UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460

	OFFICE OF PREVENTION, PESTICIDE

	AND TOXIC SUBSTANCES

  SEQ CHAPTER \h \r 1 MEMORANDUM

Date:  August 19, 2008

SUBJECT:	d-Phenothrin (Sumithrin®):  Benchmark Dose Analysis of Toxicity Endpoint for Incidental Oral Exposure

PC Code:  069005	DP Barcode: 326934

Decision No.: 364966	Registration No.: 2596-150, 2596-151

Petition No.:  None	Regulatory Action: Reregistration

Assessment Type: BMD	Reregistration Case No.: 0426

TXR No.:  0052377	CAS No.: 026022-80-2

MRID No.:  47500101	40 CFR: NA

FROM:	Becky Daiss

Biologist

Reregistration Branch 4/HED (7509C)

THROUGH:	Susan Hummel

Branch Senior Scientist

Reregistration Branch 4/HED (7509C)

TO:		Jennifer Howenstine

Chemical Review Manager

		Reregistration Branch 3

		Special Review and Registration Division (7508C)

		       and

	Ann Sibold

Review Manager

Insecticide Branch

	Registration Division (7505C)

	This provides a benchmark dose (BMD) analysis of organ weight data from a d-phenothrin 2-generation rat reproduction study with 2 litters per generation (MRID 40276404).  The phenothrin registrants submitted a benchmark dose analysis of the rat reproduction study using EPA’s BMD software.  HED agrees that a benchmark dose analysis may be appropriately used to further refine the dose response relationship.  HED conducted a separate BMD analysis for this study based in part on the registrant’s submission.

BMD Analysis

The toxicity endpoint for short- and intermediate-term incidental oral exposures to d-phenothrin was selected from a 2-generation rat reproduction study.  The NOAEL is 1000 ppm and the  LOAEL is 3000 ppm  based on decreased body weight (4-6%) and increased liver weight in F0 and F1 parental animals, and an increase in absolute and relative spleen weight, and decreased absolute uterine weight in F1 adults and on decreased body weight gain during lactation of F2b pups, and decreased litter size of F1b litters at day 1, decreased absolute heart and kidney weight in F2b males, increased relative liver weight in male and female F2b pups.

A BMD is defined as an exposure due to a dose of a substance associated with a specified low incidence of risk, generally in the range of 1% to 10%, of a health effect; or the dose associated with a specified measure or change of a biological effect.  This dose is estimated using statistical methods for fitting curves to experimental data.

EPA’s Benchmark Dose Software (BMDS version 1.4.1) was used for the BMD analysis of d-phenothrin organ weight data from the rat reproduction study.  A benchmark dose (BMD) approach is used to more accurately estimate a point of departure (POD) for the observed effects.  The BMDS continuous models were selected to model the data being evaluated based on the continuous nature of organ and body weight data.  BMDS linear, polynomial and power models were used to derive the BMD10, the estimated benchmark doses that results in 10% organ weight change, and the BMDL10, the lower 95% confidence interval on the BMD10, for the data evaluated.  The BMDS continuous model default option of relative deviation was used for the benchmark response (BMR) type, with a corresponding BMR factor of 0.1 (10%) used as a basis for BMD and BMDL derivation.  The default benchmark response (BMR) level of 10% is considered reasonable for determining a point of departure for organ weight effects because organ weight changes below 10% are ordinarily not associated with adverse effects.  Since it is particularly important that the data be adequately modeled for BMD calculation, a p-value of 0.1 was used to assess goodness of fit.

Study Used for BMD Analysis

Tesh, J.; Willoughby, C.; Fowler, J. (1986) Sumithrin: Effects upon Reproductive Performance of Rats Treated Continuously throughout Two Successive Generations: (ET-61-0101): Laboratory Project ID: 85/SUM009/331. Unpublished study prepared by Life Science Research. 1449 p.  MRID 40276404

Effects Modeled

F0 Liver Weight Females

F0 Relative Liver Weight Females

F1 Spleen Weight Males

F1 Relative Liver Weight Females

F1 Spleen Weight Females

F1 Relative Spleen Weight Females

F1 Uterus Weight Females

F1 Relative Uterus Weight Females

F2B Heart Weight Males

F2B Kidney Weight Males

F2B Body Weight Males

F2B Brain Weight Males

F2B Relative Liver Weight Males

The doses used for the BMD analysis were based on chemical intake data (mg/kg/day) provided in the toxicity study.  Chemical intake for the F1 males was based on the lifetime average (arithmetic mean) intake for each dose level.  Lifetime average doses (including dosing through gestation and weaning) were used for the F0 and F1 females.  Average doses from gestation to weaning for the F1 dams that gave birth to and nursed F2b pups were used to represent dosage for the F2b pups.  Dose-response model input data sets used in the analysis are attached (Attachment 1).

Summary of Results

	Summary results of the BMD analysis are provided in the following table.  BMDLs are selected based on absolute model fit (goodness of fit statistics i.e., P-value > 0.10), comparative model fit (Akaike Information Criteria (AIC)), and visual inspection of modeled data fit.  Results of the BMDS analysis were generally consistent across models.  The linear and the power models generally produced the same PODs and fit statistics.  Based on the AIC comparative goodness of fit measure, the linear and power models consistently provided slightly better data fit.  The polynomial model consistently generated lower BMDL10 values.  The polynomial models also tended to produce exaggerated curves which may not reflect biologically plausible dose response for the observed effects.  BMDS dose-response graphs and select model outputs are attached (Attachments 2 and 3).

A BMDL10 of 100 mg/kg/day is recommended for use in risk assessment based on the combined results of the linear, polynomial and power BMDS models.  This endpoint is considered conservative based on the methodology used to establish the dose levels used for the BMD analysis.

