# SAR Categories in Support of SNURs for 25 Chemical Substances

EPA Docket: EPA-HQ-OPPT-2009-0922

July 20, 2010

# SAR Acrylates 11/2007

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.2427 (log Kow) - 1.3597

The LC50 is in millimoles per liter (mM/L); N = 21 + 4; and the Coefficient of Determination (R 2 

# ) = 0.8628. To convert the LC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Fish 96-h LC50

y = -0.2427x - 1.3597
R 2 

### = 0.8628 n = 21 + 4 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate the toxicity of acrylates with log Kow values of less than 5.0 and molecular weights less than 1000. Allyl acry lates are expected to be about 30 times more toxic than predicted by this SAR.

OTHER APPLICATIONS: This SAR may be used for polyacrylates with log Kow values less than 5.0 and molecular weights less than 1000.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50) CBI CBI 626 1.8 -1.2 100 -0.80 P96-____ 818-61-1 2-Hydroxyethyl acrylate 116 -0.01 -0.25 -0.21 4.8 -1.38 Hansch & Leo, 1985 DUL 999-61-1 2-Hydroxypropyl acrylate 130 0.3 0.17 0.35 3.26 -1.60 Hansch & Leo, 1985 U.S. EPA, 1991 999-61-1 2-Hydroxypropyl acrylate 130 0.3 0.17 0.35 3.61 -1.56 Hansch & Leo, 1985 DUL 999-61-1 2-Hydroxypropyl acrylate 130 0.3 0.17 0.35 3.1 -1.62 Hansch & Leo, 1985 DUL CBI CBI 186 1.1 0.53 1.71 6.6 -1.45 P04-____ CBI CBI 144 0.83 0.66 4.2 -1.54 P87-____ 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 3.4 -1.40 Hansch C. et al., 1995 Datasheet 140-88-5 Ethyl acrylate 100 1.3 1.2 1.32 2.5 -1.60 Hansch & Leo, 1985 DUL 106-63-8 Isobutyl acrylate 128 2.3 2.1 2.22 2.09 -1.79 Hansch & Leo, 1985 DUL 106-63-8 Isobutyl acrylate 128 2.3 2.1 2.22 2.11 -1.78 Hansch & Leo, 1985 DUL CBI CBI 258 3.5 2.8 2.3 -2.05 P99-____ 3066-71-5 Cyclohexyl acrylate 154 2.8 3 1.48 -2.02 DUL 2499-95-8 Hexyl acrylate 156 3.2 3.4 1.09 -2.16 DUL 2499-95-8 Hexyl acrylate 156 3.2 3.4 1.14 -2.14 DUL CBI CBI 172 4 4.2 2.12 @ 2 5 2.4 -1.86 CBI CBI 105-75-9 Dibutyl fumerate 228 4 4.2 0.76 -2.48 DUL 105-75-9 Dibutyl fumerate 228 4 4.2 0.64 -2.55 DUL 105-75-9 Dibutyl fumerate 228 4 4.2 0.469 -2.69 DUL 105-75-9 Dibutyl fumerate 228 4 4.2 0.684 -2.52 DUL CBI CBI 805 MF 4.3 4.5 -2.25 P00-____ Kow Limit 5 5 -2.65 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: 2156-97-0 Lauryl acrylate 240 6.6 6.13 * DUL

90035-08-8 4-Hydroxy-3-[1,2,3,4- Tetrahydro-3-[4-(4- trifluoromethylbenzyloxy)p henyl]-1-napthyl]coumarin 543 9 8.6 0.07 -3.89 8(e)-15112

90035-08-8 4-Hydroxy-3-[1,2,3,4- Tetrahydro-3-[4-(4- trifluoromethylbenzyloxy)p henyl]-1-napthyl]coumarin 543 9 8.6 0.1 -3.73 8(e)-15112

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Brooke LT, Call DJ, Geiger DL, Northcott CE, and Pi orier SH (eds). 1984-1990. Acute toxicities of organic chemicals to Fathead minnows ( Pimephales promelas )

. Superior, WI: Center for Lake Superior Environmental Studies, University of Wisconsin-Superior. Volume 1-5. [note: the five volumes have different author sequence & publication years; DUL]

Nabholz JV and Platz RD. 1987. Environmental effects of acrylates and methacrylates. I. Category Program Support Document - Generi c SNUR and II. Generic Environmental Hazard Assessment (Addendum to Standard Review of PMN __-___ / ___ ). Washington, DC: Environmental Effects Branch, Health and Envir onmental Review Division (TS-796), Office of Toxic Substances, United States Environmental Protection Agency 20460-0001.

U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC.[DUL]

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

# SAR Acrylates 11/2007

DAPHNID 48-h LC50

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.3226 (log Kow) - 0.773

The LC50 is in millimoles per liter (mM/L); N = 7 + 3; and the Coeffici ent of Determination (R 2 

# ) = 0.7028. To convert the EC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Daphnia 48-h LC50

y = -0.3226x - 0.773
R 2



### = 0.7028 n = 7 + 3 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for ac rylates with log Kow values less than 5.0 and molecular weights less than 1000.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) CBI CBI 626 1.8 -1.2 240 -0.42 P96-____ CBI CBI 144 0.83 0.66 59 -0.39 P87-____ 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 2.6 -1.52 Hansch C. et al., 1995 Drottar, 1995 CBI CBI 258 3.5 2.8 3 -1.93 P99-____ 29590-42-9 Isooctyl acrylate 184 4.4 4.1 1.2 -2.19 Beach, 1990 5888-33-5 Isobornyl acrylate 208 4.1 4.2 0.99 -2.32 8(e)-13952 CBI CBI 805 MF 4.3 38 -1.33 P00-____ Kow Limit 5 5 -2.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: CBI CBI 571 4.7 5.4 4.3 * Unknown L00-____

90035-08-8 4-Hydroxy-3-[1,2,3,4- Tetrahydro-3-[4-(4- trifluoromethylbenzyloxy)p henyl]-1-napthyl]coumarin 543 9 8.6 0.3 -3.26 8(e)-15112

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Beach SA. 1990. Acute toxicity of isooctyl acrylate to Daphnia magna . St. Paul, MN: #M Environmental Laboratory, 3M Company; Toxicity Test Report.

Drottar K.R., Swigert J.P.. 1995. Me thyl acrylate: A 48-hour flow-through acute toxicity test with the cladoceran ( Daphnia magna ). Final Report. Wildlife International. BAAM. Washington D.C.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

# SAR Acrylates 11/2007

GREEN ALGAE 96-h EC50

ESTIMATED TOXICITY: The green algae 96-h EC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.1145 (log Kow) - 1.8295

The EC50 is in millimoles per liter (mM/L); N = 6 + 1; and the Coeffici ent of Determination (R 2 

# ) = 0.1463. To convert the EC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.4 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Algal 96-h EC50

y = -0.1145x - 1.8295
R 2 

### = 0.1463

n = 6 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for ac rylates with log Kow values less than 6.4 and molecular weights less than 1000.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal 96-h EC50 (mg/L) Log Algal 96- h EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal 96-h EC50) CBI CBI 626 1.8 -1.2 2.6 -2.38 P96-____ CBI CBI 144 0.83 0.66 2.5 -1.76 P87-____ 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 4.8 -1.25 Hansch C. et al., 1995 Thompson, 1995 CBI CBI 258 3.5 2.8 0.45 -2.76 P99-____ CBI CBI 374 1.6 4.3 18.5 -1.31 P83-____ CBI CBI 805 MF 4.3 8.5 -1.98 P00-____ Kow Limit 6.4 6.4 -3.43 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Thompson S.G., Swigert J.P.. 1995. Methyl acrylate: a 96-hour toxicity test with the freshwater alga ( Selenastrum capricormutum ). Final report Wildlife International. BAAM, Washington D.C.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

# SAR Acrylates 11/2007

FISH 30-d ChV

ESTIMATED TOXICITY: The fish chronic values (ChV) used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4834 (log Kow) - 2.2111

The ChV is in millimoles per liter (mM/L); N = 2 + 1; and the Coefficient of Determination (R 2 

# ) = 0.9766. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Fish ChV

y = -0.4834x - 2.2111
R 2 

### = 0.9766

n = 2 + 1 

## -7 -5 -3 -1 1 3 5

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0


# Log Kow (EPI)Log Fish ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for ac rylates with log Kow values less than 8.0 and molecular weights less than 1000.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV) 105-75-9 Dibutyl fumerate 228 4 4.2 0.0297 -3.885178398 DUL 818-61-1 2-Hydroxyethyl acrylate 116 -0.006 -0.25 -0.21 0.646 -2.254225471 Hansch & Leo, 1985 DUL Kow Limit 8 8 -6.27 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC.[DUL]

# SAR Acrylates 11/2007

DAPHNID ChV

ESTIMATED TOXICITY: No adequate data were available for the acrylates daphnid chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acut e-to-chronic ratio, and were based on the acute daphnid SAR for acrylates. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4896 (log Kow) - 1.773

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Daphnia ChV

y = -0.4896x - 1.773 n = 0 + 2 

## -8 -6 -4 -2 0 2 4

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV) 0 0 -1.77 1/10 D48 Acrylates SAR Kow Limit 8 8 -5.69 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Acrylates 11/2007

GREEN ALGAE ChV

ESTIMATED TOXICITY: The green algae chronic values (ChV) used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.1958 (log Kow) - 2.2582

The ChV is in millimoles per liter (mM/L); N = 4 + 1; and the Coefficient of Determination (R 2 

# ) = 0.4209. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Algal ChV

y = -0.1958x - 2.2582 n = 4 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal ChV (mg/L) Log Algal ChV (mmol/L) Reference (Meas. Kow) Reference (Algal ChV) CBI CBI 626 1.8 -1.2 1.1 -2.76 P96-____ 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 1.9 -1.66 Hansch C. et al., 1995 Thompson, 1995 CBI CBI 258 3.5 2.8 0.14 -3.27 P99-____ CBI CBI 805 MF 4.3 6.4 -2.10 P00-____ Kow Limit 8 8 -4.38 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Thompson S.G., Swigert J.P.. 1995. Methyl acrylate: a 96-hour toxicity test with the freshwater alga ( Selenastrum capricormutum ). Final report Wildlife International. BAAM, Washington D.C.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Acrylates 11/2007

FISH (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The saltwater fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.1913 (log Kow) - 1.7534

The LC50 is in millimoles per liter (mM/L); N = 1 + 1; and the Coeffici ent of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/L to mg/L, mu ltiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Fish (SW) 96-h LC50

y = -0.1913x - 1.7534 n = 1 + 1 

## -6 -4 -2 0 2 4 6

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) 96-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) 96-h LC50

(mg/L) Log Fish (SW) 96-h

LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish SW 96-h LC50) 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 1.1 -1.89 Hansch C. et al., 1995 Drottar, 1995 Kow Limit 5 5 -2.71 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Drottar K.R., Swigert J.P.. 1995. Me thyl acrylate: A 96-hour flow-through acute toxicity test with the sheepshead minnow ( Cyprinodon variegatus ). Final Report. Wildlife International. BAAM. Washington D.C.

# SAR Acrylates 11/2007

MYSID SHRIMP (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY:

The saltwater mysid shrimp 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were ca lculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.4168 (log Kow) - 1.4261

The LC50 is in millimoles per liter (mM/L); N = 1 + 1; and the Coeffici ent of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/L to mg/L, mu ltiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Mysid (SW) 96-h LC50

y = -0.4168x - 1.4261 n = 1 + 1 

## -6 -4 -2 0 2 4 6

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Mysid (SW) 96-h LC50 (mmol/



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Mysid (SW) 96-h LC50

(mg/L) Log Mysid (SW) 96-h

LC50 (mmol/L) Reference (Meas. Kow) Reference (Mysid SW 96-h LC50) 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 1.6 -1.730378469 Hansch C. et al., 1995 Drottar, 1996 Kow Limit 5 5 -3.51 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Drottar K.R., Swigert J.P.. 1996. Me thyl acrylate: A 96-hour flow-through acute toxicity test with the saltwater mysid ( Mysidopsis bahia ). Final Report. Wildlife International. BAAM. Washington D.C.

# SAR Acrylates 11/2007

FISH (SW) ChV

ESTIMATED TOXICITY: No adequate data were available for the acryla tes saltwater fish chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the acute fish (SW) SAR for acrylates. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.2527 (log Kow) - 2.7087

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Fish (SW) ChV

y = -0.2527x - 2.7087 n = 0 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) ChV (mg/L) Log Fish (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Fish SW ChV) 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 0.11 -2.89 Hansch C. et al., 1995 ACR10; Drottar, 1995 Kow Limit 8 8 -4.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Acrylates 11/2007

MYSID SHRIMP (SW) ChV

ESTIMATED TOXICITY: No adequate data were available for the acrylate s mysid shrimp (SW) chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the Mysid Shrimp (SW) 96-h LC50 SAR for acrylates. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.8748 (log Kow) - 2.0918

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Acrylates, Mysid (SW) ChV

y = -0.8748x - 2.0918 n = 0 + 2 

## -9.50 -7.50 -5.50 -3.50 -1.50 0.50 2.50

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Mysid (SW) ChV (mmol/



# APPLICATION: This SAR may be used to estimate toxicity for acrylates.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Mysid (SW) ChV (mg/L) Log Mysid (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Mysid SW ChV) 96-33-3 Methyl acrylate 86 0.75 0.73 0.8,0.739 0.16 -2.73 Hansch C. et al., 1995 ACR10; Drottar, 1985 Kow Limit 8 8 -9.09 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Aliphatic Amines 8/2008

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.6016 (log Kow) + 0.4479

The LC50 is in millimoles per liter (mM/L); N = 117 + 23; and the Coefficient of Determination (R 2 

# ) = 0.7609. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Fish 96-h LC50

y = -0.6016x + 0.4479
R 2 

### = 0.7609 n = 117 + 23 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: For aliphatic amines with log Kow values greater than 7.0, a test duration of greater than 96 hours may be required for proper expression of toxicity. Al so, if the toxicity value obtained by the use of this equation exceeds the water solubility of t he compound (measured or estimated), mortalities greater than 50% would not be expected in a saturated solution during an exposure period of 96 hours.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50) 100-97-0 Hexamethylenetetramine 140 2.5 -4.2 49800 2.55 DUL

102-71-6 Triethanolamine 149 -1.5 -2.5 -1 11800 1.90 Hansch et al., 1995 DUL CBI CBI 252 -0.9 -1.9 585 0.37 P91-____ 111-42-2 Diethanolamine 105 -1.5 -1.7 -1.43 4710 1.65 Hansch & Leo, 1985 DUL 107-15-3 Ethylenediamine 60 -1.2 -1.6 -2.04 220 0.56 Hansch et al., 1995 DUL 141-43-5 2-Aminoethanol 61 -1.3 -1.6 -1.31 2070 1.53 Hansch & Leo, 1985 DUL 140-31-8 1-(2-Aminoethyl)piperazine 129 -0.6 -1.6 2190 1.23 DUL

103-76-4 1-(2-Hydroxyethyl) piperazine 130 -0.68 -1.6 6410 1.69 DUL

5407-04-5 3-Dimethylaminopropyl chloride hydrochloride 158 3.1 -1.5 133 -0.07 DUL

7209-38-3 1,4-Bis (3-aminopropyl) piperazine 200 -1.4 -1.4 -1.43 3100 1.19 DUL CBI CBI 208 0.09 -1.4 3900 1.27 P00-____

622-40-2 4-(2-Hydroxyethyl) morpholine 131 -0.45 -1.3 2710 1.32 DUL 78-90-0 1,2-Propane diamine 74 -0.91 -1.2 1010 1.14 DUL 78-96-6 Isopropanol amine 75 -0.99 -1.2 -0.96 2520 1.53 Hansch & Leo, 1985 DUL CBI CBI 317 -3.2 -1.2 75 -0.63 P95-____ 109-76-2 1,3-Propane diamine 74 -1.5 -1.1 -1.43 1190 1.21 Hansch et al., 1995 DUL 109-85-3 2-Methoxyethylamine 75 -0.67 -0.91 524 0.84 DUL 110-73-6 2-(Ethylamino) ethanol 89 -0.46 -0.66 1480 1.22 DUL CBI CBI 249 -0.25 -0.6 677 0.43 P95-____ 109-01-3 1-Methylpiperazine 100 -0.099 -0.59 2300 1.36 DUL 110-91-8 Morpholine 87 -0.72 -0.56 -0.86 380 0.64 Hansch & Leo, 1985 Calamari et al., 1980

280-57-9 1,4-Diazabicyclo (2,2,2) octane 112 0.69 -0.49 1730 1.19 DUL 109-07-9 2-Methylpiperazine 100 -0.44 -0.38 2240 1.35 DUL 107-29-9 Acetaldoxime 59 -0.14 -0.21 -0.13 76 0.11 Hansch et al., 1995 DUL 124-40-3 Dimethylamine 45 -0.51 -0.17 -0.38 118 0.42 Hansch & Leo, 1985 Calamari et al., 1980 59-97-2 Tolazoline hydrochloride 197 MF -0.16 354 0.25 DUL 75-04-7 Ethylamine 45 -0.14 -0.15 -0.13 227 0.70 Hansch & Leo, 1985 U.S. EPA, 1990 (ERL-D)

22104-62-7 4-Dimethylamino-3-methyl2-butanone 129 0.34 -0.12 8.5 -1.18 DUL 100-37-8 N,N-Diethylethanolamine 117 0.48 0.05 1780 1.18 DUL CBI CBI 135 0.2 0.15 390 0.46 P91-____ 107-11-9 Allylamine 57 -0.09 0.21 0.03 27 -0.32 Hansch & Leo, 1985 Bridie et al., 1979 141-91-3 2,6-Dimethylmorpholine 115 0.73 0.28 387 0.53 DUL 107-10-8 Propylamine 59 0.39 0.34 0.48 308 0.72 Hansch & Leo, 1985 DUL CBI CBI 238 0 0.41 250 0.02 P91-____ 6921-29-5 Tripropargylamine 131 0.19 0.67 1.27 296 0.35 Hansch et al., 1995 DUL 75-64-9 tert-Butylamine 73 0.57 0.72 0.4 270 0.57 Hansch & Leo, 1985 Calamari et al., 1980 13952-84-6 (+-)-sec-Butylamine 73 0.74 0.76 0.74 275 0.58 Hansch & Leo, 1985 DUL

6948-86-3 N,N-Bis(2,2-diethoxyethyl) methylamine 263 1.4 0.78 637 0.38 DUL

6948-86-3 N,N-Bis(2,2-diethoxyethyl) methylamine 263 1.4 0.78 634 0.38 DUL 109-89-7 Diethylamine 73 0.54 0.81 0.58 855 1.07 Hansch & Leo, 1985 DUL 109-89-7 Diethylamine 73 0.54 0.81 0.58 182 0.40 Hansch & Leo, 1985 Calamari et al., 1980 109-73-9 Butylamine 73 0.92 0.83 0.97 268 0.56 Hansch & Leo, 1985 DUL

96-80-0 2-(Diisopropylamino) ethanol 145 1.1 0.88 201 0.14 DUL 100-64-1 Cyclohexanone oxime 113 1.2 0.91 0.84 208 0.26 TSCATS DUL

105-14-6 5-Diethylamino-2- pentanone 157 0.57 0.94 336 0.33 DUL

54-11-5 (s)-3-Methyl-2-pyrrolidinyl pyridine nicotine 162 1.3 1 1.17 4 -1.61 Hansch & Leo, 1985 Edsall, 1991 65-30-5 Nicotine sulfate 419 MF 1 1.17 12.2 -1.54 Hansch & Leo, 1985 DUL 65-30-5 Nicotine sulfate 419 MF 1 1.17 15.6 -1.43 Hansch & Leo, 1985 DUL 100-46-9 Benzylamine 107 1.1 1.1 1.09 102 -0.02 Hansch & Leo, 1985 U.S. EPA, 1990 (ERL-D) 2759-28-6 1-Benzylpiperazine 176 1.8 1.1 47.4 -0.57 DUL 127-06-0 Acetone oxime 73 0.12 1.2 0.12 558 0.88 Pomona, 1987 DUL

598-74-3 (+-)-1,2- Dimethylpropylamine 87 1.1 1.2 284 0.51 DUL

5813-64-9 2,2-Dimethyl-1- propylamine 87 1.2 1.2 475 0.74 DUL 110-58-7 Amylamine 87 1.5 1.3 1.49 177 0.31 Hansch & Leo, 1985 DUL

34274-04-9 N-(3-Methoxypropyl)-3,4,5- trimethoxybenzylamine 269 0.05 1.3 136 -0.30 DUL 124-02-7 Diallylamine 97 0.63 1.5 1.11 20 -0.69 Hansch & Leo, 1985 Bridie et al., 1979 108-91-8 Cyclohexylamine 99 1.4 1.6 1.49 90 -0.04 Hansch & Leo, 1985 Calamari et al., 1980 108-18-9 Diisopropylamine 101 1.1 1.6 1.4 196 0.29 Hansch & Leo, 1985 Calamari et al., 1980 96-29-7 2-Butanone oxime 87 0.36 1.7 0.63 843 0.99 Chem Inspect Test Inst, 1992 DUL 15673-00-4 3,3-Dimethylbutylamine 101 1.7 1.7 602 0.78 DUL

