PUBLIC RELEASE DRAFT
May 2025
EPA-740-D-25-016
May 2025
Office of Chemical Safety and
Pollution Prevention
Draft Environmental Media, General Population, and
Environmental Exposure for Dibutyl Phthalate
(DBP)
Technical Support Document for the Draft Risk Evaluation
CASRN 84-74-2
xvEPA
United States
Environmental Protection Agency
May 2025
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26 TABLE OF CONTENTS
27 SUMMARY 7
28 1 ENVIRONMENTAL MEDIA CONCENTRATION OVERVIEW 8
29 2 SCREENING LEVEL ASSESSMENT OVERVIEW 15
30 2.1 Estimating High-End Exposure 15
31 2.2 Margin of Exposure Approach 18
32 3 LAND PATHWAY 20
33 3.1 Biosolids 20
34 3.1.1 Weight of Scientific Evidence Conclusions 24
35 3.2 Landfills 24
36 3.2.1 Weight of Scientific Evidence Conclusions 26
37 4 SURFACE WATER CONCENTRATION 28
38 4.1 Modeling Approach for Estimating Concentrations in Surface Water 28
39 4.2 Measured Concentrations 32
40 4.2.1 Measured Concentrations in Surface Water 32
41 4.2,2 Measured Concentrations in Sediment 34
42 4.3 Evidence Integration for Surface Water and Sediment 35
43 4.3.1 Strengths, Limitations, and Sources of Uncertainty for Modeled and Monitored Surface
44 Water C oncentrati on 35
45 4.4 Weight of Scientific Evidence Conclusions 36
46 5 SURFACE WATER EXPOSURE TO GENERAL POPULATION 37
47 5.1 Modeling Approach 37
48 5.1.1 Dermal Exposure 37
49 5.1.2 Oral Exposure 39
50 5.2 Weight of Scientific Evidence Conclusions 40
51 6 DRINKING WATER EXPOSURE TO GENERAL POPULATION 41
52 6.1 Modeling Approach for Estimating Concentrations in Drinking Water 41
53 6.1.1 Drinking Water Ingestion 41
54 6.2 Measured Concentrations in Drinking Water 42
55 6.3 Evidence Integration for Drinking Water 44
56 6.4 Weight of Scientific Evidence Conclusions 44
57 7 FISH INGESTION EXPOSURE TO GENERAL POPULATION 45
58 7.1 General Population Fish Ingestion Exposure 46
59 7.2 Subsistence Fish Ingestion Exposure 47
60 7.3 Tribal Fish Ingestion Exposure 48
61 7.4 Weight of Scientific Evidence Conclusions 50
62 7,4.1 Strength, Limitations, Assumptions, and Key Sources of Uncertainty 50
63 8 AMBIENT AIR CONCENTRATION 51
64 8.1 Approach for Estimating Concentrations in Ambient Air 51
65 8.1.1 Release and Exposure Scenarios Evaluated 51
66 8.1.2 IIOAC Model Output Values 52
67 8,1,3 Modeled Results from IIO AC 52
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68 8.2 Measured Concentrations in Ambient Air 53
69 8.3 Evidence Integration 54
70 8.3.1 Strengths, Limitations, and Sources of Uncertainty for Modeled Air and Deposition
71 Concentrations 54
72 8.4 Weight of Scientific Evidence Conclusions 55
73 9 AMBIENT AIR EXPOSURE TO GENERAL POPULATION 56
74 9.1 Exposure Calculations 56
75 9.2 Overall Findings 56
76 10 HUMAN MILK EXPOSURES TO GENERAL POPULATION 57
77 10.1 Biomonitoring Information 57
78 10.2 Modeling Information 58
79 10.3 Hazard Information 59
80 10.4 Weight of Scientific Evidence Conclusions 59
81 11 URINARY BIOMONITORING 60
82 11.1 Approach for Analyzing Biomonitoring Data 60
83 11.1.1 Temporal Trend of MnBP 61
84 11.1,2 Changes in MHBP Concentrations 67
85 11.1,3 Daily Intake of DBP from NHANES 67
86 11.2 Limitations and Uncertainties of Reverse Dosimetry Approach 70
87 11.3 Weight of Scientific Evidence Conclusions 71
88 12 ENVIRONMENTAL BIOMONITORING AND TROPHIC TRANSFER 72
89 12.1 Aquatic Environmental Monitoring 72
90 12.2 Trophic Transfer 75
91 12.3 Weight of Scientific Evidence Conclusions 75
92 13 CONCLUSION OF ENVIRONMENTAL MEDIA CONCENTRATION, GENERAL
93 POPULATION EXPOSURE, AND RISK SCREEN 77
94 13.1 Environmental Exposure Conclusions 77
95 13.2 Weight of Scientific Evidence Conclusions for Environmental Exposure 77
96 13.3 General Population Screening Conclusions 78
97 13.4 Weight of Scientific Evidence Conclusions for General Population Exposure 80
98 REFERENCES 82
99 APPENDICES 92
100 Appendix A EXPOSURE FACTORS 92
101 A. 1 Surface Water Exposure Activity Parameters 95
102 Appendix B ESTIMATING HYDROLOGICAL FLOW DATA FOR SURFACE WATER
103 MODELING 97
104 Appendix C SURFACE WATER RISK SCREENING RESULTS 99
105 C.l Incidental Dermal Exposures (Swimming) 99
106 C.2 Incidental Ingestion 99
107 Appendix D GENERAL POPULATION DRINKING WATER RISK SCREENING
108 RESULTS 100
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Appendix E FISH INGESTION RISK SCREENING RESULTS 101
E. 1 General Population 101
E. 2 Sub si stence Fi shers 101
E.3 Tribal Populations 102
Appendix F AMBIENT AIR MONITORING STUDY SUMMARY 103
Appendix G URINARY BIOMONITORING METHODS AND RESULTS 104
LIST OF TABLES
Table 1-1. Crosswalk of Conditions of Use to Assess Occupational Exposure Scenarios 8
Table 1-2. Type of Release to the Environment by Occupational Exposure Scenario 10
Table 1-3. Exposure Pathways Assessed for General Population Screening Level Assessment 13
Table 2-1. Exposure Scenarios Assessed in Risk Screening 17
Table 2-2. Non-Cancer Hazard Values Used to Estimate Risks 19
Table 3-1. Typical Biosolids Application Scenarios 22
Table 3-2. Estimated DBP Soil Concentrations Following Application of Biosolids 22
Table 4-1. PSC Model Inputs (Chemical Parameters) 28
Table 4-2. Standard EPA "Farm Pond" Waterbody Characteristics for PSC Model Inputs 29
Table 4-3. PSC Modeling Results for Water and Benthic Sediment Using 7Q10 Flow 31
Table 4-4. PSC Modeling Results for Total Water Column Using Harmonic Mean Flow and 30Q5
Flow 32
Table 4-5. Summary of Measured DBP Concentrations in Surface Water 33
Table 4-6. Summary of Measured DBP Concentrations in Sediment 35
Table 5-1. Dermal (Swimming) Doses Across Lifestagesa 38
Table 5-2. Incidental Ingestion Doses (Swimming) Across Lifestages 40
Table 6-1. Drinking Water Doses Across Lifestages 42
Table 6-2. Summary of Measured DBP Concentrations in Drinking Water 43
Table 7-1. Fish Tissue Concentrations Calculated from Modeled Surface Water Concentrations and
Monitoring Data 46
Table 7-2. General Population Fish Ingestion Doses by Surface Water Concentration 47
Table 7-3. Adult Subsistence Fisher Doses by Surface Water Concentration 48
Table 7-4. Adult Tribal Fish Ingestion Doses by Surface Water Concentration 50
Table 8-1. IIOAC Input Parameters for Stack and Fugitive Air Releases 52
Table 8-2. Source Apportioned and Total Daily-Average and Annual-Average IIOAC-Modeled
Concentrations at 100 m from Releasing Facility 53
Table 8-3. Source Apportioned and Total Annual-Average IIOAC-Modeled Wet, Dry, and Total Air
to Soil Deposition Rates at 100 m from Releasing Facility 53
Table 11-1. Fue Values Used for the Calculation of Daily Intake Values by DBP 68
Table 11-2. Daily Intake Values for DBP Based on Urinary Biomonitoring from the 2017-2018
MIANES Cycle 69
Table 13-1. Summary of High-End DBP Concentrations in Various Environmental Media from
Environmental Releases 79
Table 13-2. Risk Screen for High-End Exposure Scenarios for Highest Exposed Populations 80
LIST OF FIGURES
Figure 2-1. Potential Human Exposure Pathways for the General Population 16
Figure 10-1. Concentrations of DBP or MnBP in Human Milk in Either Lipid (ng/g) or Wet Weight
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(ng/L) 58
Figure 11-1. Reverse Dosimetry Approach for Estimating Daily Intake 60
Figure 11-2. Urinary DBP Metabolite Concentrations for Adults (16+ Years) 62
Figure 11-3. Urinary DBP Metabolite Concentrations for Women of Reproductive Age (16-49
Years) 63
Figure 11-4. Urinary DBP Metabolite Concentrations for All Children (3 to <16 Years) by Sex 64
Figure 11-5. Urinary DBP Metabolite Concentrations for Toddlers (3 to <6 Years) 65
Figure 11-6. Urinary DBP Metabolite Concentrations for Children (6 to <11 Years) 66
Figure 11-7. Urinary DBP Metabolite Concentrations for Adolescents (11 to <16 Years) 67
LIST OF APPENDIX TABLES
Table_Apx A-l. Body Weight by Age Group 92
Table_Apx A-2. Fish Ingestion Rates by Age Group 92
TableApx A-3. Recommended Default Values for Common Exposure Factors 93
Table_Apx A-4. Mean and Upper Milk Ingestion Rates by Age 95
Table_Apx A-5. Incidental Dermal (Swimming) Modeling Parameters 95
Table Apx A-6. Incidental Oral Ingestion (Swimming) Modeling Parameters 96
Table Apx C-l. Risk Screen for Modeled Incidental Dermal (Swimming) Doses for Adults, Youths,
and Children from Modeling and Monitoring Results 99
Table Apx C-2. Risk Screen for Modeled Incidental Ingestion Doses for Adults, Youths, and
Children from Modeling and Monitoring Results 99
Table Apx D-l. Risk Screen for Modeled Drinking Water Exposure for Adults, Infants, and Toddlers
from Modeling and Monitoring Results 100
Table Apx E-l. Risk Estimates for Fish Ingestion Exposure for General Population 101
Table Apx E-2. Risk Estimates for Fish Ingestion Exposure for Subsistence Fishers 102
Table Apx E-3. Risk Estimates for Fish Ingestion Exposure for Tribal Populations 102
TableApx G-l. Limit of Detection of Urinary DBP Metabolites by NHANES Cycle 104
Table Apx G-2. Summary of Urinary DBP Metabolite Concentrations (ng/mL) from all NHANES
Cycles Between 1999-2018 105
Table Apx G-3. Regression Coefficients and P-values for Statistical Analyses of DBP Metabolite
Concentrations 110
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KEY ABBREVIATIONS AND ACRONYMS
7Q10
Lowest 7-day flow in a 10-year period
ADD
Average daily dose
ADR
Acute dose rate
AERMOD
American Meteorological Society (AMS)/EPA Regulatory Model
BAF
Bioaccumulation factor
BCF
Bioconcentration factor
CDC
Centers for Disease Control and Prevention (U.S.)
CEM
Consumer Exposure Model
COU
Condition of use
DAD
Dermal absorbed dose
DBP
Dibutyl phthalate
DI
Daily intake
EPA
Environmental Protection Agency (U.S.)
dw
Dry weight
ECHO
EPA's Enforcement and Compliance History Online Database
Fue
Fractional urinary excretion
IIOAC
Integrated Indoor-Outdoor Air Calculator (model)
EPA
Environmental Protection Agency (U.S.)
HEC
Human equivalent concentration
HED
Human equivalent dose
HM
Harmonic mean
IIOAC
Integrated Indoor/Outdoor Air Calculator (IIOAC) (Model)
Koa
Octanol:air partition coefficient
Koc
Organic carbon:water partition coefficent
Kow
Octanol:water partition coefficient
KP
Dermal permeability coefficient
LADD
Lifetime average daily dose
MCNP
Mono-(carboxynonyl) phthalate
MHBP
Mono-3-hydroxybutyl phthalate
MnBP
Mono-n-butyl phthalate
MOE
Margin of exposure
NAICS
North American Industry Classification System
NHANES
National Health and Nutrition Examination Survey
NPDES
National Pollutant Discharge Elimination System
OCSPP
Office of Chemical Safety and Pollution Prevention
OES
Occupational exposure scenario
OPPT
Office of Pollution Prevention and Toxics
PESS
Potentially exposed or susceptible subpopulation(s)
POD
Point of departure
RCRA
Resource Conservation and Recovery Act
TRI
Toxics Release Inventory
TSCA
Toxic Substances Control Act
U.S.
United States
WW
Wet weight
WWTP
Wastewater treatment plant
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233 SUMMARY
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234
l> IS I* — Kiivironiiicnliil Med in (onccnlrsilion ;iihI (icnorsil Population Kxposurc:
Key Points
I-IW e\aliiiilccl the rcasnnahK a\ailahlc information lor \arious en\ironmental media
concentrations and eslinialetl exposure usinu a conser\ ati\e scenario as a screening le\el
approach The conser\ali\e hiuh-end exposure was assumed to result from the hiuhest DIJP
releases associated with the corresponding Toxic Substances Control Act ( I SCA) condition of
use (COl ) \ ia different exposure pathways The key points are summarized below
• I-IW conducted a screening lex el assessment of general population and en\ironmental
exposure through air. water, and land (/.. soil, hiosolids. and groundwater)
I or the land pathway, there are uncertainties in the rele\ance of limited monitoring
data lor hiosolids and landfill leachate to the COl s considered I lowe\er. based on
high-quality physical and chemical property data. I-IW determined that DliP will
ha\e low persistence potential and mobility in soils Therefore, uroundwater
concentrations resulting from releases to the landfill or to agricultural lands \ ia
hiosolids applications were not quantified but are discussed <.|ualitati\ely.
I'or the water pathway. DIJP in water releases is expected to predominantly partition
into sediment and suspended particles in the water column The high-end modeled
total water column concentration of DliP for the acute human exposure scenarios
was SS5 uu I. The modeled \ alue was se\ eral orders of magnitude abo\ e any
monitored concentration likely due to conser\ati\e inputs Therefore. I-IW is
conlldent that the use of the modelled concentration to estimate risk is protectee
f or the ambient air pathway, the modeled DIJP concentrations are se\ eral orders of
maunitude abo\e any monitored concentration likely due to use of hiuh end releases
and conser\ati\e meteorological data Therefore. I-IW is conlldent that the use of
the modelled concentration to estimate risk is protectee
• Screening Ie\ el risk estimates usinu hiuh-end modeled water concentrations exceeded
the benchmark (therefore no refinement necessary) for incidental dermal contact,
incidental inuestion from swimminu. and ingestion of drinkinu water The same is true
usinu hiuh-end modeled air concentrations for inhalation of ambient air I-IW concluded
that these exposure pathways are not of concern for the ueneral population for DIJI\
• I-IW used a refined screening-lex el approach to determine that human exposure to DliP
throuuh inuestion of potentially contaminated fish is not expected to be a pathway of
concern for the ueneral population, subsistence fishers, or Tribal populations
• Dlil' is not readily found in aquatic or terrestrial oruanisms and has low
bioaccumulation and biomaunillcation potential Therefore. DliP has low potential for
trophic transfer throuuh food webs.
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1 ENVIRONMENTAL MEDIA CONCENTRATION OVERVIEW
This technical support document (TSD) accompanies th q Draft Risk Evaluation for Dibutyl Phthalate
(DBF) (U.S. EPA. 2025d). DBP is a diester of phthalic acid (CASRN 84-74-2). It is a member of the
phthalate class of chemicals that are widely used as adhesives and sealants in the construction and
automotive sectors. DBP is also commonly used in electronics, children's toys, and plastic and rubber
materials.
This draft TSD describes the use of reasonably available information to estimate environmental
concentrations of DBP in different environmental media and the use of the estimated concentrations to
evaluate exposure to the general population from releases associated with TSCA conditions of use
(COUs). EPA evaluated the reasonably available information for releases of DBP from facilities that
use, manufacture, or process DBP under industrial and/or commercial COUs as detailed in the Draft
Environmental Release and Occupational Exposure Assessment for Dibutyl Phthalate (DBP) (
2025b). Table 1-1 provides a crosswalk between COUs and occupational exposure scenarios (OESs).
Table 1-2 shows the types of releases to the environment by OES.
Table 1-1. Crosswalk of Conditions of Use to Assess Occupational
Exposure Scenarios
Life Cycle
Stage
Category
Subcategory
OES
Manufacturing
Domestic
manufacturing
Domestic manufacturing
Manufacturing
Importing
Importing
Import and repackaging
Repackaging
Laboratory chemicals in wholesale and
retail trade
Import and repackaging
Plasticizers in wholesale and retail trade
Import and repackaging
Processing as a
Intermediates in all other basic organic
chemical manufacturing
Incorporation into formulation,
mixture, or reaction product
reactant
Plasticizers in wholesale and retail trade
Incorporation into formulation,
mixture, or reaction product
Processing
Solvents (which become part of product
formulation or mixture) in all other
chemical product and preparation
manufacturing
Incorporation into formulation,
mixture, or reaction product
Solvents in soap, cleaning compound,
and toilet preparation manufacturing
Incorporation into formulation,
mixture, or reaction product
Incorporation
into formulation,
Adhesive and sealant chemicals in
construction
Incorporation into adhesives and
sealants
mixture, or
reaction product
Plasticizer (paint and coating
manufacturing; plastic material and resin
manufacturing; plastics product
manufacturing; soap, cleaning
compound, and toilet preparation
manufacturing; textiles, apparel, and
leather manufacturing
Incorporation into formulation,
mixture, or reaction product; PVC
plastics compounding; non-PVC
material compounding
Intermediates (asphalt paving, roofing,
Incorporation into formulation,
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Life Cycle
Stage
Category
Subcategory
OES
and coating materials manufacturing;
petrochemical manufacturing; rubber
product manufacturing)
mixture, or reaction product
Processing
Functional fluids (closed systems) in
printing and related support activities
Incorporation into formulation,
mixture, or reaction product
Incorporation
into articles
Plasticizer (adhesive manufacturing;
plastic product manufacturing; rubber
product manufacturing)
PVC plastics converting; non-PVC
material converting; incorporation
into adhesives and sealants
Recycling
Recycling
Recycling
Distribution
Distribution in
commerce
Distribution in commerce
Distribution in commerce
Industrial
Uses
Non-
incorporative
Solvent in Huntsman's maleic anhydride
manufacturing technology
Industrial process solvent use
activities
Solvent
Industrial process solvent use
Adhesives and
sealants
Adhesives and sealants
Application of adhesives and
sealants
Cleaning and
furnishing care
products
Cleaning and furnishing care products
Fabrication of final product from
articles
Explosive
materials
Explosive materials
Non-TSCA
Floor coverings
Floor coverings
Application of paints and coatings;
fabrication of final product from
articles
Commercial
Furniture and
furnishings not
covered
elsewhere
Furniture and furnishings not covered
elsewhere
Fabrication of final product from
articles
Uses
Inks, toner and
colorant
products
Inks, toner and colorant products (e.g.,
screen printing ink)
Application of paints and coatings
Laboratory
chemical
Laboratory chemical
Use of laboratory chemicals
Paints and
coatings
Paints and coatings
Application of paints and coatings
Personal care
products
Personal care products
Non-occupational use
Plastic and
rubber products
not covered
elsewhere
Plastic and rubber products not covered
elsewhere
Fabrication of final product from
articles
Miscellaneous
Laboratory chemical; chemiluminescent
Use of laboratory chemicals; use of
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Life Cycle
Stage
Category
Subcategory
OES
uses
light sticks; inspection penetrant kit;
lubricants;
lubricants and functional fluids;
use of penetrants and inspection
fluids
Disposal
Disposal
Disposal
Waste handling, treatment, and
disposal
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255 Table 1-2. Type of Release to the Environment by Occupational Exposure Scenario
OES"
Type of Discharge/' Air Emission,' or Transfer for Disposal'' - Data Sources''
Manufacturing
Fugitive air
Stack air
Water, incineration, or landfill
Import and repackaging
Fugitive or stack air - Toxics Release Inventory (TRI) and National Emissions
Inventory (NEI)
Land releases (includes both Resource Conservation and Recovery Act [RCRA]
Subtitle C landfills and those classified as other, underground injection, and Land
Treatment) - TRI
Surface water, direct - TRI
Surface water, indirect transfer to POTW - TRI
Surface water, indirect transfer to non-POTW - TRI
Surface water, with or without on-site treatment - Discharge Monitoring Report
(DMR)
Incorporation into
formulations, mixtures, and
reaction products
Fugitive or stack air - TRI and NEI
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI
Surface water, direct - TRI
Surface water, indirect transfer to POTW - TRI
Surface water, indirect transfer to non-POTW - TRI
PVC plastics compounding
Fugitive or stack air - TRI and NEI
Surface water, with or without on-site treatment - DMR
PVC plastics converting
Fugitive or stack air - TRI and NEI
Surface water, direct - TRI (PVC compounding as a surrogate OES)
Surface water, indirect transfer to POTW - TRI
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI (non-PVC material
manufacturing as a surrogate OES)
Non-PVC material
compounding and converting
Fugitive or stack air - TRI and NEI
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI
Surface water, direct - TRI
Surface water, indirect transfer to POTW - TRI
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OES"
Type of Discharge/' Air Emission,' or Transfer for Disposal'' - Data Sources''
Application of adhesives and
Sealants
Fugitive air
Water, incineration, or landfill
Incineration, or landfill
Application of paints and
coatings - no spray control
Fugitive air
Stack air
Wastewater, incineration, or landfill
Incineration, or landfill
Air, water, incineration, or landfill [unknown]
Application of paints and
coatings - spray control
Fugitive air
Stack air
Wastewater, incineration, or landfill
Incineration, or landfill
Application of paints,
coatings, adhesives, and
sealants
Fugitive or stack air - TRI and NEI
Industrial process solvent
use
Fugitive or stack air - TRI and NEI
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI (incorporation into
formulation, mixture, or reaction product)
Use of laboratory chemicals
- liquid
Fugitive or stack air
Wastewater, incineration, or landfill
Use of laboratory chemicals
- solid
Stack air
Air, water, incineration, or landfill [unknown]
Water, incineration, or landfill
Incineration or landfill
Use of lubricants and
functional fluids
Wastewater
Landfill
Recycling
Fuel blending (incineration)
Use of penetrants and
inspection fluids - aerosol
based
Fugitive air
Wastewater, incineration, or landfill
Use of penetrants and
inspection fluids - non-
aerosol based
Fugitive air
Wastewater, incineration, or landfill
Fabrication of final product
from articles
Fugitive or stack air, water, incineration, or landfill (dust generation from cutting,
grinding, shaping, drilling, abrading, and similar activities)
Fugitive or stack air (vapor generation from heating/plastic welding activities)
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OES"
Type of Discharge/' Air Emission,' or Transfer for Disposal'' - Data Sources''
Recycling
Fugitive or stack air - TRI and NEI (from PVC compounding and converting
OES)
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI (from Non-PVC
material manufacturing)
Surface water, with or without on-site treatment - DMR (from PVC plastics
compounding OES)
Waste handling, treatment,
and disposal
Fugitive or stack air - TRI and NEI
Land releases (includes both RCRA Subtitle C landfills and those classified as
other, underground injection, and Land Treatment) - TRI
Surface water, with or without on-site treatment - DMR
Surface water, indirect transfer to POTW - TRI
a Table 1-1 provides the crosswalk of OES to COUs
b Direct discharge to surface water; indirect discharge to non-POTW; indirect discharge to POTW
c Emissions via fugitive air or stack air, or treatment via incineration
d Transfer to surface impoundment, land application, or landfills
'' Discharge, release or emission database source(s) (i.e., TRI, DMR, or NEI). If none listed, a modeled scenario was
leveraged. See the Draft Environmental Release and Occupational Exposure Assessment for Dibutyl Phthalate (DBP)
(U.S. EPA, 2025b) for additional information on sources and model details.
Releases from all OESs were considered, but EPA focused on estimating high-end concentrations of
DBP from the largest estimated releases for its screening level assessment of environmental and general
population exposures. This means that the Agency considered the concentration of DBP in a given
environmental media resulting from the OES that had the highest release to that media compared to the
other OES(s). The OES resulting in the highest concentration of DBP varied by environmental media as
shown in Table 2-1. Additionally, EPA relied on its fate assessment to determine which environmental
pathways to consider. Details on the environmental partitioning and media assessment can be found in
the Draft Physical Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate (DBP) (
2024g). Briefly, based on DBP's fate parameters and behavior (e.g., Henry's Law constant, log Koc,
water solubility, fugacity modeling), EPA anticipates DBP to be predominantly in water and soil,
although the chemical may also be present in air and sediments. Moreover, because DBP is released to
the ambient air from industrial facilities and processes, inhalation of ambient air is a possible exposure
pathway. EPA thus quantitatively assessed concentrations of DBP in surface water, sediment, and
ambient air. Soil concentrations of DBP from land application of biosolids were not quantitatively
assessed as DBP was expected to have limited persistence potential and mobility in soils receiving
biosolids.
Environmental exposures using the predicted media concentrations of DBP are presented in Section 12.
As DBP fate and exposure from groundwater, biosolids, and landfills were not quantified, EPA
performed a qualitative assessment for all these land exposure scenarios ( 2024g).
Additionally, EPA discusses the potential DBP dietary exposures to aquatic and terrestrial organisms in
the environment in Section 12. EPA did not conduct a quantitative analysis of DBP trophic transfer, as
DBP is expected to have low bioaccumulation potential, no apparent biomagnification potential, and
thus low potential for uptake overall. For further information on the bioaccumulation and
biomagnification of DBP, please see the Draft Physical Chemistry, Fate, and Transport Assessment for
Dibutyl Phthalate (DBP) (U.S. EPA. 2024e).
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General population exposure is discussed using a risk screening approach detailed in Section 0. EPA
used a margin of exposure (MOE) approach discussed in Section 2.2 using high-end exposure estimates
(Section 2.1) to screen for potential non-cancer risks. EPA assumed that if there is no unreasonable risk
for an individual identified as having the potential for the highest exposure associated with a COU for a
given exposure pathway, then that pathway was determined not to be a pathway of concern for general
population exposure and not pursued further. If any pathways were identified as a pathway of concern
for the general population, further exposure assessments for that pathway would be conducted to include
higher tiers of modeling when available, refinement of exposure estimates, and exposure estimates for
additional subpopulations and COUs/OES.
Table 1-3 summarizes the exposure pathways assessed for the general population. For DBP, exposures
to the general population via surface water, drinking water, fish ingestion, and ambient air were
quantified, and modeled concentrations were compared to environmental monitoring data when
possible. Exposures via the land pathway {i.e., biosolids and landfills) were qualitatively assessed
because DBP is not expected to be persistent or mobile in soils. Concentrations of DBP in soil following
agricultural application of municipal biosolids were not identified during systematic review. Further
description of the qualitative and quantitative assessments for each exposure pathway can be found in
the sections linked in Table 1-3. As summarized in Table 1-3, biosolids, landfills, surface water,
drinking water, ambient air, and fish ingestion are not pathways of concern for DBP for highly exposed
populations based on the OES leading to the highest concentrations of DBP in environmental media.
Table 1-3. Exposure Pathways Assessed for General Population Screening Level Assessment
OES"
Exposure Pathway
Exposure
Route
Exposure Scenario
Pathway of
Concern''
All
Biosolids (Section 3.1)
All considered qualitatively
No
All
Landfills (Section 3.2)
All considered qualitatively
No
Manufacturing
Surface water
Dermal
Dermal exposure to DBP in surface
water during swimming (Section
5.1.1)
No
Oral
Incidental ingestion of DBP in
surface water during swimming
(Section 5.1.2)
No
Manufacturing
Drinking water
Oral
Ingestion of drinking water (Section
6.1.1)
No
Manufacturing; waste
handling, treatment,
disposal
Fish ingestion
Oral
Ingestion of fish for general
population (Section 7.1)
No
Ingestion of fish for subsistence
fishers (Section 7.2)
No
Ingestion of fish for tribal
populations (Section 7.3)
No
Waste handling,
treatment, disposal
(stack)
Ambient air
Inhalation
Inhalation of DBP in ambient air
resulting from industrial releases
(Section 9)
No
Application of paints,
coatings, adhesives,
and sealants
Oral
Ingestion from air to soil deposition
resulting from industrial releases
(Section 9)
No
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OES"
Exposure Pathway
Exposure
Route
Exposure Scenario
Pathway of
Concern''
(fugitive)
a Table 1-1 provides a crosswalk of industrial and commercial COUs to OES.
h Using the MOE approach, an exposure pathway was determined to not be a pathway of concern if the MOE was
equal to or exceeded the benchmark MOE of 30.
