mark T. Mattson of Normand eau Associates, Inc., and John R. Young of ASA Analysis & Communication, Inc.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 2 Normandeau Associates, Inc. being entrained. The hydrodynamic transport of organisms out of the withdrawal zone of the wedgewire screens by means of water currents (“sweeping flows”) is not estimated separately in this evaluation, but is included as part of the wedgewire avoidance factor. The purpose of the wedgewire avoidance factor is to be used together with the physical exclusion factor to enable estimation of the reduced number that would be entrained through wedgewire screens:

E w = ( E ) ( 1–P
a ) ( 1–P
e ) (Equation 2)

where E
w = number entrained through wedgewire screens,

E = number entrained through existing intake screens,

P a = proportion avoiding entrainment (wedgewire avoidance factor), and

P e = proportion excluded (physical exclusion factor).

The following narrative describes th e rationale, assumptions, data, and procedures used to estimate the physical exclusion factors (Section 2.1) and wedgewire avoidance factors (Section 2.2) for the IPEC alternatives analysis.



### 2.1 P HYSICAL 

### E XCLUSION 

### F ACTORS

2.1.1 Larvae

Entrainability of the early life stages of fish depe nds on what sizes of them can fit through the mesh openings. Estimates of the physical exclusion factor P
e for larvae are based on their “limiting dimension,” reflecting the fundamental assumption that a small fish attempting to avoid the screen will typically orient itself to swim directly away fro m the screen surface, so that if it is entrained it is drawn tail first through the mesh opening by the in take current. Thus the limiting dimension is not the length of the fish, but its thickness, which could be either the head or the thickest or deepest part of the body. If either the greatest width or greatest depth of the fish exceeds the width of the mesh opening, the fish will usually not be entrained. Greatest body depth (“GBD”) was selected to represent the limiting dimension for this evaluation because it is usually the most available measurement other than total length. Although GB D might in some cases be slightly smaller than head capsule width, head capsule depth, or greatest body width, the difference would be very small, and GBD is still a reasonable representation of the limiting dimension of the larva.

Estimates of P
e based on GBD can overestimate the actual fraction excluded at the upper end of the entrainment/impingement transition size range if some larvae are compressed and forced through the screen, if some pass through holes in the screen, if so me pass through gaps beside the screen, or if some are carried over the top of the screen and fall off behind the screen during screen rotation and washing. Estimates of P
e based on GBD can underestimate the fraction excluded at the lower end of the entrainment/impingement transition size range, because of fish that are small enough to fit through the screen tail first but are instead impi nged sideways across the screen mesh. No attempt was made to adjust for these biases because there is insufficient information available on which to base such adjustments.

P e varies depending on the species, the size of the individual, and the width of the mesh openings. The evaluation focused on selected species designate d as Representative Important Species for IPEC: Atlantic tomcod, striped bass, white perch, Amer ican shad, alewife, blueback herring, and bay anchovy (P
e estimates were not attempted for spottail sh iner because of insufficient data). MeshIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 3 Normandeau Associates, Inc. opening widths evaluated were 1.0 mm, 1.5 mm, 2.0 mm, 3.0 mm, 6.0 mm, and 9.0 mm. Estimates

of P
e were made for 1-mm intervals from 2 mm thr ough 70 mm. Each length class is expressed as an integer length that represents all lengths that round to that value (e.g., for lengths recorded to the nearest 0.1 mm, the 2 mm length class includes all lengths from 1.5 mm through 2.4 mm).

Estimates of P
e were primarily based on data from IPEC entrainment samples collected in 1986, which provided GBD and total length measurements to the nearest 0.1 mm for over 50,000 larvae (Normandeau 1987). Data for alewife and blue back herring were pooled with the data for unidentified clupeids (“river herring”), since onl y a few of the older young-of-the-year were identified to the species level. Sample sizes for Amer ican shad were low (a maximum of eight fish in any 1-mm length class), so because of the similarity in body shape to the closely related alewife and blueback herring, American shad data were pooled with the river herring data. For each 1-mm length class within a taxon, the proportion of GBD measure ments exceeding each of the six selected mesh sizes was calculated as a preliminary estimate of P
e .
For striped bass, white perch, clupeids (American shad and river herring), and bay anchovy, the number of measurements within many of the length classes was very good (over 50 for many length classes, with several even exceeding 1, 000), providing a goo d basis for the P
e estimates. There were, however, some length classes with no measurements, or very few. Logistic curves fit to the data did not fit the data very well. For many of the most intensively sampled length classes (where P
e was therefore known with a high degree of precision) the P
e estimates from the curves were not very close

to the P
e estimates from the actual data. Rather than sacrificing the quality of the estimates in the length classes containing most of the larvae for the sake of generating logistic regression estimates for the non-sampled length classes, the IPEC biologist team chose to use the P
e estimates from the actual data rather than from logistic models.

Although length classes with missing estimates would minimally affect the outcome of the analysis (since they are the length classes rare ly entrained) they still needed P
e estimates. Most of the missing values were obviously outside the entrainment/imp ingement transition range, and could easily be estimated by zero or one. When a missing value fe ll within the entrainment/impingement transition range, it was estimated “by eye” based on values in the sampled length classes.

Another difficulty was that in some length classes th ere were data, but they were based on a limited number of measurements and the resulting P
e estimates were questionable because they did not agree with the overall pattern shown by the adjacent well sampled length classes. Some values outside the principal entrainment/impingement transition range appeared to be unduly influenced by questionable values. For example, a length class that should have had a P
e estimate at or close to 1.00 based on the overall pattern of the data might have a P
e estimate of 0.00 or 0.50 because of a single “outlier” specimen (which could have been due to a measuring or data recording error). Original values that were influenced by one or more outliers were sm oothed using interpolation between the neighboring valid data to preserve the in tegrity of the overall pattern.

For the mesh widths of 6 and 9 mm there were almo st no useable data, except for Atlantic tomcod. P
e estimates for 6 and 9 mm mesh for the other four taxa were therefore based on estimates from the literature of the average length at which body dept hs of 6 and 9 mm are attained. Those length classes were assigned P
e = 0.50. To represent the E/I transition zone for these cases, P
e estimates of 0.05, 0.15, and 0.30 were assigned to the th ree length classes below the length class with P
e = 0.50IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 4 Normandeau Associates, Inc. and P
e estimates of 0.70, 0.85, and 0.95 were assigne d to the three length classes above the length

class with P
e = 0.50, based on the pattern seen in the well sampled length classes.

The resulting estimates of P
e are shown in Tables 2-1 through 2-5. All P
e estimates resulting from filling in missing length classes by interpolation are cl early identified by red font; also the number of actual measurements available for each length class is shown.

Results from actual field and laboratory studies were examined to determine how well the P
e estimates based on GBD agreed with empirical observations. EA (1977) conducted a field test of retention on 2.5-mm mesh at IPEC using hatchery -reared striped bass larvae. Large numbers of larvae (averaging 7 mm and 9 mm in two batches) we re released in front of the screen, with minimal (0.16%) impingement. Wild striped bass larvae im pinged on 16 and 21 June were late post yolk-sac larvae (“PYSL”) ranging from 10 to18 mm in length and early young-of-the-year (“YOY”) 17-23 mm in length, while concurrently collected larv ae from unscreened intake samples contained an overlapping but smaller length dist ribution of striped bass larvae. EA concluded that 7-9 mm larvae were not effectively excluded and that 10-18 mm larv ae were the smallest ones effectively retained by the 2.5-mm mesh. An entrainment/impingement tr ansition range for striped bass of 10-18 mm is consistent with the GBD analysis for striped bass (Table 2-2).

In flume testing conducted by Alden in 1978-1980 (summarized by Fletcher 1990), the 50% retention sizes for striped bass were roughly 25-40% longer than predicted by the GBD analysis. This would seem to indicate that larvae were extruded through the mesh in Alden’s experiments when they were theoretically too big to be entrained. Although Al den’s tests did not find any significant relationship between retention and water velocity, of the five speeds they tested only the lowest (15 cm/s) was relevant to speeds under consideration for IPEC, so th e applicability of most of the Alden data to the mesh selectivity analysis for IPEC is questionable.

Impingement rates for white perch, striped bass, and river herring smaller than 40 mm were much higher for 3.0-mm mesh intake screens than for 9.5-mm mesh screens at Danskammer Point Station (Normandeau 1989). For bay anchovy the 3.0-mm sc reens also had higher impingement rates for the 40-49 mm length class. These results are consistent with the entrainment/impingement transition sizes predicted by the GBD analysis for bay anchovy (Table 2-5).

Alden (2003) reported flume tests of retention on a standard-mesh screen (it appeared to have 3/8 inch square mesh in their photos). The 50% retention size for hybrid striped bass was about 45 mm (converted from FL to TL), which is consistent with the GBD analysis, although the IPEC data used in the GBD analysis only included two striped bass in that size range. Alden’s 50% retention size for bay anchovy was about 66-71 mm, slightly larger than the 55-60 mm predicted by the GBD analysis, although Alden’s sample size was small and the GBD prediction was extrapolated from smaller sizes. Alden’s study does not provide co nvincing evidence that the exclus ion factors based on GBD need adjustment, but the comparison is weak because of th e small sample sizes and different size ranges. There is also some uncertainty in the dimensions of Alden’s test mesh, because the dimensions of Alden’s test mesh were not specified.

EPRI (2009) reported flume tests of larval retention of eight freshwater species on 0.5-mm, 1.0-mm,

and 2.0-mm mesh at different flume velocities. One indication of the validity of the GBD approach for fine-mesh screens was that the only species effectiv ely retained by 2.0-mm mesh was blue catfish, which had head capsule depths >2.0 mm. Othe rwise, the size ranges of impinged and entrainedIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 5 Normandeau Associates, Inc. larvae were too narrow to evaluate the entrainmen t/impingement transition ranges, so this study does not provide much information for evaluating the GBD estimates of exclusion.

Based on comparisons with the results of these lab and field studies, the estimates of P
e based on GBD analysis appear to be realistic.

2.1.2 Eggs

For fish eggs, which are spherical, or nearly so, th e limiting dimension is simpler than for larvae. If the egg diameter is larger than the width of th e mesh openings, the egg would normally be excluded by the intake screens (assuming that the through-mesh velocity is not high enough to deform the egg sufficiently to “extrude” it through the mesh). Egg diameters were not measured during the 1986 entrainment abundance program at IPEC, so egg diam eters for the selected species were estimated from the ranges reported by Jones et al. (1978) for alewife, blueback herring, American shad, and bay anchovy; Hardy (1978a) for Atlantic tomcod; and Hardy (1978b) for striped bass and white perch. For the slightly elliptical eggs of bay anchovy, the minimum and maximum diameter were each estimated by averaging the values for the minor and major axes at a salinity of 5 parts per thousand. From the range, the median egg diameter was estimated as the average of the minimum and

maximum value. Since 99.73% of the items in a nor mal frequency distribution lie within ±3 standard deviations of the mean (Sokal and Rohlf 1969), the standard deviation was estimated as one-sixth of the range. The proportion of eggs with diameters larg er than screen opening widths of 1.0, 1.5, 2.0,
3.0, 6.0, and 9.0 mm were then determined from ta bulated areas of the normal curve using the median

and standard deviation estimates of egg diameter to estimate the physical exclusion factor P
e (Table 2-6).

Estimates of P
e based on egg diameter could overestimate th e actual fraction excluded if some eggs are “extruded” (compressed and forced through the screen), if some pass through holes in the screen, if some pass through gaps beside the screen, or if some are carried over the top of the screen and fall off behind the screen during screen rotation and washing. No attempt was made to adjust for this bias

because there is insufficient information av ailable on which to base an adjustment.



### 2.2 W EDGEWIRE 

### A VOIDANCE 

### F ACTORS

As discussed in Attachment B-1 to this appendix, a wide variety of studies performed by many investigators have demonstrated that fish la rvae possess the ability to swim and to use their swimming ability to evade predators, sampling gears, and, at least in under certain circumstances, intake screens. Of particular relevance here , Heuer and Tomljanovich (1978) found that the proportions of larvae entrained through wedgewire sc reen panels in a laboratory flume were much lower than the proportions of flow entrained, indi cating that larvae small enough to be entrained are capable of detecting and avoiding wedgewire sc reens (Heuer and Tomljanovich 1978). To avoid entrainment, larvae need only to swim far enough to move out of the flow entrained through the screen and into the sweeping flow that bypasses the screen.

If active avoidance and physical exclusion are tw o distinct factors contributing to entrainment reduction, their combined effect can be expr essed by the following generalization for wedgewire

screens:

P E = ( 1–P
a ) ( 1–P
e ) (Equation 3)

where P E = proportion of larvae within the withdrawal zone that are entrained,IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 6 Normandeau Associates, Inc. P a = proportion of larvae within the withdrawal zone that avoid entrainment, and

P e = proportion of larvae within the withdrawal zone that do not avoid entrainment but are physically excluded.

In field and lab tests of wedgewire screens, only P E (the combined effect of P
a and P
e ) can be directly observed. Wedgewire avoidance factors can be est imated from experimentally observed values of P E using the physical exclusion factors P
e developed in Section 2.1 above and solving Equation 3 for P
a :

P a = 1 – [ ( P E / ( 1–P
e ) ] (Equation 4)

where P
a = proportion of larvae within the withdrawal zone that avoid entrainment,

P E = proportion of larvae within the withdrawal zone that are entrained, and

P e = proportion of larvae within the withdrawal zone that do not avoid entrainment but are physically excluded.

The flume tests by Heuer and Tomljanovich (1978) compared 0.5 mm, 1.0 mm, and 2.0 mm wedgewire screen panels; through-slot velocities of 7.6, 15.2, and 22.9 cm/s; and sweeping velocities of 7.6, 15.2, 30.5, and 61.0 cm/s. The test sp ecies were striped bass, largemouth bass, smallmouth bass, bluegill, walleye, channel catfish, and musk ellunge. For each test, a wedgewire panel was

mounted flush with either the bottom or side of the flume, withdrawing water perpendicular to the

direction of flow in the flume. In the absen ce of physical exclusion or active avoidance (or attraction), the expected proportion of larvae not drawn through the wedgewire panel (the proportion “bypassed”) was the same as the proportion of the fl ume’s flow that was bypassed. The expected proportion of larvae bypassed was compared to the observed proportion of larvae that actually were bypassed. The larvae in these experiments were dist ributed uniformly both within the withdrawal zone and within the flow that bypassed the screen panel, which can be accounted for by inserting another term into Equation 3:

P E = ( 1–P b ) ( 1–P
a ) ( 1–P
e ) (Equation 5)

where P E = proportion of larvae within the entire flume that were entrained,

P b = proportion of the flume’s flow that bypassed the screen panel,

P a = proportion of larvae within the withdraw al zone that avoided entrainment, and

P e = proportion of larvae within the withdrawal zone that did not avoid entrainment but were physically excluded.

Solving for P
a to estimate the avoidance factor from the Heuer and Tomljanovich (1978) flume tests,

P a = 1 – { P E / [ ( 1–P b ) ( 1–P
e ) ] } (Equation 6)

where P
a = proportion of larvae within the withdr awal zone that avoided entrainment,

P E = proportion of larvae within the entire flume that were entrained (observed by the experimenters),

P b = proportion of the flume’s flow that bypa ssed the screen panel (determined by the experimenters from measurements of the flow in the flume and the flow withdrawn through the wedgewire panel), and

P e = proportion of larvae within the withdrawal zone that did not avoid entrainment but were physically excluded (from Section 2.1).IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 7 Normandeau Associates, Inc. To represent the system under consideration for IPEC , this evaluation of the Heuer and Tomljanovich (1978) data was limited to the results for striped bass larvae at a slot velocity of 0.15 m/s, flume
velocities of 0.15 and 0.30 m/s, and slot widths of 1.0 and 2.0 mm from their Tables 1 and 2. Striped bass were tested by in two series of trials, one in April (lengths averaging 5.6 mm) and one in June (lengths averaging 5.9 mm). For larvae exposed to panels with slots 1 mm wide, the wedgewire avoidance factor (P
a ) averaged 0.309 in April tests and 0.483 in June tests. For striped bass larvae exposed to panels with slots 2 mm wide, P
a averaged 0.412 in April tests and 0.755 in June tests.

Each of these values was the mean of P
a for four trials, where a trial was the average of three replicate

releases of about 100-200 larvae each. The overall av erages by slot width for the April and June tests combined (average length 5.75 mm) were P
a = 0.396 for 1-mm screening and P
a = 0.583 for 2-mm screening.

In 2001 and 2002, flume testing of cylindrical wedgewire screen entrainment and impingement was conducted by Alden Research Laboratory, Inc. (EPRI 2003). The screens were 12 inches in diameter and 44 inches long with 0.5, 1.0, and 2.0 mm slot wi dths, oriented both perpendicular and parallel to the flume flow. Flume speeds were 0.08, 0.15 and 0.30 m/s and slot velocities were 0.15 and 0.30 m/s. Species and life stages tested included eggs of striped bass, white sucker, and alewife and larvae of striped bass, winter flounder, white sucker, rainbow smelt, yellow perch, common carp, and bluegill. Test organisms were released from a tube close to the screen at its centerline, so all would be vulnerable to entrainment or impingement (none we re in the part of the flume flow that bypassed the screen, so Equation 4 above was the one applicable to these data).

There appears to have been substantial extrusi on of 8.9-mm striped bass larvae through 1.0-mm slots when the slot velocity was high (0.3 m/s) and th e screens were mounted perpendicular to the flume flow, since only 15% of 8.9 mm larvae should fit through 1.0 mm slots but 67% and 68% of the larvae were entrained. Neither the slot velocity nor the screen orientation, however, is representative of the system proposed for IPEC. There was little or no avoidance for the 1.0 mm wedgewire screen in the parallel orientation at 0.30 m/s flume velo city, although those three experiments did not show

the extreme extrusion as when the screen was orient ed perpendicularly. Because of the high slot velocity, these also are not representative of the pr oposed IPEC system. Low avoidance was also seen for the 2.0 mm wedgewire screen in the perpendi cular orientation, also not representative of the system proposed for IPEC.

To best represent the system under consideration fo r IPEC, this evaluation of the EPRI (2003) data was therefore limited to the results of the striped bass larvae experiments conducted at a slot velocity of 0.15 m/s through 1.0 and 2.0 mm slots in screens or iented parallel to the flow in flume velocities of

0.15 and 0.30 m/s. The mean P
a for 7.0-mm striped bass larvae and 1.0-mm slot width screens was

0.706 . The mean P
a for 8.3-mm striped bass larvae and 2.0-mm slot width screens was 0.464

.
Considered together, the results of Heuer and To mljanovich (1978) and EPRI (2003) for striped bass on 1.0 and 2.0-mm wedgewire screens suggest a fairly consistent avoidance fact or, with no indication of differences due to slot width. The size range of the striped bass larvae tested in these two studies was, however, too narrow to adequately detect any va riation in avoidance behavior related to length.

Observations over a wider range of lengths for ot her species were obtained in a field test of wedgewire screen exclusion conducte d in 1982 and 1983 in a Maryland power plant intake canal by Weisberg et al . (1987). Their study compared densities of wild-caught larvae pumped through 1.0, 2.0, and 3.0-mm slot width cylindrical wedgewire screens as well as through an unscreened samplingIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 8 Normandeau Associates, Inc. port. Bay anchovy and naked goby larvae were th e dominant species collected. No exclusion was demonstrated for eggs or larvae ≤ 4 mm, but densities of bay anchovy larvae ≥ 5 mm were lower for all

three screens than for the unscreen ed samples. Mean densities entrained appeared to decrease with decreasing slot width, although this pattern was not statistically significant. Within the four larger size ranges (5-7, 8-10, 11-14, and ≥ 15 mm), entrained densities were significantly lower than open port densities for 15 of the 20 combinations of size group, sampling year, and slot width. Mean annual bay anchovy densities from Table 1 in Weisberg et al . (1987) were used as the basis for estimating P E . Because of unequal sample volumes and numbers of samples in the two years of the study, as well as zero catches for some size groups an d slot widths, the densities from the two years were first averaged together, weighted by total sampling volume. Next, the proportion entrained for each size group and slot width (P E ) was calculated as the ratio of entrained density to open port density to enable estimating P
a by Equation 4 using P

e from the GBD analysis. Negative values for P
a in the ≤ 4 mm length class for all three slot widths were interpreted as artifacts of low catches and set to zero, resulting in the following wedgewire a voidance factors for bay anchovy larvae estimated from the data of Weisberg et al . (1987):

1.0-mm screen 2.0-mm screen 3.0-mm screen

≤ 4 mm larvae 0.000 0.000 0.000

5-7 mm larvae 0.427 0.512 0.438

8-10 mm larvae 0.860 0.747 0.662

11-14 mm larvae 1.000 0.832 0.769

≥ 15 mm larvae 0.874 0.793 0.839

The above estimates of wedgewire avoidance are ba sed on a wide range of sizes for bay anchovy and a limited size range for striped bass. To evaluate the best approach to estimate factors for other species, the estimates for striped bass and bay an chovy were compared within their common size
range. P a estimates for striped bass were 0.396 and 0.583 at 5.75 mm and 0.706 at 7.0 mm, compared to bay anchovy estimates of 0.427, 0.512, and 0.438 in the 5-7 mm length range. The good agreement among values for these two species, in spite of their different body shapes, supports using a single value (or set of values) of P
a for all species in the IPEC analysis. The P
a estimates for bay anchovy, the only species tested over a wide range of sizes, increase consistently with increasing size. This is consistent with the biology of fish larvae, which improve in swimming capability as they grow. Based on the similarity in avoidance betw een striped bass and bay anchovy of a comparable size, the increase in avoidance demonstrated by bay anchovy as they grow, and the similarity in avoidance among different slot widths tested, the 19 values highlighted in bold font above and

summarized in Table 2-7 were used to fit a generalized exponential equation for estimating wedgewire avoidance as a function of length, applicable to all species in the IPEC analysis (illustrated in Figure 2-1):

P a = 1 – e [ –0.275 ( L – 4 ) ] (Equation 7)

where P
a = proportion of larvae within the withdrawal zone that avoid entrainment,

e = base of natural logarithms (2.71828),IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 9 Normandeau Associates, Inc. L = total length (mm).

Equation 7 applies when length ≥ 4 mm (when length <4 mm, P
a is defined as zero).

Equation 7 was developed from laboratory tests of fish larvae representing the same species and sizes exposed to entrainment at IPEC. These tests studied small-scale (12 inches in diameter by 44 inches long), narrow slot, cylindrical wedgewire screens of the same proportions and orientation as those considered for application to IPEC. The resulting data were used to develop a performance curve (Figure 2-1) for 1 mm, 2 mm and 3 mm screens that expressed the probability of avoidance as a function of larval length. An important conclusion fr om our analysis of these data is that slot width did not have a significant influence on avoidance for the range of slot widths tested. This conclusion is supported by the narrow scatter of actual experiment al observations about the predicted curve. The correlation coefficient was high (R 2 = 0.872), and larval length was the predominant factor influencing the curve. However, cylindrical wedge wire screens with slot widths greater than 3 mm

were not tested. It is not clear from the av ailable laboratory studies whether this avoidance relationship is applicable full-scale cylindrical wedgewi re screens of larger slot widths, such as 6 mm

or 9mm.

A recent (20 April 2005 through 28 March 2006) full-scale evaluation of 6.35 mm cylindrical wedgewire screens was performed at the Eddystone Generating Station located on the Delaware River Estuary in Pennsylvania (Veritas et al. 2008). Th is evaluation supports the applicability of the wedgewire performance curve to full scale screens of similar design being considered for IPEC. The original cooling water intake structure for Ed dystone Units 1 and 2 was located in a shoreline bulkhead, and was equipped with conventional 9. 5 mm (3/8-inch) mesh traveling screens with no design or operational modifications to reduce impinge ment or entrainment. In the early 1990s, the intake for Units 1 and 2 was modified by removing the traveling screens and installing sixteen narrow slot cylindrical wedgewire T-type screens (eight per unit). Each wedgewire screen is 72-inch in diameter with an effective length of 144 inches (actual overall length is 240 inches including the nose cones) and is equipped with 6.35 mm (0.25 inch) wedgewire screening oriented radially around each screen with the long axis of the cylinder aligned parallel to the sweeping flow. The average throughscreen velocity is approximately 0.4 feet per second (fps).

Units 3 and 4 at Eddystone were built after Units 1 and 2, and the cooling water intake structure design included several structural modifications sp ecifically to reduce impingement and entrainment. Units 3 and 4 employ conventional 9.5 mm (3/8-inch) mesh traveling screens, with a through-screen velocity of approximately 0.88 fps at d esign flow and mean low water level.

Larvae of tessellated darter (32%), American shad (13%), Cyprinidae (9%), striped bass (9%), white perch (7%), Morone spp. (55), and American eel (5%) were the predominant fish taxa observed in the entrainment samples collected during a year-lon g entrainment study performed from April 2005 through March 2006 at Eddystone Units 1 and 2, with the peak period of entrainment abundance occurring from early May through mid-July (Table 2-5 in Veritas et al. 2008). The 6.35 mm slot width cylindrical wedgewire screens installed and operated at Unit s 1 and 2 of Eddystone Generating

Station were estimated to reduce total annual entrai nment of fish eggs and larvae combined by 60% from baseline, with a 95% confidence interval of 48 to 71% (Table 5.2, Veritas et al. 2008). In 374 paired entrainment samples over a full year at Ed dystone, the mean density of larvae entrained through wedgewire screens at Units 1 and 2 was 82% lower than the mean density of larvae entrained simultaneously through conventional 9.5 mm (3/8-inch) mesh screens at Units 3 and 4. These results from Eddystone demonstrate that a high percentage of larvae can avoid entrainment through full-scale cylindrical wedgewire screens operating under field cond itions, even at slot width greater than 6 mm.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 10 Normandeau Associates, Inc. 

### 2.3 R EFERENCES

Alden (Alden Research Laboratory, Inc.). 2003. Laboratory study to measure traveling screen retention of selected fish species. Prepared for PSEG Services Corporation Estuary Enhancement Program. Final Report.

EA (Ecological Analysts, Inc.). 1977. Preliminar y investigations into the use of a continuously operating fine mesh traveling screen to reduce ichthyoplankton entrainment at Indian Point Generating Station. Prepared for Consolid ated Edison Company of New York, Inc.

EPRI (Electric Power Research Institute). 2003. Laboratory evaluation of wedgewire screens for protecting early life stages of fish at cooling water intakes. Report 1005339.

EPRI (Electric Power Research Institute). 2009. Laboratory evaluation of fine-mesh traveling water screens for protecting early life stages of fish at cooling water intakes. Research progress update through 2008. Report 1015578. T echnical update prepared March 2009 by Alden Research Laboratory.

Fletcher, R.I. 1990. A review of reported fine mesh screen applications for high volume water-intake systems, and recommendations for further inves tigations. Prepared for Consolidated Edison Company of New York, Inc.

Hardy, J.D. Jr. 1978a. Development of fishes of th e Mid-Atlantic Bight. An atlas of egg, larval and juvenile stages. Vol. 2. Anguillidae through Sy ngnathidae. U.S. Fish Wildl. Serv. 458 p.

Hardy, J.D. Jr. 1978b. Development of fishes of th e Mid-Atlantic Bight. An atlas of egg, larval and juvenile stages. Vol. 3. Aphredoderidae through Rachycentridae. U.S. Fish Wildl. Serv. 394 p.

Heuer, J.H., and D.A. Tomljanovich. 1978. A stud y on the protection of fish larvae at water intakes using wedge-wire screening. TVA Tech. Note B26. 60 p.

Jones, P.W., F.D. Martin, and J.D. Hardy, Jr. 1978. Development of fishes of the Mid-Atlantic Bight. An atlas of egg, larval and juvenile stag es. Vol. 1. Acipenseridae through Ictaluridae. U.S. Fish Wildl. Serv. 366 p.

Normandeau (Normandeau Associates, Inc.). 1987. Indian Point Generating Station entrainment abundance program 1986 annual report. Prepared for Consolidated Edison Company of New York, Inc., and New York Power Authority.

Normandeau (Normandeau Associates, Inc.). 19 89. Danskammer Point Station fine mesh screen evaluation. 1988 study. Prepared for Central Hudson Gas and Electric Corp.

Veritas Economic Consulting, Normandeau Associ ates Inc., and ARCADIS (Veritas et al.) December 2008. Development of annual curre nt and baseline impingement mortality and entrainment estimates. Eddystone Generating St ation. Eddystone, PA. Prepared for Excelon Generation Company, LLC

Weisberg, S.B., W.H. Burton, F. Jacobs, and E.A. Ross. 1987. Reductions in ichthyoplankton entrainment with fine-mesh, wedge-wire screens . N. Amer. J. Fish. Manag. 7:386-393.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 11 Normandeau Associates, Inc. 

### 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

4 5 6 7 8 9 10 11 12 13 14 15 16

Total length (mm)Wedgewire avoidance factor



### SB/1.0

SB/2.0

BA/1.0

BA/2.0

BA/3.0

Figure 2-1. Observed wedgewire avoidance factors by length, species, and slot width, with a generalized relationship between larval length and wedgewire avoidance
factor.

Symbols show the data points used to derive the generalized curve P

a = 1 – e [ –0.275 ( L – 4 ) ] (refer to Table 2-7 for details); SB=striped bass, BA=bay anchovy, labels indicate the wedgewire slot width in millimeters.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 12 Normandeau Associates, Inc. Table 2-1. Physical exclusion factors for Atlantic tomcod.

Length (mm TL) Number

measured Physical exclusion factor P
e by mesh opening width (mm)

1.0 1.5 2.0 3.0 6.0 9.0

<5 0 0.00 0.00 0.00 0.00 0.00 0.00

5 0 0.02 0.00 0.00 0.00 0.00 0.00

6 26 0.08 0.00 0.00 0.00 0.00 0.00

7 136 0.26 0.00 0.00 0.00 0.00 0.00

8 27 0.52 0.15 0.00 0.00 0.00 0.00

9 0 0.78 0.30 0.00 0.00 0.00 0.00

10 0 0.95 0.50 0.00 0.00 0.00 0.00

11 0 1.00 0.70 0.15 0.00 0.00 0.00

12 1 1.00 0.85 0.30 0.00 0.00 0.00

13 6 1.00 1.00 0.50 0.00 0.00 0.00

14 7 1.00 1.00 0.70 0.14 0.00 0.00

15 11 1.00 1.00 0.85 0.30 0.00 0.00

16 16 1.00 1.00 1.00 0.50 0.00 0.00

17 26 1.00 1.00 1.00 0.81 0.00 0.00

18 28 1.00 1.00 1.00 0.96 0.00 0.00

19 24 1.00 1.00 1.00 0.92 0.00 0.00

20 18 1.00 1.00 1.00 0.94 0.00 0.00

21 24 1.00 1.00 1.00 1.00 0.00 0.00

22 27 1.00 1.00 1.00 0.96 0.00 0.00

23 19 1.00 1.00 1.00 0.95 0.00 0.00

24 16 1.00 1.00 1.00 1.00 0.00 0.00

25 13 1.00 1.00 1.00 1.00 0.00 0.00

26 14 1.00 1.00 1.00 1.00 0.00 0.00

27 8 1.00 1.00 1.00 1.00 0.00 0.00

28 13 1.00 1.00 1.00 1.00 0.15 0.00

29 11 1.00 1.00 1.00 1.00 0.18 0.00

30 7 1.00 1.00 1.00 1.00 0.57 0.00

31 11 1.00 1.00 1.00 1.00 0.18 0.00

32 15 1.00 1.00 1.00 1.00 0.53 0.00

33 15 1.00 1.00 1.00 1.00 0.67 0.00

34 12 1.00 1.00 1.00 1.00 0.67 0.00

35 23 1.00 1.00 1.00 1.00 0.83 0.00

36 25 1.00 1.00 1.00 1.00 0.96 0.00

37 14 1.00 1.00 1.00 1.00 0.93 0.00

38 23 1.00 1.00 1.00 1.00 0.96 0.00

39 20 1.00 1.00 1.00 1.00 1.00 0.00

40 30 1.00 1.00 1.00 1.00 0.97 0.00

41 27 1.00 1.00 1.00 1.00 1.00 0.00

42 33 1.00 1.00 1.00 1.00 1.00 0.03

43 15 1.00 1.00 1.00 1.00 1.00 0.07

44 18 1.00 1.00 1.00 1.00 1.00 0.06

45 18 1.00 1.00 1.00 1.00 1.00 0.11

46 13 1.00 1.00 1.00 1.00 1.00 0.08

47 9 1.00 1.00 1.00 1.00 1.00 0.22

48 10 1.00 1.00 1.00 1.00 1.00 0.50

49 5 1.00 1.00 1.00 1.00 1.00 0.60

50 7 1.00 1.00 1.00 1.00 1.00 0.71

51 5 1.00 1.00 1.00 1.00 1.00 0.80

52 3 1.00 1.00 1.00 1.00 1.00 0.67

>52 23 1.00 1.00 1.00 1.00 1.00 1.00IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 13 Normandeau Associates, Inc. Table 2-2. Physical exclusion factors for striped bass.