7250-67-1 1-(2-Chloroethyl) pyrrolidine Hydrochloride 170 1.4 1.7 153 -0.05 DUL 111-26-2 Hexylamine 101 2 1.8 2.06 56.6 -0.25 Hansch & Leo, 1985 DUL

103-83-3 N,N-Dimethylbenzylamine 135 2 1.8 1.98 37.8 -0.55 Hansch & Leo, 1985 DUL 60-13-9 Amphetamine sulfate 369 1.8 1.8 1.76 28.8 -1.11 Hansch & Leo, 1985; Sangste r DUL 80-52-4 1,8-Diamino-p-menthane 170 1.2 1.9 65.3 -0.42 DUL 14321-27-8 N-Ethylbenzylamine 135 2 2 1.8 57.1 -0.37 Sangster, 1993 DUL 111-68-2 n-Heptylamine 115 2.5 2.3 2.57 21.8 -0.72 Hansch & Leo, 1985 DUL 768-94-5 1-Adamantanamine 151 2 2.4 2.44 25 -0.78 Hansch & Leo, 1985 DUL CBI CBI 198 2.7 2.4 3.23 -1.79 P85-____CBI CBI 198 2.7 2.4 6.8 -1.46 P85-____ CBI CBI 198 2.7 2.4 12 -1.22 P85-____ CBI CBI 198 2.7 2.4 10.2 -1.29 P85-____ 107-45-9 tert-Octylamine 129 2.4 2.6 24.6 -0.72 DUL CBI CBI 238 MF 2.6 3.4 -1.85 P__-____ CBI CBI 494 1.2 2.6 5.8 33 -1.18 HPLC P92-____ 693-16-3 1-Methylheptylamine 129 2.8 2.7 5.11 -1.40 DUL 693-16-3 1-Methylheptylamine 129 2.8 2.7 5.28 -1.39 DUL 111-86-4 Octylamine 129 3 2.8 2.9 5.19 -1.40 Sangster, 1993 DUL 111-92-2 Dibutylamine 129 2.7 2.8 2.83 37 -0.54 Hansch & Leo, 1985 Calamari et al., 1980 CBI CBI 212 2.4 2.9 1100 0.72 P93-____ 102-69-2 Tripropylamine 143 2.8 3 2.79 50.9 -0.45 Hansch & Leo, 1985 DUL CBI CBI 200 1.9 3.1 778 0.59 P89-____ 112-20-9 Nonylamine 143 3.6 3.3 2.16 -1.82 DUL

91-65-6 N,NDiethylcyclohexylamine 155 3 3.3 21.4 -0.86 DUL CBI CBI 392 MF 3.71 0.59 -2.82 P87-____ 2016-57-1 n-Decylamine 157 4.1 3.8 1.03 -2.18 U.S. EPA, 1990 (ERL-D) 2016-57-1 n-Decylamine 157 4.1 3.8 1.04 -2.18 DUL CBI CBI 278 4.3 3.8 3.17 4.6 -1.78 Unknown P00-____ 7307-55-3 Undecylamine 171 4.6 4.3 0.21 -2.91 DUL CBI CBI 217 4.9 4.4 0.21 -3.01 P85-____ CBI CBI 217 4.9 4.4 0.66 -2.52 P85-____ CBI CBI 217 4.9 4.4 0.72 -2.48 P85-____ CBI CBI 217 4.9 4.4 3.7 0.65 -2.52 Unknown P96-____ CBI CBI 217 4.9 4.4 3.7 0.6 -2.56 Unknown P96-____ CBI CBI 217 4.9 4.4 3.7 0.2 -3.04 Unknown P96-____ 29873-30-1 N-Decylthioamine 217 4.9 4.4 0.22 -2.99 8(e)-3587 29873-30-1 N-Decylthioamine 217 4.9 4.4 0.7 -2.49 8(e)-3587 29873-30-1 N-Decylthioamine 217 4.9 4.4 0.77 -2.45 8(e)-3587 CBI CBI 228 4.9 4.4 13 -1.24 P94-____ CBI CBI 228 4.9 4.4 39 -0.77 P94-____ CBI CBI 253 4.9 4.4 0.11 -3.36 P85-____ CBI CBI 253 4.9 4.4 0.345 -2.87 P96-____ CBI CBI 253 4.9 4.4 0.38 -2.82 P96-____ CBI CBI 300 3.8 4.5 0.71 -2.63 P91-____ CBI CBI 367 4.1 4.5 2.8 -2.12 P90-____ 143-16-8 Di-n-hexylamine 185 4.8 4.7 0.78 -2.38 DUL

56296-78-7 Fluoxetin hydrochloride 346 4.1 4.7 3.82; 4.05 0.49 -2.85 Unknown; Adlard, M et al., 1995 8(e)-15316 CBI CBI 411 6.8 4.7 0.33 -3.10 P02-____ 124-22-1 Dodecyamine 185 5.2 4.8 0.103 -3.25 DUL

52898-18-7 1,3-Propanediamine, N- 3- (dodecyloxy)propyl - 301 4.1 5 0.033 -3.96 8(e)-14601

NK Hydrogenated cocoamidopropyldiethylami ne-N-oxide 343 3 5.1 0.75 -2.66 8(e)-14655 CBI CBI 940 2.4 5.2 0.28 -3.53 P05-____ 2869-34-3 Tridecylamine 199 5.7 5.3 0.0654 -3.48 DUL CBI CBI 259 5.7 5.3 0.55 -2.67 T94-___

_ 112-18-5 Dimethyl dodecyl amine 213 5.5 5.4 0.84 -2.40 SIDS, 1998 CBI CBI 295 MF 5.7 3.8 100 -0.47 HPLC P00-____ CBI CBI 316 5.7 5.7 4.9 1.466 -2.33 PMN est. P91-____

SAR Data Not Included in Regression Equation: 2706-56-1 2-(2-Aminoethyl) pyridine 122 -0.21 0.02 0.08 

### * Hansch & Leo, 1985 DUL
CBI CBI 341 3.7 4.4 4.4 

### * Unknown P03-____ CBI CBI 481 5.5 6.5 

### * 4.4 

### * -2.04 CBI
CBI CBI 481 5.5 6.5 

### * 13 

### * -1.57 CBI
CBI CBI 1527 7.1 6.7 

### * 2.5 

### * -2.79 P98-____ CBI CBI 1527 7.1 6.7 

### * 2.9 

### * -2.72 P98-____ CBI CBI 509 7.1 6.9 

### * 1 

### * -2.71 CBI
CBI CBI 509 7.1 6.9 

### * 7.9 

### * -1.81 CBI
CBI CBI 377 8.4 7.1 

### * 2.3 

### * -2.21 P00-____ CBI CBI 501 7.1 7.1 

### * 0.13 

### * -3.59 P98-_____ CBI CBI 501 7.1 7.1 

### * 0.28 

### * -3.25 P98-_____

95-38-5 2-(8-Heptadecenyl)-4,5- dihydro-1H-imidazole-1- ethanol 351 7.9 7.5 

### * 0.3 

### * -3.07 8(e)-4252
CBI CBI 439 5.7 7.5 

### * 0.13 

### * -3.53 P97-____ CBI CBI 469 7.9 7.5 

### * 0.45 

### * -3.02 P90-____ CBI CBI 494 8.6 8.1 0.82 -2.78 P05-____ CBI CBI 284 8.6 8.1 

### * 0.44 

### * -2.81 P92-____ CBI CBI 582 MF 8.2 

### * P90-____ CBI CBI 423 8.7 9.1 

### * 0.43 

### * -2.99 P00-____ CBI CBI 961 14.8 9.6 

### * P89-____ CBI CBI 565 14 13 

### * 2.3 

### * -2.39 P91-____ CBI CBI 676 11 13 

### * 0.525 

### * -3.11 P91-____ CBI CBI 1066 16 14 

### * P98-____ CBI CBI 1066 16 14 

### * 4.4 

### * -2.38 P98-____Data Not Included in SAR:

333-18-6 Ethylenediamine dihydrochloride 133 MF -3.4 >100 >-0.12 Ewell et al., 1986 CBI CBI 503 3.3 -0.47 0.2 >2400 >0.68 CBI CBI CBI CBI 503 3.3 -0.47 0.2 >2100 >0.62 CBI CBI CBI CBI 262 0.1 0.35 >500 >0.28 P91-____ CBI CBI 189 0.52 0.86 >100 >-0.39 P05-____ CBI CBI 489 3.3 1.9 >101 >-0.68 P02-____ CBI CBI 451 2 3.8 >99 >-0.66 P93-____ CBI CBI 428 5.6 <0.1 <-3.63 8(e)-_____

_

27136-73-8 2-(Heptadecenyl)-4,5- dihydro-1H-imidazole-1- ethanol 351 7.8 7.5 0.22 to 0.5 -3.2 to -2.85 CBI CBI 284 8.6 8.1 0.56 to 0.75 -2.71 to -2.58 P92-____ * indicates no effects at saturation



# REFERENCES: Bridie AL, Wolff CJM, and Winter M. 1979. The acut e toxicity of some petrochemicals to goldfish. Water Research 13:623-626. [A summary of studi es also listed in the ‘Reference’ section.]

Brooke LT, Call DJ, Geiger DL, Northcott CE, and Piorier SH (eds). 1984-1990 Acute toxicities of organic chemicals to Fathead minnows ( Pimephales promelas )

. Superior, WI: Center for Lake Superior Environmental Studies, University of Wisconsin-Superior. Volume 1-5. [note: the five volumes have different author sequence & publication years]

Calamari D, DaGasso R, Galassi S, Provini A, and Vighi M. 1980. Biodegradation and toxicity of selected amines on aquatic organisms. Chemosphe re 9: 753-762. [A summary of studies also listed in the ‘Reference’ section.]

Edsall, CC. 1991. Acute toxicities to larval Ra inbow trout of represent ative compounds detected in Great Lake fish. Bull. Env. Contam. Toxicol. 46(2):173-178.

Ewell WS, Gorsuch JW, Kringle RO, Robillard KA, and Spiegel RC. 1986. Simultaneous evolution of the acute effects of chemicals on seven aquatic species. Environ. Toxicol. Chem. 5:831-840.

Platz RD, and Nabholz JV. 1990. Generic environme ntal hazard assessment of aliphatic amines. Washington, DC: Environmental Effects Branch, Health and Environmental Review Division (TS796), Office of Toxic Substances, United Stat es Environmental Protection Agency. Unpublished manuscript.

SIAR. 2005. SIDS Initial Assess ment Report. SIAR for the 11 th 

# SIAM. N,N-Dimethyol dodecyamine. Sponsor country: Germany. [SIDS]

U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

# SAR Aliphatic Amines 11/2007

DAPHNID 48-h LC50

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.5119 (log Kow) - 0.7278

The LC50 is in millimoles per liter (mM/L); N = 44 + 15; and the Coefficient of Determination (R 2 

# ) = 0.554. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Daphnia 48-h LC50

y = -0.5119x - 0.7278
R 2 

### = 0.5405 n = 43 + 16 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: For aliphatic amines with log Kow values greater than 5.0, a test duration of greater than 48 hours may be required for proper expression of toxicity. Al so, if the acute toxicity value obtained by the use of this equation exceeds the water solub ility of the compound (measured or estimated), significant mortalities would not be expected in a saturated solution during an exposure period of 48 hours.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) CBI CBI 773 -7.6 -2.4 1.6 -2.68 P95-____ CBI CBI 144 -0.8 -2.2 1760 1.09 P90-____ 111-42-2 Diethanolamine 105 -1.5 -1.7 -1.43 55 -0.28 Hansch & Leo, 1985 Le Blanc, 1980 111-42-2 Diethanolamine 105 -1.5 -1.7 -1.43 131 0.10 Hansch & Leo, 1985 Cowgill et al., 1985 107-15-3 Ethylenediamine 60 -1.2 -1.6 -2.04 26.5 -0.35 Hansch et al., 1995 Van Leeuwen et al., 1985 CBI CBI 317 -3.2 -1.2 1.7 -2.27 P95-____ 74-89-5 Methylamine 31 -0.7 -0.64 -0.57 280 0.96 Hansch & Leo, 1985 Kuhn et al., 1989 CBI CBI 249 -0.25 -0.6 10.5 -1.38 P95-____ 124-40-3 Dimethylamine 45 -0.51 -0.17 -0.38 50 0.05 Hansch & Leo, 1985 Van Leeuwen et al., 1985 CBI CBI 163 0.4 0.05 450 0.44 P03-____ CBI CBI 135 0.2 0.15 230 0.23 P91-____ CBI CBI 3.3 -0.47 0.2 117 1.55 Unknown CBI CBI CBI 205 MF 0.2 51 -0.60 P96-____ CBI CBI 262 0.1 0.35 90 -0.46 P91-____ CBI CBI 143 1.1 0.4 42 -0.53 P91-____ CBI CBI 238 0 0.41 77 -0.49 P91-____ 109-89-7 Diethylamine 73 0.54 0.81 0.58 56 -0.12 Hansch & Leo, 1985 Van Leeuwen et al., 1985 CBI CBI 154 0.37 0.95 46 -0.52 P94-____

54-11-5 (s)-3-Methyl-2-pyrrolidinyl pyridine nicotine 162 1.3 1 1.17 0.2 -2.91 Hansch & Leo, 1985 Smith, 1988 CBI CBI 157 1 1.2 4.3 -1.56 P83-____ CBI CBI 438 MF 2.2 1.18 -2.57 P87-____ CBI CBI 198 2.7 2.4 3.8 -1.72 P85-____ CBI CBI 198 2.7 2.4 4.51 -1.64 P85-____ CBI CBI 494 1.2 2.6 5.8 7.72 -1.81 HPLC P92-____ CBI CBI 173 1.3 2.7 15 -1.06 P88-____ CBI CBI 360 2.8 0.3 -3.08 8(e)-_____ CBI CBI 212 2.4 2.9 21 -1.00 P93-____ CBI CBI 200 1.9 3.1 10 -1.30 P89-____ 54739-18-3 Fluvoxamine 318 3.1 0.84 -2.58 Henry et al., 2004 59729-33-8 Citalopram 324 3.7 3.9 -1.92 Henry et al., 2004 CBI CBI 278 4.3 3.8 3.17 5.2 -1.73 P00-____ 54739-18-3 Paroxetine 329 4 0.58 -2.75 Henry et al., 2004 29873-30-1 N-Decylthioethylamine 217 4.9 4.4 0.045 -3.68 8(e)-3588 29873-30-1 N-Decylthioethylamine 217 4.9 4.4 0.034 -3.80 8(e)-3587 CBI CBI 217 4.9 4.4 3.7 0.03 -3.86 Unknown P85-____ CBI CBI 217 4.9 4.4 3.7 0.05 -3.64 Unknown P85-____ CBI CBI 217 4.9 4.4 3.7 0.03 -3.86 Unknown P96-____ CBI CBI 228 4.9 4.4 7.5 -1.48 P94-____ CBI CBI 253 4.9 4.4 0.033 -3.88 P85-____ CBI CBI 253 4.9 4.4 0.018 -4.15 P96-____

36362-09-1 2-(Decyl thio)-ethanamine hydrochloride 254 4.9 4.4 0.033 -3.89 8(e)-3307 54910-89-3 Fluoxetine 309 4.7 0.51 -2.78 Henry et al., 2004 CBI CBI 411 6.8 4.7 0.17 -3.38 P02-____

SAR Data Not Included in Regression Equation: CBI CBI 341 3.7 4.4 4.4 

### * * Unknown P03-____

NK Hydrogenated cocoamidopropyldiethylami ne-N-oxide 343 3 5.1 

### * 0.96 

### * -2.55 8(e)-14655 79617-96-2 Sertraline 306 5.3 

### * 0.12 

### * -3.41 Henry et al., 2004 112-18-5 Dimethyl dodecyl amine 213 5.5 5.4 

### * 0.083 

### * -3.41 SIDS, 1998 CBI CBI 295 MF 5.7 3.8 

### * 0.012 

### * -4.39 HPLC P00-____ CBI CBI 295 MF 5.7 3.8 

### * 0.51 

### * -2.76 HPLC P00-____ CBI CBI 316 5.7 5.7 4.9 

### * 8.88 

### * -1.55 PMN est. P91-____ CBI CBI 323 5.6 5.7 

### * 27 

### * -1.08 P95-____ CBI CBI 377 8.4 7.1 

### * 0.065 

### * -3.76 P00-____
CBI CBI 439 5.7 7.5 

### * 0.032 

### * -4.14 P97-____ CBI CBI 469 7.9 7.5 

### * 0.23 

### * -3.31 P90-____ CBI CBI 614 11 7.5 

### * 0.13 

### * -3.67 P90-____ CBI CBI 494 8.6 8.1 0.79 *-2.80 P05-____ CBI CBI 423 8.7 9.1 

### * 0.04 

### * -4.02 P00-____ CBI CBI 565 14 13 

### * 0.97 

### * -2.77 P91-____ CBI CBI 676 11 13 

### * 0.55 

### * -3.09 P91-____

Data Not Included in SAR: CBI CBI 189 0.52 0.86 270 0.15 P-05-____

* indicates no effects at saturation



# REFERENCES: Cowgill UM, Takahashi IT, and Applegath SL. 1985. A comparison of the effect of four benchmark chemicals on Daphnia magna and Ceriodaphnia dubia/ affinis tested at two different temperatures. [A summary of studies al so listed in the ‘R eference’ section.]

Ewell WS, Gorsuch JW, Kringle RO, Robillard KA, and Spiegel RC. 1986. Simultaneous evolution of the acute effects of chemicals on seven aquatic species. Environ. Toxicol. Chem. 5:831-840.

# Gersich FM, Millazzo DP, and Voos-Esquivel C. 1988. An invertebrate lif e-cycle study of the toxicity of Daphnia magna Straus. Mammalian and Environmental Toxicology Research Laboratory. Dow Chemical Company. Study ID: ES- DR-0065-5425-6. [A summary of studies also listed in the ‘Reference’ section.]

Henry et al., 2004. Acute and chronic toxicity of fi ve selective serotonin reuptake inhibitors to Ceriodaphnia dubia. Env Tox & Chem 23:2229-2233.

LeBlanc GA. 1980. Acute Toxicity of priority pollutants to water flea ( Daphnia magna) . Bulletin of Environmental Contamination and Toxicology 24:684- 691. [A summary of studies also listed in the ‘Reference’ section.]

Lilius et al., 1995. Toxicity comparison of D. magna and D. pulex . Env Tox & Chem 14:2085- 2088.

Platz RD, and Nabholz JV. 1990. Generic environme ntal hazard assessment of aliphatic amines. Washington, DC: Environmental Effects Branch, Health and Environmental Review Division (TS796), Office of Toxic Substances, United Stat es Environmental Protection Agency. Unpublished manuscript.

Smith SB, Perry CM. 1988. Toxicity of six heterocyclic nitrogen compounds to Daphnia pulex

. Bull. Environ. Contam. Toxicol. 41(4):604-608.

U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

Van Leeuwen CJ, MASS-Diepeveen JL, Niebeek G, Vergouw WHA, Griffioen PS, and LuijkenMW. 1985. Aquatic toxicological aspects of dithiocarbamates and related compounds. I. Shortterm toxicity tests. Aquatic Toxicology 7:145-164. [A summary of studies also listed in the ‘Reference’ section.]