' Used in assessment presented in Draft Environmental Hazard Assessment for Dibutyl Phthalate (DBP) (U.S. EPA,
2024c).
306
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2 SCREENING LEVEL ASSESSMENT OVERVIEW
EPA began its DBP exposure assessment using a screening level approach that relies on conservative
assumptions. Conservative assumptions, including default input parameters for modeling environmental
media concentrations, help to characterize exposure resulting from the high-end of the expected
distribution. Most of the OESs presented in Table 1-1 report facility location data and releases in the
TRI and Discharge Monitoring Report (DMR) databases. When facility location- or scenario-specific
information are unavailable, EPA used generic EPA models and default input parameter values as
described in the Draft Environmental Release and Occupational Exposure Assessment for Dibutyl
Phthalate (DBP) ( 025b). Details on the use of screening level analyses in exposure
assessment can be found in EPA's Guidelines for Human Exposure Assessment (U.S. EPA. 2019b).
High-end exposure estimates used for screening level analyses were defined as those associated with the
industrial and commercial releases from a COU and OES that resulted in the highest environmental
media concentrations. Additionally, individuals with the greatest intake rate of DBP per body weight
were considered to be those at the upper end of the exposure distribution. Taken together, these exposure
estimates are conservative because they were determined using the highest environmental media
concentrations and greatest intake rate of DBP per kilogram of body weight. These exposure estimates
are also protective of individuals having less exposure either due to lower intake rate or exposure to
lower environmental media concentration. This is explained further in Section 2.1.
For the general population screening level assessment, EPA used an MOE approach based on high-end
exposure estimates to determine which exposure pathways were of potential concern for non-cancer
risks. Using the MOE approach, an exposure pathway associated with a COU was determined to not be
a pathway of concern if the MOE was equal to or exceeded the benchmark MOE of 30 (U.S. EPA.
2024f). Further details of the MOE approach are described in Section 2.2.
If there is no unreasonable risk for an individual identified as having the potential for the highest
exposure associated with a COU, then that pathway was determined not to be a pathway of concern. If
any pathways were identified as having potential for risk to the general population, further exposure
assessments for that pathway would be conducted to include higher tiers of modeling, additional
subpopulations, and additional OES/COUs.
2.1 Estimating High-End Exposure
General population exposures occur when DBP is released into the environment and the environmental
media is then a pathway for exposure. As described in the Draft Environmental Release and
Occupational Exposure Assessment for Dibutyl Phthalate (DBP) (U. c< H1 \ 202 '¦) and summarized in
Table 1-1 releases of DBP are expected to occur to air, water, and land. Figure 2-1 provides a graphical
representation of where and in which media DBP is expected to be found due to environmental releases
and the corresponding route of exposure.
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I a
Ambient Air
Inhalation
Landfills
(Industrial or
Muncipal)
Bathing
_ . Water
u"," Dermjt.
*ter Inhalation
Oral
Wastewater
Facility
Dnnking
Water
Treatment
Water
Recreation
Oral. Derma/
[""Sediment ]
Figure 2-1. Potential Human Exposure Pathways for the General Population
The diagram presents the media (white text boxes) and routes of exposure (italics for oral, inhalation, or dermal)
for the general population. Sources of drinking water from surface or water pipes are depicted with grey arrows.
For a screening level analysis, high-end exposures were estimated for each exposure pathway assessed.
EPA's Guidelines for Human Exposure Assessment defined high-end exposure estimates as a "plausible
estimate of individual exposure for those individuals at the upper- end of an exposure distribution, the
intent of which is to convey an estimate of exposure in the upper range of the distribution while avoiding
estimates that are beyond the true distribution" (U.S. EPA. 2019b). If risk is not found for these
individuals with high-end exposure, no unreasonable risk is anticipated for central tendency exposures,
which is defined as "an estimate of individuals in the middle of the distribution."
Identifying individuals at the upper end of an exposure distribution included consideration of high-end
exposure scenarios defined as those associated with the industrial and commercial releases from a COU
and OES that resulted in the highest environmental media concentrations. Additionally, individuals with
the greatest intake rate of DBP per body weight were considered to be those at the upper end of the
exposure. Intake rate and body weight are dependent on lifestage as shown in Appendix A.
Table 2-1 summarizes the high-end exposure scenarios that were considered in the screening level
analysis including the lifestage assessed as the most potentially exposed population based on intake rate
and body weight. Exposure scenarios were assessed quantitatively only when environmental media
concentrations were quantified for the appropriate exposure scenario. Because DBP environmental
releases from biosolids and landfills (and therefore, resulting soil concentrations) were not quantified,
exposure from soil or groundwater resulting from DBP release to the environment via biosolids or
landfills was not quantitatively assessed. Instead, the scenarios were assessed qualitatively for exposures
potentially resulting from biosolids and landfills.
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Table 2-1. Exposure Scenarios Assessed in I
tisk Screening
OES
Exposure
Pathway
Exposure
Route
Exposure Scenario
Lifestage
Analysis
(Quantitative
or Qualitative)
All
Biosolids
All considered qualitatively
Qualitative,
Section 3.1
All
Landfills
All considered qualitatively
Qualitative,
Section 3.2
PVC plastics
compounding
Surface
water
Dermal
Dermal exposure to
DBP in surface water
during swimming
All
Quantitative,
Section 5.1.1
Oral
Incidental ingestion of
DBP in surface water
during swimming
All
Quantitative,
Section 5.1.2
PVC plastics
compounding
Drinking
water
Oral
Ingestion of drinking
water
All
Quantitative,
Section 6.1.1
PVC plastics
compounding
Fish
ingestion
Oral
Ingestion of fish for
general population
Adults and
young toddlers
(1-2 years)
Quantitative,
Section 7.1
Ingestion of fish for
subsistence fishers
Adults (16 to
<70 years)
Quantitative,
Section 7.2
Ingestion of fish for
tribal populations
Adults (16 to
<70 years)
Quantitative,
Section 7.3
Waste handling,
treatment,
disposal (stack)
Ambient air
Inhalation
Inhalation of DBP in
ambient air resulting
from industrial releases
All
Quantitative,
Section 9
Application of
paints, coatings,
adhesives, and
sealants
(fugitive)
Oral
Ingestion from air to
soil deposition
resulting from
industrial releases
Infant and
children
(6 months to
12 years)
As part of the general population exposure assessment, EPA considered fenceline populations in
proximity to releasing facilities as part of the ambient air exposure assessment by utilizing pre-screening
methodology described in EPA's Draft TSCA Screening Level Approach for Assessing Ambient Air and
Water Exposures to Fenceline Communities (Version 1.0) ( 12b). For other exposure
pathways, EPA's screening method assessing high-end exposure scenarios used release data that reflects
exposures expected to occur in proximity to releasing facilities, which would include fenceline
populations.
Modeled and monitored surface water concentrations (Section 4.1) were used to estimate oral drinking
water exposures (Section 6), incidental dermal exposures (Section 5.1.1), and incidental oral exposures
(Section 5.1.2) for the general population. Modeled ambient air concentrations (Section 8.1) were used
to estimate inhalation exposures.
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If any pathways were identified as an exposure pathway of concern for the general population, further
exposure assessments for that pathway would be conducted to include higher tiers of modeling when
available and exposure estimates for additional subpopulations and COUs.
2.2 Margin of Exposure Approach
EPA used an MOE approach using high-end exposure estimates to determine if the pathway analyzed is
a pathway of concern. The MOE is the ratio of the non-cancer hazard value (or point of departure
[POD]) divided by a human exposure dose. Acute, intermediate, and chronic MOEs for non-cancer
inhalation and dermal risks were calculated using the following equation:
Equation 2-1. Margin of Exposure Calculation
Non — cancer Hazard Value (POD)
MOE =
Human Exposure
Where:
MOE
Non — cancer Hazard Value (POD)
Human Exposure
Margin of exposure for acute, short-term, or
chronic risk comparison (unitless)
Human equivalent concentration (HEC,
mg/m3) or human equivalent dose (HED, in
units of mg/kg-day)
Exposure estimate (mg/m3 or mg/kg-day)
MOE risk estimates may be interpreted in relation to benchmark MOEs. Benchmark MOEs are typically
the total uncertainty factor for each non-cancer POD. The MOE estimate is interpreted as a human
health risk of concern if the MOE estimate is less than the benchmark MOE (i.e., the total uncertainty
factor). On the other hand, for this screening level analysis, if the MOE estimate is equal to or exceeds
the benchmark MOE, the exposure pathway is not analyzed further. Typically, the larger the MOE, the
more unlikely it is that a non-cancer adverse effect occurs relative to the benchmark. When determining
whether a chemical substance presents unreasonable risk to human health or the environment, calculated
risk estimates are not "bright-line" indicators of unreasonable risk, and EPA has the discretion to
consider other risk-related factors in addition to risks identified in the risk characterization.
The non-cancer hazard values used to screen for risk are described in detail in the Draft Non-Cancer
Human Health Hazard Assessment for Dibutyl Phthalate (DBP) ( J024f). Briefly, after
considering hazard identification and evidence integration, dose-response evaluation, and weight of the
scientific evidence of POD candidates, EPA chose one non-cancer POD for acute, intermediate, and
chronic exposure scenarios (Table 2-2). Human equivalent concentrations (HECs) are based on daily
continuous (24-hour) exposure, and human equivalent doses (HEDs) are daily values.
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427 Table 2-2. Non-Cancer Hazard Values Used to Estimate Risks
Target Organ
System
Species
Du ration
POD
(mg/kg-day)
Effect
HED"
(mg/kg-day)
HEC
(mg/m3)
[|)pm|
Benchmark
MOE
Reference
Development/
Reproductive
Rat
5-14 days
throughout
gestation
BMDLs = 9
| fetal
testicular
testosterone
2.1
12
[1.0]
UFa = 3
UFh = 10
Total UF = 30
_ b
POD = point of departure; HEC = human equivalent concentration; HED = human equivalent dose; MOE = margin of
exposure; UF = uncertainty factor; BMDL5 = Benchmark dose (lower confidence limit) associated with a 5% response level
" EPA used allometric body weight scaling to the three-quarters power to derive the HED. Consistent with EPA Guidance
(TJ.S. EPA. 201 lb), the interspecies uncertainty factor (TJFa). was reduced from 10 to 3 to account remaining uncertainty
associated with interspecies differences in toxicodynamics. EPA used a default intraspecies (UFH) of 10 to account for
variation in sensitivity within human populations.
h The BMDL5 was derived through meta-regression and BMD modeling of fetal testicular testosterone data from eight studies
of DBP with rats (Gray et al. 2021; Furret al. 2014; Johnson et al. 2011; Strove et al. 2009; Howdeshell et al. 2008;
Martino-Andrade et al, 2008; Johnson et al. 2007; Kuhl et al.. 2007).
428
429 Using the MOE approach in a screening level analysis, an exposure pathway associated with a COU was
430 determined to not be a pathway of concern for non-cancer risk if the MOE was equal to or exceeded the
431 benchmark MOE of 30.
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3 LAND PATHWAY
EPA searched peer-reviewed literature, gray literature, and databases of environmental monitoring data
identified during systematic review to obtain concentrations of DBP in terrestrial land pathways {i.e.,
biosolids, wastewater sludge, agricultural soils, landfills, and landfill leachate). No monitoring data was
available from a review of government regulatory and reporting databases related to soil, landfills, or
biosolids {e.g., California Environmental Data Exchange Network [CEDEN], Water Quality Portal
[WQP]). Several academic experimental and field studies, however, have identified DBP in various
relevant compartments including leachate, activated sludge, and biosolids. EPA cannot correlate
monitoring levels from the reviewed studies with any specific releases associated with DBP TSCA
COUs. That is, EPA does not have any facility specific DBP release data since facilities do not report
releases of DBP to surface waters from TSCA COUs. As such, the present assessment of DBP exposure
via potential land pathways is qualitative in nature relying on the fate and physical-chemical
characteristics of DBP. When possible, data from the existing literature including experimental and field
data was used to support the qualitative assessment.
The monitoring studies and analysis presented in the following land pathway sections are for
informational purposes and were not used as part of the analysis for quantifying exposure estimates or
exposure risk. DBP was not anticipated to pose a substantial risk of exposure for the general population
through the biosolids or land pathways due to the low quantity of DBP released and the high sorption
causing significant retardation in either of the terrestrial system. As such, the assessments were
qualitative in nature and were not used to quantitatively determine exposure estimates. The monitoring
studies and application estimates presented here were not used as part of the analysis for quantifying
exposure estimates and are included for informational and contextual purposes.
3.1 Biosolids
The term "biosolids" refers to treated sludge that meet the EPA pollutant and pathogen requirements for
land application and surface disposal and can be beneficially recycled (40 CFR Part 503) (
1993). Biosolids generated during the treatment of industrial and municipal wastewater may be applied
to agricultural fields or pastures as fertilizer in either its dewatered form or as a water-biosolid slurry.
Biosolids that are not applied to agricultural fields or pastures may be disposed of by incineration or
landfill disposal. Landfill disposal will be discussed in further depth in Section 3.2. DBP may be
introduced to biosolids by the absorption or adsorption of DBP to particulate or organic material during
wastewater treatment. Based on the available information, the main mechanisms for the removal of DBP
in conventional municipal wastewater treatment plants are sorption to suspended organic matter,
biodegradation during activated sludge treatment, or a combination of sorption and biodegradation.
These removal mechanisms are influenced by DBP's physical-chemical properties and treatment time.
Monitoring wastewater treatment studies have reported removal ranging from 38 to 99 percent of DBP
during wastewater treatment with a representative removal of 65 to 98 percent (Wu et at.. 2019;
Salaudeen et at.. 2018a. b; Wu et at.. 1 , rani and Kazmi. 2016; Saini et at.. 2016; Trail et at.. 2014;
Huang et at.. 2013b; Shao and Ma. 2009; Rostev et at.. 2007; Peterson and Staples. 2003). The primary
removal mechanism of DBP in wastewater treatment is sorption to biosolids, with up to 90 percent of
removal due to sorption (Wu et at.. 2019; Wu et at.. JO I ; Gani and Kazmi. 2016; Huang et at.. 2013b;
Shao and Ma. 2009; Peterson and Staples. 2003). The STPWIN™ model in EPI Suite™ predicts 56
percent removal of DBP removal in wastewater treatment with 55.5 percent of removal (out of 56
percent overall removal) resulting from sorption to activated sludge and solids assuming negligible
biodegradation (U.S. EPA. 2017a). However, STPWIN™ is conservative estimate of overall removal
and may underestimate overall DBP removal across in wastewater treatment plants depending on the
specific technologies and processes implemented.
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Overall removal of DBP from various wastewater treatment plant trains ranged from 38 to over 99
percent (Tomei et ai. 2019; Salaudeen et ai. 2018a. b; Wu et ai. 2017; Gani and Kazmi. 2016; Saini et
ai. 2016; Trail et ai. 2014; Huang et ai. - 01.'h; c.Ikio and Ma. 2009; Roslev et ai. 2007; Peterson and
Staples. 2003). A survey of 50 wastewater plants in the United States saw a median removal of DBP
ranging from 68 to 98 percent ( 82). Approximately 27 to 59 percent of the overall removal
was attributed to biodegradation during primary and secondary treatment while the remainder of the
DBP removed being the result of adsorption or absorption to biosolids and organic matter (Salaudeen et
ai. 2018a. b; Wu et ai. 2017; Tran et ai. JO I i; Huang et ai. 2013b; Shao and Ma. 2009; Peterson and
Staples. 2003). See the Draft Physical Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate
(DBP) for additional detail regarding DBP wastewater treatment and removal ( )24g).
DBP has been identified in several U.S.-based and international surveys of wastewater sludge,
composted biosolids, and otherwise stabilized biosolids. A 2012 survey of North American wastewater
plants (Canada and United States) identified DBP in sludge at concentrations ranging from 1.7 to 1,260
ng/g dry weight (dw) ("Ikonomou et ai. 2012). Post-aerobic treatment (e.g. aerobic, anaerobic digestion)
of activated sludges may reduce the concentration of DBP (100% removal) and other phthalates (11-
100% removal) in treated biosolids, however, current research is limited to a single 2019 study (Tomei
etai. 2019).
No U.S.-based studies were identified evaluating the effects land application of DBP-containing
biosolids. Sludge and biosolids containing DBP have not been reported for use in surface land disposal
or agricultural application. As such, no data was identified directly evaluating the fate, persistence,
degradation, or exposure profiles of DBP in soil resulting from land application.
DBP is not expected to be persistent in topsoil if it is applied to land through biosolids applications.
Several academic studies have reported on degradation of DBP in aerobic soils. The half-life of DBP in
aerobic soils range from less than 1 to 19 days (Cheng et ai. 2018; Zhao et ai. 2016; Yuan et ai. 2011;
Xu et ai. 2008; Wang et ai. 1997; Russell et ai. 1985; Shanker et ai. 1985). In mixed aerobic and
anaerobic conditions in which oxygen or terminal electron acceptors may not be readily replaced, the
degradation of DBP may be slower. Current research suggests that the half-life of DBP may be extended
to as long as 65 days under evolving aerobic conditions (Inman et ai. 1984). In strictly anaerobic soil
conditions, DBP appears to degrade under comparable rates to aerobic or evolutionary conditions with
half-lives reported from 19 to 36 days (Shanker et ai. 1°K\ tinman et ai. 1984).
Other sources of DBP in biosolids-amended soils may include atmospheric deposition to soil. While
long-range transport and deposition of DBP in the atmosphere has not been directly monitored, Net et ai
(Net et ai. 2015) noted possible atmospheric deposition of similar phthalates in agricultural settings. A
2008 study noted concentrations up to 1,173 ng/L of DBP in precipitation samples (Peters et ai. 2008)
while a 2010 study on atmospheric deposition of phthalates notes bulk wet and dry deposition of DBP
and other phthalates from the atmosphere (Zeng et ai. 2010).
DBP present in soil through the application of biosolids or otherwise introduced to topsoil has limited
mobility within the soil column. Due to the tendency of DBP to sorb strongly to organic media and soil
(log Kow = 4.5; log Koc = 3.14-3.94), potential leaching is limited. Any leaching which does occur in
the uppermost soil layers will sorb to soil lower in the column and show minimal potential to interact
with groundwater systems. DBP is not readily taken up by agricultural crops or cover crops planted in
soils fertilized with biosolids. One study evaluating the potential for DBP to be taken up by crops
observed the largest concentrations of DBP on the surface of crops caused by the volatilization of DBP
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from soil particulate and subsequent deposition onto the surface of plant shoots and leaves (Muller and
Kordi [). Exposed plants do not readily absorb DBP from the soil nor do they incorporate DBP
into the roots, shoots, leaves, or fruiting bodies (Muller and Kordet. 1993). DBP can be present on the
surface of any plants growing in the vicinity resulting from localized atmospheric deposition of DBP
blown up by the wind or volatizing out of the top layer of soil. While possible, no studies identified thus
far in systematic review have reported that DBP is susceptible to longer range atmospheric transport
resulting in land application of DBP containing biosolids beyond the immediate region of initial
application.
Concentrations of DBP in soil following agricultural application of municipal biosolids were not
identified in any monitoring databases, release databases, or in a survey of the existing literature
identified during systematic review. As such, DBP concentrations in soil were estimated using the
concentrations identified in sludge, ranging from 1.7 to 1,260 ng/g dvv (Ikonomon et al. 2012).
Biosolids application rates and frequencies were selected using EPA's recommendation to the public in
the Land Application of Biosolids (
Table 3-1) (U.S. EPA. 2000a). Annual application rates ranged from 2 to 100 tons of dry biosolids per
application per acre, with frequency ranging from three times a year to once every 5 years.
Table 3-1. Typical Biosolids Application Scenarios
Vegetation
Application Frequency
(year1)
Application Rate
(tons/acre)
Corn
1
5-10
Small grain
1-3
2-5
Soybeans
1
2-20
Hay
1-3
2-5
Forested land
0.2-0.5
5-100
Range land
0.5-1
2-60
Reclamation sites
1
60-100
Soil surface concentrations and incorporated concentrations were calculated from the minimum and
maximum recommended application rates for each agricultural crop cover (Table 3-2). Minimum (1.7
ng/g) and maximum (1,260 ng/g) concentrations of DBP in biosolids were selected from the observed
concentrations in biosolids during the 2008 EPA National Sewage Survey ( 309).
Table 3-2. Estimated DBP Soil Concentrations Following Applicai
tion of Biosolids
Crop
Sludge
Concentration
(mg/kg)"
Application
Rate
(kg/acre)h
Frequency
(year-1)b
Surface
Concentration
(mg/m2)
Topsoil
Concentration
(mg/kg)
Corn
1.7
5,080
1
0.00
0.000
Corn
1.7
10,161
1
0.00
0.000
Corn
1260
5,080
1
1.58
0.01
Corn
1260
10,161
1
3.16
0.01
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Crop
Sludge
Concentration
(mg/kg)"
Application
Rate
(kg/acre)h
Frequency
(year-1)b
Surface
Concentration
(mg/m2)
Topsoil
Concentration
(mg/kg)
Hay
1.7
2,032
1
0.00
0.000
Hay
1.7
5,080
3
0.01
0.000
Hay
1,260
2,032
1
0.63
0.00
Hay
1,260
5,080
3
4.75
0.02
Small grains
1.7
2,032
1
0.00
0.000
Small grains
1.7
5,080
3
0.01
0.000
Small grains
1,260
2,032
1
0.63
0.00
Small grains
1,260
5,080
3
4.75
0.02
Soybeans
1.7
5,080
1
0.00
0.000
Soybeans
1.7
20,321
1
0.01
0.000
Soybeans
1,260
5,080
1
1.58
0.01
Soybeans
1,260
20,321
1
6.33
0.03
a Tameted National Sewage Sludge Survey Sampling and Analysis Technical Report CU.S. EPA, 2009).
b EPA Recommended Application Rates were taken from EPA 832-F-00-064, Biosolids
Technology Fact Sheet: Land Application of Biosolids CU.S. EPA. 2000a).
c Recommended incorporation depth of 7 inches (18 cm) as outlined in 40 CFR Part 503.
d An average topsoil bulk density value of 2,530 lb/yd3 (1,500 kg/m3) was selected from NRCS Soil
Quality Indicators (USD A. 2008).
Using the generic application scenarios and biosolids concentrations collected from national surveys, the
typical concentration of DBP in biosolids may range by several orders of magnitude depending largely
on the source material and method of application. The surface loading rate for spray or near surface
injection applications range from 9xl0~5 to 6.3 mg/m2 while mixing applications (assuming a 7-inch
tilling depth) may range from 3><10~6 to 0.03 mg/m3—depending on the application rate, frequency, and
applied biosolids concentration.
Once in the soil, DBP is expected to have a high affinity to soil and sediment (log Koc = 3.14-3.94) and
organic media (log Kow = 4.5), which would limit mobility from biosolids or biosolid amended soils.
Similarly, high sorption to particulate and organics would likely lead to high retardation which would
limit infiltration to and mobility within surrounding groundwater systems. DBP is slightly soluble in
water (11.2 mg/L) and does have limited potential to leach from biosolids and infiltrate into deeper soil
strata. Since DBP does have high hydrophobicity and a high affinity for soil sorption, it is unlikely that
DBP will migrate from potential biosolids-amended soils via groundwater infiltration. DBP has been
detected in surface runoff originating from landfills containing DBP PARC. , ). However, the
limited mobility and high sorption to soil suggests that infiltration of such stormwater runoff would be
of minimal concern to deeper groundwater systems.
There is limited information available related to the uptake and bioavailability of DBP in land applied
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soils. DBP's solubility and sorption coefficients suggest that bioaccumulation and biomagnification will
not be of significant concern for soil-dwelling organisms. Similarly, no studies were identified
evaluating the bioaccumulation potential of DBP. Based on the solubility (11.2 mg/L) and
hydrophobicity (log Kow = 4.5; log Koc = 3.14-3.94), DBP is not expected to have potential for
significant bioaccumulation, biomagnification, or bioconcentration in exposed organisms. Studies
evaluating the uptake of DBP into crops planted in DBP containing soils found that DBP was not found
in any of the plant tissues {i.e., roots, shoots, leaves) resulting from uptake via soil or water. DIBP, a
DBP isomer, was found, however, on the surface of the plants due to localized atmospheric transport
and deposition but is not readily absorbed by plants directly through the soil (Muller and Kordet. 1993).
BAF and BCF were modeled using the BCFBAF™ model in EPI Suite™ with an estimated log BCF
ranging from 2.02 to 2.35 (upper-lower trophic levels) and log BAF ranging from 2.20 to 2.37 (upper-
1 ower trophi c 1 evel s) ( ).
There is limited measured data on concentrations of DBP in biosolids or soils receiving biosolids, and
there is uncertainty that concentrations used in this analysis are representative of all types of
environmental releases. However, the high-quality biodegradation rates and physical and chemical
properties suggest that DBP will have limited persistence potential and mobility in soils receiving
biosolids.
3.1.1 Weight of Scientific Evidence Conclusions
There is considerable uncertainty in the applicability of using generic release scenarios and wastewater
treatment plant modeling software to estimate concentrations of DBP in biosolids. There is currently no
direct evidence that biosolids containing DBP are being consistently applied agricultural fields in any
part of the United States. However, this may be due to lack of testing and monitoring data, as DBP has
been identified in various wastewater sludges as previous stated. There is currently limited evidence that
biosolids containing appreciable concentrations of DBP is being incorporate into soils for agricultural or
disposal purposes. Consequentially, while theoretically possible, there is currently no direct, observed
evidence demonstrating the update of DBP from soil into plants in a manner which would cause
significant exposure to those individuals consuming or coming into contact with such plants. However,
the lack of direct observations does not filter out the possibility of such an exposure mechanism, but
instead reflects the limited data available for DBP in stabilized biosolids and its land application to soil.
Additionally, there is uncertainty in the relevancy of the biosolids monitoring data to the COUs
considered in this evaluation. However, due to the high confidence in the biodegradation rates and
physical and chemical data, there is robust confidence that DBP in soils will not be mobile and will have
low persistence potential. The existing literature suggests that DBP present in biosolid amended soils
will likely not be absorbed by any plants or crops growing in the soil. While field and experimental data
are limited, soil dwelling organisms may be exposed to DBP through soils which have been amended
with DBP containing biosolids applied as fertilizers but are not expected to readily accumulate DBP
through ingestion or absorption.
3.2 Landfills
For this assessment, landfills will be considered to be divided into two zones: (1) "upper-landfill" zone
with typical environmental temperatures and pressures {i.e., 1 atm, 20-25 °C, aerobic conditions), where
biotic processes are the predominant route of degradation for DBP; and (2) "lower-landfill" zone where
elevated temperatures and pressures exist, and abiotic degradation is the predominant route of
degradation. In the upper-landfill zone where oxygen might still be present in the subsurface, conditions
may still be favorable for aerobic biodegradation. However, photolysis is not considered to be a
significant source of degradation in this zone. In the lower-landfill zone, conditions are assumed to be
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anoxic, and temperatures present in this zone are likely to inhibit aerobic and anaerobic biodegradation
of DBP. Temperatures in lower landfills may be as high as 70 °C; At temperatures at and above 60 °C,
biotic processes are significantly inhibited and are likely to be completely irrelevant at 70 °C (Huang et
ai. 2013a). Hydrolysis may still degrade DBP in the lower landfill even with the elevated temperatures.
Photolysis, however, will only impact degradation on the outermost surface of the landfill where DBP
may be exposed to sunlight prior to daily capping. Once the daily cap has been applied, the lack of light
penetration would prevent further photolysis.