Length (mm TL) Number

measured Physical exclusion factor P
e by mesh opening width (mm)

1.0 1.5 2.0 3.0 6.0 9.0

<4 5 0.00 0.00 0.00 0.00 0.00 0.00

4 103 0.06 0.00 0.00 0.00 0.00 0.00

5 943 0.02 0.00 0.00 0.00 0.00 0.00

6 2,786 0.04 0.00 0.00 0.00 0.00 0.00

7 2,745 0.26 0.00 0.00 0.00 0.00 0.00

8 2,583 0.65 0.01 0.00 0.00 0.00 0.00

9 1,749 0.86 0.07 0.00 0.00 0.00 0.00

10 798 0.92 0.40 0.01 0.00 0.00 0.00

11 468 0.98 0.78 0.08 0.00 0.00 0.00

12 224 1.00 0.95 0.35 0.00 0.00 0.00

13 117 0.99 0.94 0.77 0.00 0.00 0.00

14 67 1.00 0.96 0.91 0.00 0.00 0.00

15 36 1.00 1.00 1.00 0.08 0.00 0.00

16 21 1.00 0.95 0.81 0.19 0.00 0.00

17 22 0.95 0.95 0.91 0.41 0.00 0.00

18 8 1.00 1.00 0.87 0.75 0.00 0.00

19 7 1.00 1.00 1.00 1.00 0.00 0.00

20 5 1.00 1.00 1.00 1.00 0.00 0.00

21 3 1.00 1.00 1.00 1.00 0.00 0.00

22 1 1.00 1.00 1.00 1.00 0.00 0.00

23 3 1.00 1.00 1.00 1.00 0.00 0.00

24 1 1.00 1.00 1.00 1.00 0.00 0.00

25 4 1.00 1.00 1.00 1.00 0.00 0.00

26 2 1.00 1.00 1.00 1.00 0.00 0.00

27 2 1.00 1.00 1.00 1.00 0.05 0.00

28 2 1.00 1.00 1.00 1.00 0.15 0.00

29 1 1.00 1.00 1.00 1.00 0.30 0.00

30 0 1.00 1.00 1.00 1.00 0.50 0.00

31 0 1.00 1.00 1.00 1.00 0.70 0.00

32 0 1.00 1.00 1.00 1.00 0.85 0.00

33 1 1.00 1.00 1.00 1.00 0.95 0.00

34 0 1.00 1.00 1.00 1.00 1.00 0.00

35 1 1.00 1.00 1.00 1.00 1.00 0.00

36 0 1.00 1.00 1.00 1.00 1.00 0.00

37 0 1.00 1.00 1.00 1.00 1.00 0.00

38 1 1.00 1.00 1.00 1.00 1.00 0.00

39 0 1.00 1.00 1.00 1.00 1.00 0.05

40 0 1.00 1.00 1.00 1.00 1.00 0.15

41 0 1.00 1.00 1.00 1.00 1.00 0.30

42 0 1.00 1.00 1.00 1.00 1.00 0.50

43 0 1.00 1.00 1.00 1.00 1.00 0.70

44 0 1.00 1.00 1.00 1.00 1.00 0.85

45 0 1.00 1.00 1.00 1.00 1.00 0.95

>45 1 1.00 1.00 1.00 1.00 1.00 1.00IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 14 Normandeau Associates, Inc. Table 2-3. Physical exclusion factors for white perch.

Length (mm TL) Number

measured Physical exclusion factor P
e by mesh opening width (mm)

1.0 1.5 2.0 3.0 6.0 9.0

<3 3 0.00 0.00 0.00 0.00 0.00 0.00

3 122 0.01 0.00 0.00 0.00 0.00 0.00

4 1,189 0.00 0.00 0.00 0.00 0.00 0.00

5 1,761 0.00 0.00 0.00 0.00 0.00 0.00

6 1,871 0.01 0.00 0.00 0.00 0.00 0.00

7 1,410 0.20 0.00 0.00 0.00 0.00 0.00

8 721 0.64 0.02 0.00 0.00 0.00 0.00

9 865 0.85 0.09 0.00 0.00 0.00 0.00

10 1,047 0.94 0.41 0.02 0.00 0.00 0.00

11 830 0.97 0.78 0.12 0.00 0.00 0.00

12 640 0.99 0.95 0.49 0.00 0.00 0.00

13 478 1.00 0.97 0.83 0.01 0.00 0.00

14 325 0.99 0.97 0.94 0.04 0.00 0.00

15 217 1.00 0.99 0.96 0.15 0.00 0.00

16 110 0.99 0.99 0.97 0.45 0.00 0.00

17 77 1.00 1.00 0.99 0.82 0.00 0.00

18 44 1.00 1.00 1.00 0.91 0.00 0.00

19 53 1.00 1.00 1.00 0.96 0.00 0.00

20 15 1.00 1.00 0.93 0.93 0.00 0.00

21 16 1.00 1.00 1.00 0.87 0.00 0.00

22 15 1.00 1.00 1.00 1.00 0.00 0.00

23 17 1.00 1.00 1.00 0.94 0.00 0.00

24 11 1.00 1.00 1.00 0.91 0.00 0.00

25 6 1.00 1.00 1.00 1.00 0.00 0.00

26 8 1.00 1.00 1.00 0.87 0.12 0.00

27 4 1.00 1.00 1.00 1.00 0.25 0.00

28 5 1.00 1.00 1.00 1.00 0.40 0.00

29 3 1.00 1.00 1.00 1.00 0.33 0.00

30 2 1.00 1.00 1.00 1.00 0.50 0.00

31 0 1.00 1.00 1.00 1.00 0.70 0.00

32 1 1.00 1.00 1.00 1.00 0.85 0.00

33 2 1.00 1.00 1.00 1.00 0.95 0.00

34 2 1.00 1.00 1.00 1.00 1.00 0.00

35 2 1.00 1.00 1.00 1.00 1.00 0.00

36 2 1.00 1.00 1.00 1.00 1.00 0.00

37 0 1.00 1.00 1.00 1.00 1.00 0.00

38 1 1.00 1.00 1.00 1.00 1.00 0.00

39 0 1.00 1.00 1.00 1.00 1.00 0.05

40 1 1.00 1.00 1.00 1.00 1.00 0.15

41 1 1.00 1.00 1.00 1.00 1.00 0.30

42 3 1.00 1.00 1.00 1.00 1.00 0.50

43 0 1.00 1.00 1.00 1.00 1.00 0.70

44 0 1.00 1.00 1.00 1.00 1.00 0.85

45 4 1.00 1.00 1.00 1.00 1.00 0.95

>45 16 1.00 1.00 1.00 1.00 1.00 1.00IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 15 Normandeau Associates, Inc. Table 2-4. Physical exclusion factors for river herring and American shad.

Length (mm TL) Number

measured Physical exclusion factor P
e by mesh opening width (mm)

1.0 1.5 2.0 3.0 6.0 9.0

<7 286 0.00 0.00 0.00 0.00 0.00 0.00

7 435 0.01 0.00 0.00 0.00 0.00 0.00

8 624 0.00 0.00 0.00 0.00 0.00 0.00

9 699 0.00 0.00 0.00 0.00 0.00 0.00

10 760 0.03 0.00 0.00 0.00 0.00 0.00

11 781 0.07 0.00 0.00 0.00 0.00 0.00

12 844 0.15 0.00 0.00 0.00 0.00 0.00

13 781 0.33 0.00 0.00 0.00 0.00 0.00

14 766 0.57 0.01 0.00 0.00 0.00 0.00

15 629 0.76 0.04 0.00 0.00 0.00 0.00

16 454 0.88 0.15 0.01 0.00 0.00 0.00

17 308 0.96 0.39 0.02 0.00 0.00 0.00

18 208 0.98 0.67 0.03 0.00 0.00 0.00

19 128 0.98 0.83 0.18 0.00 0.00 0.00

20 78 0.99 0.96 0.59 0.00 0.00 0.00

21 46 1.00 1.00 0.89 0.02 0.00 0.00

22 16 1.00 1.00 0.94 0.06 0.00 0.00

23 16 1.00 0.94 0.88 0.43 0.00 0.00

24 19 1.00 1.00 0.90 0.42 0.00 0.00

25 12 1.00 1.00 0.83 0.50 0.00 0.00

26 7 1.00 1.00 1.00 0.71 0.00 0.00

27 4 1.00 1.00 1.00 1.00 0.00 0.00

28 3 1.00 1.00 1.00 0.67 0.00 0.00

29 2 1.00 1.00 1.00 1.00 0.05 0.00

30 3 1.00 1.00 1.00 1.00 0.15 0.00

31 1 1.00 1.00 1.00 1.00 0.30 0.00

32 1 1.00 1.00 1.00 1.00 0.50 0.00

33 1 1.00 1.00 1.00 1.00 0.70 0.00

34 0 1.00 1.00 1.00 1.00 0.85 0.00

35 1 1.00 1.00 1.00 1.00 0.95 0.00

36 0 1.00 1.00 1.00 1.00 1.00 0.00

37 2 1.00 1.00 1.00 1.00 1.00 0.00

38 3 1.00 1.00 1.00 1.00 1.00 0.00

39 1 1.00 1.00 1.00 1.00 1.00 0.05

40 0 1.00 1.00 1.00 1.00 1.00 0.15

41 0 1.00 1.00 1.00 1.00 1.00 0.30

42 0 1.00 1.00 1.00 1.00 1.00 0.50

43 0 1.00 1.00 1.00 1.00 1.00 0.70

44 0 1.00 1.00 1.00 1.00 1.00 0.85

45 0 1.00 1.00 1.00 1.00 1.00 0.95

>45 3 1.00 1.00 1.00 1.00 1.00 1.00IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 16 Normandeau Associates, Inc. Table 2-5. Physical exclusion factors for bay anchovy.

Length

(mm TL) Number

measured Physical exclusion factor P
e by mesh opening width (mm)

1.0 1.5 2.0 3.0 6.0 9.0

<9 3,582 0.00 0.00 0.00 0.00 0.00 0.00

9 936 0.01 0.00 0.00 0.00 0.00 0.00

10 879 0.03 0.00 0.00 0.00 0.00 0.00

11 859 0.10 0.01 0.00 0.00 0.00 0.00

12 854 0.24 0.02 0.00 0.00 0.00 0.00 13 1,063 0.35 0.03 0.01 0.00 0.00 0.00 14 1,227 0.50 0.07 0.00 0.00 0.00 0.00 15 1,398 0.71 0.20 0.01 0.00 0.00 0.00 16 1,372 0.84 0.36 0.03 0.00 0.00 0.00 17 1,187 0.93 0.55 0.09 0.00 0.00 0.00

18 889 0.97 0.71 0.20 0.00 0.00 0.00

19 755 0.99 0.81 0.38 0.00 0.00 0.00

20 614 1.00 0.88 0.57 0.01 0.00 0.00

21 427 1.00 0.93 0.74 0.02 0.00 0.00

22 317 1.00 0.97 0.86 0.11 0.00 0.00

23 231 1.00 0.98 0.92 0.23 0.00 0.00

24 163 1.00 1.00 0.94 0.41 0.00 0.00

25 105 1.00 0.99 0.96 0.73 0.00 0.00

26 79 1.00 1.00 0.97 0.85 0.00 0.00

27 52 1.00 1.00 1.00 1.00 0.00 0.00

28 31 1.00 1.00 1.00 0.94 0.00 0.00

29 29 1.00 1.00 0.97 0.93 0.00 0.00

30 12 1.00 1.00 1.00 1.00 0.00 0.00

31 7 1.00 1.00 1.00 1.00 0.00 0.00

32 9 1.00 1.00 1.00 1.00 0.00 0.00

33 5 1.00 1.00 1.00 1.00 0.00 0.00

34 3 1.00 1.00 1.00 1.00 0.00 0.00

35 2 1.00 1.00 1.00 1.00 0.05 0.00

36 0 1.00 1.00 1.00 1.00 0.15 0.00

37 0 1.00 1.00 1.00 1.00 0.30 0.00

38 1 1.00 1.00 1.00 1.00 0.50 0.00

39 1 1.00 1.00 1.00 1.00 0.70 0.00

40 1 1.00 1.00 1.00 1.00 0.85 0.00

41 0 1.00 1.00 1.00 1.00 0.95 0.00

42 1 1.00 1.00 1.00 1.00 1.00 0.00

43 0 1.00 1.00 1.00 1.00 1.00 0.00

44 0 1.00 1.00 1.00 1.00 1.00 0.00

45 0 1.00 1.00 1.00 1.00 1.00 0.00

46 0 1.00 1.00 1.00 1.00 1.00 0.00

47 0 1.00 1.00 1.00 1.00 1.00 0.00

48 0 1.00 1.00 1.00 1.00 1.00 0.00

49 0 1.00 1.00 1.00 1.00 1.00 0.00

50 0 1.00 1.00 1.00 1.00 1.00 0.00

51 0 1.00 1.00 1.00 1.00 1.00 0.05

52 0 1.00 1.00 1.00 1.00 1.00 0.15

53 0 1.00 1.00 1.00 1.00 1.00 0.30

54 0 1.00 1.00 1.00 1.00 1.00 0.50

55 0 1.00 1.00 1.00 1.00 1.00 0.70

56 0 1.00 1.00 1.00 1.00 1.00 0.85

57 0 1.00 1.00 1.00 1.00 1.00 0.95

>57 0 1.00 1.00 1.00 1.00 1.00 1.00IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 17 Normandeau Associates, Inc. Table 2-6. Physical exclusion factors for eggs.

Species (reference) Egg diameter (mm) Mesh width (mm) Z area P
e Min Max Median SD

Alewife (1) 0.80 1.27 1.04 0.08 1.0 -0.45 0.174 0.674

1.5 0.000

2.0 0.000

3.0 0.000

6.0 0.000

9.0 0.000

Blueback

herring

(1) 0.87 1.11 0.99 0.04 1.0 0.25 0.099 0.401

1.5 0.000

2.0 0.000

3.0 0.000

6.0 0.000

9.0 0.000

American

shad (1) 2.50 3.80 3.15 0.22 1.0 1.000

1.5 1.000

2.0 1.000

3.0 -0.69 0.255 0.755

6.0 0.000

9.0 0.000 Bay anchovy (1) 0.89 1.30 1.09 0.07 1.0 -1.37 0.415 0.915

1.5 0.000

2.0 0.000

3.0 0.000

6.0 0.000

9.0 0.000

Atlantic

tomcod

(2) 1.39 1.70 1.55 0.05 1.0 1.000

1.5 -0.87 0.308 0.808

2.0 0.000

3.0 0.000

6.0 0.000

9.0 0.000 Striped

bass (3) 1.30 4.60 2.95 0.55 1.0 1.000

1.5 -2.64 0.496 0.996

2.0 -1.73 0.458 0.958

3.0 0.09 0.036 0.464

6.0 0.000

9.0 0.000

White perch

(3) 0.65 1.09 0.87 0.07 1.0 1.77 0.462 0.038

1.5 0.000

2.0 0.000

3.0 0.000

6.0 0.000

9.0 0.000IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 18 Normandeau Associates, Inc. Table 2-7. Data used to fit a generalized curve for estimating wedgewire avoidance as a function of length.

Reference Species Slot

width (mm) Total length (mm) Wedgewire

avoidance
factor (P a )

Weisberg et al . (1987) Bay anchovy 1 4 0.000
Weisberg et al . (1987) Bay anchovy 2 4 0.000
Weisberg et al . (1987) Bay anchovy 3 4 0.000
Heuer and Tomljanovich (1978) Striped bass 1 5.75 0.396
Heuer and Tomljanovich (1978) Striped bass 2 5.75 0.583
Weisberg et al . (1987) Bay anchovy 1 6 0.427
Weisberg et al . (1987) Bay anchovy 2 6 0.512
Weisberg et al . (1987) Bay anchovy 3 6 0.438
EPRI (2003) Striped bass 1 7.0 0.706
EPRI (2003) Striped bass 2 8.3 0.464
Weisberg et al . (1987) Bay anchovy 1 9 0.860
Weisberg et al . (1987) Bay anchovy 2 9 0.747
Weisberg et al . (1987) Bay anchovy 3 9 0.662
Weisberg et al . (1987) Bay anchovy 1 12.5 1.000
Weisberg et al . (1987) Bay anchovy 2 12.5 0.832
Weisberg et al . (1987) Bay anchovy 3 12.5 0.769
Weisberg et al . (1987) Bay anchovy 1 15 0.874
Weisberg et al . (1987) Bay anchovy 2 15 0.793
Weisberg et al . (1987) Bay anchovy 3 15 0.839

Length ranges are represented by the midpoints of the ranges, 4 mm was used to represent the

≤ 4 mm category, and 15 mm was used to represent the ≥ 15 mm categoryIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 19 Normandeau Associates, Inc. 

## 3.0 I MPINGEMENT 

## M ORTALITY OF 

## S MALL 

## F ISH ON 

## F INE 

## -M ESH 

## I NTAKE 

## S CREENS AT 

## D ANSKAMMER 

## P OINT 

## S TATION



### 3.1 A PPROACH

Impingement survival studies were conducte d at Danskammer Point Generating Station (“Danskammer”) during the fall of 1986 (Normande au 1988a) and during the spring and summer of 1988 to evaluate the survival of fish impinged on fine mesh traveling screens (Normandeau 1989). The results of those Danskammer studies provide one of the few, in-situ tests of size selectivity of full scale conventional traveling screens of standard a nd fine mesh installed and operated at a large cooling water intake structure (“CWIS”), and th e only full scale study of traveling screen mesh selectivity from the Hudson River. Although fish survival from conventional traveling screens of either standard or fine mesh are likely to exhib it lower survival than observed from Ristroph traveling screens (Fletcher 1990), their mesh selectivity characteristi cs are applicable to traveling screens of similar mesh that have been improve d by adding fish handling structures.

Intuitively, the use of fine mesh traveling scr eens would be expected to result in increased impingement survival of fish by being less abrasive to fish impinged and returned to the source water through a spray wash and sluice system compared to standard mesh screens. However, fine mesh traveling screens may exhibit higher impingement rates than standard mesh screens because smaller fish than would be entrained through a standard m esh screen would be retained on a fine mesh screen, increasing the impingement rate when added to the larger fish impinged. Furthermore, recruitment of smaller fish to fine mesh screens might also re duce the overall impingement survival rate if the smaller fish are more fragile than the older and larger fish that would be impinged on conventional mesh screens. The offsetting results of potentia lly increasing survival of some large fish while increasing impingement rates of small fish (which coul d have lower survival rates than the large fish), indicates a need to evaluate empirical and site sp ecific data to compare the mesh selectivity and the mortality rates characteristic of fine and standard mesh screens such as the study performed in 1988 at Danskammer for applicability to the Indian Point alternative technology assessment.

Danskammer is located on the west shore of the Hudson River 66 miles upstream from the southern tip of Manhattan in New York City. The Unit 3 and Unit 4 CWISs are located in a common intake bulkhead at the end of a 450 ft long by 30 ft wide intake canal, with Unit 3 on the east and Unit 4 on the west. Unit 3 has two intake pumps, each ope rating at 41,000 gallons per minute (gpm), for a combined maximum intake flow of 82,000 gpm, wh ich enters the CWIS after passing through three traveling screens equipped with 3. 2 mm square stainless steel mesh. Unit 4 has three intake pumps, each operating at 50,000 gpm, for a combined maximu m intake flow of 150,000 gpm, which enters the CWIS after passing through three traveling screens equipped with 9.5 mm square stainless steel mesh. Relatively few fish were impinged duri ng the 1986 study (1,178 fish, both units combined; Normandeau 1988a), so this analysis examines the impingement survival and mesh selectivity

differences between the standard and fine mesh screens from the 1988 study (9,688 fish, both units combined). An additional advantage to analyzin g the 1988 data is that the spring and summer sampling period corresponds to the seasonal presence of fish eggs and larvae of a size that might be entrained through the standard mesh scree ns but impinged on a fine mesh screen.

Impingement abundance and survival sampling at Danskammer occurred at night on three randomlyselected dates per week beginning 1 May and c ontinuing through 23 August 1988 (NormandeauIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 20 Normandeau Associates, Inc. 1988b). During each 10-hour sampling night, six to thirteen pairs of 30-minute impingement samples were simultaneously collected from Unit 3 and Unit 4 in a specially designed survival tank. The Unit 3 screens were continuously washed at a speed of one revolution per five minutes during impingement survival sample collections, and the Un it 4 screens were continuously washed at a speed of one revolution every ten minutes. All fish a nd blue crabs collected were classified as alive, stunned, or dead at the time of initial collection ( time 0, or “initial survival”), and then all live and stunned fish were held for subsequent latent survival observations at 2.5, 8, 12, 24, 48, and 96 hours

after initial collection. The survival tests were term inated after 96 hours, and all fish in each survival class (alive, stunned, and dead) were preserved as se parate samples from each test in 10% buffered

formalin and later examined to determine and e numerate each species, and to measure the length (millimeters total length) and weight (n earest 0.1 gram) of each individual.

The original data files from the 1988 Danskammer stud y were restored to modern digital media and reanalyzed to calculate survival for each species (and for all taxa combined) and length class from the fine mesh and standard mesh traveling screens. In the original analysis, stunned fish were considered
alive; however stunned fish were reclassified and c onsidered dead in this re-analysis to provide a

more conservative estimate of survival and one cons istent with Fletcher (1990). Unfortunately, to minimize handling stress, alive and stunned fish in the Danskammer study were not measured for length until the 96-hour observation period when they were placed in preservative and taken to the laboratory for length measurement. Therefore, it w as not possible to re-evaluate survival by length

class for individual fish taxa or for all fish taxa combined at intermediate survival observation

intervals such as the 8-hour interval used for the Indian Point Ristroph screen survival studies (Fletcher 1990). Accordingly, the results of this re-a nalysis are based on the initial (time 0) and latent (time 96 hours) observations.

An illustration of the relationship between initial, intermediate, and latent survival is shown for abundant fish taxa and for all fish taxa combined (tot al) in Table 3-1. It is apparent from the data in Table 3-1 that there is some additional mortality occurring beyond the eight-hour observation interval

that makes the 96-hour latent survival values con servatively high. The Danskammer study attempted to obtain and test control fish to adjust the su rvival data presented in Table 3-1. However the collection methods (seining and trawling) were too harsh, resulting in poor survival of the control fish, and consequently the inability to use these data to calculate control adjusted survival.

Size selectivity of the fine mesh (Unit 3) and standa rd mesh (Unit 4) conventional traveling screens at Danskammer was evaluated by examining the adjust ed length frequency distributions of the fish collected from each unit. Adjusted length frequenc y distributions were based on the density of fish (number per unit volume of intake flow sampled by taxon or all taxa combined) caught in each 10 mm length class scaled to adjust for the lower CWIS flow rate inherent in the design of Unit 3 (based on n=1,813 fish measured) compared to Unit 4 (based on n=7,720 fish measured). Fish densities for Unit 3 were scaled upward by multiplying by a factor of 1.7570 to account for the lower intake flow actually sampled at Unit 3 (3,884,346 m 3 ) compared to Unit 4 (6,824,822 m 3 ). It is clear that this factor compares closely to the ratio of differences in design intake flow for Unit 4 compared to Unit 3 (150,000 gpm/82,000 gpm = 1.8290), indicating both units sampled at nearly the same as their rated capacity during the 1988 study.

Size selectivity of the fine mesh traveling screen s was apparent in the adjusted length frequency

distributions for the fine mesh and standard mesh screens (Figures 3-1 through 3-3). The fine mesh screens of Unit 3 impinged more fish (Figure 3-1) and a greater proportion of fish (Figure 3-2) belowIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 21 Normandeau Associates, Inc. 50 mm (total length) than the standard mesh screens of Unit 4. The 20-29 mm length class comprised the greatest proportion of fish impinged at Unit 3 and the 50-59 mm length class comprised the greatest proportion of fish impinged at Unit 4 (Figure 3-2). Comparing the cumulative relative length frequency distributions (Figure 3-3) also suggested that there was some avoidance, escapement or loss of larger fish in the 60 mm to 140 mm lengt h classes from the fine mesh screens of Unit 3, because the two cumulative frequency distributions converged at 140 mm and well above the

retention size for the standard mesh screens of Un it 4. Avoidance or escapement from the fine mesh screens may be related to differences in approach ve locity relative to the size of the fish impinged (EPRI 2003), resulting in the larger fish exposed to the fine mesh screens at Unit 3 being more capable of avoiding impingement by swimming away because of the slower approach velocity compared to Unit 4, so that the difference betw een size distributions between the two units was probably not related to mesh selectivity.

Differences in the number and proportion of fish impinged in the larger length classes between the

standard and fine mesh screens in this Danskamme r study, even though both units were sampling the same source water body in simultane ous and paired collections, suggests the data cannot be pooled into one composite size frequency distribution to determ ine selectivity for application to Indian Point. To further examine the differences in mesh selectivity and survival of the portion of fish impinged on

the fine mesh screens at Danskammer Unit 3 but of a size expected to be entrained through the standard mesh screens at Unit 4, the total lengt h corresponding to the median (50%) limiting body dimensions of the selected, abundant taxa (Section 2. 1) were used to classify the fish into two size

classes:

Class 1 = small fish of a length with median (50%) greatest body depth less than or equal to 9.5 mm that would be retained on the fine mesh but entrained through the standard mesh, and

Class 2 = large fish of a length with median (50%) greatest body depth larger than 9.5 mm that would be impinged on both the fine mesh and standard mesh.

The following fish total length dimensions were used to classify the Danskammer impingement collections into small (Class 1) and large (Class 2) size categories based on the median 50% greatest body depth:

Fish Taxon Class 1 Total Length (mm) Class 2 Total Length (mm) Bay anchovy <54 > 54 Striped bass <42 > 42 White perch <42 > 42 Clupeids <42 > 42

All others <42 > 42



### 3.2 R ESULTS

3.2.1 Bay Anchovy

Nearly all (97%; n = 235) of the 246 bay anchovy retained on the fine mesh screens of Danskammer Unit 3 and measured for length were less than 54 mm total length (Length Class 1), while only 37% (n = 17) of the 46 bay anchovy caught and measuredfrom the standard mesh screens of Unit 4 were of this small size (Table 3-2). These observations s uggest that about two-thirds of the bay anchovy of

the size retained on the fine mesh screens would have been entrained through the standard meshIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 22 Normandeau Associates, Inc. screen. If avoidance is considered comparable for the small, Length Class 1 bay anchovy in the combined impingement collections from Unit 3 and Unit 4 of Danskammer, and both Units are considered sampling the same source population, then 93% of the bay anchovy less than 54 mm total length were retained on the 3.2 mm fine mesh conve ntional traveling screens compared to just 7% for the standard 9.5 mm mesh conventional traveling screen s (Table 3-3). Low initial (time 0) survival of the total catch of bay anchovy on both standard a nd fine mesh screens (Tables 3-4, 3-5, and 3-6), compounded with low numbers from Unit 4, indicate that both fine mesh and standard mesh screens

tested at Danskammer exhibited extr emely low survival for bay anchov y, particularly when compared to the survival for this species fro m the fish conservation Ristroph traveling screens and a state of the art fish return system like the one presently installed and operated at Indian Point (Table 3-7; Fletcher 1990).

3.2.2 Striped Bass

Nearly all (94%; n = 381) of the 404 striped bass retained on the fine mesh screens of Danskammer Unit 3 and measured for length were less than 42 mm total length (Length Class 1), while nearly all (82%; n = 223) of the 272 striped bass caught and measured from the standard mesh screens of Unit 4 were large fish in Length Class 2 (Table 3-2). Th ese observations suggest that most striped bass of

the size retained on the fine mesh screens would have been entrained through the standard mesh screen. If avoidance is considered comparable for the small, Length Class 1 striped bass in the combined impingement collections from Unit 3 and Unit 4 of Danskammer, and both Units are considered sampling the same source population, then 89% of the striped bass less than 42 mm total length were retained on the 3.2 mm fine mesh c onventional traveling screens compared to just 11% for the standard 9.5 mm mesh conventional traveling screens (Table 3-3).

The initial (time 0) survival of the striped bass less than 42 mm total length impinged on both standard and fine mesh screens were nearly identi cal (34% at Unit 3 vs. at 35% Unit 4; Table 3-5), while the extended (time 96) survival of these Lengt h Class 1 fish was higher for the fine mesh screen (17%) compared to the standard mesh screen (8%). The initial (time 0) survival rates of the striped bass greater than or equal to 42 mm total length impinged on both standard and fine mesh screens were also nearly identical (77% Unit 3 vs. 75% unit 4; Table 3-6), while the extended (time 96) survival of these Length Class 1 fish was higher for the fine mesh screens (39%) compared to the standard mesh screens (11%). The absolute surv ival was higher for striped bass impinged on fish conservation traveling screens and a state of the art fish return system like the one presently installed and operated at Indian Point (Table 3-7; Fletch er 1990), and the results from the Danskammer fine mesh impingement study suggest that comparable or higher survival could be achieved for the small fish of a size that would be entrained through the standard mesh screens but retained on a 3.2 mm fine mesh traveling screens.

3.2.3 White Perch

Slightly more than half (55%; n = 529) of the 956 white perch retained on the fine mesh screens of Danskammer Unit 3 and measured for length were less than 42 mm total length (Length Class 1), while nearly all (95%; n = 3,243) of the 3,420 white perch caught and measured from the standard mesh screens of Unit 4 were large fish in Length Class 2 (Table 3-2). These observations suggest that most white perch of the size retained on the fine mesh screens would have been entrained through the

standard mesh screen. If avoidance is considered comparable for the small, Length Class 1 white perch in the combined impingement collections from Unit 3 and Unit 4 of Danskammer, and bothIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 23 Normandeau Associates, Inc. Units are considered sampling the same source popula tion, then 75% of the white perch less than 42 mm total length were retained on the 3.2 mm fine mesh conventional traveling screens compared to 25% for the standard 9.5 mm mesh conventional traveling screens (Table 3-3).

The initial (time 0) survival of the white perch less than 42 mm total length impinged on the fine mesh screens of Unit 3 was lower (18%) compared to the standard mesh screens on Unit 4 (44%; Table 3-5). The extended (time 96) survival of these Length Class 1 white perch was higher for the fine mesh screen (12%) compared to the standard mesh screen (5%; Table 3-5). The initial (time 0) survival of the white perch greater than or equa l to 42 mm total length impinged on the fine mesh screens was also lower (53%) compared to the st andard mesh screens on Unit 4 (87%; Table 3-6), while the extended (time 96) survival of these Le ngth Class 1 fish was comparable for both screens (22% at Unit 3 vs. 19% at Unit 4; Table 3-6). The absolute survival was higher for white perch impinged on fish conservation Ristroph traveling scree ns and a state of the art fish return system like the one presently installed and opera ted at Indian Point (Table 3-7; Fletcher 1990), and the results from the Danskammer fine mesh impingement study s uggest that comparable or lower survival could

be achieved for the small fish of a size that would be entrained through the standard mesh screens but retained on a 3.2 mm fine mesh traveling screens.

3.2.4 Clupeids

Nearly two-thirds (63%; n = 754) of the 1,189 clupeids retained on the fine mesh screens of Danskammer Unit 3 and measured for length were less than 42 mm total length (Length Class 1), while nearly all (96%; n = 2,622) of the 2,732 cl upeids caught and measured from the standard mesh screens of Unit 4 were large fish greater than or equal to 42 mm total length in Length Class 2 (Table 3-2). These observations suggest that most clupeid s of the size retained on the fine mesh screens would have been entrained through the standard m esh screen. If avoidance is considered comparable for the small, Length Class 1 clupeids in the comb ined impingement collections from Unit 3 and Unit
4 of Danskammer, and both Units are considered sampling the same source population, then 87% of the clupeids less than 42 mm total length were retained on the 3.2 mm fine mesh conventional traveling screens compared to just 13% for the standard 9.5 mm mesh conventional traveling screens (Table 3-3). Low initial (time 0) survival of the total catch of clupeids on both standard and fine mesh screens (Tables 3-4, 3-5, and 3-6), indicat es that these fragile fish do not survive well from either fine mesh or standard mesh traveling scr eens at Danskammer compared to fish conservation Ristroph traveling screens and a state of the art fish return system like the one presently installed and operated at Indian Point (Table 3-7; Fletcher 1990).

3.2.5 All Other Fish Taxa

Slightly more than half (54%; n = 211) of the 394 fish of 22 taxa comprising the all other fish taxa category retained on the fine mesh screens of Danskammer Unit 3 and measured for length were less than 42 mm total length (Length Class 1), while nearly all (94%; n = 1,171) of the 1,250 all other fish taxa caught and measured from the standard mesh screens of Unit 4 were large fish in Length Class 2 (Table 3-2). These observations suggest that most of the all other fish taxa of the size retained on the

fine mesh screens would have been entrained thro ugh the standard mesh screen. If avoidance is considered comparable for the small, Length Class 1 all other fish taxa in the combined impingement
collections from Unit 3 and Unit 4 of Danskammer, a nd both Units are considered sampling the same source population, then 73% of the these fish less th an 42 mm total length were retained on the 3.2IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 24 Normandeau Associates, Inc. mm fine mesh conventional traveling screens compared to 27% for the standard 9.5 mm mesh conventional traveling screens (Table 3-3).

The initial (time 0) survival of the all other fish taxa less than 42 mm total length impinged on the fine mesh screens of Unit 3 was lower (45%) compar ed to the standard mesh screens on Unit 4 (82%; Table 3-5). The extended (time 96) survival of th ese Length Class 1 all other fish taxa for the fine mesh screen (38%) remained slightly more than ha lf of the latent survival for the standard mesh screen (71%; Table 3-5). The initial (time 0) survival of the all other fish taxa greater than or equal to 42 mm total length impinged on the fine mesh scr eens was also lower (67%) compared to the standard mesh screens on Unit 4 (93%; Table 3-6), and the extended (time 96) survival of these Length Class 2 fish remained lower for the fine mesh screens (49% Unit 3 vs. 61% Unit 4; Table 3-6). The absolute survival was higher for all other fi sh taxa impinged on fish conservation traveling screens and a state of the art fish return system lik e the one presently installed and operated at Indian Point (Fletcher 1990), and the results from the Da nskammer fine mesh impingement study suggest that comparable or lower survival could be achie ved for the small fish of a size that would be entrained through the standard mesh screens but re tained on a 3.2 mm fine mesh traveling screens.

3.2.6 All Fish Taxa Combined

Ignoring the differences in survival by fragile and hardy fish species identified by taxon in the Danskammer study, examination of the entire fish community sampled during the 1988 study revealed that two-thirds (66%; n = 2,110) of the 3, 185 fish in the aggregate community of small fish represented by Length Class 1 were retained on th e fine mesh screens of Danskammer Unit 3 and measured for length (Table 3-2). Nearly all (94%; n = 7,288) of the 7,720 fish caught and measured

from the standard mesh screens of Unit 4 were la rge fish in Length Class 2 (Table 3-2). These observations suggest that most of the fish of the size retained on the fine mesh screens would have been entrained through the standard mesh screen. If avoidance is considered comparable for the small, Length Class 1 fish in the combined impingement collections from Unit 3 and Unit 4 of Danskammer, and both Units are considered sampli ng the same source population, then 83% of the small fish in Length Class 1were retained on the 3.2 mm fine mesh conventional traveling screens compared to just 17% for the standard 9.5 mm me sh conventional traveling screens (Table 3-3).

