PSEG Comments on Proposed 316(b) Rule 

Appendix A—August 18, 2011

 A-22 

Attachment C 

Excerpt from 

Salem Generating Station 

NJPDES Permit No. NJ0005622 

Response to NJPDES Permit Special Conditions G.9: 

INTEGRATED FINDINGS REPORT 

Attachment 9: Special Study Report 

Salem Generating Station 

Estimated Latent Impingement Mortality Rates: 

Updated Pooled Estimates Using Data from 

1995, 1997, 1998, 1999, 2000 and 2003

PSEG Nuclear LLC 

Estuary Enhancement Program 

November 2004 
Special Study Report 

Salem Generating Station 

Estimated Latent Impingement Mortality Rates: 

Updated Pooled Estimates Using Data from 

1995, 1997, 1998, 1999, 2000 and 2003 

Prepared for 

PSEG Services Corp. 

Prepared by 

AKRF 

7250 Parkway Drive, Suite 210 

Hanover, MD 21076 

June 18, 2004 
1

I. INTRODUCTION 

 This report contains updated estimates of latent impingement mortality (“LIM”) 

rates for the new intake screens at Salem Generating Station (“Station”). These LIM rate 

estimates update the LIM rate estimates presented in Appendix L of PSEG’s March 1999 

Permit Renewal Application for Salem Generating Station (“1999 Application”), and the 

LIM rate estimates presented in the Public Service Enterprise Group report entitled 

“Special Study Report, Salem Generating Station. Estimated Latent Impingement 

Mortality Rates: Updated Pooled Estimates Using 1995, 1997, 1998, 1999, and 2000 

Data” (prepared by PBS&J, Beltsville, MD, June 2001). The current updates include 

data on fish examined in LIM studies in 2003, as well as those examined in LIM studies 

in 1995, 1997, 1998, 1999 and 2000. 

II. METHODS 

A. Pooled Estimates of LIM Rates 

 The updated estimates of LIM rates were computed using the methods for 

calculating pooled LIM rate estimates that are described in Appendix F, Attachment F-2 

of the 1999 Application. The pooled estimates of LIM rates for the new intake screens 

were based on fish collected during two-unit combined sluice operation only. For each 

species, estimates were computed for months in which at least 30 fish (initially alive) 

were examined for latent impingement mortality. With 30 fish, the 95% confidence 

interval for an estimated LIM rate of 0.5 is roughly 0.3 to 0.7; the 95% confidence 

interval for an estimated LIM rate of 0.0 is roughly 0.0 to 0.1; and the 95% confidence 

interval for an estimated LIM rate of 1.0 is roughly 0.9 to 1.0. 

B. Predicted LIM Rates from Logistic Regression Analysis 

 For months in which fewer than 30 fish of a species were examined for latent 

impingement mortality, a predicted latent impingement mortality rate was calculated 

based on the average water temperature and salinity, and the average length of fish 

impinged during the month. The relationship between latent impingement mortality rate 

and the predictor variables (i.e., water temperature, salinity and fish length) was 

characterized with a logistic regression model. The logistic regression model gives equal 

weight to each fish examined in the LIM studies. The logistic regression analysis used all 

of the data (with reported temperature, salinity and fish length) from latent impingement 

mortality studies that were used to compute the pooled LIM rate estimates. 

 The following logistic regression model was used to characterize the relationship 

between latent impingement mortality rate and the predictor variables: 

∑=

= +

5

1

0 , logit( )

i

pk β βiXi k
2

where 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

− =

k

k

k

p

p p 1 logit( ) ln

and 

pk = probability of latent impingement mortality during experiment k

β 0 = intercept term of the logistic regression model 

βi = coefficient of term i in the logistic regression model 

Xi,k = value of variable Xi (see list below) based on the temperature, 

salinity and average length of fish in experiment k

X1 = average length of fish 

X2 = temperature 

X3 = salinity 

X4 = (X2,k)× (X1,k) temperature-length interaction 

X5 = (X3,k)× (X1,k) salinity-length interaction 

 Variables X4 and X5 are interaction variables that allow the effects on the latent 

impingement mortality rate of temperature and salinity to vary depending on the length of 

the fish. A preliminary analysis indicated that additional terms (e.g., quadratic terms) 

would not materially improve the predictive ability of the model. A stepwise procedure 

was used which only retained terms in the model that were statistically significant 

(pr=0.001) for explaining variability in latent impingement mortality rates. 