DBP may be deposited into the landfill through various waste streams including consumer waste,
residential waste, industrial waste, and municipal waste—including dewatered wastewater biosolids. No
studies were identified in systematic review determining the concentration of DBP in waste entering
landfills in the United States. A 1997 study of German refuse, however, identified phthalates in
residential refuse; DBP was identified in residential refuse with the highest concentrations of DBP
present in compound materials (e.g., plastic products) (610-2,160 (J,g/g) and other plastics (36-763 i-ig/g)
(Bauer and Herrmann. 1997). All other tested fractions (Food waste, paper, cardboard, plastic films,
textiles, compound packaging, and diapers) had DBP contents ranging from 1.8 to 121 ng/g (Bauer and
Herrmann. 1997). Combined, refuse contained approximately 1 1.4 to 105 |ag of DBP per gram waste.
Several facilities have reported annual releases of DBP to landfill facilities through the TRI. Major
OESs include Repackaging into large and small containers, Incorporation into formulation, mixture, or
reaction product, non-PVC material manufacturing (compounding or converting), and waste handling,
treatment, and disposal. Waste handling, treatment, and disposal makes up the majority of OESs
contributing to DBP releases, sixty percent of contributing facilities (12 of 20) and 85 percent of overall
contributions (by mass). DBP releases to Resource Conservation and Recovery Act (RCRA) Subtitle C
landfills include 265,000 kg (on-site) and 54,500 kg (off-site) annually. Approximately 91,000 kg are
released annually to other off-site landfills (U.S. EPA. 2025b).
One of the potential disposal methods for biosolids following stabilization is landfilling. and contribute
to the presence of DBP in landfills. No data directly measuring DBP in dewatered or stabilized biosolids
was identified during systematic review. A 2012 survey of North American wastewater plants (Canada
and United States), however, identified DBP in sludge at concentrations ranging from 1.7 to 1,260 ng/g
dvv (Ikonomou et ai. 2012). Beyond North America, DBP has been identified in sludge at various
concentrations in wastewater plants located in China (Zhu et ai. 2019; Mens et ai. 2014).
DBP is capable of leaching from bioreactors simulating landfill conditions using residential waste. One
1997 study evaluating a variety of phthalates, including DBP, estimated a leaching potential over 90
days using 50 kg of unaltered refuse. The refuse leached 1.1 g of total phthalates per 1 ton of refuse with
DBP making up approximately 6.0 to 6.7 percent of total phthalates (66 to 74 mg of DBP per 1 ton of
residential refuse) (Bauer and Herrmann. 1997). No studies have directly evaluated the presence of DBP
in leachate collected directly from landfills in situ. However, DBP is expected to have a high affinity to
particulate (log Koc = 3.14-3.94) and organic media (log Kow = 4.5), which would cause significant
retardation in groundwater and limit leaching to groundwater. Because of its high hydrophobicity and
high affinity for soil sorption, it is unlikely that DBP will migrate from landfills via groundwater
infiltration. Nearby surface waters, however, can be susceptible to DBP contamination via surface water
runoff if it is not captured before interacting with surface water.
While persistence in landfills has not been directly measured, DBP can undergo abiotic degradation via
carboxylic acid ester hydrolysis to form 2-butyl phthalate and 1 -butanol ( 2024a). DBP can
then by further hydrogenated to form phthalic acid (Huang et ai. 2013a). The phthalic acid product has
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been noted accumulate in landfills, particularly in the lower landfill, where further degradation may be
limited due to acidic conditions preventing reactions with the free aromatic acid (Huang et ai. 2013a).
Hydrolysis is not expected to be a significant degradation pathway in landfills with an estimated half-life
of 3.4 years under standard environmental conditions (at pH 7 and 20 °C) ( i).
Temperature in lower landfills, however, often exceed 70 °C in very complex matrices. In such matrices,
temperature, pressure, ionic strength, and chemical activity may all effect the hydrolysis rate of DBP.
With the very limited data available, the hydrolysis rate of DBP cannot reliably be estimated in the
complex conditions present in lower landfills. Chemical rates of reaction, in general, tend to increase as
temperature, pressure, and chemical activity increase. In both the upper and lower landfills, DBP is
shielded from light and photolysis is not considered a significant abiotic degradation pathway.
DBP may be degrade biologically; The biological degradation pathway for DBP includes the primary
degradation of DBP to a monoester form, such as 2-butyl phthalate, followed by hydrogenation to
phthalic acid; Phthalic acid may ultimately be degraded to CO2 and/or CH4 under aerobic or anaerobic
conditions, respectively (Huang et ai. 2013a). In the lower landfill, high temperatures (>60 °C) and low
water content can partially or completely inhibit biological degradation (Huang et ai. 2013a). Aerobic
and anaerobic degradation of DBP, however, has not been directly measured in landfills. Aerobic
degradation of DBP; however, has been measured experimentally. DBP is readily degradable in aerobic
soil conditions with a half-life ranging less than 4 hours to 19 days (Cheng et ai. 2018; Zhao et ai.
2016; Yuan et ai. 2011; Xu et ai. 2008; Wang et ai. 1997; Russell et ai. 1985; Shanker et; 5).
DBP might also degrade under anaerobic conditions such as those that would exist in lower landfills.
Anaerobic biodegradation of DBP in soil has been measured with a half-life extending up to 65 days
(Shanker et ai. 1985; Inman et ai. 1984). DBP can be more persistent in areas with high leachate
production, such as in the lowest sections of the lower landfill, where temperature, pressure, pH, and
ionic strength may exceed bacteria's habitable zones thereby limiting biotic degradation of DBP (Huang
et ai. 2013a).
DBP's sorption coefficients suggest that bioaccumulation and biomagnification will not be of significant
concern for soil-dwelling organisms adjacent to landfills. DBP is not expected to have potential for
significant bioaccumulation, biomagnification, or bioconcentration in exposed organisms. Studies
evaluating the uptake of DBP into crops planted in DBP containing soils found that DBP was not found
in any of the plant tissues {i.e., roots, shoots, and leaves) resulting from uptake via soil or water. DBP
was found, however, on the surface of the plants due to localized atmospheric transport and deposition,
but it is not readily absorbed by plants directly through the soil (Mutter and Kordel. 1993).
BAF and BCF were modeled using the BCFBAF™ model in EPI Suite™ with an estimated log BCF
ranging from 2.02 to 2.35 (upper-lower trophic levels) and log BAF ranging from 2.20 to 2.37 (upper-
1 ovver trophic levels) ( :017a).
3.2.1 Weight of Scientific Evidence Conclusions
There is uncertainty in the relevancy of the landfill leachate monitoring data to the COUs considered in
this evaluation. While there is evidence that DBP is present in refuse and may be present in biosolids
disposed of in a landfill, the examined refuse did not originate in United States and is from 1997.
Although the data demonstrates that DBP might exist in and leach from landfill refuse, there is
uncertainty as to if the presented study accurately reflects the current state of refuse and landfill DBP
with respect to landfills operating within the United States.
Based on the biodegradation and hydrolysis data for conditions relevant to landfills, there is high
confidence that DBP will be persistent in landfills. There is currently no direct evidence that the general
populus or surrounding fauna have been directly exposed to DBP through refuse or waste disposed of
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717 through landfills. Although possible, there has been no data to suggest that DBP is present in
718 environmental compartment adjacent to landfills as the direct result of landfill operations.
719
720 Overall, due to high-quality physical and chemical property data, there is robust confidence that DBP is
721 unlikely to be present in landfill leachates. The existing literature suggests that if DBP is disposed of in a
722 landfill, it will likely not be absorbed by any nearby plants. Although experimental data are limited, the
723 available data does not support the likelihood that soil dwelling organisms will be exposed to DBP, nor
724 does it show that DBP will accumulate in landfills as a result of the disposal of biosolids or refuse.
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4 SURFACE WATER CONCENTRATION
EPA searched peer-reviewed literature, gray literature, and databases of environmental monitoring data
to obtain concentrations of DBP in surface water and aquatic sediments. Although the available
monitoring data were limited, DBP was found in detectable concentrations in ambient surface waters,
finished drinking water, and in aquatic sediments. TSCA industrial releases of DBP to surface waters
were reported to EPA via the TRI and DMR databases and are described in Draft Environmental
Release and Occupational Exposure Assessment for Dibutyl Phthalate (DBP) ( 025b). The
Agency conducted modeling of industrial releases to surface water to assess the expected resulting
environmental media concentrations from TSCA COUs presented in Table 1-1. Section 4.1 presents
EPA modeled surface water concentrations and modeled sediment concentrations. Section 4.2.1 includes
a summary of monitoring concentrations for ambient surface water, and Section 4.2.2 includes
monitoring concentrations for sediment found from the systematic review process.
4.1 Modeling Approach for Estimating Concentrations in Surface Water
EPA conducted modeling using the EPA's Variable Volume Water Model (VVWM) in Point Source
Calculator (PSC) tool ( ) to estimate surface water and sediment concentrations of DBP
resulting from TSCA COU releases. PSC inputs include physical and chemical properties of DBP {i.e.,
Kow, Koc, water column half-life, photolysis half-life, hydrolysis half-life, and benthic half-life) and
reported or estimated DBP releases to water ( 25b), which are used to predict receiving
water column concentrations and partitioning to pore water and sediment in the benthic region of
streams.
Site-specific parameters influence how partitioning occurs over time. For example, the concentration of
suspended sediments, water depth, and weather patterns all influence how a chemical may partition
between compartments. However, the physical and chemical properties of the chemical itself also have
major influences on partitioning and half-lives in aqueous environments. DBP has a log Koc range of
3.14 to 3.94, indicating a high potential to sorb to suspended solids in the water column and settled
sediment in the benthic environment ( ).
Physical, chemical, and environmental fate properties selected by EPA for this assessment were applied
as inputs to the PSC model (Table 4-1). Selected values are described in detail in the Draft Physical
Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate (DBP) ( 24g). The PSC
Model relies on the Heat of Henry parameter, which was estimated from temperature variation of the
Henry's Law constant calculated by HENRY WIN™ in EPI Suite™ ( ZOlSbY
Table 4-1. PSC Model Inputs (Chemical Parameters)
Parameter
Value
Koc
4,898 mL/g
Water Column Half-Life
10 days at 25 °C
Photolysis Half-Life
1.15 days at 30N
Hydrolysis Half-Life
8,030 days at 25 °C
Benthic Half-Life
2.9 days at 25 °C
Molecular Weight
278.35 g/mol
Vapor Pressure
0.0000201 torr
Water Solubility
11.2 mg/L
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Parameter
Value
Henry's Law Constant
0.00000181 atmm3/mol
Heat of Henry
74,826 J/mol
Reference Temp
25 °C
a For details on selected values, see Draft Physical Chemistry, Fate, and Transport Assessment
for DibutvlPhthalate (DBP) (U.S. EPA. 2024s).
A common setup for the model environment and media parameters was applied consistently across all
PSC runs. The standard EPA "farm pond" waterbody characteristics were used to parameterize the water
column and sediment parameters (Table 4-2), which is applied consistently as a conservative screening
scenario. Standardized waterbody geometry was also applied consistently across runs, with a
standardized width of 5 m, length of 40 m, and depth of 1 m. Only the release parameters (daily release
amount and days of release) and the hydrologic flow rate were changed between model runs for this
chemical to reflect facility-specific release conditions.
Table 4-2. Standard EPA "Farm Pond" Waterbody Characteristics for PSC Model Inputs
Parameter
Value
DFAC (represents the ratio of vertical path lengths to depth as defined in EPA's
exposure analysis modeling svstem [EXAMS] (U.S. EPA, 2019c))
1.19
Water column suspended sediment
30 mg/L
Chlorophyll
0.005 mg/L
Water column foc (fraction of organic carbon associated with suspended sediment)
0.04
Water column dissolved organic carbon (DOC)
5.0 mg/L
Water column biomass
0.4 mg/L
Benthic depth
0.05 m
Benthic porosity
0.50
Benthic bulk density
1.35 g/cm3
Benthic foc
0.04
Benthic DOC
5.0 mg/L
Benthic biomass
0.006 g/m2
Mass transfer coefficient
0.00000001 m/s
A required input for the PSC model is the hydrologic flow rate of the receiving water body. For facilities
reporting releases to TRI, relevant flow data from the associated receiving waterbody were collected.
Databases that were queried to estimate a flow rate include EPA's Enforcement and Compliance History
Online (ECHO) that contains facilities with a National Pollutant Discharge Elimination System
(NPDES) permit, National Hydrography Dataset Plus (NHDPlus), and NHDPlus V2.1 Flowline
Network Enhanced Runoff Method (EROM) Flow. The complete methods for retrieving and processing
flow data are detailed in Appendix B. For OESs where releases were estimated using a generic scenario,
there were no reported data from available sources (e.g., TRI and DMR). Without TRI and DMR data,
EPA cannot identify the receiving water bodies and their location-specific hydrological flow data. Thus,
the Agency generated a distribution of flow metrics by collecting flow data for facilities across a North
American Industry Classification System (NAICS) code associated with each COU for a DIBP-releasing
facility. Databases that were queried to develop the distribution include EPA's ECHO, which includes
facilities with an NPDES permit, as well as NHDPlus and NHDPlus V2.1 EROM Flow. Although this
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modeled distribution of hydrological flow data is specific to an industry sector rather than a facility, it
provides a reasonable estimate of the distribution of location-specific values. The complete methods for
retrieving and processing flow data by NAICS code are also provided in Appendix B.
Different hydrological flow rates were used for different exposure scenarios. The 30Q5 flows {i.e., the
lowest 30-day average flow that occurs in a 5-year period) are used to estimate acute, incidental human
exposure through swimming or recreational contact. The annual average flow represents long-term flow
rates, but a harmonic mean provides a more conservative estimate and is preferred for assessing
potential chronic human exposure via drinking water. The harmonic mean is also used for estimating
human exposure through fish ingestion because it takes time for chemical concentrations to accumulate
in fish. Lastly, for aquatic or ecological exposure, a 7Q10 flow {i.e., the lowest 7-day average flow that
occurs in a 10-year period) is used to estimate exceedances of concentrations of concern for aquatic life
(I £007). The regression equations for deriving the harmonic mean and 7Q10 flows are
provided in Appendix B. Hydrologic flows in the receiving waterbodies were added to facility effluent
flows as the rate of effluent contributes a substantial amount of flow to receiving waterbodies in many
cases. The median, 75th percentile, and 90th percentile (P50, P75, P90, respectively) flows from the
distribution were applied to represent variation in the potential receiving waterbodies for OESs in which
releases were estimated using generic scenarios.
Manufacturing OES was chosen as an appropriate OES for a screening level assessment based on it
resulting in a conservatively high surface water concentration based on high volumes of releases paired
with an assumption of a low flow (P50) in the receiving water body, with environmental concentrations
exceeding those estimated in all other OES. Additionally, the generic release scenario for the
Manufacturing OES estimates a combined release to wastewater, incineration, or landfill. Because the
proportion of the release from Manufacturing OES to just surface water could not be determined from
reasonably available information, and the discharge as wastewater includes the possibility of direct
discharge without further treatment, for screening purposes EPA assumed that all of the release would
be directly discharged to surface water, to represent an upper-bound of surface water concentrations.
The tiered exposure approach utilized the highest resulting environmental concentrations from this
release scenario as the basis of a screening analysis for general population exposure. Table Table 4-3
and Table 4-4 presents the surface water concentrations associated with the Manufacturing OES
modeled with median, 75th percentile, and 90th percentile (P50, P75, P90, respectively) flows. The
hydrologic flow distribution for the generic scenario was developed from receiving waterbody flows
from relevant facilities with NPDES permits, and this process is described in more detail in
13.4Appendix B.
Although Manufacturing OES was utilized for screening purposes, EPA prioritized use of programmatic
data with actual release data from reporting facilities where overall confidence in the estimates would be
higher. For estimating surface water concentrations from releases, the Agency prioritized the use of TRI
annual release reports over DMR monitoring data, reviewing DMR period data as supporting
information for the releases reported to TRI. Therefore, EPA estimated surface water concentrations
from Waste handling, treatment, and disposal OES that had release data collected from TRI and DMR
databases. Surface water concentrations associated with Waste handling, treatment, and disposal OES
are presented in Table 4-3 and Table 4-4.
Receiving water body DBP concentrations were estimated at the point of release {i.e., stream DBP
concentration at the location where DBP-containing effluent is discharging). Release data were collected
from TRI and DMR databases, which represent effluent loading after any on-site treatment; therefore, no
further treatment or removal is estimated in this high-end release estimate screening assessment. For
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releases estimated using generic scenarios, EPA also assumed no treatment or removal for a high-end
release estimate screening assessmnt. Due to the partitioning of the compound to solids (in addition to
some expected biodegradation), wastewater treatment is expected to be effective at removing DBP from
the water column prior to discharge, with treated effluent showing up to a 96.6 percent reduction in one
study (Trail et at.. 2014). and an EPA review finding a typical removal efficiency of 68 percent (U.S.
EPA. 19821
Release modeling values shown in Table 4-3 are carried through to the ecological risk assessment for
further evaluation as a conservative high-end approach to screen for ecological risk as discussed in the
Draft Environmental Hazard Assessment for Dibutyl Phthalate (DBP) ( 324c), following the
screening approach as described in Section 5.3.1 of the Draft Risk Evaluation for Dibutyl Phthalate
(DBP) (U.S. EPA. 2Q25dY
Table 4-3. PSC Modeling Results for Water and Benthic Sediment Using 7Q10 Flow
OES
Number of
Operating
Days Per
Year
Daily
Release
Flow
Distribution
Percentile h
7Q10
Total Water
Column
7Q10
Benthic Pore
Water
7Q10
Benthic
Sediment
(kg/day)"
Concentration
Concentration
Concentration
(^g/L)
(^g/L)
(mg/kg)
Waste handling,
N/A (Reported
14.40
6.01
0.335
treatment, and
286
0.043
water body flow
disposal (TRI-
reported release)
obtained from
NHDPlus)
Manufacturing
P50
1,160
484.0
27
(generic
multimedia
release)
300
43
P75
67.8
28.2
1.58
P90
4.00
1.67
0.093
Application of
P50
920
383
21.4
paints and coatings
(no spray control)
(generic
multimedia
P75
53.6
22.3
1.25
287
34
P90
3.17
1.32
0.074
release)
Use of lubricants
P50
703
34.20
1.91
and fluids (generic
4
26
P75
41
2.61
0.146
wastewater
release)
P90
2.42
0.12
0.0066
a Details on operating days and daily releases are provided in the Draft Environmental Release and Occupational
Exposure Assessment for Dibutyl Phthalate (DBP) (U.S. EPA, 2025b)
b The P50, P75, and P90 flows refer to the 50th, 75th, and 90th percentiles of the distribution of water body flow rates
in generic release scenarios; see Appendix B.
For the purpose of a screening analysis as described in Section 2, EPA modeled high-end surface water
concentrations using releases associated with OESs leading to the highest surface water concentrations.
The OES with the highest total water column concentrations (Manufacturing) was additionally run under
harmonic mean and 30Q5 flow conditions. Surface water concentrations shown in Table 4-4 are carried
through to the human health risk assessment for further evaluation as a conservative high-end approach
to screen for human health risk as discussed in the screening approach detailed in Section 2.
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Table 4-4. PSC Modeling Results for Total Water Column Using Harmonic Mean Flow and 30Q5
Flow
OES
Flow
Distribution
Percentile h
Release
Estimate
(kg/day)"
Harmonic
Mean
Flow
(m3/d)
30Q5 Flow
(m3/d)
Harmonic
Mean
Concentration
(^g/L)
30Q5
Concentration
(^g/L)
Manufacturing
(generic
multimedia
release)
P50
43
69,800
13,821
616.0
885.0
P75
43
1,763,000
926,000
24.4
46.6
P90
43
25,240,000
14,320,000
1.7
3.0
Waste handling,
treatment, and
disposal (TRI
reported
release)
N/A (Reported
water body
flow obtained
from
NHDPlus)
0.132
9,139
9,139
14.5
14.5
a Details on operating days and daily releases are provided in the Draft Environmental Release and
Occupational Exposure Assessment for Dibutvl Phthalate (DBP) (U.S. EPA, 2025b)
b The P50, P75, and P90 flows refer to the 50th, 75th, and 90th percentiles of the distribution of water body
flow rates in generic release scenarios; see Appendix B.
4.2 Measured Concentrations
EPA identified monitoring studies through systematic review to provide context to modelling results.
The monitoring studies presented here were not used as part of the analysis for quantifying exposure
estimates. Measured concentrations of DBP in surface water and sediment are presented in Section 4.2.1
and 4.2.2, respectively.
4,2,1 Measured Concentrations in Surface Water
A total of three references were identified from the United States that reported DBP in surface water
fNWOMC. 2021; Li et al. I , Liuetal.. 2013) (Table 4-5). EPA STOrage and RETrieval (STORET)
data were obtained through the Water Quality Portal (WQP), which houses publicly available water
quality data from the U.S. Geological Survey (USGS), EPA, and state, federal, Tribal, and local
agencies (NWQMC. 2021). Since 2004, the maximum level reported in water was 40 |ig/L. Where the
media subdivision was specified as surface water, the maximum level reported was 8.2 |ig/L.
In March 2008 through June 2009, Liu et al. (2013) assessed the spatial distribution of phthalates in
Lake Pontchartrain, LA, before, during, and after the opening of the Bonnet Carre Spillway that
occurred April to May 2008. Forty-two freshwater samples were collected from the Bonnet Carre
Spillway at 6 sites located about 1 mile apart. DBP was detected in 95 percent of these samples with
concentrations ranging from nondetect to 5.9 |ig/L. Fifty-four samples were also collected from the
central lake area at 6 sites located near Lake Maurepas to the Causeway Bridge, with 1 site near the
Manchac Pass. DBP was detected in 80 percent of these samples with concentrations up to 3.9 |ig/L.
For the central lake area, authors reported that concentrations of phthalates, including DBP, were close
to zero before opening of the spillway, increased significantly after opening of the spillway, and dropped
back down to almost zero 1 year following the spillway opening. For the Bonnet Carre Spillway area,
authors reported that phthalate levels were high even before the spillway opened due to freshwater flows
from the Mississippi River, but levels dropped close to zero 1 year following the spillway opening.
Samples collected in June 2009 showed phthalate increases, once again likely from a combination of
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rain/storm water, industrial discharges, and inputs from the Mississippi River (Liu et al. ).
Li et al. ( ) evaluated chemical emissions and residuals associated with the installation of UV-cured
in-place pipes (CIPPs) for stormwater culverts at three sites in Syracuse, New York, and one site in
Fairfax, Virginia. Standing water at culvert inlets and outlets, truck water, and rinse water exiting each
CIPP were sampled and analyzed at New York sites whereas truck water and rinse water were sampled
and analyzed in Virginia. A maximum DBP concentration of 12.5 |ig/L was found in rinse water at New
York Site #3. No DBP was detected in samples of truck water or rinse water in Virginia.
Four additional studies, three from France and one from South Korea, reported levels of DBP in surface
water. Valton et al. (2014) examined levels of phthalates in the Orge River, a suburban tributary of the
Seine River. The authors reported that the Orge River basin is characterized by intense human impact
associated with agricultural areas upstream and urbanized and industrialized areas downstream. They
collected freshwater samples from the outlet of the Orge River basin and found DBP at an average
concentration of 120 ng/L (0.12 |ig/L). Sampling year, number of samples, and detection frequency were
not reported.
From 2015 to 2016, Bach et al. (2020) conducted a national sampling campaign in France of drinking
water networks supplied by groundwater, surface water, or a mixture of both. As part of this sampling
campaign, 114 raw surface water samples were collected. DBP was detected once at a concentration of
768 ng/L (0.768 |ig/L).
A study conducted by Schmidt et al. (2020) in 2017 to 2018 quantified phthalate concentrations in the
Rhone River in Aries city, France. This river exports water to the Gulf of Lion, the main freshwater
source of the Mediterranean Sea. Surface water samples were collected monthly in duplicate at an arm's
length from the dock in the Rhone River. DBP was detected in all samples with a mean concentration of
32.8 ng/L (0.328 |ig/L).
From 2016 to 2017, Lee et al. (2019) assessed the seasonal and spatial distribution of phthalate esters in
air, surface water, sediments, and fish in the Asan Lake in South Korea. Asan Lake is one of the largest
artificial lakes in Korea and is mainly used for agricultural and industrial purposes and discharges to
Asan Bay. Forty-seven surface water samples were collected at 12 sampling locations. DBP was
detected in approximately 53 percent of samples at a mean concentration of 0.03 |ig/L and maximum
concentration of 0.34 |ig/L.
Table 4-5. Summary of Measured DBP Concentrations in Surface Water
Reference
Sampling Location
DBP Concentration
Sampling Notes
Water Quality Portal
(WOP) (NWOMC.
202 \y
United States
Overall: ND-40 ue/L
Maximum levels bv media
subdivision (fis/L):
26.8 (unspecified); 40
(groundwater); 8.2 (surface
water); 15 (stormwater); 14
(wastewater)
U.S. STOrage and
RETrieval (STORET)
water quality data, 2004
and after
Liu et al. (2013)
United States
Bonnet Carre Spillwav (6
locations; n = 42)
FOD: 95%
Freshwater samples from
Lake Pontchartrain, LA,
before, during, and after
opening of the Bonnet
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Reference
Sampling Location
DBP Concentration
Sampling Notes
<0.03-5.9 jig/L
Central lake area (6
locations; n = 54)
FOD: 80%
<0.03-3.9 jig/L
Carre Spillway that
occurred April/May
2008, March 2008-June
2009
Li et al. (2019)
United States
Standing water (|_is/L)
NY sites: 4.8-9.6; VA site:
not evaluated
Rinse water (ue/L)
NY sites: 6.3-12.5; VA site:
ND
Truck water (ue/L)
NY sites: 4.8-6.5; VA site:
ND
Water sampling
conducted before and
after installation of
CIPPs, including
standing water at culvert
inlets and outlets, truck
water, and rinse water,
2017
Valton et al. (2014)
France
FOD and sample number
NR
mean ± SD = 120 ± 80 ng/L
Freshwater samples from
the outlet of the Orge
River basin, date NR
Bach et al. (2020)
France
FOD = 0.88%* (n= 114),
<500-768 ng/L
LOQ = 500 ng/L
* Calculated
National screening study
to examine phthalates in
raw surface water (prior
to treatment for use as
drinking water),
November 2015-July
2016
Schmidt et al. (2020)
France
FOD 100% (n = 22)
Median, mean ± SD (range)
= 19.0, 32.8 ±31.0 (7.3-
107.7) ng/L
LOQ = 0.03 ng/L
Monthly Rhone River
samples, May 2017-
April 2018
et al. (2019)
South Korea
FOD = 53.2% (n = 47)
Mean, median (range) =
0.03, 0.01 (ND-0.34) jig/L
* A value of zero was used
for nondetects. LOD and
LOQ were 0.00 and 0.01
(ig/L, respectively.
Freshwater samples from
Asan Lake collected at 12
sampling locations,
2016-2017
FOD = frequency of detection; ND = non-detect; LOD = limit of detection; SD = standard deviation; LOQ = limit of
quantification
a Represents samples dated 2004 and after. Values where "result sample fraction" is "total," and "result status
identifier" is "final." Results presented by media subdivision if media subdivision was specified. Results may be
estimated or actual results.
921 4,2,2 Measured Concentrations in Sediment
922 EPA searched peer-reviewed literature, gray literature, and databases of environmental monitoring data
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to obtain concentrations of DBP in sediment. One reference from the United States was available. EPA
STORET sediment data (surface, subsurface, or unspecified matrices) were obtained through the WQP
(NWQMC. 2021). Since 2004, the maximum level in sediment (59,900 |ig/kg dw) came from a sample
where media subdivision was unspecified (Table 4-6).
From 2016 to 2017, Lee et al. (2019) assessed the seasonal and spatial distribution of phthalate esters in
air, surface water, sediments, and fish in the Asan Lake in South Korea. Asan Lake is one of the largest
artificial lakes in Korea and is mainly used for agricultural and industrial purposes and discharges to
Asan Bay. It is likely affected by pollution coming from an industrial complex and two nearby cities.
Forty-seven sediment samples were collected at 12 sampling locations. DBP was detected in
approximately 64 percent of samples at a mean concentration of 73.6 |ig/kg dw.