The all fish taxa combined category exhibited a re latively low initial (time 0) survival (17%; n = 357) of the 2,110 small fish represented by Length Class 1 th at were impinged on the fine mesh screens of Unit 3 compared to 37% initial survival for Lengt h Class 1 fish impinged on the standard mesh screens of Unit 4 (160 fish out of 432 total fish = 37%; Table 3-5). The extended (time 96) survival of these Length Class 1 fish was also lower for the fi ne mesh screen (10%) compared to the standard mesh screen (16%; Table 3-5). The initial (time 0) survival of the all fish taxa combined category of larger Length Class 2 fish impinged on the fine mesh screens was also lower (45%) compared to the standard mesh screens on Unit 4 (59%; Table 3-6), while the extended (time 96) survival of these Length Class 2 fish was comparable for both screens (18% Unit 3 vs. 18% Unit 4; Table 3-6). The absolute survival was higher for all fish taxa (combined) impinged on fish conservation traveling screens and a state of the art fish return system lik e the one presently installed and operated at Indian Point (Fletcher 1990), and the results from the Da nskammer fine mesh impingement study suggest that comparable survival could be achieved for th e small fish of a size that would be entrained through the standard mesh screens but retain ed on a 3.2 mm fine mesh traveling screens.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 25 Normandeau Associates, Inc. 

### 3.3 R EFERENCES

EPRI (Electric Power Research Institute). 2000. Technical evaluation of the utility of intake approach velocity as an indicator of poten tial adverse environmental impact under Clean Water Act Section 316(b). Report 1000731.

Fletcher, R.I. 1990. Flow dynamics and fish recovery experiments: water intake systems. Transactions of the American Fisheries Society 119: 393-415.

Normandeau (Normandeau Associates, Inc.). 19 88a. Danskammer Point Station fine mesh screen evaluation – 1986 study. Prepared for Ce ntral Hudson Gas and Electric Corporation.

Normandeau (Normandeau Associates, Inc.). 1988b. Standard operating procedures for the

1986/1988 Danskammer Point Station fine mesh screen evaluation. Prepared for Central Hudson Gas and Electric Corporation.

Normandeau (Normandeau Associates, Inc.). 19 89. Danskammer Point Station fine mesh screen evaluation – 1988 Study. Prepared for Ce ntral Hudson Gas and Electric Corporation.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 26 Normandeau Associates, Inc. Figure 3-1. Adjusted (for differences in volume sampled) length frequency distributions for fish impinged on the 3.2 mm fine mesh conventional traveling screens at Danskammer Unit 3 and the 9.5 mm standard mesh conventional traveling screens at Unit 4, 1 May through 23 August 1988. Unit 3 Unit 4Adjusted Count

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,20 0

Length10-19 mm20-29 mm30-39 mm40-49 mm50-59 mm60-69 mm70-79 mm80-89 mm90-99 mm100-109 mm110-119 mm120-129 mm130-139 mm140-149 mm150-159 mm160-169 mm170-179 mm180-189 mm190-199 mm200 + mmIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 27 Normandeau Associates, Inc. Figure 3-2. Relative (percent) adjusted length frequency distributions for fish impinged on the 3.2 mm fine mesh conventional traveling screens at Danskammer Unit 3 and the 9.5 mm standard mesh conventional traveling screens at Unit 4, 1 May through 23 August 1988. Unit 3 Unit 4Relative (Percent) Frequency

0 10 20 30 40 50 60 70 80 90 10

0

Length10-19 mm20-29 mm30-39 mm40-49 mm50-59 mm60-69 mm70-79 mm80-89 mm90-99 mm100-109 mm110-119 mm120-129 mm130-139 mm140-149 mm150-159 mm160-169 mm170-179 mm180-189 mm190-199 mm200 + mmIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 28 Normandeau Associates, Inc. Figure 3-3. Cumulative relative length frequency distributions for fish impinged on the 3.2 mm fine mesh conventional traveling screens at Danskammer Unit 3 and the 9.5 mm standard mesh conventional traveling screens at Unit 4, 1 May through 23 August 1988. Unit 3 Unit 4Cumulative Relative(Percent) Frequency

0 10 20 30 40 50 60 70 80 90 10

0

Length10-19 mm20-29 mm30-39 mm40-49 mm50-59 mm60-69 mm70-79 mm80-89 mm90-99 mm100-109 mm110-119 mm120-129 mm130-139 mm140-149 mm150-159 mm160-169 mm170-179 mm180-189 mm190-199 mm200 + mmIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 29 Normandeau Associates, Inc. Table 3-1. Results of the Danskammer fine mesh traveling screen impingement survival study, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit Total

Number

Collected Number Dead

at 0 Hours Number Held

for 96 Hours Total Percent Alive at Observation Time in Hours

0 2.5 8 12 24 48 96

Bay anchovy 3 137 134 3 0.7% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

4 45 45 0 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Striped bass 3 226 141 85 32.3% 25.7% 23.9% 23.5% 23.0% 21.2% 19.0%

4 276 87 189 43.8% 40.9% 31.9% 29.7% 24.3% 16.7% 10.5%

White perch 3 544 357 187 23.5% 22.1% 20.2% 20.0% 19.1% 17.1% 16.9%

4 3474 516 2958 41.8% 40.3% 36.6% 35.8% 31.1% 23.0% 18.0%

Clupeids 3 679 591 88 2.5% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0%

4 2754 2551 203 0.7% 0.5% 0.5% 0.2% 0.2% 0.2% 0.0%

All others 3 236 100 136 48.7% 48.7% 49.2% 48.3% 47.5% 45.8% 41.9%

4 1317 96 1221 74.4% 73.7% 73.1% 73.7% 72.9% 67.7% 59.6%

Total 3 1822 1323 499 18.3% 16.1% 15.4% 15.1% 14.7% 13.7% 12.8%

4 7866 3295 4571 32.7% 31.8% 29.7% 29.2% 26.9% 22.1% 18.3%IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 30 Normandeau Associates, Inc. Table 3-2. Number and percent of fish collected in Length Class 1 (representing the

fraction of small fish retained on the fine mesh screen of Unit 3 but not on the standard mesh screen of Unit 4) and Length Class 2 (representing the fraction of large fish retained on both the fine mesh and standard mesh screens) for which length was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit Number of Fish Measured Percent Caught by Length Class

All Fish Caught Length

Class 1 Length

Class 2 Length

Class 1 Length

Class 2 Bay anchovy 3 242 235 7 97.1% 2.9%

4 46 17 29 37.0% 63.0% Striped bass 3 404 381 23 94.3% 5.7%

4 272 49 223 18.0% 82.0% White perch 3 956 529 427 55.3% 44.7%

4 3,420 177 3,243 5.2% 94.8% Clupeids 3 1,189 754 436 63.4% 36.7%

4 2,732 110 2,622 4.0% 96.0%

All other taxa 3 394 211 183 53.6% 46.4%

4 1,250 79 1,171 6.3% 93.7%

All taxa 3 3,185 2,110 1,075 66.2% 33.8%

4 7,720 432 7,288 5.6% 94.4%IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 31 Normandeau Associates, Inc. Table 3-3. Number and percent of fish collected in Length Class 1 (representing the

fraction of small fish retained on the fine mesh screen of Unit 3 but not on the standard mesh screen of Unit 4) that contributed to the combined impingement collection from both Units, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit Number in Length Class 1 Percent in Length Class 1 Bay anchovy 3 235 93.3%

4 17 6.7%

Both 252 100.0% Striped bass 3 381 88.6%

4 49 11.4%

Both 430 100.0% White perch 3 529 74.9%

4 177 25.1%

Both 706 100.0% Clupeids 3 754 87.3%

4 110 12.7%

Both 864 100.0%

All other taxa 3 211 72.8%

4 79 27.2%

Both 290 100.0%

All taxa 3 2,110 83.0%

4 432 17.0%

Both 2,542 100.0%IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 32 Normandeau Associates, Inc. Table 3-4. Number of fish and percent impingement survival for all fish for which length was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit All Fish Regardless of Size Class

Number of Fish Percent Alive

Alive

Time 0 Alive

Time 96 All Fish Caught Time 0 Time 96

% SE % % SE % Bay anchovy 3 2 0 242 0.7 0.5 0.0

4 0 0 46 0.0 0.0 Striped bass 3 148 76 404 36.5 2.4 18.7 1.9

4 185 29 272 68.0 2.8 10.7 1.9 White perch 3 322 158 956 33.6 1.5 16.5 1.2

4 2,906 618 3,420 85.0 0.6 18.1 0.7 Clupeids 3 156 0 1,189 13.1 1.0 0.0

4 208 0 2,732 7.6 0.5 0.0

All other taxa 3 218 170 394 55.4 2.5 43.3 2.5

4 1,150 769 1,250 92.0 0.8 61.5 1.4

All taxa 3 845 404 3,185 26.5 0.8 12.7 0.6

4 4,449 1,416 7,720 57.6 0.6 18.3 0.4IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 33 Normandeau Associates, Inc. Table 3-5. Number of fish and percent impingement survival for Length Class 1 representing the fraction of small fish retained on the fine mesh screen (Unit 3) but not on the standard mesh screen (Unit 4) for which length was determined, adjusted for differences in intake flow between Danskammer Point Station Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit Small Fish Retained on Fine Mesh But Not On Standard Mesh (Length Class 1)

Number of Fish Percent Alive

Alive

Time 0 Alive

Time 96 All Fish Caught Time 0 Time 96

% SE % % SE %
Bay anchovy 3 2 0 235 0.7 0.6 0.0

4 0 0 17 0.0 0.0 Striped bass 3 130 67 381 34.1 2.4 17.5 1.9

4 17 4 49 34.7 6.8 8.2 3.9 White perch 3 93 65 529 17.6 1.7 12.3 1.4

4 78 9 177 44.1 3.7 5.1 1.7 Clupeids 3 37 0 754 4.9 0.8 0.0

4 0 0 110 0.0 0.0

All other

taxa 3 95 81 211 45.0 3.4 38.3 3.3

4 65 56 79 82.3 4.3 70.9 5.1

All taxa 3 357 213 2,110 16.9 0.8 10.1 0.7

4 160 69 432 37.0 2.3 16.0 1.8IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 34 Normandeau Associates, Inc. Table 3-6. Number of fish and percent impingement survival for Length Class 2 representing the fraction of large fish retained on both the fine mesh and standard mesh screens for which length was determined, adjusted for differences in intake flow between Unit 3 and Unit 4, 1 May – 23 August 1988. (Unit 3 = 3.2 mm fine mesh, Unit 4 = 9.5 mm standard mesh).

Fish Taxon Unit Large Fish Retained on both Fine Mesh and Standard Mesh (Length Class 2)

Number of Fish Percent Alive

Alive

Time 0 Alive

Time 96 All Fish Caught Time 0 Time 96

% SE % % SE % Bay anchovy 3 0 0 7 0.0 0.0

4 0 0 29 0.0 0.0 Striped bass 3 18 9 23 76.9 8.8 38.5 10.2

4 168 25 223 75.3 2.9 11.2 2.1 White perch 3 228 93 427 53.5 2.4 21.8 2.0

4 2,828 609 3,243 87.2 0.6 18.8 0.7 Clupeids 3 119 0 436 27.4 2.1 0.0

4 208 0 2,622 7.9 0.5 0.0

All other taxa 3 123 90 183 67.3 3.5 49.0 3.7

4 1,085 713 1,171 92.7 0.8 60.9 1.4

All taxa 3 488 192 1,075 45.4 1.5 17.8 1.2

4 4,289 1,347 7,288 58.9 0.6 18.5 0.5IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 35 Normandeau Associates, Inc. Table 3-7. Comparison of 8-hour survival (percent alive) and the total number of fish collected (N Total) for common fish impinged on the Danskammer Point Station fine mesh conventional traveling screens at Unit 3 (3.2 mm), the standard mesh traveling screens at Unit 4 (9.5 mm) tested between 1 May and 23 August 1988, and the Ristroph screen version 2 installed and tested at Indian Point Unit 2, screen well 26 during 16 September through

24 October 1986.

Taxon Danskammer Indian Point Ristroph 1

Unit 3 Fine Mesh Unit 4 Standard Mesh Unit 2

N Total % Alive N Total % Alive N Total % Alive
Bay anchovy 137 0.0% 45 0.0% 1,060 77%
Striped bass 226 23.9% 276 31.9% 86 91%
White perch 544 20.2% 3,474 36.6% 1,806 86%

American shad 51 0.0% 724 0.0% 169 65%

Blueback herring 183 0.0% 1,598 0.8% 277 74%

1 Data source: Fletcher (1990) Table 4 cumulative dead and injured after 8 hours.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 36 Normandeau Associates, Inc. 

## 4.0 L OVETT 

## G UNDERBOOM 

## E FFECTIVENESS AND 

## M ESH 

## S ELECTIVITY 

## A NALYSIS



### 4.1 A PPROACH

The AFB is a relatively new fish protection technol ogy for use at CWISs to meet Clean Water Act §316(b) performance requirements (EPA 2004). While th e AFB is permeable to water, it is relatively impermeable to fish, shellfish, a nd ichthyoplankton and, therefore, is one of only a few technologies capable of reducing both impingement and entr ainment of aquatic organisms (EPA 2004). Gunderboom has a patented full-water-depth f ilter curtain composed of polyethylene or polypropylene fabric panels that is supported by flotation billets at the surface of the water and anchored to the bottom of the water body (LMS 1998b, 2005). This AFB system is referred to as the Gunderboom Marine Life Exclusion SystemTM (Gunderboom MLESTM). The Gunderboom MLESTM completely surrounds a CWIS, preventing organisms from entering the intake. Since the surface area of an MLESTM is large compared to the surface ar ea of the intake structure’s traveling screens, through-screen water velocity can be reduced to belo w 0.5 fps, thereby enabling even small fish and larvae to swim or drift away from the filter curtain.

The engineering performance of a Gunderboom MLESTM was evaluated at Lovett Generating Station (“Lovett”) in each year 1994 through 2002 with the objectives of designing, installing and testing a full scale system that could be installed and reliabl y operated at Lovett Station to exclude fish eggs and larvae from entrainment into Lovett’s cooling water intake system (CWIS) (LMS 1996, 1997, 1998a, 1998b, 2005). Biological effectiveness testing began in 2003 with an evaluation of sampling methodology and techniques (ASA 2003), followed by four consecutive years of complete seasonal sampling from May through October of 2004, 2005, 2006, and 2007 (ASA 2004, 2005, 2006, 2007). Lovett ceased operation in 2008 and was dismantled.

Lovett consisted of three fossil-fueled, steam electri c units (Units 3, 4, a nd 5) having net generating capacities of 63 megawatts of electric power (M We), 197 MWe, and 202 MWe, respectively, for a

total of 463 MWe for all three units combined. The once through design cooling water intake flows were 42,000 gpm for Unit 3, 104,300 gpm for Unit 4, and 112,000 gpm for Unit 5, for a total of 258,300 gpm. Cooling water for each of the three Lovett units was withdrawn from the Hudson River estuary through shoreline intakes equipped with c onventional 3/8-inch mesh traveling screens. The

AFB installed and tested at Lovett was made from two layers of non-woven fabric (LMS 1998b) that encircled the shoreline bulkhead containing the CWISs for Unit 3, Unit 4, and Unit 5. The outer layer had 0.5 mm diameter perforations spaced on-center at 6.4 mm, and the inner layer was vented with horizontal 5.1 cm flaps spaced at 0.6 m (LMS 1998b).

Biological effectiveness was determined by comp aring the percent difference in density of entrainment-sized ichthyoplankton from pairs of pum ped samples collected inside and outside of a deployed AFB enclosing the Lovett CWIS. Lovett Station was located on the west bank of the Hudson River estuary just north of Stony Point, New York, 41 miles upstream from the southern tip of Manhattan in New York City. Lovett was sli ghtly downstream and almost directly across the
Hudson River from Indian Point, which is located on the east bank at mile point 42. Accordingly, both Lovett and Indian Point are exposed to the same source water body population of ichthyoplankton during the same seasonal cycle and ar e likely to experience similar entrainment intoIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 37 Normandeau Associates, Inc. the CWISs of each plant. Therefore, the Gunderboo m system tested at Lovett Station was considered a likely surrogate for the effectiv eness and selectivity of a similar system if designed, installed and operated at Indian Point as an alternative technol ogy for impingement and entrainment mitigation.



### 4.2 R ESULTS

The four reports regarding the biological effec tiveness of the AFB evaluated at Lovett (ASA 2004, 2005, 2006, and 2007) describe the sampling designs and methods specified in the project-specific Standard Operating Procedures (LMS 2005). These Standard Operating Procedures, which assured consistency of methods among years, are briefly summarized in this report. Five pairs of ichthyoplankton samples of an average volume of about 70 m 3 each were collected during two nights per week by pumping for 60-75 minutes at 200-240 gpm in the protected (from entrainment) water on the intake side of the deployed AFB and in an ad jacent area outside of the AFB beginning in May and continuing through August of each year. One night was sampled every other week from early September through mid-October of each year. The sa mples from the intake side of the deployed AFB were considered representative of the “test” loca tion, and the samples from the river side were considered the “control” location (5 test and 5 c ontrol samples per night). All samples were filtered through a 505 micron net suspended in a barrel sa mpler, preserved in 10% buffered formalin, and processed in the laboratory to inde ntify and enumerate the ichthyoplankton species collected in four life stage categories: eggs, yolk sac larvae, post yolk sac larvae, and juveniles. Length (mm total length) was measured for a random subsampl e of up to 25 larvae and juveniles of each ichthyoplankton taxon in each test or control sampl e. In addition to the nighttime sampling, three pairs of daytime samples were collected one day each week from June through August. The final achieved sampling designs for each year , 2004 through 2007, were as follows:

Year Sampling Dates Number of Samples
Start End Day Night Total

2004 10-May 15-Oct 24 358 382
2005 28-Apr 13-Oct 24 392 416
2006 22-May 13-Oct 18 324 342
2007 27-May 15-Oct 18 320 338
2004-07 28-Apr 15-Oct 84 1,394 1,478

Post yolk sac larvae was the dominant life stage in a ll samples, contributing 91% (2,380) of the total ichthyoplankton collected at the test location (2,619) and 94% (17,661) of the total ichthyoplankton

collected at the control location (18,730) over the four-year study.

The Lovett AFB evaluation focused on six target ta xa: striped bass, white perch, river herring (alewife and blueback herring), ba y anchovy, American shad, and A tlantic tomcod. However, only the first four taxa were caught in sufficient numbers to estimate the exclusion effectiveness.

The AFB system installed and operated at Lovett during 2004 through 2007 exhibited an average exclusion effectiveness of 79% for all species and life stages of ichthyoplankton combined, with inter-annual variation ranging from a low of 40% in 2004 to a high of 95% in 2007 (Table 1). The Lovett AFB was estimated to exclude, on average among the four years, 89% of the bay anchovy (inter-annual range 68% to 100%), 89% of the striped bass (inter-annual range 85% to 94%), 85% ofIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 38 Normandeau Associates, Inc. the white perch (inter-annual range 62% to 97%), a nd 52% of the river herring (inter-annual range of -57% to 99%) over the four years of testing.

The Lovett AFB system did not exhibit size selec tivity in its exclusion efficiency during 2004 through 2007. Kolmogorov-Smirnov two-sample tests (Siegel 1956; SAS 2003) of the standardized (percent) length-frequency distributions from the ic hthyoplankton collected and measured from both the test and control locations were not significantl y different (p>0.05) indicating no size selectivity of the AFB for all taxa combined (p>KSa = 0.9375), or for bay anchovy (p>KSa = 0.8079), striped bass (p>KSa = 0.8186), white perch (p>KSa = 0.8186), an d river herring (p>KSa = 1.0000). Figure 1 illustrates the absence of statistically significant si ze selectivity by comparing the length frequency of

all taxa collected and measured in one millimeter length groups from the test and control locations during the 2004 through 2007 study.

A likely explanation for the absence of significant size selectivity of the Lovett AFB is that the effective mesh opening of the non-woven outer layer (0 .5 mm) was typically smaller than the smallest (i.e. “limiting”) dimensions of the fish eggs and larvae exposed to entrainment at the Lovett CWIS. The table below compares the length range and great est body depth range for bay anchovy, striped bass, white perch and river herring larvae from me asurements taken in Indian Point entrainment samples (1983-1987), and demonstrates that nearly all of the larvae of fish taxa exposed to the Lovett AFB were considerably larger than 0.5 mm in limiting body dimensions.

Larval Fish Taxon Total Length Range (mm) Greatest Body Depth Range (mm)

Bay anchovy 1.8-42 0.2-7.1
Striped bass 3.2-56 0.5-10.6
White perch 2.0-90 0.3-22
River herring 3.3-59.7 0.2-13.2

As a result, ichthyoplankton appearing inside th e deployed Lovett AFB and sampled at the test location would likely have originated in unfiltered water from the control location outside of the AFB that had entered by either overtopping, underflow, or by other means indicating partial failure of the deployment. Unfiltered water sampled at the test lo cation would be expected to have the same length frequency of ichthyoplankton as water sampled at th e control location, because the water did not pass through the mesh openings where size selectivity wo uld occur. Some ichthyoplankton sampled inside the deployed AFB at Lovett may also have originated from individuals trapped inside during deployment, depending on when deployment occu rred relative to the onset of the spawning season (May) for most species of Hudson River fishes. When the AFB was deployed at Lovett in late April (2005) or early May (2004), which was prior to th e spawning season, the first weekly samples from

both inside and outside the filter barrier exhib ited zero densities of icht hyoplankton (ASA 2004, 2005). However, when the Lovett AFB was deploy ed during the spawning season in late May of 2006 and 2007, the first weekly samples from both in side and outside of the filter barrier contained ichthyoplankton (ASA 2006, 2007).

The 79% overall average percent effectiveness and the absence of size selectivity both suggest that performance of the Lovett AFB is directly related to its time of deployment with respect to the Hudson River fish spawning season, the proportion of th e total intake flow drawn directly through theIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 39 Normandeau Associates, Inc. filtration mesh, and the density of ichthyoplankton in the volume of unfiltered water drawn into the intake when deployment fails.



### 4.3 R EFERENCES

ASA Analysis and Communication, Inc. (ASA). 2003. Gunderboom MLESTM Evaluation Study at the Lovett Generating Station - Results of 2003 Biological Monitoring. Prepared for Mirant New York, Inc.

ASA Analysis and Communication, Inc. (ASA). 2004. Gunderboom MLESTM Evaluation Study at the Lovett Generating Station - Results of 2004 Biological Monitoring. Prepared for Mirant Lovett, LLC.

ASA Analysis and Communication, Inc. (ASA). 2005. Gunderboom MLESTM Evaluation Study at the Lovett Generating Station - Results of 2005 Biological Monitoring. Prepared for Mirant Lovett, LLC.

ASA Analysis and Communication, Inc. (ASA). 2006. Gunderboom MLESTM Evaluation Study at the Lovett Generating Station - Results of 2006 Biological Monitoring. Prepared for Mirant Lovett, LLC.

ASA Analysis and Communication, Inc. (ASA). 2007. Gunderboom MLESTM Evaluation Study at the Lovett Generating Station - Results of 2007 Biological Monitoring. Prepared for Mirant Lovett, LLC.

EPA (U.S. Environmental Protection Agency). 2004. National Pollutant Discharge Elimination System—final regulations to establish requireme nts for cooling water intake structures at Phase II existing facilities. 40 CFR Parts 9, 12 2, 123, 124, and 125. Federal Register 69(131): 41756-41693.

Lawler, Matusky, and Skelly Engineers (LMS). 1996. Lovett Generating Station Gunderboom System Evaluation Program 1995. Prepared for Orange and Rockland Utilities, Inc.

Lawler, Matusky, and Skelly Engineers (LMS). 1997. Lovett Generating Station Gunderboom System Evaluation Program 1996. Prepared for Orange and Rockland Utilities, Inc.

Lawler, Matusky, and Skelly Engineers (LMS). 1998a. Lovett Generating Station Gunderboom System Evaluation Program 1997. Prepared for Orange and Rockland Utilities, Inc.

Lawler, Matusky, and Skelly Engineers (LMS). 1998b. Lovett Generating Station Gunderboom System Evaluation Program 1998. Prepared for Orange and Rockland Utilities, Inc.

Lawler, Matusky, and Skelly Engineers (LMS). 2005. Biological Monitoring Program Related to the

Effectiveness Evaluation of the Lovett Ge nerating Station Gunderboom Marine Life Exclusion System (MLES). Prepared for Mirant Lovett, LLC.

SAS Institute, Inc. (SAS). 2003. The data analys is was generated using SA S software, Version 9 of the SAS System for Windows. Copyright © (2002-2003) SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.

Siegel, S. 1956. Nonparametric statistics for th e behavioral sciences. McGraw-Hill Book Company, Inc. 312 p.

Sokal, R.R., and F.J. Rohlf. 1969. Biometry. The principals and practice of statistics in biological research. W.H. Freeman and Company. 776 p.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 40 Normandeau Associates, Inc. 

### Lovett Gunderboom Size Selective Exclusion Effectiveness for All Fish Species 2004-2007

0% 5% 10% 15% 20% 25% 30% 35%

1 3 5 7 9 11 1 3 15 17 1 9 2 1 23 25 2 7 2 9 31 33
Length Group (mmtl) Test (n=439)

Control (n=2459)

Figure 4-1. Length Frequency (one mm length groups) of all larval fish taxa combined collected by simultaneous pairs of samples taken inside (test) or outside (control) of a deployed AFB at Lovett Station on the Hudson River, New York, from May through October 2004, 2005 and 2007 (2006 length data not available).IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 41 Normandeau Associates, Inc. Table 4-1. Summary of annual percent exclusion effectiveness for fish larvae collected by simultaneous pairs of samples taken inside and outside of a deployed AFB at Lovett Station on the Hudson River, New York, from May through October 2004, 2005, 2006 and 2007.

Fish Taxon Year Percent of

Catch Percent

Effectiveness

Bay Anchovy 2004 34% 68%

2005 32% 99%

2006 39% 89%

2007 52% 100%

2004-07 Mean 39% 89%
Striped Bass 2004 35% 85%

2005 43% 94%

2006 21% 90%

2007 22% 88%

2004-07 Mean 30% 89%

White Perch 2004 2% 62%

2005 3% 97%

2006 8% 89%

2007 1% 92%

2004-07 Mean 4% 85%
River Herring 2004 1% -57%

2005 1% 84%

2006 4% 81%

2007 2% 99%

2004-07 Mean 2% 52%
All Species 2004 100% 40%

2005 100% 92%

2006 100% 89%

2007 100% 95%

2004-07 Mean 100% 79%IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 42 Normandeau Associates, Inc. 

## 5.0 V ERIFICATION OF 

## C OMPUTER 

## C ODE



### 5.1 A PPROACH

Three separate SAS programs were subjected to i ndependent QC and verifi cation to validate the estimates of entrainment and impingement reductions for various technology alternatives evaluated for IPEC. The three programs were developed a nd run by Dr. John Young of ASA Communications, Inc. and subjected to QC inspection and verifica tion by Ms. Susan Ward (SAS Programmer) and Mr. Paul Lindsay (Fisheries Scientist) of Norma ndeau. The SAS programs subjected to QC and

verification were as follows:

1. Program 1h (22 September 2009 Revision) , consisting of 6,865 individual programming steps (lines of code) used to estimate current entrainm ent rates and their age 1 equivalents for IPEC based on an association developed between past rates (1983-87) and past in-river densities compared to present rates and present in-river de nsity data for fish e ggs and larvae derived from the Hudson river monitoring program data. The number of lines actually reviewed was
far in excess of 6,865, because line numbers shown in the SAS code are only assigned to original program code and not to the many lines of notes inserted between them by SAS when the program is executed, showing the num bers of observations and variables in the intermediate data sets that were an importan t part of the material inspected during the verification process.

2. Program IP-CollEff1981-1990 (22 September 2009 Revision) , consisting of 187 individual programming steps (lines of code) used to estimate impingement collection efficiency coefficients for application to estimate impingement rates from 1981 through 1990 actual impingement data for IPEC.

3. Program IP-StrataImpByLengthClass 1981-1990 (22 September 2009 Revision) , consisting of 549 individual programming steps (lines of code) used to apply the collection efficiency coefficients developed by Program IP-CollEff1981-1990 to calculate collection efficiency adjusted impingement counts for Unit 2 and Unit 3 of IPEC by year, stratum, and taxon from 1981 through 1990 for IPEC.

The QC and verification was based on independent ch ecks of the written code, input files, and output generated for each SAS program. Each program w as rerun by Normandeau in a single pass (rather than one part at a time) and the results were compar ed to the preliminary analysis, to verify that the same input data were used for the quality control as for the preliminary runs of program steps. The SAS logs (output from SAS documenting the progress of the data input, processing, and output steps) were examined in detail to ascertain the data pathwa ys between the input and output data files. The number of observations reported by these SAS logs in the intervening steps (“work files”) were

reviewed to determine how the data files were ma nipulated with respect to the dimensions of the sampling design (“sort variables”). The internal documentation (“comments” ) and the program code were compared to make sure that they were in agreement and that the calculations are technically sound and performing as intended.

Several sections of the program were tested by independently (i.e. by hand) calculating values from input variables to verify that the results matched the output files produced by the program, to make sure the program was performing as expected.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 43 Normandeau Associates, Inc. No attempt was made to verify the equations or parameters for impingement survival, mechanical
entrainment survival, thermal entr ainment survival, or plant operating data (those are from earlier work that has been reviewed and accepted)—these e quations and parameters were merely verified as producing values (e.g., survival rat es) within reasonable ranges.

Notes were made in a bound copy of the SAS log. The results of the QC and verification process

were summarized in Section 5.0 of Normand eau’s Appendix B report dated January 2010. Calculations made during the QC and verification and additional comments were also documented in Excel files of some of the intermediate data sets (or subsets of them).

Red font in the documentation below indicates potential issues identified by Normandeau for

resolution. Follow-up response by ASA is noted in blue font.



### 5.2 P ROGRAM 

### 1 H



### . SAS 

### (22S EP 

### 09 R EVISION 

### )

5.2.1 Entrainment Section 1—Estimate River Standing Crops for 1983-1987 and

2000-2007

Lines: 13,916-13,990

Input: work.LRSlv345 (72,142 obs.)

Output: work.mean8 (1,687 obs.)

Purpose: Calculate mean density (by taxon year week region strata) and weight by strata volumes to get “standing crop” (by taxon year week), representing a weighted mean density.

Comments: For the 7 taxa, 241 combinations of year/week, and 8 combinations of region/strata there should be 13,496 obs. There are 56 obs. missing because of 8 missing combinations of year/week/region/strata for each of the 7 taxa, causing the missing data as to be counted zero densities in calculating the means.

Follow-up: The 8 missing cells are:

Year Week Region Strata

1984 19 4 1, 2, 3

1984 22 4 2

1984 22 5 2

1985 21 4 1
2001 11 5 2, 3

Although substitution could be done from samp led strata, the infrequent occurrence of missing strata would have only a minor, if any, effect on the results. For instance, in week 11 all taxa except Atlantic tomcod w ould have had zero abundance, thus no bias

would have occurred due to the two strata in region 5 going unsampled. No action

taken.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 44 Normandeau Associates, Inc. 5.2.2 Entrainment Section 2—Estimate Entrainment Densities for 1983-1987

Lines: 14,431-14,437

Input: work.Lv3456 (186,592 obs.)

Output: work.entcheck (16,044 obs.)

Purpose: Calculate daily mean entrainment densiti es and total volumes sampled to verify against annual report tables.

Comments: Compared values for striped bass between work.entcheck and report Table B-2 of the 1987 entrainment abundance report. For some dates the daily volumes are too high and densities are too low because void samples were included in the calculation, causing the void samples to be treated as zero densities in calculating the means. Void samples should be deleted from the analysis. Other daily means differed slightly (by <5%, usually <1%). Those small differences can be attributed to the weighting effect of calculating the means slightly differently th an in the report (due to small differences among sample volumes and whether replicate samples were pooled before averaging the 2-hour periods together). Both averaging methods are defensible and the close similarity of their results justifies the current approach.

Follow-up: For 1985-1987 data, level 3 data were selected to use only USE_CODE = 1 samples. For 1983 and 1984 data, level 5 records were dropped if sample volume was missing or 0. When level 34 (merged level 3 and 4 if r ecord exists in level 3) and level 5 were merged, records were retained only if sample exists in both lv34 and lv5.

Lines: 14,468-14,516

Input: work Lv3456 (186,592 obs.)

Output: out.E02_entweeklyden (651 obs.)

Purpose: Calculate weekly mean entrainment densities.

Comments: Compared values for striped bass in week 24 of 1987 (Sunday 14Jun through Saturday 20Jun) between out.E02_entweeklyden and Table B-2 of the 1987 entrainment abundance report. Values are in agreement (except for very small rounding errors).

Lines: 14,616

Input: out.entweeklyden (837 obs.)

Output: printout of that file

Comments: This is an old file name from a prior version of the program (the updated out.E02_entweeklyden has 651 obs.). The sub sequent analysis is not affected because it doesn’t use out.entweeklyden (this print step can be ignored).IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 45 Normandeau Associates, Inc. 5.2.3 Entrainment Section 3—Relationship of Entrainment Density to Standing Crop

Lines: 14,750-15,199

Input: out.E02_entweeklyden (651 obs.) out.E01_LRSweeklycrop (1,687 obs.)

Output: out.E03_entriverout (364 obs.) out.E03_predparms (28 obs.)

Purpose: Use geometric mean regression to rela te river standing crop in regions 3-5 with entrainment densities by taxon stage week during 1983-1987 when the two programs coincided; substitute the ratio of the means from the two programs when regression

was unsuccessful.