 The predicted latent impingement mortality rate in each month was calculated as 

follows: 

Ym m

e

p ˆ

1

~ 1

− + =

where 

∑=

= +

5

1

0 , ˆ ˆ ˆ

i

Ym β βiX m i

and 

pm

~ = predicted latent impingement mortality rate in month m

X m,i = the value of variable Xi based on the average historical (1977-

2001) temperature, salinity and impinged fish length during 

month m

βi

ˆ = maximum likelihood estimate of the coefficient for term i of the 

logistic regression model 

The variance of each predicted value was estimated using the Taylor series 

approximation (Kendall, M. and A. Stuart, 1977): 
3

( ) ( ) m Y

Y

m Y

e

e

p m

m

ˆ vaˆr

1

) ~ vaˆr(

2

2 ˆ

ˆ

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

+

= −

−

where 

( ) ∑∑ ( ) = =

=

5

0

5

0

, , ˆ , ˆ coˆv ˆ vaˆr

i j

Ym X m iX m j βi β j

and 

( ) βi β j

ˆ , ˆ c oˆv = estimated covariance between βiˆ and β jˆ (from the logistic 

regression) 

Xm,0 = 1 for all months m

The approximate 95% confidence limits for the predicted latent impingement mortality 

rate in month m were computed as: 

(1.96 vaˆr( ˆ )) ~pm ± × pm

C. Confidence Limits for Pooled LIM Rate Estimates 

 For the purpose of comparing monthly predicted values of latent impingement 

mortality rates (from the logistic regression analysis) to pooled monthly estimates of 

latent impingement mortality rates, confidence limits were calculated for the pooled 

estimates. Confidence limits were calculated based on the binomial distribution (Beyer, 

W.H., 1966). For upper confidence limits, the following equation was solved for ρ UCL : 

ρ ( ) − ρ = α ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ∑=

− r

x

n x

UCL

x

UCL

x

n

0

1 

and for lower confidence limits, the following equation was solved for ρ LCL : 

ρ ( ) − ρ = α ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ∑=

− n

x r

n x

LCL

x

LCL

x

n

1

where 

ρ LCL = lower confidence limit for the pooled monthly estimate of the 

LIM rate 

ρ UCL = upper confidence limit for the pooled monthly estimate of the 

LIM rate 

n = total number of fish on which the pooled monthly estimate of the 

LIM rate was based 
4

r = total number of fish (out of n) that did not survive the LIM 

experiment 

α = probability level for the confidence limits (for 95% confidence 

limits, α = 0.025) 
5

III. RESULTS 

 Estimates of monthly LIM rates based on the pooled estimation method are 

presented in Table 1. Also presented in Table 1 are predicted LIM rates (from the 

logistic regression analysis) for months in which fewer than 30 fish of a taxon were 

examined in the LIM studies. Numbers of fish examined in the LIM studies, by taxon 

and month, are listed in Table 2. Numbers of fish examined in the LIM studies and 

included in the logistic regression analysis (i.e., fish for which length, temperature and 

salinity were reported) are listed in Table 3. 

 Monthly predicted LIM rates with 95% confidence limits are presented in Figures 

1 through 7. For comparison, these figures also depict monthly estimates of LIM rates 

with 95% confidence limits from the pooled estimation method. These graphs depict 

monthly LIM rate estimates (based on the pooled estimation method) for all months that 

provided any fish that were included in the logistic regression analysis, not just months in 

which at least 30 fish were examined. For the purpose of comparing predicted (from the 

logistic regression) LIM rates to estimated (from the pooled estimation method) LIM 

rates, the estimated LIM rates were computed using only fish included in the logistic 

regression analysis (i.e., fish for which length, temperature and salinity were reported). 

 Estimated coefficients for the logistic regression model are listed in Table 4. 

 The logistic regression analysis was not conducted for blue crab because blue crab 

were only collected for LIM studies during two days in September 1998, and temperature 

was not reported in the data. All hogchoker examined during LIM studies survived, and 

therefore a logistic regression analysis was not conducted for hogchoker. 