# SAR Aliphatic Amines 8/2008

GREEN ALGAE 96-h EC50

ESTIMATED TOXICITY: The green algae 96-h EC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.3708 (log Kow) -1.3744

The EC50 is in millimoles per liter (mM/L); N = 49 + 10; and the Coefficient of Determination (R 2 

# ) = 0.306. To convert the EC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 7.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Algal 96-h EC50

y = -0.3708x - 1.3744
R 2 

### = 0.306 n = 49 + 10 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 7, or if t he compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal 96-h EC50 (mg/L) Log Algal 96- h EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal 96-h EC50) CBI CBI 773 -7.6 -2.4 0.02 -4.59 P95-____ 107-15-3 Ethylenediamine 60 -1.2 -1.6 -2.04 61 0.01 Hansch et al., 1995 Van Leeuwen et al., 1985 CBI CBI 132 -0.7 -1.5 27 -0.69 P94-____ CBI CBI 317 -3.2 -1.2 0.05 -3.80 P95-____ CBI CBI 329 -0.85 2.2 -2.17 P94-____ CBI CBI 89 -0.6 -0.74 480 0.73 P91-____ CBI CBI 249 -0.25 -0.6 6.2 -1.60 P95-____ CBI CBI 249 -0.25 -0.6 7.3 -1.53 P95-_____ 110-91-8 Morpholine 87 -0.72 -0.56 -0.86 28 -0.49 Hansch & Leo, 1985 Calamari et al., 1980 124-40-3 Dimethylamine 45 -0.52 -0.17 -0.38 30 -0.18 Hansch & Leo, 1985 Van Leeuwen et al., 1985 124-40-3 Dimethylamine 45 -0.52 -0.17 -0.38 9 -0.70 Hansch & Leo, 1985 Calamari et al., 1980 CBI CBI 163 0.4 0.05 0.27 -2.78 P03-____ CBI CBI 135 0.2 0.15 36 -0.57 P91-____ CBI CBI 143 1.1 0.4 16 -0.95 P91-____ CBI CBI 238 0 0.41 38 -0.80 P91-____ CBI CBI 185 0.64 0.71 -2.42 8(e)-____ 75-64-9 tert-Butylamine 73 0.57 0.72 0.4 16 -0.66 Hansch & Leo, 1985 Calamari et al., 1980 13952-84-6 (+-)-sec-Butylamine 73 0.74 0.76 0.74 275 0.58 Hansch & Leo, 1985 8(e)-14540 109-89-7 Diethylamine 73 0.54 0.81 0.58 56 -0.12 Hansch & Leo, 1985 Van Leeuwen et al., 1985 109-89-7 Diethylamine 73 0.54 0.81 0.58 20 -0.56 Hansch & Leo, 1985 Calamari et al., 1980 108-91-8 Cyclohexylamine 99 1.4 1.6 1.49 20 -0.69 Hansch et al., 1995 Calamari et al., 1980 108-18-9 Diisopropylamine 101 1.1 1.6 1.4 20 -0.70 Hansch et al., 1995 Calamari et al., 1980 CBI CBI 438 MF 2.2 0.21 -3.32 P87-____ 98-94-2 Dimethylcyclohexylamine 127 2.1 2.3 0.31 -2.61 8(e)-14542 CBI CBI 161 2.7 2.4 1.04 -2.19 P85-____ CBI CBI 198 2.7 2.4 1 -2.30 P85-____ CBI CBI 592 6.5 2.5 0.14 -3.63 P88-____ CBI CBI 238 MF 2.6 4 -1.77 P91-____ CBI CBI 173 1.3 2.7 1.8 -1.98 P88-____ 111-86-4 Octylamine 129 3 2.8 2.9 0.12 -3.03 Sangster, 1993 8(e)-14541 111-86-4 Octylamine 129 3 2.8 2.9 0.22 -2.77 Sangster, 1993 U.S.EPA, 1990 (ERL-D) 111-92-2 Dibutylamine 129 2.7 2.8 2.8 19 -0.83 Hansch & Leo, 1985 Calamari et al., 1980 CBI CBI 360 2.8 0.114 -3.50 8(e)-____ 102-06-7 N,N'-Diphenyl-guanidine 211 MF 2.9 2.6 -1.91 8(e)-13109 CBI CBI 212 2.4 2.9 0.25 -2.93 P93-____ CBI CBI 487 3.4 3 28 -1.24 P02-____ CBI CBI 200 1.9 3.1 2.9 -1.84 P89-____

49745-95-1 Dobutamine hydrochloride 338 2.5 3.5 0.76 -2.65 8(e)-15346 CBI CBI 278 4.3 3.8 3.17 0.3 -2.97 Unknown P00-____ CBI CBI 228 4.9 4.4 0.06 -3.58 P94-____ CBI CBI 253 4.9 4.4 0.03 -3.93 P85-____ CBI CBI 341 3.7 4.4 4.4 0.14 -3.39 Unknown P03-____ CBI CBI 300 3.8 4.5 0.02 -4.18 P91-____ CBI CBI 411 6.8 4.7 0.1 -3.61 P02-____ CBI CBI 639 3.5 5.2 37 -1.24 P96-____ CBI CBI 940 2.4 5.2 0.33 -3.45 P05-____ 112-18-5 Dimethyl dodecyl amine 213 5.5 5.4 0.007 -4.48 SIDS, 1998 CBI CBI 316 5.7 5.7 4.9 0.038 -3.92 PMN est. P91-____ CBI CBI 323 5.6 5.7 0.01 -4.51 P95-____

SAR Data Not Included in Regression Equation:
CBI CBI 377 8.4 7.1 

### * 0.091 

### * -3.62 P00-____
CBI CBI 439 5.7 7.5 

### * 0.052 

### * -3.93 P97-____
CBI CBI 469 7.9 7.5 

### * 0.006 

### * -4.89 P90-____
CBI CBI 614 11 7.5 

### * 0.23 

### * -3.43 P90-____
CBI CBI 328 7.1 8.1 

### * 0.13 

### * -3.4 P86-____
CBI CBI 582 ` 8.2 

### * P90-____
CBI CBI 423 8.7 9.1 

### * 0.035 

### * -4.08 P00-____
CBI CBI 676 11 13 

### * 1.7 

### * -2.6 P91-____
CBI CBI 737 MF 14 

### * P89-____ CBI CBI 1066 16 14 

### * 0.66 

### * -3.21 P98-____

Data Not Included in SAR: CBI CBI 189 0.52 0.86 18 -1.02 P05-____ CBI CBI 737 MF 14 >10 >-1.87 CBI

* indicates no effects at saturation



# REFERENCES: Calamari D, DaGasso R, Galassi S, Provini A, and Vighi M. 1980. Biodegradation and toxicity of selected amines on aquatic organisms. Chemos phere 9:753-762. [A summary of studies also listed in the ‘Reference’ section.]

Platz RD, and Nabholz JV. 1990. Generic environme ntal hazard assessment of aliphatic amines. Washington, DC: Environmental Effects Branch, Health and Environmental Review Division (TS796), Office of Toxic Substances, United Stat es Environmental Protection Agency. Unpublished manuscript.

# U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 14 00 Pennsylvania Ave., N.W.

Van Leeuwen CJ, Maas-Diepeveen JL, Niebeek G, Vergouw WHA, Griffioen PS, and LuijkenMW. 1985. Aquatic toxicological aspects of dithiocarbamates and related compounds. I. Shortterm toxicity tests. Aquatic Toxicology 7:145-164. [A summary of studies also listed in the ‘Reference’ section.]

# SAR Aliphatic Amines 11/2007

FISH ChV

ESTIMATED TOXICITY: The fish chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5648 (log Kow) - 1.3894

The ChV is in millimoles per liter (mM/L); N = 3; and the Coefficient of Determination (R 2 

# ) = 0.9979. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Fish ChV

y = -0.5648x - 1.3894
R 2 

### = 0.9979 n = 3 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0


# Log Kow (EPI)Log Fish ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV)

54-11-5 (s)-3-Methyl-2-pyrrolidinyl pyridine nicotine 162 1.3 1 1.17 1.8 -1.95 Hansch & Leo, 1985 Passino-Reader, 1995

CBI CBI 253 4.9 4.4 0.03 -3.93 P85-____(Analogue),P96-____

36362-09-1 2-(Decyl thiol) ethyl amine hydrochloride 253 4.9 4.4 0.038 -3.82 8(e)-3305

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Passino-Reader DR, Berlin WH, and Hickey JP. 1995. Chronic bioassays of Rainbow trout fry with compounds representative of contaminants in Great Lakes fish. J. Great Lakes Res. 21:373- 383.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Aliphatic Amines 11/2007

DAPHNID ChV

ESTIMATED TOXICITY: The daphnid chronic values (ChV) used to devel op this SAR were measured and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.0977 (log Kow) - 3.7304

The ChV is in millimoles per liter (mM/L); N =3; and the Coefficient of Determination (R 2 

# ) = 0.9538. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Daphnia ChV

y = -0.0977x - 3.7304
R 2 

### = 0.9538 n = 3 

## -6.00 -4.00 -2.00 0.00 2.00 4.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV) CBI CBI 326 MF 5.4 0.018 -4.26 8(e)-___

_ CBI CBI 253 4.9 4.4 0.018 -4.15 P85-___

_ CBI CBI 253 4.9 4.4 0.017 -4.17 P96-___

_ SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

36362-09-1 2-(Decyl thiol) ethyl amine hydrochloride 253 4.9 4.4 0.013- 0.0248 -4.29 to -4.01 8(e)-3307

* indicates no effects at saturation



# REFERENCES: Platz RD, and Nabholz JV. 1990. Generic environme ntal hazard assessment of aliphatic amines. Washington, DC: Environmental Effects Branch, Health and Environmental Review Division (TS796), Office of Toxic Substances, United Stat es Environmental Protection Agency. Unpublished manuscript. [A summary of studies also listed in the ‘Reference’ section.]

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Aliphatic Amines 11/2007

GREEN ALGAE ChV

ESTIMATED TOXICITY: The green algae chronic values (ChV) used to devel op this SAR were measured and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4862 (log Kow) - 1.5487

The ChV is in millimoles per liter (mM/L); N = 32 + 7; and the Coeffici ent of Determination (R 2 

# ) = 0.5639. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 7.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Algal ChV

y = -0.4862x - 1.5487
R 2 

### = 0.5639 n = 32 + 7 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines with log Kow values less than or equal to 7.0 and molecular weights less than 1000.

LIMITATIONS: If the log Kow value is greater than 7.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal ChV (mg/L) Log Algal ChV (mmol/L) Reference (Meas. Kow) Reference (Algal ChV) CBI CBI 132 -0.7 -1.5 16.7 -0.90 P94-____ CBI CBI 329 -0.85 1.6 -2.31 P94-____ CBI CBI 89 -0.6 -0.74 140 0.20 P91-____ CBI CBI 249 -0.25 -0.6 1.8 -2.14 P95-____ 110-91-8 Morpholine 87 -0.72 -0.56 -0.86 10 -0.94 Hansch & Leo, 1985 Calamari et al., 1980 124-40-3 Dimethylamine 45 -0.52 -0.17 -0.38 2 -1.35 Hansch & Leo, 1985 Calamari et al., 1980 CBI CBI 163 0.48 0.05 0.01 -4.21 P03-____ CBI CBI 135 0.2 0.15 15 -0.95 P91-____ CBI CBI 205 MF 0.2 5 -1.61 P96-____ CBI CBI 143 1.1 0.4 9 -1.20 P91-____ CBI CBI 238 0 0.41 28 -0.93 P91-____ CBI CBI 185 0.64 0.4 -2.67 8(e)-____ 75-64-9 tert-Butylamine 73 0.57 0.72 0.4 2 -1.56 Hansch & Leo, 1985 Calamari et al., 1980 109-89-7 Diethylamine 73 0.54 0.81 0.58 2 -1.56 Hansch & Leo, 1985 Calamari et al., 1980 108-91-8 Cyclohexylamine 99 1.4 1.6 1.49 5 -1.30 Hansch & Leo, 1985 Calamari et al., 1980 108-18-9 Diisopropylamine 101 1.1 1.64 1.4 5 -1.31 Hansch et al., 1995 Calamari et al., 1980 CBI CBI 438 MF 2.2 0.042 -4.02 P87-____ 111-92-2 Dibutylamine 129 2.7 2.8 2.83 2.5 -1.71 Hansch & Leo, 1985 Calamari et al., 1980 111-86-4 Octylamine 129 3 2.8 2.9 0.65 -2.30 Sangster, 1993 Calamari et al., 1980 CBI CBI 212 2.4 2.9 0.24 -2.95 P93-____ CBI CBI 487 3.4 3 4.5 -2.03 P02-____ CBI CBI 200 1.93 3.1 1.6 -2.10 P89-____ CBI CBI 278 4.3 3.8 3.17 0.22 -3.10 Unknown P00-____ CBI CBI 228 4.9 4.4 0.013 -4.24 P94-____ CBI CBI 253 4.9 4.4 0.009 -4.45 P85-____ CBI CBI 341 3.7 4.4 4.4 0.035 -3.99 HPLC P03-____ CBI CBI 300 3.8 4.5 0.017 -4.25 P91-____ CBI CBI 411 6.8 4.7 0.07 -3.77 P02-____ CBI CBI 639 3.5 -1.6 4 -2.20 P96-____ CBI CBI 940 2.4 5.2 0.18 -3.72 P05-____ CBI CBI 316 5.7 5.7 4.9 0.005 -4.80 PMN est. P91-____ CBI CBI 323 5.6 5.7 0.002 -5.21 P95-____

SAR Data Not Included in Regression Equation: CBI CBI 377 8.4 7.1 

### * 0.054 

### * -3.84 P00-____ CBI CBI 439 5.7 7.5 

### * 0.01 

### * -4.64 P97-____ CBI CBI 469 7.9 7.5 

### * 0.002 

### * -5.37 P90-____ CBI CBI 614 11 7.5 

### * 0.1 

### * -3.79 P90-____ CBI CBI 423 8.7 9.1 

### * 0.009 

### * -4.67 P00-____ CBI CBI 676 11 13 

### * 0.44 

### * -3.19 P91-____ CBI CBI 1066 16 14 

### * 0.47 

### * -3.36 P98-____

Data Not Included in SAR: CBI CBI 189 0.52 0.86 4.4 -1.63 P05-____

* indicates no effects at saturation



# REFERENCES: Calamari D, DaGasso R, Galassi S, Provini A, and Vighi M. 1980. Biodegradation and toxicity of selected amines on aquatic org anisms. Chemosphere 9:753-762.

Platz RD, and Nabholz JV. 1990. Generic environme ntal hazard assessment of aliphatic amines. Washington, DC: Environmental Effects Branch, Health and Environmental Review Division (TS796), Office of Toxic Substances, United Stat es Environmental Protection Agency. Unpublished manuscript. [A summary of studies also listed in the ‘Reference’ section.]

U.S. Environmental Protection Agency (USEPA). 1989. Report on alga toxicity tests on selected OTS chemicals. Unpublished preliminary draft. Corvallis Environmental Research La boratory. Corvallis, OR: United States En vironmental Protection Agency.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from data submitted under the “Toxic Substanc e Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Aliphatic Amines 11/2007

FISH (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY: No adequate data were available for the aliphatic amines SAR fish (SW) acute endpoint. Predictions for this endpoint are based on the ali phatic amines SAR for the freshwater fish 96-h LC50 endpoint. The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.5978 (log Kow) + 0.4684

The EC50 is in millimoles per liter (mM/L). To c onvert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Fish (SW) 96-h LC50

F96 Aliphatic Amines SAR Equation y = -0.5978x + 0.4684 

## -6 -4 -2 0 2 4 6

-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0



# Log Kow (EPI)Log Fish (SW) 96-h LC5(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 6.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) 96-h LC50

(mg/L) Log Fish (SW) 96-h

LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish (SW) 96-h LC50) CBI CBI 455 3.4 2 17 -1.43 P93-___

_ SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Aliphatic Amines 11/2007

MYSID SHRIMP (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY:

No adequate data were available for the aliphatic amines SAR mysid (SW) EC50 endpoint. Predictions for this endpoint are based on the a liphatic amines SAR for the freshwater daphnid 48-h endpoint. The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.5224 (log Kow) - 0.7287

The EC50 is in millimoles per lit er (mM/L). To convert the EC50 fr om mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Mysid 48-h EC50

D48 Aliphatic Amines SAR Equation y = -0.5224x - 0.7287 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Mysid 48-h EC50 (mmol/



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 6, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Mysid 48-h LC50 (mg/L) Log Mysid 48

- h LC50 (mmol/L) Reference (Meas. Kow) Reference (Mysid 48-h LC50) CBI CBI 455 3.4 2 2.6 -2.24 P93-___

_ SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Aliphatic Amines 11/2007

GREEN ALGAE (SW) 96-h EC50

ESTIMATED TOXICITY: No adequate data were available for the aliphatic amines SAR green algae (SW) EC50 endpoint. Predictions for this endpoint are based on the aliphatic amines SAR for the freshwater green algae 96-h endpoint. The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.3725 (log Kow) - 1.3828

The EC50 is in millimoles per lit er (mM/L). To convert the EC50 fr om mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 7.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Algal (SW) 96-h EC50

GA96 Aliphatic Amines SAR Equation y = -0.3725x - 1.3828 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal (SW) 96-h EC5(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 7.0, or if the compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal (SW) 96-h EC50

(mg/L) Log Algal (SW) 96-h

EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal (SW) 96-h EC50) CBI CBI 455 3.4 2 0.5 -2.96 P93-___

_ 141-43-5 Monoethanolamine 61 -1.3 -1.6 -1.31 80 0.12 Hansch C. et al., 1995 Roseth S. et al., 1996

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Roseth S, Edvardsson T, Stenersen J. 1996. Compar ison of acute toxicity of process chemicals used in the oil refinery. Toxicol. Chem. 15:1211.

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N. W. (Unpublished test data.)

# SAR Aliphatic Amines 11/2007

FISH (SW) ChV

ESTIMATED TOXICITY: No adequate data were available for the aliphatic amines SAR fish (SW) chronic value (ChV) endpoint. Predictions for this endpoint are based on the aliphatic amines SAR for the freshwater fish ChV endpoint. The SAR equation used to estimate toxicity is:

Log 96-h ChV (mmol/L) = -0.5648 (log Kow) – 1.3894

The Chv is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Fish(SW) ChV

FChV Aliphatic Amines SAR Equation y = -0.5648x - 1.3894 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

REFERENCES:

# SAR Aliphatic Amines 11/2007

MYSID SHRIMP (SW) ChV

ESTIMATED TOXICITY: No adequate data were available for the aliphatic amines SAR mysid (SW) chronic value (ChV) endpoint. Predictions for this endpoint are based on the aliphatic amines SAR for the freshwater daphnid ChV endpoint. The SAR equation us ed to estimate toxicity is:

Log 96-h ChV (mmol/L) = -0.0977 (log Kow) – 3.7304

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Mysid ChV

DChV Aliphatic Amines SAR Equation y = -0.0977x - 3.7304 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Mysid (SW) ChV (mmol/



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

REFERENCES:

# SAR Aliphatic Amines 11/2007

GREEN ALGAE (SW) ChV

No adequate data were available for the aliphatic amines SAR green algae (SW) chronic value (ChV) endpoint. Predictions for this endpoint are based on the aliphatic amines SAR for the freshwater green algae ChV endpoint. The SAR equation used to estimate toxicity is:

Log 96-h ChV (mmol/L) = -0.4731 (log Kow) – 1.597

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 7.0 Maximum MW: 1000

GRAPH:


# SAR for: Aliphatic Amines, Algal (SW) ChV

GAChV Aliphatic Amines SAR Equation y = -0.4731x - 1.597 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal (SW) ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for aliphatic amines.

LIMITATIONS: If the log Kow value is greater than 7, or if t he compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. CLogP Kow SRC log Kow Meas. log Kow Algal (SW) ChV (mg/L) Log Algal (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Algal (SW) ChV) CBI CBI 455 3.4 2 0.37 -3.09 P93-___

_ SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave ., N.W. (Unpublished test data

# SAR Alkoxy Silanes 11/2007

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.4507 (log Kow) - 0.7837

The LC50 is in millimoles per liter (mM/L); N = 3 + 2; and the Coeffici ent of Determination (R 2 

# ) = 0.9542. To convert the LC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Alkoxy Silanes, Fish 96-h LC50

y = -0.4507x - 0.7837
R 2 

### = 0.9542

n = 3 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxy silanes.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50) CBI CBI 222 MF -1.7 213 -0.02 P90-___

_ CBI CBI 222 MF -1.7 200 -0.05 P90-___

_ CBI CBI 263 MF 1.7 13 -1.31 P91-___

_ CBI CBI 328 MF 1.7 5.4 -1.78 P00-___

_ SAR Data Not Included in Regression Equation: CBI CBI 347 MF 6.7 * P93-____ CBI CBI 1067 MF 7.3 * P88-____

Data Not Included in SAR: CBI CBI 307 MF -0.12 >100 >-0.49 P81-____ CBI CBI 278 MF 0.56 >74 >-0.57 CBI CBI CBI 189 0.52 0.86 >100 >-0.39 P-05-____ CBI CBI 206 MF 1 >83 >-0.39 P82-____ CBI CBI 197 MF 2.2 >100 >-0.29 P81-____

* indicates no effects at saturation



# REFERENCES: US EPA Memo, 2003

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Alkoxy Silanes 11/2007

DAPHNID 48-h LC50

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.1509 (log Kow) – 1.0196

The LC50 is in millimoles per liter (mM/L); N = 6 + 2; and the Coeffici ent of Determination (R 2 

# ) = 0.3151. To convert the LC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:



# SAR for: Alkoxy Silane, Daphnia 48-h LC50

y = -0.1509x - 1.0196
R 2 

### = 0.3151

n = 6 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxy silanes.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) CBI CBI 222 MF -1.7 37 -0.78 P90-___

_ CBI CBI 221 MF 0.2 51 -0.64 P96-___

_ 78-62-6 Dimethyldiethoxysilane 148 MF 1.6 0.61 1.25 -2.07 Hansch C, et al, 1995 May Passino DR, Smith SB, 1987 CBI CBI 263 MF 1.7 25 -1.02 P91-_____ CBI CBI 197 MF 2.2 7.6 -1.41 P81-____ CBI CBI 228 MF 4.1 8.6 -1.42 P91-____/ P91-___

_ SAR Data Not Included in Regression Equation: CBI CBI 347 MF 6.7 * P93-____ CBI CBI 1067 MF 7.3 * P88-____

Data Not Included in SAR: CBI CBI 278 MF 0.6 >74 >-0.57 CBI CBI CBI 189 0.52 0.86 270 0.15 P05-____ CBI CBI 328 MF 1.7 >2.0 >-2.21 CBI CBI CBI 206 MF 1 >83 >-0.39 P82-____ CBI CBI 307 MF -0.12 >100 >-0.49 P81-____

* indicates no effects at saturation



# REFERENCES: May Passino DR, Smith SB. 1987. Acute bioassay s and hazard evaluation of representative contaminants detected in Great Lakes fish. Env. Toxicol. Chem. 6:901-907.