Table 4-6. Summary of Measured DBP Concentrations in Sediment
Reference
Sampling
Location
DBP Concentration
Sampling Notes
Water Quality Portal
(WOP) (NWOMC. 2021)fl
United States
Overall: 59,900 j^ig/kg dw
Maximum levels by media
subdivision (j^ig/kg):
59,900 (unspecified, dw); 6,610
(surface); 200 (subsurface, dw)
U.S. STOrage and
RETrieval (STORET)
water quality data, 2004
and after
Lee et al. (2019)
South Korea
FOD 63.8% (n = 47)
Mean, median (range) = 73.6, 13.3
(ND*-535) (ig/kg dw
* A value of zero was used for
nondetects. LOD and LOQ were
0.40 and 1.21 j^ig/kg dw, respectively
Freshwater samples from
Asan Lake collected at 12
sampling locations, 2016-
2017
dw = dry weight; FOD = frequency of detection; ND = non-detect; LOD = limit of detection; LOQ = limit of
quantification
a Represents samples dated 2004 and after. Values where "result sample fraction" is "total" and "result status
identifier" is "final." Results presented by media subdivision if media subdivision was specified. Results may be
estimated or actual results.
4.3 Evidence Integration for Surface Water and Sediment
4,3,1 Strengths, Limitations, and Sources of Uncertainty for Modeled and Monitored
Surface Water Concentration
EPA used PSC to estimate concentrations of DBP within surface water and sediment. PSC considers
model inputs of physical and chemical properties of DBP {i.e., Kow, Koc, water column half-life,
photolysis half-life, hydrolysis half-life, and benthic half-life) and allows EPA to estimate sediment
concentrations in addition to surface water concentrations. The use of physical and chemical properties
of DBP refined through the systematic review process and supplemented by EPA models increases
confidence in the application of the PSC model. A standard EPA waterbody geometry and sediment
characteristics were used to represent a consistent and conservative receiving waterbody scenario, with
chemical-specific release amounts and receiving waterbody hydrologic flow rates.
The modeled data represent estimated concentrations near actual facilities that are actively releasing
DBP to wastewater, while the measured concentrations presented above in Table 4-5 represent sampled
ambient water concentrations of DBP. However, measured concentrations are not necessarily associated
with TSCA COUs, and the source or sources of these concentrations are unknown. Furthermore, the
measured data may not represent locations where the general population may be exposed, either
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incidentally or via drinking water. Measured DBP data are included in the exposure assessment as a
point of reference and comparison with the modeled release estimates to verify that exposure estimates
from modeled releases are not underestimating environmental concentrations reported in monitoring
data. Differences in magnitude between modeled and measured concentrations may be due to measured
concentrations not being geographically or temporally close to known releases of DBP. Monitoring data
did not specifically target industrial releases and may reflect concentrations from sources not regulated
under TSCA. While monitoring data locations are known, these data were not evaluated for proximity to
known industrial releases.
Concentrations of DBP within the sediment were estimated using the highest 2015 to 2020 annual
releases and estimates of 7Q10 hydrologic flow data for the receiving water body that were derived from
the NHDPlus V2.1 EROM flow data, for the specific reach codes associated with releasing facilities as
listed on their NPDES permits. The 7Q10 flow represents the lowest 7-day flow in a 10-year period and
is a conservative approach for examining a condition where a potential contaminant may be predicted to
be elevated due to periodic low flow conditions. Flow data collected via the EPA ECHO API and the
NHDPlus V2.1 EROM flow database include self-reported hydrologic reach codes on NPDES permits
and the best available flow estimations from the EROM flow data. Additionally, a regression-based
calculation was applied to estimate flow statistics from NHD-acquired flow data, which introduces some
uncertainty. The confidence in the flow values used, with respect to the universe of facilities for which
data were pulled, should be considered moderate-to-robust, given the self-reported linkages to actual
releasing facilities.. EPA assumes that the results presented in this section include a bias toward
overestimation of resulting environmental concentrations due to conservative assumptions made in light
of the uncertainties.
Release data were collected from TRI and DMR databases for use in this assessment, as described in the
Draft Environmental Release and Occupational Exposure Assessment for Dibutyl Phthalate (DBP)
( E025b). While TRI includes total annual reported loadings, DMR reporting includes
monitoring summaries over shorter periods, such as weekly or monthly average concentrations. EPA's
Pollutant Loading Tool is used to extrapolate DMR monitoring data and estimate annual total release.
EPA reviews the period monitoring data from DMR reporting to verify annual load estimates from the
Pollutant Loading Tool. In this assessment, two releasing facilities within the Waste handling, treatment,
and disposal - POTW OES were identified as having erroneously high annual release amounts estimated
by the Pollutant Loading Tool. Inspection of the DMR period data showed reports of DBP below the
detection limit for all but one sample between the two facilities, with that single daily maximum sample
reporting a concentration of 0.28 |ig/L. Based on these records, EPA excluded the release estimates from
these two facilities from the consideration of the high-end of the Waste handling, treatment, and disposal
- POTW OES, and the next highest release was considered.
4.4 Weight of Scientific Evidence Conclusions
Modeled inputs were derived from reasonably available literature collected and evaluated through
EPA's systematic review process for this TSCA risk evaluation. All monitoring and experimental data
included in this analysis were from articles rated "medium" or "high" quality from this process.
Monitoring data demonstrate that DBP can be detected in various types of water and sediment around
the country. While monitoring data are limited and may not specifically target peak concentrations in the
environment resulting from facility effluent, environmental monitoring data show generally low
concentrations within the water column, and notable partitioning to sediment. The high-end modeled
concentrations, based on industrial release data, for surface water and sediment exceeded the highest
values available from monitoring studies by one to two orders of magnitude. This supports EPA's
approach in conducting a screening evaluation using the highest modeled DBP concentrations.
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5 SURFACE WATER EXPOSURE TO GENERAL POPULATION
Concentrations of DBP in surface water resulting from TSCA COU releases can lead to different
exposure scenarios, including dermal exposure (Section 5.1.1) or incidental ingestion exposure (Section
5.1.2) to the general population swimming in affected waters. Additionally, DBP surface water
concentrations may impact drinking water exposure (Section 6) and fish ingestion exposure (Section 7).
For the purpose of risk screening, exposure scenarios were assessed for various lifestages (e.g., adult,
youth, children) using the highest concentration of DBP in surface water based on the highest releasing
OES (PVC plastics compounding) as estimated in Section 4.1.
5.1 Modeling Approach
5.1.1 Dermal Exposure
The general population may swim in surface waters (streams and lakes) that are affected by DBP
contamination. Modeled surface water concentrations estimated in Section 4.1 were used to estimate
acute doses (ADR) and average daily doses (ADD) from dermal exposure while swimming. The
following equations were used to calculate incidental dermal (swimming) doses for adults, youth, and
children:
Equation 5-1. Acute Incidental Dermal Calculation
(SWC x Kv x SA x ET x CF1 x CF2)
ADR=- E BW "
Where:
ADR
Acute dose rate (mg/kg-day)
SWC
Surface water concentration (ppb or |ig/L)
Kp
Permeability coefficient (cm/h)
Skin surface area exposed (cm2)
ET
Exposure time (h/day)
CF 1
Conversion factor (1.0x10-3 mg/|ig)
CF2
Conversion factor (1.0xl0~3 L/cm3)
BW
Body weight (kg)
Equation 5-2. Average Daily Incidental Dermal Calculation
(SWC x Kp x SA x ET x RD x ED x CF 1 x CFZ)
ADD =
(BW x AT x CF3)
Where:
ADD = Average daily dose (mg/kg-day)
SWC = Chemical concentration in water (|ig/L)
Kp = Permeability coefficient (cm/h)
Si4 = Skin surface area exposed (cm2)
ET = Exposure time (h/day)
RD = Release days (days/year)
ED = Exposure duration (years)
BW = Body weight (kg)
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AT
CF1
CF2
CF 3
Averaging time (years)
Conversion factor (1,0/ 10 3 mg/|ig)
Conversion factor (1.0/10 3 L/cm3)
Conversion factor (365 days/year)
A summary of inputs utilized for these exposure estimates are provided in Appendix A. EPA used the
DBP dermal permeability coefficient (Kp) of 0.016 cm/h ( 024b) and Consumer Exposure
Model (CEM) (U.S. EPA; ICF Consulting. 2022) to estimate the steady-state aqueous permeability
coefficient of DBP.
Table 5-1 shows a summary of the estimates of ADRs and ADDs due to dermal exposure while
swimming for adults, youth, and children. Doses are calculated using Equation 5-1 and Equation 5-2,
using the highest surface water concentration from the Manufacturing OES. Dermal doses were also
calculated using the highest monitored surface water concentration from the WQP ((NWOMC. 2021);
Section 4.2.1) as the surface water concentration. Doses calculated using the surface water monitoring
data are on the same order of magnitude as corresponding doses modeled using the high-end
Manufacturing OES.
Releases associated with the Manufacturing OES resulted in the highest total water column
concentrations among reported releases, with water concentrations of 885 |ig/L using 30Q5 flow (the
lowest 30-day average flow in a 5-year period). Because of relevance to the exposure route, acute
incidental surface water exposures and acute drinking water exposures were derived from the 30Q5 flow
concentrations, and chronic drinking water exposures were derived from the harmonic mean (HM) flow
concentrations. COUs mapped to the Manufacturing OES are shown in Table 1-1. Manufacturing OES
was chosen as an appropriate OES for a screening level assessment based on it resulting in a
conservatively high surface water concentration based on high volumes of releases associated with low
flow metrics (P50). Additionally, the generic release scenario for the Manufacturing OES estimates a
combined release to wastewater, incineration, or landfill. The proportion of the release from
Manufacturing OES to just surface water could not be determined from reasonably available
information, so for screening purposes EPA assumed that all of the release would be to wastewater to
represent an upper-bound of surface water concentrations and no wastewater treatment was assumed.
Table 5-1. Dermal (Swimming) Doses Across Lifestages"
Scenario
Water Column
Concentrations
Adult (21+ years)
Youth (11—15 years)
Child (6-10 years)
30Q5
Cone.
(jig/L)
Harmonic
Mean
Cone.
(Mg/L)
ADRpot
(mji/kji-
day)
ADD
(mji/kji-
day)
ADRpot
(msj/ks-
day)
ADD
(mji/kji-
day)
ADRpot
(mji/kjj-
day)
ADD
(mji/kjj-
day)
Manufacturing6
885
616
1.04E-02
1.97E-05
7.93E-03
1.51E-05
4.81E-03
9.17E-06
Highest monitored
surface water
(NWOMC. 2021)
26.8
26.8
3.14E-04
8.59E-07
2.40E-04
6.58E-07
1.46E-04
3.99E-07
30Q5 =30 consecutive days of lowest flow over a 5-year period; POT = potential
a Doses calculated using Equation 5-1 and Equation 5-2.
b Only this OES was used in the screening assessment because it resulted in the highest surface water concentrations.
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5.1,2 Oral Exposure
The general population may swim in surfaces waters (streams and lakes) that are affected by DBP
contamination. Modeled surface water concentrations estimated in Section 4.1 were used to estimate
ADR and ADD due to ingestion exposure while swimming.
The following equations were used to calculate incidental oral (swimming) doses for adults, youth, and
children using the Manufacturing OES that resulted in the highest modeled surface water concentrations,
as well as calculated using the highest monitored surface water concentration from the WQP (NWOMC.
2021):
Equation 5-3. Acute Incidental Ingestion Calculation
(SWC xIRx CF1)
ADR = -—m—-
Where:
ADR
Acute dose rate (mg/kg-day)
SWC
Surface water concentration (ppb or |ig/L)
IR
Daily ingestion rate (L/day)
CF 1
Conversion factor (1.0x10-3 mg/|ig)
BW
Body weight (kg)
Equation 5-4. Average Daily Incidental Calculation
(SWC x IR x ED x RD x CF1)
ADD =
(BW x AT x CF2)
Where:
ADD
Average daily dose (mg/kg-day)
SWC
Surface water concentration (ppb or |ig/L)
IR
Daily ingestion rate (L/day)
ED
Exposure duration (years)
RD
Release days (days/yr)
CF 1
Conversion factor (1.0x10-3 mg/|ig)
BW
Body weight (kg)
AT
Averaging time (years)
CF2
Conversion factor (365 days/year)
A summary of inputs utilized for these estimates are presented in Appendix A. 1. Incidental ingestion
doses derived from the modeled concentration presented in Section 4.1 and the above exposure
equations are presented in Table 5-2.
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Table 5-2. Incidenta Ingestion Doses (Swimming) Across Lifestages
Scenario
Water Column
Concentrations
Adult (21+ years)
Youth (11-15 years)
Child (6-10 years)
30Q5
Cone.
(Hg/L)
Harmonic
Mean Cone.
(Hg/L)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
Manufacturing(P50) a
885
616
3.05E-03
5.82E-06
4.74E-03
9.03E-06
2.67E-03
5.09E-06
Highest monitored
surface water
CNWOMC. 2021)
26.8
26.8
9.25E-05
2.53E-07
1.43E-04
3.93E-07
8.09E-05
2.22E-07
30Q5 = 30 consecutive days of lowest flow over a 5-year period; POT = potential
a Only this OES paired with low flow assumptions was used in the screening assessment because it resulted in the
highest surface water concentrations.
5.2 Weight of Scientific Evidence Conclusions
Surface water and sediment concentrations of DBP were modeled using facility release data reported to
TRI and DMR databases. As such, EPA has moderate to robust confidence in the release data and the
resulting modeled surface water concentrations at the point of release in the receiving waterbody. The
high end of those resulting concentrations and exposure estimates are presented in this document.
Screening level risk estimates derived from the exposures modeled in this section are discussed in
Appendix C and demonstrate no risk estimates for the general population below the benchmark. The
screening approach applied for modeling, in conjunction with the available monitoring data showing
lower concentrations than those modeled, provide multiple lines of evidence and robust confidence that
releases to surface water will not exceed the release concentrations presented in this assessment, which
do not appear to pose risk to human health.
Swimming Ingest ion/Dermal Estimates
Two scenarios (youth being exposed dermally and through incidental ingestion while swimming in
surface water) were assessed as high-end potential exposures to DBP in surface waters. EPA's Exposure
Factors Handbook provided detailed information on the youth skin surface areas and event per day of
the various scenarios ( ). Non-diluted surface water concentrations were used when
estimating dermal exposures to youth swimming in streams and lakes. DBP concentrations will dilute
when released to surface waters but it is unclear what level of dilution will occur when the general
population swims in waters with DBP releases.
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6 DRINKING WATER EXPOSURE TO GENERAL POPULATION
Drinking water in the United States typically comes from surface water {i.e., lakes, rivers, and
reservoirs) and groundwater. The source water then flows to a treatment plant where it undergoes a
series of water treatment steps before being dispersed to homes and communities. In the United States,
public water systems often use conventional treatment processes that include coagulation, flocculation,
sedimentation, filtration, and disinfection, as required by law.
Very limited information is reasonably available on the removal of DBP in drinking water treatment
plants. As stated in th q Draft Physical Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate
(U.S. EPA. 2024e\ no data were identified by the EPA for DBP in U.S. drinking water. Based on the
low water solubility and log Kow, DBP in water is expected to mainly partition to suspended solids
present in water. The reasonably available information suggests that the use of flocculants and filtering
media could potentially help remove DBP during drinking water treatment by sorption into suspended
organic matter, settling, and physical removal.
6.1 Modeling Approach for Estimating Concentrations in Drinking Water
6.1,1 Drinking Water Ingestion
Drinking Water Intake Estimates via Modeled Surface Water Concentrations
Modeled surface water concentrations estimated in Section 4.1 were used to estimate drinking water
exposures. For this screening exercise, only the highest modeled facility release was included in the
drinking water exposure analysis, alongside the highest monitored surface water concentration. The
estimated exposure concentrations presented in this section reflect releases reported by a facility as
actual effluent loading (after any wastewater treatment). A range of wastewater and drinking water
treatment removal efficiencies for DBP are discussed in Draft Physical Chemistry, Fate, and Transport
Assessment for Dibutyl Phthalate ( 24g), and the high-end exposure from a modeled facility
release presented here does not include any additional calculated removal from drinking water treatment.
The drinking water scenario presented here is expected to be the scenario most representative of a
possible upper-bound for drinking water exposure in the general population.
Drinking water doses were calculated using the following equations:
Equation 6-1. Acute Drinking Water Ingestion Calculation
ADRpot —
(.SWC X (l
¦) x IRdw x RD x CF1)
(BW x AT)
Where:
ADRpot
SWC
RD
CF1
BW
DWT
Potential acute dose rate (mg/kg/day)
Surface water concentration in receiving waterbody (ppb or |ig/L; 30Q5
cone for ADR, harmonic mean for ADD, LADD, LADC)
Removal during drinking water treatment (%) (not applied for this analysis)
Drinking water intake rate (L/day)
Release days (days/yr for ADD, LADD, and LADC; 1 day for ADR)
Conversion factor (1.0x10-3 mg/|ig)
Body weight (kg)
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AT = Exposure duration (years for ADD, LADD, and LADC; 1 day for ADR)
Equation 6-2. Average Daily Drinking Water Ingestion Calculation
/ DWT\
(.SWC x (l - =^j-J x IRdw xEDxRDx CF1)
(BW x AT x CF2)
ADDP0T
Where:
ADDpot -
Potential average daily dose (mg/kg/day)
SWC
Surface water concentration in receiving waterbody (ppb or |ig/L; 30Q5
cone for ADR, harmonic mean for ADD, LADD, LADC)
DWT
Removal during drinking water treatment (%) (not applied for this analysis)
IRdw
Drinking water intake rate (L/day)
ED
Exposure duration (years for ADD, LADD, and LADC; 1 day for ADR)
RD
Release days (days/yr for ADD, LADD, and LADC; 1 day for ADR)
BW
Body weight (kg)
AT
Exposure duration (years for ADD, LADD, and LADC; 1 day for ADR)
CF 1
Conversion factor (1.0x10-3 mg/|ig)
CF2
Conversion factor (365 days/year)
The ADR and ADD from drinking water for chronic non-cancer were calculated using the 95th
percentile ingestion rate for drinking water. The lifetime average daily dose (LADD) was not estimated
because available data are insufficient to determine the carcinogenicity of DBP ( 2024f).
Therefore, EPA is not evaluating DBP for carcinogenic risk. Table 6-1 summarizes the drinking water
doses for adults, infants, and toddlers. These estimates do not incorporate additional dilution beyond the
point of discharge, and in this case, it is assumed that the surface water outfall is located very close
(within a few km) to the drinking water intake location. Applying dilution factors would decrease the
concentration at the intake as well as the dose for all scenarios.
Table 6-1. Drinking Water Doses Across Lifestages
Scenario
Surface Water
Concentrations
Adult
(21+ years)
Infant
(Birth to <1 vear)
Toddler
(1-5 vears)
30Q5
Cone.
(Hg/L)
Harmonic
Mean
Cone.
(hs/L)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
ADRpot
(mg/kg-
day)
ADD
(mg/kg-
day)
Manufacturing"
885
616
3.56E-02
1.86E-05
1.25E-01
4.74E-05
4.44E-02
2.03E-05
Highest
monitored
surface water
CNWOMC. 2021)
26.8
26.8
1.08E-03
8.07E-07
3.78E-03
2.06E-06
1.35E-03
8.84E-07
30Q5 = 30 consecutive days of lowest flow over a 5-year period; POT = potential
a Only this OES was used in the screening assessment because it resulted in the highest surface water concentrations.
6.2 Measured Concentrations in Drinking Water
EPA searched peer-reviewed literature, gray literature, and databases of environmental monitoring data
to obtain concentrations of DBP in drinking water. EPA identified monitoring studies through
systematic review to provide context to modelling results. The monitoring studies presented here were
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not used as part of the analysis for quantifying exposure estimates. No studies conducted in the United
States or Canada were identified that reported concentrations of DBP in drinking water. Drinking water
quality data from 2011 through 2022 were obtained from the California Water Boards (2022) for 39
counties in the state (Table 6-2). For the more than 200 active, inactive, or proposed water systems and
facilities, DBP was detected in approximately two percent of samples at levels up to 3.1 |ig/L. The
highest level of DBP was detected in a 2015 sample from an active Arvin Community Services water
system in Kern County. Table 6-2 also presents DBP levels in drinking water from two studies
conducted in high-income foreign countries. Bach et al. (2020) conducted a national screening study in
France to examine levels of phthalates in raw and treated tap water. From 2015 to 2016, 283 treated
water samples were examined: 166 supplied by groundwater, 89 supplied by surface water, and 28
supplied by a mixture of surface and groundwater. DBP was detected once for each of the three supply
types at a maximum level of 1,340 ng/L. In a second study conducted in Romania in 2017, phthalates
were measured in municipal drinking water and consumed bottled water (Sulentic et al.. 2018). Ten tap
water samples and sixteen bottled water samples that combined brand, type (still or gas), and storage
conditions (room temperature or refrigerated) were collected and analyzed for four phthalates. DBP was
not detected in the tap water samples. Overall, the median level of DBP in bottled water was 3.23 |ig/L.
Still water (5.61 |ig/L) had a higher median concentration of DBP than gas water (2.16 |ig/L). Bottled
water at room temperature (3.87 |ig/L) had a higher median concentration of DBP than bottled water
that was refrigerated (3.05 |ig/L).
Table 6-2. Summary of
Measured DBP Concentrations in Drinking Water
Reference
Sampling Location
DBP Concentration
Sampling Notes
United States
FOD: 1.9% (3 detects in raw
(untreated) water [2 inactive, 1
active wells] from Arvin
Community Services in Kern
County)
Overall: <1-3.1 (ig/L
Over 1,500 records of
DBP levels in drinking
water, 2011-2022
Bach et al. (2020)
France
FOD = 1.2% (n = 283)
Level bv supplv tvpe (ns/L)
Surface water (n = 89):
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6.3 Evidence Integration for Drinking Water
EPA estimates low potential exposure to DBP via drinking water, with or without considering expected
treatment removal efficiencies, even under high-end release scenarios. These exposure estimates also
assume that the drinking water intake location is very close (within a few km) to the point of discharge
and do not incorporate any dilution beyond the point of discharge. Actual concentrations in raw and
finished water are likely to be lower than these conservative estimates as applying dilution factors will
decrease the exposure for all scenarios, and additional distances downstream would allow further
partitioning and degradation. Monitoring data from finished drinking water in the United States are
mostly non-detect for DBP, with a highest reported concentration of 3.1 |ig/L, corroborating the
expectation of very little exposure to the general population via treated drinking water. Monitoring data
also present evidence for generally low concentrations in ambient waters beyond direct points of release.
Screening level risk estimates derived from the exposures discussed in this section are presented in
Appendix 13.4C.2 and screening level risk estimates were above the benchmark MOE at the upper-
bound of exposure for all but the most extreme and unlikely release and exposure scenarios.
6.4 Weight of Scientific Evidence Conclusions
EPA has moderate to high confidence in the surface water as drinking water exposure scenario due to
the site-specific uncertainty presented in this section and robust evidence of presenting an upper-bound
of exposure with risk beyond the benchmark. As described in Section 3.2, EPA did not assess drinking
water estimates as a result of leaching from landfills to groundwater and subsequent migration to
drinking water wells.
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7 FISH INGESTION EXPOSURE TO GENERAL POPULATION
To estimate exposure to humans from fish ingestion, EPA used multiple surface water concentrations in
its assessment: the water solubility of 11.2 mg/L ( )24g), the maximum modeled
concentration based on reported and estimated releases, and the measured concentrations from
monitoring data. Incorporating multiple surface water concentrations accounts for the variation shown in
Table 7-1, such as when an OES may result in concentrations exceeding the water solubility limit. The
selected surface water concentrations are also the highest among modeled and monitored values,
facilitating their use in a screening level analysis that incorporates conservative assumptions.
Another important parameter in estimating human exposure to a chemical through fish ingestion is the
bioaccumulation factor (BAF). BAF is preferred over bioconcentration factor (BCF) because it
considers the animal's uptake of a chemical from both diet and the water column. For DBP, one high-
quality study reporting BAF values for fish was identified during systematic review. Li et al. (2024)
reported BAF values of 410 L/kg for tilapia and 314 L/kg for common carp (see Draft Physical
Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate (DBP) ( 24g)). The BAFs
of both fish species were included in this risk evaluation since tilapia is primarily herbivorous and is at a
lower trophic level, while common carp reside at the bottom of the water column where DBP is
expected to partition and would represent exposure at a higher trophic level. Table 7-1 compares the fish
tissue concentration calculated using empirical BAFs with the measured fish tissue concentrations
obtained from literature. Fish tissue concentrations calculated with empirical BAFs and water solubility
limit were two to three orders of magnitude higher than empirical levels reported within published
literature. This indicates that calculated fish tissue concentrations with the water solubility limit are
likely overestimated.
The Manufacturing OES resulted in the highest concentration of DBP in receiving waters across all
OESs (Section 4.1). The concentration was modeled using VVWM-PSC and represents the harmonic
mean based on the highest modeled 95th percentile release to water. Surface water concentrations were
estimated for various flows {i.e., P50, P75, and P90). However, EPA does not expect waterbodies with
P50 flow rates to receive high-end industrial and commercial releases and thus did not consider modeled
surface water concentrations based on P50 flows. For OESs with TRI reported releases, the Waste
handling, treatment, and disposal OES had the highest release to surface water. The surface water
concentrations for this OES were also modeled using VVWM-PSC and represents the harmonic mean.
Fish tissue concentrations calculated with the modeled surface water concentration were within the same
order of magnitude or one order lower than empirical levels reported within published literature (Table
7-1).
In addition, EPA calculated fish tissue concentrations using the highest measured DBP concentrations in
surface water. As described in Section 4.2.1, the maximum concentration was 8.2 |ig/L (8,2/ 10 3 mg/L)
from the WQP (NWQMC. 2021). Fish tissue concentrations calculated with empirical BAFs and
monitored water surface concentrations are similar to the measured fish tissue concentrations obtained
from literature (Table 7-1).
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Table 7-1. Fish Tissue Concentrations Calculated from Modeled Surface Water Concentrations
and Monitoring Data
Approach
Data Description
Surface Water
Concentration
Fish Tissue
Concentration
Water
solubility limit
Empirical BAF values of 410
L/kg for tilapia and 314 L/kg
for common carp (Li et aL
2024)
Estimates of the water
solubility limit for DBP,
which is approximately 11.2
mg/L (Howard et aL, 1985)
4.59E03 mg/kg ww
(tilapia)
3.52E03 mg/kg ww
(common carp)
Modeled
surface water
concentrations
Empirical BAF values of 410
L/kg for tilapia and 314 L/kg
for common carp (Li et aL.
2024)
2.24E-02 mg/L for
Manufacturing OES, P75,
HE (generic scenario)
10.1 mg/kg ww (tilapia)
7.66 mg/kg ww (common
carp)
1.7E-03 mg/L for
Manufacturing OES, P90,
HE (generic scenario)
0.70 mg/kg ww (tilapia)
0.53 mg/kg ww (common
carp)
1.45E-02 mg/L for Waste
Handling, Treatment,
Disposal-POTW (TRI
reported release)
5.95 mg/kg ww (tilapia)
4.55 mg/kg ww (common
carp)
Monitored
surface water
concentration
Highest measured
concentration from WQP
(NWOMC. 2021) and
empirical BAF values of 410
L/kg for tilapia and 314 L/kg
for common carp (Li et aL.
2024)
8.2E-03 mg/L
3.36 mg/kg ww (tilapia)
2.57 mg/kg ww (common
carp)
Fish tissue
monitoring
data (wild-
caught)
19 studies from over 70
different species, including
four U.S. and two Canadian
studies
N/A
Ranee for U.S. and
Canadian studies:
ND-35 mg/kg ww
Range for other studies:
ND-3.9 mg/kg ww
HE = high-end; ND = non-detect; ww = wet weight
7.1 General Population Fish Ingestion Exposure
EPA estimated exposure from fish consumption using age-specific fish ingestion rates (TableApx A-2).
Adults have the highest 50th percentile fish ingestion rate (IR) per kilogram of body weight for the
general population, as shown in Table Apx A-2. A young toddler between 1 and 2 years has the highest
90th percentile fish IR per kilogram of body weight. This section estimates exposure and risks for adults
and toddlers aged 1 to 2 years who have those two lifestages with the highest fish IR per kilogram of
body weight among all lifestages in this used as a screening level approach.
The ADR and ADD for chronic non-cancer estimates were calculated using the 90th percentile and
central tendency IR, respectively. Cancer exposure (LADD, lifetime average daily dose) and risks were
not characterized because there is insufficient evidence of DBP's carcinogenicity ( 324f).