IV. LITERATURE CITED 

Beyer, W.H. (ed.) 1966. CRC Handbook of Tables for Probability and Statistics. The 

Chemical Rubber Co. Cleveland, OH. 

Kendall, M. and A. Stuart. 1977. The Advanced Theory of Statistics. Vol. 1. Macmillan 

Publishing Co., Inc. New York, NY. 
6

Table 1. Monthly latent impingement mortality rate estimates for two-unit, combined sluice operation with the n

system based on the pooled estimation method (shaded cells) and based on the logistic regression analysibased on data collected from 1995 through 2003. Estimates for Alosids are for American shad, alewife acombined. Predicted latent impingement mortality rates for weakfish could not be computed for January no weakfish were reported in impingement collections in those months. Consequently, the average length variable required for the logistic regression analysis) in those months could not be computed. The logisti

was not conducted for blue crab or hogchoker due to data limitations. 

TAXON JAN FEB MAR APR MAY JUN JUL AUG SEP 

Alosids 0.081 0.083 0.139 0.209 0.512 0.715 0.808 0.813 0.725 Atlantic Croaker 0.204 0.217 0.218 0.433 0.302 0.282 0.106 0.377 0.157 Bay Anchovy 0.022 0.024 0.062 0.465 0.491 0.716 0.907 0.963 0.947 Spot 0.233 0.279 0.450 0.749 0.611 0.469 0.252 0.135 0.090 Striped Bass 0.000 0.000 0.001 0.002 0.002 0.013 0.339 0.132 0.190 Weakfish . . 0.033 0.147 0.035 0.559 0.639 0.538 0.186 White Perch 0.063 0.007 0.012 0.043 0.318 0.235 0.340 0.125 0.059 Blue Crab 0.023 Hogchoker 0.000 0.000 0.000 
7

Table 2. Total number of fish examined in latent impingement mortality studies (by taxon and month) during tw

sluice operation of the new intake screen system. 

TAXON JAN FEB MAR APR MAY JUN JUL AUG SEP OCT 

Alosids 11 43 7 2 11 20 39 Atlantic Croaker 452 180 706 708 47 5 23 212 Bay Anchovy 1 303 212 162 43 54 57 260 Spot 3 4 22 Striped Bass 5 6 1 23 280 317 105 196 Weakfish 1239 2439 2170 349 47 White Perch 32 16 115 44 22 191 551 101 895 Blue Crab 43 Hogchoker 120 211 79 15 
8

Table 3. Total number of fish examined in latent impingement mortality studies (by taxon and month) during tw

sluice operation of the new intake screen system. This table only lists fish from studies in which fish lengand salinity were reported, and therefore were included in the logistic regression analysis. 

TAXON JAN FEB MAR APR MAY JUN JUL AUG SEP OCT 

Alosids 11 43 7 2 11 20 39 Atlantic Croaker 434 180 698 696 44 5 23 212 Bay Anchovy 1 302 212 151 42 51 57 259 Spot 3 4 22 Striped Bass 5 6 1 22 280 317 105 196 Weakfish 1015 2285 2073 349 47 White Perch 32 16 115 41 22 191 551 101 895 
9

Table 4. Estimated coefficient values from the logistic regression analysis. Missing values indicate the term in t

model was not statistically significant. 

TAXON 

0

ˆ

β

(Intercept) 

1

ˆ

β

(Length) 

2

ˆ

β

(Temperature)

3

ˆ

β

(Salinity) 

4

ˆ

β

(TemperatureLength 

Interaction) 

Alosids -3.0011 . 0.1710 . . Atlantic Croaker -0.7680 . . -0.1774 . Bay Anchovy -4.0239 . 0.2684 . . Spot 3.8315 . . -0.6959 . Striped Bass 1.3428 -0.1154 . . 0.0022 Weakfish -1.9848 . 0.1243 . . White Perch -5.6016 . 0.1100 . 0.0007 
10

Figure 1. Monthly estimates of latent impingement mortality rates for Alosids (i.e., 

American shad, alewife and blueback herring). Estimates of latent impingement 

mortality rate based on the pooled estimation method (orange dots) with 95% 

confidence intervals (orange bars), and predicted latent impingement mortality 

rates based on the logistic regression analysis (green dots) with 95% confidence 

intervals (green bars). Hatched orange bars indicate months in which fewer than 

30 fish were examined during the impingement mortality rate studies. The pooled 

estimates in this figure only include fish from studies in which fish length, water 

temperature and salinity were reported (i.e., the fish included in the logistic 

regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Alosids

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
11

Figure 2. Monthly estimates of latent impingement mortality rates for Atlantic croaker. 