BMDS Modeling Results for d-Phenothrin – Rat Reproduction Study

Effects Modeled	BMDL10  Results by Model (mg/kg/day)

	Linear	Polynomial 2°	Power

F0 Liver Weight Females	169	90*	169

F0 Relative Liver Weight Females	156	90*	156

F1 Relative Liver Weight Females	184	118	184

F1 Spleen Weight Males	84	66*	84

F1 Spleen Weight Females	120	90*	120

F1 Relative Spleen Weight Females	94	90*	96

F1 Uterus Weight Females	103	90*	103

F1 Relative Uterus Weight Females	115	90*	115

F2B Heart Weight Males	136	92*	136

F2B Kidney Weight Males	129	92*	129

F2B Body Weight Males	153	92*	153

F2B Brain Weight Males	165	92*	165

F2B Relative Liver Weight Males	153	103	154

* Modeled BMDL10 is below the empirical NOAEL based on chemical intake data.  Conservatively assume BMDL10 equals chemical intake NOAEL.

Attachment

Attachment 1 – BMDS Inputs

Attachment 2 -   BMDS dose-response graphs and model outputs Attachment 1 – BMDS Inputs

Inputs for d-Phenothrin BMD Analysis

F0 Liver Wt Females (Table 43 pg 124)

Dose (ppm)	Dose (mkd) 2	N	Liver Weight (g)	SD

0	0	20	13.6	1.1

300	26.6	20	14.3	1.3

1000	90	20	14.6	2

3000	271	20	15.3	1.6

F0 Relative Liver Wt Females (Table 44 pg 126)

Dose (ppm)	Dose (mkd) 2	N	Relative Liver Weight (g)	SD

0	0	20	3.89	0.36

300	26.6	20	3.94	0.27

1000	90	20	4.14	0.43

3000	271	20	4.39	0.36

F1 Relative Liver Wt Females (Table 92 pg 196)

	Dose (ppm)	Dose (mkd) 2	N	Relative Liver Weight (g)	SD

0	0	18	3.57	0.21

300	26.6	17	3.59	0.27

1000	90	20	3.72	0.28

3000	271	20	3.96	0.25

F1 Spleen Wt Males (Table 89 pg 189)

Dose (ppm)	Dose (mkd) 2	N	Spleen Weight (g)	SD

0	0	20	0.87	0.1

300	15.5	20	0.88	0.11

1000	65.6	20	0.87	0.14

3000	198	20	0.9	0.68

F1 Spleen Wt Females (Table 91 pg 195)

Dose (ppm)	Dose (mkd) 2	N	Spleen Weight (g)	SD

0	0	19	0.53	0.06

300	26.6	17	0.55	0.06

1000	90	20	0.57	0.09

3000	271	19	0.61	0.13

F1 Relative Spleen Wt Females (Table 92 pg 197)

	Dose (ppm)	Dose (mkd) 2	N	Relative Spleen Weight (g)	SD

0	0	18	0.148	0.014

300	26.6	17	0.149	0.021

1000	90	20	0.154	0.022

3000	271	19	0.176	0.034

F1 Uterus Wt Females (Table 91 pg 195)

Dose (ppm)	Dose (mkd) 2	N	Uterus Weight (g)	SD

0	0	19	0.72	0.18

300	26.6	17	0.68	0.26

1000	90	20	0.6	0.11

3000	271	20	0.6	0.13

F1 Relative Uterus Wt Females (Table 92 pg 197)

	Dose (ppm)	Dose (mkd) 2	N	Relative Uterus Weight (g)	SD

0	0	18	0.203	0.049

300	26.6	17	0.186	0.074

1000	90	20	0.162	0.03

3000	271	20	0.173	0.039

F2B Heart Weight Males (Table 85 pg 178)

Dose (ppm)	Dose (mkd) 2	N	Heart Weight (g)	SD

0	0	10	0.5	0.06

300	26.4	10	0.479	0.034

1000	92	10	0.456	0.031

3000	285	10	0.417	0.044

F2B Kidney Weight Males (Table 85 pg 178)

	Dose (ppm)	Dose (mkd) 2	N	Kidney Weight (g)	SD

0	0	10	1.13	0.14

300	26.4	10	1.05	0.06

1000	92	10	1.01	0.08

3000	285	10	0.93	0.15

F2B Body Weight Males (Table 85 pg 178)

Dose (ppm)	Dose (mkd) 2	N	Body Weight (g)	SD

0	0	9	85.5	10.3

300	26.4	10	82.5	5.8

1000	92	10	79.2	4

3000	285	10	73.9	11.1

F2B Relative Brain Weight Males (Table 86 pg 181)

	Dose (ppm)	Dose (mkd) 2	N	Brain Weight (g)	SD

0	0	9	1.858	0.157

300	26.4	10	1.908	0.125

1000	92	10	1.957	0.131

3000	285	10	2.083	0.224

F2B Relative Liver Weight Males (Table 86 pg 182)

	Dose (ppm)	Dose (mkd) 2	N	Relative Liver Weight (g)	SD

0	0	9	5.08	0.4

300	26.4	10	4.98	0.39

1000	92	10	5.22	0.39

3000	285	10	5.67	0.36

F2B Relative Liver Weight Females (Table 88 pg 186)

	Dose (ppm)	Dose (mkd) 2	N	Relative Liver Weight (g)	SD

0	0	10	5.26	0.24

300	26.4	10	5.01	0.23

1000	92	10	5.23	0.33

3000	285	10	5.86	0.33

1 Dose based on actual chemical intake data

Attachment 2  - BMDS Outputs

F0 Liver Weight Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	258	169	0.41	152

Polynomial 2°	157	63	0.39	154

Power	258	169	0.41	152

F0 Relative Liver Weight Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	212	156	0.66	-81

Polynomial 2°	155	76	0.73	-80

Power	212	156	0.66	-81

F1 Relative Liver Weight Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	243	184	0.89	-128

Polynomial 2°	232	118	0.71	-126

Power	243	184	0.89	-128

F1 Spleen Weight Males

Model	BMD10	BMDL10	P-Value	AIC

Linear	639	84	0.99	-84

Polynomial 2°	317	24	0.91	-82

Power	218	84	0.91	-82

F1 Relative Spleen Weight Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	136	94	0.88	-475