Estimated exposure to DBP from fish ingestion were calculated using the following equation:
Equation 7-1. Fish Ingestion Calculation
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(.SWC x BAF xIRx CF1 x CF2 x ED)
ADR or ADD
AT
Where:
ADR = Acute dose rate (mg/kg/day)
ADD = Average daily dose (mg/kg/day)
SWC = Surface water (dissolved) concentration (|ig/L)
BAF = Bioaccumulation factor (L/kg wet weight)
IR = Fish ingestion rate (g/kg-day)
CF 1 = Conversion factor (0.001 mg/|ig)
CF2 = Conversion factor for kg/g (0.001 kg/g)
ED = Exposure duration (year)
AT = Averaging time (year)
The inputs to this equation can be found in Draft Fish Ingestion Risk Calculator for Dibutyl Phthalate
(DBF) ( 1025c). The years within an age group {i.e., 62 years for adults) was used for the
exposure duration and averaging time to estimate non-cancer exposure. The exposures calculated using
the water solubility limit and maximum modeled and monitored surface water concentrations, with
empirical BAFs, are presented in Table 7-2. Corresponding screening level risk estimates are shown in
Appendix E. 11. Fish ingestion is not expected to be a pathway of concern for the general population
based on the conservative screening level risk estimates using an upper-bound of exposure.
Table 7-2. General Population Fish Ingestion Doses by Surface Water Concentration
Surface Water Concentration
and Scenario
Adult ADR
(mg/kg-day)
Young Toddler ADR
(mg/kg-day)
Adult ADD
(mg/kg-day)
Water solubility limit (11.2
mg/L)
1.27 (tilapia)
9.76E-01 (common carp)
1.89 (tilapia)
1.45 (common carp)
2.89E-01 (tilapia)
2.22E-01 (common carp)
Manufacturing OES, P75, HE
(generic scenario) (2.24E-02
mg/L)
2.78E-03 (tilapia)
2.13E-03 (common carp)
4.12E-03 (tilapia)
3.16E-03 (common
carp)
6.30E-04 (tilapia)
4.83E-04 (common carp)
Monitored surface water
concentration (8.2E-03 mg/L)
(NWOMC. 2021)
9.33E-04 (tilapia)
7.15E-04 (common carp)
1.39E-03 (tilapia)
1.06E-03 (common
carp)
2.12E-04 (tilapia)
1.62-04 (common carp)
HE - high end
7.2 Subsistence Fish Ingestion Exposure
Subsistence fishers represent a potentially exposed or susceptible subpopulation(s) (PESS) group due to
their greatly increased exposure via fish ingestion (average of 142.4 g/day of fish consumed compared to
a 90th percentile of 22.2 g/day for the general population) (U.S. EPA. 2000b). The ingestion rate for
subsistence fishers applies only to adults aged 16 to less than 70 years. EPA calculated exposure for
subsistence fishers using Equation 7-1 and the same inputs as the general population, with the exception
of the increased ingestion rate. EPA is unable to determine subsistence fishers' exposure estimates
specific to younger lifestages based on lack of reasonably available information. Furthermore, unlike the
general population fish ingestion rates, there is no central tendency or 90th percentile ingestion rate for
subsistence fishers. The same value was used to estimate both the ADD and ADR.
Conservative exposure estimates based on the water solubility limit resulted in screening level risk
estimates below the benchmark as described in Appendix E.2. Therefore, EPA refined its evaluation by
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using the OES that resulted in the highest modeled surface water concentrations based on releases to
water combined with the flow rate of the receiving water body (Section 4.1). This refined analysis did
not result in screening level risk estimates below the benchmark. Therefore, ingestion of fish potentially
contaminated with DBP is not expected to be a pathway of concern for the subsistence fisher.
Table 7-3. Adult Subsistence Fisher Doses by Surface Water Concentration
Surface Water Concentration and Scenario
ADR/ADD (mg/kg-day)
Water solubility limit (11.2 mg/L)
8.17 (tilapia)
6.26 (common carp)
Manufacturing OES, P75, HE (generic scenario) (2.24E-02
mg/L)
1.78E-02 (tilapia)
1.36E-02 (common carp)
Monitored surface water concentration (8.2E-03 mg/L)
(NWOMC. 2021)
5.98E-03 (tilapia)
4.58E-03 (common carp)
HE - high end
7.3 Tribal Fish Ingestion Exposure
Tribal populations represent another PESS group. In the United States there are a total of 574 federally
recognized American Indian Tribes and Alaska Native Villages and 63 state recognized tribes. Tribal
cultures are inextricably linked to their lands, which provide all their needs from hunting, fishing, food
gathering, and grazing horses to commerce, art, education, health care, and social systems. These
services flow among natural resources in continuous interlocking cycles, creating a multi-dimensional
relationship with the natural environment and forming the basis of Tamamvit (natural law) (Harper et al..
2012). Such an intricate connection to the land and the distinctive life ways and cultures between
individual tribes create many unique exposure scenarios that can expose tribal members to higher doses
of contaminants in the environment. EPA used the reasonably available information to quantitatively
evaluate the tribal fish ingestion pathway for DBP but lacks reasonably available data to assess other
exposure scenarios unique to tribal populations.
U.S. EPA (201 la) (Chapter 10, Table 10-6) summarizes relevant studies on current tribal-specific fish
ingestion rates that covered 11 tribes and 94 Alaskan communities. The highest central tendency value
(a mean) ingestion rate per kilogram of body weight is reported in a 1997 survey of adult members (16+
years) of the Suquamish Tribe in Washington. Adults from the Suquamish Tribe reported a mean
ingestion rate of 2.7 g/kg-day, or 216 g/day assuming an adult body weight of 80 kg. In comparison, the
ingestion rates for adult subsistence fishers and the general population are 142.2 and 22.2 g/day,
respectively. A total of 92 adults responded to the survey funded by the Agency for Toxic Substances
and Disease Registry (ATSDR) through a grant to the Washington State Department of Health, of which
44 percent reported consuming less fish/seafood today compared to 20 years ago. One reason for the
decline is restricted harvesting caused by increased pollution and habitat degradation (Duncan. 2000).
In addition to the current mean fish ingestion rate, EPA reviewed literature and surveys to identify a
high-end (i.e., 90th or 95th percentile) fish ingestion rate. The surveys asked participants to estimate
their daily fish consumption over the course of a year by meal size and meal frequency. The highest 95th
percentile fish and shellfish ingestion rate was 874 g/day, or 10.9 g/kg-day assuming a body weight of
80 kg, for male adults (18+ years) of the Shoshone-Bannock Tribes in Idaho (Polissar et al.. 2016). The
95th percentile ingestion rate for males and females combined was similar at 10.1 g/kg-day. The
Suquamish Tribe also reported similar high-end (90th percentile) ingestion rates for adults ranging from
8.56 to 9.73 g/kg-day (Duncan. 2000). Estimated high-end fish ingestion rates were lower for other
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tribes in Alaska, the Pacific Northwest, Great Lakes region, and northeastern North America. To
evaluate a current high-end exposure scenario, EPA used the highest 95th percentile ingestion rate of
10.9 g/kg-day.
Because current fish consumption rates are suppressed by contamination, degradation, or loss of access,
EPA reviewed existing literature for ingestion rates that reflect heritage rates. Heritage ingestion rates
refer to typical fish ingestion prior to non-indigenous settlement on tribal fisheries resources as well as
changes in culture and lifeways ( ). Heritage ingestion rates were identified for four
tribes, all located in the Pacific Northwest region. The highest heritage ingestion rate was reported for
the Kootenai Tribe in Idaho at 1,646 g/day, or 20.6 g/kg-day assuming an adult body weight of 80 kg
(RIDOLFI. 2016; Northcote. 1973). Northcote (1973) conducted a comprehensive review and evaluation
of ethnographic literature, historical accounts, harvest records, archaeological and ecological
information, as well as other studies of heritage consumption. The heritage ingestion rate is estimated
for Kootenai members living in the vicinity of Kootenay Lake in British Columbia, Canada; the
Kootenai Tribe once occupied territories in parts of Montana, Idaho, and British Columbia. It is based
on a 2,500 calorie per day diet, assuming 75 percent of the total caloric intake comes from fish which
may overestimate fish intake. However, the higher ingestion rate also accounted for salmon fat loss
during migration to spawning locations by using a lower caloric value for whole raw fish. Northcote
(1973) assumed a caloric content of 113.0 cal/100 g wet weight. In comparison, the U.S. Department of
Agriculture's Agricultural Research Service (1963) estimates a caloric content for fish sold in the United
States to range from 142 to 242 cal/100 g of fish.
EPA calculated exposure via fish consumption for tribes using Equation 7-1 and the same inputs as the
general population except for the ingestion rate. Three ingestion rates were used: 216 g/day (2.7 g/kg-
day) for a central tendency current consumption rate; 874 g/day (10.9g/kg-day) as a high-end current
tribal fish ingestion rate; and 1,646 g/day (20.58 g/kg-day) for heritage consumption. Similar to
subsistence fishers, EPA used the same ingestion rate to estimate both the ADD and ADR. The heritage
ingestion rate is assumed to be applicable to adults. For current ingestion rates, U.S. EPA (201 la)
provides values specific to younger lifestages, but adults still consume higher amounts of fish per
kilogram of body weight. An exception is for the Squaxin Island Tribe in Washington that reported an
ingestion rate of 2.9 g/kg-day for children under 5 years. That ingestion rate for children is nearly the
same as the adult ingestion rate of 2.7 g/kg-day for the Suquamish Tribe. As a result, exposure estimates
based on current ingestion rates (IR) focused on adults (Table 7-4).
Table 7-4 presents multiple exposure estimates for the tribal populations. Conservative exposure
estimates based on the water solubility limit resulted in screening level risk estimates below the
benchmark as described in Appendix E.3. As a result, EPA refined its evaluation by using the two OESs
that resulted in the highest modeled surface water concentrations. The surface water releases were
estimated based on generic scenarios for one of the OESs and reported in TRI for the other OES.
(Section 4.1). This refined analysis resulted in screening level risk estimates below the benchmark for
the Manufacturing OES at the P75 flow rate and the current 95th percentile fish ingestion rate and
heritage fish ingestion rate. However, EPA has slight confidence in the modeled surface water
concentrations for the Manufacturing OES because the estimated release did not provide sufficient
information to determine the fraction that discharges to water only. As such, EPA relied on reported TRI
data for the Waste handling, treatment, and disposal OES where EPA has moderate-to-robust confidence
in the risk estimates. Screening -level risk estimates for the Waste handling, treatment, and disposal OES
were above benchmark for all scenarios. Therefore, ingestion of fish potentially contaminated with DBP
is not a pathway of concern for tribal populations.
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Table 7-4. Adult Tribal Fish Ingestion Doses by Surface Water Concentration
Surface Water Concentration
and Scenario
ADR/ADD (mg/kg-day)
Current Tribal IR,
Mean
Current Tribal IR, 95th
Percentile
Heritage IR
Water solubility limit (11.2
mg/L)
1.24E01 (tilapia)
9.50 (common carp)
5.01E01 (tilapia)
3.83E01 (common carp)
9.45E01 (tilapia)
7.24E01 (common carp)
Manufacturing OES, P75, HE
(generic scenario) (2.24E-02
mg/L)
2.70E-02 (tilapia)
2.07E-02 (common carp)
1.09E-01 (tilapia)
8.35E-02 (common carp)
2.06E-01 (tilapia)
1.58E-01 (common carp)
Manufacturing OES, P90, HE
(generic scenario) (1.7E-03
mg/L)
1.88E-03 (tilapia)
1.44E-03 (common carp)
7.60E-03 (tilapia)
5.82E-03 (common carp)
1.43E-02 (tilapia)
1.10E-02 (common carp)
Waste Handling, Treatment,
Disposal-POTW (TRI reported
release) (1.45E-02 mg/L)
1.61E-02 (tilapia)
1.23E-02 (common carp)
6.48E-02 (tilapia)
4.96E-02 (common carp)
1.22E-01 (tilapia)
9.37E-02 (common carp)
Monitored surface water
concentration (8.2E-03 mg/L)
fNWOMC. 2021)
9.08E-03 (tilapia)
6.95E-03 (common carp)
3.66E-02 (tilapia)
2.81E-02 (common carp)
6.92E-02 (tilapia)
5.30E-02 (common carp)
CT - central tendency; HE - high end
7.4 Weight of Scientific Evidence Conclusions
7.4,1 Strength, Limitations, Assumptions, and Key Sources of Uncertainty
To account for the variability in fish consumption across the United States, fish intake estimates were
considered for general population, subsistence fishing populations, and tribal populations. A
conservative screening analysis using the water solubility limit and the highest modeled surface water
concentrations did not result in screening level risk estimates to be below the benchmark for the general
population and subsistence fishers. However, for the tribal populations consuming fish at the 95th
ingestion rate and heritage rate, risk estimates were below the benchmark for the highest modeled
surface water concentration from the Manufacturing OES and P75 flow rate. EPA has only slight
confidence in those risk estimates because the Manufacturing OES had modeled releases from generic
scenarios discharging to multiple environmental media, and there is insufficient information to
determine the fraction going to each of the media types. As such, EPA relied on reported TRI data for
the Waste handling, treatment, and disposal OES where EPA has moderate-to-robust confidence in the
risk estimates. Screening-level risk estimates for the Waste handling, treatment, and disposal OES were
above benchmark for all scenarios. Therefore, ingestion of fish potentially contaminated with DBP is not
a pathway of concern for tribal populations.
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8 AMBIENT AIR CONCENTRATION
EPA considers both modeled and monitored concentrations in the ambient air for this draft ambient air
exposure assessment for DBP. The Agency's modeling estimates both short- and long-term
concentrations in ambient air as well as dry, wet, and total deposition rates. EPA considers monitoring
data from published literature for additional insight into ambient air concentrations of DBP.
8.1 Approach for Estimating Concentrations in Ambient Air
EPA uses the Integrated Indoor/Outdoor Air Calculator (IIOAC) Model to estimate daily- and annual-
average concentrations of DBP in the ambient air as well as annual average wet, dry, and total
deposition rates of DBP from the ambient air. IIO AC is a spreadsheet-based tool that estimates outdoor
air concentrations using pre-run results from a suite of dispersion scenarios in a variety of
meteorological and land-use settings within EPA's American Meteorological Society/Environmental
Protection Agency Regulatory Model (AERMOD). Additional information on IIO AC can be found in
the user guide (U.S. EPA. 2019d).
In line with previously peer-reviewed methodology ( 22b). EPA's analysis with IIOAC
estimates ambient concentrations of DBP at three distances (e.g., 100; 100-1,000, and 1,000 ms) from
the releasing facility. EPA considers three different datasets for DBP releases including EPA estimated
releases based on production volumes of DBP from facilities that manufacture, process, repackage, or
dispose of DBP estimated by EPA methods ( I5h\ releases reported to TRI by industry
(2017 to 2022 reporting years), and releases reported to the NEI ( !025b) by industry (2017
and 2020 reporting years). The maximum fugitive release value used in this assessment was reported to
the 2017 NEI dataset and is associated with the Application of paints, coatings adhesives, and sealants
OES. The maximum stack release value used in this assessment was reported to the TRI dataset and is
associated with the Waste handling, treatment, and disposal OES. Both maximum release values
represent the maximum release reported across all facilities and COUs and are used as direct inputs to
the IIOAC model to estimate concentrations and deposition rates.
8.1.1 Release and Exposure Scenarios Evaluated
The release and exposure scenarios evaluated for this analysis are summarized below.
• Release: Maximum Release (kg/site-day)
• Release Dataset:
o Fugitive: 2017 NEI
o Stack: TRI
• Release Type: Stack and Fugitive
• Release Pattern: Consecutive
• Distances Evaluated: 100, 100-1,000, and 1,000 m
• Meteorological Station:
o South (Coastal): Surface and Upper Air Stations at Lake Charles, Louisiana
• Operating Scenario: 250 days per year; 24 h/day and 8 hours per day to identify the scenario
resulting in the maximum ambient air concentration. This is the operating scenario associated
with the releases modeled.
• Topography: Urban and Rural
• Particle Size:
o Coarse (PMio): Particulate matter with an aerodynamic diameter of 10 microns
o Fine (PM2.5): Particulate matter with an aerodynamic diameter of 2.5 microns
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EPA used default release input parameters integrated within the IIOAC Model for both stack and
fugitive releases along with a user-defined length and width for fugitive releases as listed in
Table 8-1.
Table 8-1. IIOAC Input Parameters for Stack and
Fugitive Air Releases
Stack Release Parameters
Value
Stack height (m)
10
Stack diameter (m)
2
Exit velocity (m/sec)
5
Exit temperature (K)
300
Fugitive Release Parameters
Value
Length (m)
10
Width (m)
10
Angle (degrees)
0
Release height (m)
3.05
8.1.2 IIOAC Model Output Values
The IIOAC Model provides multiple output values (see Draft Ambient Air IIOAC Exposure Results and
Risk Calculations for DibutylPhthalate (DBF) (I v « « \ 2025a)). A description of select outputs
relied upon in this draft assessment are provided below. These outputs were relied upon because they
represent a more conservative exposure scenario where modeled concentrations are expected to be
higher, thus more protective of exposed populations and ensuring potential high-end exposures are not
missed during screening for the ambient air pathway.
Fenceline Average: represents the daily-average and annual-average concentrations at 100 m distance
from a releasing facility.
High-End, Daily-Average: represents the 95th percentile daily average of all modeled hourly
concentrations across the entire distribution of modeled concentrations at 100 m.
High-End, Annual-Average: 95th percentile annual-average concentration across the entire distribution
of modeled concentrations at 100 m.
High-End, Annual Average Deposition Rate: 95th percentile annual-average deposition rate across the
entire distribution of modeled deposition rates at 100 m.
8.1.3 Modeled Results from IIOAC
All results for each scenario described in Section 8.1.1 are included in the Draft Ambient Air IIOAC
Exposure Results and Risk Calculations for Dibutyl Phthalate (DBF) ( 25a). EPA utilized
the highest estimated concentrations and deposition rates across all modeled scenarios to evaluate
exposures and deposition rates near a releasing facility. This exposure scenario represents a national
level exposure estimate inclusive of sensitive and locally impacted populations who live next to a
releasing facility.
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The IIOAC model provides source apportioned concentrations and deposition rates (fugitive and stack)
based on the respective releases. To evaluate exposures and total deposition rates for this ambient air
assessment, EPA assumes the fugitive and stack releases occur simultaneously throughout the day and
year. Therefore, the total concentration and deposition rate used to evaluate exposures and derive risk
estimates in this ambient air assessment is the sum of the separately modeled fugitive and stack
concentrations and total deposition rates at 100 m from a releasing facility. The source apportioned
concentrations and the total concentrations for the scenario used are provided in Table 8-2.
Table 8-2. Source Apportioned and Total Daily-Average and Annual-Average IIOAC-Modeled
Concentrations at 100 in from Releasing Facility
Source Type
Daily-Average Concentration
(jig/m3)
Annual-Average
Concentration (jig/m3)
Fugitive
16.73
11.46
Stack
0.53
0.37
Total
17.26
11.82
The source apportioned wet and dry deposition rates and the total deposition rates for the scenario used
in the Draft Environmental Hazard Assessment for Dibutyl Phthalate (DBP) ( 24c) are
provided in Table 8-3.
Table 8-3. Source Apportioned and Total Annual-Average IIOAC-Modeled Wet, Dry, and Total
Air to Soil Deposition Rates at 100 m from Releasing Facility
Source Type
Total Annual-Average Air to Soil Deposition Rates (g/m2)
Total
Wet
Dry
Fugitive
1.96E-04
1.94E-04
2.80E-06
Stack
2.75E-05
2.67E-05
1.48E-06
Total
2.23E-04
2.21E-04
4.28E-06
8.2 Measured Concentrations in Ambient Air
EPA identified monitoring studies through systematic review to provide context to modelling results.
The monitoring studies presented here were not used as part of the analysis for quantifying exposure
estimates. EPA reviewed published literature as described in the Draft Systematic Review Protocol for
Dibutyl Phthalate (DBP) (U.S. EPA. 2025e) to identify studies where ambient concentrations of DBP
were measured. The available data found include data from a Chinese study (Zhu et al. 2016). which
measured concentrations of several phthalates including DBP. A simple plot of the measured
concentrations is provided in Appendix F.
EPA also identified a single U.S. study through its systematic review process where DBP concentrations
were measured at three New York City air sampling stations (Bove et al.. 1978). Findings from this
study are summarized in Appendix F. Measured concentrations of DBP in these two studies were low,
generally in the ng/m3 range. How these data do or do not reflect conditions in the United States (in
relation to the foreign study) or TSCA COUs (in relation to both the foreign study and U.S. study) is
unknown, limiting the utility of these data to this assessment.
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Uncertainties associated with monitoring data from other countries limit their applicability to this risk
assessment. It is unknown how these data do or do not reflect conditions in the United States or TSCA
COUs. Information needed to link the monitoring data to foreign industrial processes and crosswalk
those to TSCA COUs is not available. The proximity of the monitoring site to a releasing facility
associated with a TSCA COU is also unknown. Furthermore, regulation of emissions standards often
vary between the United States and foreign countries.
EPA also reviewed EPA's Ambient Monitoring Technology Information Center (AMTIC) database but
did not find any monitored DBP concentrations (U.S. EPA. 2022a).
8.3 Evidence Integration
EPA relied on the IIO AC-modeled concentrations and deposition rates to characterize human and
ecological exposures for the ambient air exposure assessment. Modeled DBP ambient air concentrations
were estimated using the maximum ambient air release, conservative meteorological data, and a distance
of 100 m from a releasing facility. The modeled concentrations are higher than measured concentrations
(Sections 8.1 and 8.2, respectively ). Caution is needed when interpreting such a comparison, however,
because modeled concentrations are near a releasing facility (100 m), and it is unknown if the sampling
sites are located at a similar distance from a site.
8,3,1 Strengths, Limitations, and Sources of Uncertainty for Modeled Air and Deposition
Concentrations
The approach and methodology used in this ambient air exposure assessment replicates previously peer-
reviewed approaches and methods, as well as incorporates recommendations provided during peer
review of other ambient air exposure assessments.
A strength of the IIO AC modeling includes use of environmental release data from multiple databases
across multiple years (including data that are required by law to be reported by industry). These
databases undergo repeatable quality assurance and quality control reviews ( 2025b). These
release data are used as direct inputs to EPA's peer-reviewed IIO AC Model to estimate concentrations at
several distances from releasing facilities where individuals may reside for many years. The specific
maximum release value used for this assessment came from an industry reported release value and was
the highest value across multiple datasets considered. For OESs that had no facility-reported release data
(e.g., TRI or NEI), DBP releases were estimated and used as a direct input to the IIO AC model. Any
limitations and uncertainties of these estimated releases, as described in the Draft Environmental
Release and Occupational Exposure Assessment for Dibutyl Phthalate (DBP) ( 025b). are
carried over to this ambient air exposure assessment.
The IIO AC Model also has limitations in what inputs can and cannot be changed. Since it is based on
pre-run scenarios within AERMOD, default input parameters (e.g., stack characteristics and 2011-2015
meteorological data) are already predefined. Site-specific information like building dimensions, stack
heights, elevation, and land use cannot be changed in IIO AC and therefore presents a limitation on the
modeled results for DBP. This is in addition to the data gap EPA has on certain parameters like building
dimensions, stack heights, and release elevation since such information has not been provided by
industry to EPA for consideration which creates additional limitations on using other models to their full
potential. Furthermore, IIO AC does not consider the presence or location of residential areas relative to
the 100 m distance from releasing facilities, the size of the facility, and the release point within a
facility. For larger facilities, 100 m from a release point may still fall within the facility property where
individuals within the general population are unlikely to live or frequent. In contrast, for smaller
facilities, there may be individuals within the general population living 100 m away from the release
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point and therefore could be exposed continuously. However, most individuals may not stay within their
residences 24 hours per day, 7 days per week throughout the year.
The use of estimated annual release data to calculate daily average releases can underestimate exposure.
Since the maximum annual release value (for stack and fugitive emissions) from each release point is
used in this assessment, EPA assumes operations are continuous and releases are the same for each day
of operation when calculating daily average concentrations. This assumption may result in modeled
concentrations missing true peak releases (and associated exposures). However, EPA utilized multiple
conservative assumptions leading to a high ambient air concentrations appropriate for a screening level
assessment.
8.4 Weight of Scientific Evidence Conclusions
EPA has moderate confidence in the IIOAC-modeled results used to characterize exposures and
deposition rates. Despite the limitations and uncertainties (Section 8.3) potentially under- or
overestimating ambient air exposure, this screening level analysis presents a reasonable upper-bound of
exposure. Multiple conservative inputs (e.g., maximum estimated ambient air release) and assumptions
(e.g., an individual lives at the same location 100 m from a facility for their entire lifetime and spends
the entirety of their day every day at that location) bias the resulting exposure estimates toward
overestimation. These exposure estimates are thus protective, and ambient air exposure is not a pathway
of concern.
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9 AMBIENT AIR EXPOSURE TO GENERAL POPULATION
9.1 Exposure Calculations
Modeled ambient air concentration outputs from IIOAC need to be converted to estimates of exposure to
derive risk estimates. For this exposure assessment, EPA assumes the general population is continuously
exposed {i.e., 24 hours per day, 365 days per year) to outdoor ambient air concentrations. Therefore,
daily average modeled ambient air concentrations are equivalent to acute exposure concentrations, and
annual average modeled ambient air concentrations are equivalent to chronic exposure concentrations
used to derive risk estimates (Section 8.1.3). Calculations for general population exposure to ambient air
via inhalation and ingestion from air to soil deposition for lifestages expected to be highly exposed
based on exposure factors can be found in Draft Ambient Air IIOAC Exposure Results and Risk
Calculations For DibutylPhthalate (DBF) ( 2025a).
9.2 Overall Findings
Based on the results from the analysis of the maximum estimated release and high-end exposure
concentrations presented in this document and the Draft Non-cancer Human Health Hazard Risk
Assessment for Dibutyl Phthalate (DBF) (U.S. EPA. 2024f). EPA does not expect an inhalation risk
from ambient air nor ingestion risk from air to soil deposition to result from exposures to DBP from
industrial releases. Because no exposures of concern were identified at the maximum release scenario,
EPA does not expect a different finding for smaller releases and therefore additional or more detailed
analyses for exposure to DBP through inhalation of ambient air or ingestion from air to soil deposition is
not necessary.
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10 HUMAN MILK EXPOSURES TO GENERAL POPULATION
Infants are potentially more susceptible for various reasons, including their higher exposure per body
weight, immature metabolic systems, and the potential for chemical toxicants to disrupt sensitive
developmental processes. Reasonably available information from oral studies of experimental animal
models (i.e., rats and mice) also indicates that DBP is a developmental and reproductive toxicant (U.S.
24f). EPA considered exposure (Section 10.1) and hazard (Section 10.3) information, as well as
pharmacokinetic models (Section 10.2), to determine the most scientifically supportable appropriate
approach to evaluate infant exposure to DBP from human milk ingestion. The Agency concluded that
the most appropriate approach is to use human health hazard values that are based on fetal and infant
effects following maternal exposure during gestational and/or perinatal period. In other words, infant
exposure and risk estimates from maternal exposure are expected to also be protective of nursing infants.
10.1 Biomonitoring Information
DBP has the potential to accumulate in human milk because of its small mass (278.34 Daltons or g/mol)
and lipophilicity (log Kow = 4.5). EPA identified 13 biomonitoring studies, of which 1 is from the
United States, from reasonably available information that investigated if DBP or its metabolites were
present in human milk. DBP or its metabolites were detected in human milk samples in each of these
studies. A summary of the biomonitoring studies is provided in Figure 10-1. None of the studies
characterized if any of the study participants may be occupationally exposed to DBP.
DBP's primary metabolite, mono-n-butyl phthalate (MnBP), was measured in 21 samples collected from
the Mother's Milk Bank in California. The concentrations ranged from 0.69 to 210.24 ng/g lipid weight
(lw) with a median of 14.2 ng/g (Hartle et ai. 2018). The highest lipid weight concentration among eight
n on-U.S. studies was nearly the same (21 1.2 ng/g lw) (Brucker-Davis et ai. 2008). For wet weight
among the non-U.S. studies, the maximum concentration was 10,900 [j,g/L (median 9.6 (J,g/L, minimum
0.6 (J,g/L, n=130) among 130 Finnish and Danish mothers (Main et ai. 2006). The authors reported that
the interindividual variation for MnBP is extreme and that contamination may have occurred during
collection of the human milk samples at home (e.g., from air particles, breast pumps). The other six
studies had concentrations that ranged from 0.4 to 32.03 (.ig/L (Kim et ai. 2018; From me et ai. JO I I;
Lin et ai. 2011; Schlumpf et ai. 2010; Latini et ai. 2009; Hogberg et ai. 2008).