Comments: The program code is consistent w ith the stated method (did not attempt to independently run the regressions)

5.2.4 Entrainment Section 4—Predict 2000-2007 Entrainment Densities

Lines: 15,327-15,476

Input: out.E01_LRSweeklycrop (1,687 obs .) and out.E03_predparms (28 obs.)

Output: out.E04_ent_00_07 (5,549 obs.)

Purpose: Estimate weekly standing crops for 2000-2007 by linear interpolation for unsampled weeks between the first and last weekly occurrence by taxon stage year and combine the resulting data sets with the parameters developed in entrainment step 3 to estimate

entrainment densities for 2000-2007.

Comments: Independently calculated weekly stripe d bass entrainment densities for all four life stages using data from the input files, and th en compared the values with those in the output file. The values agreed exactly.

5.2.5 Entrainment Section 5—Estimate 2000-2007 Entrainment Length-Frequencies

Lines: 15,507-15,536

Input: out.E02_entlenfreq (3,426 obs.)

Output: work.weeklyLF (1,435 obs.)

Purpose: Calculate proportion in each length cl ass by taxon stage week for all years of

entrainment measurement data combined.

Comments: Independently calculated weekly lengt h class proportions for striped bass PYSL using the input data and compared them to several values in the output file out.E05_entdenlen. The values agreed exactly.

Lines: 15,538-15,647

Input: work.weeklyLF (1435 obs.)

Output: work.weeklyLFlags (27,153 obs.)

Purpose: Use length class proportions from the first and last weeks of the entrainment data set (weeks 18 and 29) to estimate proportions in weeks before and after those weeks.

Comments: Examined several values for striped b ass in the output file out.E05_entdenlen for weeks <18 and >29. They all cont ained the appropriate values.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 46 Normandeau Associates, Inc. 5.2.6 Entrainment Section 6—Create Flow Data Sets

Lines: 15,740-15,902

Input: old.ipopdata (3,288 obs.)

Output: out.E06_flow (9,864 obs.)

Purpose: Plant flows for scaling up entrainment densities to numbers entrained.

Comments: Examined a subset of the output file (2003 values only). U1SWflow is always zero for case 0 (baseline). For 26Oct 03, U2CWflow exceeds the capacity flow for all 6 pumps running for 24 hours.

Follow-up: U1SWflow reset to 16,000 gpm for baseline case. Data for 26Oct03 are somewhat high for all unit 1 and 2 flows and for MW variables for both units. However, values are not high enough to distort the analysis.

5.2.7 Entrainment Section 7—Survival and Exclusion Parameter Values

Lines: 15,927-16,259

Input: excldata.csv (345 obs. from Norm andeau’s mesh exclusion analysis) other parameters input as “cards” or by program code

Output: out.E07_casedefs (23 obs.) out.E07_entsurv (476 obs.) out.E07_excludesurv (576 obs.) out.E07_excldata (2,940 obs.)

Purpose: Provide definitions of the vari ous cases and parameter values for estimating entrainment survival, physical exclusi on based on slot width/mesh size, and impingement survival of excluded organisms.

Comments: Case 0.5 (full flow with entrainment su rvival) is one of the cases with the parameters for 100% mortality, however these wrong para meters do not get used to calculate

entrainment survival for case 0.5 in section 8 below.

5.2.8 Entrainment Section 8—Calculate Numbers and Losses by Case

Lines: 16,316-16,371

Input: R01.ichwclv5 (5,206 obs.) R02.ichwclv5 (5,498 obs.) R03.ichwclv5 (5,509 obs.) R04.ichwclv5 (5,521 obs.) R05.ichwclv5 (5,522 obs.) R06.ichwclv5 (5,513 obs.) R07.ichwclv5 (5,506 obs.) R87.ichwclv5 (3,477 obs.)

Output: work.wqmean (300 obs.) out.E08_entdenlenflow_lba (1,802,234 obs.)

Purpose: Use weekly mean salinities from regions 3-5 to calculate mechanical entrainment survival by case taxon lif_stag length year week date.

Comments: Examined a subset of out.E08_entde nlenflow_lba (May-August 2003 striped bass PYSL data for cases 0, 0.5, 1, 4, 10, 10.5, 14, and 15). Salint =1 in all 8,792 obs.

examined. One is the default value for week s that have no salinity data, so that value should occur rarely if at all.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 47 Normandeau Associates, Inc. Follow-up: Salint was added to the keep statements wh en the work.Baseline, work.Alternative, and work.ClosedCycle data sets are created.

Lines: 16,613, 16,614

Purpose: Assign avoidance factor for the AFB a lternative based on the percentage of Lovett’s intake flow that was not filtered by the Gunderboom.

Comments: Avoidance factor ( favoid ) for AFB should be 0.79 rather than 0.82 (which was a preliminary value that has been subsequently revised).

Follow-up: favoid changed to 0.79.

Lines: 16,310-16,778

Input: out.E06_flow (9,864 obs.) out.E05_entlenden (18,653 obs.) out.E07_excldata (2,940 obs.) out.E07_entsurv (476 obs.) out.E07_excludesurv (576 obs.)

Output: out.E08_entdenlenflow_lba (1,802,234 obs.)

Purpose: Merge flows, discharge temperatures, predicted entrainment densities, exclusion factors, entrainment survival parameters, and impingement survival parameters and calculate the numbers avoiding, exclud ed, and entrained by each case taxon stage length year week date, and the corresponding losses (for each unit, separately for CW flow and SW flow).

Comments: Sm (daily mechanical entrainment survival ra tes): verified for cases 1, 4, 10, 10.5, and 14 using length, salinity, and the entrainmen t survival parameters ME0, MEL, LamE, alpha, and gamma for striped bass PYSL in May-August 2003 and checked to see that it is zero for cases 1 and 15 and that it is the same for case 0.5 as for case 1 (all OK). Wrong mechanical survival parameters fo r case 0.5 (100% mortality) are OK because they do not get used in the calculations. ST2 (daily Unit 2 thermal entrainment survival rates): verified the for cases 1, 4, 10, 10.5, and 14 using distemp2, beta, and Tcrit for striped bass PYSL in May-August 2003; checked to see that ST2 is the same for case 0.5 as for case 1; and looked at plots of ST2 against distemp2 to make sure the parameters represent plausible curves (all OK). Non-zero thermal survival rates for case 0 (baseline, where all values are 99% or 100% survival) and for case 15 (closed cycle, where the values are above but close to zero) are OK because they all get cancelled out by a mechanical survival rate of zero. Sx (daily impingement survival rates of “entrainables” that are excluded by technology alternatives): verified for cases 4, 10, and 10.5 using length and the impinge ment survival parameters Aimp, Bimp, and Cimp for the striped bass PYSL in May-August 2003 and looked at plots of Sx against length to make sure the parameters represent plausible curves (all OK). Values for cases 0, 0.5, 1, 14, and 15 are irrelevant in these examples because exclusion is always

zero. SWEnt1 is always zero for cases 0 and 0.5 because U1SWflow is always zero

for those two cases. Ent3 (daily estimated number entrained by the Unit 3 cooling water flow): verified for cases 0, 0.5, 1, 4, 10, 10.5, 14, and 15 using pent, entfreq, U3CWflow, exclusion, and (for case 4) le ngth for striped bass PYSL in May-August 2003 (all OK). TotLoss_mil (daily entrainment losses): verified for cases 0, 0.5, 1, 4, 10, 10.5, 14, and 15 using SWEnt1, SWEnt2, SWEnt3, Ent2, Ent3, Sm, ST2, ST3, SWExc2, SWExc3, Exc2, Exc3, Sx, and (fo r case 10.5) Slatent for striped bass PYSL in May-August 2003. Entrainment losse s were correctly calculated from those variables, but the losses from the Unit 1 service water are missing

.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 48 Normandeau Associates, Inc. Follow-up: Baseline U1SWflow changed to 16,000 gpm.

5.2.9 Entrainment Section 9—Calculate Equivalent Life Stage Values

Lines: 16,898-17,761

Input: stageequiv (9 obs., cards) balparm (9 values in the code) spottailLH (28 obs., cards) fecundity (46 obs., cards) Life Tables061109.csv (228 obs.)

Output: out.E09_eqloss_A1_balanced (256 obs.)

Purpose: Calculate factors for converting lo sses into biomass production (“production forgone”), yield, and consumption.

Comments: Independently calculated several of the intermediate variables for survival, mortality, growth, and weight, both cumulative and within life stage, for most of the taxa/life stages from the input values. Verified the life cycle balancing by independently calculating the lifetime fecundity per egg (OK). Verified the calculation of eqage (used for calculating age 1 equivalents): OK. Independently calculated values for Cum_Pi (cumulative biomass production in gram s forgone per individual entrained at each life stage over the entire lifespan) for five life stages of alewife and striped bass: egg values matched exactly but other stages disagreed, often by a fraction of 1% but sometimes by as much as 10-14% because the production forgone for the entrained
stage uses weight (the start weight of the stage) instead of medweight (the weight at entrainment, at the median death of the entrained stage). The sum of duration over the first year of life for all taxa except spo ttail shiner is longer than 365 days, making

age >365 days for the start of stage A1, the age of equivalence. This doesn’t affect the analysis though, which is based on the correct stage mortality rates ( Zdur was calculated after multiplying daily mortalities F and M by duration , but those daily mortalities were originally calculated by dividing stage mortalities by the inflated durations, so the effect of the excess days in age 0+ is cancelled out). One effect of the extra age 0+ days is that spottail shiner stage A1_06 (the first month after the age of equivalence) is put into work.stageage in the early part of step 10 but we ultimately don’t present spottail shiner entrainment data. Values of either Yi or Ci (or both) are questionable because when compared with independent estimates of total future biomass production (which would include biomass that goes to both fisheries and consumption), the sum of Yi + Ci ranged from 23% to 313% higher than the combined sum of the weight at the time of entrainment ( medweight ) and all future biomass production ( cum_Pi ) per entrained individual in 10 examples examined. The lost consumption values, which are calculated from Ci , are not ultimately used in the alternatives report. As far as Yi is concerned, we could just assume that Baranov’s Catch Equation for the equivalent yi eld model (EPRI 2004) is defensible.

Follow-up: medweight substituted for weight in equation for Pi_loss

. Yi is an approximation to the true age-specific lost yield. Depending upon survival and fishing mortality values,

Yi may over or underestimate the true lost yield.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 49 Normandeau Associates, Inc. 5.2.10 Entrainment Section 10—Convert Entrainment Loss to Equivalent Loss

Lines: 17,775-17,787

Input: out.E09_eqloss_A1_balanced (256 obs.)

Output: work.LHeqloss (223 obs.) work.stageage (96 obs.)

Purpose: Assign lif_stag =0 to eggs, lif_stag =1 to YSL, lif_stag =3 to PYSL, and lif_stag =5 to every other stage.

Comments: eggs for taxa 3, 32, and 35 and PYSL of taxon 28 are assigned the wrong lif_stag (5, which is juveniles) because of mismatches in stg_name . For example, stg_name =eggs for some taxa but stg_name =egg for other taxa (without the final “s”). This does no harm in work.stageage because that file is only used to provide stg_num for the lif_stag =5 (juvenile) entrainment estimates. S pottail shiner yearlings in June are assigned the wrong lif_stag (5, juveniles) because line 17,785 includes stg_num =15 for spottail shiner due to its age (365 days). This also does no harm in work.stageage, for the same reason (and also because we ultimately don’t present entrainment losses for spottail shiner). The same wrong lif_stag values are merged from work.LHeqloss

into the full entrainment data set work.e nt, but his does no harm either, because the merging is done by stg_num rather than by lif_stag and no further data manipulations are done by lif_stag

.

Lines: 17,812-17,818

Input: work.ent2 (430,192 obs.) work.stageage (96 obs.)

Output: work.ent2 (430,260 obs.)

Purpose: Merge entrainment loss data for juve niles with life history data by taxon lif_stag

month.

Comments: 60,191 obs. from work.ent2 did not match up with any records in work.stageage (mostly cases of juveniles being entrained in the month before the month in which the juvenile stage is reached according to out.E09_eqloss_A1_balanced, except for American shad entrained in July, which di dn’t match because there is no record in out.E09_eqloss_A1_balanced for shad in July). This is rectified by assigning
stg_num =4 to these records. 68 obs. from wo rk.stageage did not match up with any records in work.ent2, resulting in work.e nt2 after the merge having 68 extra obs. with missing values for totent_mil

, totLoss_mil , and other variables originally from out.E08_entdenlenflow_lba. Stg_num =4 is assigned to these 68 unmatched records, replacing the correct stage_num , but these records do not affect the subsequent totals because of the missing loss values.

Line: 17,832-17,837

Input: work.LHeqloss (223 obs.) work.ent (1,802,302 obs.)

Output: work.ent (1,802,302 obs.)

Purpose: Merge life history parameters w ith entrainment loss data by taxon stg_num.

Comments: At least one record has the wrong month value. Shad eggs occurred only in 2002, and only in two weeks of that year (each represen ted by seven daily estimates in the file),IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 50 Normandeau Associates, Inc. resulting in 322 records (23 cases, 1 year, 2 weeks, 7 days per week). In the first day of the first week, case 0 differs from all 22 other cases in the value of month (5 for case 0 and 4 for all other cases on that date). This resulted from merging two files with

different values for the variable month but the same values of taxon and stg_num

. For the analysis we want the month value from work.ent, so perhaps month should be dropped from work.LHeqloss before the merge. A month discrepancy also occurred in other records in the merged file, including records from 1987 (which does no harm because it is not used for subsequent analysis) and some records with stg_num =4 and missing values for the entrainment numbers and losses (which shouldn’t affect the outcome because the estimates will be summed later by month).

Follow-up: Code changed so that month variable not brought into work.ent1. Note it is needed in

work.ent2.

Line: 17,845

Input: totloss_mil, cum_Pi, S1

Output: prodforgn_kg

Purpose: Multiply the production forgone per entrai ned individual (in grams) by the number of entrained organisms lost (in millions) to estimate the biomass production forgone (and convert to kilograms).

Comments: Dividing by S1 is not necessary because cum_Pi already has accounted for entrainment occurring at the median death of the entr ained stage, and therefore dividing by S1 now inflates the production forgone estimates (not only of the entrained stage, but also every subsequent stage up to the expected lifespan).

Follow-up: Code changed to remove S1 from the calculation.

5.2.11 Entrainment Section 11—Produce Output Tables

Lines: 17,953-17,970

Input: out.E10_losssummary2_lba (1,111 obs.)

Output: work.SBratio (8 obs.)

Purpose: Estimate proportion of striped bass pr oduction forgone that w ould have resulted in fishing yield, for converting production fo rgone of other species into striped bass equivalent lost yield.

Comments: Overestimation of production forgone due to dividing cum_Pi by S1 in line 17,845 would cause the ratio to be too low (but if lost yield is too high, that could have a larger influence, causing the ratio to be too high).

Follow-up: Change to previous section will correct.

Lines: 18,011-18,046

Input: out.E10_losssummary.lba (6,246 obs.)

Output: work.monthlyalternatives (5,658 obs.) work.negred (1 obs.)

Purpose: Calculate monthly percent reductions fro m baseline for numbers entrained, entrainment losses, and entrainment age 1 equivalent losses by case taxon year (work.negred is for any negative percent reductions).IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 51 Normandeau Associates, Inc. Comments: Shad in April 2002 has a negative percent reduction for all three metrics due to the

month error for the baseline case in section 10.

Follow-up: This issue corrected by dropping month from Ent1 data set.

5.2.12 Impingement Sections 1 and 2—River Abundance in 1983-1987 and 2000-2007; Correlation of Standing Crops

Lines: Beginning 18547 and 18901

Input: Beach Seine and Fall Shoals program datasets for 1983 – 1 990 and 2000 – 2007.

Purpose: Determine standing crop for both program s, and to correlate various life stages across the two programs.

Comments: Confirmed selection of data, verified correlation coefficients and level of significance

of correlations. In the merge of LV34 and LV5 the result contains 3 records more than expected (66968 – LV34, 68940 (LV5 ), resulting file is 66971.

Follow-up: Corrected by summing LV5 by year
, taxon and sample to eliminate multiple LV5 records for same sample.

Lines: 18,800-18,849

Input: work.fsslv345 (66,971 obs.) old.volarea (39 obs.)

Output: work.mean4 (9,328 obs.) work.mean5 (1,248 obs.)

Purpose: Average FSS densities by taxon year w eek region strata, convert to standing crop estimates using stratum volumes, combine regi ons and strata (for regions 3-5) by taxon year week.

Comments: There are three issues with the FSS standing cr ops. One is a shoal sample in region 5 in 2007 (a region not sampled in the shoal st ratum). Another issue is that sampling in two weeks (week 29 in 1986 and week 29 in 2005) spilled over into the following week, causing two extra weeks in work.mean4 and work.mean5. This could be due to the dates, for example if sampling didn’t finish until Sunday. It could be rectified by changing all records for week 30 in 1985 and in 2005 to week 29. The third issue is that there are no stratum 3 samples in these 3 regions at all in the last 3 sampling weeks of the season in all years 2000-2007 (a design change that compromises the comparability of the standing crops from th e 1980s and the 2000s). All these missing

and extra strata have the effect of biasi ng the densities and standing crops low because of the mismatches in sampling design. The missing stratum 3 samples could be rectified by using an appropriate stratum volume weighting procedure that does not lower the mean density when a stratum is missing by effectively counting it as zero.

Follow-up: Shoal samples in region 5 dropped. W eek 30 reassigned as week 29. Deleted strata 3 samples after week 42 in all years.

5.2.13 Impingement Section 3—Merge Abundance Ratios with Densities and Estimate Impingement

Lines: Beginning 19100

Input: Impstratadensities, abundratios, flow (flow and op data, 2000-2008)

Output: Impdenflow, StrataMeans

Purpose: Estimate impingement.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 52 Normandeau Associates, Inc. Comments: Merges impdensities and abundratios by taxon; Adjusts densities based on the ratios.

Calculates flow for each Unit. Note that SW Unit 3 is assigned as 36,000 in entrainment section of program code, while the 1990 report indicated SW at Unit 3 is 30,000. Sums flow over Case, Unit, Year, Stra ta, Month. Subsets Impdensity file for years >1983 (1984-1990 only used). Calculates mean daily adjusted number impinged by Unit Strata and Taxon (average over 7 years) . Merges this file in to the Monthflow

file that has been zerofilled for all 8 taxa. Assigns avoidance factors according to case, and ristroph survival coefficient according to taxon. Avoidance factor for case 14 should be changed from 0.82 to 0.79. Calculates the “multiplier” – the avoidance factor adjusted number impinged. Calculates the number lost multiplier as the probability of “not” avoiding times the probability of not surviving impingement.

Follow-up: New SW pumps for Unit 3 have higher capacity. Changed favoid to 0.79.

5.2.14 Impingement Section 4—Convert to Equivalent Losses

Comments: Confirmed assignment of year class, elim inating early life stages. Reviewed equivalent loss, lossyield_kg, lostconsum_kg, and prodforgn_kg. The equation for prodforgn_kg should be modified by removing the S1 in the denominator. Remaining program steps were reviewed for appropriate s ubsetting. No issues were found.

Follow-up: Removed S1 from denominator.

5.2.15 Outstanding Consideration

Comments: Confirm the correlation between the impingeme nt densities calculated in this effort and the densities that are being prepared for delivery to NRC as part of an independent task.

These efforts utilize similar source data and should be reviewed to confirm their

confluence.

Follow-up: Outputs for this effort and for the N RC delivery are substantially different and would be very difficult to compare.



### 5.3 P ROGRAM 

### IP-C OLL 

### E FF 

### 1981

- 1990. SAS 

### (22S EP 

### 09 R EVISION 

### )

5.3.1 Step 1—Calculate Collection Efficiency Coefficients

Lines: Beginning 766

Input: IMPWCLV5 for the period 1981-1990 IMPDFLV3 for the period 1981-1990

Output: ALL_CE8190 (N=5888)

Purpose: Calculate collection efficiency coeffici ents by date for use in determining collection efficiency adjusted impingement counts.

Comments: Water temperature is averaged across all three units, using task_cd=90 or task_cd=99

records.

LV3 and LV5 records are merged, and the average water temperature by date is calculated. For instances where water temper ature is missing, temperature is linearly interpreted from the preceding and succeeding dates.

Collection efficiency coefficients are calc ulated for each year, unit, and date based on the following equations:

Unit 2 Coll_Eff= (-0.00871 * H2O_Temp) + 0.51858;

Unit 3 Coll_Eff=(-0.00792 * H2O_Temp) +0.71640;IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 53 Normandeau Associates, Inc. Equations were confirmed against the 1990 report. Time interval over which temperatures were interpolated varied from a day to over 100 days.

Follow-up: Substantial periods sometimes passed be tween samples due to unit outages. No action

taken.

Lines: Beginning 968 – Joining sample collection data from LV3, LV4 for all years.

Input: 1981 -1990 LV3, LV4 or LV4b data files.

Output: All_LV3 (N=4616), ALL_LV4 (N=4613) merged to JOIN_SAMP (N=4616)

Purpose: Gather field sample specific information containing unit, date, volume.

Comments: LV3 and LV4 files are merged and resulting JOIN_SAMP file created (N=4616). Merges All_CE8190 and JOIN_SAMP to create SAMP_CE (N=4616)



### 5.4 P ROGRAM 

### IP-S TRATA 

### I MP 

### B Y 

### L ENGTH 

### C LASS 

### 1981

- 1990. SAS 

### (22S EP 

### 09 R EVISION 

### )

5.4.1 Step 2—Join Catch Data to the Collection Efficiency Data from Step 1

Lines: Beginning 1044

Input: 1981-1990 Level 5 files (IMPDFLV5 N=34789) SAMP_CE (N=4616) PAD_SAMP (zero filled file) (N=577000, which is 4616 samples x 125 taxa)

Output: ADJ_CT (N=577007) SUM_CT (395000)

Purpose: To calculate collection efficiency adjusted counts by year, unit, strata and taxon

Comments: Creates a file with a records for ever y taxon for every sample (referred to as zero filling– in samples where a taxon was not collected, counts will be ‘0’, hence the file is zerofilled, allowing for the correct calculation of mean density). Merges this zero filled file with the LV5 file, expecting resulting file to be 577000 records. Sums adjusted counts by Year, Date, Unit and Taxon.

Resulting file was 577007 records. Seven samp les have two records for various taxa, and in 5 of the 7 cases, the counts on the records are different.

Follow-up: If records have the same total_ct , it was assumed that a single valid record was duplicated. If the records have different total_ct , it was assumed both records were valid and they were combined into a single record. Resulting file has 577000 records. Of the taxa being used in this analysis, only a single sample date (1/11/1981) was substantially affected. On that date, for Un it 3, catch of yearling striped bass was 30 in

one record and 21 in the other. For white perch, 21 yearling white perch were listed on one record, and 2307 on the other. Other instances for the 14 records were for taxa not used in this analysis.

5.4.2 Step 3—Calculate Strata Numbers

Lines: Beginning 1152

Input: ADJ_CT (N=577007)

Output: Strata_CT, Y81jj (1981 treated separ ately due to daily sampling, Strata_MNIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 54 Normandeau Associates, Inc. Purpose: Adjust counts according to collection e fficiency coefficients. Sum over samples to obtain year date unit and taxon sums. Extract Month from date, assign strata based on month and separate blue crabs from other taxa . Calculate a mean and standard error by year unit strata taxon. Determine the number of samples collected in each strata.

5.4.3 Step 4—Bring in Plant Operation Data

Lines: Beginning 1250

Input: Circflow file: plant operation data; SUM_CT file

Output: Countvol and StrataDens files

Final file is Impstratadensities

Purpose: Obtain plant volume by date and adju st densities according to daily volume by year, date, and unit.

Comments: Density = (collection efficiency adjusted daily count * 1000000) / daily volume. Computes average by year unit strata and taxon.



### 5.5 V ERIFICATION OF 

### S ENSITIVITY 

### A NALYSIS AND 

### C UMULATIVE 

### A NALYSIS

After the alternatives analysis software program ha d been finalized following the QC and verification process described above, the program was further m odified to accomplish two additional goals. One was to explore the sensitivity of the alternatives anal ysis outcome to variations in the parameters of the equation estimating larval fish avoidance to wedge wire screens as a function of larval length. The second goal was to relate the cumulative loss reductions of alternative technologies to the cumulative loss reductions of closed cycle cooling over the en tire projected lifetime of IPEC operation to reflect differing implementation schedules. Normandeau wa s asked to perform a QC verification of the software developed for the sensitivity analysis and the cumulative analysis. ASA provided the revised software, IPEC Alternatives – Program 1H5_011110.sas, which included a new section “J01 – Cumulative Analysis over Remaining Plant Life” at the end.

The method of checking the new section of the prog ram was the same as had been employed earlier for verifying the earlier sections. ASA’s finalized program code was set aside and a copy created for the purpose of modifying code to run in Normand eau’s network environment. Data libraries were resolved, input data files were reconciled, a nd the program was run iteratively, resolving all discrepancies until the program ran error free. A PDF document containing all of the output listings produced by the program, as well as a separate PD F document containing the SAS log file of code execution, were created. This allowed for caref ul review of program execution by facilitating inspection of intermediate steps in the execution pr ocess. Some program steps created intermediate data files that were saved automatically as Excel CSV files. Other program steps created “permanent” SAS datasets, which are not erased at the end of program execution. Selected SAS permanent datasets were also ex amined during the QC process.

The sensitivity analysis was not reflected in the fina l program code, but rather had been performed by ASA rerunning the program varying the parameters in the single program line containing the avoidance factor equation. No rmandeau confirmed the results of the sensitivity analysis by modifying the final SAS program, IPEC Alterna tives – Program 1H5_011110.sas, to alter the lengthbased avoidance factor. The original model used the following equation:

Avoidance factor = 1 – e (-0.275*(Length-4))

To test the results of the sensitivity analysis, the eq uation was modified to reflect one of the alternate formulations of the avoidance relationship that had been used in the sensitivity analysis:

Avoidance factor = 1 –e (-0. 18 *(Length- 8 ))IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 55 Normandeau Associates, Inc. Results of the modified program confirme d the results of the sensitivity analysis.

In addition to the program itself, ASA provided a ser ies of SAS output datasets containing the results of the alternatives analysis. Part of the verifica tion process was to compare these datasets to results independently generated by Norma ndeau using the SAS code provided by ASA. The Proc Compare routine in SAS compares SAS datasets based on all vari ables, and all records in each of two files. Records containing different variables or different values for variables, or datasets containing a different number of records are flagged. The resu lts of Proc Compare for the seven output datasets provided by ASA showed initially that the first four datasets did not differ in any variable values from the Normandeau results, but that substantial di fferences were found in the final three summary

datasets. Examination of the code and the discr epant results revealed that the output datasets provided by ASA reflected a different scenario run – comparing the losses under the alternative technology cases to the losses under the current technolog y case, rather than to the regulatory baseline

case. Normandeau modified the code to calcula te the loss reductions from the current technology, and performed the Proc Compare on all seven output da tasets again. The results of the Proc Compare then indicated that all datasets obtained by ASA and Normandeau, Out2 through Out8, were equivalent. Discrepancies between corresponding vari able values in the two datasets were nearly always less than 0.0001% (one part in one milli on). The few small discrepancies that were found were reasonable results of differing versions of SAS and differing hardware between ASA and

Normandeau. This exercise verified that the results of the program could be independently replicated.

Other steps in the verification process for the cumu lative analysis included following the data flow throughout the new section J01 to verify that the intermediate data sets contained the appropriate number of observations and independently recalculati ng the results of intermediate steps for several data points. The code was examined and examples were recalculated to verify that the program performed as described in the internal documentation (comment lines in the program). The steps in the cumulative analysis in the new program secti on J01 performed as designed and all values checked were correctly calculated by the program.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 56 Normandeau Associates, Inc. Attachment B-1

Literature Review of Fish Larvae Avoidan ce Swimming Behavior as Applied to IPEC

Clutter and Anraku (1968) reviewed several publishe d studies and concluded that avoidance of towed plankton nets by larval fish is supported by ov erwhelming evidence. Factors influencing the degree

of avoidance included larval detection of tur bulence of water passing through the mesh, larval detection of a pressure front before contact with the sampling gear, the approach speed, and the size of the sampling gear. Although these observations were based on plankton nets moving through a (relatively) stationary water mass containing the larv ae, the same principles should apply to stationary CWW screens in a moving water mass containing larvae. The extensive body of evidence demonstrating larval avoidance of plankton nets establishes the means by which fish larvae are capable of CWW screen avoidance: their swimming ability.

The scientific literature has a large amount of information on the swimming capabilities of fish and fish larvae from as early as 1926 (Breder 1926, cited in EPRI 2000). The most recent tabulation of fish swimming capabilities from the peer reviewed scientific litera ture was published by Beamish (1978), and reviewed by Hammer (1995). There are several types of swimming behavior exhibited by fish (EPRI 2000):

 cruising is the normal swimming activity sustained by fish performing their daily activities,

 critical swimming is the prolonged swimming speed a fish can main tain when forced to swim in a confined space of continuous flow,

 burst swimming is avoidance activity repr esented by short-duration darts, and

 fast start swimming is the initial thrust of a burst swimming activity.

The various authors presented in this review have used different terms to differentiate among these swimming behaviors. In this review, we will use the authors’ original terminology but associate the terms cruising , prolonged, or burst swimming behaviors in parenth eses as applied to the author’s usage. These three terms have physiological defi nitions consistent among fisheries scientists that relate to the use of energy reserves leading to fatigue. Specifically, the time for 50% of the test subjects to fatigue (unable to maintain position in a current), expressed as swimming speed in body lengths per second, distinguishes among the three types of swimming behavior (Beamish 1978). Cruising can be sustained nearly indefinitely, bur st swimming leads to the most rapid fatigue, and prolonged swimming is intermedia te between the two (EPRI 2000).

Cruising and prolonged swimming, which are used more by larger fish than by larvae, are both essentially continuous modes of swimming. Burst swimming is the mode most characteristic of larvae, and it differs from the other two modes by in corporating substantial periods of rest between very short bursts of active swimming. During the resting intervals between the bursts, the forward motion may be sustained briefly as a glide if the larva is large enough for its momentum to overcome

the resistance of the water. Then the mode of burst swimming can be described as “beat and glide” swimming (Weihs 1980) or “beat-and-coast” swi mming (Webb and Weihs 1986). However, the potential for gliding during the rest intervals of burst swimming is limited by the ratio of inertial to frictional forces, expressed by the Reynolds number (Weihs 1980). For a very small (newly hatched) larva, the Reynolds number is too low to permit glid ing between bursts. In addition, a bulky yolk sac is a further impediment to gliding during the fi rst few days after hatching, so yolk-sac larvae are ineffectual swimmers. After the yolk sac is abso rbed, the increasing size and speed of the growing larva eventually raise the Reynolds number enough to make gliding possible. This transition betweenIPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 57 Normandeau Associates, Inc. burst swimming with no gliding to burst swimming with gliding takes place between the lengths of 5 and 15 mm for northern anchovy larvae (Weihs 1980).

Blaxter (1986) summarized the capabilities acquired earl y during development of larval fish that provide them with the ability to detect a threat a nd initiate evasive action. Soon after hatching, eyes and neuromasts (sensory cells on the lateral surf ace of the body) are sufficiently well developed to

enable larvae to react to visual and mechanical stimuli. Larvae can swim up to 20 body lengths (“BL”) per second for very short periods (bursts ) and 10-20 BL/s for longer periods (prolonged ). Some species can maintain 4-5 BL/s for prolonged periods (e.g., 30 min), and cruising speeds of 1-3 BL/s can be maintained indefinitely.

Eaton and DiDomenico (1986) noted that the escap e response in fish appears very early during development, as early as 44 hours after fertilization, even before normal hatching begins. The typical startle response incorporates a “C-type fast start” (burst ) enabling the young fish to swim a distance equal to its body length in about 100 milliseconds (“ms”; i.e., 10 body lengths per second). While this behavior is primarily a predator avoidance r esponse, it does demonstrate that an extremely rapid acceleration is possible at a very young stage. Webb and Weihs (1986) re ported that during “beatand-coast” swimming (i.e., burst and cruise swimming), larval northern anchovy (a West Coast species) have a maximum (burst ) speed exceeding 10 BL/s. Measurements of burst swimming speed by Fuiman (1986) for zebra danio larvae averaging 3.6 mm in length indicated that some of the earlier

estimates of burst speed may be conservatively low. He observed burst speeds that reached 15 cm/s within 20 ms, the equivalent of 40-50 BL/s.

Miller et al. (1988) summarized burst swimming in a relationship be tween length (“L”) in mm and speed (“S”) in cm/s where S=3.33+0.71 L. This equates to about 10 cm/s (10 BL/s) for a 10-mm larva, faster than the through-slot velocity of 7.6 cm/s (0.25 ft/s) that is within the range under

consideration for IPEC’s CWW screens.

For the typical larval swimming mode (burst swimming), the following table shows the burst swimming speed in cm/s at 10 BL/s (Eaton and DiDomenico 1986, Webb and Weihs 1986, and Miller et al. 1988), 20 BL/s (Blaxter 1986), and 40 BL/s (Fuiman 1986) related to the typical species and sizes of fish larvae exposed to entrainment at IPEC:

Taxon Quartile Total Length (mm) Swimming speed (cm/sec)

Burst

@ 10 BL/sec Burst

@ 20 BL/sec Burst

@ 40 BL/sec

Striped bass 25% 6.2 6.2 12.4 24.8

50% 7.4 7.4 14.8 29.6

75% 8.6 8.6 17.2 34.4

White perch 25% 5.4 5.4 10.8 21.6

50% 7.1 7.1 14.2 28.2

75% 10.4 10.4 20.8 41.6

River herring 25% 9.3 9.3 18.6 37.2

50% 11.9 11.9 23.8 47.6

75% 14.3 14.3 28.6 57.2

Bay anchovy 25% 9.1 9.1 18.2 36.4

50% 13.8 13.8 27.6 55.2

75% 17.0 17.0 34.0 68.0

These data illustrate that the average (50% quartile ) Hudson River fish larva exposed to entrainment at IPEC can swim briefly (burst ) at a speed of between 7.1 and 13.8 cm/sec (0.23-0.45 feet/sec) depending on the taxon, at the conservative estimate of 10 BL/s.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 58 Normandeau Associates, Inc. Relationships between length and swimming speed fo r larger fish (50 mm and larger) presented by Videler (1993) are consistent with the estimates fo r larvae: S=0.15+2.4 L for sustained (cruising ) swimming, S=0.61+2.4 L for prolonged swimming, and S=0.4+7.4 L for burst swimming (where speed is in m/s and length is in m). The smaller the fish, the faster the swimming speed in terms of body lengths per second. The smallest fish upon wh ich these relationships were based represent the approximate entrainment-to-impingement transition size for 3/8-inch mesh screens, but extrapolating the equations to smaller fish implies that burst speed for PYSL could be at least 10 BL/s and the prolonged swimming speed could be faster than the proposed 7.6 cm/s intake velocity.