Polynomial 2°	174	65	0.95	-472

Power	171	96	0.99	-474

F1 Uterus Weight Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	179	103	0.25	-184

Polynomial 2°	46	26	0.93	-184

Power	179	103	0.25	-184

F2B Heart Weight Males

Model	BMD10	BMDL10	P-Value	AIC

Linear	183	136	0.54	-207

Polynomial 2°	111	58	0.68	-206

Power	183	136	0.54	-207

F2B Kidney Weight Males

Model	BMD10	BMDL10	P-Value	AIC

Linear	182	129	0.32	-130

Polynomial 2°	90	47	0.34	-129

Power	182	129	0.32	-130

F2B Body Weight Males

Model	BMD10	BMDL10	P-Value	AIC

Linear	226	153	0.72	206

Polynomial 2°	145	61	0.76	207

Power	119	80	0.72	206

Statistically Significant results but Poor BMDS Model Fit p < 0.1

F2B Relative Liver Wt Females

Model	BMD10	BMDL10	P-Value	AIC

Linear	157	123	0.52	-41

Polynomial	185	83	0.29	-39

Power	188	125	0.31	-39

Spleen Wt Males

====================================================================

   	  Polynomial Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt

 							Wed Aug 06 08:01:17 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

   The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.126025

                            rho =            0   Specified

                         beta_0 =     0.870503

                         beta_1 =  0.000136116

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1

     alpha            1     3.2e-009    -4.1e-009

    beta_0     3.2e-009            1        -0.67

    beta_1    -4.1e-009        -0.67            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.119761        0.0189359           0.0826476            0.156875

         beta_0         0.870503        0.0519428            0.768697            0.972308

         beta_1      0.000136116      0.000496681        -0.000837362          0.00110959

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    20       0.87        0.871          0.1        0.346       -0.00649

 15.5    20       0.88        0.873         0.11        0.346         0.0955

 65.6    20       0.87        0.879         0.14        0.346         -0.122

  198    20        0.9        0.897         0.68        0.346         0.0329

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           44.902731            5     -79.805462

             A2           99.284439            8    -182.568877

             A3           44.902731            5     -79.805462

         fitted           44.890181            3     -83.780363

              R           44.852647            2     -85.705294

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              108.864          6          <.0001

   Test 2              108.763          3          <.0001

   Test 3              108.763          3          <.0001

   Test 4            0.0250993          2          0.9875

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is less than .1.  Consider running a

non-homogeneous variance model

The p-value for Test 3 is less than .1.  You may want to consider a

different variance model

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =         639.53

            BMDL =        84.4008

====================================================================

   	  Polynomial Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt

 							Wed Aug 06 08:06:22 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

   The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.126025

                            rho =            0   Specified

                         beta_0 =     0.874783

                         beta_1 = -0.000121189

                         beta_2 = 1.25015e-006

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1       beta_2

     alpha            1     4.4e-010    -6.9e-011    -8.5e-011

    beta_0     4.4e-010            1        -0.69         0.59

    beta_1    -6.9e-011        -0.69            1        -0.98

    beta_2    -8.5e-011         0.59        -0.98            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.119742        0.0189329           0.0826344             0.15685

         beta_0         0.874783        0.0643098            0.748738             1.00083

         beta_1     -0.000121189       0.00233296         -0.00469371          0.00445133

         beta_2     1.25015e-006     1.10752e-005       -2.04568e-005        2.29572e-005

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    20       0.87        0.875          0.1        0.346        -0.0618

 15.5    20       0.88        0.873         0.11        0.346         0.0878

 65.6    20       0.87        0.872         0.14        0.346        -0.0286

  198    20        0.9          0.9         0.68        0.346         0.0026

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           44.902731            5     -79.805462

             A2           99.284439            8    -182.568877

             A3           44.902731            5     -79.805462

         fitted           44.896552            4     -81.793103

              R           44.852647            2     -85.705294

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              108.864          6          <.0001

   Test 2              108.763          3          <.0001

   Test 3              108.763          3          <.0001

   Test 4            0.0123588          1          0.9115

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is less than .1.  Consider running a

non-homogeneous variance model

The p-value for Test 3 is less than .1.  You may want to consider a

different variance model

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =          317.4

            BMDL =        23.7592

====================================================================

   	  Power Model. (Version: 2.14;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt

 							Wed Aug 06 08:09:26 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

   The form of the response function is:

   Y[dose] = control + slope * dose^power

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   The power is restricted to be greater than or equal to 1

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.126025

                            rho =            0   Specified

                        control =         0.87

                          slope =   0.00306657

                          power =     0.431264

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha      control        slope        power

     alpha            1     3.3e-009    -1.7e-005    -1.7e-005

   control    -7.5e-009            1     -0.00029     8.1e-005

     slope     3.8e-006     -0.00029            1           -1

     power    -3.8e-006     8.1e-005           -1            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha          0.11974        0.0189326           0.0826332            0.156848

        control         0.873333         0.044673            0.785776            0.960891

          slope     3.78513e-031     3.07838e-027       -6.03314e-027         6.0339e-027

          power          12.5608           1537.9            -3001.68              3026.8

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    20       0.87        0.873          0.1        0.346        -0.0431

 15.5    20       0.88        0.873         0.11        0.346         0.0862

 65.6    20       0.87        0.873         0.14        0.346        -0.0431

  198    20        0.9          0.9         0.68        0.346      8.27e-008

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           44.902731            5     -79.805462

             A2           99.284439            8    -182.568877

             A3           44.902731            5     -79.805462

         fitted           44.897163            4     -81.794326

              R           44.852647            2     -85.705294

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              108.864          6          <.0001