US EPA Memo, 2003

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Alkoxy Silanes 11/2007

GREEN ALGAE 96-h EC50

ESTIMATED TOXICITY: The green algae 96-h EC50 values used to develop this SAR were measured, and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.0714 (log Kow) – 2.2481

The EC50 is in millimoles per liter (mM/L); N = 3 + 1; and the Coeffici ent of Determination (R 2 

# ) = 0.4347. To convert the EC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.4 Maximum MW: 1000

GRAPH:


# SAR for: Alkoxy Silanes, Algal 96-h EC50

y = -0.0714x - 2.2481
R 2 

### = 0.4347

n = 3 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxy silanes.

LIMITATIONS: If the log Kow value is greater than 6.4, or if the compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Algal 96-h EC50 (mg/L) Log Algal 96- h EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal 96-h EC50) CBI CBI 222 MF -1.7 0.9 -2.39 P90-___

_ CBI CBI 328 MF 1.7 3.7 -1.95 P00-___

_ CBI CBI 1440 MF 7.3 1.7 -2.93 P88-____

SAR Data Not Included in Regression Equation: CBI CBI 347 MF 6.7 * P93-____

Data Not Included in SAR: CBI CBI 278 MF 0.6 >64 >-0.64 CBI CBI CBI 189 0.52 0.86 18 -1.02 P05-____

* indicates no effects at saturation



# REFERENCES: US EPA Memo, 2003

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Alkoxy Silanes 6/2008

FISH ChV

ESTIMATED TOXICITY: No adequate data were available for the alkoxy silanes fish chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the acute fish SAR for alkoxysilanes. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5608 (log Kow) – 1.7837

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Alkoxy Silanes, Fish ChV

y = -0.5608x - 1.7837 n = 0 + 2 

## -7.00 -5.00 -3.00 -1.00 1.00 3.00 5.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish ChV (mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxysilanes.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV) 1/10 F96 0 0 -1.78 1/10 F96 Alkoxy Silanes SAR Kow Limit 8 8 -6.27 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Alkoxy Silanes 6/2008

DAPHNID ChV

ESTIMATED TOXICITY: No adequate data were available for the Alkoxysilanes daphnid chronic value SAR endpoint. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the acute daphnid SAR for alkoxysilanes. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4576 (log Kow) – 2.0196

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8 Maximum MW: 1000

GRAPH:


# SAR for: Alkoxy Silanes, Daphnia ChV

y = -0.4576x - 2.0196 n = 0 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxysilanes.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV) 1/10 D48 0 0 -2.02 1/10 D48 Alkoxy Silanes SAR Kow Limit 8 8 -5.68 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR: CBI CBI 222 MF -1.7 >1.0 -2.35 P90-___

_

* indicates no effects at saturation



# REFERENCES: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Alkoxy Silanes 11/2007

GREEN ALGAE ChV

ESTIMATED TOXICITY: The green algae chronic values (ChV) used to devel op this SAR were measured and the octanol water partition coefficients (Kow) were calc ulated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.1538 (log Kow) – 1.6957

The ChV is in millimoles per liter (mM/L); N = 7; and the Coefficient of Determination (R 2 

# ) = 0.5215. To convert the ChV from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Alkoxy Silanes, Algal ChV

y = -0.1538x - 1.6957
R 2 

### = 0.5215 n = 7 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for alkoxy silanes.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI) log Kow (M) Algal ChV (mg/L) Log Algal ChV (mmol/L) Reference (Meas. Kow) Reference (Algal ChV) CBI CBI 221 MF 0.2 5 -1.65 P96-___

_

CBI CBI 328 MF 1.7 2.5 -2.12 P00-____

CBI CBI 347 MF 6.7 0.2 -3.24 P93-____

CBI CBI 347 MF 6.7 0.57 -2.78 P93-____

CBI CBI 347 MF 6.7 1.8 -2.29 P93-____

CBI CBI 347 MF 6.7 2.9 -2.08 P93-____ CBI CBI 1440 MF 7.3 0.8 -3.26 P88-___

_ SAR Data Not Included in Regression Equation:

Data Not Included in SAR: CBI CBI 222 MF -1.7 <1.0 <-2.35 P90-___

_ CBI CBI 180 MF -1.7 0.04 -3.65 P92-___

_ CBI CBI 278 MF 0.56 >64 >-0.64 CBI CBI CBI 189 0.52 0.86 4.4 -1.63 P05-____

* indicates no effects at saturation



# REFERENCES: U.S. EPA Memo, 2003

U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Epoxides, Poly 8/3/2006

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: No adequate data were available for the polyepoxides SAR fish acute (96-hour) toxicity endpoint. Predictions for this endpoint are based on the polyepoxides SAR for the freshwater fish 14-d LC50 endpoint. The SAR equation used to estimate toxicity is:

Log 14-d LC50 (mmol/L) = -0.3487 (log Kow) - 1.3539

The LC50 is in millimoles per liter (mM/L) . To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Poly, Fish 96-h LC50

F14-d Polyepoxides SAR Equation y = -0.3487x - 1.3539 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 5, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. log Kow) Reference (Fish 96-h LC50)

Kow Limit 5 5 -2.65 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

000000-00-0 Diglycidyl ether of bisphenol A 340 3.1 3.8 5.3 * * - Bailey and Rhinehart, 1976 CBI CBI 334 4.2 5.1 * * P01-____

CBI CBI 368 4.9 5.5 *1.18 *-2.49 L96-____; P88-____; F48 CBI CBI 609 7.1 7.7 * * P91-____ precurso r

Data Not Included in SAR: 000000-00-0 1,3,5-Triazine-2,4,6(1H,3H, 5 297 MF 1.2 0.457 >77 >-0.59 L00129 8e-11501; inequality

* indicates no effects at saturation



# REFERENCES: Bailey, R.E. and W.L. Rhinehart. 1976. Evaluation of D.E.R. 331, diglycidyl ether of bisphenol-A, in the aquatic environment. R&D Report D0004653. Midland, MI: The Dow Chemical Company.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Epoxides, Poly 8/3/2006

FISH 14-day LC50 (Mortality)

ESTIMATED TOXICITY: The fish 14-day LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 14-d LC50 (mmol/L) = -0.3487 (log Kow) - 1.3539

The LC50 is in millimoles per liter (mM/L); N = 2 + 1; and the Coefficient of Determination (R 2 

# ) = 0.87. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.0 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Poly, Fish 14-d LC50

y = -0.3487x - 1.3539
R 2 

### = 0.87 n = 2 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 14-d LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 6.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 14-d LC50 (mg/L) Log Fish 14-d LC50 (mmol/L) Reference (Meas. log Kow) Reference (Fish 14-d LC50) 1464-53-5 1,3-Butadiene diepoxide 86 -1.8 -0.58 -0.28 2.66 -1.51 Deneer et al., 1988 Deneer et al., 1988 2426-07-5 1,2,7,8-Diepoxyoctane 142 -0.2 1.4 6.64 -1.33 Deneer et al., 1988 Kow Limit 6 6 -3.60 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Deneer, J.W., Sinnige, T.L., Seinen, W., and J.L.M. Hermens. 1988. A quantitative structure-activity relationship for the acute toxicity of some epoxy compounds to the guppy. Aquatic Toxicology. 13: 195-204.

# SAR Epoxides, Poly 8/3/2006

DAPHNID 48-h LC50

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.5144 (log Kow) - 0.1579

The LC50 is in millimoles per liter (mM/L); N = 2 + 3; and the Coefficient of Determination (R 2 

# ) = 0.999. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Poly, Daphnia 48-h LC50

y = -0.5144x - 0.1579
R 2 

### = 0.999 n = 2 + 3 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. log Kow) Reference (Daphnia 48-h LC50) CBI CBI 297 MF 1.2 0.457 46 -0.81 L-00-____ L-00-____ CBI CBI 297 MF 1.2 0.457 54 -0.74 L-00-____ L-00-____ Kow Limit 5 5 -2.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

000000-00-0 Diglycidyl ether of bisphenol A 340 3.1 3.8 5.3 * * - Bailey and Rhinehart, 1976 CBI CBI 334 4.2 5.1 * * P01-____

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Bailey, R.E. and W.L. Rhinehart. 1976. Evaluation of D.E.R. 331, diglycidyl ether of bisphenol-A, in the aquatic environment. R&D Report D0004653. Midland, MI: The Dow Chemical Company.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Epoxides, Poly 7/2008

GREEN ALGAE 96-h EC50

ESTIMATED TOXICITY: No adequate data were available for the polyepoxides SAR green algae toxicityendpoint. Predictions for this endpoint are based on the green algae SAR for monoepoxides. The determined equation used to estimate toxicity is:

Log 48-h EC50 (mmol/L) = -0.6934 (log Kow) + 0.7712

The LC50 is in millimoles per liter (mM/L) . To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.4 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Mono, Algal 96-h EC50

y = -0.6934x + 0.7712
R 2 

## = 0.9458

n = 3 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50(mmol/L)



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 6.4, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

REFERENCES:

# SAR Epoxides, Poly 8/3/2006

FISH ChV

ESTIMATED TOXICITY: No adequate data were available for the polyepoxides fish chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio and were based on the acute 14-day fish SAR for polyepoxides. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4895 (log Kow) – 2.3539

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Poly, Fish ChV

y = -0.4895x - 2.3539 n = 0 + 2



## -8.00 -6.00 -4.00 -2.00 0.00 2.00 4.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0


# Log Kow (EPI)Log Fish ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 8, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. log Kow) Reference (Fish ChV)

1/10 F14-d SAR 0 0 -2.35 1/10 F14-d Polyepoxide SAR Kow Limit 8 8 -6.27 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Epoxides, Poly 8/3/2006

DAPHNID ChV

ESTIMATED TOXICITY: No adequate data were available for the polyepoxides daphnid chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio and were based on the acute daphnid SAR for polyepoxides. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5665 (log Kow) - 1.1579

The ChV is in millimoles per liter (mM/L). To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, Poly, Daphnia ChV

y = -0.5665x - 1.1579 n = 0 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. log Kow) Reference (Daphnia ChV) 1/10 D48 Epoxides, poly 0 0 -1.16 D48 Epoxides, poly Kow Limit 8 8 -5.69 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Epoxides, Poly 7/2008

GREEN ALGAE ChV

ESTIMATED TOXICITY: No adequate data were available for the polyepoxides SAR green algae toxicityendpoint. Predictions for this endpoint are based on the green algae SAR for monoepoxides. The determined equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.6111 (log Kow) + 0.5084

The LC50 is in millimoles per liter (mM/L) . To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Epoxides, mono, Algal ChV

y = -0.6111x + 0.5084 n = 1 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for polyepoxides.

LIMITATIONS: If the log Kow value is greater than 6.4, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

REFERENCES:

# SAR Esters 7/2008

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.5717 (log Kow) + 0.2768

The LC50 is in millimoles per liter (mM/L); N = 81 + 16; and the Coefficient of Determination (R 2 

# ) = 0.786. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the ester.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:


# SAR for: Esters, Fish 96-h LC50

y = -0.5717x + 0.2768
R 2 

### = 0.7848 n = 82 + 16 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50) 97-64-3 Ethyl lactate 118 0.31 -0.18 320 0.43 Bowmer et al. 79-20-9 Methyl acetate 74 0.14 0.37 0.18 320 0.64 Hansch & Leo, 1985 DUL 79-20-9 Methyl acetate 74 0.14 0.37 0.18 399 0.73 Hansch & Leo, 1985 DUL 111-15-9 2-Ethoxyethyl acetate 132 0.68 0.59 41 -0.51 Bailey et al., 1985 111-15-9 2-Ethoxyethyl acetate 132 0.68 0.59 42.1 -0.50 DUL CBI CBI 158 0.27 0.67 0.94 110 -0.16 None given P00-___

_ 138-22-7 Butyl lactate 146 1.4 0.80 75 -0.29 Bowmer et al. 141-78-6 Ethyl acetate 88 0.70 0.90 0.7 230 0.42 Hansch & Leo, 1985 Veith et al (1984)/ DUL 105-53-3 Diethyl malonate 160 1.1 0.90 0.96 11.8 -1.13 Pomona, 1987 DUL 105-53-3 Diethyl malonate 160 1.1 0.90 0.96 15.4 -1.02 Pomona, 1987 DUL 105-53-3 Diethyl malonate 160 1.1 0.90 0.96 17.4 -0.96 Pomona, 1987 DUL CBI CBI 146 1.0 1.0 77 -0.28 P94-_____ CBI CBI 146 1.2 1.1 70 -0.32 P97-____/Analog 109-60-4 Propyl acetate 102 1.2 1.4 1.24 60 -0.23 Hansch & Leo, 1985 DUL 1129-35-7 Methyl 4-cyanobenzoate 161 1.5 1.4 46.8 -0.54 DUL

5292-45-5 Dimethyl-2- nitroterephthalate 239 1.7 1.5 6.52 -1.56 DUL/Veith et al. (1984) 540-88-5 tert-Butyl acetate 116 1.4 1.7 1.76 327 0.45 Hansch et al., 1995 DUL CBI/CBI CBI/CBI 144 0.90 1.7 244 0.23 P93-____/ P93-___

_ 619-50-1 Methyl-p-nitrobenzoate 181 1.9 1.7 1.89 23.8 -0.88 Sotomatsu et al., 1993 DUL 120-61-6 Dimethyl terephthalate 194 2.1 1.7 2.25 14.3 -1.13 Hansch & Leo, 1985 SIDS (2000) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 39 -0.70 Ellington & Floyd, 1997 Staples et. al (1997) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 50 -0.59 Ellington & Floyd, 1997 Staples et. al (1997) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 56 -0.54 Ellington & Floyd, 1997 Staples et. al (1997) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 121 -0.21 Ellington & Floyd, 1997 Staples et. al (1997)/DUL CBI CBI 328 2.2 1.7 5.4 -1.78 P00-___

_ 94-09-7 Ethyl-p-aminobenzoate 165 1.9 1.8 1.86 35.4 -0.67 Hansch & Leo, 1985 DUL 94-09-7 Ethyl-p-aminobenzoate 165 1.9 1.8 1.86 36 -0.66 Hansch & Leo, 1985 DUL

886-86-2 Ethyl 3-aminobenzoate, methanesulfonic acid salt 261 1.9 1.8 79 -0.52 DUL 123-86-4 Butyl acetate 116 1.7 1.8 1.78 18 -0.81 Hansch et al., 1995 DUL

2150-47-2 Methyl-2,4- dihydoxybenzoate 168 1.9 2.1 38.5 -0.64 Veith et al (1984) 5372-81-6 Dimethyl-2-amino 209 2.1 2.1 8.94 -1.37 DUL/Veith et al. (1984) 93-89-0 Ethyl benzoate 150 2.6 2.3 2.64 10.8 -1.14 Hansch & Leo, 1986 DUL

42087-80-9 Methyl-4-chloro-2- nitrobenzoate 216 2.4 2.3 27.7 -0.89 DUL 141-28-6 Diethyl adipate 202 1.8 2.4 16.8 -1.08 DUL 141-28-6 Diethyl adipate 202 1.8 2.4 19.3 -1.02 DUL 1126-46-1 Methyl -p-chlorobenzoate 171 2.8 2.5 2.87 11 -1.19 Pagou & Koutselinis, 1994 DUL 706-14-9 gamma-Decanolactone 170 2.4 2.6 2.72 18 -0.98 Hansch & Leo, 1985 DUL 6283-86-9 2-Ethylhexyl lactate 202 3.4 2.7 32 -0.80 Bowmer et al. 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 12 -1.27 Ellington & Floyd, 1996 Staples et. al (1997) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 16.7 -1.12 Ellington & Floyd, 1996 Staples et. al (1997) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 16.8 -1.12 Ellington & Floyd, 1996 Staples et. al (1997) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 17 -1.12 Ellington & Floyd, 1996 Staples et. al (1997) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 30 -0.87 Ellington & Floyd, 1996 Veith et al. (1984) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 31.8 -0.84 Ellington & Floyd, 1996 Staples et. al (1997)/DUL 142-92-7 Hexyl acetate 144 2.9 2.8 4 -1.56 DUL 142-92-7 Hexyl acetate 144 2.8 2.8 4.4 -1.51 Veith et al (1984) 123-66-0 Ethyl hexanoate 144 2.8 2.8 8.94 -1.21 Veith et al (1984)/ DUL 5464-71-1 Octyl lactate 202 3.5 2.8 24 -0.93 Bowmer et al. 607-81-8 Diethyl benzylmalonate 250 2.9 3.0 2.76 5.43 -1.66 Hansch & Leo, 1985 DUL CBI/CBI CBI/CBI 487 3.4 3.0 20 -1.39 P05-____/P02-____ 118-61-6 Ethyl salicylate 166 3.0 3.1 3 19.6 -0.93 Korenman & Danilov, 1990 Veith et al (1984)

2905-69-3 Methyl-2,5- dichlorobenzoate 205 3.2 3.1 14 -1.17 DUL 141-03-7 Dibutyl succinate 230 3.6 3.4 4.46 -1.71 DUL

000000-00-0 N, Nbis(isopropoxycarbonylmet 307 3.8 3.6 3.2 -1.98 8(e)-12513 CBI CBI 362 3.9 3.8 1.1 -2.52 8(e)-_____/P-90-____

_ 84-62-8 Diphenyl phthalate 318 4.5 4.1 0.08 -3.60 DUL 84-62-8 Diphenyl-1-phthalate 318 4.5 4.1 0.8 -2.60 Veith et al. (1984) 744-45-6 Diphenyl isophthalate 318 5.1 4.1 0.8 -2.60 Veith et al. (1984)

1929-73-3 2,4-D butoxy ethanol ester 321 4.7 4.1 5.6 -1.76 Mount and Stephan, 1967 110-40-7 Diethyl sebacate 258 3.9 4.3 2.7 -1.98 DUL 110-40-7 Diethyl sebacate 258 3.9 4.3 2.73 -1.98 DUL 105-99-7 Dibutyl adipate 258 3.9 4.3 3.64 -1.85 DUL CBI CBI 285 3.7 4.3 4.2 1.6 -2.25 None given 8(e)-____/P91-____ CBI CBI 270 4.5 4.5 1.26 -2.33 P00-___

_ 84-69-5 Diisobutyl phthalate 278 4.4 4.5 4.1 0.9 -2.49 Hansch & Leo, 1985 Staples et. al (1997)/DUL 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.48 -2.76 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.61 -2.66 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.85 -2.51 Ellington & Floyd, 1996 Staples et. al (1997)/DUL 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.9 -2.49 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.92 -2.48 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.1 -2.40 Ellington & Floyd, 1996 DUL/Veith et al. (1984) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.1 -2.40 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.54 -2.26 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.6 -2.24 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 2.2 -2.10 Ellington & Floyd, 1996 Staples et. al (1997) 3126-90-7 Di-n-butyl-m-phthalate 278 5.3 4.6 4.3 0.9 -2.49 Pomona, 1987 Veith et al. (1984) 1962-75-0 Di-n-butyl terephthalate 278 5.3 4.6 5.5 5.53 -1.70 Hansch et al., 1995 DUL 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 0.82 -2.58 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 1.5 -2.32 Ellington & Floyd, 1996 Staples et. al (1997)85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 1.7 -2.26 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 2.1 -2.17 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 3.3 -1.98 Ellington & Floyd, 1996 Staples et. al (1997) Kow Limit 5 5 -2.65 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: CBI CBI 509 3 2.3 2.1 * * None given P91-___

_ CBI CBI 468 1.6 2.8 3 * * None given P95-___

_ CBI CBI 298 3.8 3.9 * * P-90-___

_ CBI CBI 461 4.2 4.2 2.6 * * None given P00-____ CBI CBI 290 5.7 5.1 4.4 * * P91-___

_ CBI/CBI CBI/CBI 252 6.3 5.4 0.043 

### * -3.77 P01-____/L98-____ 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 * DeBruijn et al. 1989 Veith et al. (1984) 137-89-3 Di-n-octyl-m-phthalate 391 9.2 8.4 * * Veith et al. (1984) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 * * Ellington & Floyd, 1996 Veith et al. (1984)/DUL 4654-26-6 Di-n-octyl-p-phthalate 391 9.5 8.5 * * Veith et al. (1984) CBI CBI 368 1.3 0.99 0.6 27 -1.13 None given P93-_____; mixture CBI CBI 644 9.3 12 * * P90-___

_ CBI CBI 595 17 16 * * P91-___

_

84731-63-5 Diisotridecyl dodecanedioate 595 16 16 * * Veith et al. (1984) CBI CBI 525 11 11 * * P-90-____