EPRI (2000) conducted a literature review and evaluation to determ ine whether intake approach velocities of no more than 0.5 ft/s can prevent impingement impacts of CWIS. Their evaluation focused on the prolonged swimming speeds of impingeable si ze juveniles and adults near conventional intakes (the speed of continuous sw imming that can be maintained for a prolonged period of time before the fish fatigues such as when forced to hold position in an intake current; as opposed to burst speeds or indefinitely sustainable “cruising” speeds). Most data presented were for fish too large to be vulnerable to entrainmen t through fine-mesh or CWW screens, but critical swimming speeds for some of the smaller fish may be applicable to IPEC. Critical swimming speeds for bay anchovy included 10 cm/s at 28 mm, 11.9 cm/s at 33 mm, and 17.7 cm/s at 34 mm; prolonged swimming speeds for Atlantic menhaden included 17-21 cm/s at 36 mm; and critical swimming speeds for striped bass included 35 cm/s at 25 mm . Impingement of bay anchovy and Atlantic menhaden in large numbers in estuaries was attribut ed to median swimming speeds at or below 0.5 ft/s at lengths around 30 mm. If, however, the intake flow at IPEC were to be reduced to 0.25 ft/s (7.6 cm/s), then even the typically vulnerable species such as bay anchovy and Atlantic menhaden may be able to avoid entrainment.

References

Beamish, F.W.H. 1978. Swimming capacity. Pag es 101-187, in W.S. Hoar and D.J. Randall, eds. Fish Physiology. Volume VII. Loco motion. Academic Press, New York.

Blaxter, J.H.S. 1986. Development of sense orga ns and behaviour of tele ost larvae with special reference to feeding and predator avoidan ce. Trans. Amer. Fish. Soc. 115(1):98-114.

Breder, C. M. 1926. The locomotion of fishes. Zoologica 4: 159-256.

Clutter, R.I., and M. Anraku. 1968. Avoidance of samplers. Pages 57-76 in D.J. Tranter (ed), Zooplankton sampling. UNESCO Monographs on oceanographic me thodology, No. 2.

Eaton, R.C., and R. DiDomenico. 1986. Role of the teleost escape response during development. Trans. Amer. Fish. Soc. 115(1):128-142.

EPRI (Electric Power Research Institute). 2000. Technical evaluation of the utility of intake approach velocity as an indicator of potential adverse environmental im pact under Clean Water Act Section 316(b). Report 1000731.

Fuiman, L.A. 1986. Burst-swimming performance of larval zebra danios and the effects of diel temperature fluctuations. Trans. Amer. Fish. Soc. 115(1):143-148.

Hammer, C. 1995. Fatigue and exercise tests with fish. Comparative Bioche mistry and Physiology

A 112: 1-20.

Miller, T.J., L.B. Crowder, J.A. Rice, and E.A. Marschall. 1988. Larval size and recruitment

mechanisms in fishes: toward a conceptual framework. Can. J. Fish. Aquat. Sci. 45(9):1657-

1670.

Videler, J.J. 1993. Fish swimming. Fish and fisheries series 10. Chapman and Hall, London, UK.IPEC Alternatives Analysis

Appendix B 2-1-10.DOC, 2/2/10 59 Normandeau Associates, Inc. Webb, P.W., and D. Weihs. 1986. Functional locomotor morphology of early life history stages of fishes. Trans. Amer. Fish. Soc. 115(1):115-127.

Weihs, D. 1980. Energetic significance of cha nges in swimming modes during growth of larval anchovy, Engraulis mordax . Fish. Bull., U.S. 77(3):597-604.

# Appendix C

Empirical Assessment of Expected Population-Level Effects of

Reductions in Entrainment Losses at Ent ergy Nuclear Indian Point Units 2 and 3

February 2010

Prepared by

AKRF, Inc. 7250 Parkway Drive

Suite 210 Hanover, Maryland 21076

### 1 

### INTRODUCTION

Entergy Nuclear Indian Point 2, LLC a nd Entergy Nuclear Indian Point 3, LLC (“Entergy”) retained AKRF, Inc. to evaluate the population-level eff ects of reductions in

entrainment losses associated with certain alternative intake te chnologies considered as part of Entergy’s alternative tec hnology assessment undertaken pursuant to the New York State Department of Environmental Conservation (“NYSDEC”) Assistant Commissioner’s August 13, 2008 Interim Decision. 1 

### This report supports the “Biolo gical Effectiveness of Alternative Intake Technologies for Indian Point Units 2 a nd 3” (the “Biological Report”) prepared by

Lawrence W. Barnthouse of LWB Environmenta l Services, Inc., Douglas G. Heimbuch of AKRF, Inc., Mark T. Mattson of Normandeau Associates, Inc., and John R. Young of ASA Analysis & Communication, Inc.

Changes in population abundance resulting fr om reductions in entrainment losses caused by alternative intake technologies cannot be dete rmined by calculating age-1 equivalents. As noted in the Biological Report, projected be nefits of alternative intake technologies, measured as reducti ons in entrainment losses, have been expressed in terms of potential annual increases in age-1 equivalent s (USEPA, 2006; Enercon Services, Inc., 2010). In the calculation of age-1 equivalents, entr ainment losses for each life stage (i.e. eggs, larvae, yolk-sac larvae, post-yolk sac larvae, juvenile fish, and fish ) are converted into equivalent one-year-old fish. Conversion to age-1 equivalent s enables an analysis because

entrainment losses for each alternative intake technology evaluated can be expressed in terms of a common metric. Although a convenient metr ic for summarizing entrainment losses that occur over several life stages (primarily eggs and larvae), the calcula ted age-1 equivalents do not provide any indication of the actual change s in age-1 population abundance that likely

would result due to the reducti on in entrainment losses. These estimates are theoretical calculations based on estimates of the average fraction of entrained fi sh that would have survived to an age of 1 year. As shown in the AEI Report, however, su rvival rates of early life stages of fish in the H udson River are highly variable, and correlations between these

survival rates and abundance indices for larv ae and juveniles are of ten low. Hence, increasing the abundance of larvae through reductions in entrainment losses may lead to little

or no increase in the abundance of older fish. To assess the lik ely changes in fish population abundance that correspond to calculated increases in age-1 equivalents, field measurements

1 As noted in Biological Effectiveness of Alternativ e Intake Technologies for Indian Point Units 2 and 3

(Barnthouse et al. 2010), a 2003 draft permit issued by NYSDEC Staff proposed modifications to the cooling water intake structure at Entergy’s Indian Point Ente rgy Center (“IPEC”) nuclear powered electric generating stations 2 and 3 (individually, “Unit 2” and “Unit 3,” and collectively, the “Stations”). These modifications include possible construction and operation of two larg e counter-flow, forced dr aft, plume abated hybrid cooling towers (the “NYSDEC Proposed Project”). Counsel for Entergy also informed AKRF that consideration of the NYSDEC Propos ed Project is subject to an alte rnative technologies assessment. Accordingly, the Department may revisit its proposed modifications to the draft SPDES permit for the Stations and change them pursuant to Entergy’s alternative technologies assessment.

### 2 of changes in fish population abundance corr esponding to actual in creases in larval abundance (expressed in terms of increases in age-1 equivalents) would be needed.

Field measurements of changes in juven ile abundance in res ponse to increases in larval abundance have been recorded by the Long River Survey (“LRS”), Beach Seine Survey (“BSS”), and Fall Juvenile Survey (“FJS”) for over 30 years on the Hudson River (field data documented in annual “Year Class Reports”, e.g. EA, 1996). The historical data document what can be viewed as naturally- occurring experiments (i.e., the response of abundance at the juvenile lifestage to a change in abundance at the larval lifestage)of the

effects of increases in rive rwide post-yolk sac larva (“PY SL”) abundance (that can be expressed in terms of age-1 e quivalents) on changes in riverwide juvenile abundance. Those naturally-occurring experiments can be used to address the question of what demonstrable changes in fish populations can be expected fr om reducing entrainment losses at the IPEC

Stations.



### METHODS

Overview

To address the objective of this assessme nt, the relationship between increases in PYSL abundance and changes in abundance of older fish was characterized for American shad, river herring (alewife and blueback herr ing, collectively), striped bass, white perch, Atlantic tomcod, and bay anchovy. These are se ven of the eight representative important species (“RIS”) studied in the Biological Report . Spottail shiner was not included in this assessment because, as noted in the AEI Report, the LRS sampling program does not adequately sample larval spotta il shiner. For each of the seven species under consideration, the annual riverwide PYSL abundance, expre ssed in terms of age-1 equivalents, was calculated for each year from 1974 through 2005. All pairs of years ( i,j )were listed, and the change in abundance from year i to year j , for each pair of years was recorded:

j i j i 

### N N PYSL

, 1

, 1

, 

### ~ ~

   (1)

where

j i 

### PYSL

, 

###  = the change in PYSL abundance between years 

### i and 

### j , expressed in terms of age-1 equivalents,

i 

### N

,

1 

### ~ = PYSL abundance in year, 

### i , expressed in terms of age-1 equivalents, and

j 

### N

,

1 

### ~ = PYSL abundance in year, 

### j , expressed in terms of age-1 equivalents.

Next, all pairs of years in which PYSL abundance was greater in year 

### j than in year 

### i (i.e.,



### 0

, 

###   j

i 

### ) were identified. With 32 years of abundance estimates, there were 1,024 pairs of

years, of which 496 had an increas e in PYSL abundance in year j as compared to year i (and 496 pairs had a decrease in PYSL abundance, and 32 pairs had no change). Evaluating all

### 3 pairs of years, rather than only adjacent years, eliminates any possible influence of long-term

trends in abundance or survival of larvae on th e outcome of the analys is, thereby eliminating potential confounding effects of trends in envi ronmental conditions (un-related to Station operation).

For each pair of years with an increase in PYSL abundance, the corresponding change in observed juvenile abundance was calculated. For each species, estimates of changes in juvenile abundance were based on the annual juvenile index of abundance from the AEI Report. To eliminate the effect of uncertain ge ar efficiencies (i.e., th e proportion of fish in front of a sampling net that is actually collected by the net) on the magnitude of juvenile abundance index values, the indices of juvenile abundance were standardized to the average (over all years of data listed below for each sp ecies) juvenile index value for each species. For river herring, striped bass and white perch, the juvenile indices were based on the Beach Seine Survey from 1974-2005. For American sh ad, the juvenile index was based on the Fall Shoals Survey from 1985-2005 (years with beam trawl sampling). Accordingly, the assessment for American shad only addresse d the 441 pairs of years from 1985-2005 (210 of

which had increases in PYSL abundance).

Changes in juvenile abundance were expre ssed in terms of multiples of the long-term average juvenile a bundance index value:

I J JI JI JUV j i

j i 

### 

  *

, 

### (2)

where

*

, j i 

### JUV  

### = the change in juvenile abundance between years i and j , relative to the long-term average juvenile abundance,

i 

### JI = the juvenile abundance index value in year i

,

j 

### JI = the juvenile abundance index value in year j , and



### I J = the long-term average value of the juvenile abundance index.

The estimates of increases in PYSL abundance, expressed in terms of age-1 equivalents, were computed using the same methods used to express reductions in entrainment losses in terms of age-1 equivale nts (ASAAC, 2009). Ther efore, the estimates

of increases in PYSL abundan ce are directly comparable to the projections of potential increases in age-1 equivalents due to reduced entrainment losses. The projected range of potential annual increases in age-1 equivalents due to eliminating current entrainment losses resulting from the Stations (Table 1, repr oduced from ASAAC, 2009) were compared to the range of year-to-year increases in riverwide age-1 equivalent s. For those year-to-year increases in riverwide age-1 equivalents that fell within the range of potential annual

### 4 increases in age-1 equivalents due to elimina ting current entrainment losses associated with the Stations’ operation, the corresponding change s in juvenile abundance were summarized. The changes in juvenile abundance for those pair s of years indicate the change in juvenile abundance that could be expected if current en trainment losses associat ed with operation of

the Stations were eliminated.

Estimation of PYSL Abundance



### For each species, the annual riverwide pos t yolk sac larval abundance, expressed in terms of age-1 equivalents, was calculated fr om an estimate of the number of organisms entering the post yolk sac larv al lifestage (USEPA, 2006):

JUV PYSL Z Z

y y 

### e e N N ˆ ˆ

, 0

, 1 

### ˆ ~

  

###  (3)

where

y 

### N

,

1 

### ~ = the calculated age-1 equivalents ba sed on an estimate of the number of organisms that enter the PYSL lifestage,

y 

### N

,

0 

### ˆ = an estimate of the number of organisms that enter the PYSL lifestage,

PYSL 

### Z ˆ 

### = an estimate of the instantaneous mortality rate for the PYSL lifestage,

and

JUV 

### Z ˆ 

### = an estimate of the instantaneous mortality rate for the juvenile lifestage.

Each estimate of the number of organisms entering the post yolk sac larval lifestage was based on reported estimates of riverwide standing crops from the Long River Survey (e.g., see EA, 1996), and on the following relationship between average abundan ce over an interval of time and the number of organisms at the beginning of the interval (Ricker, 1975): 

#  

Z e N N Z





### 

 1

0 

### (4)

and


#   Z 

### e Z N N





###   1 0 

### (5)

where



### N = the average number of organisms aliv e (e.g., per day) during an interval of time over which the organisms experience mortality,

0 

### N = the number of organisms alive at the beginning of the interval, and

Z 

### = instantaneous mortality rate during the interval.

For each daily cohort, the average PYSL abunda nce can be represented in terms of the number alive and still in the PYSL lifestage on each day of the sampling season:

### 5 

# 

 

###  T

t t c

PYSL c 

### N D N

1 , 

### 1 

### (6)

where

c 

### N 

### = the average number of cohort, c 

### , organisms alive (per day) during the interval from the first day cohort, c 

### , entered the PYSL lifestage to the last day cohort, c 

### , was in the PYSL lifestage,

t c 

### N

, 

### = the number of cohort, c 

### , organisms alive on day, t



### ,

PYSL 

### D 

### = the PYSL lifestage duration (days), and

T 

### = the duration of the sampling season (days).

noting that D PYSL 

### < T 

### , and that N c,t



### is zero on all days during which cohort c 

### is not in the PYSL lifestage (i.e., cohort c 

### is in the YSL or juvenile lifestage).

Because PYSL are not identified to indi vidual daily cohorts by the LRS sampling program (only the total number of PYSL ar e reported), equation (6) was summed over all daily cohorts. Summing over cohorts allows the average PYSL abundance to be represented in terms of the average daily abundance of PYSL during the sampling season as:

*

1 , 

### 1 1 N D T N D N D N N

PYSL T

t t

PYSL c T

t t c

PYSL c c 

###     

#   

 

### (7)

where the average daily PYSL abun dance over the sampling season is:



# 

 

###  T

t t 

### N T N

1 * 

### 1 (8)

and

t 

### N = the number of PYSL alive on day, t , and

* 

### N = the average number alive, per day, during the sampling season.

Substituting equation (7) into equation (5) give s the following formula for estimating the number of organisms entering the PYSL lifesta ge based on reported standing crop estimates from the Long River Survey: 

#   *

ˆ

, 0 

### ˆ

1 ˆ

ˆ

y

PYSL

y

Z PYSL

y 

### N D

T

e Z N

PYSL 



###   

### (9)

where hats (^) indicate estimates for the corresponding parameters.

### 6 This method is based on the assumption that the full spatial and temporal extent of PYSL presence was subject to sampling. To te st this assumption, the spatial and temporal patterns of PYSL abundance, in relation to th e regions and weeks sampled by the LRS, were examined for each target taxon (i.e., American shad, Atlantic tomcod, bay anchovy, river herring, striped bass and white perch). Th e spatial pattern of PYSL abundance was expressed in terms of the relative abundance in each of the 13 regions of the Hudson River (from the Battery to the Fede ral Dam at Troy) during in th e sampling season (ASAAC 2009). A spatial pattern characterized by low relati ve abundance at the southern boundary of the spatial extent of sampling, i.e., in regions 0 (Battery) and 1 (Yonkers), and high relative

abundance elsewhere in the River was consider ed evidence that most of the population was upstream of the southern boundary ; and therefore, the LRS ade quately sampled the spatial extent of PYSL for a species. However, a spatial pattern character ized by high relative abundance in regions 0 and 1, and low rela tive abundance elsewhere in the River was considered evidence that a substantial portion of the PYSL likely were downstream of the southern boundary; and therefore, may have mi ssed by LRS sampling. Similarly, a temporal pattern characterized by an increase in a bundance followed by a decrease in abundance during the sampling season was considered evidence that the sampling season bracketed the period of PYSL presence. However, a tempor al pattern characterized by greatest abundance occurring at the beginning or end of the sampling period was considered evidence that the sampling season may have missed the period of highest PYSL abundance.

American shad, river herring, striped bass and white perch exhibited spatial patterns of PYSL abundance that indicated the LRS samp ling program adequately sampled the spatial extent of PYSL presence (Figures 1-4). Howe ver, spatial pattern of PYSL bay anchovy and Atlantic tomcod indicated a substantial por tion of the PYSL population may have been outside the area subject to sa mpling by the LRS (Figures 5 a nd 6). American shad, river herring, striped bass, white perch, and bay anchovy exhibited tempor al patterns of PYSL abundance that indicated the LRS sampling program adequately sampled the temporal extent of PYSL presence (Figures 7-11). However, th e temporal pattern of PYSL Atlantic tomcod indicated the LRS sampling seas on generally occurred too late to capture the full period of PYSL Atlantic tomcod presence (Figure 12).

Based on these results Atla ntic tomcod and bay anchovy were excluded from further analysis. For the remaining four taxa (Ameri can shad, river herring, striped bass and white perch), annual estimates of PYSL average abundance during the sampling season from AEI Report (Barnthouse, et al 2008) were used for th e analysis in equation (9). Those estimates were based on LRS data from weeks 18 through 26 (the weeks consistently sampled by the LRS in all years, 1974-2005).

Expected Changes in Juvenile Abundance



### For those year-to-year increases in PYSL abundance with riverwide age-1 equivalents that fell within the range of potential annual increase s in age-1 equivalents due to eliminating

entrainment losses associated with current operat ion of the Stations , the corresponding

### 7 changes in juvenile abundance were summarized. Expected ch anges in juvenile abundance were characterized in terms of the probability that the change would be an increase in juvenile abundance, and in term s of the expected magnitude of change in juvenile abundance.

The probability ( 

### P ) that the change in juvenile abundance would be an increase was

estimated as:



### n x P  ˆ (10)

n = the number of pairs of years ( i’,j’ ) that satisfied the criterion of a PYSL abundance increase within the range of potential annual in creases in age-1 equivalents due to eliminating curre nt IPEC entrainment losses, and

x = of those pairs of years, the number of pairs of years with increases in juvenile

abundance.

A non-parametric Sign test (Kenda ll and Stuart, 1979) was used to test the hypothesis that the underlying probability of an increase in juven ile abundance was 0.5 (i.e., a decrease in abundance was just as likely as an increase in abundance). In addition, exact 95% binomial confidence limits (Beyer, 1968) for the estimate of the probability of an increase in juvenile

abundance were calculated.

For each species, the expected magnitude of change in juvenile abundance was calculated as the average of change s in juvenile abundance over the n pairs of years:



# 

 

###   

'

, '

, *

, 

### 1

~

j i j i j i Juv 

### JUV

n (11)

and an approximate 95% confiden ce interval was calculated as: 

#  

Juv n Juv 

### e s t   

 

### ~

. . ~

1 

### . (12)

where



#    

) 1 ( ~

~

. . '

, '

, 2 *

,



###  

 

  

# 





### n n JUV

e s j i j i Juv j i

Juv 

### (13)

and t n-1 

### is the t 

### -statistic with n 

### -1 degrees of freedom. This approximation does not explicitly

account for covariance associated with individual years that were included in more than one pair of years. Therefore, the widths of the approximate confidence intervals are likely to be

underestimates.

### 8 

### RESULTS

For each of the 4 taxa (American shad, ri ver herring, striped bass and white perch), the projected range of potential annual increas es in age-1 equivalents due to eliminating

current entrainment losses associ ated with the Stations’ operati on is very small compared to the range of year-to-year incr eases in riverwide PY SL abundance calculated from historical data (Figures 13 through 16). Within the proj ected range of potential annual increases in age-1 equivalents due to eliminating current en trainment losses associat ed with the Stations’ operation, the estimated probability of observing an increase in juvenile abundance is not significantly different than 50:50 for any of the 4 taxa (Table 2). Within that range, the estimated average annual change in juvenile abundance is not significantly different from zero for any of the 4 taxa (Table 3).



### CONCLUSIONS

The metric of potential in creases in equivalent age-1 abundance was used in the Biology Report to compare the efficacies of al ternative intake technologies at reducing

entrainment losses associated with current operat ion of the IPEC Stations. Although a convenient metric for comparing the efficacies of alternative intake technologies, the calculated age-1 equivalents cannot be used to predict changes in the abundance of age-1 fish at the species population level. The results from this assessment show that historical increases in PYSL abundance, of the magnitude that is proj ected will occur by eliminating

current entrainment losses associated with the Stations’ operation, did not result in corresponding increases in juvenile abundance (t he lifestage immediat ely preceding age-1). Rather, the juvenile abundance was just a lik ely to decline as increase, and the average change in juvenile abundance was not significantly different from zero.

Based on: (1) empirical rela tionships between year-to-ye ar increases in riverwide PYSL abundance (expressed in terms of age-1 equivalents) and year-to-year changes in riverwide juvenile abun dance, and (2) the projected ranges of relatively small potential increases in age-1 equivalents due to elimina ting current entrainment losses associated with IPEC Stations’ operation, no alte rnative intake technology consid ered as part of Entergy’s alternative technology assessment w ould be expected to result in a demonstrable increase in juvenile abundance of American shad, rive r herring, striped bass or white perch.

The results and conclusion of this assessment are consistent with the results and conclusions of the AEI Report (Barnthouse, et al, 2008), which used a completely different

set of methods to demonstrate that historical operations of the IPEC Stations have had no measurable effect on fish populations in the Hudson River.

### 9 

### REFERENCES

ASA Analysis and Communication (A SAAC). 2009. Biological an alysis of selected cooling system alternatives for Indian Point Energy Center.

Barnthouse, L.W., D.G. Heimbuch, W. Van Wi nkle, and J. Young. 2008. Entrainment and Impingement at IP2 And IP3: A Biological Impact Assessment.

Beyer, W.H. 1968. Handbook of tables for Probability and Statistics (2 n d 

### ed). CRC Press, Inc. Cleveland. 642 pp.

EA Engineering, Science and Technology (E A). 1996. 1995 year class report for the Hudson River estuary monitoring program. Prepared for Consolidated Edison Company of New York, Inc. New York, New York.

Enercon Services, Inc. 2010. Evaluation of al ternative intake technologies at Indian Point Units 2 & 3. Prepared for Entergy Nuclear Indian Point 2, LLC, and Entergy Nuclear Indian Point 3, LLC.

Kendall, M. and A. Stuart. 1979. The Adva nced Theory of Statistics: Volume 2 (4 t h 

### ed). Charles Griffin & Company Ltd, London. 748 pp.

Ricker, W.E. 1975. Computation and interpre tation of biological statistics of fish populations. Bulletin of the Fisheries Resear ch Board of Canada. Bulletin 191. 382 p. Department of the Environment, Fish eries and Marine Service. Ottawa.

USEPA. 2006. Regional Benefits Analysis for the Final Section 316( b) Phase III Existing

Facilities Rule. U.S. Environmenta l Protection Agency, Office of Water, Washington, DC. EPA-821-R-04-007.

### 10 Table 1. Projected annual increases in of age-1 equivalents due to eliminating current

entrainment losses associated with IP EC Stations’ opera tion (ASAAC, 2009).

Taxon 1 

### Projected Range of Potential Annual Increases in Age-1 Equivalents Due to Eliminating

Current Entrainment Losses From

IPEC Units 2 and 3

Minimum Projected

Annual

Increase in Age-1 Equivalents Maximum Projected

Annual Increase in Age-1 Equivalents

River Herring 12,100 86,900

American Shad <1 200 Striped Bass 76,300 561,400
White Perch 54,100 347,200

1 Bay anchovy and Atlantic tomcod were not included in the analysis because available data on the spatial and

temporal distributions of these species indicated the LRS may not have adequately sampled the full spatial and temporal extent of PYSL presence.

### 11 Table 2. Probabilities of increases in juve nile abundance correspondi ng to observed year-toyear increases in PYSL abundance (expressed in terms of age-1 equivalents) in the Hudson River that were within the project ed range of potential annual increases in age-1 equivalents due to eliminating entr ainment losses associated with current Stations’ operation.

Taxon 1 

### Number of

Pairs of

Years with

Increase in

PYSL

Abundance

that

Satisfied the

Criteria ( n 

### ) Number of

Those Pairs

of Years

with

Increase in

Juvenile

Abundance ( x 

### ) Critical Value ( k 

### )

for Sign

Test

H 0 

### : P 

### =0.5

Reject H 0 

### if

x<k



### or x>(n-k) 

### Probability of Increase in Annual Juvenile

Abundance

Estimate Lower 95%

Confidence

Limit Upper 95%

Confidence

Limit

River Herring 24 11 7 0.46 0.26 0.67

American Shad 6 2 0 0.33 0.04 0.78 Striped Bass 87 44 35 0.51 0.40 0.61

White Perch 14 10 3 0.71 0.41 0.92

1 Bay anchovy and Atlantic tomcod were not included in the analysis because available data on the spatial and

temporal distributions of these species indicated the LRS may not have adequately sampled the full spatial and temporal extent of PYSL presence.

### 12 Table 3. Expected change in magnitude of juvenile abundance corresponding to observed year-to-year increases in PY SL abundance (expressed in te rms of age-1 equivalents) in the Hudson River that were within the pr ojected range of potential annual increases in age-1 equivalents due to eliminating en trainment losses associated with current Stations’ operation.

Taxon 1 

### Average Annual Change in Juvenile

Abundance (as % of Historical Average Juvenile Abundance)

Estimate Lower 95%

Confidence

Limit Upper 95%

Confidence

Limit

River Herring +10% -35% +55%

American Shad -13% -46% +19% Striped Bass +10% -7% +27%

White Perch +20% -27% +67%

1 Bay anchovy and Atlantic tomcod were not included in the analysis because available data on the spatial and

temporal distributions of these species indicated the LRS may not have adequately sampled the full spatial and temporal extent of PYSL presence.

### 13 Figure 1. Spatial pattern of abundance of PYSL American shad in the Hudson River. Based

on LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g American Shad

### 14 Figure 2. Spatial pattern of abundance of PYSL river herring in the Hudson River. Based on

LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g River Herring

### 15 Figure 3. Spatial pattern of abundance of PYSL striped bass in the Hudson River. Based on

LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g Striped Bass

### 16 Figure 4. Spatial pattern of abundance of PYSL white perch in the Hudson River. Based on

LRS data from 1974-2005.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g White Perch

### 17 Figure 5. Spatial pattern of abundance of PYSL bay anchovy in the Hudson River. Based on LRS data from 1991-2005 (years with sampling through week 40, and sampling of region 0).

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g Bay Anchovy

### 18 Figure 6. Spatial pattern of abundance of PY SL Atlantic tomcod in the Hudson River. Based on LRS data from 1995-2005 (years with sampling beginning by week 9, and sampling of region 0).

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

0 1 2 3 4 5 6 7 8 9 10 11 12

Region R e l a t i v e D e n s i t y O b s e r v e d i n

E

a c h R e g i o n o f S a m p l i n g Atlantic Tomcod

### 19 Figure 7. Temporal pattern of abundance of PYSL American shad in the Hudson River.

Based on LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g American Shad

### 20 Figure 8. Temporal pattern of abundance of PY SL river herring in the Hudson River. Based

on LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g River Herring

### 21 Figure 9. Temporal pattern of abundance of PY SL striped bass in the Hudson River. Based

on LRS data from 1974-2005.

0.00 0.05 0.10 0.15 0.20 0.25

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g Striped Bass

### 22 Figure 10. Temporal pattern of abundance of PY SL white perch in the Hudson River. Based

on LRS data from 1974-2005.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g White Perch

### 23 Figure 11. Temporal pattern of abundance of PYSL bay anchovy in the Hudson River. Based on LRS data from 1991-2005 (years with sampling through week 40, and sampling of region 0).

0.00 0.05 0.10 0.15 0.20 0.25

9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g Bay Anchovy

### 24 Figure 12. Temporal pattern of abundance of PYSL Atlantic tomcod in the Hudson River. Based on LRS data from 1995-2005 (years with sampling beginning by week 9, and sampling of region 0).

0.00 0.05 0.10 0.15 0.20 0.25

9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39

Week R e l a t i v e A b u n d a n c e O b s e r v e d i n

E

a c h W e e k o f S a m p l i n g Atlantic Tomcod25-3-2-10123 0 2 ,5 00 5,000 7, 50 0 10, 000 12,500 1 5, 000 17,500 20 ,0 00 22,500Projected Range of Potential Annual Increase in Age-1 EquivalentsDue to Eliminating Current IPEC Entrainment LossesObserved Year-to-Year Increase in PYSL Abundance(Expressed as Increase in Equivalent Age-1 Abundance)ObservedChangeinJuvenileAbundance(ExpressedasaMultipleofAverageJuvenileAbundance)American ShadFigure 13. Observed year-to-year changes inriverwide juvenile abundance of Americanshad in response to observed year-to-yearincreases in riverwide PYSL abundance.Based on all pairs of years (1985-2005)with observed positive change in PYSLabundance.26-4-3-2-101234 0 200,000 400,000 6 00,000 80 0, 0 00 1,000 , 000 1 , 20 0, 00 0 1, 4 00, 0 00 1,600,000 1,800,000 2,000,000 2,200,000 2 , 400 , 000 2,6 0 0, 00 0 2, 8 0 0 , 00 0 3,0 0 0, 0 00Projected Range of Potential Annual Increase in Age-1 EquivalentsDue to Eliminating Current IPEC Entrainment LossesObserved Year-to-Year Increase in PYSL Abundance(Expressed as Increase in Equivalent Age-1 Abundance)ObservedChangeinJuvenileAbundance(ExpressedasaMultipleofAverageJuvenileAbundance)River HerringFigure 14. Observed year-to-year changesin riverwide juvenile abundance of riverherring in response to observed year-to-yearincreases in riverwide PYSL abundance.Based on all pairs of years (1974-2005)with observed positive change in PYSLabundance.27-2-1.5-1-0.500.511.52 0 1,00 0 ,000

2, 00 0,0 0 0 3 ,0 00, 00 0 4, 0 00,0 0 0 5,00 0 ,000

6, 00 0,0 00 7,00 0 ,000

8, 0 00,0 0 0 9 ,0 00, 00 0 10, 0 00, 00 0Projected Range of Potential Annual Increase in Age-1 EquivalentsDue to Eliminating Current IPEC Entrainment LossesObserved Year-to-Year Increase in PYSL Abundance(Expressed as Increase in Equivalent Age-1 Abundance)ObservedChangeinJuvenileAbundance(ExpressedasaMultipleofAverageJuvenileAbundance)Striped BassFigure 15. Observed year-to-year changesin riverwide juvenile abundance of stripedbass in response to observed year-to-yearincreases in riverwide PYSL abundance.Based on all pairs of years (1974-2005)with observed positive change in PYSLabundance.28-3-2-10123 0 5,000 , 000

10, 0 00,0 00 15, 000 ,00 0

2 0, 000 ,0 00 2 5, 000, 00 0 30 ,0 00, 00 0 3 5 ,000, 00 0 40, 0 00, 00 0Projected Range of Potential Annual Increase in Age-1 EquivalentsDue to Eliminating Current IPEC Entrainment LossesObserved Year-to-Year Increase in PYSL Abundance(Expressed as Increase in Equivalent Age-1 Abundance)ObservedChangeinJuvenileAbundance(ExpressedasaMultipleofAverageJuvenileAbundance)White PerchFigure 16. Observed year-to-year changesin riverwide juvenile abundance of white perch in response to observed year-to-yearincreases in riverwide PYSL abundance.Based on all pairs of years (1974-2005)with observed positive change in PYSLabundance.

# Appendix D

Responses to Issues Raised in NYSDEC’s FEIS

Lawrence W. Barnthouse, Ph. D. LWB Environmental Services, Inc.



## February 2010

### 1 In the Final Environmental Impact Statement for State Pollution Discharge Elimination System (“SPDES”) permit renewals at the Roseton 1 & 2, Bowline 1& 2, and Indian Point 2 & 3 steam electric generating st ations (the “FEIS”), the New York State Department of Environmental Conservation (“NYSDEC”) raised issues concerning the impacts of entrainment and impingement on fi sh populations and communities that were

not addressed in the Draft Envi ronmental Impact Statement (the “DEIS”) prepared by the Hudson River utility companies. Many of these i ssues were initially raised in a review of the DEIS prepared for NYSDEC by ESSSA Technologies, Inc. (ESSA 2000).