   Test 2              108.763          3          <.0001

   Test 3              108.763          3          <.0001

   Test 4             0.011136          1           0.916

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is less than .1.  Consider running a

non-homogeneous variance model

The p-value for Test 3 is less than .1.  You may want to consider a

different variance model

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

               Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD = 217.612

            BMDL = 84.6088

F2B Relative Liver Wt Males

====================================================================

   	  Linear Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 09:49:09 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =      0.14812

                            rho =            0   Specified

                         beta_0 =      5.00476

                         beta_1 =   0.00231011

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1

     alpha            1    -1.7e-010     1.2e-009

    beta_0    -1.7e-010            1        -0.68

    beta_1     1.2e-009        -0.68            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.136086        0.0308175           0.0756853            0.196488

         beta_0          5.00118        0.0804478              4.8435             5.15885

         beta_1       0.00232607      0.000528502          0.00129023          0.00336191

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0     9       5.08            5          0.4        0.369          0.641

   26    10       4.98         5.06         0.39        0.369           -0.7

   92    10       5.22         5.22         0.39        0.369         0.0413

  285    10       5.67         5.66         0.36        0.369         0.0505

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           19.849949            5     -29.699898

             A2           19.905731            8     -23.811463

             A3           19.849949            5     -29.699898

         fitted           19.392062            3     -32.784124

              R           11.528531            2     -19.057061

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              16.7544          6         0.01023

   Test 2             0.111564          3          0.9904

   Test 3             0.111564          3          0.9904

   Test 4             0.915774          2          0.6326

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =        215.005

            BMDL =        152.815

====================================================================

   	  Polynomial Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 09:50:51 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =      0.14812

                            rho =            0   Specified

                         beta_0 =      5.02406

                         beta_1 =   0.00153781

                         beta_2 = 2.58955e-006

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1       beta_2

     alpha            1    -2.2e-008     3.6e-008    -3.6e-008

    beta_0    -2.2e-008            1        -0.72         0.63

    beta_1     3.6e-008        -0.72            1        -0.98

    beta_2    -3.6e-008         0.63        -0.98            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.135805        0.0307537           0.0755286            0.196081

         beta_0          5.01966         0.103357             4.81709             5.22224

         beta_1       0.00161646       0.00255005         -0.00338154          0.00661446

         beta_2      2.3668e-006     8.32101e-006       -1.39421e-005        1.86757e-005

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0     9       5.08         5.02          0.4        0.369          0.491

   26    10       4.98         5.06         0.39        0.369         -0.715

   92    10       5.22         5.19         0.39        0.369          0.271

  285    10       5.67         5.67         0.36        0.369        -0.0223

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           19.849949            5     -29.699898

             A2           19.905731            8     -23.811463

             A3           19.849949            5     -29.699898

         fitted           19.432472            4     -30.864944

              R           11.528531            2     -19.057061

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              16.7544          6         0.01023

   Test 2             0.111564          3          0.9904

   Test 3             0.111564          3          0.9904

   Test 4             0.834954          1          0.3608

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =        231.837

            BMDL =        103.096

====================================================================

   	  Power Model. (Version: 2.14;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 09:52:15 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = control + slope * dose^power

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   The power is restricted to be greater than or equal to 1

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =      0.14812

                            rho =            0   Specified

                        control =         4.98

                          slope =   0.00351618

                          power =     0.933981

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha      control        slope        power

     alpha            1     3.3e-009     1.9e-009    -2.2e-009

   control     3.3e-009            1        -0.65         0.62

     slope     1.9e-009        -0.65            1           -1

     power    -2.2e-009         0.62           -1            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.135522        0.0306898           0.0753715            0.195673

        control          5.02588        0.0979186             4.83396             5.21779

          slope      0.000579886       0.00235882         -0.00404332          0.00520309

          power           1.2419         0.706931           -0.143665             2.62745

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0     9       5.08         5.03          0.4        0.368          0.441

   26    10       4.98         5.06         0.39        0.368         -0.679

   92    10       5.22         5.19         0.39        0.368          0.299

  285    10       5.67         5.67         0.36        0.368        -0.0388

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           19.849949            5     -29.699898

             A2           19.905731            8     -23.811463

             A3           19.849949            5     -29.699898

         fitted           19.473058            4     -30.946115

              R           11.528531            2     -19.057061

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              16.7544          6         0.01023

   Test 2             0.111564          3          0.9904

   Test 3             0.111564          3          0.9904

   Test 4             0.753783          1          0.3853

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

               Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD = 232.078

            BMDL = 154.244

Relative Liver Wt Females

====================================================================

   	  Linear Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 10:44:51 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.082075

                            rho =            0   Specified

                         beta_0 =      5.07781

                         beta_1 =   0.00260235

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1

     alpha            1       9e-011    -9.4e-010

    beta_0       9e-011            1        -0.67

    beta_1    -9.4e-010        -0.67            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha        0.0890665        0.0199159           0.0500321            0.128101

         beta_0          5.07781         0.063588             4.95318             5.20244

         beta_1       0.00260235      0.000423063          0.00177316          0.00343154

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    10       5.26         5.08         0.24        0.298           1.93

   26    10       5.01         5.15         0.23        0.298          -1.44

   92    10       5.23         5.32         0.33        0.298         -0.924

  285    10       5.86         5.82         0.33        0.298          0.429

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           32.109647            5     -54.219293

             A2           33.248386            8     -50.496772

             A3           32.109647            5     -54.219293

         fitted           28.367445            3     -50.734889

              R           15.052602            2     -26.105204

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              36.3916          6          <.0001

   Test 2              2.27748          3          0.5168

   Test 3              2.27748          3          0.5168

   Test 4               7.4844          2          0.0237

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is less than .1.  You may want to try a different

model

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =        195.124

            BMDL =        151.164

====================================================================

   	  Polynomial Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 10:47:56 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.082075