Estimates of latent impingement mortality rate based on the pooled estimation 

method (orange dots) with 95% confidence intervals (orange bars), and predicted 

latent impingement mortality rates based on the logistic regression analysis (green 

dots) with 95% confidence intervals (green bars). Hatched orange bars indicate 

months in which fewer than 30 fish were examined during the impingement 

mortality rate studies. The pooled estimates in this figure only include fish from 

studies in which fish length, water temperature and salinity were reported (i.e., the 

fish included in the logistic regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Atlantic Croaker

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
12

Figure 3. Monthly estimates of latent impingement mortality rates for bay anchovy. 

Estimates of latent impingement mortality rate based on the pooled estimation 

method (orange dots) with 95% confidence intervals (orange bars), and predicted 

latent impingement mortality rates based on the logistic regression analysis (green 

dots) with 95% confidence intervals (green bars). Hatched orange bars indicate 

months in which fewer than 30 fish were examined during the impingement 

mortality rate studies. The pooled estimates in this figure only include fish from 

studies in which fish length, water temperature and salinity were reported (i.e., the 

fish included in the logistic regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Bay Anchovy

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
13

Figure 4. Monthly estimates of latent impingement mortality rates for spot. Estimates of 

latent impingement mortality rate based on the pooled estimation method (orange 

dots) with 95% confidence intervals (orange bars), and predicted latent 

impingement mortality rates based on the logistic regression analysis (green dots) 

with 95% confidence intervals (green bars). Hatched orange bars indicate months 

in which fewer than 30 fish were examined during the impingement mortality rate 

studies. The pooled estimates in this figure only include fish from studies in 

which fish length, water temperature and salinity were reported (i.e., the fish 

included in the logistic regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Spot

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
14

Figure 5. Monthly estimates of latent impingement mortality rates for striped bass. 

Estimates of latent impingement mortality rate based on the pooled estimation 

method (orange dots) with 95% confidence intervals (orange bars), and predicted 

latent impingement mortality rates based on the logistic regression analysis (green 

dots) with 95% confidence intervals (green bars). Hatched orange bars indicate 

months in which fewer than 30 fish were examined during the impingement 

mortality rate studies. The pooled estimates in this figure only include fish from 

studies in which fish length, water temperature and salinity were reported (i.e., the 

fish included in the logistic regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Striped Bass

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
15

Figure 6. Monthly estimates of latent impingement mortality rates for weakfish. 

Estimates of latent impingement mortality rate based on the pooled estimation 

method (orange dots) with 95% confidence intervals (orange bars), and predicted 

latent impingement mortality rates based on the logistic regression analysis (green 

dots) with 95% confidence intervals (green bars). Predicted latent impingement 

mortality rates for weakfish could not be computed for January and February 

because no weakfish were reported in impingement collections in those months. 

Consequently, the average length of impinged fish (a variable required for the 

logistic regression analysis) in those months could not be computed. The pooled 

estimates in this figure only include fish from studies in which fish length, water 

temperature and salinity were reported (i.e., the fish included in the logistic 

regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Weakfish

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate
16

Figure 7. Monthly estimates of latent impingement mortality rates for white perch. 

Estimates of latent impingement mortality rate based on the pooled estimation 

method (orange dots) with 95% confidence intervals (orange bars), and predicted 

latent impingement mortality rates based on the logistic regression analysis (green 

dots) with 95% confidence intervals (green bars). Hatched orange bars indicate 

months in which fewer than 30 fish were examined during the impingement 

mortality rate studies. The pooled estimates in this figure only include fish from 

studies in which fish length, water temperature and salinity were reported (i.e., the 

fish included in the logistic regression analysis). 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

White Perch

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Latent Impingement Mortality Rate