This attachment documents a re-evalua tion of these issues by Entergy Nuclear Indian Point 2, LLC and Enter gy Nuclear Indian Point 3, LLC (collectively “Energy”) and provides further support for the conc lusion reached in Entergy’s Adverse Environmental Impacts (“AEI”) Report (Barntho use et al. 2008) that historical operations of Indian Point Energy Center (“IPEC”) Units 2 and 3 have not adve rsely affected fish populations and communities in the Hudson River. 1



## D.1 Correction of errors and misinterpretations in ESSA/Deriso critiques of the DEIS

ESSA (2000) conducted a review of the DE IS on behalf of NY SDEC, identifying a number of purported weaknesses in the DEIS. The purpose of this section is to evaluate

the relevance of ESSA’s revi ew in light of Entergy’s Ja nuary 2008 AEI Report and other current documents, and to correct some errors made in ESSA’s review. Many of ESSA’s

criticisms of the DEIS are no longer relevant due to Ente rgy’s submission of the AEI Report and other current documents, which are based on more recent data and on detailed empirical analysis (as opposed to predicti ve models) of Hudson River data sets.

Entergy’s AEI Report and other current documents cast doubt on the relevance and accuracy of ESSA’s criticisms concerning the method used to compare entrainment and impingement mitigation alternatives and the detailed population-level impact analyses for Atlantic tomcod, bay anchovy, st riped bass, and white perch. The first

reason that ESSA’s criticisms of the DEIS are no longer relevant is that a larger data set was available for the AEI Report as compared to the DEIS. The DEIS is based on data collected through 1997, whereas th e AEI Report is based on data collected through 2004.

This difference is important because some of the key conclusions in the DEIS, which were criticized by ESSA, relied on comparisons between population trends over the period 1991-1997 and similar trends over ear lier time periods. The availability of 7 additional post-1990 years allowe d for more meaningful comp arisons between recent and earlier time periods. The second reason that ESSA’s criticisms of the DEIS must be discounted is that the AEI Report was based on a fundamentally different approach to

1 This report supports the “Biological Effectiveness of Alternative Intake Technologies for Indian Point Units 2 and 3” (the “Biological Report”) prepared by Lawrence W. Barnthouse of LWB Environmental Services, Inc., Douglas G. Heimbuch of AKRF, Inc., Mark T. Mattson of Norm andeau Associates, Inc., and John R. Young of ASA Analysis & Communication, Inc.

### 2 evaluating the impacts of Indian Point’s c ooling water withdrawal s on Hudson River fish populations. Whereas the DEIS relied on pred ictive models to quantify impacts of cooling water withdrawals on future popula tion trends, the AEI Report relied on empirical analyses of the 30-year time series of Hudson River data to test alternative hypotheses concerning causes of historical changes in fish populations. Critical assumptions required to implement the populatio n models used in the DEIS, which were a major focus of ESSA’s review, we re not used in the AEI Report.

The following sections identify specific issues raised by ESSA that are now irrelevant, and also those issues that are s till relevant. Additional quantitative analyses performed to address some of these issu es are documented in Attachment D-1.



### D.1.1 ESSA Overview

ESSA’s review included three major components:

1. A review of the entrainment and impingeme nt mitigation alternatives discussed in the DEIS, including the methods used to calculate Fish Protection Points (“FPP”),

which were used in the DEIS to evalua te the influence of alternative outage schedules on entrainment mortality.

2. Detailed evaluations of entrainment a nd impingement impact assessments for Atlantic tomcod, bay anchovy, striped bass, white perch, and American shad. A significant portion of the ESSA work for each species involved a detailed review of population models used in the DEIS.

3. A review of the evaluation of cooling to wer alternative presented in the DEIS. 2



### D.1.2 ESSA criticisms that are no longer relevant

Density-dependence

ESSA (2000) stated (p. iii) that “The ba sic logic of the DEIS rests heavily upon arguments that density-dependent mechanisms of compensatory survival offset the effects of generating station induced entrainment and impinge ment mortality.” In other words, ESSA challenges the DEIS’s conclusi on that mortality caused by entrainment and impingement reduces competition for food between the young fish that are not entrained or impinged, leading to increase d survival that offsets the plant-induced mortality. For this reason, a significant portion of ESSA’s work involved a detailed review of population dynamics models that were used in the DEIS to quan tify density-dependence in Hudson River fish populations. With the exception of specific data-related

2 The technology alternatives addressed in the DEIS are superseded by the alternative technologies

discussed in this report. Accordin gly, ESSA’s comments on the DEIS cooling tower alternative are not

relevant and need not be discussed here.

### 3 uncertainties discussed below, however, E SSA’s comments on density-dependence and modeling are no longer releva nt, because Entergy’s AEI Report did not rely on densitydependence, and did not use models of the type critiqued by ESSA.

The Fish Protection Point (“FPP”) system

In the DEIS, the amount of protection from entrainment that could be achieved by reducing cooling water flow is expressed as FPPs, which were used to compare the biological benefits of altern ative unit outage schedules. FPPs are not used to quantify biological benefits associated w ith the alternative technologies analyzed in this report. Thus, most of ESSA’s comments concerning FPPs are not relevant. Both the FPP system and the AEI Report assessment approach, however, relied on entrainment and impingement estimates termed conditional mortality rates (“CMR”). 3 

### Hence, ESSA’s

comments on the methods and data used to ca lculated CMRs are st ill relevant and are

discussed below.

Bay anchovy individual-based model

ESSA commented on the use in the DE IS of an “individual-based population model” to quantify potential impacts of coo ling water withdrawals on bay anchovy. The model in question was not used in the AE I Report, Thus, ESSA’s comments on the model are no longer relevant.

Alternative American shad modeling

As an addendum to ESSA’s (2000) repor t, Deriso et al. (2000a) used an alternative spawner-recruit model to quantif y the combined impacts of cooling water withdrawals and fishing on American shad. According to the model results derived by Deriso et al. (2000a), entrainment and im pingement at Hudson River power plants significantly affect the abunda nce and sustainable harvest of adult shad.

Conclusions based on the analysis of Deri so et al. (2000a) are no longer relevant, for two reasons. First, a recent stock assess ment performed by the A tlantic States Marine Fisheries Commission (ASMFC 2007) conclu ded a serious decline in the coastwide

abundance of American shad has occurred since 1990, that the primary cause of the decline is increased mortality of adult fish (not the early life stages of fish that are susceptible to cooling water withdrawals), and that commercial fishing is the most likely cause of the increased mortality. The ch apter on the Hudson River American shad population, which came to this same c onclusion, was drafted by NYSDEC staff. Mortality to early life stages related to cooling water withdrawals was not identified as a significant contributing cause.

3 CMRs estimate the fraction by which the abunda nce of young-of-the-year fish is reduced due to

entrainment or impingement [AEI Report, p. 13]. For entrainment, CMRs are a function of the spatial and temporal distributions of susceptible life stages within the river, the rates of cooling water withdrawals by power plants, and the mo rtality rates of entrained organisms

### 4 Second, potential mortality of Hudson Rive r American shad related to cooling water withdrawals has already been greatly reduced since the DEIS was completed. According to Table V-26 of the DEIS, th e Albany Steam Plant was historically responsible for 85% of all entrainment and impingement mortality of American shad. This plant was permanently shut down in 2005.



### D.1.3 ESSA criticisms that are still relevant

As discussed in more detail below, some of ESSA’s criticisms of the DEIS are relevant and, accordingly, must be addressed in turn. In total, ESSA focuses on five issues that are relevant to this SPDES pr oceeding. First, Section 2.5 of ESSA (2000)

discusses issues related to entrainment estimation and the use of CMR estimates for the years 1991-1997 as the basis for calculating FPPs . Because CMRs were also used in Entergy’s AEI Report as metrics for entrainment impacts, these comments are potentially relevant to the AEI Report and other relate d documents. ESSA expressed “substantial

concerns” about the influence on FFP calcu lations of inter-annual variation and uncertainties in through-pla nt survival rates.

Second, Section 3 of ESSA’s report discusse s issues relating to the assessment of impacts of entrainment and impingement on A tlantic tomcod. Some of these issues involved assumptions concerning density-dep endence and carrying capacity used in modeling tomcod population dynamics. As noted above, these issu es are no longer relevant because the AEI Report did not re ly on density-dependence and did not use models of the type critiqued by ESSA. Howe ver, ESSA also raised concerns regarding uncertainty in data sources, the magnitude of fishing pressure, temperature effects, and effects of changes in flow and nutrients. These issues are addressed below.

Third, Section 4 of ESSA’s report discusse s issues relating to the assessment of impacts on bay anchovy. Most of these issues concern the bay anchovy individual-based model used in the DEIS. These bay anchovy-re lated criticisms are not relevant because this individual-based model was not used in the AEI Report. However, ESSA also commented on analyses of impacts of pred ation on bay anchovy provided in the DEIS, and on ecological factors contributing to va riations in bay anc hovy abundance. These issues are still relevant, a nd are addressed below.

Fourth, Section 5 of ESSA’s report discusse s issues relating to the assessment of impacts on striped bass. In addition to critic isms related to populat ion modeling that are no longer relevant because the AEI Report did not rely on models of the kind used in the DEIS, ESSA expressed concerns about the reliability of the st riped bass abundance

indices used in the DEIS. This issue is still relevant and is addressed below.

Fifth, and finally, Section 6 of ESSA’s report discusses issues relating to the assessment of impacts on white perch. Some of these issues relate to analyses of densitydependence that are no longer relevant becau se the AEI Report did not rely on densitydependence. ESSA, however, also criticized the DEIS’s analys es of temporal variation in

### 5 white perch abundance, and of alternative hypotheses concerning causes of this variation. In addition, ESSA recommended the use of “production foregone” modeling to quantify ecosystem-level effects of entrainment and im pingement. These issues are relevant and

are discussed below.



### D.1.4 Detailed evaluation of relevant issues

Uncertainty in estimating CMRs

CMRs were a key component of the FPP system used in the DEIS and the hypothesis-testing approach used in Entergy’s AEI Report. In both of these applications,

CMRs were used as measures of entrainment and impingement mortality. As discussed in Section 2.3 of the AEI Report, CMRs should not be used as measures of the impacts of entrainment and impingement mortality on the long-term abundance or sustainability of susceptible fish populations.

ESSA criticized the DEIS’s use of th rough-plant survival rates in the CMR estimates, and also expressed concern that changes in the riverw ide distribution of entrainable life stages during the period 1991- 1997 might invalidate the use of CMRs as measures of plant-related mortal ity rates during this period.

With regard to through-plant mortality ra tes, ESSA (2000) notes that the DEIS used mechanical mortality rates averaged over all plants for which data were available, and that inadequate data for estimating mechan ical mortality rates was available for some species. Because of these data limitations, ESSA (2000) concludes that the through-plant mortality rates used in the DEIS were “low er bounds” on actual entrainment mortality. This criticism does not apply to assessmen ts performed for Unit 2 and Unit 3, because through-plant mortality rates for fish species entrained at these Units are based solely on data collected at Unit 2 and Unit 3, so that no averaging across plants is needed. Where data were inadequate to estimate a through -plant survival rate , zero survival was conservatively assumed.

With regard to inter-annual variation in entrainment, ESSA (2000) presents a table (Table 4, p. 13) and several figures (Fig ures 1a through 1e) showing an apparent decline in CMR values during the period fr om 1991-1997 used for the FPP baseline. In section 2.5.2, ESSA (2000) argues that these a pparent declines coul d indicate a shift in

the distribution of entrainable lif e stages of fish in response to altered habita t conditions. The annual CMR values are based on year-s pecific survey data that track the longitudinal, i.e. upstream or downstream, distri bution of fish within the river. Thus, the CMR estimates only account for upstream or downstream movements. The models used to calculate CMRs do not, however, utilize year-specific estimates of the lateral distribution of fish in the vicinity of each fa cility, including Units 2 and 3. Instead, the

models use to calculate CMRs use a plant-specific distributi on factor derived from data collected over several years in the 1980s to estimate the density of entrained organisms in cooling water withdrawn by each facility, relative to the aver age density of organisms in

### 6 the river cross-section adjacent to the intake st ructure. ESSA (2000) suggested that if the habitat changes that lead to alterations in the upstream-downstr eam distribution of entrainable organisms also led to a movement of organisms toward the shoreline where they would be more vulnerable to entrainm ent, then recent CMRs and FPP values would

be biased and would underestim ate the actual entrainment mortality imposed by cooling

water withdrawals. Because the most recent years (i.e., 1991-1997) were the basis for evaluating the alternative outage schedules ad dressed in the DEIS, the level of fish protection provided by all of the alte rnatives would be overestimated.

Entergy’s AEI Report evaluated both time tr ends in CMRs and trends in upstream

vs. downstream distribution of Representative Important Species (“RIS”) using a larger

data set than was available for the DEIS. A statistically significant shift in upstream

versus downstream distribution of larv ae over the period 1984-2004 was observed for only one species, spottail shiner . Statistically sign ificant long-term trends in CMR values for Unit 2 and Unit 3 were not observed for any species. Hence, th e analysis documented in the AEI Report, which incl uded 7 additional years of data , showed that the arguments used by ESSA to support its conjecture abou t biased CMR values are not supported by available data. Contrary to ESSA’s assert ions, the spatial distributions of the species most susceptible to entrainment at Indian Point have not changed, and the estimated CMR values show no long-term trend. No empirical evidence supports ESSA’s speculation that larval fish might have m oved toward the shoreline in recent years, resulting in increased susceptibility to entrainment and biased CMR values.

Additional evidence supporti ng the validity of the CMR as a measure of annual variations in mortality at Unit 2 and Unit 3 is provided in Attachment D-1. Attachment D-1 documents an analysis of the relationship between CMR estimates for 

### Unit 2 and Unit

3 and a simple, empirical predictor of entrainment risk based on (1) larval location in the river and (2) cooling water withdrawal rates at IP and IP3. The empirical predictor does not include the distribution factors and survival estimates that were criticized by ESSA. If ESSA’s claims concerning uncertainties and biases in the CMRs had merit, then the CMR values should be weakly correlated with independent measures of entrainment susceptibility and the nature of the relationship should be different during years after 1990 than during the period from 1974-1990. Attachment D-1 shows that, for all of the species addressed in ESSA’s comments (Atlantic tomcod, American shad, bay anchovy, river herring, striped bass, and white perch), CMR values are strongly correlated with independent measures of larval location and cooling water withdrawal rates. Moreover, none of these relationships are different during the years after 1990 than during the years 1974-1990. Furthermore, Attachment D-1 shows that the available data support the conclusion that a systematic shift in nearshore-offshore distributions patterns of larvae did not occur between the 1980’s and 1990’s, as hypothesized by ESSA. Hence, ESSA’s concern that recent CMR rates 

### would be

biased and would underestimate the actual entrainment mortality imposed by cooling

water withdrawals is invalid.

Uncertainties in the Atlantic tomcod assessment

ESSA’s comments on the Atlantic tomcod assessment were summarized in Section 3 of the review report and documente d in a companion report (Parnell et al.

### 7 2000). These comments addressed four issues that are relevant to the AEI Report and other reports related to this SPDES pro ceeding: uncertainty in data sources, the magnitude of fishing pressure, temperature e ffects, and effects of changes in flow and

nutrients.

At the outset, Entergy has resolved ESSA’s concerns regarding data uncertainty. ESSA noted unresolvable discrepancies between the data presented in Appendix VI-4-B and Table 9 of Appendix V-3-C of the DEIS . In preparing the AEI Report, Entergy performed a complete review of all data s ources and fully documente d all data used in Appendix B to that report. The tables referre d to in ESSA’s comments were not used in the AEI Report. Therefore, the discrepancie s noted by ESSA do not affect any analyses

that are relevant to the current proceeding.

ESSA claimed that the data used in Atlantic tomcod population modeling was of “poor quality” because estimates of annual egg production were derived from spawner abundance data, sex ratios, age structure, an d age-specific fecundity. According to ESSA, this approach leads to “confounding.” In fact, estim ates of spawner abundance, sex ratio, age structure, and age-specific fecundity are commonly used to estimate egg production, when estimates of the necessary pa rameters are available. Deriso et al. (2000a) used these same parameters as i nputs to their spaw ner-recruit model for

American shad. Models that utilize these kinds of data are termed “age-structured” models, and are discussed in Chapter 6 of Qu inn and Deriso (1999). The Atlantic tomcod mark-recapture program provides annual estimate s of all of the parameters needed to calculate egg production. ESSA did not review or criticize the methods used in this mark-recapture program. In sum, ESSA’s claim th at the data derived from this survey are “poor quality” is groundless.

ESSA claimed that the time series of a bundance data used in the Atlantic tomcod analysis was too short, because data were available only through 1997. As noted above, the AEI Report conclusions are based on an additional 7 years of data. The critical period of concern for Atlantic tomcod, both in the DEIS and in the AEI Report, began in 1991. Thus, the additional 7 years of data is critical, as the AEI Repor t’s time series of available data for the post-1990 period is tw ice as long (1991-2004) than the DEIS data (1991-1997). Thus, the AEI Report addressed ESSA’s concern regarding data availability.

ESSA claimed that the DEIS should have evaluated the importance of fishing mortality as an influence on Atlantic tomc od population dynamics. The AEI Report also could not address this impact as there is no data are available concerning the magnitude of fishing mortality for Atlant ic tomcod. In the absence of data, fishing mortality could not be included in the list of potential cause s of change evaluated in the AEI Report.

ESSA noted that the DEIS did not addre ss effects of temperature on Atlantic tomcod. The AEI Report addresses relationshi ps between long-term trends in river temperature and Atlantic tomcod abundance. It concludes that elevated summer temperatures are associated with reduced surv ival of juvenile Atlantic tomcod, however,

### 8 long-term trends in river temperature ca nnot account the decline in tomcod abundance that has occurred since 1990. The AEI report concludes that other factors, probably including predation by striped bass, we re responsible fo r this decline.

ESSA noted that the DEIS did not addre ss effects of changes in river flow and nutrients on the growth and survival of juveni le Atlantic tomcod. ESSA provided no hypothesis concerning how flow itself could aff ect Atlantic tomcod growth or survival. In the absence of a plausibl e causal hypothesis, the inclusi on of flow in the suite of

causes addressed in the AEI Re port would have been meaningl ess. Changes in nutrient concentrations could conceivably lead to ch anges in the growth or survival of many species, however, no long-term, riverwide data on nutrient concentrations are available for the Hudson River. Hence, this parameter could not be included in the trends analyses performed for the AEI Report.

Uncertainties in the bay anchovy assessment

ESSA’s comments on the bay anchovy asse ssment were summarized in Section 4 of the review report and documented in a companion report (Par nell and Marmorek 2000). The bulk of the review focused on the results of bay anchovy population modeling. Since no population model was incl uded in the AEI Report, most of ESSA’s comments are no longer relevant. Three issu es raised by ESSA are still relevant, however: (1) the importance of immigration from New York Harbor in maintaining the bay anchovy population present in the Hudson River estuary; (2) the importance of predation as a factor influencing bay anc hovy abundance; and (3) the potential influence of entrainment on the biomass of bay anchovy available to predators.

These issues have been addressed in publis hed scientific studies and in additional new analyses documented in Attachment D-1. As discussed in the DEIS (pp. V-112 to V-114), bay anchovy is a marine species that is abundant in coastal waters and estuaries along the Atlantic and Gulf coasts, between Maine and the Yucatan Peninsula, Mexico. During summer, bay anchovies are abundant in the Hudson River and in adjacent marine waters. However, during winter they migrat e south and are virtually absent from the New York region. This simple fact of life hi story demonstrates that the Atlantic coastal population is the ultimate source of all ba y anchovies present in the Hudson River. Dunning et al. (2006a) documented the presen ce of bay anchovy eggs and larvae in New York Harbor, the East River, and Long Island Sound. They f ound that the peak abundance of bay anchovy eggs and larvae in these water bodies wa s about eight times higher than in the Huds on River. That finding clearly demonstrates that a large source population is available in waters adjacent to the Hudson. Dunning et al. (2006a) also found that bay anchovy eggs were present only in the lower estuary, adjacent to New

York Harbor.

The likely nature of movements between coastal waters and the Hudson River is

examined further in Attachment D-1. The purpose of this analys is is to determine whether bay anchovy larval abundance in the Hudson River can be predicted by salinity, freshwater flow rate and water temperature. Literature discussed in the DEIS shows that

### 9 bay anchovy spawn primarily in waters with salinities greater than 10 parts per thousand (“ppt”), or about one-third the salinity of seawater (33 ppt). The salinity of the Hudson River estuary is determined by the degree of mixing between marine waters transported into the Hudson by tidal movements and fres h water transported downstream from the Hudson River watershed. Salinities are high est at the lower end of the estuary and gradually decrease upstream. When freshw ater flows are high, le ss marine water is transported into the Hudson, the salinity of the lower Hudson decreases, and the proportion of the river within which salinit ies are suitable for bay anchovy spawning decreases. When freshwater flows are low, more marine water is transported into the Hudson, the salinity of the lower Hudson increa ses, and the proportion of the river within

which salinities are suitable for bay anchovy spawning increases.

If bay anchovy in the Hudson River are onl y a small fraction of the mid-Atlantic stock, and if they enter the Hudson River opportunistically depending on the movement

of saline waters from New York Harbor in to the Hudson, then larval abundance should be correlated with physical properties of the Hudson. When a large proportion of the river is influenced by the intrusion of sa line marine waters, more bay anchovy should move into the river to spawn, and more larvae should be present than in years when a low proportion of the river is influe nced by marine intrusion.

The analysis presented in Attachment D-1 examines the relationship between the bay anchovy larval abundance index used in the AEI Rreport and the proportion of the Hudson River with salinity greater than 5 parts per thousand (“ppt”) during the spring, freshwater flow rates in the spring, and the pr oportion of the river with high temperatures (>75 o 

### F) in the spring. As documented in Atta chment D-1, a strong relationship exists between the abundance of bay anchovy larv ae in the Hudson and these physical properties of the River. Since the abundance of larvae is an indicator of the abundance of the spawning adults that pr oduced the larvae, these resu lts indicate that more bay anchovy move into the river to spawn when salinities are hi gh than when salinities are low. Together with the immigration findings of Dunning et.al. (2 006a), the analysis documented in Attachment D-1 supports the proposition that the bay anchovy population present in the Hudson River is a component of a much larger coas tal population, of which a variable fraction enters the river opport unistically depending on annual salinity

conditions.

With respect to predation, although the AEI Report concluded that entrainment at Unit 2 and Unit 3 was not an important influenc e on the survival of bay anchovy larvae to the juvenile stage, it did not include a quantitative analysis of potential predation effects. Attachment D-1 documents an analysis that addresses the influences of both entrainment and striped bass predation on the survival of bay anchovy larvae in the Hudson River. The first step in this analysis shows that the abundance of juvenile bay anchovy in the Hudson is strongly influenced by the spatial distribution of larvae. When larvae are widely distributed, juvenile bay anchovy are mo re abundant than in y ears when larvae are

restricted to the lower river. The second step in the analysis shows that, in contrast to the influence of spatial distribution, entrainment, as measured using the same CMR values used in the AEI Report, has no detectable influence on the abundance of juvenile bay

### 10 anchovy. The third step in the analysis show s that potential striped bass predation, as measured using a striped bass abundance index, has a statistically significant in fluence on the abundance of juvenile bay anchovy. This result supports the conclusion of the AEI Report that entrainment at Unit 2 and Unit 3 has no influence on the abundance of bay anchovy in the Hudson River, but that pred ation by striped bass may be an important influence on this population.

ESSA asserted that, even if immigration from outside the Hudson River replaced bay anchovy lost due to entrainment and impingement, immigration would not compensate for the potential ecological impacts of entrainment on coastwide bay anchovy abundance. ESSA recommended that a “production foregone” analysis be performed to address the potential impacts on predators due to reduced coastwide abundance of bay anchovy. Production foregone re fers to the loss in potential future prey

biomass that occurs because the entrained and impinged prey are no longer feeding and growing. Because the potential prey biomass is reduced, prey consumption by predators is also reduced, resulting in a reduction in predator bioma ss. Estimates of production foregone due to bay anchovy entrainment ar e provided in Attachment D-1. Such

estimates are used in economic benefits anal yses to quantify the potential reduction in harvest of predator fish resulting from reduced abundanc e of prey (EPA 2004, EPRI 2004). As discussed in section D.2 below, production foregone models utilize unreastically conservative assumptions about th e fate of entrained and impinged fish and, therefore, overestimate the actual reductions in predator biomass and harvest that would result from entrainment and impinge ment of prey such as bay anchovy.

Uncertainties in the striped bass assessment

ESSA’s comments on the striped bass assessment were summarized in Section 5 of the review report and documented in a comp anion report (Deriso et al 2000b). Most of the comments related to the striped bass popul ation model used in the DEIS, and are no longer relevant because the AEI Report did no t rely on a population dynamics model. However, ESSA also criticized the juvenile abundance indice s, including the Beach Seine Survey (“BSS”) index, used as inputs to the striped bass population model. According to ESSA, these indices are unreliable measur es of the annual production of young striped

bass from the Hudson River. Because the AEI Report relied on the BSS index, this

criticism is still relevant and is addressed below.

Barnthouse et al. (2003) showed that th e striped bass BSS index is strongly correlated with the NYSDEC juvenile striped bass index, and that both of these indices are strongly correlated with measures of s ubsequent 1-year-old a nd 2-year-old striped bass abundance derived from the annual stripe d bass mark-recapture survey. This finding supports the validity of the BSS index. Sim ilar analyses documented in Appendix A to the AEI Report also supported the validity of th e BSS index. The fact the Atlantic States Marine Fisheries Commission accepts the NYSDE C index, which is strongly correlated with the BSS index, as a valid measure of striped bass recruitment from the Hudson River, further supports the va lidity of the BSS index. Th is support for the BSS index mitigates against ESSA’s concern about the validity of the index.

### 11 Moreover, ESSA’s critique of the B SS and NYSDEC juvenile abundance indices

was based on an assertion that the rate of migration of juvenile striped bass out of the Hudson has changed since 1988 as a result of improvements in water quality in the lower Hudson. According to ESSA, since 1988 juven ile striped bass have been emigrating to the Long Island Sound during the late summer and fall period in which both the generators and NYSDEC are conducting their su rveys. ESSA supported this assertion with data showing an increase in the abundance of juvenile striped bass in the western Long Island Sound in recent years. If the fraction of juvenile striped bass emigrating from the Hudson into Long Island Sound during the late summer and fall has increased,

then index results for recent years would be biased becaus e the surveys are sampling a smaller proportion of the habitat occupied by juvenile striped bas than they were in earlier years. This bias, according to ESSA, would affect both the BSS and the NYSDEC

indices.

After ESSA’s review of the DEIS, Dunning et.al. (2006b) documented the presence of striped bass larvae in the East River, and demonstrated that striped bass

larvae from the lower Hudson River could be passively transported, by tidal currents, to the East River and western Long Island Sound. Hence, the juvenile striped bass present in Long Island Sound during the late summer and fall could have been passively transported out of the Hudson as larvae, ra ther than emigrating as juveniles.

Accordingly, Attachment D-1 contains an analysis of the source of the juvenile striped bass present in western Long Island Sound. The analysis us es two variables to explain patterns of juvenile abundance in Western Long Island Sound. The first is the abundance of striped bass larv ae in the Hudson River, and th e second is freshwater flow in June. This analysis show s that striped bass juvenile a bundance in Western Long Island Sound is proportional to larval abundance in the Hudson River; and that the proportionality depends on the fres hwater flow rate in June. Higher freshwater flow rates are associated with higher pr oportions of the larval abundan ce leaving the River. There

is no indication that this relationship changed after 1988. Thus, ESSA’s concern that

both the BSS and NYSDEC indices are biased is unfounded.

The results from this analysis indicate that the recent increase in abundance of juvenile striped bass in western Long Isla nd Sound has been due to a combination of

increased larval abundance in the Hudson River and inter-annual variab ility in freshwater flow rates. These results, together with the previous findings di scussed above, strongly support the validity of the BSS index as a meas ure of long-term trends in the abundance of juvenile striped bass in the Hudson River.

Uncertainties in the white perch assessment

ESSA’s comments on the white perch assess ment were summarized in Section 6 of the review report and documented in a companion report (Par nell and Marmorek 2000). ESSA criticized the method used in the DEIS to explore temporal variations in white perch abundance, and to evaluate alte rnative hypotheses that could explain those

### 12 variations. In addition, ESSA criticized the indices of de nsity-independent survival of larvae white perch. Finally, ESSA recommended the use of an index of “biomass loss to the ecosystem” to address the impact of wh ite perch entrainment both on the white perch population and on the Hudson River ecosystem.

In the DEIS, temporal variations in a bundance of white perch life stages were addressed by subdividing the available time series (1974-1 997) in terms of three time periods: 1974-1979, 1980-1988, and 1989-1997. ESSA ar gued that this subdivision is subjective, and that an alte rnative subdivision could lead to different conclusions concerning the nature of the trends. This comment is no longer relevant, because the white perch analysis in the AEI Report did not subdivide the available time series (1974- 2004) into segments.

In the DEIS, five alternative hypotheses concerning causes of changes in the abundance of white perch were evaluated: fishing, entrainment, water quality, competition with striped bass, and predatio n by striped bass. ESSA argued that the evaluations in the DEIS relied on subjective vi sual evaluation of pa tterns and correlations between indices. For this reason, ESSA conc luded that the evaluations did not provide information useful for forecasting the effect of power plant water withdrawal on the Hudson River white perch population. This comment is still relevant, because hypothesis-testing is a key component of the AEI Report.

T 

### he approach taken to hypothesis-testi ng in the AEI Report was, however, quite different from the approach taken in the DEIS. The AEI Report relied on the “ecoepidemiology” approach documented by Su ter (2007). This approach involves the comparative testing of relevant hypotheses ag ainst five criteria for evaluating causal

associations. The five criteria and the st eps involved in applyi ng the criteria were described in Section 3 of the AEI Report. C onsistent with Suter et al. (2007), the intent was not to definitively identify the causes of changes in the abundance of white perch and other fish populations, but to distinguish between causal agents that possibly could have

contributed to the observed cha nges and agents that are very unlikely to have contributed to those changes. For white perch, as for th e other species addressed in the AEI Report,

entrainment at Unit 2 and Unit 3 was found to be a very unlikely to have contributed to historical abundance trends. No attempt was made to forecast future trends in abundance of any species. However, the implication of the analysis documented in the AEI Report is that, since entrainment at Unit 2 and Unit 3 is unlikely to have influenced historical abundance trends in white perch or other sp ecies, it is similarly unlikely to influence

future trends.

ESSA criticized the DEIS for using the post yolk-sac larval (“PYSL”) abundance index as an index of density-independent surviv al of PYSL. This comment is irrelevant, because the PYSL index was not used in this way in the AEI Report. In the AEI Report,

the PYSL index was used stri ctly as an abundance index. The survival of white perch PYSL was addressed by comparing the PYSL index to the white perch juvenile index from the Beach Seine Survey. This surviv al index would include the effects of both density-dependent and density-independent surv ival. Thus, ESSA’s concern is no longer

relevant.

### 13 ESSA recommended that the DEIS should be revised to address “biomass lost to the ecosystem,” i.e., the loss of food available to predators due to the entrainment and impingement of white perch. These losses w ould include the biomass of fish killed by entrainment and impingement, the loss of biomass due to the future growth of the entrained and impinged fish, and the loss of biomass harvest by fisheries due to entrainment and impingement mortality. Acco rding to ESSA, such an assessment should make the conservative assumption that all mortality represents a food source no longer available to predators. In other words, th e entrained and impinged fish are completely removed from the ecosystem, predators that would have consumed those fish do not find alternative prey, and prey that would have b een consumed by those fish are not consumed by other predators.

The fallacy of ESSA’s preferred conservati ve assumption is discussed in depth in

Section D.2 of this attachment. All fish entrained or impinged at Unit 2 and Unit 3 are returned to the river, where they are sus ceptible to consumption by the same suite of predators that would have consumed them had they not been entrained or impinged. Because of the many interconnect ing links in typical estuar ine food webs, little or no biomass would actually be lost to the ecosystem.



### D.1.5 Conclusion

Comments made in ESSA’s (2000) re view of the DEIS do not affect the reliability of Entergy’s AEI Report, the analysis of alternative technologies documented in this report, or any other report submitted by Entergy in this Proceeding. An in-depth analysis of ESSA’s review shows that all of ESSA’s substantive comments are either irrelevant as to the AEI Report and other documents, or are easily refuted by additional analyses of the available Hudson River da ta and published scientific literature.



## D.2 Impacts on the Hu dson River ecosystem

The FEIS incorrectly concl udes that power plants ha ve appreciable indirect effects on fish populations in the Hudson River. (FEIS at 51-45). Quoting from a report prepared by Henderson and Seaby (2000), the FE IS states that “Lar ge temporal changes in fish species abundance together with a sm all decrease in total species richness and diversity suggest that the Hudson estuary ecosystem is far from equilibrium” (FEIS, p. 52) and “it is not possible to dismiss the influence of the power plants on the fish community, particularly when it is proposed to further increase fishing mortality rates.” In later paragraphs, th e FEIS argues that:

 Mortality related to cooling wa ter withdrawals is not compar able to fishing mortality.

 Mortality related to cooling water withdrawals is comparab le to habitat degradation.

### 14  Mortality related to cooling water withdraw als decreases the forage base for Hudson River fish species and short- circuits the trophic pyramid.

 Mortality of small organisms related to cool ing water withdrawals could contribute to the development of harmful algal blooms.

 Mortality related to cooling water withdr awals directly reduc es the quantity of organisms within the water column over significant stretches of the river.

All of these arguments conflict with well-documented scientific facts concerning the Hudson River estuary and coastal/mari ne ecosystems in gene ral. The following subsections specifically address each of the arguments raised in the FEIS.