                            rho =            0   Specified

                         beta_0 =      5.16868

                         beta_1 =    -0.001032

                         beta_2 = 1.21861e-005

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1       beta_2

     alpha            1     1.1e-009    -3.9e-011    -5.2e-010

    beta_0     1.1e-009            1        -0.71         0.61

    beta_1    -3.9e-011        -0.71            1        -0.98

    beta_2    -5.2e-010         0.61        -0.98            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha        0.0815686        0.0182393           0.0458202            0.117317

         beta_0          5.16868        0.0771258             5.01751             5.31984

         beta_1        -0.001032        0.0019381         -0.00483062          0.00276662

         beta_2     1.21861e-005     6.35516e-006       -2.69788e-007         2.4642e-005

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    10       5.26         5.17         0.24        0.286           1.01

   26    10       5.01         5.15         0.23        0.286          -1.55

   92    10       5.23         5.18         0.33        0.286          0.588

  285    10       5.86         5.86         0.33        0.286        -0.0484

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           32.109647            5     -54.219293

             A2           33.248386            8     -50.496772

             A3           32.109647            5     -54.219293

         fitted           30.126221            4     -52.252442

              R           15.052602            2     -26.105204

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              36.3916          6          <.0001

   Test 2              2.27748          3          0.5168

   Test 3              2.27748          3          0.5168

   Test 4              3.96685          1          0.0464

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is less than .1.  You may want to try a different

model

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =        252.599

            BMDL =        192.768

====================================================================

   	  Polynomial Model. (Version: 2.12;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Thu Aug 07 10:25:26 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   Signs of the polynomial coefficients are not restricted

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =      0.14812

                            rho =            0   Specified

                         beta_0 =      5.02417

                         beta_1 =   0.00152596

                         beta_2 = 2.63032e-006

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha       beta_0       beta_1       beta_2

     alpha            1    -2.1e-008     3.4e-008    -3.5e-008

    beta_0    -2.1e-008            1        -0.73         0.63

    beta_1     3.4e-008        -0.73            1        -0.98

    beta_2    -3.5e-008         0.63        -0.98            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha         0.135834        0.0307605           0.0755451            0.196124

         beta_0          5.01976          0.10365             4.81661             5.22291

         beta_1       0.00160492       0.00255253         -0.00339795           0.0066078

         beta_2     2.40664e-006      8.3247e-006       -1.39095e-005        1.87228e-005

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0     9       5.08         5.02          0.4        0.369           0.49

 26.4    10       4.98         5.06         0.39        0.369         -0.719

   92    10       5.22         5.19         0.39        0.369          0.276

  285    10       5.67         5.67         0.36        0.369        -0.0226

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           19.849949            5     -29.699898

             A2           19.905731            8     -23.811463

             A3           19.849949            5     -29.699898

         fitted           19.428201            4     -30.856402

              R           11.528531            2     -19.057061

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              16.7544          6         0.01023

   Test 2             0.111564          3          0.9904

   Test 3             0.111564          3          0.9904

   Test 4             0.843496          1          0.3584

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is greater than .1.  The model chosen seems

to adequately describe the data

             Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD =        232.036

            BMDL =        103.192

====================================================================

   	  Power Model. (Version: 2.14;  Date: 02/20/2007)

  	  Input Data File: C:\BMDS\UNSAVED1.(d)

  	  Gnuplot Plotting File:  C:\BMDS\UNSAVED1.plt Wed Aug 06 10:48:47 2008

 ====================================================================

 BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    The form of the response function is:

   Y[dose] = control + slope * dose^power

   Dependent variable = MEAN

   Independent variable = dose

   rho is set to 0

   The power is restricted to be greater than or equal to 1

   A constant variance model is fit

   Total number of dose groups = 4

   Total number of records with missing values = 0

   Maximum number of iterations = 250

   Relative Function Convergence has been set to: 1e-008

   Parameter Convergence has been set to: 1e-008

                  Default Initial Parameter Values

                          alpha =     0.082075

                            rho =            0   Specified

                        control =         5.01

                          slope =  0.000988471

                          power =      1.19537

           Asymptotic Correlation Matrix of Parameter Estimates

           ( *** The model parameter(s)  -rho

                 have been estimated at a boundary point, or have been specified by the user,

                 and do not appear in the correlation matrix )

                  alpha      control        slope        power

     alpha            1     1.1e-009    -1.9e-009     1.9e-009

   control     1.1e-009            1        -0.55         0.54

     slope    -1.9e-009        -0.55            1           -1

     power     1.9e-009         0.54           -1            1

                                 Parameter Estimates

                                                         95.0% Wald Confidence Interval

       Variable         Estimate        Std. Err.     Lower Conf. Limit   Upper Conf. Limit

          alpha        0.0821321        0.0183653           0.0461368            0.118127

        control          5.14238        0.0642091             5.01653             5.26823

          slope     5.11233e-006     3.53688e-005       -6.42092e-005        7.44339e-005

          power          2.09703          1.21652           -0.287307             4.48137

     Table of Data and Estimated Values of Interest

 Dose       N    Obs Mean     Est Mean   Obs Std Dev  Est Std Dev   Scaled Res.

------     ---   --------     --------   -----------  -----------   ----------

    0    10       5.26         5.14         0.24        0.287            1.3

   26    10       5.01         5.15         0.23        0.287          -1.51

   92    10       5.23         5.21         0.33        0.287          0.226

  285    10       5.86         5.86         0.33        0.287        -0.0112

 Model Descriptions for likelihoods calculated

 Model A1:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

 Model A2:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma(i)^2

 Model A3:        Yij = Mu(i) + e(ij)

           Var{e(ij)} = Sigma^2

     Model A3 uses any fixed variance parameters that

     were specified by the user

 Model  R:         Yi = Mu + e(i)

            Var{e(i)} = Sigma^2

                       Likelihoods of Interest

            Model      Log(likelihood)   # Param's      AIC

             A1           32.109647            5     -54.219293

             A2           33.248386            8     -50.496772

             A3           32.109647            5     -54.219293

         fitted           29.988517            4     -51.977034

              R           15.052602            2     -26.105204

                   Explanation of Tests

 Test 1:  Do responses and/or variances differ among Dose levels?