Six non-U.S. studies measured DBP concentrations in human milk. The highest was observed in a
cohort of 125 French mothers, (range: 1 1.8-529.4 ng/g; mean: 81.2 ng/g) (Brucker-Davis et ai. 2008).
Six other studies measured DBP concentrations that ranged from less than 0.1 to 11 ng/g lw and less
than 0.28 to 173.6 ng/mL wet weight (ww) (Kim et ai. 2020; Zimmermann et ai. 2012; Fromme et ai.
2011; Chen et ai. 2008; Hogberg et ai. 2008; Zhu et ai. 2006).
Although biomonitoring studies consistently detect DBP in human milk, concentrations reported in these
studies reflect total infant exposure. Biomonitoring data do not distinguish between exposure routes or
pathways and do not allow for source apportionment. In other words, the contribution of specific TSCA
COUs to overall exposure cannot be determined.
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Concentrations of DBP in ng/g
| General Population
NonUS
\7 Lognormal Distribution (CT and 90th percentile)
787934 - Fromme et al., 2011 - DE
0.01
0.1 1
10
Concentration (ng/g)
Concentrations of MnBP in ng/g
¦¦¦ General Population
US Not Specified ^ Lognormal Distribution (CT and 90th percentile)
4728555 - Hartle et al., 2018 - US
NonUS Lipid
1249442 - Schlumpf et al., 2010 - CH
0.01 0.1 1 10 100 1000
Concentration (ng/g)
¦¦ V
E
Concentrations of DBP in ng/L
General Population
A Normal Distribution (CT and 90th percentile)
NonUS
V Lognormal Distribution (CT and 90th percentile)
673262 - Chen et al., 2008 - CN
673465 - Hogberg et al., 2008 - SE
10
100 1000 10A4
Concentration (ng/L)
10A5
10*6
Concentrations of MnBP in ng/L
| General Population
A Normal Distribution (CT and 90th percentile)
US
V Lognormal Distribution (CT and 90th percentile)
673259 - Calafat, et al., 2004 - US
<1
NonUS
673480 - Main et al., 2006 - DK, FI
<3
<1
6815879 - Kim el al., 2020 - KR
4728479 - Kim et al., 2018 - KR
IV V
787934 - Fromme et al., 2011 - DE
¦v V
673525 - Latini et al., 2009 - IT
^7
1249442 - Schlumpf et al., 2010 - CH
^¦D
699479 - Lin et al., 2011 - TW
¦V V
10 100 1000 10A4 10A5 10A6 10*7 10A8
Concentration (ng/L)
Figure 10-1. Concentrations of DBP or MnBP in Human Milk in Either Lipid (ng/g) or Wet
Weight (ng/L)
10.2 Modeling Information
EPA explored the potential to model DBP concentrations in human milk resulting from specific sources
of maternal exposures with the aim of providing quantitative estimates of COU-specific milk exposures
and risks. The Agency identified a pharmacokinetic model described in Kapraun et al. (2022) as the best
available model to estimate transfer of lipophilic chemicals from mothers to infants during gestation and
lactation; hereafter referred to as the Kapraun Model. The only chemical-specific parameter required by
the Kapraun Model is the elimination half4ife in the animal species of interest.
EPA considered the model input data available for DBP and concluded that uncertainties in establishing
an appropriate half4ife value precludes using the model to quantify lactational transfer and exposure
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from TSCA COUs. Measurement of the parent phthalate {i.e., DBP) in organs, tissues, and matrices is
prone to error and contamination from sampling materials because of its rapid hydrolysis (Koch and
Calafat. 2009). DBP is rapidly hydrolyzed to its primary monoester metabolite, MnBP, which is also a
minor metabolite of benzyl butyl phthalate (BBP). This indicates that neither the parent compound nor
the primary metabolite is a sensitive biomarker of exposure to DBP. As a result, measured half-life
values for DBP and MnBP in plasma that were reported in Chang et al. (2013) and Fennel 1 et al. (2004)
were not considered. Furthermore, DBP's short 4-carbon side chain indicates that it is metabolized
through only hydrolysis and degradation (Wane et al.. 2019). Secondary oxidized metabolites are thus
not readily detectable. These uncertainties in establishing an appropriate half-life value for DBP does
not support using the model to quantify lactational transfer and exposure for TSCA COUs.
Instead, exposure estimates for workers, consumers, and the general population were compared against
the hazard values designed to be protective of infants and expressed in terms of maternal exposure levels
during gestation and the perinatal period.
10.3 Hazard Information
EPA considered multigenerational developmental and reproductive toxicity studies of rats that evaluated
the effects of oral exposures to DBP. The critical effect is disruption to androgen action during the
critical window of male reproductive development {i.e., during gestation), leading to a spectrum of
effects on the developing male reproductive system that is consistent with phthalate syndrome. These
effects follow gestational or perinatal oral exposures to DBP and are attributable to antiandrogenic
effects during gestation (see Draft Human Health Hazard Assessment for Dibutyl Phthalate (DBP) Qj.S.
Mf)). No studies were identified that evaluated only lactational exposure {i.e., from birth to
weaning) from quantified levels of DBP or its metabolites in milk. However, the hazard values are based
on developmental and reproductive toxicity in the offspring following maternal exposure during
gestation and the perinatal period. Because these values designed to be protective of infants are
expressed in terms of maternal exposure and hazard values to assess direct exposures to infants are
unavailable, EPA concluded that further characterization of infant exposure through human milk
ingestion would not be informative.
10.4 Weight of Scientific Evidence Conclusions
EPA considered infant exposure to DBP through human milk because the available biomonitoring data
demonstrate that DBP can be present in human milk and hazard data demonstrate that the developing
male reproductive system may be particularly susceptible to the effects of DBP. Although EPA explored
the potential to model milk concentrations and concluded that there is insufficient information {e.g.,
sensitive and specific half-life data) available to support modeling of the milk pathway, the Agency also
concluded that modeling is not needed to adequately evaluate risks associated with exposure through
milk. This is because the POD used in this draft assessment is based on male reproductive effects
resulting from maternal exposures throughout sensitive phases of development in multigenerational
studies. EPA therefore has confidence that the risk estimates calculated based on maternal exposures are
protective of a nursing infant.
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11 URINARY BIOMONITORING
Reverse dosimetry is an approach, as shown in Figure 11-1, of estimating an external exposure or intake
dose to a chemical using biomonitoring data (U.S. EPA. 2019b). In the case of phthalates, the U.S.
Centers for Disease Control and Prevention's (CDC) National Health and Nutrition Examination Survey
(NHANES) dataset provides a relatively recent (data available from 2017-2018) and robust source of
urinary biomonitoring data that is considered a national, statistically representative sample of the non-
institutionalized, U.S. civilian population. Phthalates have elimination half-lives on the order of several
hours and are quickly excreted from the body in urine and to some extent feces (ATSDR. 2022; EC/HC.
2015). Therefore, the presence of phthalate metabolites in NHANES urinary biomonitoring data
indicates recent phthalate exposure.
Reverse dosimetry is a powerful tool for estimating exposure, but reverse dosimetry modeling does not
distinguish between routes or pathways of exposure and does not allow for source apportionment (i.e.,
exposure from TSCA COUs cannot be isolated). Instead, reverse dosimetry provides an estimate of the
total dose (or aggregate exposure) responsible for the measured biomarker. Therefore, intake doses
estimated using reverse dosimetry are not directly comparable to the exposure estimates from the
various environmental media presented in this document. However, the total intake dose estimated from
reverse dosimetry can help contextualize the exposure estimates from TSCA COUs as being potentially
underestimated or overestimated.
[ Reverse Dosimetry ]
> Biomonitoring (urinary) data representative of the U.S.
population by age
> Aggregate exposure estimates are not source apportioned
Urinary concentration
of phthalate metabolite
d
O
I
I
~
Reverse dosimetry
j model
p. Daily intake of parent
phthalate
Figure 11-1. Reverse Dosimetry Approach for Estimating Daily Intake
11.1 Approach for Analyzing Biomonitoring Data
EPA analyzed urinary biomonitoring data from NHANES, which reports urinary concentrations for 15
phthalate metabolites specific to individual phthalate diesters. Specifically, EPA analyzed data for two
metabolites of DBP; mono-3-hydroxybutyl phthalate (MHBP) (measured in the 2013-2018 NHANES
cycles) and mono-n-butyl phthalate (MnBP) (measured in the 1999-2018 NHANES cycles). Although
MHBP was measured in the 2013 to 2018 NHANES cycles, the data for the 2013 to 2014 NHANES
cycle was determined to be inaccurate due to procedural error and was only released as surplus data,
which is not readily publicly available. As a result, the present analysis only includes urinary MHBP
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data from the 2015 to 2018 NHANES cycles. Sampling details can be found in Appendix G.
Urinary concentrations of DBP metabolites were quantified for different life stages and included women
of reproductive age (16-49 years ), adults (16+ years), adolescents (11 to <16 years), children (6 to <11
years), and toddlers (3 to <6 years), when data were available. Urinary concentrations of DBP
metabolites were analyzed for all available NHANES survey years to examine the temporal trend of
DBP exposure. However, intake doses using reverse dosimetry were calculated for the NHANES cycle
(2017-2018) as being most representative of current exposures because it was the most recently
available data.
NHANES uses a multi-stage, stratified, clustered sampling design that intentionally oversamples certain
demographic groups; to account for this, all data was analyzed using the survey weights provided by
NHANES and analyzed using weighted procedures in SAS and SUDAAN statistical software. Median
and 95th percentile concentrations were calculated in SAS and reported for life stages of interest.
Median and 95th percentile concentrations are provided in TableApx G-2. Statistical analyses of DBP
metabolite trends over time were performed with PROC DESCRIPT using SAS-callable SUDAAN.
11.1.1 Temporal Trend of MnBP
Figure 11-2 through Figure 11-7 show urinary MnBP concentrations plotted over time for the various
populations to visualize the temporal exposure trends. All data used for the temporal exposure trends are
provided in Table Apx G-2. Overall, MnBP urinary concentrations have decreased over time for all life
stages.
From 1999 to 2018, 50th and 95th percentile urinary MnBP concentrations significantly decreased over
time among all children under 16 (p < 0.001 for both percentile exposures) (Figure 11-4), as well as for
children aged 3 to less than 6 years (p < 0.001) (Figure 11-5), 6 to less than 11 years (p < 0.001) (Figure
11-6), and 11 to less than 16 years (p < 0.001) (Figure 11-7).
From 1999 to 2018, median and 95th percentile urinary MnBP concentrations significantly decreased
among all adults (p < 0.001 for both percentile exposures), female adults (p < 0.001 for 50th and 95th
percentile), male adults (p < 0.001 for 50th and 95th percentile) (Figure 11-2), and women of
reproductive age (p < 0.001 for 50th and 95th percentile) (Figure 11-3).
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1822
Adults (age 16+)
Females Males
1823
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oo-
C
O
c
QJ
U
c
O
u
_§ 50-
HJ
¦4—'
OJ
E
Q_
CQ
Q
rTiT
¥TY*T*
c!V ti1 ^ (S> A ^ k i^i kV & A
(A rv>s ffl) p{) pft |A )/b |^5 A r5^ rsN p(b c\0 rvV «P> p/b ^ A
NHANES cycle
Figure 11-2. Urinary DBP Metabolite Concentrations for Adults (16+ Years)
Metabolite
^ MNBP
MHBP
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1826
Women of reproductive age (16-49)
150-
CiO
c
o
£Z
CL>
u
c
o
u
100-
Metabolite
MNBP
A MHBP
O
_Q
ro
4-1
E
Q.
CO
Q
50-
jp eft1, csf* (S? ^ ^ ^
•f& 't& •!& 'r$ 'r& •<$> ' '<£>
Oi' K c$> eP rS? pV cf? cN° ftv-
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1830
NHANES cycle
Figure 11-3. Urinary DBP Metabolite Concentrations for Women of Reproductive Age (16-49
Years)
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All children (3-<16)
Females
Males
200-
GD
C
C
o
c
&
Metabolite
MNBP
A MHBP
CSV (\v* row (vu i/V kV fjo A (A cOf J)« rvb iQS A k v« iv v\
"jP 'y> yy 'n? 'n? 'jP 'iv5 'jv5 ':
? o?> of? rS^ of? cxN oK* cv^ c& oS> of? ^ of? o> cX*
r Lit T.
> k5>
^ ^ <$r ^ ^ i? -i? 1?
^ ^ ^ ^ ^ ^ ^ rp ^
NHANES cycle
Figure 11-4. Urinary DBF Metabolite Concentrations for All Children (3 to <16 Years) by Sex
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Toddlers (3-<6)
60-
GO
£Z
C
O
c
Q)
U
c
o
u
o
_Q
rc
¦M
E
CQ
Q
40-
20-
0-
1836
1837
1838
Metabolite
MNBP
A MHBP
NHANES cycle
Figure 11-5. Urinary DBP Metabolite Concentrations for Toddlers (3 to <6 Years)
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Children (6-<11)
200-
£ 50-
e»o
c
c
O
a> 00 •
u
c
O
u
O
_Q
03
"I 50-
Q_
CQ
Q
0-
r" T-u T
<& C?> "5s ¦O' •?>
-IF •/
c» ^ c£ ^ ^
N# <£> ^ ^ ^ ^ ^ ^
Metabolite
^=\ MNBP
A mhbp
1839
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NHANES cycle
Figure 11-6. Urinary DBF Metabolite Concentrations for Children (6 to <11 Years)
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Children (6-<11)
200-
Q0
o
(1)
u
o
u
150-
100 -
Metabolite
Fjq MNBP
MHBP
O
ro
¦M
<1)
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Q_
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Q
50-
0-
f *
T"1 Tj- T.
'$
» 4? «$? ct> c&
&
•V*
NHANES cycle
Figure 11-7. Urinary DBP Metabolite Concentrations for Adolescents (11 to <16 Years)
11.1.2 Changes in MHBP Concentrations
As mentioned in Section 11.1, only data from the 2015 to 2018 NHANES cycles were analyzed for
MHBP resulting in the two data points shown for MHBP concentrations in Figure 11-2 through Figure
11-7. Therefore, a temporal trend analysis was not conducted for MHBP. However, a comparison of the
metabolite concentrations between the 2015 to 2016 and 2017 to 2018 NHANES cycles show that while
95th percentile MHBP concentrations tended to decrease between the two cycles for children and adults,
they increased among women of reproductive age. Meanwhile, 50th percentile MHBP concentrations
tended to increase between the two cycles among children under 16 years, decrease for adults, and have
no significant changes for women of reproductive age.
11.1.3 Daily Intake of DBP from NHANES
Using DBP metabolite concentrations measured in the most recently available sampling cycle (2017-
2018), EPA estimated the daily intake of DBP through reverse dosimetry. Reverse dosimetry approaches
that incorporate basic pharmacokinetic information are available for phthalates (Koch et al.. 2007; Koch
et al.. 2003; David. 2000) and have been used in previous phthalate risk assessments conducted by U.S.
Consumer Product Safety Commission (CPSC) (2014) and Health Canada (Health Canada. 2020) to
estimate daily intake values for exposure assessment. For phthalates, reverse dosimetry can be used to
estimate a daily intake (DI) value for a parent phthalate diester based on phthalate monoester
metabolites measured in human urine using Equation 11-1 (Koch et al.. 2007) below. For DBP, the
phthalate monoester metabolites are MHBP and MnBP.
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Equation 11-1. Calculating the Daily Intake Value from Urinary Biomonitoring Data
(UE5um x CE)
Phthalate DI = -—^ x MWParent
F UccTirn
Where:
Phthalate DI
UF
KJ L-i o-j/rn
CE
Fuec
MW-,
parent
Daily intake (|ig/kg-day) value for the parent phthalate diester
Sum molar concentration of urinary metabolites associated with
the parent phthalate diester (|imol/g)
Creatinine excretion rate normalized by body weight (mg/kg-
day). CE can be estimated from the urinary creatinine values
reported in biomonitoring studies (i.e., NHANES) using the
equations of Mage et al. (2008) based on age, gender, height,
and race, as was done by Health Canada (Health Canada. 2020)
and U.S. CPSC (2014).
Summed molar fraction of urinary metabolites. The molar
fraction describes the molar ratio between the amount of
metabolite excreted in urine and the amount of parent
compound taken up. Fue values used for daily intake value
calculations are shown in Table 11-1.
Molecular weight of the parent phthalate diester (g/mol)
Table 11-1. Fue Values Used for the Calculation of Daily Intake Values by DBP
Metabolite
Fuefl
Reference
Study Population
MnBP
0.69
Anderson et al. (
n = 10 men (20-42 years of age) and 10
women (18-77 years of age)
a Fue values are presented on a molar basis and were estimated by study authors based on metabolite excretion over a
24-hour period.
Daily intake values were calculated for each participant from NHANES. A creatinine excretion rate for
each participant was calculated using equations provided by Mage et al. (2008). The applied equation is
dependent on the participant's age, height, race, and sex to accommodate variances in urinary excretion
rates. Creatinine excretion rate equations were only reported for people who are non-Hispanic Black and
non-Hispanic White, so the creatinine excretion rate for participants of other races were calculated using
the equation for non-Hispanic White adults or children, in accordance with the approach used by U.S.
CPSC (2015). Daily intake values for DBP are reported in Table 1 1-2.
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Table 11-2. Daily Intake Values for DBP Based on Urinary Biomonitoring from the 2017-2018
NHANES Cycle
Demographic
50th Percentile Daily Intake
Value (Median |95% CI|)
(Hg/kg-day)
95th Percentile Daily Intake
Value (Median |95%CI|)
(jig/kg-day)
All
0.33 (0.3-0.36)
1.16 (0.96-1.35)
Females
0.31 (0.27-0.35)
1.02 (0.93-1.11)
Males
0.34 (0.31-0.37)
1.33 (0.93-1.72)
White non-Hispanic
0.33 (0.29-0.38)
0.97 (0.7-1.24)
Black non-Hispanic
0.32 (0.28-0.37)
1.18 (0.84-1.52)
Mexican-American
0.29 (0.24-0.33)
0.91 (0.68-1.13)
Other
0.38 (0.31-0.44)
1.8 (-0.29-3.88)
Above poverty level
0.38 (0.33-0.43)
1.26 (0.91-1.62)
Below poverty level
0.31 (0.27-0.34)
1.04 (0.84-1.24)
Toddlers (3 to <6 years)
0.55 (0.5-0.6)
1.54(1.07-2)
Children (6 to <11 years)
0.36(0.31-0.41)
1.37 (0.88-1.86)
Adolescents (12 to <16 years)
0.28 (0.21-0.34)
0.62 (0.37-0.88)
Adults (16+ years)
0.21 (0.17-0.25)
0.61 (0.39-0.84)
Male toddlers (3 to <6 years)
0.56 (0.49-0.63)
2.02(1.31-2.74)
Male children (6 to <11 years)
0.38 (0.32-0.44)
1.41 (-0.01 to 2.83)
Male adolescents (12 to <16 years)
0.33 (0.26-0.4)
0.62 (-1.03 to 2.27)
Male adults (16+ years)
0.21 (0.15-0.28)
0.59 (0.35-0.83)
Female toddlers (3 to <6 years)
0.51 (0.44-0.57)
1.44(1.04-1.84)
Female children (6 to <11 years)
0.34 (0.28-0.41)
0.95 (0.62-1.29)
Female adolescents (12 to <16 years)
0.26 (0.17-0.34)
0.61 (0.29-0.94)
Women of reproductive age (16-49 years)
0.21 (0.16-0.26)
0.61fl
Female adults (16+ years)
0.21 (0.16-0.26)
0.61fl
All
0.33 (0.3-0.36)
1.16 (0.96-1.35)
a 95% confidence intervals (CI) could not be calculated due to small sample size or a standard error of zero
The calculated daily intake values in this analysis are similar to those reported by the U.S. CPSC (2014)
and Health Canada (Health Canada. 2020). The daily intake values in the present analysis are calculated
with all available NHANES data between 1999 and 2018, while the CPSC report only contains estimates
for MnBP calculated with data from the 2005-2006 NHANES cycle and the Health Canada analysis
used data from the 2007-2011 cycles of the Canadian Health Measures Survey.
Median and 95th percentile daily intake values in the U.S. CPSC (. ) report were estimated for men
and women of reproductive age (15-45 years). U.S. CPSC reports a median daily intake value for adults
aged 15 to 45 year as 0.66 |ig/kg-day and a 95th percentile daily intake value of 2.6 |ig/kg-day.
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Health Canada assessment reports median daily intake values for male children and female children
aged 6 to 11 as 1.3 |ig/kg-day (Health Canada. 2020). Among 12 to 19 year-old males, the median daily
intake value was 1.4 |ig-kg/day and the 95th percentile was 3.2 |ig-kg/day, and among 12 to 19 year-old
females, the median daily intake value was 0.71 |ig-kg/day and the 95th percentile was 1.8 |ig-kg/day
The reported median and 95th percentile daily intake values for adults (ages 20-49 years) were 0.58 and
1.8 |ig/kg-day for males and 0.55 and 0.6 |ig/kg-day for females.
As described previously, reverse dosimetry modeling does not distinguish between routes or pathways
of exposure and does not allow for source apportionment {i.e., exposure from TSCA COUs cannot be
isolated). Therefore, general population exposure estimates from exposure to ambient air, surface water,
and soil are not directly comparable. However, in contrasting the general population exposures
estimated for a screening level analysis with the NHANES biomonitoring data, many of the acute dose
rates or average daily doses from a single exposure scenario exceed the total daily intake values
estimated using NHANES. Taken together with results from U.S. CPSC (2014) stating that DBP
exposure comes primarily from personal care products for women and diet and indoor exposures for
infants, toddlers, and children, and that the outdoor environment did not contribute to DBP exposures,
the exposures to the general population ambient air, surface water, and drinking water quantified in this
assessment are likely overestimates, as estimates from individual pathways exceed the total intake
values measured even at the 95th percentile of the U.S. population for all ages. This supports the use of
exposure values in this assessment for a screening level analysis for the general population.
11.2 Limitations and Uncertainties of Reverse Dosimetry Approach
Controlled human exposure studies have been conducted and provide estimates of the urinary molar
excretion factor {i.e., the Fue) to support use of a reverse dosimetry approach. These studies most
frequently involve oral administration of an isotope-labelled {e.g., deuterium or carbon-13) phthalate
diester to a healthy human volunteer and then urinary excretion of monoester metabolites is monitored
over 24 to 48 hours. Fue values estimated from these studies have been used by both U.S. CPSC (2014)
and Health Canada (Health Canada. 2020) to estimate phthalate daily intake values using urinary
biomonitoring data.
Use of reverse dosimetry and urinary biomonitoring data to estimate daily intake of phthalates is
consistent with approaches employed by both U.S. CPSC (2014) and Health Canada (Health Canada.
2020). However, there are challenges and sources of uncertainty associated with the use of reverse
dosimetry approaches. The U.S. CPSC considered several sources of uncertainty associated with use of
human urinary biomonitoring data to estimate daily intake values and conducted a semi-quantitative
evaluation of uncertainties to determine the overall effect on daily intake estimates (see Section 4.1.3 of
(CPSC. 2014)). Identified sources of uncertainty include (1) analytical variability in urinary metabolite
measurements; (2) human variability in phthalate metabolism and its effect on metabolite conversion
factors {i.e., the Fue); (3) temporal variability in urinary phthalate metabolite levels; (4) variability in
urinary phthalate metabolite levels due to fasting prior to sample collection; (5) variability due to fast
elimination kinetics and spot samples; and (6) creatinine correction models for estimating daily intake
values.
In addition to some of the limitations and uncertainties discussed above and outlined by U.S. CPSC
(2014). the short half-lives of phthalates can be a challenge when using a reverse dosimetry approach.
Phthalates have elimination half-lives on the order of several hours and are quickly excreted from the
body in urine and to some extent feces ( PR. 2022; EC/HC. 2015). Therefore, spot urine samples, as
collected through NHANES and many other biomonitoring studies, are representative of relatively
recent exposures. Spot urine samples were used by Health Canada (Health Canada. 2020) and U.S.
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CPSC (2014) to estimate daily intake values. However, due to the short half-lives of phthalates, a single
spot sample may not be representative of average urinary concentrations that are collected over a longer
term or calculated using pooled samples (Shin et al. 2019; Aylward et ai. 2016). Multiple spot samples
provide a better characterization of exposure, with multiple 24-hour samples potentially leading to better
characterization, but are less feasible to collect for large studies (Shin et al.. 2019). Due to rapid
elimination kinetics, the U.S. CPSC concluded that spot urine samples collected at a short time (2-4
hours) since last exposure may overestimate human exposure, while samples collected at a longer time
(<14 hours) since last exposure may underestimate exposure (see Section 4.1.3 of U.S. CPSC (2014)
(U.S. CPSC. 2014)for further discussion).
11.3 Weight of Scientific Evidence Conclusions
For the urinary biomonitoring data, despite the uncertainties discussed in Section 11.2, overall, the U.S.
CPSC (2014) concluded that factors that might lead to an overestimation of daily intake seem to be well
balanced by factors that might lead to an underestimation of daily intake. Therefore, reverse dosimetry
approaches "provide a reliable and robust measure of estimating the overall phthalate exposure." Given
a similar approach and estimated daily intake values, EPA has robust confidence in the estimated daily
intake values calculated using reverse dosimetry on NHANES biomonitoring data. Again, reverse
dosimetry modeling does not distinguish between routes or pathways of exposure and does not allow for
source apportionment {i.e., exposure from TSCA COUs cannot be isolated), but EPA has robust
confidence in the use of its total daily intake value calculated using NHANES to contextualize the
exposure estimates from TSCA COUs as being overestimated as described in Section 11.1.3.
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12 ENVIRONMENTAL BIOMONITORING AND TROPHIC
TRANSFER
EPA assessed the environmental concentrations of DBP resulting from industrial and commercial
release estimates. Because DBP fate and exposure from groundwater, biosolids, and landfills were not
quantified, the Agency performed a qualitative assessment for all exposure scenarios ( 324g).
The assessments described in this TSD include the potential DBP dietary exposures to aquatic and
terrestrial organisms in the environment. EPA described the potential exposures of DBP to aquatic
organisms and aquatic-dependent terrestrial species through a qualitative description of the
biomonitoring data of studies of DBP in organism body tissue.
12.1 Aquatic Environmental Monitoring
Studies on DBP concentrations in aquatic species within the pool of reasonably available information
were coupled with larger investigations on dialkyl phthalate esters. Measured DBP concentrations (wet,
dry, or lipid equivalent) stemmed from studies examining phthalate ester levels in aquatic ecosystems.
Multiple aquatic species had DBP concentrations quantified and reported, from a total of 17 studies.
These DBP concentrations in aquatic organisms were evaluated to contextualize the qualitative
evaluation of trophic transfer and were not ultimately used in a quantitative analysis.
Wet Weight Summaries
Measured DBP concentrations stemmed from studies examining phthalate ester levels in aquatic
ecosystems. Multiple aquatic species had DBP wet weight (ww) concentrations reported and/or
calculated from a total of nine studies. Upon examining the highest geometric mean and/or average DBP
wet weight concentration at each trophic level, there is no discernable trend for DBP as it transfers up
trophic levels. Because DBP is expected to partition to lipid-containing tissues, only whole body, liver,
and brain tissue samples are reported in this TSD. Samples from muscle and soft tissue may provide an
underestimate of DBP concentrations.
DBP wet weight concentrations were reported for two primary producers from aquatic ecosystems (Chi.
2009; McConnell. 2007). In Vancouver, British Columbia, Canada, the green algae (Prasiola
meridionalis) from the urban False Creek Harbor had a geometric mean whole body DBP concentration
at 0.02 mg/kg ww (McConnell. 2007). This was lower than the average DBP concentration found in the
aquatic plant Potamogeton crispus from Northern China's Haihe River in the urban portion of Tianjin
that was measured in the plant's above ground tissue at approximately 0.078 mg/kg ww (Chi. 2009).