Data Not Included in SAR: 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 >1.24 >-2.35 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.2-1.8 -2.36 - -2.19 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 >0.78 >-2.6 Ellington & Floyd, 1996 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.1 >-3.53 Ellington & Floyd, 1996 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.11 >-3.48 Ellington & Floyd, 1996 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.2 >-3.22 Ellington & Floyd, 1996 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.24 >-3.14 Ellington & Floyd, 1996 Staples et. al (1997) 27554-26-3 Diisooctyl phthalate 391 8.6 8.4 >0.13 >-3.48 Staples et. al (1997) 27554-26-3 Diisooctyl phthalate 391 8.6 8.4 >0.14 >-3.45 Staples et. al (1997) 27554-26-3 Diisooctyl phthalate 391 8.6 8.4 >0.23 >-3.23 Staples et. al (1997) 27554-26-3 Diisooctyl phthalate 391 8.6 8.4 >0.29 >-3.13 Staples et. al (1997) 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >19.51 >-1.3 DeBruijn et al. 1989 ETFS 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >100 >-0.59 DeBruijn et al. 1989 ETFS 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >100 >-0.59 DeBruijn et al. 1989 ETFS 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >770 >0.29 DeBruijn et al. 1989 ETFS 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >1106.2 >0.45 DeBruijn et al. 1989 ETFS 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.16 >-3.39 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.2 >-3.29 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.32 >-3.09 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.327 >-3.08 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.67 >-2.77 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >0.67 >-2.77 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 Staples et. al (1997) 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >100 >-0.59 Ellington & Floyd, 1996 EPA, 8e-14321 117-84-0 Dioctyl phthalate 391 8.9 8.5 8.1 >19.5 >-1.30 Ellington & Floyd, 1996 Staples et. al (1997)

111381-90-9 (111381-89-6) Di(heptyl,nonyl,undecyl) phthalate 419 9.7 9.4 >0.13 >-3.51 Staples et. al (1997)

111381-90-9 (111381-89-6) Di(heptyl,nonyl,undecyl) phthalate 419 9.7 9.4 >0.17 >-3.39 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 419 9.7 9.4 >0.19 >-3.34 Staples et. al (1997)

111381-90-9 (111381-89-6) Di(heptyl,nonyl,undecyl) phthalate 419 9.7 9.4 >0.21 >-3.30 Staples et. al (1997)

111381-90-9 (111381-89-6) Di(heptyl,nonyl,undecyl) phthalate 419 9.7 9.4 >0.23 >-3.26 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 425 9.7 9.4 >0.1 >-3.63 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 425 9.7 9.4 >0.14 >-3.48 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 425 9.7 9.4 >0.16 >-3.42 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 10.7 10.4 >0.37 >-3.08 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 10.7 10.4 >0.47 >-2.98 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 10.7 10.4 >0.62 >-2.86 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 10.7 10.4 >1 >-2.65 Staples et. al (1997) 3648-20-2 Di-undecyl phthalate 475 12 11.5 >0.22 >-3.33 Staples et. al (1997) 3648-20-2 Di-undecyl phthalate 475 12 11.5 >0.73 >-2.81 Staples et. al (1997) 3648-20-2 Di-undecyl phthalate 475 12 11.5 >0.74 >-2.81 Staples et. al (1997) 3648-20-2 Di-undecyl phthalate 475 12 11.5 >1.3 >-2.56 Staples et. al (1997) 3648-20-2 Di-undecyl phthalate 475 12 11.5 >1.4 >-2.53 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 13.5 >0.12 >-3.65 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 13.5 >0.14 >-3.58 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 13.5 >0.15 >-3.55 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 13.5 >0.26 >-3.31 Staples et. al (1997)

* indicates no effects at saturation

# REFERENCES: Bowmer CT, Hooftman RN, Hanstveit AO, Venderbosch PWM, Van der Hoeven N. 1998. The ecotoxicity and the biodegradability of lactic acid, alkyl lactate esters and lactate salts. Chemosphere 37(7):1317-1333.

Brooke LT, Call DJ, Geiger DL, Northcott CE, and Piorier SH (eds). 1984-1990. Acute toxicities of organic chemicals to Fathead minnows ( Pimephales promelas )

. Superior, WI: Center for Lake Superior Environmental Studies, University of Wisconsin-Superior. Volume 1-5. [note: the five volumes have different author sequence & publication years; DUL]

Mount and Stephan.1967. A method establishing acceptable toxicant limits for fishmalathion and the butoxyethanol ester of 2,4-D. Trans. Amer. Fish. Soc. 96 (2) 185 - 193

SIAR. 2005. SIDS Initial Assessment Report. SIAR for the 11 th 

# SIAM. Dimethyl terephthalate. Sponsor country: United States.

Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USE PA). 1990. Summary of structure-activity data files: University of Wisconsin-Super ior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC. [DUL]

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

Veith GD, DeFoe D, and Knuth M. 1984. Structure-activity relationships for screening organic chemicals for potential ecotoxicity effects. Drug Metabolism Reviews 15 (7): 1295 - 1303.

# SAR Esters 11/2007

FISH 14-d LC50 (Mortality)

ESTIMATED TOXICITY: The fish 14-d LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h (mmol/L) = - 1.223 (log Kow) + 3.7379

The LC50 is in millimoles per liter (mM/L); N = 1 + 1; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the ester.

Maximum K ow 

# : 6.0 Maximum MW: 1000

GRAPH:


# SAR for: Esters, Fish 14-d LC50

y = -1.223x + 3.7379 n = 1 + 1 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 14-d LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

# LIMITATIONS: If the log Kow value is greater than 6.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 14-d LC50 (mg/L) Log Fish 14-d LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 14-d LC50) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 2.3 -2.13 Ellington & Floyd, 1996 Staples et. al (1997) Kow Limit 6 6 -3.60 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

# SAR Esters 11/2007

DAPHNID 48-h LC50

ESTIMATED TOXICITY:

The daphnid 48-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.6277 (log Kow) + 0.7017

The LC50 is in millimoles per liter (mM/L); N = 40 + 21; and the Coefficient of Determination (R 2 

# ) = 0.7985. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the ester.

Maximum K ow 

# : 5.0 Maximum MW: 1000

GRAPH:



# SAR for: Esters, Daphnia 48-h LC50

y = -0.6277x + 0.7017
R 2 

### = 0.7985 n = 40 + 21 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



## Log Kow (EPI)Log Daphnia 48-h LC50 (mmol/



# APPLICATIONS: This SAR may be used to estimate toxicity for the following esters. 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates, derived from aliphatic alcohols and phenols.

# LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) Methyl lactate 104 -0.22 -0.67 749 0.86 Bowmer et al. Methyl lactate 104 -0.22 -0.67 780 0.88 Bowmer et al. Ethyl lactate 118 0.33 -0.18 560 0.68 Bowmer et al. Ethyl lactate 118 0.33 -0.18 683 0.76 Bowmer et al. Isopropyl lactate 132 0.62 0.23 802 0.78 Bowmer et al. n-Propyl lactate 132 0.84 0.31 413 0.50 Bowmer et al. n-Propyl lactate 132 0.84 0.31 423 0.51 Bowmer et al. CBI 158 0.27 0.67 0.94 63 -0.40 None given P-00-____

Isobutyl lactate 146 1.2 0.73 395 0.43 Bowmer et al. Butyl lactate 146 1.4 0.80 320 0.34 Bowmer et al. Butyl lactate 146 1.4 0.80 423 0.46 Bowmer et al. CBI 146 1.0 1.0 500 0.53 P94-____

_ CBI 146 1.2 1.1 1000 0.84 P97-____/Analog

Isoamyl or Isopentyl lactate 160 1.8 1.2 193 0.08 Bowmer et al. Pentyl lactate 160 1.9 1.3 238 0.17 Bowmer et al. Dimethyl terephthalate 194 2.1 1.7 2.3 30.4 -0.80 Hansch & Leo, 1985 Datasheet Dimethyl phthalate 194 1.5 1.7 1.6 45.9 -0.63 Ellington & Floyd, 1997 Staples et. al (1997) 2-Ethylhexyl lactate 202 3.4 2.7 83 -0.39 Bowmer et al. Diethyl phthalate 222 2.5 2.7 2.4 86 -0.41 Ellington & Floyd, 1996 Staples et. al (1997) Diethyl phthalate 222 2.5 2.7 2.4 90 -0.39 Ellington & Floyd, 1996 Nabholz (1987) Octyl lactate 202 3.5 2.8 37 -0.74 Bowmer et al. Octyl lactate 202 3.5 2.8 45 -0.65 Bowmer et al. CBI 286 4.0 3.3 0.018 -4.20 X97-____ N, N- 307 3.8 3.6 3.2 -1.98 8(e)-12513 CBI 362 3.9 3.8 0.28 -3.11 8(e)-____/P-90-___

_ CBI 184 3.6 4.0 1.1 -2.22 P92-____/ 8(e)-___

_ CBI 244 4.8 4.3 3.3 -1.87 P92-___

_ CBI 285 3.7 4.3 4.2 3.32 -1.93 None given 8(e)-____/P91-____ Dibutyl phthalate 278 4.7 4.6 4.5 3 -1.97 Ellington & Floyd, 1996 Staples et. al (1997) Dibutyl phthalate 278 4.7 4.6 4.5 3.4 -1.91 Ellington & Floyd, 1996 Nabholz (1987) Dibutyl phthalate 278 4.7 4.6 4.5 3.7 -1.88 Ellington & Floyd, 1996 Staples et. al (1997) Dibutyl phthalate 278 4.7 4.6 4.5 5.2 -1.73 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 1 -2.49 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 1.6 -2.29 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 1.7 -2.26 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 1.8 -2.24 Ellington & Floyd, 1996 Staples et. al (1997) Butyl-benzyl phthalate 312 4.8 4.8 4.7 1.83 -2.23 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 2.4 -2.11 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 3.7 -1.93 Ellington & Floyd, 1996 Nabholz (1987) Butyl-benzyl phthalate 312 4.8 4.8 4.7 3.7 -1.93 Ellington & Floyd, 1996 Staples et. al (1997) Kow Limit 5 5 -2.73 NO Cutoff NO SAR

t Included in Regression Equation: CBI 468 1.6 2.8 3 * * None given P-95-____ CBI 298 3.8 3.9 * * P-90-____ CBI 252 6.3 5.4 * * P01-____ CBI 284 5.4 5.5 4.7 2.7 -2.02 None given P95-____ Butyl 2-ethylhexyl phthalat e 334 6.6 6.5 * Nabholz (1987) Dihexyl phthalate 335 6.8 6.6 * Nabholz (1987)Diisooctyl phthalate 390 8.6 8.4 * Nabholz (1987) Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 * DeBruijn et al. 1989 Nabholz (1987)/ Staples et. al (1 9 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 *4.69 *3.26 DeBruijn et al. 1989 ETFSDi-(n-hexyl, n-octyl, ndecyl)- phthalate 390 8.9 8.5 * Nabholz (1987) Di-(n-octyl)-phthalate 391 8.9 8.5 * Nabholz (1987) Di-(heptyl, nonyl, undecyl)- phthalate 419 9.7 9.4 * Nabholz (1987) Diisononyl phthalate 419 9.7 9.4 * Nabholz (1987) Diisodecyl phthalate 447 11 10 * Nabholz (1987) CBI 525 11 11 * * P-90-____ Diundecyl phthalate 475 12 12 * Nabholz (1987) Ditridecyl phthalate 531 14 13 * Nabholz (1987) CBI 290 5.7 - 4.4 * * None given P-91-_____ CBI 455 - - * * P-90-____/T-89-___

_
CBI 509 (n=1) >= 3.0 - 2.1 * * None given P-91-_____

u ded in SAR: Dimethyl phthalate 194 1.5 1.7 >52 >-0.57 Nabholz (1987)

Warfarin 308 2.9 2.2 2.6 0.288 -3.03 Sangster, 1994 Lilius et al., 1995; 24-hour study duration. CBI 487 3.4 3 >90 >-0.73 P05-____/P02-____ Butyl-benzyl phthalate 312 4.8 4.8 >0.96 >-2.51 Staples et. al (1997) Butyl (2-ethylhexyl) phthalate 334 6.6 6.5 >0.07 >-3.68 Staples et. al (1997) Dihexyl phthalate 335 6.8 6.6 >0.18 >-3.27 Staples et. al (1997) Diisoctyl phthalate 390 8.6 8.4 >0.16 >-3.39 Staples et. al (1997) Di-(2-ethylhexyl) phthalate 391 8.6 8.4 >0.16 >-3.39 Staples et. al (1997) Di-(2-ethylhexyl) phthalate 391 8.6 8.4 >1 >-2.59 Staples et. al (1997)Di-(n-hexyl, n-octyl, ndecyl) phthalate 390 8.9 8.5 >0.33 >-3.07 Staples et. al (1997) Dioctyl phthalate 391 8.9 8.5 >10 >-1.59 Staples et. al (1997) Di-(heptyl, nonyl, undecyl)- phthalate 419 9.7 9.4 >0.04 >-4.02 Staples et. al (1997) Diisononyl phthalate 419 9.7 9.4 >0.06 >-3.84 Staples et. al (1997) Diisononyl phthalate 419 9.7 9.4 >1 >-2.62 Staples et. al (1997) Diisodecyl phthalate 447 11 10 >0.02 >-4.35 Staples et. al (1997) Diisodecyl phthalate 447 11 10 >1 >-2.65 Staples et. al (1997) Diundecyl phthalate 475 12 12 >0.02 >-4.38 Staples et. al (1997) Ditridecyl phthalate 531 14 13 >0.05 >-4.03 Staples et. al (1997) Ditridecyl phthalate 531 14 13 >1 >-2.73 Staples et. al (1997)

* indicates no effects at saturation



# REFERENCES: Bowmer CT, Hooftman RN, Hanstveit AO, Venderbosch PWM, Van der Hoeven N. 1998. The ecotoxicity and the biodegradability of lactic acid, alkyl lactate esters and lactate salts. Chemosphere 37(7):1317-1333.

Nabholz JV. 1987. The acute and chronic toxicity of dialkyl phthalate esters to daphnids. Interagency memorandum to “Whom it may c oncern”. Washington DC: Office of Toxic Substances, Environmental Effects Branch, Health and Environmental Review Division (TS-796), United States Environmental Protection Agency, 20460-0001.

Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Esters 11/2007

GREEN ALGAE 96-h EC50 (Growth)

ESTIMATED TOXICITY:

The green algae 96-h EC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.6744 log (Kow) + 0.4247

The EC50 is in millimoles per liter (mM/L); N = 20 + 6; and the Coefficient of Determination (R 2 

# ) = 0.8426. To convert the EC50 from mM/L to mg/L, multiply by the molecular weight of the ester.

Maximum K ow 

# : 6.4 Maximum MW: 1000

GRAPH:


# SAR for: Esters, Algal 96-h EC50

y = -0.6744x + 0.4247
R 2 

### = 0.8426 n = 20 + 6



## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50 (mmol/L



# APPLICATIONS: This SAR may be used to estimate toxicity for the following esters. 5. Acetates 6. Benzoates 7. Dicarboxylic aliphatics 8. Phthalates, derived from aliphatic alcohols and phenols.

LIMITATIONS: If the log Kow value is greater than 6.4, or if the compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal 96-h EC50 (mg/L) Log Algal 96- h EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal 96-h EC50) 97-64-3 Ethyl lactate 118 0.33 -0.18 2300 1.29 Bowmer et al. 617-51-6 Isopropyl lactate 132 0.62 0.23 180 0.13 Bowmer et al. CBI CBI 158 0.27 0.67 0.94 16 -0.99 None given P00-____ 585-24-0/ 68166-83-6/ 77027-84-0 Isobutyl lactate 146 1.2 0.73 64 -0.36 Bowmer et al. 138-22-7 Butyl lactate 146 1.4 0.80 329 0.35 Bowmer et al. 19329-89-6 Isoamyl or Isopentyl lactate 160 1.8 1.2 41 -0.59 Bowmer et al. 6382-06-5 Pentyl lactate 160 1.9 1.3 46 -0.54 Bowmer et al. 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 313 0.21 Ellington & Floyd, 1997 Staples et. al (1997) CBI CBI 328 1.7 3.7 -1.95 P00-____ 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 85.6 -0.41 Ellington & Floyd, 1996 Staples et. al (1997) 5464-71-1 Octyl lactate 202 3.5 2.8 7.6 -1.42 Bowmer et al. CBI CBI 487 3.4 3.0 28 -1.24 P02-____ CBI CBI 487 3.4 3.0 42 -1.06 P05-____/P02-____ CBI CBI 362 3.8 3.9 1.4 -2.41 8(e)-____/P-90-____ CBI CBI 461 MF 4.2 2.6 0.48 -2.98 None given P-00-_____ CBI CBI 244 4.8 4.3 0.4 -2.79 P92-____ CBI CBI 285 3.7 4.3 4.2 0.41 -2.84 None given 8(e)-____/P91-____ 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.4 -2.89 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.6 -2.72 Ellington & Floyd, 1996 Staples et. al (1997) 110-33-8 Dihexyl adipate 315 6.0 6.3 0.038 -3.92 8(e)-9618 Kow Limit 6.4 6.4 -3.43 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

CBI CBI 468 1.6 2.8 2.96 @25C, pH5.7 * * None given P-95-____ 103-09-3 2-Ethylhexyl acetate 172 3.7 3.7 * * Datasheet CBI CBI 252 6.3 5.4 * * P01-____ CBI CBI 284 5.4 5.5 4.7 * * None given P-95-____ CBI CBI 262 6.7 5.6 6.64 * * H P L C P90-____

Data Not Included in SAR: 84-66-2 Diethyl phthalate 222 2.5 2.9 >100 >-0.346 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 >13 >1.33 Staples et. al (1997)

* indicates no effects at saturation



# REFERENCES: Bowmer CT, Hooftman RN, Hanstveit AO, Venderbosch PWM, Van der Hoeven N. 1998. The ecotoxicity and the biodegradability of lactic acid, alkyl lactate esters and lactate salts. Chemosphere 37(7):1317-1333.Confidential Business Information

Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Esters 11/2007

FISH 32/33-d ChV

ESTIMATED TOXICITY: The fish chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.6762 log Kow - 0.5608

The ChV is in millimoles per liter (mM/L); N = 3 + 3; and the Coefficient of Determination (R 2 

# ) = 0.876. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

GRAPH:


# SAR for: Esters, Fish ChV

y = -0.6762x - 0.5608
R 2



### = 0.876 n = 3 + 3 

## -7.00 -5.00 -3.00 -1.00 1.00 3.00 5.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0


# Log Kow (EPI)Log Fish ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

# LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV) 79-20-9 Methyl acetate 74 0.18 0.37 0.18 72.1 -0.01 Hansch & Leo, 1985 DUL 105-53-3 Diethyl malonate 160 1.1 0.9 0.96 0.76 -2.32 Pomona, 1987 USEPA, 1991/ DUL 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.22 -3.15 Ellington & Floyd, 1996 Staples et. al (1997) Kow Limit 8 8 -6.27 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: CBI CBI 262 6.7 5.6 6.64 * * H P L C P90-____ 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 *31.8 *1.1 DeBruijn et al. 1989 ETFS

Data Not Included in SAR: 141-78-6 Ethyl acetate 88 0.71 0.86 0.73 < 9.65 <-0.96 Hansch & Leo, 1985 DUL

1929-73-3 2,4-D butoxy ethanol ester 321 4.7 4.1 0.67 -2.68 Mount and Stephan, 1967; incorrect duration. 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >0.5 >-2.89 DeBruijn et al. 1989 ETFS

* indicates no effects at saturation



# REFERENCES:Mount and Stephan.1967. A method establishing acceptable toxicant limits for fishmalathion and the butoxyethanol ester of 2,4-D. Trans. Amer. Fish. Soc. 96 (2) 185 - 193 Mount and Stephan, 1967

Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USE PA). 1990. Summary of structure-activity data files: University of Wisconsin-Super ior (UWS) and ORD Environmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC. [DUL]

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Esters 11/2007

DAPHNID 21-d ChV

ESTIMATED TOXICITY: The daphnid ChV values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.7395 log Kow + 0.7253

The ChV is in millimoles per liter (mM/L); N = 13 + 11; and the Coefficient of Determination (R 2 

# ) = 0.8578. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1,000

GRAPH:


# SAR for: Esters, Daphnia ChV

y = -0.7395x + 0.7253
R 2 

## = 0.8578 n = 13 + 11 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 14.9 -1.11 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 38.4 -0.76 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.14 -3.30 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 3126-90-7 Di-n-butyl-iso phthalate 278 5.3 4.6 0.15 -3.27 Nabholz (1987) 84-72-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.32 -2.94 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 84-72-2 Dibutyl phthalate 278 4.7 4.6 4.5 1 -2.44 Ellington & Floyd, 1996 Nabholz (1987) 84-72-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.4 -2.30 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 84-72-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.55 -2.25 Ellington & Floyd, 1996 Staples et. al (1997) 84-72-2 Dibutyl phthalate 278 4.7 4.6 4.5 1.5 -2.27 Ellington & Floyd, 1996 Nabholz (1987) 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.44 -2.85 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.63 -2.69 Ellington & Floyd, 1996 Nabholz (1987)/ Staples et. al (1 9

85-69-8 Butyl (2-ethylhexyl) phthalate 334 6.6 6.5 0.088 -3.58 Staples et. al (1997) Kow Limit 8 8 -5.69 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

111381-90-9 (111381-89-6) Di(heptyl,nonyl,undecyl) phthalate 419 9.7 9.4 * * Nabholz (1987) 117-81-7 Di-(2-ethylhexyl) phthalate 391 8.6 8.4 * * Nabholz (1987) 117-84-0 Dioctyl phthalate 391 8.9 8.5 * * Nabholz (1987) 119-06-2 Ditridecyl phthalate 531 14 13 * * Nabholz (1987) 123-79-5 Dioctyl adipate 371 8.1 8.3 35 -1.03 8(e)-9781 CBI CBI 262 6.7 5.6 6.64 * * H P L C P90-____ 25724-58-7 (68515-51-5) Di-(n-hexyl, n-octyl, ndecyl)- phthalate 390 8.9 8.5 * * Nabholz (1987) 26761-40-0 Diisodecyl phthalate 447 11 10 * * Nabholz (1987) 27554-26-3 Diisooctyl phthalate 390 8.6 8.4 * * Nabholz (1987) 28553-12-0 Diisononyl phthalate 419 9.7 9.4 * * Nabholz (1987) CBI CBI 547 12 12 * * P-94-____ 3648-20-2 Diundecyl phthalate 475 12 12 * * Nabholz (1987) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 * * Ellington & Floyd, 1996 Nabholz (1987) 85-69-8 Butyl 2-ethylhexyl phthalat e 334 6.6 6.5 * * Nabholz (1987)

Data Not Included in SAR: 117-81-7 Di-(2-ethylhexyl)-phthalate 391 8.6 8.4 7.6 >0.0856 >-3.66 DeBruijn et al. 1989 ETFS

* indicates no effects at saturation



# REFERENCES: Nabholz JV, 1987. The acute and chronic toxicity of dialkyl phthalate esters to daphnids Interagency memorandum to “Whom it may concern”. Washington, DC: Office of Toxic Substances, Environmental Effects Branch, Health and Environmental Review Division (TS-796), United States Environmental Protection Agency, 20460-0001.

Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Esters 11/2007

GREEN ALGAE ChV

ESTIMATED TOXICITY: The green algae chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5331 (log Kow) - 0.4564

The ChV is in millimoles per liter (mM/L); N = 13 + 5; and the Coefficient of Determination (R 2 

# ) = 0.721. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1,000

GRAPH:
SAR for: Esters, Algal ChV

y = -0.5331x - 0.4564
R 2 

### = 0.721 n = 13 + 5 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



## Log Kow (EPI)Log Algal ChV (mmol/L



# APPLICATIONS: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal ChV (mg/L) Log Algal ChV (mmol/L) Reference (Meas. Kow) Reference (Algal ChV) 97-64-3 Ethyl lactate 118 0.33 -0.18 320 0.43 Bowmer et al. CBI CBI 158 0.27 0.67 0.94 2.5 -1.80 None given P-00-____ 138-22-7 Butyl lactate 146 1.4 0.8 100 -0.16 Bowmer et al. 6382-06-5 Pentyl lactate 160 1.9 1.3 11 -1.16 Bowmer et al. CBI CBI 328 1.7 2.5 -2.12 P00-____ 5464-71-1 Octyl lactate 202 3.5 2.8 3.2 -1.80 Bowmer et al. CBI CBI 487 3.4 3 4.5 -2.03 P02-____ CBI CBI 487 3.4 3.0 7 -1.84 P05-____/P02-____ 103-09-3 2-Ethylhexyl acetate 172 3.7 3.7 15 -1.06 Datasheet CBI CBI 362 3.9 3.8 0.11 -3.52 8(e)-____/P-90-____ CBI CBI 461 MF 4.2 2.6 0.27 -3.23 None given P-00-____ CBI CBI 244 4.8 4.3 0.3 -2.91 P92-____ CBI CBI 285 3.7 4.3 4.2 0.39 -2.86 None given P91-____ Kow Limit 8 8 -4.38 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: CBI CBI 468 1.6 2.8 3 * * None given P95-____ CBI CBI 252 6.3 5.4 * * P01-____ CBI CBI 284 5.4 5.5 4.7 * * None given P95-____ CBI CBI 262 6.7 5.6 6.64 * * H P L C P90-____

Data Not Included in SAR: 617-51-6 Isopropyl lactate 132 0.62 0.23 <100 <-0.12 Bowmer et al. 585-24-0/ 68166-83-6/ 77027-84-0 Isobutyl lactate 146 1.3 0.69 <32 <-0.66 Bowmer et al. 585-24-0/ 68166-83-6/ 77027-84-0 Isobutyl lactate 146 1.3 0.73 <32 Bowmer et al.

19329-89-6 Isoamyl or Isopentyl lactate 160 1.8 1.2 <10 <-1.2 Bowmer et al.

* indicates no effects at saturation



# REFERENCES: Bowmer CT, Hooftman RN, Hanstveit AO, Venderbosch PWM, Van der Hoeven N. 1998. The ecotoxicity and the biodegradability of lactic acid, alkyl lactate esters and lactate salts. Chemosphere 37(7):1317-1333.Confidential Business InformationConfidential Business Information

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Esters 11/2007

FISH (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The saltwater fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = - 0.6157 (log Kow) + 0.5406

The LC50 is in millimoles per liter (mM/L); N = 6 + 3; and the Coefficient of Determination (R 2 

# ) = 0.9013. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5 Maximum MW: 1,000

GRAPH:



# SAR for: Esters, Fish (SW) 96-h LC50

y = -0.6157x + 0.5406
R 2 

### = 0.9013

n = 6 + 3 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) 96-h LC50 (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS:

# If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) 96-h LC50

(mg/L) Log Fish (SW) 96-h

LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish SW 96-h LC50) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 29 -0.83 Ellington & Floyd, 1996 Staples et al. (1997) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 57.31 -0.53 Ellington & Floyd, 1996 Zaroogian et al. (1985) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 29.979 -0.87 Ellington & Floyd, 1996 Zaroogian et al. (1985) 84-66-2 Diethyl phthalate 222 2.5 2.7 2.4 29 -0.88 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 0.51 -2.79 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 4.7 3 -2.02 Ellington & Floyd, 1996 Staples et al. (1997) Kow Limit 5 5 -2.71 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: 51630-58-1 Fenvalerate 420 6.8 6.8 6.2 0.004 -5.02 Hansch & Leo, 1985 Zaroogian et al., 1985 52645-53-1 Permethrin 391 7.1 7.4 6.5 0.068 -3.76 Hansch & Leo, 1985 Zaroogian et al., 1985

Data Not Included in SAR: 131-11-3 Dimethyl phthalate 194 1.5 1.7 100-115 -0.29 - -0.23 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 >0.6 >-2.67 Staples et. al (1997) 85-68-7 Butylbenzyl phthalate 312 4.8 4.8 >0.68 >-2.66 Staples et. al (1997) 85-69-8 Butyl 2-ethylhexyl phthalat e 334 6.6 6.5 >1.36 >-2.39 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.78 >-2.63 Ellington & Floyd, 1996 Staples et. al (1997) 27554-26-3 Diisooctyl phthalate 390 8.6 8.4 >0.48 >-2.91 Staples et. al (1997) 117-81-7 Di-(2-ethylhexyl) phthalate 391 8.6 8.4 8.1 >0.17 >-3.36 DeBruijn et al. 1989 Staples et. al (1997) 25724-58-7 (68515-51-5) Di-(n-hexyl, n-octyl, ndecyl)- phthalate 390 8.9 8.5 >0.37 >-3.02 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 419 9.7 9.4 >0.52 >-2.91 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 11 10 >0.47 >-2.98 Staples et. al (1997) 3648-20-2 Diundecyl phthalate 475 12 12 >0.22 >-3.33 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 14 >0.65 >-2.91 Staples et. al (1997)

* indicates no effects at saturation



# REFERENCES: Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

Zaroogian G, JF Heltshe and M Johnson. 1985. Estimation of toxicity to marine species with structure activity models developed to estimate toxicity to freshwater fish. Aquatic Toxicology, 6:251-270.

# SAR Esters 11/2007

MYSID SHRIMP (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The saltwater mysid shrimp 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = - 0.8003 (log Kow) + 0.8931

The LC50 is in millimoles per liter (mM/L); N = 4 + 2; and the Coefficient of Determination (R 2 

# ) = 0.9433. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5 Maximum MW: 1,000

GRAPH:


# SAR for: Esters, Mysid (SW) 96-h LC50

y = -0.8003x + 0.8931
R 2 

### = 0.9433

n = 4 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

# LIMITATIONS: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Mysid (SW) Inv 96-h LC50 (mg/L) Log Mysid (SW) Inv 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Mysid SW Inv 96-h LC50) 131-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 68.6 -0.45 Ellington & Floyd, 1996 Staples et. al (1997) 84-66-2 Diethyl phthalate 222 2.5 2.7 4.5 10.3 -1.33 Ellington & Floyd, 1996 Staples et. al (1997) 84-74-2 Dibutyl phthalate 278 4.7 4.6 4.5 0.5 -2.75 Ellington & Floyd, 1996 Staples et. al (1997) 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.9 -2.54 Ellington & Floyd, 1996 Staples et. al (1997) Kow Limit 5 5 -3.51 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: 51630-58-1 Fenvalerate 420 6.8 6.8 6.2 0.0001 -6.62 Hansch et al., 1995 Zaroogian et al., 1985

Data Not Included in SAR: 85-69-8 Butyl 2-ethylhexyl phthalat e 334 6.6 6.5 >0.5 >-2.82 Staples et. al (1997) 84-75-3 Dihexyl phthalate 335 6.8 6.6 6.8 >0.32 >-3.02 Ellington & Floyd, 1996 Staples et. al (1997) 103-23-1 Di(2-ethylhexyl) adipate 371 7.9 8.1 > 0.23 >-3.2 8(e)-10258 27554-26-3 Diisooctyl phthalate 390 8.6 8.4 >0.55 >-2.85 Staples et. al (1997) 117-81-7 Di-(2-ethylhexyl) phthalate 391 8.6 8.4 7.6 >0.37 >-3.02 DeBruijn et al. 1989 Staples et. al (1997) 25724-58-7 Di-(n-hexyl, n-octyl, n- 390 8.9 8.5 >0.26 >-3.18 Staples et. al (1997) 28553-12-0 Diisononyl phthalate 419 9.7 9.4 >0.39 >-3.03 Staples et. al (1997) 26761-40-0 Diisodecyl phthalate 447 11 10 >0.08 >-3.75 Staples et. al (1997) 3648-20-2 Diundecyl phthalate 475 12 12 >0.29 >-3.21 Staples et. al (1997) 119-06-2 Ditridecyl phthalate 531 14 14 >0.8 >-2.81 Staples et. al (1997)

* indicates no effects at saturation



# REFERENCES: Staple CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

Zaroogian G, JF Heltshe and M Johnson. 1985. Estimation of toxicity to marine species with structure activity models developed to estimate toxicity to freshwater fish. Aquatic Toxicology. 6:251-270.

# SAR Esters 11/2007

FISH (SW) ChV

ESTIMATED TOXICITY: The fish (SW) chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = - 0.5338 (log Kow) - 0.4594

The ChV is in millimoles per liter (mM/L); N = 0 + 2; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8 Maximum MW: 1,000

GRAPH:



# SAR for: Esters, Fish (SW) ChV

y = -0.5338x - 0.4594 n = 0 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) ChV (mmol/L



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS:

# If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) ChV (mg/L) Log Fish (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Fish SW ChV) 0 0 -0.46 1/10 F96 (SW) Esters SAR Kow Limit 8 8 -4.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES:

# SAR Esters 11/2007

MYSID SHRIMP (SW) ChV

ESTIMATED TOXICITY: The saltwater mysid shrimp ChV values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -1.7097 (log Kow) + 4.5873

The ChV is in millimoles per liter (mM/L); N = 1 + 1; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8 Maximum MW: 1000

GRAPH:



# SAR for: Class, Mysid (SW) ChV

y = -1.7097x + 4.5873 n = 1 + 1 

## -10.00

-8.00 -6.00 -4.00 -2.00 0.00 2.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Mysid (SW) ChV (mmol/



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS:

# If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Mysid (SW) ChV (mg/L) Log Mysid (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Mysid SW ChV) 85-68-7 Butyl-benzyl phthalate 312 4.8 4.8 4.7 0.075 -3.62 Ellington & Floyd, 1999 Staples et. al (1997) Kow Limit 8 8 -9.09 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Staples CA, Adams W, Parkerton TF, Gorsuch JW, Biddinger GR, Reinert KH. 1997. Aquatic toxicity of eighteen phthalate esters . Environmental Toxicology and Chemistry, 16 (5): 875-891.

# SAR Esters 11/2007

EARTHWORM 14-d LC50 (Mortality)

ESTIMATED TOXICITY: The earthworm 14-d LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.3224 (log Kow) + 1.76

The LC50 is in millimoles per kilogram dry weight soil (mM/kg dry weight); N = 1+ 1; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/kg to mg/kg, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6 Maximum MW: 1000

GRAPH:



# SAR for: Esters, Earthworm 14-d LC50

y = -0.3224x + 1.76 n = 1 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Earthworm 14-d LC5(mmol/kg)



# APPLICATION: This SAR may be used to estimate toxicity for the following esters: 1. Acetates 2. Benzoates 3. Dicarboxylic aliphatics 4. Phthalates derived from aliphatic alcohols and phenol.

LIMITATIONS: If the log Kow value is greater than 6.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# DATA:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Earthworm LC50 (mg/kg) Log Earthworm

LC50 (mmol/kg) Reference (Meas. Kow) Reference Earthworm (LC50) 113-11-3 Dimethyl phthalate 194 1.5 1.7 1.6 3160 1.21 Ellington & Floyd, 1996 Neuhauser et al., 1985 Kow Limit 6 6 -0.17 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation: CBI CBI 468 1.6 2.8 3 * * None given P-95-____

Data Not Included in SAR:

* indicates no effects at saturation



# REFERENCES: Neuhauser, E.F., Loehr, R.C., Malecki, M.R., Milligan, D.L. and Durkin, P.R. 1985. The toxicity of selected organic chemicals to the earthworm Eisenia fetida . Journal of Environmental Quality 14: 383-388.

# SAR Phenols, Poly 12/2007

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the co mputer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.585 (log Kow) + 0.1437

The LC50 is in millimoles per liter (mM/L); N = 12 + 12; and the Coefficient of Determination (R 2 

# ) = 0.7274. To convert the LC50 from mM/L to mg/L, mult iply by the molecular weight of the compound.

Maximum K ow 

# : 7.0 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Fish 96-h LC50

y = -0.585x + 0.1437
R 2 

# = 0.7274 n = 12 + 12 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 7.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

# Data:

CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96- h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50)

1965-09-9 4,4'-Dihydroxydiphenyl Ether 202 3.1 3.1 5.22 -1.59 DUL

1965-09-9 4,4'-Dihydroxydiphenyl Ether 202 3.1 3.1 6.39 -1.50 DUL 80-05-7 Bisphenol A 228 3.7 3.6 3.32 4.6 -1.70 Hansch & Leo, 1985 Alexander et al., 1988 80-05-7 Bisphenol A 228 3.7 3.6 3.32 4.7 -1.69 Hansch & Leo, 1985 Alexander et al., 1988 CBI CBI 322 3.4 3.6 1.5 -2.33 P89-____

97-23-4 2,2'-Methylene bis(4- chlorophenol) 269 4.3 4.3 4.26 0.31 -2.94 Hansch & Leo, 1985 DUL

CBI CBI 246 4.4 4.4 4.41 @ 23C, pH 6.4) 0.91 -2.43 P88-____ CBI CBI 270 5.1 5 0.54 -2.70 8(e)-____

NK 3-(2H-Benzotriazol-2-yl)- 1',1',1'-tris(4- hydroxyphenyl)ethane 423 6.6 5.3 0.16 -3.42 8(e)-13307

NK 3-(2H-Benzotriazol-2-yl)- 1',1',1'-tris(4- hydroxyphenyl)ethane 423 6.6 5.3 0.35 -3.08 8(e)-13307

79-95-8 4,4'-Isopropylidene bis(2,6- dichlorophenol 366 6 6.2 1.33 -2.44 DUL

70-30-4 2,2'-Methylene bis(3,4,6- trichlorophenol 407 7.1 6.9 7.54 0.021 -4.29 Hansch, C. et al., 1995 DUL

SAR Data Not Included in Regression Equation:

CBI CBI 485 6.5 5.7 >4.19 @ 25C, pH6.4 

### * Unknown P98-____ CBI CBI 411 6.8 6.5 3.3 

### * P92-____

CBI CBI 527 7.4 6.7 >4.23 @ 18C 

### * P91-____ CBI CBI 425 7.2 7 

### * P92-____ CBI CBI 544 6.8 7.2 

### * 0.4 

### * -3.13 8(e)-____ CBI CBI 544 6.8 7.2 

### * 0.51 

### * -3.03 8(e)-____
CBI CBI 553 8 7.6 1.9 

### * Unknown P91-____ CBI CBI 630 10 7.6 

### * P01-____ CBI CBI 635 6.3 8.1 

### * 50 

### * -1.1 P99-____ CBI CBI 520 11 11 

### * 4.1 

### * -2.10 P95-____
CBI CBI 658 MF 12 

### * P87-____ CBI CBI 744 21 21 

### * P91-____ CBI CBI 806 22 22 >6.6 

### * HPLC P94-____

Data Not Included in SAR: 80-05-7 Bisphenol A 228 3.7 3.6 3.32 3 to 3.5 -1.88 to -1.81 Hansch & Leo, 1985 Soc. Plastics Ind. Inc., 1984 80-05-7 Bisphenol A 228 3.7 3.6 3.32 4 to 6 -1.76 to -1.58 Hansch & Leo, 1985 Alexander, 1984

* indicates no effects at saturation



# References: Alexander HM. 1984. Bisphenol A biochemical oxygen demand (BOD) and fish toxicity data. Internal letter to L.M. Thomka, Dow Chemic al Co. TSCA 4(A) submission, Fiche No. OTS0509952, Doc. No. 40- 8486010, U.S. EPA, Washington, DC.

Alexander HC, Dill DC, Smith LW, Guiney PD, and Do rn P. 1988. Bisphenol A: Acute aquatic toxicity. Environ. Toxicol. Chem. 7:19-26.

Brooke LT, Call DJ, Geiger DL, Northcott CE, and Pior ier SH (eds). 1984-1990 Acute toxicities of organic chemicals to Fathead minnows ( Pimephales promelas )

. Superior, WI: Center for Lake Superior Environmental Studies, University of Wisconsin-Superior. Volume 1-5. [note: the five volumes have different author sequence & publication years; DUL]

Soc. Plastics Ind., Inc.. 1984. Appendix D. Environmen tal Effects Of Bisphenol A. TSCA 4(A) submission, Fiche No. OTS0509967. Doc. No. 40-8486028, U.S. EPA, OTS, Washington, D.C..

# U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD En vironmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC. [DUL]

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Phenols, Poly 12/2007

DAPHNID 48-h LC50

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using the co mputer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.7683 (log Kow) + 1.1595

The LC50 is in millimoles per liter (mM/L); N = 5 + 8; and the Coeffici ent of Determination (R 2 

# ) = 0.8648. To convert the LC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.5 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Daphnia 48-h LC50

y = -0.7683x + 1.1595
R 2 

## = 0.8648

n = 5 + 8 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50(mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 5.5, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) 80-05-7 Bisphenol A 228 3.7 3.6 3.32 3.9 -1.77 Hansch & Leo, 1985 Soc. Plastics Ind. Inc., 1984 80-05-7 Bisphenol A 228 3.7 3.6 3.32 10.2 -1.35 Hansch & Leo, 1985 Alexander et al., 1988 CBI CBI 322 3.4 3.6 4.78 -1.83 P89-____

CBI CBI 246 4.4 4.4 4.41 @ 23C, pH 6.4) 2.56 -1.98 P88-____

NK 3-(2H-Benzotriazol-2-yl)- 1',1',1'-tris(4- hydroxyphenyl)ethane 423 6.6 5.3 0.4 -3.02 8(e)-13307

SAR Data Not Included in Regression Equation: 70-30-4 Hexachlorophene 407 7.1 6.9 7.54 0.198 -3.31 Hansch, C. et al., 1995 Lilius et al., 1995 70-30-4 Hexachlorophene 407 7.1 6.9 7.54 1.5 -2.43 Hansch, C. et al., 1995 Lilius et al., 1995 CBI CBI 544 6.8 7.2 

### * 0.96 

### * -2.75 8(e)-_____ CBI CBI 553 8 7.6 1.9 * Unknown P91-____ CBI CBI 630 10 7.6 * P01-____ CBI CBI 635 6.3 8.1 

### * 2.4 

### * -2.39 P99-____ CBI CBI 520 11 11 

### * 0.94 

### * -2.74 P95-____
CBI CBI 744 21 21 

### * 0.87 

### * -2.93 P91-____

Data Not Included in SAR: CBI CBI 270 5.1 5 >8 >-1.53 8(e)-____

* indicates no effects at saturation



# References: Alexander HC, Dill DC, Smith LW, Guiney PD, and Do rn P. 1988. Bisphenol A: Acute aquatic toxicity. Environ. Toxicol. Chem. 7:19-26.