          (A2 vs. R)

 Test 2:  Are Variances Homogeneous? (A1 vs A2)

 Test 3:  Are variances adequately modeled? (A2 vs. A3)

 Test 4:  Does the Model for the Mean Fit? (A3 vs. fitted)

 (Note:  When rho=0 the results of Test 3 and Test 2 will be the same.)

                     Tests of Interest

   Test    -2*log(Likelihood Ratio)  Test df        p-value

   Test 1              36.3916          6          <.0001

   Test 2              2.27748          3          0.5168

   Test 3              2.27748          3          0.5168

   Test 4              4.24226          1         0.03943

The p-value for Test 1 is less than .05.  There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is greater than .1.  A homogeneous variance

model appears to be appropriate here

The p-value for Test 3 is greater than .1.  The modeled variance appears

 to be appropriate here

The p-value for Test 4 is less than .1.  You may want to try a different

model

               Benchmark Dose Computation

Specified effect =           0.1

Risk Type        =     Relative risk

Confidence level =          0.95

             BMD = 242.961

            BMDL = 182.751

Page   PAGE  1  of   NUMPAGES  43


UNITED STATES OF AMERICA

DEPARTMENT OF TRANSPORTATION

OFFICE OF THE SECRETARY

WASHINGTON, DC

Issued by the Department of Transportation on April 26, 2004

   NOTICE OF ACTION TAKEN -- DOCKET OST-2001-10218

________________________________________________________________________
_________________________________

This serves as notice to the public of the action described below, taken
by the Department official indicated (no additional confirming order
will be issued in this matter).

Application of    American Airlines, Inc.    filed   4/5/04  to:

XX Renew exemption under 49 U.S.C. 40109 to provide the following
service:

Scheduled foreign air transportation of persons, property, and mail
between Ft. Lauderdale, Florida, and Caracas, Venezuela.

Applicant rep:  Carl B. Nelson, Jr.<PHONE_NUMBER>    DOT Analyst:
Sylvia Moore<PHONE_NUMBER>

D I S P O S I T I O N

XX  Granted (see below)

The above action was effective when taken:   April 26, 2004, through
April 26, 2006

Action taken by:   Paul L. Gretch, Director

		    Office of International Aviation

XX  The authority granted is consistent with the aviation agreement
between the United States and Venezuela.

Except to the extent exempted or waived, this authority is subject to
the terms, conditions, and limitations indicated:  XX  Holder’s
certificates of public convenience and necessity

	   XX  Standard exemption conditions (attached)

________________________________________________________________________
______________

On the basis of data officially noticeable under Rule 24(g) of the
Department's regulations, we found the applicant qualified to provide
the services authorized.

Under authority assigned by the Department in its regulations, 14 CFR
Part 385, we found that (1) our action was consistent with Department
policy; (2) grant of the exemption authority was consistent with the
public interest; and (3) grant of the authority would not constitute a
major regulatory action under the Energy Policy and Conservation Act of
1975.  To the extent not granted, we denied all requests in the
referenced Docket.  We may amend, modify, or revoke the authority
granted in this Notice at any time without hearing at our discretion.

Persons entitled to petition the Department for review of the action set
forth in this Notice under the Department’s regulations, 14 CFR
§385.30, may file their petitions within seven (7) days after the date
of issuance of this Notice.  This action was effective when taken, and
the filing of a petition for review will not alter such effectiveness.

An electronic version of this document is available on the World Wide
Web at:

http://dms.dot.gov//reports/reports_aviation.asp

U.S. Carrier Exemption Conditions

In the conduct of the operations authorized, the U.S. carrier
applicant(s) shall:

(1)  Hold at all times effective operating authority from the government
of each country served;

(2)  Comply with applicable requirements concerning oversales contained
in 14 CFR 250 (for scheduled operations, if authorized);

(3)  Comply with the requirements for reporting data contained in 14 CFR
241;

(4)  Comply with requirements for minimum insurance coverage, and for
certifying that coverage to the Department, contained in 14 CFR 205;

(5)  Except as specifically exempted or otherwise provided for in a
Department Order, comply with the requirements of 14 CFR 203, concerning
waiver of Warsaw Convention liability limits and defenses;

(6)  Comply with all applicable requirements of the Federal Aviation
Administration and with all applicable U.S. Government requirements
concerning security.  To assure compliance with all applicable U.S.
Government requirements concerning security, the holder shall, before
commencing any new service (including charter flights) to or from a
foreign airport, contact its Principal Security Inspector (PSI) to
advise the PSI of its plans and to find out whether the Transportation
Security Administration has determined that security is adequate to
allow such airport(s) to be served; and

(7)  Comply with such other reasonable terms, conditions, and
limitations required by the public interest as may be prescribed by the
Department of Transportation, with all applicable orders and regulations
of other U.S. agencies and courts, and with all applicable laws of the
United States.

The authority granted shall be effective only during the period when the
holder is in compliance with the conditions imposed above.

											08/2003


[Federal Register Volume 87, Number 109 (Tuesday, June 7, 2022)]
[Notices]
[Pages 34679-34681]
[FR Doc No: 2022-12239]

-----------------------------------------------------------------------

DEPARTMENT OF ENERGY

Federal Energy Regulatory Commission

Combined Notice of Filings #1

    Take notice that the Commission received the following electric
corporate filings:

    Docket Numbers: EC22-69-000.
    Applicants: Broad River Energy LLC, KMC Thermo, LLC, Onward Thermal
Holdings, LLC.
    Description: Joint Application for Authorization Under Section 203
of the Federal Power Act of Broad River Energy LLC, et al.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5430.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: EC22-70-000.
    Applicants: Texpo Power, LP, EnerPenn USA LLC.
    Description: Joint Application for Authorization Under Section 203
of the Federal Power Act of Texpo Power, LP, et al.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5434.
    Comment Date: 5 p.m. ET 6/21/22.