### D.2.1 Comparison of cooling water withdrawals to fishing mortality

Mortality due to commercial and recrea tional fishing has a greater impact on Hudson River fish populations than cooling wa ter withdrawals from the Stations. The FEIS agrees, but mischaracterizes the actua l effects of fishing mortality. The FEIS correctly notes that “aquatic re source mortality from power plants is not comparable to the ‘selective cropping’ that occu rs in a regulated fishing or hunting season”(FEIS, p. 53). The FEIS goes on, however, to in correctly portray the effects of fishing and particularly overfishing on fish populations: “only selected species are ha rvested, and the forage base remains intact or is improved because fewer individuals higher on the food chain are available to consume lower food chain organi sms. Furthermore, fishing and hunting seasons are generally established during that part of the annual cycle which provides both

maximum benefit to the users and ensures the sustainability of th e population. Mortality at these Hudson River power plants is not limi ted to a specific, benign season; it occurs throughout the annual cycle, whenever the pl ants operate their ‘once-through pumps’.” (p. 53).

The FEIS’s benign view of harvesting stands in stark contrast to the conclusions concerning ecological effects of fishing e xpressed in the report of the Pew Oceans Commission (2003), prepared by a blue-ribbon panel that included then-New York Governor George Pataki. Pages 38-41 of this report summarize both the catastrophic effects of overfishing on marine ecosystems, and the management failures that lead to overfishing. Worldwide, populati ons of large-bodied top carni vore species such as tuna, swordfish, salmon, and many sharks, have been drastically depleted by harvesting. As the populations of these species decline, fisher men shift their attenti on to smaller species, eventually depleting these species as well. The consequences of this process, termed “fishing down the food web,” are describe d in the following way by the Pew Oceans

Commission:

“The consequences of this disruption can be severe. Diversified food webs with sufficient population sizes at all trophic levels al low predators to switch among prey as the abundance and mix of species in a system naturally fluctuates. Overfishing of top-

### 15 trophic species and subsequently mid- and low-trophic species removes this natural benefit of biodiversity by gradually disrupti ng and truncating trophic relationships. This leads to unpredictable changes, such as increased disease outbreaks and the proliferation of previously suppressed pe sts and weedy species.”

This conclusion is supported by a report prepared for the Pew Oceans Commission by Dayton et al. (2002), which provides a comprehensive review of the ecological effects of fishing. Other adve rse effects of fishing discussed by the Commission and by Dayton et al . (2002) include the physical effects of gears such as bottom trawls and dredges, and the bycatch of unwanted fish captured by fishermen who are targeting other species.

The Pew Commission’s conclu sions concerning the ofte n catastrophic effects of poor fishery management practices are also supported by other published literature. Myers and Worm (2003) recently found that harvesting has reduced the worldwide biomass of large, predatory fi sh by 90% from the levels that were present prior to the introduction of modern fishing technologies. These predators play an important role both in controlling the abundance of other specie s and in controlling the pathways through which energy and biomass move through ma rine food webs (Steele and Schumacher 2000, Jackson et al. 2001, Daskalov 2002). Re ducing the abundance of large predators leads to increased abundance of forage fish and pelagic inverteb rates (e.g., jellyfish), decreased abundance of zooplankton, and incr eased abundance of phytoplankton and suspended organic matter (Ste ele and Schumacher 2000).

The Pew Commission also discussed the fi shery characteristics and management failures that have repeatedly led to overfishing, in spite of the best intentions of management agencies. Key fishery character istics that encourage overfishing include excess capacity of fishing fleets and the avai lability of new technologies that greatly increases the ability of fishermen to loca te schools of fish and exploit previously inaccessible areas. Key management failures include the single-species approach to harvest regulation, an emphasis on short-te rm commodity production, and the influence of commercial fishing interests on ma nagement decisions. The Commission recommended a variety of changes in fish ery management policie s to address these

concerns.

With respect to the problems discusse d in the Pew Commission report and other authoritative sources, cooling water withdrawal s are far less destructive than fishing. Cooling water withdrawals entrain and im pinge organisms only from the immediate vicinity of intake structures, and only wh en pumps are operating. They do not target specific species such as large predators, do not actively se ek out schools of fish, and do not physically alter the habita t from which cooling water is withdrawn. Entergy’s AEI Report documents a comparison between fi shing mortality and mortality due to

entrainment at Units 2 and 3 for two harves ted RIS species: striped bass and American shad. For both species, entrainment mortality is negligibly small compared to fishing mortality.

### 16 In short, the FEIS is correct in stati ng that cooling water withdrawals are not comparable to harvesting, but incorrect in characterizing its effects as somehow benign.



### D.2.2 Comparison of cooling water withdrawals to habitat degradation

The FEIS (p. 35) states that “Rathe r than ‘selective cropping,’ the impacts associated with power plants are more comp arable to habitat degradation; the entire natural community is impacted.” This statement mischaracterizes the true nature of habitat degradation as compared to cooling water withdrawals.

Habitat degradation resulting from the rapi d urbanization of coastal environments was identified the Pew Commission (2003) as a primary threat to ecologically and economically important species as well as to rare and unique habitats (p. 51). Urbanization directly destroys habitats such as forests and wetlands, reducing the value of these habitats to support fish and wildlife, control runoff, and pr ovide natural pollution

control. Increased runoff from the transfor mation of vegetated su rfaces to impervious surfaces such as roads and parking lots causes increased flooding and pollutant loading. Polluted runoff was identified by the Pew Commission (p. 56) as “probably the most harmful impact of development on marine and freshwater ecosystems.” As shown in the figure on p. 50 of the Pew Commi ssion report, in 1930 the development “footprint” of the New York metropolitan area covered onl y a small region of the Hudson Valley immediately surrounding New York City. By 1990, the entire valley between the Battery and the Hudson Highlands had been affected by urban and suburban development.

In addition to degradation related to urban sprawl, the Hudson River has been affected by damming, dredging, an d filling ever since the arrival of European settlers. As discussed by Miller et al . (2006), the northern third of the Hudson River estuary has been substantially modified since the late 18 th 

### century by dredge and fill activities associated with navigational channel maintena nce. Wetlands and natural shoreline that formerly fringed the Hudson have also be en dredged and filled to support railroad construction. According to Squires (1992), 54% of the eastern shore of the Hudson and 63% of the western shore are lined by railro ads immediately adjacen t to the river and largely constructed from fill. These activities have caused significant losses of intertidal and shallow-water areas that serve as importa nt nursery habitats for fish. In addition, approximately half of the tributaries to th e estuary have dams or other anthropogenic obstructions on or near their mouths, rest ricting the spawning habitat available to migratory species such as river he rring (Schmidt and Cooper 1996).

Although dams may be removed to facilita te fish migration, the other changes discussed above are permanent and irreversible . As noted by Daniels et al. (2005), they have affected the composition of the Hudson River fish community in ways that are difficult to quantify because significant physical modifica tions of the Hudson predate reliable biological studi es of the river.

### 17 Cooling water withdrawals, in contrast, a ffect only the organisms present in the

water column within the withdrawal zone of the intake structure, and only when pumps are operating. Cooling water w ithdrawals do not permanently alter the river channel, shoreline, or any other physic al characteristic of the Hudson River. They do not affect rates of runoff or introduce pollutants into th e river. Clearly, coo ling water withdrawals cannot legitimately be compared to habitat degradation of the kinds highlighted by the

Pew Oceans Commission and the other sources cited above.



### D.2.3 Impacts of cooling water wi thdrawals on ecological function

The FEIS incorrectly concludes that there are a variety of purported adverse effects of cooling water withdrawals on the ecological functions th at would have been provided by entrained or impinged organisms. As discussed in greater detail below, the FEIS improperly makes this conclusion base d on the outdated concept of a “trophic pyramid,” or the idea that organisms with in aquatic ecosystems may be grouped into relatively discrete “trophic levels.” The FEIS states (p. 53) that the abundance of plankton (including microscopic pl ants and animals, as well as fish eggs and larvae) is reduced, thereby reducing the avai lability of food for organism s that are not entrained or impinged. In addition to depriving larger organisms of food, the loss of these small organisms may, according to the FEIS (p. 54), contribute to the development of harmful algal blooms (see section 3.4). The FEIS (p. 54 ) also claims that losses of small fish “short-circuits” the trophic pyramid and compromises th e health of the natural community because the entrained or impinged fish are no longer able to perform their normal ecological functions. For example, rather than serving as food for a valuable fish such as striped bass or a bi rd, a bay anchovy entrained by a power plant cooling system and killed would be useful only as food for lower trophic level organisms. It would no longer be able to feed, concentrate nutrients into its tissues, or distribute its “manure” (i.e., waste products) for use by other organi sms. The loss of millions of anchovies would, presumably, result in a significant reduction in the abundance food available predators, and also a decrea se in the amount of plankton concentrated, concentrated, processed, and redistributed as wast e products throughout the estuary.

These claims made in the FEIS conflict wi th scientific facts concerning the nature of estuarine food webs, the ecology of specifi c fish species inhabiting the Hudson River, and the key aspects of cooling system operations at the Stations. The idea that organisms within aquatic ecosystems may be grouped into relatively discrete “trophic levels” as primary producers (plants that fix carbon using sunlight as an energy source), primary consumers (animals that eat plants), sec ondary consumers (animals that eat primary consumers) and so on at higher and higher levels was first formalized by Lindeman (1942). According to this theory, organisms at each level feed primarily on organisms at

the next lower level. Animals that die before they are consumed are consumed by scavengers that feed primarily on dead organisms, or are degraded by decomposer organisms, primarily bacteria and fungi. D ecomposition releases dissolved nutrients that can be used again by the primary produ cers at the bottom of the pyramid.

### 18 Figure 1a depicts the cyclical flow of biomass in the Hudson River ecosystem, consistent with this view. Microscopic pl ants called “phytoplankton” withdraw nutrients from the water to support their growth. The phytoplankton are consumed by microscopic invertebrates called “zooplankton” that are, in turn, consumed by small fish such as bay anchovy. These smaller fish are then consum ed by predatory fish like striped bass. Plants and animals that die from causes other than consumption by larger animals fall to the bottom of the estuary, where they may be consumed by scavengers (e.g., crabs, sand shrimp, and bottom-feeding fish). Ultimatel y, their tissues are broken down by bacteria and fungi. The nutrients released by d ecomposition are then available for uptake by phytoplankton. Figure 1b depicts the influe nce of entrainment on the Hudson River ecosystem, according to the FEIS (p. 54). Entrainment “short-circuits” the trophic pyramid by killing small fish, which then return directly to the scavenger/decomposer pool rather than being consumed by predator s. Predator consumption (and subsequent growth) is reduced in dir ect proportion to the losses caused by entrainment.

This characterization of ecosystems in terms of a “trophic pyramid” is now recognized as a gross oversimplification of reality. In a comprehensive review of terrestrial and aquatic food webs, Polis and St rong (1996) stated (p. 815) that “the notion that species clearly aggregat e into discrete, homogeneous trophic levels is fiction.” Rather than being organized in to discrete levels, with pl ants at the base and large predators at the top, in real food webs mo st animals consume organisms from multiple trophic levels. Moreover, the food consumed by typical predator speci es is often derived from a combination of plant-based and d ecomposer-based production, and the species consumed change depending on developm ental stage and spat ial location. The characterization of ecosystem structure advocated by Polis and Strong (1996) is supported by a wide variety of theoretica l and empirical food web studies such as Murdoch (1966), Peters (1977) , Darnell (1961), Hanski (1987), Baird and Ulanowicz 1989, Hall and Rafielli (1991), Polis and Holt (1992), Vander Zanden and Vadeboncoeur 2002, and Thompson et al. 2007.

The Hudson River ecosystem is consistent with the view of food webs expressed by Polis and Strong (1996). Striped bass larvae, for example, feed primarily on small invertebrates called “copepods,” (Limburg et al. 1998), which are an important component of the zooplankton. Copepods, in turn, feed on both phytoplankton and on decomposer microorganisms growing on the surfaces of organic particles suspended in the water column. Juvenile striped ba ss feed on copepods, but also on larger invertebrates such as gammarids and chir onomids (Gardinier and Hoff, 1982). These invertebrates feed on plants and decomposi ng organic matter, and in addition gammarids are active predators on zooplankton and even fi sh eggs and larvae (Poje et al. 1988).

Striped bass begin feeding on fish when they reach a length of 76-150 mm, but still feed primarily on inverteb rates until they reach a length of about 200 mm (Gardinier and Hoff, 1982). Other Hudson River fish sp ecies similarly feed on a wide variety of organisms at different stages of their lif e cycles. White perch feed primarily on invertebrates such as gammarids, but also on fish eggs and larvae and even plants (Bath and O’Connor 1985).1Figure 1. Flows of biomass in an estuary such as the HudsonRiver, according to the classical “trophic pyramid” concept discussed inthe FEIS. Plants are the ultimate source offood for all higher organisms. Small plants (phytoplankton) suspended in the water areconsumed by small invertebrates (zooplankton), which are then consumed by small fish such as bay anchovy. Larger fish such asstriped bass consume bay anchovies. All organisms that die without being consumedby higher organisms are decomposed by “lower”organisms such as scavengers (e.g., crabs),bacteria, and fungi. Thenutrients released are taken up by plants, to produce newbiomassto support the trophic pyramid. Entrainment “short-circuits” the pyramid, returning entrained organisms directly to the decomposerpool and reducing the food available to predators.Small FishPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrientsSmall FishPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrients(a)no I&EPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrientsSurvivorsLossesReduced predatorabundance caused byreduction in prey abundanceLosses“short-circuited”to decomposerpool(b)with I&E

### 1 Juvenile bluefish that enter the Hudson River prey primarily on smaller fish, but also consume blue crabs and sand shrimp (J uanes et al. 1995; Buckel and Conover 1997). The fish consumed by bluefish include other piscivore species (striped bass), planktivorous species (bay anchovy, American shad, and river herring), and benthic invertebrate-feeding species (whi te perch and Atlantic tomcod).

Figure 2a depicts the flow of biomass accord ing to the more realistic view of the Hudson River ecosystem summarized above. In addition to the biomass flow pathways shown in Figure 1a, additional flows show the consumption of decomposers by zooplankton, and the direct consumption of zooplankton by predator y fish. Figure 2b depicts the influence of entrainment on the Hudson River ecosystem, consistent with the more complex food web of Figure 2a. Rather than being transfer red directly to the scavenger/decomposer pool, entrained orga nisms are available for consumption by predators. Fish and invertebrate scavengers that consume entrained organisms are also susceptible to predation. Consumption by thes e organisms retains much of the entrained biomass within the food web, greatly reducing th e quantity that is lost to decomposers. The decomposing organisms themselves may be consumed by invertebrates, even further reducing the loss of biomass to the food web.

Because of the complexity of real food webs, the poten tial fate of the entrained anchovy discussed in the FEIS (p. 54) is actua lly far more varied, and the impacts much lower, than is implied in the FEIS. Since many entrained fish, including fragile species such as bay anchovy, are initially alive when returned to the river, the anchovy in question could still be consumed by a predat or, possibly even the same striped bass that

would have consumed it had it not been entr ained. If not immediately consumed by a predator, the anchovy could sink toward the bottom and be consumed by a white perch, Atlantic tomcod, or other benthi c-feeding fish species, or by a crab or sand shrimp. Any of these species would then be capable of performing the an chovy’s function of concentrating and distributing nu trients, and could in turn be consumed by a striped bass or other predator. If, instead of being consumed, the anchovy were decomposed by bacteria and fungi, these micr oorganisms would themselves be susceptible to grazing by

invertebrates such as cladoc era, copepods, or gammarids, which would in turn be available for consumption by st riped bass, white perch, bay an chovies, or other fish. Due to these complex biomass flow pathways, the effects, if any, of the entrainment of bay anchovy and other small fish at the Stati ons would be diffused throughout the entire ecosystem and would be much smaller than implied in the FEIS.



### D.2.4 Influence of cooling water withdrawals on the risk of algal

blooms

The FEIS’s concern that algal blooms ma y be caused by cooli ng water withdrawals is not supported by literature. On pp. 53- 54, the FEIS states that losses of small planktonic organisms due to en trainment “may be a factor that leads to harmful algal blooms.” A paper by Capriulo et al. (2002) is cited in s upport of this statement.1Figure 2. Flows of biomass in anestuary according to current ecological science.Most animals are “omnivores” that consume manytypes of organisms at different points intheir life cycles. In addition to feeding on fish, striped bass also feed on zooplankton and onscavengers such as crabs and shrimp. Evenbacteria and fungi are consumed by zooplankton and other invertebrates. Entrainedorganisms are available for consumption bothby predators and by other organisms that are in turn consumed by predators. Retentionof biomass within the food web minimizes any reduction in food available to predators.Small FishPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrients(a)no I&ESmall FishPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrients(a)no I&EPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrientsSurvivorsLossesPrey reduction offset bydirect consumption ofentrained fish and increasedabundance of invertebrateand scavenger preyLossesConsumed atMultiple trophiclevels(b)with I&EPredatorsZooplanktonPhytoplanktonScavengers/DecomposersDissolvedNutrientsSurvivorsLossesPrey reduction offset bydirect consumption ofentrained fish and increasedabundance of invertebrateand scavenger preyLossesConsumed atMultiple trophiclevels(b)with I&E

### 2 This paper does not, in fact, discuss either entrainment or algal blooms. Instead, it

focuses on the influence of enhanced nut rient inputs on western Long Island Sound, and in particular on alternative expl anations for the fact that incr eased nutrient inputs have led to increased production of phytoplankton (free- floating algae) and z ooplankton, but not to increased production of fish. The authors conclude that the excess production of planktonic algae and zoopla nkton is being diverted to microbial decomposition and production of ctenophores (gelatinous, predator y organisms related to jellyfish) rather than to production of fish. This paper clearly does not support the statement made in the

FEIS.

For the effect hypothesized in the FEIS to occur, it would have to be the case that the productivity of planktonic algae in the Hudson River was limited at least in part by the grazing activities of zooplankton and fish la rvae entrained at the Stations. Reduced abundance of these grazers could then, according to this hypothesis, result in increased production of algae, including the kinds of algae responsible for harmful blooms. However, it has long been known that phyt oplankton production in the lower Hudson River estuary, where the Stations are located, is limited by light penetration and by the flushing of suspended phytoplankton out of the river (Moran and Limburg 1986, Gladden et al. 1988). Miller and St . John (2006) confirmed through a modeling study that primary production in the lower Hudson is limited by li ght penetration and by flushing. Since production is limited by these abiotic factors, removal of grazers by entrainment should not lead to increased pro duction of planktonic algae.



### D.2.5 Influence of entrainment on the quantity of organisms present
within the water column

The FEIS states broad, unsupported conclusi ons about the types of organisms that are entrained at the Stations. According to p. 54 of the FEIS, cooling water withdrawals by Indian Point and other power plants reduc e the quantity of orga nisms present within the water column, a process termed “draw- down.” This statement is supported by citations to a report from H ydroQual (1999). Figures take n from that report show the probabilities that particles (e.g., fish eggs or larvae) released into the river at various locations will be entrained at a power plant within 7 days following release. Figure 3-7, on p. 55 of the FEIS, shows that under low-fl ow conditions Indian Point can entrain particles from locations between RM 20 a nd RM 70. Figure 3-8, on p. 56 of the FEIS, shows that under high-flow conditions partic les originating between RM 25 and RM 100 can be entrained. The FEIS concludes from these figures that drawdown due to cooling water withdrawals “dramatically reduces food availability within the ecosystem, and, thus, survivability of multiple species over significant stretches of the Hudson River.”

The FEIS does not explicitly state the kinds of organisms to which this statement

refers. If it is intended to a pply to all organisms, then it c onflicts with the conclusions of the Nuclear Regulatory Commission (“N RC”) staff in the Draft Supplemental Environmental Impact Statement (“DSEI S”) for IP2 and IP3 (USNRC 2009). The DSEIS states on p. 4-4 that entrainment of phytoplankton and zooplankton “has never

### 3 been found to be a problem at operating nuclear power plants and is not expected to be a problem during the license renewal term.”

As applied only to early life stages of fi sh, the conclusion stated in the FEIS is also invalid, for two reasons. First, as is clearly shown in the two figures cited, the probability that any particular particle will be entrained at Indian Point never exceeds 15%, even at the locations in the immediate vicinity of the plant, and only during low flow conditions. Under high flow conditions the maximum probability of entrainment is less than 10% in the vicinity of the plant. Second, as discussed in Section D.2.3, entrainment does not remove any biomass from th e river. Since all biomass is returned to the river, there is no reduc tion in the quantity of orga nisms present. Even those organisms killed or injured by en trainment still are av ailable as food for other organisms.

If the “drawdown” hypothesized in the FEIS actually occurred, there should be an

observable reduction in the abunda nce of entrainable life stag es of fish in the river regions from which cooling water is withdrawn, as compared to adjacent regions. In fact, the available data for the Hudson River prov ide no evidence for any such reductions. Figure V-115 of the DEIS plots the spatial pa tterns in abundance, taxonomic richness, and diversity of larval fish in the Hudson River over the years 1974- 1997. None of these metrics shows any observable decline in re gion 4, where the Stations are located, compared to adjacent regions 3 and 5.



### D.2.6 Conclusion

The discussion of ecosystem-level effects on pp. 51-54 of the FEIS is not based on any analyses of the biological data availa ble for the Hudson River, or on a realistic description of how cooling wa ter withdrawals at a power plant might interact with the populations and communities pres ent in the Hudson River. In stead, it is based on invalid comparisons and simplistic hypotheses, togeth er with a misleading characterization of power plant operations.

Power plant cooling systems do not actively seek out specific fish species or large concentrations of fish, and do not hunt fish until populations are depl eted. Cooling water withdrawals at the Stations do not physically alter fish habitat and do not reduce the ability of the habitat to support fish. Water withdrawal s and consequent entrainment of fish cease whenever pumps are shut down, and do not resume until pumps are restarted. Even when pumps are operating and water is withdrawn, all of the water and entrained organisms are returned to the river, with no eviden ce of any “drawdown” of organisms in the vicinity of Indian Point.

The conclusions reached in the FEIS ar e conjectural and inconsistent with the

available scientific facts. There is no evid ence that any of the effects discussed in the FEIS have actually occurred in the Hudson Ri ver, and much evidence that any such effects, even if they do occur, are immeasurably small.

### 4 

### D.3 References

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ecosystem. Ecological Monographs 59 :329-364.

Bath, D. W., and J. M. O’Connor. 1985. Food pr eferences of white perch in the Hudson River estuary. New York Fish and Game Journal 32 :63-70.

Buckel , J.A., and D. O. Conover. 1997. Move ments, feeding period, and daily ration of piscivorous young-of-the-year bluefish Pomatomus saltatrix in the Hudson River estuary. Fishery Bulletin 95 :665-679.

Capriulo, G. M., G. Smith, R. Troy, G. H. Wi kfors, J. Pellet, and C. Yarish. 2002. The planktonic food web structure of a temperat e zone estuary, and its alteration due to eutrophication. Hydrobiologia 475/476 :263-333.

Daniels, R. A., K. E. Limburg, R. E. Schmidt, D. L. Strayer, and R. C. Chambers. 2005. Changes in fish assemblages of the tidal H udson River, New York. Transactions of the American Fisheries Society Symposium 45 :471-503.

Darnell, R. M. 1961. Trophic spectrum of an estuarine community, based on studies of Lake Ponchartrain, Louisiana. Ecology 42 :553-568.

Daskalov, G. M. 2002. Overfishing drives a trophic cascade in the Black Sea. Marine Ecology Progress Series 225 :53-63.

Dayton, P. K., S. Thrush, and F. C. Cole man. 2002. Ecological effects of fishing in marine ecosystems of the United States. Prepared for the Pew Oceans Commission.

Gardinier, M. and T.B. Hoff. 1982. Diet of striped bass in the Hudson River estuary.

New York Fish and Game Journal

. 29 :152-165.

Gladden, J. B., F. R. Cantelmo, J. M. Cr oom, and R. Shapot. 1988. Evaluation of the Hudson River ecosystem in relation to the dynamics of fish populations. American Fisheries Society Monograph 4 :37-52.

Hall, S. J., and D. Rafielli 1991. Food-web patterns: Lessons from a species-rich web. Journal of Animal Ecology 60 :823-841.

Hanski, I. 1987. Plankton th at don’t obey the rules. Trends in Ecology and Evolution

2 :350-351.

Henderson, P. A., and R. M. Seaby. 2000. Technical comments on the Draft Environmental Impact Statement for the Stat e Pollutant Discharge Elimination System

Permit Renewal for Bowline Point 1&2 I ndian Point 2&3 and Roseton 1&2 steam generating stations. Pi sces Conservation, Ltd.

### 5 HydroQual, Inc. 1999. Modeli ng the entrainment of passive particlesinto Hudson River power plants. Prepared for Orange and Rockland Utilities, February, 1999.

Jackson, J.B.C., M. X. Kirby, W. H. Berger, K. A. Bjorndal, L. W. Botsford, B. J. Bourque, R. H. Bradbury, R. Cooke, J. Erlandson, J. A. Estes, T. P. Hughes, S. Kidwell, C. B. Lange, H. S. Lenihan, J. M. Pandolfi, C. H. Peterson, R. S. Steneck, M. J. Tegner,

and R. R. Warner. 2001. Histor ical overfishing and the re cent collapse of coastal

ecosytems. Science 293 :629-638.

Juanes, F., R. E. Marks, K. A. McKow n, and D. O. Conover. 1993. Predation by age-0 bluefish on age-0 anadromous fish es in the Hudson River estuary. Transactions of the American Fisheries Society 122 :348-356.

Limburg, K. E., M. L. Pace, and K. K. Arend. 1998. Growth, mortality, and recruitment

of larval Morone spp. in relation to food availabi lity and temperature in the Hudson

River. Fishery Bulletin 97 :80-91.

Lindeman, R. L. 1942. The trophic- dynamic aspect of ecology. Ecology 23 :399-417.

Miller, R. L., and J. P. St. John. 2006. Mode ling primary production in the lower Hudson River estuary. pp. 140-156 in Levinton, J. S., and J. R. Waldman (eds.) The Hudson River Estuary . Cambridge University Press, New York.

Miller, D., J. Ladd, and W. C. Nieder. 2006. Channel morphology in the Hudson River estuary: Historical changes and opportunities for restora tion. pp. 29-38 in Waldman, J., K. Limburg, and D. Strayer (eds.) Hudson River Fishes and their Environment. American Fisheries Society Symposium 51

.

Moran, M. A., and K. E. Limburg. 1986. The Hudson River ecosystem. Pp. 6-49 in Limburg, K. E., M. A. Moran, and W. H. McDowell (eds.) The Hudson River Ecosystem. Springer-Verlag, New York.

Murdoch, W. W. 1966. “Community structure, population control, and competition” – a critique. The American Naturalist 100 :219-226.

Myers, R. A., and B. Worm. 2003. Rapid wo rldwide depletion of predatory fish

communities. Nature 423 :280-283.

Peters, R. H. 1977. The unpredictable problem of tropho-dynamics. Environmental Biology of Fishes 2 :97-101.

Pew Oceans Commission. 2003. America’s living o ceans: Charting a course for change.

Poje, G. V., S. A. Riordan, and J. M. O’Connor. 1988. Food habits of the amphipod Gammarus tigrinus in the Hudson River and the eff ects of diet upon its growth and

### 6 reproduction. Pp. 255-270 in C. L. Smith (ed.) Fisheries Research in the Hudson River. State University of New York Press, Albany, NY.

Polis, G. A., and R. D. Holt. 1992. Intragu ild predation: The dynamics of complex trophic interactions. Trends in Ecology and Evolution 7 :151-154.

Polis, G. A., and D. R. Strong. 1996. Food web complexity and community dynamics.

The American Naturalist 147 :813-846.

Schmidt, R. E., and S. Cooper. 1996. A cat alog of barriers to upstream movement of migratory fishes in Hudson River tribut aries. Final report to the Hudson River Foundation, New York, NY.

Squires, D. F. 1992. Quantifying anthropogeni c shoreline modification of the Hudson River estuary from European contact to modern time. Coastal Management 20 :343-354.

Steele, J. H., and M. Schumacher. 20 00. Ecosystem structure before fishing. Fisheries

Research 44 :201-205.

Thompson, R. M., M. Hemberg, B. M. Starzoms ki, and J. B. Shurin. 2007. Trophic levels and trophic tangles: The prevalence of omnivory in real food webs. Ecology 88 :612-617.

U.S. Nuclear Regulatory Co mmission (USNRC). 2009. Generic environmental impact statement for license renewal of nuclear pl ants. Supplement 38. Regarding Indian Point Nuclear Generating Unit Nos. 2 and 3. Draft report for comment.

Vander Zanden, M. J., and Y. Vadeboncoeur. 2002. Fishes as integrators of pelagic and

benthic food webs in lakes. Ecology 83 :2152-2161.

### 7 

## Attachment D-1

Supplemental Analyses to Address Concerns Regarding

Validity of CMR Estimates as Meas ures of Risk to Entrainment,

Emigration of YOY Striped Bass from the Hudson River, and Dynamics of the Bay Anchovy YOY Population in the Hudson River

Prepared by

AKRF, Inc. Hanover, Maryland

12/29/09

### 8 CMR Estimates

In the AEI Report, estimates of CMRs from the DEIS are used as measures of the

relative risk of entrainment.

Concerns Raised in the ESSA Review

ESSA’s review of the DEIS included a cr itique of the CMR estimates presented in the DEIS. They concluded that the CMR es timates, although appropriate measures in principal, were unreliable measures of entrainm ent effects due to details of the method of estimation (ESSA 2000, page iv):

“The shift to accounting for the effects of outages or partial flow

reductions based on units which reflect the indicator of concern (CMR) is

a useful and laudable method. Our revi ew however suggests concern with several aspects of the propos al and supporting analyses:

 Our review suggests concern with the estimation of entrainment

which serves as the fundamental basis for the CMR data on which the FPP system is based. Specifi cally, there is considerable uncertainty in forecast CMRs due to applications of W parameter values from a period with diffe rent species distributions and possibly different intake rates. Un til this concern can be clearly resolved, the entrainment estimates for the 1991 to 1997 data series (on which the FPP system is based) should be viewed with skepticism.”

For each entrainable life stage, the W-ratio (W parameter) represents the ratio of density in the vicinity to the intake to the overall density in the re gion adjacent to a power plant. For the DEIS, estimates of W-ratios were calculated using the available entrainment data (1981-1987). ESSA speculated that a shift in habi tat quality (from the 1980’s to the 1990’s) had caused a shift in near shore distribution patterns of entrainable life stages, and therefore, th ey concluded the estimated W -ratios could not be used to estimate CMRs for the 1990’s. ESSA provided no evidence that a shift in nearshore distribution patterns had occurred. Neverthele ss, they based a major conclusion of their review on that speculation, claiming observed changes in CMR estimates were due to biases introduced by shifts in nearshor e distribution patterns (ESSA 2000, page 18):

“As discussed in the beginning of this section, the entrainment estimates published in the DEIS suggest a curi ous decline in the estimation of entrainment during the 1990s. If, for example, the habitat change in the

Hudson River caused a shift to a more inshore distribution of larvae, the effect would be relatively lower densiti es in the areas sampled by the LRS.

### 9 Since inshore densities are predicted from the offshore densities using 1980s-based regression equations, an ove rall reduction in predicted larval density would result. When combin ed with a constant value of W (also determined during the 1980s) the eff ect could be to predict reduced

entrainment at a time when it wa s actually increasing. This raises fundamental concerns regarding estimat es of entrainment during the 1990s and the prediction of future entrainm ent with the current model.” (ESSA 2000, page 18)

ESSA did not conduct an analysis of field data to corroborate their conclusion that a shift in nearshore distribution patterns was the cause for the lower CMR estimates during the 1990’s, nor did they consider alternative hy potheses (e.g., interannual variability in freshwater flow rates that affect longitudinal distribution patterns of larvae in the River) to explain the lo wer CMR estimates in the 1990’s.

In addition to their primary concern re garding W-ratios, ESSA identified three potential sources of uncertainty in input parameter estimates required for the CMR

calculations:

1) Relative probability of capture (“RPC”) 2) Unsampled areas 3) Through-plant mortality

Each of these identified potential sources of uncertainty was due to limitations in available data. For the RPC estimates, spec ies-specific data were not available for all RIS. Similarly, the available data on through- plant mortality did not support species- and plant-specific estimates for all RIS and all plants addressed in the DEIS. Regarding unsampled areas, ESSA stated, “We recognize th e difficulty in obtaini ng a complete field data set, and the methods described in the DEIS to provide a complete data set for analysis are not unreasonable.” Nevertheless, they still list ed unsampled areas as one of

the “more obvious sources of error.”

For each of these potential sources of uncertainty, ESSA provided a narrative

discussion of the basis for their concern. Ho wever, they did not provide any assessment of the likely magnitude of uncertainty or bi as that might be introduced by each potential source, nor of the magnitude of uncertainty or bias that might be introduced collectively by all potential sources.

New Analyses Confirming Validity of CMR Estimates for Use in AEI Report

Nearshore-Offshore Spatial Distribution Patterns

An empirical assessment of nearshore-o ffshore spatial distribution patterns in the vicinity of the Station was conducted to ad dress ESSA’s speculati on that the apparent decline in CMR estimates beginning in 1990 was due to a shift in the nearshore-offshore

### 10 spatial distribution pattern of larvae, which cau sed CMR estimates to be biased low. If there had been a shift in the spatial distri bution of entrainable lif e stages towards the nearshore areas after the 1980’s, then the a bundance in the nearshore areas should have

increased relative to the abundance in the offshore areas. For each year from the 1980’s and 1990’s post yolk-sac larvae (“PYSL”) abundance in each sampling stratum (i.e., channel, bottom, and shoal) of the Indian Point Region was estim ated based on stratumspecific PYSL density estimates from th e Longitudinal River Survey (“LRS”) and

estimates of the volume of water in each stratum (ASAAC, 2007). The channel and bottom strata are those offshore portions of th e river where water depths are greater than

20 feet. The shoal stratum consists of th e nearshore portion of the river where water depths are between 10 feet and 20 feet. The portion of the river wh ere water depths are

less than 10 feet is referred to as the s horezone, and is not sampled by the LRS. The

shorezone contains less than 3% of the rive r volume in the Indian Point Region, and the

shoal stratum contains less th an 6% of the river volume in the Indian Point Region (ASAAC, 2007, table 2-11).