Lilius et al., 1995. Toxicity comparison of D. magna and D. pulex . Env Tox & Chem 14:2085-2088. [24- hour]

Soc. Plastics Ind., Inc.. 1984. Appendix D. Environmen tal Effects Of Bisphenol A. TSCA 4(A) submission, Fiche No. OTS0509967. Doc. No. 40-8486028, U.S. EPA, OTS, Washington, D.C..

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Phenols, Poly 12/2007

GREEN ALGAE 96-h EC50 (Growth)

ESTIMATED TOXICITY: The green algae 96-h EC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using t he computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h EC50 (mmol/L) = -0.0887 (log Kow) – 1.8928

The EC50 is in millimoles per liter (mM/L); N = 7 + 5; and the Coeffici ent of Determination (R 2 

# ) = 0.0076. To convert the EC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.4 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Algal 96-h EC50

y = -0.0887x - 1.8928
R 2 

## = 0.0076

n = 7 + 5 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50(mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 6.4, or if the compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal 96-h EC50 (mg/L) Log Algal 96- h EC50 (mmol/L) Reference (Meas. Kow) Reference (Algal 96-h EC50)

49745-95-1 Dobutamine hydrochloride 338 2.5 3.5 0.76 -2.65 8(e)-15346 80-05-7 Bisphenol A 228 3.7 3.6 3.32 2.73 -1.92 Alexander et al., 1988 80-05-7 Bisphenol A 228 3.7 3.6 3.32 2.5 -1.96 Soc. Plastics Ind. Inc., 1984 CBI CBI 322 3.4 3.6 0.74 -2.64 P89-____

CBI CBI 246 4.4 4.4 4.41 @ 23C, pH 6.4) 2.3 -2.03 P88-____ CBI CBI 270 5.1 5 22 -1.09 8(e)-____ CBI CBI 378 5.5 5.3 0.11 -3.54 P95-____

SAR Data Not Included in Regression Equation:

CBI CBI 485 6.5 5.7 >4.19 @ 25C, pH6.4 * Unknown P98-____

CBI CBI 527 7.4 6.7 >4.23 @ 18C * Unknown P91-____ CBI CBI 630 10 7.6 * P01-____ CBI CBI 635 6.3 8.1 

### * 27 

### * -1.00 P99-____ CBI CBI 520 11 11 * P95-____

Data Not Included in SAR:

* indicates no effects at saturation



# References: Alexander HC, Dill DC, Smith LW, Guiney PD, and Do rn P. 1988. Bisphenol A: Acute aquatic toxicity. Environ. Toxicol. Chem. 7:19-26.

Soc. Plastics Ind., Inc.. 1984. Appendix D. Environmen tal Effects Of Bisphenol A. TSCA 4(A) submission, Fiche No. OTS0509967. Doc. No. 40-8486028, U.S. EPA, OTS, Washington, D.C..

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Phenols, Poly 12/2007

FISH 30-d ChV

ESTIMATED TOXICITY: The fish 30-d chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using t he computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.6618 (log Kow) - 0.2069

The ChV is in millimoles per liter (mM/L); N = 3 + 3; and the Coefficient of Determination (R 2 

# ) = 0.833. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Fish ChV

y = -0.6618x - 0.2069
R 2 

## = 0.8333

n = 3 + 3 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 

# Log Kow (EPI)Log Fish ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV)

97-23-4 2,2'-Methylene bis(4- chlorophenol) 269 4.3 4.3 4.26 0.122 -3.34 Hansch, C. et al., 1995 DUL CBI CBI 256 5.6 5.2 0.16 -3.20 P90-____/P88-____/P94-____

70-30-4 2,2'-Methylene bis(3,4,6- trichlorophenol 407 7.1 6.9 7.54 0.00481 -4.93 Hansch, C. et al., 1995 DUL

SAR Data Not Included in Regression Equation:

CBI CBI 485 6.5 5.7 >4.19 @ 25C, pH6.4 * Unknown P98-____ CBI CBI 630 10 7.6 * P01-____

CBI CBI 527 7.4 6.7 >4.23 @ 18C * Unknown P91-____

Data Not Included in SAR:

NK 3-(2H-Benzotriazol-2-yl)- 1',1',1'-tris(4- hydroxyphenyl)ethane 423 6.6 5.3 15.2 to 28.2 -1.44 to -1.18 8(e)-13307

70-30-4 2,2'-Methylene bis(3,4,6- trichlorophenol 407 7.1 6.9 7.54 <0.00289 <-5.15 Hansch, C. et al., 1995 DUL

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 1990. Summary of structure-activity data files: University of Wisconsin-Superior (UWS) and ORD En vironmental Research Laboratory, Duluth, MN (ERL-D) research team. Computer printout from Environmental Effects Branch, HERD, U.S. EPA, Washington, DC. [DUL]

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Phenols, Poly 12/2007

DAPHNID 21-d ChV

ESTIMATED TOXICITY: The daphnid 21-d chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using t he computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.7946 (log Kow) + 0.785

The ChV is in millimoles per liter (mM/L); N = 3 + 1; and the Coefficient of Determination (R 2 

# ) = 0.936. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Daphnia ChV

y = -0.7946x + 0.785
R 2 

## = 0.936 n = 3 + 1 

# -6.00 -4.00 -2.00 0.00 2.00 4.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV) CBI CBI 306 4 4.4 0.9 -2.53 8(e)-____/P87-____ CBI CBI 256 5.6 5.2 0.061 -3.62 P90-____/P88-____/P94-____

CBI CBI 527 7.4 6.7 >4.23 @ 18C 0.019 -4.44 P91-____

SAR Data Not Included in Regression Equation: CBI CBI 630 10 7.6 * P01-____

Data Not Included in SAR:

NK 3-(2H-Benzotriazol-2-yl)- 1',1',1'-tris(4- hydroxyphenyl)ethane 423 6.6 5.3 5.83 to 9.85 -1.86 to -1.63 8(e)-13307

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from data submitted under the “Toxic Substance Control Act” (TSCA). Public Law 94-469, 90 Stat. 2003, October 11, 1976. Washington DC: OPPT, USEPA, 1400 Pennsylvania Ave., N.W.

# SAR Phenols, Poly 12/2007

GREEN ALGAE ChV

ESTIMATED TOXICITY: The green algae chronic values (ChV) used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated using t he computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.274 (log Kow) - 2.0044

The ChV is in millimoles per liter (mM/L); N = 4 + 4; and the Coefficient of Determination (R 2 

# ) = 0.0717. To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Phenols, Poly, Algal ChV

y = -0.274x - 2.0044
R 2 

## = 0.0717

n = 4 + 4 

# -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for phenols, poly.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Algal ChV (mg/L) Log Algal ChV (mmol/L) Reference (Meas. Kow) Reference (Algal ChV) CBI CBI 322 3.4 3.6 0.3 -3.03 P89-____

CBI CBI 246 4.4 4.4 4.41 @ 23C, pH 6.4) 2.2 -2.05 P88-____ CBI CBI 378 5.5 5.3 0.002 -5.28 P95-____

CBI CBI 527 7.4 6.7 >4.23 @ 18C 0.38 -3.14 P91-____

SAR Data Not Included in Regression Equation:

CBI CBI 485 6.5 5.7 >4.19 @ 25C, pH6.4 * Unknown P98-____ CBI CBI 630 10 7.6 * P01-____ CBI CBI 635 6.3 8.1 

### * 8.8 

### * -1.86 P99-____ CBI CBI 520 11 11 * P95-____

Data Not Included in SAR:

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 2006. Database of environmental toxicity data from Premanufacture Notifications (PMN). Washington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Schiff Bases 10/2007

FISH 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.2543 (log Kow) - 1.4244

The LC50 is in millimoles per liter (mM/L); N = 3 + 1; and the Coeffici ent of Determination (R 2 

# ) = 0.4807. To convert the LC50 from mM/L to mg/L , multiply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

Graph:



# SAR for: Schiff Bases, Fish 96-h LC50

y = -0.2543x - 1.4244
R 2 

### = 0.4807

n = 3 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish 96-h LC50 (mmol/L)



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish 96-h LC50 (mg/L) Log Fish 96-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish 96-h LC50) CBI CBI 181 2.7 2.6 3.16 1.1 -2.22 P97-___

_ CBI CBI 259 -0.2 1.3 1.4 -2.27 P90-___

_ CBI CBI 259 -0.2 1.3 18 -1.16 P90-___

_ Kow Limit 5 5 -2.65 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Schiff Bases 10/2007

DAPHNID 48-h LC50 (Mortality)

ESTIMATED TOXICITY: The daphnid 48-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 48-h LC50 (mmol/L) = -0.3895 (log Kow) - 0.7827

The LC50 is in millimoles per liter (mM/L); N = 1 + 1; and the Coeffici ent of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/L to mg/L, mult iply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

Graph:


# SAR for: Schiff Bases, Daphnia 48-h LC50

y = -0.3895x - 0.7827 n = 1 + 1



## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia 48-h LC50 (mmol/L)



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia 48

- h LC50 (mg/L) Log Daphnia 48-h LC50 (mmol/L) Reference (Meas. Kow) Reference (Daphnia 48-h LC50) CBI CBI 181 2.7 2.6 3.16 2.9 -1.80 P97-____ Kow Limit 5 5 -2.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Schiff Bases 10/2007

GREEN ALGAE 96-h EC50 (Growth)

ESTIMATED TOXICITY: No adequate data were available for the schiff bases SAR green algae 96-hr EC50 endpoint. Predictions for this endpoint are based on SARs for neutral organics. The neutral organic SAR equation used to estimate toxicity is:

Log EC50 (mmol/L) = -0.6155 log Kow + 0.5135

To convert the EC50 from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.4 Maximum MW: 1000

Graph:



# SAR for: Neutral Organics, Algal 96-h EC50

-6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal 96-h EC50 (mmol/L



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 6.4, or if the compound is solid and the EC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

References:

# SAR Schiff Bases 10/2007

FISH ChV

ESTIMATED TOXICITY: No adequate data were available for the schiff ba ses fish chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acut e-to-chronic ratio, and were based on the acute fish SAR for schiff bases. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4807 (log Kow) - 2.4244

The ChV is in millimoles per liter (mM/L); N = 0 + 2; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the ChV from mM/L to mg/L, multip ly by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Schiff Bases, Fish ChV

y = -0.4807x - 2.4244 n = 0 + 2



## -7.00 -5.00 -3.00 -1.00 1.00 3.00 5.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0


# Log Kow (EPI)Log Fish ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish ChV (mg/L) Log Fish ChV (mmol/L) Reference (Meas. Kow) Reference (Fish ChV) 0 0 -2.42 1/10 F96 Schiff Bases SAR Kow Limit 8 8 -6.27 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References:

# SAR Schiff Bases 10/2007

DAPHNID ChV

ESTIMATED TOXICITY: No adequate data were available for the Schiff bases daphnid chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the acute daphnid SAR for schiff bases. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5361 (log Kow) - 1.4015

The ChV is in millimoles per liter (mM/L); N = 0 + 2; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the ChV from mM/L to mg/L, multip ly by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Schiff Bases, Da phnia ChV

y = -0.5361x - 1.4015 n = 0 + 2 

## -8.00 -6.00 -4.00 -2.00 0.00 2.00 4.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Daphnia ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Daphnia ChV (mg/L) Log Daphnia ChV (mmol/L) Reference (Meas. Kow) Reference (Daphnia ChV)

CBI CBI 181 2.7 2.6 3.16 0.29 -2.80 1/10 D48 Schiff Base SAR; P97

-

____ Kow Limit 8 8 -5.69 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References:

# SAR Schiff Bases 10/2007

ALGAL ChV

ESTIMATED TOXICITY: No adequate data were available for the schiff bases SAR algal ChV endpoint. Predictions for this endpoint are based on SARs for neutral organics. The neutral organic SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.5362 log Kow -0.0865

To convert the ChV from mM/L to mg/L, multiply by the molecular weight of the compound.

Maximum K ow 

# : 6.0 Maximum MW: 1000

Graph:


# SAR for: Neutral Organics, Algal ChV

-6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Algal ChV (mmol/L



# Application: This SAR may be used to estimate toxicity for schiff bases.

Limitations: If the log Kow value is greater than 6.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

References:

# SAR Schiff Bases 10/2007

FISH (SW) 96-h LC50 (Mortality)

ESTIMATED TOXICITY: The fish (SW) 96-h LC50 values used to develop this SAR were measured and the octanol water partition coefficients (Kow) were calculated usi ng the computer program, KOWWIN (Version 1.67). The SAR equation used to estimate toxicity is:

Log 96-h LC50 (mmol/L) = -0.487 (log Kow) - 0.2751

The LC50 is in millimoles per liter (mM/L); N = 1 + 1; and the Coeffici ent of Determination (R 2 

# ) = N/A. To convert the LC50 from mM/L to mg/L, mult iply by the molecular weight of the compound.

Maximum K ow 

# : 5.0 Maximum MW: 1000

Graph:



# SAR for: Schiff Bases, Fish (SW) 96-h LC50

y = -0.487x - 0.2751 n = 1 + 1 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) 96-h LC50 (mmol/L)



# Application: This SAR may be used to estimate toxicity for Schiff bases.

Limitations: If the log Kow value is greater than 5.0, or if the compound is solid and the LC50 exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) 96-h LC50

(mg/L) Log Fish (SW) 96-h

LC50 (mmol/L) Reference (Meas. Kow) Reference (Fish SW 96-h LC50) CBI CBI 259 -0.2 1.3 32 -0.91 P90-____ Kow Limit 5 5 -2.71 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References: U.S. Environmental Protection Agency (USEPA). 20 06. Database of environmental toxicity data from Premanufacture Notifications (PMN). Wash ington DC: Risk Assessment Division (RAD), OPPT, USEPA, 1400 Pennsylvania Ave., N.W. (Unpublished test data.)

# SAR Schiff Bases 10/2007

FISH (SW) ChV

ESTIMATED TOXICITY: No adequate data were available for the schiff bases fish (SW) chronic value (ChV) SAR. Predictions for this endpoint were estimated using the acute-to-chronic ratio, and were based on the acute fish (SW) SAR for schiff bases. The SAR equation used to estimate toxicity is:

Log ChV (mmol/L) = -0.4212 (log Kow) - 1.3606

The ChV is in millimoles per liter (mM/L); N = 0 + 2; and the Coefficient of Determination (R 2 

# ) = N/A. To convert the ChV from mM/L to mg/L, multip ly by the molecular weight of the compound.

Maximum K ow 

# : 8.0 Maximum MW: 1000

Graph:



# SAR for: Schiff Bases, Fish (SW) ChV

y = -0.4212x - 1.3606 n = 0 + 2 

## -6.00 -4.00 -2.00 0.00 2.00 4.00 6.00

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0



# Log Kow (EPI)Log Fish (SW) ChV (mmol/L)



# Application: This SAR may be used to estimate toxicity for Schiff bases.

Limitations: If the log Kow value is greater than 8.0, or if the compound is solid and the ChV exceeds the water solubility by 10X, no effects at saturation are predicted.

Data:CAS No. Chemical Name M.W. log Kow (CLogP) log Kow (EPI ) log Kow (M) Fish (SW) ChV (mg/L) Log Fish (SW) ChV (mmol/L) Reference (Meas. Kow) Reference (Fish SW ChV)

CBI CBI 259 -0.2 1.3 3.2 -1.91 1/10 F96(SW) Schiff Bases; P90-____ Kow Limit 8 8 -4.73 NO Cutoff NO SAR

SAR Data Not Included in Regression Equation:

Data Not Included in SAR:

* indicates no effects at saturation



# References:

## Interpretative Assistance Document for Polymers August 2007 

# 1 

# Interpretive Assistance Document for Polymers for Sustainable Futures Screening Assessments

August 2007

This document provides general guidelines for as sessment of polymers t hat have an average number molecular weight (MW n 

# ) of greater than 1,000. This document follows the methods used by EPA’s New Chemicals Program. This document was developed as a teaching aid to help conduct assessments of large polymers under the Sustainable Futures Initiative. For technical reasons, many of the screening methods contained in the Sustainable Futures Initiative can not be used to evaluate large polymers. The information set out in this document are not final A gency actions, but are intended solely to provide assistance with review. They are not intended, nor can they be relied upon, to create any rights enforceable by any party in liti gation with the United States. EPA officials may decide to follow the guidance provided in this document, or to act at va riance with the guidance, based on an analysis of specific circumstances. P LEASE NOTE: It is strongly suggested that any Sustainable Futures Summary Assessment provide an interpretation of model estimati ons relative to potential risk for the chemical being evaluated.

PLEASE NOTE: The assessment methods described in this document should not be used to assess polymers with MW n 

# <1000. Polymers with MW n 

# <1000 should be assessed as discrete chemicals using EPI Suite, ECOSAR, and other methods in the Sust ainable Futures Initiative, as appropriate.

The assessment methods described here should be us ed only as general guidelines for assessment of polymers of similar type. Some polymers may be outside the scope of this document.

These estimation methods should not be used in plac e of measured data on the polymer being evaluated. Please note that data available on structurally similar polymers may be more accurate than assessments based on the estimation methods described in this document.

Reference: The main source of assessment methods describe d in this document is Boethling, Robert S. and Nabholz, J. Vincent “Environment al Assessment of Polymers under the U.S. Toxic Substances Control Act”, pp. 187-234, in Ecological Assessment of Polymers St rategies for Product Stewardship and Regulatory Programs , Hamilton, John D. and Sutcliffe, Roger (eds.), (1997) Van Nostrand Reinhold.

CONTENTS

Availability of Sustainable Fu tures / P2 Fram ework Mo dels...................................................................... ... 2

Three Types of Polymers Grouped by Average Number Molecular Weight (MW n 

# ) and Low Molecular Weight (LMW) Materi al Composition .............................................................................................. . 2

Physical / Chemical Property Estimations ....................................................................................... ............. 3

Environmental Fa te Estimations ................................................................................................. .................. 4

Aquatic Toxicity Estimations ................................................................................................... ...................... 5

Human Health Haza rd Estimations................................................................................................ ............... 9

Data Collection Table for Assessment of Polymers............................................................................... ..... 11

## Interpretative Assistance Document for Polymers August 2007 

# 2 

# Availability of Sustainable Futures / P2 Framework Models

EPISuiteTM: http://www.epa.gov/opptintr/exposure/pubs/episuite.htm

ECOSAR: http://www.epa.gov/opptintr/newchems/tools/21ecosar.htm

OncoLogic: http://www.epa.gov/oppt/newchems/tools/oncologic.htm

E-FAST: http://www.epa.gov/opptintr/exposure/pubs/efast.htm

ChemSTEER: http://www.epa.gov/opptintr/exposure/pubs/chemsteerdl.htm

NOTE: Due to the dynamic nature of the Internet, the URLs listed in th is document may have changed. A search using any of the publicly available sear ch engines may be necessary to the new URL.



# Three Types of Polymers Grouped by Av erage Number Molecular Weight (MW n 

# ) and Low Molecular Weight (L MW) Material Composition

Polymers can be grouped into three categories by MW n 

# and LMW material composition. These distinctions are used to determine if the polymer is assessed only as a polymer, or if oligomers may also need to be addressed. Monomers may need to be assessed if there is high content of residual monomer and/or the monomer has known aquatic or human he alth hazards. The assessment of monomer or oligomer toxicity is in addition to, or in lieu of, any polymer specific assessment.

• Category 1 : Polymers with low molecular weight (MW n 

# <1,000). These polymers may be able to be assessed as a single, discrete structure in EPI Suite and ECOSAR, subject to the normal limitation of the software. This is possible when the composition and structure of the polymer is known. In order to complete the assessment, find a reasonable represent ative structure of MW <1,000 and use this in the P2 modeling programs.

• Category 2 : Polymers with high molecular weight (MW n 

# >1,000) and large low molecular weight (LMW) material composition ( ≥ 25% with MW <1,000; ≥ 10% with MW <500). These polymers can be assessed for environmental fate and toxicity as the polymer; however, oligomers may need to be assessed in addition to account for any increased toxicity due to these lower molecular weight compounds.

• Category 3 : Polymers with high molecular weight (MW n 

# >1,000) and minimal LMW material (<25% with MW <1,000; <10% with MW <500). These are generally assessed solely as the polymer. However, as stated above, if a high percentage of unreacted monomers with potential health concerns are present, additional assessment may be required to address concerns for the

monomer.

## Interpretative Assistance Document for Polymers August 2007 

# 3 

# P HYSICAL / CHEMICAL PROPERTY ESTIMATIONS

Several properties of the polymer are very import ant and may be required for the assessment of the polymer. These properties are those associated with structure, size, and composition of the polymer to be assessed. In addition, some properties can be estimated based simply on the large size of the material. Properties that fall into thes e two categories are indicated below.