    Take notice that the Commission received the following exempt
wholesale generator filings:

    Docket Numbers: EG22-132-000.
    Applicants: Sheppard Mullin Richter & Hampton LLP.
    Description: Tres City Power submits Request for Commission
Certification of Exempt Wholesale Generator Status.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5057.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: EG22-133-000.
    Applicants: Wolf Tank Storage LLC.
    Description: Wolf Tank Storage LLC submits Request for Commission
Certification of Exempt Wholesale Generator Status.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5058.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: EG22-134-000.
    Applicants: Sheppard Mullin Richter & Hampton LLP.
    Description: Tres Port Power LLC submits Request for Commission
Certification of Exempt Wholesale Generator Status.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5060.
    Comment Date: 5 p.m. ET 6/22/22.

    Take notice that the Commission received the following electric
rate filings:

    Docket Numbers: ER14-1480-001.
    Applicants: KMC Thermo, LLC.
    Description: Compliance filing: Informational Filing Pursuant to
Schedule 2 of the PJM.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5354.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: ER20-1997-001.
    Applicants: Cheyenne Light, Fuel and Power Company.
    Description: Compliance filing: Order No. 864 Supplemental
Compliance Filing to be effective 1/27/2020.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5164.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER21-1555-002.
    Applicants: New Mexico Wind, LLC.
    Description: Compliance filing: Compliance Filing for Live Tariff
Records in ER21-1555 to be effective 3/31/2021.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5074.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1991-000.
    Applicants: New England Power Pool Participants Committee.
    Description: Sec.  205(d) Rate Filing: June 2022 Membership Filing
to be effective 5/1/2022.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5335.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: ER22-1992-000.
    Applicants: Consolidated Edison Company of New York, Inc.
    Description: Sec.  205(d) Rate Filing: PASNY Tariff Value Stack
Comp 5-31-2022 to be effective 6/1/2022.

    Filed Date: 5/31/22.
    Accession Number: 20220531-5352.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: ER22-1993-000.
    Applicants: Louisiana Generating LLC.
    Description: Request to Recover Costs Associated with Acting as a
Local Balancing Authority of Louisiana Generating LLC.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5369.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: ER22-1994-000.
    Applicants: PJM Interconnection, L.L.C.
    Description: Sec.  205(d) Rate Filing: Original ISA, Service
Agreement No. 6473; Queue No. AE1-153 to be effective 5/3/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5044.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1995-000.
    Applicants: Alabama Power Company.
    Description: Sec.  205(d) Rate Filing: Attachment S (APCO) 2022
Updated Depreciation Rates Filing to be effective 1/1/2023.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5054.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1996-000.
    Applicants: Alabama Power Company.
    Description: Sec.  205(d) Rate Filing: Attachment S (SEGCO) 2022
Updated Depreciation Rates Filing to be effective 1/1/2023.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5055.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1997-000.
    Applicants: Southern Electric Generating Company.
    Description: Sec.  205(d) Rate Filing: SEGCO 2022 Updated
Depreciation Rates Filing to be effective 1/1/2023.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5056.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1998-000.
    Applicants: Midcontinent Independent System Operator, Inc.
    Description: Sec.  205(d) Rate Filing: 2022-06-01_SA 2829 Entergy
Arkansas-Pine Bluff Energy 1st Rev GIA (J328 J1425) to be effective 5/
19/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5075.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-1999-000.
    Applicants: Number Three Wind LLC.
    Description: Baseline eTariff Filing: Application for Market-Based
Rate Authorization to be effective 8/1/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5085.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2000-000.
    Applicants: Deseret Generation & Transmission Co-operative, Inc.
    Description: Sec.  205(d) Rate Filing: 2022 RIA Annual Update and
Amend to be effective 7/1/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5094.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2001-000.
    Applicants: Black Hills Power, Inc.
    Description: Sec.  205(d) Rate Filing: Filing of Amended and
Restated Standard LGIA with Fall River Solar, LLC to be effective 6/2/
2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5107.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2002-000.
    Applicants: PJM Interconnection, L.L.C.
    Description: Sec.  205(d) Rate Filing: Amendment to WMPA SA No.
5556; Queue No. AE1-123 to be effective 12/10/2019.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5121.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2003-000.
    Applicants: PJM Interconnection, L.L.C.
    Description: Sec.  205(d) Rate Filing: Original ISA, Service
Agreement No. 6466; Queue No. AE1-040 to be effective 5/22/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5125.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2004-000.
    Applicants: PacifiCorp.
    Description: Compliance filing: OATT Revised LGIP & SGIP Compliance
Filing to be effective 4/1/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5134.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2005-000.
    Applicants: PJM Interconnection, L.L.C.
    Description: Sec.  205(d) Rate Filing: ISA, SA No. 5561; Queue No.
AC1-043/AD1-115 to be effective 5/6/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5157.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2006-000.
    Applicants: Gulf Power Company
    Description: Compliance filing: Order No. 676-J Compliance Filing
to be effective 12/31/9998.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5180.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2007-000.
    Applicants: Duke Energy Florida, LLC, Duke Energy Progress, LLC,
Duke Energy Carolinas, LLC.
    Description: Sec.  205(d) Rate Filing: Duke Energy Florida, LLC
submits tariff filing per 35.13(a)(2)(iii: Revisions to Attachments J
and K to Joint OATT to be effective 8/1/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5225.
    Comment Date: 5 p.m. ET 6/22/22.

    Docket Numbers: ER22-2008-000.
    Applicants: SEPV Sierra, LLC.
    Description: Baseline eTariff Filing: Market-Based Rate Application
to be effective 6/2/2022.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5240.
    Comment Date: 5 p.m. ET 6/22/22.