DBP wet weight concentrations have been reported for 11 species of primary consumers (e.g.,
crustaceans, mollusks, invertebrates, and herbivorous finfish) (Hu et al.. 2016; McConnell. 2007; Giam
et ai. 1978). The hepatopancreas of the dungeness crab (Cancer magister) from the urban False Creek
Harbor in Vancouver, British Columbia, Canada had a geometric mean DBP concentration at 0.015
mg/kg ww (McConnell. 2007). For five mollusk species, geometric mean DBP concentrations ranged
from 0.0023 to 0.034 mg/kg ww in the whole bodies of the softshell clam {Mya arenaria) and the blue
mussel (Mytilus edulis), which were both measured from the urban False Creek Harbor in Vancouver,
British Columbia, Canada, respectively (McConnell. 2007). The great blue spotted mudskipper
(.Boleophthalmuspectinirostris), an herbivorous finfish, from the coastal city Ningbo in the Yangtze
River Delta in China had an average DBP concentration at approximately 0.022 mg/kg ww in
homogenized organs (Hu et al.. 2016). Thus, geometric mean/average DBP concentrations ranged from
0.0023 to 0.034 mg/kg ww for primary consumers (McConnell. 2007).
Omnivorous finfish are secondary and tertiary consumers that had DBP wet weight concentrations
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reported and/or calculated for 11 species (Lucas and Polidoro. 2019; H.u et al. 2016; Jarosova et al.
2012; McConnelt. 2007; Camanzo et al.. 1987; De Vault. 1985; Giam , )
Homogenized organs of the flathead grey mullet (Mugil cephalus) from the coastal city Ningbo in the
Yangtze River Delta had the lowest average DBP concentration at approximately 0.0064 mg/kg ww (Hu
et al.. 2016). Carp from tributaries/harbors of five Wisconsin and one Ohio river had the highest
geometric mean, whole body DBP concentration at 8.36 mg/kg ww (De Vault. 1985). These samples
were collected as part of a contaminant monitoring program in the Great Lakes region and were
collected from areas with histories of known chemical contamination.
Similar to omnivorous finfish, piscivorous finfish are secondary and tertiary consumers. DBP wet
weight concentrations were reported for 40 piscivorous species (Lucas and Polidoro. 2019; Hu et al..
2016; McConnell. 2007; Peiinenburg and Struiis. 2006; Camanzo et al.. 1987; De Vault. 19' , ti.m et
al.. 1978; U.S. EPA. 1974). The herring (iClupeapallasii) from the coastal city Wenling in the Yangtze
River Delta had the lowest average DBP concentration in homogenized organs at approximately 0.0024
mg/kg ww (Hu et al.. 2016). The striped bonito (Sarda orientalis) from the coastal city Wenling in the
Yangtze River Delta had the highest average DBP concentration in homogenized organs at
approximately 0.079 mg/kg ww (Hu et al.. 2016). Additionally, bream and roach finfish, a piscivore and
an omnivore, from a mix of contaminated and non-contaminated sites throughout the Netherlands were
homogenized and had a geometric mean DBP concentration at 0.001 mg/kg ww (Peiinenburg and
Struii s. 2006).
Dry Weight Summaries
Multiple aquatic species had DBP dry weight concentrations reported from a total of six studies. Upon
examining the highest geometric mean and/or average DBP dry weight concentration at each trophic
level, there is no discernable trend for DBP as it transfers up trophic levels due to only two levels being
available for comparison. Because DBP is expected to partition to lipid-containing tissues, only whole
body, liver, and brain tissue samples are reported here. Samples from muscle and soft tissue can provide
an underestimate of DBP concentrations.
DBP dry weight concentrations were reported for two primary producers from aquatic ecosystems (Saliu
et al.. 2019; Chi. 2009). The aquatic plant Potamogeton crispus from Northern China's Haihe River in
the urban portion of Tianjin had the highest average DBP concentration in its roots at 1.28 mg/kg dw
(Chi. 2009). Whole-body plankton had the lowest mean DBP concentrations outside the Faafu Atoll,
islands included in the Republic of Maldives, at 0.0069 mg/kg dw (Saliu et al.. 2019).
Omnivorous finfish are secondary and tertiary consumers that had DBP dry weight concentrations
reported for six species (Valton et al.. 2014; Adeniyi et al.. JO I I; Huang et al.. 2008). In the mouth of
Nigeria's Ogun River, which flows through agriculture, urbanized, and industrial areas, the highest
mean DBP concentration was measured in the whole body of Synodontis sp. at approximately 1.72
mg/kg dw (Adeniyi et al.. 2011). The lowest mean DBP concentration was also measured in the mouth
of Nigeria's Ogun River in the whole body of Tilapia sp. at approximately 0.69 mg/kg dw (Adeniyi et
al. 2011).
Lipid Equivalent Summaries
Measured DBP concentrations stemmed from studies examining phthalate ester levels in aquatic
ecosystems. Multiple aquatic species had DBP equivalent lipid concentrations reported and/or calculated
from a total of four studies. If a study provided lipid content and reported concentrations in wet weights,
equivalent lipid concentrations were calculated by dividing a species' wet weight concentration by its
lipid content. Upon examining the highest geometric mean and/or average DBP equivalent lipid
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concentration at each trophic level, DBP generally decreases in concentration as it transfers up trophic
levels.
DBP equivalent lipid concentrations were reported for only one primary producer from aquatic
ecosystems (McConnell. 2007). In Vancouver, British Columbia, Canada, the green algae (Prasiola
meridionalis) from the urban False Creek Harbor had a geometric mean whole body DBP concentration
at 4.9 mg/kg equivalent lipid (McConnell. 2007).
DBP concentrations were reported for three species of primary consumers (e.g., crustaceans and
mollusks) (McConnell. 2007). The dungeness crab (Cancer magistef) from the urban False Creek
Harbor in Vancouver, British Columbia, Canada had a higher geometric mean DBP concentration in its
muscle than its hepatopancreas at 0.56 and 0.25 mg/kg equivalent lipid, respectively (McConnell. 2007).
For two mollusk species, geometric mean DBP concentrations ranged from 0.65 to 0.71 mg/kg
equivalent lipid in the whole bodies of softshell clam (Mya arenaria) and blue mussel (Mytilus edulis),
which were both from the urban False Creek Harbor in Vancouver, British Columbia, Canada
(McConnell. 2007). As a collective, primary consumers had geometric mean DBP concentrations
ranging from 0.25 to 0.71 mg/kg equivalent lipid (McConnell. 2007).
Omnivorous finfish are secondary and tertiary consumers that had DBP equivalent lipid concentrations
reported and/or calculated for nine species (McConnell. 2007; Camanzo et at.. 19S , \ s -!5).
Carp from tributaries/harbors of five Wisconsin and one Ohio river had the highest geometric mean,
whole body DBP concentration at approximately 22.56 mg/kg equivalent lipid (De Vault. 1985). The
shiner perch (Cymatogaster aggregata) from the urban False Creek Harbor in Vancouver, British
Columbia, Canada, had the lowest geometric mean DBP concentration in its whole body at 0.73 mg/kg
equivalent lipid (McConnell. 2007).
Similar to omnivorous finfish, piscivorous finfish are secondary and tertiary consumers. DBP equivalent
lipid concentrations were reported for 13 piscivorous species (McConnell. 2007; Peiinenburg and
Struiis. 2006; Camamzo et at.. 1987; De Vault. 1985). The white-spotted greenling (.Hexogrammos
stelleri) had the lowest geometric mean DBP concentration in its muscle at 0.12 mg/kg equivalent lipid
while the spiny dogfish (Squalus acanthias) had the highest geometric mean DBP concentration in its
muscle at 0.3 mg/kg lipid equivalent, which were both from the urban False Creek Harbor in Vancouver,
British Columbia, Canada (McConnell. 2007). Additionally, bream and roach finfish, a piscivore and an
omnivore, from a mix of contaminated and non-contaminated sites throughout the Netherlands were
homogenized and had a geometric mean DBP concentration at 0.2 mg/kg equivalent lipid based on a
median lipid content of 0.5 percent (Peiinenburg and Struiis. 2006). It should be noted that the heads and
tails of bream and roach finfish were removed before homogenization.
Unknown Unit Summaries
Measured DBP concentrations stemmed from studies examining phthalate ester levels in aquatic
ecosystems. Two studies had DBP concentrations reported and/or calculated for multiple aquatic
species, but did not specify their units as either wet, dry, or lipid equivalent concentrations. Upon
examining the highest geometric mean/average DBP concentration at each trophic level, there is no
discernable trend for DBP as it transfers up trophic levels due to only two levels being available for
comparison.
Omnivorous finfish are secondary and tertiary consumers that had DBP concentrations reported and/or
calculated for three species (Adeogun et al.. 2015). The redbelly tilapia (Tilapia zillii) from the
manmade Lake Eleyele in Ibadan, Nigeria, had the highest geometric mean DBP concentration in its
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muscle, gill, liver, and kidney at approximately 0.35 mg/kg (Adeoeum et al..! ). Meanwhile, the
Morymyrus rume from the manmade Lake Asejire in Ibadan, Nigeria, had the lowest geometric mean
DBP concentration in its muscle, gill, liver, and kidney at approximately 0.19 mg/kg (Adeoeum et al..
2015).
Similar to omnivorous finfish, piscivorous finfish are secondary and tertiary consumers that had DBP
concentrations reported and/or calculated for two piscivorous species (Adeoeum et al.. 2015). Geometric
mean DBP concentrations ranged from approximately 0.23 to 0.26 mg/kg in the muscle, gill, liver, and
kidney of the obscure snakehead (Parachanna obscura) and the African pike characin (Hepsetus odoe),
which were both from the manmade Lake Eleyele in Ibadan, Nigeria (Adeoeum et al.. 2015).
12.2 Trophic Transfer
EPA did not conduct a quantitative analysis of DBP trophic transfer. Due to its physical and chemical
properties, environmental fate, and exposure parameters, DBP is not expected to persist in surface water,
groundwater, or air. DBP has a water solubility of 11.2 mg/L, a log Koc value of 3.69, an estimated BCF
value of 159.4 L/kg, monitored fish BAF values between 110 and 1,247 L/kg, monitored aquatic
invertebrate BAF values between 500 and 6,600 L/kg, and a terrestrial biota-sediment accumulation
factor (BSAF) between 0.35 and 11.8 kg/kg. DBP is expected to have low bioaccumulation potential, no
apparent biomagnification potential, and thus low potential for uptake overall. For further information
on the sources of these values, please see the Draft Physical Chemistry, Fate, and Transport Assessment
for DibutylPhthalate (DBP) (U.S. EPA. 2024e). A study in 18 marine species found that the food-web
magnification factor for DBP is 0.70, indicating biodilution as trophic level increases (Mackintosh et al..
2004). DBP is (1) expected to degrade rapidly via direct and indirect photolysis; (2) have environmental
biodegradation half-life in aerobic environments on the order of days to weeks; (3) is not subject to long
range transport; (4) transforms in the environment via biotic and abiotic processes to form monobutyl
phthalate, butanol, and phthalic acid; (5) shows strong affinity and sorption potential for organic carbon
in soil and sediment; and (6) will be removed at rates between 65 and 98 percent in conventional
wastewater treatment systems. DBP may persist in sediment, soil, biosolids, or landfills after release to
these environments, but bioavailability is expected to be limited. The estimated BCF suggests DBP does
not meet the criteria to be considered bioaccumulative (estimated BCF/BAF > 1,000 L/kg) and
bioaccumulation and bioconcentration in aquatic and terrestrial organisms are not expected (U.S. EPA.
2012). Despite monitored BCF values exceeding 1,000 L/kg in the common carp (Cyprinus carpio), a
bottom-feeding omnivorous fish, from a study in Asan Lake, South Korea in Lee et al. ( ) (although
these samples were desiccated before analysis, suggesting that they overestimate body burden in the live
fish, and Asan Lake is one of the largest artificial lakes in Korea and is mainly used for agricultural and
industrial purposes, meaning it is likely affected by pollution coming from an industrial complex and
two nearby cities), and) as well as in several aquatic invertebrates (Mayer Jr et al.. 1973). the available
evidence from body burdens in higher trophic level piscivorous fish and the food-web magnification
factor study conducted by Mackintosh et al. (2004) provide evidence that trophic transfer of DBP is not
a likely source of significant DBP exposure. This conclusion is consistent with the observations made
for other phthalates with measured BCF/BAFs such as di-isodecyl phthalate (D1DP) ( )24h).
di-isononyl phthalate (D1NP) ( M), dicyclohexyl phthalate (DCHP) ( 024d).
and di-ethylhexyl phthalate (DEHP) ( ).
12.3 Weight of Scientific Evidence Conclusions
Based on the reasonably available data, EPA has robust confidence that that DBP is found in relatively
low concentrations (or not at all) in aquatic organism tissues—especially at higher trophic levels.
Furthermore, DBP has low bioaccumulation and biomagnification potential in aquatic and terrestrial
organisms, and thus low potential for trophic transfer through food webs. EPA therefore does not expect
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2168 risk from trophic transfer in wildlife at environmentally relevant concentrations of DBP and has
2169 proceeded with a qualitative assessment of trophic transfer in the environmental risk characterization
2170 (see Section 5.3 of the Draft Risk Evaluation for Dibutyl Phthalate (DBP) ( 2025d).
2171
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13 CONCLUSION OF ENVIRONMENTAL MEDIA
CONCENTRATION, GENERAL POPULATION EXPOSURE, AND
RISK SCREEN
13.1 Environmental Exposure Conclusions
DBP is expected to be released to the environment via air, water, and biosolids to landfills as detailed
within the environmental release assessment presented in the Draft Environmental Release and
Occupational Exposure Assessment for Dibutyl Phthalate (DBP) ( ,5b). Environmental
media concentrations were quantified in ambient air, soil from ambient air deposition, biosolids, surface
water, and sediment. Further details on the environmental partitioning and media assessment can be
found in the Draft Physical Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate (DBP)
( ig).
For the land pathway, there are uncertainties in the relevance of limited monitoring data for biosolids
and landfill leachate to the COUs considered. However, based on high-quality physical and chemical
property data, EPA determined that DBP has low persistence potential and mobility in soils. Therefore,
groundwater concentrations resulting from releases to the landfill or to agricultural lands via biosolids
applications were not quantified but are discussed qualitatively. Modeled soil DBP concentrations from
air deposition to soil (Section 8) and modeled DBP concentrations in biosolids-amended soils from
OESs (Table 3-2) with the resulting highest concentrations to soil are assessed quantitatively with
hazard thresholds (U.S. EPA. 2024c) for relevant soil-dwelling organisms and plants within the DBP
environmental risk characterization section ( 2025d).
For the water pathway, relevant flow data from the associated receiving waterbody were collected for
facilities reporting to TRI. Quantified release estimates to surface water were evaluated with PSC
modeling. For each COU with surface water releases, the highest estimated release to surface water was
modeled. Releases were evaluated for resulting environmental media concentrations at the point of
release {i.e., in the immediate receiving waterbody receiving the effluent). Due to uncertainty about the
prevalence of wastewater treatment from DBP-releasing facilities, all releases are assumed initially to be
released to surface water without treatment. The resulting surface water, pore water, and benthic
sediment concentrations are presented within Table 4-3 and will be utilized within the environmental
risk characterization for DBP for quantitative risk characterization.
Based on the conclusions on the physical and chemical and fate properties of DBP presented in the Draft
Physical Chemistry, Fate, and Transport Assessment for Dibutyl Phthalate (DBP) ( E024g),
EPA conducted a qualitative assessment trophic transfer in biota. Multiple aquatic species had DBP
concentrations quantified and reported from a total of 17 studies. Because DBP does not biomagnify and
is characterized as demonstrating trophic dilution, EPA did not conduct a quantitative modeling analysis
of the trophic transfer of DBP through food webs. The Agency has robust confidence that DBP has
limited bioaccumulation and bioconcentration potential based on physical chemical and fate properties,
biotransformation, and empirical bioaccumulation metricsO. Additionally, due to the physical chemical
properties, environmental fate, and exposure parameters of DBP, it is not expected to persist in surface
water, groundwater, or air.
13.2 Weight of Scientific Evidence Conclusions for Environmental Exposure
The weight of scientific evidence supporting the exposure estimate is decided based on the strengths,
limitations, and uncertainties associated with the exposure estimates, which are discussed in detail for
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biosolids (Section 3.1.1), landfills (Section 3.2.1), surface water (Section 4.4), ambient air (Section
8.3.1), and environmental biomonitoring and trophic transfer (Section 12.3). EPA summarized its weight
of scientific evidence using confidence descriptors: robust, moderate, slight, or indeterminate confidence
descriptors. The Agency used general considerations {i.e., relevance, data quality, representativeness,
consistency, variability, uncertainties) as well as chemical-specific considerations for its weight of
scientific evidence conclusions.
For its quantitative assessment, EPA modeled exposure due to various exposure scenarios resulting from
different pathways of exposure. Exposure estimates used high-end inputs for the purpose of a screening
level analysis as demonstrated within the land pathway for modeled concentrations of DBP in biosolids-
amended soils at relevant COUs and air to soil deposition of DBP (Section 3.1). Within the water
pathway, the release resulting in the highest environmental concentrations are presented within Section
4.1. When available, monitoring data were compared to modeled estimates to evaluate overlap,
magnitude, and trends. Differences in magnitude between modeled and measured concentrations
(Section 4.2) may be due to measured concentrations not being geographically or temporally close to
known releasers of DBP. The high-end modeled concentrations in the surface water for TRI-reported
releases and the modeled concentrations for generic release scenarios using a P75 or P90 flow (these
flow rates are considered more likely than the P50 to receive high-end industrial and commercial
releases) are the same order of magnitude as the high-end monitored concentrations found in surface
water. This confirms EPA's expectation that a screening approach with high-end modeled releases is
appropriate. The Agency has robust confidence that DBP has limited bioaccumulation and
bioconcentration potential based on physical chemical and fate properties, biotransformation, and
empirical metrics of bioaccumulation metrics.
13.3 General Population Screening Conclusions
The general population can be exposed to DBP from various exposure pathways. As shown in Table 2-1,
exposures to the general population via surface water, drinking water, fish ingestion, and ambient air
were quantified using a conservative, high-end scenario screening approach while exposures via the land
pathway {i.e., biosolids and landfills) were qualitatively assessed. Based on the high-end estimates of
environmental media concentrations summarized in Table 13-1, general population exposures were
estimated for the lifestage that would be most exposed based on intake rate and body weight.
The maximum fugitive release value used in this assessment was reported to the 2017 NEI dataset and is
associated with the Application of paints, coatings, adhesives and sealants (from institutional furniture
manufacturing) OES. The maximum stack release value used in this assessment was reported to the TRI
dataset and is associated with the Waste handling, treatment, and disposal (from paint and coating
manufacturing) OES.
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Table 13-1. Summary of High-End DBP Concentrations in Various Environmental Media from
Environmental Releases
OES"
Release Media
Environmental Media
DBP Concentration
Manufacturing (P50)
Water
Surface water (30Q5 flow)
616 |ig/L
Surface water (harmonic mean
flow)
885 |ig/L
Waste handling, treatment,
disposal
Water
Surface water (30Q5 flow)
14.5 ng/L
Surface water (harmonic mean)
14.5 ng/L
Highest monitored surface water
fNWOMC. 2021)
Water
Surface water (30Q5 flow)
26.8 (ig/L
Surface water (harmonic mean)
26.8 (ig/L
Waste handling, treatment,
disposal (Stack)
Ambient air
Daily-averaged total (fugitive
and stack, 100m)
17.26 (ig/m3
Application of paints, coatings,
adhesives, and sealants
(Fugitive)
Annual-averaged total (fugitive
and stack, 100m)
11.82 (ig/m3
a Table 1-1 provides the crosswalk of OESs to COUs
Table 13-2 summarizes the conclusions for the exposure pathways and lifestages that were assessed for
the general population. EPA conducted a quantitative evaluation for the following: incidental dermal and
incidental ingestion from swimming in surface water, drinking water ingestion, fish ingestion, and
ambient air. Biosolids and landfills were assessed qualitatively in Sections 3.1 and 3.2, respectively.
Results indicate that no pathways were of concern for DBP for the highest exposed populations except
for one—fish ingestion for Tribal populations. Because screening risk estimates resulted in risk values
below the benchmark for fish ingestion for tribal populations using water solubility as the water
concentration, EPA refined its evaluation by using the three OESs that resulted in the highest modeled
surface water concentrations based on releases to water combined with the flow rate of the receiving
water body (Section 4.1). This refined analysis resulted in screening level risk estimates below the
benchmark for the PVC plastic compounding OES based on current 95th percentile ingestion rate and
heritage ingestion rate (see Section 7.3). Therefore, ingestion of fish potentially contaminated with DBP
can be a pathway of concern for tribal populations.
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Table 13-2. Risk Screen for High-
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nd Exposure Scenarios for Highest Exposed Populations
OES(s)
Exposure
Pathway
Exposure
Route
Exposure Scenario
Lifestage
Pathway of
Concern''
All
Biosolids
(Section 3.1)
No specific exposure scenarios were assessed for
qualitative assessments
No
All
Landfills
(Section 3.2)
No specific exposure scenarios were assessed for
qualitative assessments
No
Manufacturing
Surface water
Dermal
Dermal exposure to DBP in
surface water during
swimming (Section 5.1.1)
All
No
Oral
Incidental ingestion of DBP
in surface water during
swimming (Section 5.1.2)
All
No
Manufacturing
Waste handling,
treatment, disposal
Drinking
water
Oral
Ingestion of drinking water
(Section 6.1.1)
All
No
Manufacturing
Waste handling,
treatment, disposal
Fish ingestion
Oral
Ingestion of fish for general
population (Section 7.1)
Adults and
young toddlers
(1-2 years)
No
Ingestion of fish for
subsistence fishers (Section
7.2)
Adults (16 to
<70 years)
No
Ingestion of fish for tribal
populations (Section 7.3)
Adults (16 to
<70 years)
No
Waste handling,
treatment, disposal
(stack)
Ambient air
Inhalation
Inhalation of DBP in ambient
air resulting from industrial
releases (Section 9)
All
No
Application of paints,
coatings, adhesives,
and sealants
(fugitive)
Oral
Ingestion of soil from air to
soil deposition resulting from
industrial releases (Section 9)
Infants and
children
(6 month to 12
years)
No
a Table 1-1 provides a crosswalk of COUs to OES
b Using the MOE approach as a risk screening tool, an exposure pathway was determined to not be a pathway of
concern if the MOE was equal to or exceeded the benchmark MOE of 30.
13.4 Weight of Scientific Evidence Conclusions for General Population
Exposure
The weight of scientific evidence supporting the exposure estimate is decided based on the strengths,
limitations, and uncertainties associated with the exposure estimates, which are discussed in detail for
biosolids (Section 3.1.1), landfills (Section 3.2.1), surface water (Section 4.3.1 and 4.4), drinking water
(Section 6.4), fish ingestion (Section 7.4.1), ambient air (Sections 8.3.1 and 8.4), human milk (Section
10.4), and urinary biomonitoring (Section 11.2 and I I 3).
EPA summarized its weight of scientific evidence using confidence descriptors: robust, moderate, slight,
or indeterminate confidence descriptors. The Agency used general considerations {i.e., relevance, data
quality, representativeness, consistency, variability, uncertainties) as well as chemical-specific
considerations for its weight of scientific evidence conclusions.
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EPA determined robust confidence in its qualitative assessment and conclusions pertaining to exposures
from biosolids (Section 3.1.1) and landfills (Section 3.2.1). For its quantitative assessment, the Agency
modeled exposure due to various exposure scenarios resulting from different pathways of exposure.
Exposure estimates used high-end inputs for the purpose of a screening level analysis. When available,
monitoring data were compared to modeled estimates to evaluate overlap, magnitude, and trends to
inform confidence in the quantitative exposure assessment of surface water (Sections 4 and 5), drinking
water (Section 6), fish ingestion (Section 7), ambient air (Sections 8 and 9), and human milk (Section
10). EPA has robust confidence that the screening level analysis was appropriately conservative to
determine that no environmental pathway has the potential for non-cancer risks to the general
population. Despite slight to moderate confidence in the estimated absolute values themselves,
confidence in exposure estimates capturing high-end exposure scenarios was robust given the many
conservative assumptions. Additionally, EPA conducted reverse dosimetry to calculate daily intake
values for DBP using biomonitoring data from NHANES. Notably, many of the acute dose rates or
average daily doses from a single exposure scenario exceed the total daily intake values estimated even
at the 95th percentile of the U.S. population for all ages using NHANES. Furthermore, risk estimates for
high-end exposure scenarios were still consistently above the benchmarks adding to confidence that
non-cancer risks are not expected.
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2763 APPENDICES
PUBLIC RELEASE DRAFT
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2764
2765 Appendix A EXPOSURE FACTORS
2766
2767 Table Apx A-l. Body Weight by Age Group
Age Group"
Mean Body Weight (kg)''
Infant (<1 year)
7.83
Young toddler (1 to <2 years)
11.4
Toddler (2 to <3 years)
13.8
Small child (3 to <6 years)
18.6
Child (6 to <11 years)
31.8
Teen (11 to <16 years)
56.8
Adults (16+ years)
80.0
a Age group weighted average
* See Table 8-1 of U.S. EPA (
2768
Table Apx A-2. Fish Ingestion
iates by Age Group
Age Group
Fish Ingestion Rate
(g/kg-day)"
50th Percentile
90th Percentile
Infant (<1 year) b
N/A
N/A
Young toddler (1 to <2 years) b
0.053
0.412
Toddler (2 to <3 years) h
0.043
0.341
Small child (3 to <6 years) b
0.038
0.312
Child (6 to <11 years)b
0.035
0.242
Teen (11 to <16 years) b
0.019
0.146
Adult (16+ years)c
0.063
0.277
Subsistence fisher (adult) d
1.78
a Age group weighted average, using body weight from Table Apx A-l
b See Table 20a of U.S. EPA (2014)
c See Table 9a of U.S. EPA (2014)
dU.S. EPA (2000b)
2770
2771
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2772 Table Apx A-3. Recommended Default Values for Common Exposure Factors
Symbol
Definition
Recommended
Default Value
Recommended Default
Value
Source/Notes
Occupational
Residential
ED
Exposure duration
(hours/day)
8
24
EF
Exposure frequency
(days/year)
250
365
EY
Exposure years
(years)
40
Varies for Adult (chronic non-
cancer)
78 (Lifetime)
1 Infant (birth to <1 year)
5 Toddler (1-5 years)
5 Child (6-10 years)
5 Youth (11-15 years)
5 Youth (16-20 years)
Number of years in age group
Note: These age bins may vary
for different measurements and
sources
AT
Averaging time
non-cancer
Equal to total
exposure duration or
365 days/yr x EY;
whichever is greater
Equal to total exposure
duration or 365 days/yr x EY;
whichever is greater
See pg. 6-23 of Risk
assessment guidance for
superfund, volume I: Human
health evaluation manual (Part
A). (U.S. EPA. 1989)
Averaging time
cancer
78 years
(28,470 days)
78 years
(28,470 days)
See Table 18-1 of the Exposure
Factors Handbook (U.S. EPA,
2011 a)
BW
Body weight (kg)
80
80 Adult
7.83 Infant (birth to <1 year)
16.2 Toddler (1-5 years)
31.8 Child (6-10 years)
56.8 Youth (11-15 years)
71.6 Youth (16-20 years)
65.9 Adolescent woman of
childbearing age (16 to <21)
- apply to all developmental
exposure scenarios
See Table 8-1 of the Exposure
Factors Handbook (U.S. EPA,
2011a)
(Refer to Figure 31 for age-
specific BW)
Note: These age bins may vary
for different measurements and
sources
See Table 8-5 of the Exposure
Factors Handbook (U.S. EPA,
2011a)
IRdw-acute
Drinking water
ingestion rate
(L/day) - acute
3.219 Adult
3.219 Adult
1.106 Infant (birth to <1 year)
0.813 Toddler (1-5 years)
1.258 Child (6-10 years)
1.761 Youth (11-15 years)
2.214 Youth (16-20 years)
See Tables 3-15 and 3-33;
weighted average of 90th
percentile consumer-only
ingestion of drinking water
(birth to <6 \ ears) (U.S. EPA.
2011a)
IRdw-chronic
Drinking water
ingestion rate
(L/day) - chronic
0.880 Adult
0.880 Adult
0.220 Infant (birth to <1 year)
Chapter 3 of the Exposure
Factors Handbook (U.S. EPA,
2011a). Table 3-9 per capita
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Symbol
Definition
Recommended
Default Value
Recommended Default
Value
Source/Notes
Occupational
Residential
0.195 Toddler (1-5 years)
0.294 Child (6-10 years)
0.315 Youth (11-15 years)
0.436 Youth (16-20 years)
mean values; weighted
averages for adults (21-49 and
50+years), for toddlers (years
1-2, 2-3, and 3 to <6).
IRmc
Incidental water
ingestion rate (L/h)
0.025 Adult
0.05 Child (6 to < 16 years)
Evaluation of Swimmer
Exposures Using the
SWIMODEL Algorithms and
Assumptions (U.S. EPA.