Important physical-chemical properties for polymers include:

• Monomers from which the polymer is created, and relative mole fraction of each monomer

• Molecular weight (MW) distribution

• Number average molecular weight (MW n 

# ) in Daltons and how it was determined

• Oligomer content of the polymer (i.e. percentages with MW ≤ 1000 and MW ≤ 500)

• Physical form

• Equivalent weight of any reactive functional groups (RFG) and/or cationic charge density, which can be determined from the structure.

• Particle size distribution

• Swellability

• Water solubility or dispersability – polymers t hat form micro emulsions or gels may be mistaken for soluble, but may not be truly soluble.

General physical / chemical and environmental fate properties for most polymers with MW n 

# >1,000

• Vapor Pressure <10 -8 

# mm Hg

• Henry’s Law constant <10 -8 

# atm-m 3 

# /mol

## Interpretative Assistance Document for Polymers August 2007 

# 4 

# ENVIRONMENTAL FATE ESTIMATIONS

The most important parameters to evaluate in the fate assessment of polymers are electronic charge (density being secondary), MW n 

# , and solubility/dispersability.

Vapor Pressure – Polymers with MW n 

# >1000 generally have a vapor pressure of <10 -8 

# mm Hg. This indicates that the chemical is likely to exist solely as particulate matter in the atmosphere. As particulate matter, atmospheric oxidation is not expected to be a significant route of environmental removal.

Henry’s Law Constant – Due to the large size and low vapor pr essure of most polymers, those with MW n 

# >1000 generally have Henry’s Law constant of <10 -8 

# atm-m 3 

# /mol. Due to this, volatilization from water or moist soil is not expected to occur at an appreciable rate, with half-lives for volatilization of >1 year.
Bioconcentration Factor (BCF) – Due to the large size and insolu bility of most polymers, they are typically of low concern for bioconcentration. Those with MW n 

# >1,000 will typically be of low concern; for estimations that require a numeric BCF (E-FAST), 100, which is within the range of low BCF concern, can be used.

Soil Adsorption and Mobility

• Cationic, amphoteric, nonionic – These polyme rs will generally absorb strongly to soil and sediment.

• Anionic polymers – Anionic polymers usually have low sorption to soil. However, due to large size and weight parameters, these materi als may still have low mobility in soil.

POTW removal – Removal of polymers in sewage treatment is dependent primarily on solubility, but may be influenced by binding potential for sludge.

• Cationic, Amphoteric, and Nonionic MW n 

# Removal 500 – 1,000 50 – 90% (50% typically used) >1000 90%

• Anionic

 If solubility and/or dispersability are negligible, use table for cationic, amphoteric, and nonionic polymers above.

 If soluble and/or dispersible MW n 

# Removal <5,000 0 – 50% (0% typically used) 5,000 – 20,000 50% 20,000 – 50,000 75% >50,000 90%

Biodegradation – The vast majority of polymers are es sentially non-biodegradable. While some exceptions exist, these polymers are usually specif ically designed to be biodegradable materials (to replace more resistant polymers as a more environmenta lly friendly alternative). Often, to substantiate this claim, biodegradation studies are available on these biodegradable types of polymers. In the case of highly degradable polymers, assessment of the degradation products may be warranted.

Hydrolysis – Hydrolysis of susceptible groups on polyme rs is solubility dependent. Polymers with poor water solubility may have reduced susceptibility to hydrolysis.

## Interpretative Assistance Document for Polymers August 2007 

# 5 

# AQUATIC TOXICITY ESTIMATIONS

Average Molecular Weight (MW n 

# ), Monomer, and Low Molecular Weight (LMW) Material Composition Categories – When assessing polymers that fit into category 1 above, it may be more relevant to find a discrete representative structur e with MW of <1,000 and assess this structure using ECOSAR or other methods of aquatic hazards estimati on. Polymers that fit into category 2 above may require assessment of the polymer itself, but further assessment of the low molecular weight components of the polymer mixture may also be needed to fully characterize the aquatic hazard. If no data on the compound are available, ECOSAR or other methods for aquatic hazard estimation can be used to assess the LMW components. Lastly, polym ers that contain large amounts of residual monomers may require assessment of the monomer to fully characterize the aquatic hazards associated with the mixture.

Insoluble Polymers – Insoluble polymers are not expected to be toxic unless the material is in the form of finely divided particles. Most often, the toxici ty of these polymer particles does not depend on a specific reactive structural feature, but occurs from occlusion of respiratory organs such as gills. For these polymers, toxicity typically occurs only at high concentration; acute toxicity values are generally >100 mg/L and chronic toxicity values are generally >10 mg/L (low toxicity).

Nonionic Polymers – These polymers are generally of low co ncern for aquatic hazard, due to negligible water solubility. Two exceptions exist. The first is for nonionic polymers that have monomers blocked in such a way as to use the polymer as a surfactant or dispersant, which may cause toxicity to aquatic organisms. The second is for nonionic polymers with significant oligomer content (i.e., ≥ 25% with MW <1,000; ≥ 10% with MW <500), which may be a concern on the basis of bioavailability of the LMW material. In this case the LMW oligomers, if t hey are <1,000 MW, can be assessed using ECOSAR or other methods for aquatic hazard assessment.

Anionic Polymers – Polyanionic polymers with MW n 

# >1,000 that are soluble or dispersible in water may pose a concern for direct or indirect toxicity. T hese polymers are further divided into 2 subclasses: Poly(aromatic acids) and Poly(aliphatic acids)

.

• Poly(aromatic acids) – These chemicals are usually poly(aromatic sulfate/carboxylate) structures and generally are of moderate hazard concer n to aquatic organisms, with acute LC 50 

# /EC 50 

# values between 1 mg/L and 100 mg/L, depending upon the ex act structure of the polymer. Monomers associated with toxicity include: carboxylated/ sulfonated diphenolsufones, sulfonated phenols, sulfonated cresols, sulfonated diphenylsulf ones, and sulfonated dipheny lethers. Monomers usually associated with low aquatic toxicity concern include: sulfonated naphthalene and sulfonated benzene.

The toxicity of this type of polymer appears to be moderate and not affected by water hardness. Toxicity can be estimated by a nearest analog approach using test data available for polymers of known composition. A collection of data on polymer s of this type is available in table 10.4 (pp. 207 – 208) in the Boethling, Nabholz reference cited above.

• Poly(aliphatic acids) – This type of polymer is m ade up of repeating carboxylic acid, sulfonic acid, and/or phosphinic acid monomers. At pH 7 this polymer type generally exhibits low toxicity toward fish and daphnid, with LC 50 

# values >100 mg/L. However, there may be toxicity hazard concerns for green algae; toxicity to algae is believed to arise from chelation of nutrients.

The toxicity of this type of polymer can be assumed to be low for fish and daphnid. Green algae toxicity can be determined using a nearest analog approach with test data collected for similar polymers of known composition. The toxicity is highly dependent on the structure of the polymer, with space between repeating acid units and addition of non-chelating groups affecting toxicity. A collection of data on polymers of this type is ava ilable in table 10.5 (pg. 209) in the Boethling, Nabholz reference cited above.

Water hardness has been shown to mitigate the toxici ty of poly(aliphatic acid) polymers to green algae. As water hardness increases, toxicity tends to decrease. This is due to the abundance of chelating cations that “fill” the ch elation sites of the polymer, allo wing more nutrients to remain in

## Interpretative Assistance Document for Polymers August 2007 

# 6 the water. In many cases a mitigating factor can be applied to the estimated toxicity values. The appropriate mitigating factor, if any, can be discerne d from table 10.6 (pg. 212) in the Boethling, Nabholz reference cited above.

Cationic Polymers – Cationic polymers that may pose a conc ern for aquatic hazard are those that have a net positive charge or that may bec ome cationic in the environment.

• Cationic Atom - The most common atoms that may have net positive charge include, but are not limited to, nitrogen (ammonium), phosphorus (phosp honium), and sulfur (sulfonium); with nitrogen constituting the cationic atom in >99% of polymers.

• Percent Amine Nitrogen (%A-N) – The percent of amine nitrogen (or other cationic atom) is used in the cationic nitrogen polymer SARs for estimation of aquatic toxicity. Nitrogens directly substituted to an aromatic ring, nitrogens in an ar omatic ring, amides, nitriles, nitro groups, and carbo diimides are not counted for determining %A-N.

%A-N can be determined using the following equation: %A-N = 100 × [typical wt% of amine subunit in polymer] × [number of cationic nitrogens in subunit] × [atomic wt of N] ÷ [MW of amine subunit]

For smaller polymers, where the total number of nitrogens per polymer molecule is known, or non-polymers that may have toxicity similar to cationic polymers, the %A-N can be determined

as: %A-N = 100 × [number of amines in compound] × 14.01 [atomic wt of N] ÷ [MWn of polymer]

• Polymer Backbone – In addition to the cation-producing group, polymers of this type are assessed according to their backbo ne, which can be carbon-based, silicone-based (i.e., Si-O), or natural (chitin, starch, tannin).

Cationic Polymer SARs – The SARs for determination of aquatic hazard from cationic polymers are based on the %A-N. At high %A-N (typ ically 3.5% or 4.3%), it has been found that the aquatic hazard no longer correlates with increasing %A-N and is essentia lly constant. At this poi nt the aquatic hazard is based on the geometric mean of similar polymers with measured data.

## Interpretative Assistance Document for Polymers August 2007 

# 7 SAR Equations for Estimating Aquatic Toxicity of Polycationic Polymers

Carbon-Based Silicon-Based Natural-Based Fish Acute* If %A-N ≤ 3.5; Log [Fish 96-hr LC 50 

## ] = 1.209 - 0.462 × %A-N

If %A-N >3.5; Fish 96-hr LC 50 

## = 0.28 mg/L If %A-N ≤ 3.5; Log [Fish 96-hr LC 50 

## ] = 2.203 - 0.963 × %A-N

If %A-N >3.5; Fish 96-hr LC 50 

## = 1.17 mg/L Data indicate that acute toxicity toward fish will be similar or less than that for carbon-based backbone polymers. SAR analysis should employ the nearest analog method. Daphnid Acute* If %A-N ≤ 3.5; Log [Daphnid 48-hr LC 50 

## ] = 2 

# .839 – 1.194 × %A-N

If %A-N >3.5; Daphnid 48-hr LC 50 

## = 0.10 mg/L Data indicate that acute toxicity toward Daphnids will be similaror less than that for carbonbased backbone polymers. SAR analysis should employ the nearest analog method. If %A-N ≤ 4.3; Log [Daphnid 48-hr LC 50 

## ] = 2.77 - 0.412 × %A-N

If %A-N >4.3; Daphnid 48-hr LC 50 

## = 11 mg/L

Green Algal Acute* If %A-N ≤ 3.5; Log [Green Algae 96-hr EC 50 

## ] = 1.569 - 0.97 × %AN

If %A-N >3.5; Green Algae 96-hr EC 50 

## = 0.040 mg/L Data indicate that acute toxicity toward green algae will be similar or less than that for carbon-based backbone polymers. SAR analysis should employ the nearest analog method. Data indicate that acute toxicity toward green algae will be less than that for carbon-based backbone polymers. SAR analysis should employ the nearest analog method.

Fish Chronic* Acute to Chronic Ratio (ACR) of 18 Acute to Chronic Ratio (ACR) of 18 Acute to Chronic Ratio (ACR) of 18 Daphnid Chronic* Acute to Chronic Ratio (ACR) of 14 Acute to Chronic Ratio (ACR) of 14 Acute to Chronic Ratio (ACR) of 14 Green Algal Chronic* If %A-N ≤ 3.5; Log [Green Algae ChV] = 1.057 - 1 × %A-N

If %A-N >3.5; Green Algae ChV = 0.020 mg/L Use the SAR for methodology above for carbon-based backbone polymers Data indicate that chronic toxicity toward green algae will be less than that for carbon-based backbone polymers. SAR analysis should employ the nearest analog method.



# *Please note conditions for application of Mitigation Factors (MF) on page 8, for certain scenarios and cationic/amphoteric polymers. This may affe ct the quantitative result s of polymer profile.

Amphoteric Polymers – These polymers contain both positiv e and negative charges in the same polymer. The toxicity of these polymers is depend ent on cation-to-anion ratio (CAR) and the overall cationic charge density. Toxicity increases with ca tionic charge density and, when charge density is constant, increases with CAR. The toxicity of t hese polymers may be reduced by a toxicity reduction factor (TRF) calculated for each endpoint. In cases where chronic endpoints are estimated using an acute to chronic ration (ACR), apply the ACR after the TRF is applied to the acute endpoint, no further TRF is applied to the chromic endpoint.

The toxicity of these polymers is predicted in 4 steps:

Step 1 : a. Calculation of the %A-N: this is done as for cationic polymers above. b. Calculation of the CAR; this calculation is as follows: CAR = ratio of cations to anions in the chemic al = [total number of cations] ÷ [total number of anions]

Step 2 : Estimate the aquatic toxicity from the %A-N as if the polymer were polycationic.

Step 3 : Calculate the TRF from the CAR for each end point from the following equations:

Fish Acute TRF (96-hr LC 50 

# ): Log [TRF] = 1.411 - 0.257 × CAR

Daphnid Acute TRF (48-hr LC 50 

# ): Log [TRF] = 2.705 - 0.445 × CAR

Green Algae Acute (96-hr EC 50 

# ): Log [TRF] = 1.544 - 0.049 × CAR

## Interpretative Assistance Document for Polymers August 2007 

# 8 Green Algae Chronic (96-hr ChV): Log [TRF] = 1.444 - 0.049 × CAR

Step 4 : The predicted value from Step 2 is multiplied by the correct TRF to generate the final toxicity value.

Cationic and Amphoteric Polymers: Mitigation of Toxicity – Standard aquatic hazard testing media (OECD) usually has a low total organic content (TOC) which may result in artificially high toxicity of polycationic and amphoteric polymers in those media. Surface waters tend to have higher total organic content (TOC) and dissolved organi c content (DOC) than w hat is used in standard (OECD) aquatic toxicity testing media. It has been shown that DOC, particularly humic and other acidic compounds, reduces the toxicity of cationic and amphoteric polym ers to the aquatic environ ment. Due to this, the aquatic hazard may be over estimated in laboratory testing of this type of polymer, which, in large part is what the SAR methods are based on. In order to correc t for TOC in actual surface water versus that in laboratory testing media, a mitigating factor (M F) has been calculated, based on testing done with standard media compared to testing done with media containing a standard 10 mg/L TOC as humic acid, to apply to the aquatic effect levels estimated usi ng SAR equations. The MF is dependent on the overall charge density, calculated as %A-N, for the polymer. Several conditions and/or structural features have been shown to affect the mitigation factor, which are discussed below.

• Mitigating Factor (MF) for Polymers that are formed by the random reaction of monomers and have minimal oligomer content (i.e., <25% with MW <1,000; <10% with MW <500):

For charge density where %A-N is ≥ 3.5: MF = 110

For charge density where %A-N is 3.5 – 0.7: Log [MF] = 0.858 + 0.265 × %A-N

For charge density where %A-N is <0.7: Do not use a MF for these cases; MFs have not been established, but are expected to be <7.

• Conditions effecting Mitigation Factor (MF) value:

It has been shown that as LMW component composition increases, the MF decreases. For compounds with high LMW component compositions, do not apply a mitigation factor.

The mitigating factor has been shown to be decreased by the addition of ethoxy groups, or ethoxy ether groups, substituted dire ctly on the nitrogen i.e. N(CH 2 

# CH 2 

# O) n 

# , with the mitigations factor being decreased for each additional group of this type bonded to the nitrogen.

If a single ethoxy group is attached, the MF is multiplied by 0.67

If two ethoxy groups are attached, the MF is multiplied by 0.33

If three ethoxy groups are attached, the MF is essentially 0

## Interpretative Assistance Document for Polymers August 2007 

# 9 

# HUMAN HEALTH HAZARD ESTIMATIONS

Non-Cancer Human Health Hazard

– The approach for assessing potential human health concerns posed by a polymer depends on the type and availability of toxicity data. In most cases, there is a paucity of data, which precludes adequat e evaluation of the polymer itse lf, and requires an assessment based on information available for, e.g ., close analogs, chemical class, or the constituent monomer(s). The following text presents a hierarchical approach o ften used in evaluating the human health effects of polymers.

Assessment Based On Toxicity Data For The Polymer Or Analog

– For some polymers, adequate toxicity data exist in the literature or are supplied by the submitter for assessing the potential health effects of the polymer. In this case, systemic effect s, as well as portal of entry effects, are thoroughly evaluated based on data for the polymer itself. In t he absence of adequate data on the polymer, or to fill specific data gaps, the assessment will be based on structurally related anal og(s) that have adequate toxicity information.

Assessment Based On Chemical Class Information

– Often, either no toxicity data are available or the data may be inadequate for thorough evaluation of the heal th effects of the polymer. For these polymers, several lines of evidence are used in parallel. The assessment may be based on the toxicity information available for the chemical class. For example, if a polymer has a stru cture similar to that of amphoteric surfactants, the toxicity of the polymer may be assessed based on information available for such surfactants. The toxicity of a polymer may also be evaluated based on its intended use. For example, if the polymer is a chelating agent, the assessment will co nsider the toxicity information available for such agents based on their functional effect. The evaluation sh ould also take into consideration the presence of reactive functional groups (RFGs) on the side chains. A key consideration is whether these side chains are likely to have biological functions in the context of their presence on a larger molecule (since they may not be available for interaction with the same cellular targets as a small molecule would be with the same structure). Additionally, if the polymer is expected to undergo hydrolysis (in the environment, under physiological conditions such as the acidic pH of the stomach, or enzymatically), the evaluation of the health effects should take into consideration the to xicity data available for the hydrolysis product(s). If hydrolysis is expected, then the toxicity assessment may also need to consider potential toxicity of the hydrolysis products. In other instances, the size or c hemical properties (e.g., solubility) of the polymer will raise the question rega rding its bioavailability. Typically, polymers with mo lecular weight > 1000 are considered to be of limited bioavailability. If it is know n, or if there is evidence to suggest that the polymer is not bioavailable, the evaluation will be limited to consideration of portal of entry effects.

Assessment Based On Residual Monomers

– It may also be appropriate to develop an assessment based on the toxicity information of the low molecular we ight species or residual monomers if they exist in a product at significant quantities (e.g., >10%).

Lung Effects Of High Molecular Weight Polymers – Polymers with MW n 

# of >10,000 are generally of concern only for lung effects. For concerns specific to lung toxicity, these polymers are typically divided into 3 classes; soluble, insoluble, and swellable. The associated hazard concer ns are qualitative, rather than quantitative, and are used to identify inhalation concerns. Additional guidance on the human health assessment of high molecular weight polymers is available at: http://www.epa.gov/opptintr/new chems/pubs/hmwtpoly.htm

.

• Soluble – Soluble polymers of MW n 

# 10,000 – 13,000 are not expected to exhibit lung toxicity because they can rapidly clear from the respir atory tract, preventing lung overload. However, soluble polymers of MW n 

# >13,000 may have the potential to cause lung overloading effects. Polymers that are soluble as well as swellable (tea bag test shows loss of material) are considered soluble for the determination of lung effect concerns.

• Insoluble – There are concerns for insoluble polymers with MW n 

# >10,000 for the potential to cause lung overloading. Studies have shown irreve rsible lung damage as a result of respiration

## Interpretative Assistance Document for Polymers August 2007 

# 10 of polymer particles with MW n 

# >70,000. Additional concerns exis ts for ultra-fine particles with significant amounts of <10 micron material.

• Swellable – Polymers of this type that can absorb th eir weight or greater in water have serious health concerns for fibrosis and/or cancer.

Cancer Human Health Hazard

– OncoLogic may be used to assess the potential human health cancer concerns for polymers. The assessment uses input on basic properties, structural features, and components of the polymer; not all of these properties are required, however, more data input will lead to a more accurate assessment of the potential carcino genic effects. In addition, the software goes through several yes or no questions to help in the assessment. The data needed, as well as many of the questions that will be as ked, are listed below.

• Average molecule weight (MW n 

# )

• Is the polymer made of covalently linked repeating units?

• Does the polymer contain >2% residual monomer?

• Does the polymer contain >2% material with MW ≤ 500?

• Does the polymer contain any of the following atoms: Beryllium (Be), Cadmium (Cd), Chromium (Cr), Nickel (Ni), Arseni c (As), Antimony (Sb)?

• Is the polymer crosslinked?

• Any reactive functional gro ups (RFGs) on the polymer or unreacted monomers should be included.

• Water solubility of the polymer.

• Is the polymer expected to be inflammatory?

• Is the polymer expected to accumulate in soft tissues?

• What routes of exposure (ingest ion, injection, and/or inhalation) are expected? Is the polymer going to be in a form that is easily respirable?Data Collection Sheet for Assessment of PolymersThis data collection sheet can be used to collect data important to the assessment of polymers.Polymer Representative StructureMole Ratio (orPercent) ofeachmonomerAre themonomersblocked?MWn%<1000,% <500ResidualMonomer(s)(Wt %)Solubility/Dispersability/SwellabilityParticle sizeOverallPolymerChargeReactive Functional Groups(RFGs, if any)Wt % of RFGsCation Generating Groups (if any)Percent of Amine Nitrogen (%A-N)Interpretative AssistanceDocument for PolymersAugust 200711