    Take notice that the Commission received the following qualifying
facility filings:

    Docket Numbers: QF22-681-000.
    Applicants: goCDG Credits 28, LLC.
    Description: Form 556 of goCDG Credits 28, LLC.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5420.
    Comment Date: 5 p.m. ET 6/21/22.

    Docket Numbers: QF22-682-000.
    Applicants: goCDG Credits 100, LLC.
    Description: Form 556 of goCDG Credits 100, LLC.
    Filed Date: 5/31/22.
    Accession Number: 20220531-5422.
    Comment Date: 5 p.m. ET 6/21/22.

    Take notice that the Commission received the following electric
reliability filings:

    Docket Numbers: RR22-3-000.
    Applicants: North American Electric Reliability Corporation.
    Description: North American Electric Reliability Corporation's
Report of Comparisons of Budgeted to Actual Costs for 2021 for NERC and
the Regional Entities.
    Filed Date: 6/1/22.
    Accession Number: 20220601-5063.
    Comment Date: 5 p.m. ET 6/22/22.

    The filings are accessible in the Commission's eLibrary system
(https://elibrary.ferc.gov/idmws/search/fercgensearch.asp) by querying
the docket number.
    Any person desiring to intervene or protest in any of the above
proceedings must file in accordance with Rules 211 and 214 of the
Commission's Regulations (18 CFR 385.211 and 385.214) on or before 5:00
p.m. Eastern time on the specified comment date. Protests may be
considered, but intervention is necessary to become a party to the
proceeding.
    eFiling is encouraged. More detailed information relating to filing

requirements, interventions, protests, service, and qualifying
facilities filings can be found at: http://www.ferc.gov/docs-filing/efiling/filing-req.pdf. For other information, call<PHONE_NUMBER>
(toll free). For TTY, call<PHONE_NUMBER>.

    Dated: June 1, 2022.
Debbie-Anne A. Reese,
Deputy Secretary.
[FR Doc. 2022-12239 Filed 6-6-22; 8:45 am]
BILLING CODE 6717-01-P


[Federal Register: July 1, 2010 (Volume 75, Number 126)]
[Notices]
[Page 38169-38170]
[DOCID:fr01jy10-131]

-----------------------------------------------------------------------

DEPARTMENT OF TRANSPORTATION

Federal Aviation Administration

Notice of Intent To Prepare an Environmental Assessment and
Request for Public Scoping Comments for the Air Tour Management Plan
Program at Petrified Forest National Park

AGENCY: Federal Aviation Administration (FAA).

ACTION: Notice of Intent To Prepare an Environmental Assessment and To
request public scoping comments.

-----------------------------------------------------------------------

SUMMARY: The FAA, with National Park Service (NPS) as a cooperating
agency, has initiated development of an Air Tour Management Plan (ATMP)
for Petrified Forest National Park (Petrified Forest), pursuant to the
National Parks Air Tour Management Act of 2000 (Pub. L. 106-181) and
its implementing regulations (14 CFR Part 136, Subpart B, National
Parks Air Tour Management). The objective of the ATMP is to develop
acceptable and effective measures to mitigate or prevent the
significant adverse impacts, if any, of commercial air tour operations
on the natural resources, cultural resources, and visitor experiences
of a national park unit and any Tribal lands within or abutting the
park. It should be noted that the ATMP has no authorization over other
non-air-tour operations such as military and general aviation
operations. In compliance with the National Environmental Policy Act of
1969 (NEPA) and FAA Order 1050.1E, an Environmental Assessment (EA) is
being prepared.
    In April 2010, the NPS and FAA held a two-day kickoff meeting at
Petrified Forest; minutes may be found at: http://parkplanning.nps.gov/
projectHome.cfm?parkId=88&projectId=30802.
    The purpose of the kickoff meeting was for the FAA and NPS to have
the opportunity to share information regarding environmental and other
issues to consider in the development of an ATMP. Materials presented
at the meeting included information on: park resources; the acoustical
environment at Petrified Forest; current and historical air tour
operations; and representative air tour flight paths. In addition,
Petrified Forest staff provided information regarding sensitive park
resources, Tribal concerns, and tourism patterns.
    The FAA and NPS are now inviting the public, agencies, Tribes, and
other interested parties to provide comments, suggestions, and input on
the scope of issues to be addressed in the environmental process.

DATES: By this notice, the FAA is requesting comments on the scope of
the EA for the ATMP at Petrified Forest. Comments must be submitted by
August 2, 2010.

FOR MORE INFORMATION CONTACT: Keith Lusk--Mailing address: P.O. Box
92007, Los Angeles, California 90009-2007. Telephone:<PHONE_NUMBER>.
Street address: 15000 Aviation Boulevard, Lawndale, California 90261.
    Written comments on the scope of the EA should be submitted
electronically via the electronic public comment form on the NPS
Planning, Environment and Public Comment System at: http://
parkplanning.nps.gov/projectHome.cfm?parkId=88&projectId=30802, or sent
to the mailing address above.

SUPPLEMENTARY INFORMATION: A public scoping packet that describes the
project in greater detail is available at:
     http://parkplanning.nps.gov/
projectHome.cfm?parkId=88&projectId=30802.
     Alpine Public Library.
     Flagstaff City-Coconino Public Library.
     Northern Arizona University Library-Cline Library.
     Gallup Public Library.
     Holbrook Public Library.
     Northland Pioneer College Library.
     Larson Public Memorial Library.
     New Mexico State University Library.
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BILLING CODE 4910-13-P


Listening Session on Tribal Declarations Pilot Guidance 2[nd] Draft
April 5, 2016  -  at Leech Lake Band of Ojibwe, MN

Details were provided to attendees during the L0580 course delivery.

Attendees:
Duane Oothoudt, Tribal EM, Leech Lake Band of Ojibwe, MN,
Mike Keyport, Tribal EM, Grand Portage Band, MI,
Michael Conner, Tribal EM Director, Bois Forte Band of Chippewa Indians, MN,
Roy Holmes, State of Minnesota, Tribal Liaison