Abundance in the shoal stratum was used as an indicator of relative abundance in nearshore areas (because sampling was not conducted in the shorezone), and abundance

in the channel and bottom strata were used as indicators of rela tive abundance in the offshore areas. For each species and year, th e ratio of abundance in the shoal stratum to

the combined abundance in the channel and bottom strata was used as a measure of nearshore-offshore distribution pattern:

y s bottom bottom y s channel channel y s shoal shoal

y s offshore y s nearshore

y s 

### D v D v D v

A A

r

, , , , , ,

, , , ,

, 

### ˆ ˆ

ˆ

  

where

y s 

### r

, 

### ˆ is the estimated nearshore-offshore abundance ratio,

v shoal 

### is the volume of the shoal stratum in the Indian Point Region

v channel 

### is the volume of the channel st ratum in the Indian Point Region

v bottom 

### is the volume of the bottom stratum in the Indian Point Region

y s shoal 

### D

, , 

### is the average PYSL density in the shoal stratum of the Indian Point Region for species, s , in year, y ,

y s channel 

### D

, , 

### is the average PYSL density in th e channel stratum of the Indian Point Region for species, s , in year, y ,

y s bottom 

### D

, , 

### is the average PYSL density in the bottom stratum of the Indian Point Region for species, s , in year, y ,

Estimates of average PYSL density were based on ichthyoplankton sa mpling in weeks 18 through 26 (the weeks consisten tly sampled in all years).

### 11 The average ratio for the earlier peri od of years (1981-1987), and approximate 95% confidence limits for the average ratio were computed as:



# 

 

###  1987

1981 , 1

, 

### ˆ 7 1

ˆ

y y s period s 

### r r



#    

1

, 1

, 

### ˆ 96

. 1 ˆ period s period s 

### r se r Limits Confidence   



### where 

#    

1

, 1

, 

### ˆ var ˆ period s period s 

### r r se 



### and 

#     

#         

 

###   

 

  

 

 

 

 

 

  1987

1981 2

, , , , 2

, , , , 2

, 1

, 

### ˆ ˆ var

ˆ ˆ var

ˆ 49

1

ˆ var

y y s offshore y s offshore

y s nearshore y s nearshore

y s period s 

### A A

A A

r r 



### Parallel equations were used for the later period of years (1988-1997).

The estimated average ratio decreased from the earlier period of years to the later period of years for half of the species of interest (Ameri can shad, bay anchovy and river herring), and increased for half of the species of interest (Atlantic tomcod, striped bass and white perch). However, no changes in th e estimated average ratio were statistically significant (Table D-1-1) for any species (b ased on overlapping 95% confidence limits). These results support the conclusion that ther e was no systematic shift in the nearshoreoffshore spatial distribution of entrai nable larvae, as speculated by ESSA.

CMR as Metric of Risk to Entrainment



### To address the overall validity of the CM R estimates as measures of risk to entrainment, an assessment was conducted to determine whether the CMR estimates were well correlated with a simple , empirical predictor of entr ainment risk based on larval

location in the river and on Indian Point coo ling water withdrawal rates. The empirical predictor did not include the th ree inputs to the CMR estimates that ESSA criticized, i.e., RPC, unsampled areas adjustments, and through-plant mortality.

For each species, the empirical assess ment examined the relationship between:

1) Estimates of CMR 2) The proportion of larv ae in the river that occurred in Regions 3, 4 and 5 3) Cooling water flow rates at Indian Point.

The relationship was examined separately for each species, s , with the following logistic regression model:

### 12 

#  

y s y s y s 

### F P CMR logit

, 2

, 1 0

, 

###      



### or

 

y s y s F P y s 

### e CMR

, 2

, 1 0 

### 1 1

,    



 

###  



### where

CMR s,y 

### is the CMR estimate for species, s 

### , in year, y 

### ,

P s,y 

### is an estimate of the proportion of larvae in the river during the period of entrainment vulnerabi lity that were in Regions 3,4 and 5 during year, y 

### , and

F

s,y 

### is the average monthly cooling wa ter flow rate at Indian Point during the period of entrainmen t vulnerability during year,

y



### .

The logit transformation wa s used for the regression because it kept the CMR estimates bounded by 0 and 1, while allowing the linear combination of explanatory variables to be unbounded. The variable, P s,y 

### was calculated as a weighted average of the proportion in Regions 3, 4 and 5, where the weights represented the relative amount of water withdrawn by the Stations from each of the three regions (from Table X-15, Appendix VI-I-B, DEIS). The Stations’ flow data from May and June were used to represent the period of entrainm ent vulnerability for American shad, river herring, striped bass and white perch; data from April we re used for Atlantic tomcod (data from ichthyoplankton sampling were not available from earlier months in most years); and data from June and July were used for bay anchovy.

Results from the regression analyses were highly significant for all species and

are summarized in Tables D-1-2 and D-1-3. Plots of predicted versus observed values from these regressions are presented in Figures D-1-1 to D-1-6. These results show that uncertainties in the input para meters identified by ESSA (w hich were excluded from this empirical assessment) did not materially affect the overall patt erns of CMR’s as

indicators of risk to entrainment. Furtherm ore, there is no indicati on that the relationship

between CMR estimates from the DEIS and the key factors affecting risk to entrainment (i.e., proportion of larval popula tion in Regions 3, 4 and 5, a nd Indian Point cooling water flow rate) changed beginning in 1991. This result provides additional support for the conclusion that any apparent declines in CM R estimates in the 1990’s were simply due to inter-annual variability in na turally occurring longitudinal distribution patterns and in cooling water flow rates at the Station.

### 13 Striped Bass Indices of Abundance



### The AEI Report uses indices of stripe d bass larval abundance from the LRS and indices of striped bass juvenile abundance from the Beach Seine Survey (“BSS”) to examine the relationship between striped bass larval abundance and resulting juvenile

abundance.

Concerns Raised in the ESSA Review



### The ESSA review challenged the validity of the BSS and NY SDEC’s beach seine survey (“JSB”) as providing valid measures of striped bass juvenile abundance. They

concluded that:

“In summary, the indices of abundan ce of juveniles (BSS, JSB, WLI-0 indices) ... each pertain to a portion of recruitment present in a specific habitat. As such, they would not be e xpected to produce reliable indices of

abundance of recruitment for the entire Hudson River striped bass population.” (ESSA 2000, page 23)

ESSA did not mention that the Atlantic St ates Marine Fisherie s Commission relies on juvenile striped bass indices from the JSB along with juvenile i ndices from Maryland’s and New Jersey’s beach seine surveys to condu ct their Atlantic co ast striped bass stock assessments. The ASMFC’s striped bass stock assessments are the basis for striped bass management on the Atlantic coast.

ESSA’s claim apparently was based on th eir belief that age-0 striped bass were emigrating from the Hudson River at faster rates since 1988 than in prior years:

“Changes in the water quality of the Hudson River could have affected the reliability of the BSS and JSB as indices of year-class strength. NY harbor water quality improvements due in part to sewage treatment in the lower

Hudson River from RM 20 down to RM 0 in recent years have opened a window allowing access to the Long Island habitat (NYSDEC comm.). The BSS and JSB may be fine estimates of juvenile densities in the beach zones for which they were designed, but fail completely to index yearclass strength because of variable residence time and emigration from the sampling area (i.e., more recruitment could have occurred post-1988 than actually measured). Thus BSS and JSB may be significantly underestimated in recent years.” (D eriso, et.al. 2000, page 3)

ESSA supported this contention by citing ag e-0 striped bass data collected by NYSDEC in Western Long Island Sound (“WLI-0”):

“[BSS and JSB] measure juvenile density in the lower Hudson River

beach seine habitat. The existence of the WLI-0 index indicates that

### 14 neither of the first two indices m easure abundance of the entire yearclass.”

These statements suggest that ESSA found an upward trend in a bundance indices from the WLI-0 Survey starting after 1988 that c ould not be explained by changes in the inRiver abundance of age-0 striped bass.

New Analyses Confirming Validity of BSS Indices of Abundance for Use in AEI Report



### Subsequent to ESSA’s review of th e DEIS, Dunning et.al. (2006a) documented the presence of striped bass larvae in the East River, and demonstrat ed that striped bass

larvae from the lower Hudson River could be passively transported, by tidal currents, to the East River and Western Long Island Sound. They found that 12% or more of striped bass larvae in the Battery Region of the H udson River would be transported by tidal currents to the upper East River/Western Long Island Sound Region. They also found that the abundance of striped bass larvae in the East River was correlated with the abundance of larvae in the Battery Region, whic h in turn was correlated with freshwater

flow rates in the Hudson River. These re sults suggest that sm all age-0 striped bass collected by the WLI-0 survey likely were Hudson River fi sh transported through the

East River as larvae.

To address the question of whether in creases in striped bass age-0 abundance indices from the WLI-0 Survey since 1988 were due to increases in the emigration rate from the Hudson River, the relationship between:

1) WLI-0 age-0 striped bass abundance i ndices (from J.B. Socrates, 2005), and 2) Striped bass larval abundance in the Hudson River, and Hudson River

freshwater flow when stri ped bass larvae are abundant.

The relationship was examined with th e following non-linear regression model:

 

y June G

y y 

### L WLI

, 1 

### exp 0  

###  

### 



### where

WLI ,y 

### is the WLI-0 abundance index for July through October for striped bass in year, y,

L

y 

### is the Hudson River striped ba ss post yolk sac larval abundance index for year, y 

### , and

G

June,y 

### is the monthly freshwater flow (measured by USGS at Green Island) for June in year, y.

### 15 In this model, the abundance of juvenile striped bass in Western Long Island Sound in each year is directly proportional to the st riped bass post yolk sac larvae abundance in the Hudson River in that year. The proportionali ty depends only on the fr eshwater flow rate in June of that year. The exponential term allows the relationshi p between freshwater flow rate and the proportionality to be non-linear.

Results from this regression analyses were highly significant and are summarized

in Table D-1-4. Plots of predicted versus observed valu es from the regression are presented in Figures D-1-7a and D-1-7b. These results clearly indicate that the abundance of age-0 striped bass in West ern Long Island Sound can be adequately predicted from the abundance pattern of larv al striped bass in the Hudson River and the

level of freshwater flow in June. Furthermore, there is no indication of a change in emigration rate, unrelated to changes in fres hwater flow, since 1988 (Figure D-1-8). Any apparent upward trend in abundance of age- 0 striped bass in Western Long Island Sound can be explained by changes in larval abundanc e and freshwater flow rates in the Hudson

River.

The results from this analysis together with the findings of the Dunning et.al. (2006) study, and the reliance by the AS MFC on beach seine survey indices of abundance for striped bass for the purpose of managing the Atlantic coast striped bass stock, provide confirmation that the BSS i ndices of striped bass juvenile abundance are valid measures of striped bass juvenile abundance as used in the AEI Report.

Bay Anchovy Abundance Trends



### The AEI Report concluded that entrainmen t of bay anchovy at Indian Point could be rejected as an explanation for long-term trends in the abundance of age-0 bay anchovy in the Hudson River. The AEI Report also c oncluded that predation by striped bass was a likely explanation for trends in abundance of age-0 bay anchovy.

Concerns Raised in the ESSA Review



### ESSA’s review of the DEIS included a critique of the discussion of factors affecting bay anchovy abundance in the Hudson River, including stri ped bass predation:

“Predation by PYSL and YOY striped ba ss should be one of the major influences on the abundance of YOY bay anchovy in the Hudson River.”

“The PYSL index for striped bass ranged from 1.48 to 15.40 during the period from 1988 through 1997 and the regression was statistically significant (p-0.010). The predatio n hypothesis explaine d about 60% of

the variation in the abundance of YOY bay anchovy (R2 = 0.580).” (page V-115, DEIS)

### 16 ESSA’s critique also addressed Hudson River immigration/em igration of the midAtlantic coastal stock of bay anchovy:

“Bay anchovy are part of a coastal population that spawns not only in the Hudson River but in many other pa rts of the Hudson-Raritan estuary complex. ... the abundance of anchovy within the river may change continually, due to movements of anc hovy into and out of the estuary.” (page V-116, DEIS)

ESSA dismissed these claims in the DE IS, citing shortcomi ngs in the underlying analyses. Regarding striped ba ss predation, ESSA concluded:

“We found the analysis difficult to follow and unconvincing. ... For example, it does not present the underly ing model, discuss the statistical uncertainty of the data, cite relevant literature, or refer to any previous DEIS work that might lend support to the approach taken (e.g., previous technical workshops).” (page 8, Parnell and Marmorek, 2000)

Regarding bay anchovy immigration/ emigration, ESSA concluded:

“We find the methods and results tenuous and feel the results do not support the discussion in Chapter V-G. Chapter V-G also assumes that entrainment of bay anchovy is offset by immigration from a larger coastal stock, but presents no evidence that supports this assu mption.” (page 1, Parnell and Marmorek, 2000)

ESSA’s review of the DEIS also included a critique of an analysis of striped bass predation on bay anchovy conducted by Dr. Ke nneth Rose (Appendix VI-4-D, DEIS). Again, ESSA dismissed the conclusions of this analysis, citing shortcomings of the analysis:

“We find the results of bay anc hovy population (production forgone) modeling to be speculative for seve ral reasons. ... The DEIS analysis greatly overestimates the predatory de mand of striped ba ss and bluefish by: 1) using an incorrect striped bass age-structure, 2) applying the highest

observed values for the contribution of bay anchovy to the diet of striped bass, and 3) estimating river-wide a bundance of striped bass and bluefish using near-shore striped bass and bl uefish densitie s and river-wide volume. The analysis of entrainmen t effects on the daily biomass of bay anchovy attempts to address the dyna mic changes in entrainment and predators’ requirements missed in the analysis of predatory demand. However, the analysis assumes that all natural mortality is due to predation and this ove restimates true predation. For example, the fact that spawner immigration is required in the model to avoid population

### 17 extinction may mean that mortality is set too high elsewhere.” (page 22, ESSA 2000).

Although the ESSA review of the DEIS challenged the cl aims in the DEIS that striped bass predation and immigration/emig ration by the mid-Atlan tic bay anchovy stock were major factors affecting bay anchovy a bundance in the Hudson River, ESSA did not provide any evidence to refute these claims.

New Analyses Regarding Tre nds in Bay Anchovy Abundance



### Subsequent to ESSA’s review of th e DEIS, Dunning et.al. (2006b) documented the presence of bay anchovy e ggs and larvae in New York Ha rbor, the East River, and Long Island Sound. They found that the peak abundance of bay anchovy eggs and larvae in nearby waterways were about eight times larg er than those in the Hudson River. That finding clearly supports the pr oposition that bay anchovy abu ndance in the Hudson River influenced greatly by immigration/emigra tion by the mid-Atlant ic coastal stock.

The likely nature of immigration/emigration of the mid-Atlantic coastal stock was examined further with an empirical asse ssment of the relationship between larval abundance in the Hudson River and salinity and temperature in the River. The purpose of the empirical assessment was to determine whether bay anchovy larval abundance in the Hudson River could be predicted by salinity, freshwater flow and temperature. If bay anchovy in the Hudson River are only a small fr action of the mid-Atlantic stock, and if they enter the Hudson River opportunistically depending on annual salinity, freshwater flow and temperature conditions, then larval abundance would be correlated with salinity, freshwater flow and temperature.

The empirical assessment examin ed the relationship between:

1) Bay anchovy index of PYSL abundance, and 2) Three measures of physical properti es of the Hudson River during the spring: a) The proportion of the river with salinity greater th an 5 ppt during the spring (i.e., weeks 18 through 26), b) The freshwater fl ow rate in June, and c) The proportion of the river with temperature greater than 75 o 

### F during the spring (i.e., weeks 18 through 26).

The relationship was examined with the following log-linear regression model: 

#  

Ty y June Sy y e 

### R G R PYSL 3

, 2 1 0 

### log     

###    

where

PYSL y 

### is the bay anchovy PYSL abundance index for year, y ,

### 18 R Sy 

### is an estimate of the proportion of the river with salinity greater than 5 ppt during the spring (i.e., weeks 18 through 26) in

year, y ,

G

June,y 

### is the monthly freshwater flow (measured by USGS at Green Island) for June in year, y , and

R Ty 

### is an estimate of the proportion of the river with temperature greater than 75 o 

### F during the spring (i.e., weeks 18 through 26) in year, y

.

A log-linear model was used to allow for non- linear relationships between the response and explanatory variables. The variable, R S y 

### was calculated using the following formula:

y W W

W W

R S s s r r S s y W s r s r

W

W W y W y

R r



### V V

R

, 12

1 , 12

1 , , , ,

, 

### *

* 1 max

min max

min 

### 

 

 

  

 

 

  

 

               
 

    

 

    

 

 

#     




   





### where

S r 

### V

, 

### is the volume of region r and stratum s ,

r 

### S s  

### defines the subset of strata that were consistently sampled within region r ,

y W s r ,

, , 

###  = 1 if the average salinity in region r , stratum s , week W and year,

y , was greater than 5 ppt,

y W s r ,

, , 

###  = 0 otherwise, and

y W

, 

### *  

### = 1 if all 12 standard regions and all standard strata (a total of 27 region-strata combinations) were sampled in week W of

year y , and

y W

, 

### *  

### = 0 otherwise.

The variable, R T y 

### was calculated using the same method, but with the term,

y W s r ,

, , 

### 

, redefined as:

### 19 y W s r ,

, , 

###  = 1 if the average water temperature in region r , stratum s , week

W

and year, y , was greater than 75 o 

### F,

y W s r ,

, , 

###  = 0 otherwise, and

Results from the regression analyses were statistically significant and are summarized in Table D-1-5. Plots of pred icted versus observed values from these regressions are presented in Fi gures D-1-9a and D-1-9b. These results, together with the findings of Dunning et.al. (2006b) support the proposition that bay anchovy in the Hudson River are only a small fraction of the mid-Atlantic stock, th at enter the Hudson River opportunistically depending on annual phys ical conditions of the Hudson River.

An additional analysis was conducted to examine the possible effects of entrainment at the Stations and striped ba ss predation on juve nile abundance of bay anchovy. This additional empirical assessmen t examined of the relationship between:

1) Bay anchovy juvenile abundance in the Hudson River, and 2) Four potential pr edictor variables: a) Bay anchovy PYSL abundance, b) Extent of the Hudson River occupied by PYSL bay anchovy, c) Entrainment at Indian Point (as measured by CMR), and d) Striped bass predatio n pressure (as measured by the striped bass PYSL index of abundance).

This relationship was examined in three steps. First, a base relationship was examined that included only PYSL abundanc e and the extent of the ri ver occupied by PYSL bay anchovy as predictor variables. The base re lationship was examined with the following log-linear regression equation: 

#  

y y y e 

### Z PYSL JUV 2 1 0 

### log 

###      

where

JUV y 

### is the index of abundance of bay anchovy juveniles in year, y , based on data from the FSS, and

Z

y 

### is a measure of the extent of the river occupied by PYSL bay anchovy.

A log-linear model was used to allow for non- linear relationships between the response and explanatory variables. The variable Z y 

### was computed as an abundance-weighted average region number, where the region-spec ific proportion of the riverwide abundance

### 20 of PYSL was used as the weight fo r each region. Larger values of Z y 

### indicate the distribution of bay anchovy PY SL extended farther upriver. Results from the base regression analysis showed that the proportion of the river occupied by PYSL bay anchovy was statistically significan t, but bay anchovy PYSL abundance per se was not statistically significant for pr edicting juvenile abundance (Table D-1-6). Therefore, the term for bay anchovy PYSL abundance was not included in the last two steps of the analysis.

Next, the potential effect of entrainment at Indian Point was examined by adding annual estimates of bay anchovy CMR ( CMR y 

### ) to the regression equation: 

#  

y y y e 

### CMR Z JUV 2 1 0 

### log 

###      

to determine whether the inclusion of entrainment effects improved the ability to predict bay anchovy juvenile abundance. If the Stations ’ entrainment affected survival from PYSL to the juvenile life stage, including a term for entrainment in the regression equation should improve the predictions.

The third step was to examine the potential effect of striped bass predation by adding the striped bass PYSL a bundance index (as a measure of striped bass predation) to the regression equation: 

#  

y y y e 

### L Z JUV 2 1 0 

### log 

###      

to determine whether the inclusion of stripe d bass predation effects improved the ability to predict bay anchovy juvenile abundance. If striped bass predation affected survival from PYSL to the juvenile life stage, includ ing a term for striped bass predation in the regression equation should improve the predictions.

Results from this series regression an alyses are summarized in Tables D-1-6 through D-1-8. The results from the base re gression analysis indicate that juvenile bay anchovy abundance depends on how much of the river is occupied by PYSL bay anchovy, and that bay anchovy PYSL abundance, per se , is not a good predictor of juvenile abundance. This result suggests that in years with high PYSL abundance concentrated downriver, juvenile abundance is not like ly to be high as we ll. However, in years with similarly high PYSL abundance sp read over many regions, juvenile abundance is likely to be high.

The term for Indian Point entrainment wa s not statistically significant (p=0.7593), indicating that the Stations’ entrainment did not have a significant effect on bay anchovy survival from PYSL to the juvenile life stage. However, the term for striped bass predation was statistically si gnificant (p=0024), indi cating that striped bass predation had a significant effect on bay anchovy survival from PYSL to the juvenile life stage.

### 21 Literature Cited



### ASAAC. 2007. 2005 year class report for the Hudson River estuary monitoring program. Prepared for Dynegy Roseton L.L.C.

Deriso, R.B., D.R. Marmorek, and I. Parnell. 2000. Review of the A ssessment of Striped Bass. Companion Report to a Review of the DEIS for SPDES Permits for three Hudson River Generating Stations. Prep ared by ESSA Technologies Ltd., Vancouver, BC, for NYSDEC, Albany, NY. 6 pp.

Dunning, D.J., Q.E. Ross, A.F. Blumberg, and D.G. Heimbuch. 2006a. Transport of striped bass larvae out of the Lower Huds on estuary. American Fisheries Society Symposium 51:273-286.

Dunning, D.J., Q.E. Ross, M.T. Mattson, a nd D.G. Heimbuch. 2006b. Distribution and abundance of bay anchovy eggs and larv ae in the Hudson River and nearby waterways. American Fisher ies Society Symposium 51:215-226.

ESSA Technologies Ltd. 2000. Review of the Draft Environmental Impact Statement for SPDES Permits for the Bowline Point 1 & 2, Indian Point 2 & 3, and Roseton 1 & 2 Steam Electric Generating Stations. Pr epared for NYSDEC, Albany NY. 31 pp.

Parnell, I. and D.R. Marmorek. 2000. Re view of the Assessment of Bay Anchovy. Companion Report to a Review of the DE IS for SPDES Permits for three Hudson River Generating Stations. Prepared by ESSA Technologies Ltd., Vancouver, BC, for NYSDEC, Albany, NY. 9 pp.

J.B. Socrates. 2005. An investigation of the movements and growth of the 2003 Hudson River year class in Western Long Island ba ys. A study of the striped bass in the

marine district of New York State. Annual report for PL89-304, project AFC-29.

### 22 Tables



### Table D-1-1. Results from assessment of ra tio of PYSL abundance in offshore (channel and bottom strata) and nearshore (shoal st ratum) areas of the Indian Point Region

of the Hudson River.

Species Average Abundance Ratio (nearshore/offshore)

1980-1989 Average Abundance Ratio (nearshore/offshore)

1990-1990

Lower

95%

Confidence

Limit Estimate Upper

95%

Confidence

Limit Lower

95%

Confidence

Limit Estimate Upper

95%

Confidence

Limit

American

Shad 0.095 0.196 0.300 0.033 0.125 0.216

Atlantic

Tomcod 0.001 0.010 0.020 -0.002 0.035 0.071

Bay Anchovy 0.028 0.084 0.139 0.045 0.055 0.064

River Herring 0.035 0.149 0.263 0.062 0.096 0.131

Striped

Bass 0.040 0.066 0.092 0.059 0.075 0.091

White

Perch 0.039 0.051 0.063 0.043 0.052 0.061

### 23 Table D-1-2. Results from non-lin ear regression (res ponse variable = CMR s,y 

### ) analyses of annual CMR estimates ( CMR s,y 

### ) with proportion of larval population in regions 3,4 and 5 ( P s,y 

### ), and the Stations’ cooling water flow ( F s,y 

### ) as predictor variables.

Species Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( P s,y 

### ) 2 

### 



### ( F s,y 

### )

American

Shad 0.80 <0.0001 -5.79 [<0.0001] 26.48 [<0.0001] 5.2x10 -6



### [0.7907]

Atlantic

Tomcod 0.79 <0.0001 -3.32 [<0.0001] 5.60 [<0.0001] 2.4x10 -5



### [<0.0001]

Bay Anchovy 0.68 <0.0001 -3.64 [<0.0001] 1.50 [0.0060] 2.5x10 -5



### [<0.0001]

River Herring 0.83 <0.0001 -5.80 [<0.0001] 31.99 [<0.0001] 2.3x10 -5



### [0.0003]

Striped Bass 0.60 <0.0001 -4.33 [<0.0001] 4.38 [0.0137] 2.5x10 -5



### [0.0002]

White Perch 0.75 <0.0001 -4.96 [<0.0001] 18.60 [<0.0001] 2.3x10 -5



### [0.0001]

### 24 Table D-1-3. Results from linear regression (response variable = logit( CMR s,y 

### )) analyses of annual CMR estimates ( CMR s,y 

### ) with proportion of larval population in regions 3,4 and 5 ( P s,y 

### ), and the Stations’ cooling water flow ( F s,y 

### ) as predictor variables.

Species Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( P s,y 

### ) 2 

### 



### ( F s,y 

### )

American

Shad 0.46 0.0008 -6.92 [<0.0001] 36.89 [0.0004] 1.5x10 -5



### [0.2381]

Atlantic

Tomcod 0.76 <0.0001 -3.32 [<0.0001] 5.07 [<0.0001] 2.5x10 -5



### [<0.0001]

Bay Anchovy 0.71 <0.0001 -3.85 [<0.0001] 1.71 [0.0024] 2.7x10 -5



### [<0.0001]

River Herring 0.61 <0.0001 -6.57 [<0.0001] 65.25 [<0.0001] 1.9x10 -5



### [0.0871]

Striped Bass 0.54 <0.0001 -4.43 [<0.0001] 3.90 [0.0266] 2.8x10 -5



### [<0.0001]

White Perch 0.76 <0.0001 -5.38 [<0.0001] 22.49 [<0.0001] 2.6x10 -5



### [<0.0001]

### 25 Table D-1-4. Results from regression an alysis of annual estimates of striped bass juveniles in Western Long Island Sound ( WLI y 

### ) with striped bass PYSL abundance index ( L y 

### ) and freshwater flow in June ( G June,y 

### ) as predictor variables.

Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(scaling constant) 1 

### 



### ( G June,y 

### )

0.97 <0.0001 4.87x10 -12



### [<0.0001] 0.1839 [<0.0001]

### 26 Table D-1-5. Results from regression anal ysis of annual estimate s of bay anchovy PYSL abundance ( PYSL y 

### ) with proportion of the river with salinity gr eater than 5 ppt in the spring ( R Sy 

### ), freshwater flow in June, and proportion of the river with temperature greater than 75 o 

### F in the spring ( R Ty 

### ) as the predictor variables.

Response

Variable

[Analysis Method] Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( R Sy 

### ) 2 

### 



### ( G June,y 

### ) 3 

### 

( R Ty 

### )

ln( PYSL y 

### ) [Linear Regression] 0.65 <0.0001 17.4437 [<0.0001] 12.4662 [0.0049] -8.99x10-5 [0.0521] 11.5884 [0.0040]

PYSL y 

### [Non-Linear Regression] 0.97 <0.0001 19.7984 [<0.0001] 3.7096 [0.1014] -0.0001 [.0209] 9.1256 [<0.0001]

Table D-1-6. Results from regression anal ysis of annual estimates of juvenile bay anchovy abundance ( JUV y 

### ) with bay anchovy PYSL abundance ( PYSL y 

### ) and extent of river occupied by PYSL ( Z y 

### ) as the predictor variables.

Response

Variable

[Analysis Method] Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( PYSL y 

### ) 2 

### 



### ( Z

y 

### )

ln( JUV y 

### ) [Linear Regression] 0.37 0.0237 18.0424 [<0.0001] -3.15x10 -11



### [0.7034] 0.4384 [0.0077]

JUV y 

### [Non-Linear Regression] 0.46 <0.0001 18.0423 [<0.0001] -3.50x10 -11



### [0.6238] 0.4629 [0.0009]

### 27 Table D-1-7. Results from regression anal ysis of annual estimates of juvenile bay anchovy abundance ( JUV y 

### ) with the extent of ri ver occupied by bay anchovy PYSL ( Z y 

### ), and the Stations’ entrainment ( CMR y 

### ) as the predictor variables.

Response

Variable

[Analysis Method] Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( Z

y 

### ) 2 

### 



### ( CMR y 

### )

ln( JUV y 

### ) [Linear Regression] 0.37 0.0243 18.1220 [<0.0001] 0.4294 [0.0073] -0.0070 [0.7593]

JUV y 

### [Non-Linear Regression] 0.45 <0.0001 18.0210 [<0.0001] 0.4558 [0.0034] 0.0015 [0.9418]

Table D-1-8. Results from regression anal ysis of annual estimates of juvenile bay anchovy abundance ( JUV y 

### ) with the extent of ri ver occupied by bay anchovy PYSL ( Z y 

### ), and striped bass predation ( L y 

### ) as the predictor variables.

Response

Variable

[Analysis Method] Overall Regression Individual Parameter Estimates with Significance Level [Pr>|t|]

R 2 

### Pr>F
0 

### 

(intercept) 1 

### 



### ( Z

y 

### ) 2 

### 



### ( L

y 

### )

ln( JUV y 

### ) [Linear Regression] 0.65 0.0002 18.7277 [<0.0001] 0.2769 [0.0235] -0.74x10 -10



### [0.0024]

JUV y 

### [Non-Linear Regression] 0.57 <0.0001 18.5615 [<0.0001] 0.3394 [0.0061] -1.42x10 -10



### [0.0742]

### 28 Figures



### Figure D-1-1. Results of regression analys is of American shad CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 American Shad CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 29 Figure D-1-2. Results of regression analys is of Atlantic tomcod CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Atlantic Tomcod CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 30 Figure D-1-3. Results of regression anal ysis of bay anchovy CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.05 0.10 0.15 0.20 0.25

0.00 0.05 0.10 0.15 0.20 0.25 Bay Anchovy CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 31 Figure D-1-4. Results of regression analys is of river herring CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 River Herring CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 32 Figure D-1-5. Results of regression anal ysis of striped bass CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 Striped Bass CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 33 Figure D-1-6. Results of regression anal ysis of white perch CMR estimates with proportion of PYSL in regions 3,4 and 5; and the Stations’ coo ling water flow as predictor variables.

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 White Perch CMR

Prediction Based on Indian Point Cooling Water Flows and Proportion of PYSL in Regions 3,4 and 5

CMR Estimate P r e d i c t e d C M R

1975-1990 1991-2002

### 34 Figure D-1-7a. Results of regression anal ysis of abundance index for striped bass young of year (“YOY”) in Western Long Island Sound with Hudson River striped bass

PYSL index of abundance and freshwater fl ow in June as predictor variables.

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0

WLIS age-0 abundance index P r e d i c t e d W L I S a g e - 0 a b u n d a n c e i n d e x

1984-1988 1989-2004 Striped Bass Juvenile Abundance in Western Long Island Sound

Prediction Based on

PYSL Abundance and

Freshwater Flow in June

### 35 Figure D-1-7a. Results of regression anal ysis of abundance index for striped bass YOY in Western Long Island Sound with Huds on River striped bass PYSL index of

abundance and freshwater flow in June as predictor variables. Plotted on logarithmic scale.

0.1 1.0 10.0 100.0

0.1 1.0 10.0 100.0

WLIS age-0 abundance index P r e d i c t e d W L I S a g e - 0 a b u n d a n c e i n d e x

1987-1988 1989-2004 Striped Bass Juvenile Abundance in Western Long Island Sound (plotted on log scale)

Prediction Based on

PYSL Abundance and

Freshwater Flow in June

### 36 Figure D-1-8. Ratio of: 1) index of a bundance of YOY striped bass in Western Long Island Sound to 2) index of abundance of PYSL striped bass in the Hudson River; predicted by freshwater flow in June. Relationship based on results of regression analysis depicted in Figure D-1-7.

0.0 1.0 2.0 3.0 4.0 5.0 6.0

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

Green Island Flow in June (cfs) P r e d i c t e d R a t i o o f W L I S / P Y S L I n d i c e s ( x 1 0 9 )

1984-1988 1989-2004 Predicted Ratio of Juvenile striped bass abundance in WLIS to PYSL striped bass abundance in Hudson River

Based on Freshwater Flow in June

### 37 Figure D-1-9a. Results of regression analys is of bay anchovy PY SL abundance in the Hudson River with salinity, freshwater fl ow and water temperature as predictor

variables.

0.0E+00 1.0E+09 2.0E+09 3.0E+09 4.0E+09 5.0E+09 6.0E+09

0.0E+00 1.0E+09 2.0E+09 3.0E+09 4.0E+09 5.0E+09 6.0E+09

PYSL Index P r e d i c t e d P Y S L I n d e x

1974-1990 1991-2005 Bay Anchovy PYSL Abundance

Prediction Based on Salinity, Freshwater Flow, and Water Temperature

### 38 Figure D-1-9b. Results of regression analys is of bay anchovy PY SL abundance in the Hudson River with salinity, freshwater fl ow and water temperature as predictor variables. Plotted on logarithmic scale.

12.0 14.0 16.0 18.0 20.0 22.0 24.0

12.0 14.0 16.0 18.0 20.0 22.0 24.0

PYSL Index (log

e ) P r e d i c t e d P Y S L I n d e x ( l o g e )

1974-1990 1991-2005 Bay Anchovy PYSL Abundance

Prediction Based on Salinity, Freshwater Flow, and Water Temperature