2015 a)
IRfish
Fish ingestion rate
(g/day)
22 Adult
Estimated Fish Consumption
Rates for the U.S. Population
and Selected Subpopulations
(U.S. EPA. 2014)
This represents the 90th
percentile consumption rate of
fish and shellfish from inland
and nearshore waters for the
U.S. adult population 21 years
of age and older, based on
NHANES data from 2003-
2010
IRsoil
Soil ingestion rate
(mg/day)
50 Indoor workers
100 Outdoor
workers
100 Infant (<6 months)
200 Infant to Youth (6 months
to <12 years)
100 Youth to Adult (12+
years)
1,000 Soil Pica Infant to
Youth (1 to <12 years)
50,000 Geophagy (all ages)
U.S. EPA Risk Assessment
Guidance for Superfund
Volume I: Human Health
Evaluation Manual (1991)
Chapter 5 of the Exposure
Factors Handbook (U.S. EPA,
20113). Table 5-1. Uooer
percentile daily soil and dust
ingestion
SAwater
Skin surface area
exposed (cm2) used
for incidental water
dermal contact
19,500 Adult
7,600 Child (3 to < 6 years)
10,800 Child (6 to < 11 years)
15,900 Youth (11 to< 16
years)
Chapter 7 of the Exposure
Factors Handbook (U.S. EPA,
2011a). Table 7-1;
recommended mean values for
total body surface area, for
children (sexes combined) and
adults by sex
KP
Permeability
constant (cm/h) used
for incidental water
dermal contact
0.001
Or calculated using Kp
equation with chemical
specific Kow and MW (see
exposure formulas)
EPA Dermal Exposure
Assessment: Principles and
Applications (U.S. EPA, 1992).
Table 5-7, "Predicted Kp
Estimates for Common
Pollutants"
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Symbol
Definition
Recommended
Default Value
Recommended Default
Value
Source/Notes
Occupational
Residential
SAsoil
Skin surface area
exposed (cm2) used
for soil dermal
contact
3,300 Adult
5,800 Adult
2,700 Child
EPA Risk Assessment
Guidance for Superfund RAGS
Part E for Dermal Exposure
(U.S. EPA. 2004)
AF soil
Adherence factor
(mg/cm2) used for
soil dermal contact
0.2 Adult
0.07 Adult
0.2 Child
EPA Risk Assessment
Guidance for Superfund RAGS
Part E for Dermal Exposure
(Ij.S. EPA. 2004)
2773
2774
2775 Table Apx A-4. Mean and Upper Milk Ingestion Rates by Age
Age Group
Milk Ingestion (mL/kg day)
Mean
Upper (95th percentile)
Birth to <1 month
150
220
1 to <3 month
140
190
3 to <6 month
110
150
6 to <12 month
83
130
Birth to <1 year
104.8
152.5
2776 A.1 Surface Water Exposure Activity Parameters
2777
2778 Table Apx A-5. Incidental Dermal (Swimming) Modeling Parameters
Input
Description
(Units)
Adult
(21+
years)
Youth
(11-15
years)
Child
(6-10
years)
Notes
Reference
BW
Body weight (kg)
80
56.8
31.8
Mean body weight. Chapter 8 of the Exposure
Factors Handbook, Table 8-1
U.S. EPA (2021)
SA
Skin surface area
exposed (cm2)
19,500
15,900
10,800
U.S. EPA Swimmer Exposure Assessment
Model (SWIMODEL)
U.S. EPA (2015a)
ET
Exposure time
(h/day)
3
2
1
High-end default short-term duration from
U.S. EPA Swimmer Exposure Assessment
Model (SWIMODEL)
U.S. EPA (2015a)
ED
Exposure duration
(years for ADD)
57
5
5
Number of years in age group
U.S. EPA (2021)
AT
Averaging time
(years for ADD)
57
5
5
Number of years in age group
U.S. EPA (2021)
KP
Permeability
coefficient (cm/h)
0.0071 cm/h
CEM estimate aqueous Kp
(U.S. EPA; I OF
Consulting, 2022)
2779
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2780
2781 Table Apx A-6. Incidental Oral Ingestion (Swimming) Modeling Parameters
Input
Description
(Units)
Adult
(21+
ycars)
Youth
(11-15
years)
Child
(6-10
years)
Notes
Reference
IRinc
Ingestion rate (L/h)
0.092
0.152
0.096
Upper percentile ingestion while
swimming. Chapter 3 of the Exposure
Factors Handbook, Table 3-7.
U.S. EPA (2019a)
BW
Body weight (kg)
80
56.8
31.8
Mean body weight. Chapter 8 of the
Exposure Factors Handbook, Table 8-1.
U.S. EPA (2021)
ET
Exposure time
(hr/day)
3
2
1
High-end, default, short-term duration
from U.S. EPA Swimmer Exposure
Assessment Model (SWIMODEL);
based on competitive swimmers in the
age class
U.S. EPA (2015a)
IRinc-
daily
Incidental daily
ingestion rate
(L/day)
0.276
0.304
0.096
Calculation: ingestion rate x exposure
time
IR/BW
Weighted
incidental daily
ingestion rate
(L/kg-day)
0.0035
0.0054
0.0030
Calculation: ingestion rate/body weight
ED
Exposure duration
(years for ADD)
57
5
5
Number of years in age group
U.S. EPA (2021)
AT
Averaging time
(years for ADD)
57
5
5
Number of years in age group
U.S. EPA (2021)
CF1
Conversion factor
(mg/ng)
1.00E-03
CF2
Conversion factor
(days/year)
365
2782
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Appendix B ESTIMATING HYDROLOGICAL FLOW DATA FOR
SURFACE WATER MODELING
EPA's ECHO database was accessed via the Application Programming Interface (API) and queried for
facilities regulated under the Clean Water Act. All available NPDES permit IDs were retrieved from the
facilities returned by the query. An additional query of the DMR REST service was conducted via the
ECHO API to return the National Hydrography Dataset Plus (NHDPlus) reach code associated with the
receiving waterbody for each available facility. Modeled flow metrics were then extracted for the
retrieved reach codes from the NHDPlus V2.1 Flowline Network's Enhanced Runoff Method (EROM)
Flow database. The EROM database provides modeled monthly average flows for each month of the
year. While the EROM flow database represents averages across a 30-year time period, the lowest of the
monthly average flows was selected as a substitute for the 30Q5 (the lowest 30-day average flow that
occurs on average once every 5 years) flow used in modeling, as both approximate the lowest observed
monthly flow at a given location. The substitute 30Q5 flow was then plugged into the regression
equation used by the EPA surface water model, E-FAST, to convert between these flow metrics and
solved for the 7Q10 (the lowest 7-day average flow that occurs on average once every 10 years) using
EquationApx B-l. In previous assessments, the EPA has selected the 7Q10 flow as a representative
low flow scenario to assess ecological impacts from effluent discharges into streams, while the harmonic
mean represents a more average flow for assessing chronic drinking water exposure.
Equation Apx B-l. Calculating the 7Q10 Flow
1.0352
fo409 snLxmi\
7QW = \ MLD 1.782 )
0 409 CfS
MLD
Where:
7Q10 = Modeled 7Q10 flow, in million liters per day (MLD)
30(^5 = Lowest monthly average flow from NHD, in MLD
Further, the harmonic mean (HM) flow was calculated using Equation Apx B-2, derived from the
relevant E-FAST regression (1, ^ \ 20071
Equation Apx B-2. Calculating the Harmonic Mean Flow
0.473 / f \ 0.552
(0.409 jj/j-fi x AM
HM
{0A09mnxAM)°473 x (°-409mi7x 7H
= 1.194 x - - -
0 409 CfS
MLD
Where:
HM = Modeled harmonic mean flow, in MLD
AM = Annual average flow from NHD, in MLD
7Q10 = Modeled 7Q10 flow from the previous equation, in MLD
In addition to the hydrologic flow data retrieved from the NHDPlus database, information about the
facility effluent rate was collected, as available, from the ECHO API. The receiving waterbody flow was
then calculated as the sum of the hydrologic flow estimated from regression, and the facility effluent
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flow. From the distribution of resulting receiving waterbody flow rates across the pooled flow data of all
relevant NAICS codes, the median (P50) flow rate was applied as a conservative low flow condition
across the modeled releases (Figure Apx B-l). Additional refined analyses were conducted for the
scenarios resulting in the greatest environmental concentrations by applying the 75th and 90th percentile
(P75 and P90, respectively) flow metrics from the distribution, which were expected to be more
representative of the flow conditions associated with high-end releases.
200-
C/5
C
o
.£ "CD
150-
c/>
^ J5
CD O
^ CO 100
O O
XI 2
I!
_cu
CD
ir.
50-
0-
10*
_±j
103
_L
¦I
10°
_L
4
_L
10'
10°
10°
Combined Plant Effluent and
Receiving Waterbody 7Q10 Modeled Flow (m3/day)
Figure Apx B-l. Distribution of Receiving Waterbody 7Q10 Modeled Flow for Facilities with
Relevant NAICS Classifications
For each COU with surface water releases, the highest estimated release of DBP to surface water was
used to estimate the corresponding DBP concentrations in the receiving water body. The total days of
release associated with the highest COU release was applied as continuous days of release per year (e.g.,
a scenario with 250 days of release per year was modeled as 250 consecutive days of release, followed
by 115 days of no release, per year). Raw daily concentration estimates from PSC were manually
evaluated for the highest resulting concentrations in an averaging window equal to the total days of
release (for example, a scenario with 250 days of release was evaluated for the highest 250-day average
concentration). The frollmean function in the data.table package in R was used to calculate the rolling
averages. The function takes in the concentration values to be averaged (extracted from the PSC Daily
Output File) and the number of values to include in the averaging window which was total days of
release (extracted from the PSC Summary Output File). The function outputs a list of averages from
consecutive averaging windows (for example, the first average will be for values 1- total days of release
and the second average will be for values 2- total days of release +1).
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Appendix C SURFACE WATER RISK SCREENING RESULTS
C.l Incidental Dermal Exposures (Swimming)
Based on the estimated dermal doses in [ADD], EPA screened for risk to adults (21+ years), youth (11-
15 years), and children (6-10 years). Table Apx C-l summarizes the acute MOEs based on the dermal
doses. Using the total acute dose based on the highest modeled 95th percentile, the MOEs are greater
than the benchmark of 30 (U.S. EPA. 2024f). Based on the conservative modeling parameters for
surface water concentration and exposure factors parameters, risk for non-cancer health effects for
dermal absorption through swimming is not expected.
TableApx C-l. Risk Screen for Modeled Incidental Dermal (Swimming) Doses for Adults,
Youths, and Children from Modeling and Monitoring Results
Scenario
Water Column
Concentrations
Adult
(21 + years)
Youth
(11-15 years)
Child
(6-10 years)
30Q5 Cone.
(jig/L)
Harmonic Mean
Cone. (jig/L)
Acute MOE
Acute MOE
Acute MOE
Manufacturing (P50)
885
616
203
265
437
Highest monitored surface water
(NWOMC 2021)
26.8
26.8
6,697
8,748
14,420
C.2 Incidental Ingestion
Based on the estimated incidental ingestion doses in Table 5-2, EPA screened for risk to adults (21+
years), youth (11-15 years), and children (6-10 years). Table Apx C-2 summarizes the acute MOEs
based on the incidental ingestion doses. Using the total acute dose based on the highest modeled 95th
percentile, the MOEs are greater than the benchmark of 30 ( 24f). Based on the
conservative modeling parameters for surface water concentration and exposure factors parameters,
risk for non-cancer health effects for incidental ingestion through swimming is not expected.
Table Apx C-2. Risk Screen for Modeled Incidental Ingestion Doses for Adults, Youths, and
Children from Modeling and Monitoring Results
Scenario
Water Column
Concentrations
Adult
(21+ years)
Youth
(11—15 years)
Child
(6—10 years)
30Q5 Cone.
(^g/L)
Harmonic Mean
Cone. (jig/L)
Acute MOE
Acute MOE
Acute MOE
Manufacturing (P50)
885
616
688
443
786
Highest monitored surface
water (NWOMC 2021)
26.8
26.8
22,713
14,641
25,956
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Appendix D GENERAL POPULATION DRINKING WATER RISK
SCREENING RESULTS
Based on the estimated drinking water doses in Table 6-1, EPA screened for risk to adults (21+ years),
infants (birth to <1 year), and toddlers (1-5 years). TableApx D-l summarizes the acute and chronic
MOEs based on the drinking water doses. Using the total acute and chronic dose based on the highest
modeled 95th percentile, the MOEs are greater than the benchmark of 30 ( 24f) except for
the Manufacturing OES, which is based on a high-end release estimate to multiple environmental media,
paired with a very low flow assumptions. This protective screening scenario, with the entirety of the
estimated environmental release assumed to be released directly to surface water, results in an MOE less
than the benchmark in only the most extreme hypothetical exposure scenario with an unlikely
confluence of factors. Based on the conservative modeling parameters for drinking water concentration
and exposure factors parameters, risk for non-cancer health effects for drinking water ingestion is not
expected.
This assessment assumes that concentrations at the point of intake for the drinking water system are
equal to the concentrations in the receiving waterbody at the point of release, where treated effluent is
being discharged from a facility. In reality, some distance between the point of release and a drinking
water intake would be expected, providing space and time for additional reductions in water column
concentrations via degradation, partitioning, and dilution. Some form of additional treatment would
typically be expected for surface water at a drinking water treatment plant, including coagulation,
flocculation, and sedimentation, and/or filtration. This treatment would likely result in even greater
reductions in DBP concentrations prior to releasing finished drinking water to customers.
Table Apx D-l. Risk Screen for Modeled Drinking Water Exposure for Adults, Infants, and
Toddlers from Modeling and Monitoring Results
Water Column
Adult
Infant
Toddler
Concentrations
(21 + years)
(Birth to <1 year)
(1-5 years)
Scenario
30Q5
Cone.
(^g/L)
Harmonic
Mean Cone.
(^g/L)
Acute
Chronic
Acute
Chronic
Acute
Chronic
MOE
MOE
MOE
MOE
MOE
MOE
Manufacturing (P50
flow)
616
885
59
110,000
17
44,000
47
100,000
Manufacturing (P75
flow)
24.4
46.6
1,120
2,900,000
319
1,100,000
898
2,600,000
Manufacturing (P90
1.7
3.0
17,000
41,000,000
4,958
16,000,000
14,000
37,000,000
flow)
Waste Handling,
14.5
14.5
3,599
4,800,000
1,026
1,900,000
2,884
4,400,000
Treatment, and
Disposal (TRI
Reported Release)
High from
26.8
26.8
1,947
2,601,209
555
1,018,360
1,561
2,376,062
Monitoring
Without Wastewater
Treatment fNWOMC.
202 n
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Appendix E FISH INGESTION RISK SCREENING RESULTS
E.l General Population
Using conservative exposure estimates based on the water solubility limit as the surface water
concentration, acute and chronic non-cancer risk estimates for the general population were below the
benchmark of 30 for both fish species (TableApx E-l). In comparison, the risk estimates using the
highest monitored surface water concentration (NWQMC. 2021) (Section 4.2.1) exceed the benchmark
by two to three orders of magnitude. EPA then refined its analysis by modeling surface water
concentrations based on the high-end harmonic mean release for the Manufacturing OES. The acute,
non-cancer risk estimate using modeled surface water concentration for the PVC plastics compounding
OES exceeded the benchmark of 30. These results indicate that fish ingestion is not a pathway of
concern for DBP for the general population.
Table Apx E-l. Risk Estimates for Fish Ingestion Exposure for General Population
Acute Non-Cancer MOE
UFs = 30
Adult, Chronic and
Non-Cancer MOE
UFs = 30
Adult
Young Toddler
Water solubility limit (11.2 mg/L)
2 (tilapia)
2.2 (common carp)
1 (tilapia)
1.4 (common carp)
7 (tilapia)
9 (common carp)
PVC plastics compounding (HE,
1.78E-02 mg/L)
1,037 (tilapia)
1,354 (common carp)
698 (tilapia)
912 (common carp)
4,567 (tilapia)
5,964 (common carp)
Manufacturing OES, P75, HE
(generic scenario) (2.24E-02 mg/L)
756 (tilapia)
988 (common carp)
510 (tilapia)
665 (common carp)
3,332 (tilapia)
4,351 (common carp)
Monitored surface water
concentration (8.2E-03 mg/L)
(NWOMC. 2021)
2,251 (tilapia)
2,939 (common carp)
1,516 (tilapia)
1,980 (common carp)
9,915 (tilapia)
12,946 (common carp)
HE = high-end; MOE = margin of exposure; PVC = polyvinyl chloride; UF = uncertainty factor
E.2 Subsistence Fishers
Acute and chronic non-cancer risk estimates for subsistence fishers were below the benchmark using the
water solubility limit as the surface water concentration for both fish species (Table Apx E-2). In
comparison, the risk estimates using the highest monitored surface water concentration (NWQMC.
2021) (Section 4.2.1) exceed the benchmark by one order of magnitude. EPA then refined its analysis by
modeling surface water concentrations based on the high-end harmonic release for the Manufacturing
OES. The acute and chronic non-cancer risk estimates exceeded the benchmark of 30 for both fish
species. These results indicate that fish ingestion is not a pathway of concern for DBP for subsistence
fishers.
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Table Apx E-2. Risk Estimates for Fish Ingestion Exposure for Subsistence Fishers
Acute and Chronic Non-Cancer MOE
UFs = 30
Water solubility limit (11.2 mg/L)
0.3 (tilapia)
0.3 (common carp)
Manufacturing OES, P75, HE (generic scenario) (2.24E-02
mg/L)
198 (tilapia)
154 (common carp)
Monitored surface water concentration (8.2E-03 mg/L)
(NWOMC. 2021)
351 (tilapia)
458 (common carp)
HE = high-end; MOE = margin of exposure; UF = uncertainty factor
Note: The acute and chronic MOEs are identical because the exposure estimates and the POD do not change between
acute and chronic.
E.3 Tribal Populations
Acute and chronic non-cancer risk estimates were below the benchmark using the water solubility limit
as the surface water concentration (Table Apx E-2). EPA then refined its analysis by using the three
OESs that reported releases and resulted in the highest modeled surface water concentrations. The
Agency also included the highest monitored surface water concentrations from the WQP (NWQMC.
2021) (Section 4.2.1). The highest modeled surface water concentration based on the PVC plastics
compounding OES resulted in some non-cancer risk estimates to be below the benchmark. Risk
estimates for other OESs are two to three orders of magnitude above the benchmark. Non-cancer risk
estimates are below the benchmark for the PVC plastics compounding OES. These results indicate that
fish ingestion can be a pathway of concern for DBP for Tribal populations.
Table Apx E-3. Risk Estimates for Fish Ingestion Exposure for Tribal Populations
Acute and Chronic Non-Cancer MOE
UFs = 30
Current IR, Mean
Current IR, 95th
Percentile
Heritage IR
Water solubility limit (11.2 mg/L)
0.2 (tilapia)
0.2 (common carp)
0.0 (tilapia)
0.1 (common carp)
0.0 (tilapia)
0.0 (common carp)
Manufacturing OES, P75, HE (generic
scenario) (2.24E-02 mg/L)
78 (tilapia)
102 (common carp)
19 (tilapia)
25 (common carp)
10 (tilapia)
13 (common carp)
Manufacturing OES, P90, HE (generic
scenario) (1.7E-03 mg/L)
1,116 (tilapia)
1,457 (common carp)
276 (tilapia)
361 (common carp)
146 (tilapia)
191 (common carp)
Waste Handling, Treatment, Disposal-POTW
(TRI reported release) (1.45E-02 mg/L)
231 (tilapia)
171 (common carp)
57 (tilapia)
42 (common carp)
30 (tilapia)
22 (common carp)
Monitored surface water concentration (8.2E-
03 ms/L) (NWOMC. 2021)
231 (tilapia)
302 (common carp)
57 (tilapia)
75 (common carp)
30 (tilapia)
40 (common carp)
CT = central tendency; HE = high end; IR = ingestion rate; OES = occupational exposure scenario
Note: The acute and chronic MOEs are identical because the exposure estimates and the point of departure (POD) do
not change between acute and chronic.
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Appendix F AMBIENT AIR MONITORING STUDY SUMMARY
China Study (Zhu et al.. 2016)
Chinese study saying cancer risks 3.51 xl0~8 to 9.75xlO~u well below 1x10-6.
Phthalates
CO
E
c
0
1
"E
8
CN
o
+¦
£
o
+
Ji
o
~
+
Qj
in
0
1
Qj
iO
Although the phthalates DEHP, DEHA, and DIBP are typically considered indoor contaminants from
plastics and consumer goods, the concentration difference between outdoor air in urban/industrial and
rural communities suggests some industrial or transportation sources as well.
New York City Study (Bove et al.. 1978)
Airborne di-Butyl and di-(2-Ethylhexyl)-phthalate at three New York City Air Sampling Stations
Di-butyl phthalate concentrations in New York City air were 3.73, 5.69, and 3.28 ng/m3, while di(2-
ethylhexyl)-phthalate concentrations were 10.20, 16.79, and 14.20 ng/m3.
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Appendix G URINARY BIOMONITORING METHODS AND
RESULTS
EPA analyzed urinary biomonitoring data from the CDC's NHANES, which reports urinary
concentrations for 15 phthalate metabolites specific to individual phthalate diesters. Two metabolites of
DBP, mono-n-butyl phthalate (MnBP) and mono-3-hydroxybutyl phthalate (MHBP), have been reported
in the NHANES data.
MnBP has been reported in NHANES beginning with the 1999 cycle and measured in 26,740 members
of the general public, including 7,331 children under 16 year and 19,409 adults aged 16 years and older.
Although MHBP was measured in the 2013 to 2018 NHANES cycles, the data for the 2013 to 2014
NHANES cycle was determined to be inaccurate due to procedural error and only released as surplus
data, which is not readily publicly available (https://wwwn.cdc.gov/Nchs/Nhanes/2013-
2014/SSPHTE H htm). As a result, the present analysis only includes urinary MHBP data from the
2015 to 2018 NHANES cycles. The present analysis of MHBP includes data from the 2015 to 2018
NHANES cycles and has been measured in 5,737 participants, including 1,961 children under 16 years
and 3,776 adults aged 16 years and older.
Urinary MnBP and MHBP concentrations were quantified using high performance liquid
chromatography-electrospray ionization-tandem mass spectrometry. Limits of detection (LOD) for each
cycle on NHANES are provided in TableApx G-l. Values below the LOD were replaced by the lower
LOD divided by the square root of two (NCHS. 2021).
Table Apx G-l. Limit of Detection of Urinary
DBP Metabolites by NHANES Cycle
NHANES Cycle
MnBP
MHBP
1999-2000
0.94
-
2001-2002
0.94
-
2003-2004
0.4
-
2005-2006
0.6
-
2007-2008
0.6
-
2009-2010
0.4
-
2011-2012
0.2
-
2013-2014
0.4
-
2015-2016
0.4
0.4
2017-2018
0.4
0.4
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of Urinary DBP Metabolite Concentrations (ng/mL) from all NHANES Cycles Between 1999-2018
NHANES
Cycle
Metabolite
Age
Group
Subset
Sample
Size
Detection
Frequency
50th Percentile
(95% CI) (ng/mL)
95th Percentile (95%
CI) (ng/mL)
Creatinine
Corrected 50th
Percentile (95%
CI) (ng/mL)
Creatinine Corrected
95th Percentile (95%
CI) (ng/mL)
2017-2018
MHBP
Adults
All adults
1,896
1,896 (70.94%)
0.7 (0.6-0.7)
3.2 (2.7-3.9)
0.8 (0.73-0.9)
3.87 (3.28^1.4)
2017-2018
MHBP
Adults
At or above poverty level
467
467 (75.16%)
0.5 (0.5-0.7)
2.8(2.4^.1)
0.78 (0.7-0.85)
3.5 (2.74^1)
2017-2018
MHBP
Adults
Below poverty level
337
337 (72.7%)
0.8(0.28-1.3)
4.9(2.7-11.8)
1.04 (0.9-1.23)
5.16 (4.22-6.83)
2017-2018
MHBP
Adults
Black non-Hispanic
438
438 (75.34%)
0.9(0.7-1.4)
4.6 (2.6-6.6)
0.71 (0.6-0.84)
3.84 (2.79-5.71)
2017-2018
MHBP
Adults
Females
952
952 (69.01%)
0.9(0.6-1.1)
4.4 (3.3-7)
1.13 (0.98-1.33)
4.51 (3.73-5.26)
2017-2018
MHBP
Adults
Males
944
944 (72.88%)
0.7 (0.6-0.7)
3.1 (2.7-4.1)
0.67 (0.62-0.74)
3.33 (2.76^1)
2017-2018
MHBP
Adults
Mexican American
278
278 (66.55%)
0.4 (0.28-0.7)
2.7(1.6^.9)
0.85 (0.65-0.96)
3.51 (2.86^1.05)
2017-2018
MHBP
Adults
Other
532
532 (67.48%)
0.5 (0.28-0.8)
3.1 (1.9—4.1)
0.9(0.74-1.05)
4.67 (3.82-6.09)
2017-2018
MHBP
Adults
Unknown income
840
840 (67.14%)
0.6(0.4-1)
3.3 (1.4-4.4)
0.79 (0.63-0.99)
4.71 (3.08-6.78)
2017-2018
MHBP
Adults
White non-Hispanic
648
648 (72.69%)
0.5 (0.4-0.7)
3.2 (2.1-4.3)
0.79 (0.7-0.92)
3.75 (2.92^1.4)
2017-2018
MHBP
Children
Adolescents (11 to <16
years)
213
213(81.69%)
4.2 (3.3-5.9)
32 (24^15.5)
0.98 (0.78-1.16)
2.45 (2.13-3.47)
2017-2018
MHBP
Children
Adolescents (11 to <16
years)
213
213(81.69%)
4.2 (3.3-5.9)
32 (24^15.5)
0.98 (0.78-1.16)
2.78 (2.13-3.63)
2017-2018
MHBP
Children
All children
866
866 (84.18%)
1.3(1.1-1.4)
4.9 (4.4-5.8)
1.15 (0.93-1.49)
4.4 (3.47-5.37)
2017-2018
MHBP
Children
At or above poverty level
231
231 (88.31%)
1.3(1.1-1.4)
4.7(3.7-5.8)
1.11 (0.79-1.55)
3.89 (2.94^1.88)
2017-2018
MHBP
Children
Below poverty level
234
234 (85.9%)
1.4(1.2-2)
5.9 (4.8-7)
1.45 (1.16-1.62)
5.23 (3.79-7.02)
2017-2018
MHBP
Children
Black non-Hispanic
207
207 (87.44%)
1.5(1-2.1)
5.2 (3.7-7.7)
1.06 (0.84-1.18)
3.99 (2.59-7.02)
2017-2018
MHBP
Children
Children (6 to <11 years)
274
274 (89.05%)
5.8 (4.2-9)
38.4 (29.7-103.7)
1.83 (1.44-2.18)
4.91 (4.5-5.56)
2017-2018
MHBP
Children
Children (6 to <11 years)
274
274 (89.05%)
5.8 (4.2-9)
38.4 (29.7-103.7)
1.83 (1.44-2.18)
5.71 (4.4-7.78)
2017-2018
MHBP
Children
Females
447
447 (82.77%)
1.2 (0.7-1.5)
4.9 (4-6.2)
1.33 (0.98-1.89)
4.41 (3.73-6.21)
2017-2018
MHBP
Children
Males
419
419(85.68%)
1.2(1-1.3)
4.9(3.9-6.6)
0.97 (0.82-1.22)
4.4 (2.87-6.67)
2017-2018
MHBP
Children
Mexican American
139
139(80.58%)
1 (0.5-1.3)
3.3 (2.5-5.9)
1.04 (0.91-1.22)
3.3(2.18-6.78)
2017-2018
MHBP
Children
Other
262
262 (83.97%)
1.2 (0.9-1.7)
6.3 (4.9-23.3)
1.45 (1-1.85)
6.51 (3.61-138)
2017-2018
MHBP
Children
Toddlers (3 to <6 years)
379
379 (82.06%)
5.7(4.4-8.1)
25 (13.7-34.9)
0.71 (0.38-0.79)
1.51 (1.09-2.35)
2017-2018
MHBP
Children
Toddlers (3 to <6 years)
379
379 (82.06%)
5.7(4.4-8.1)
25 (13.7-34.9)
0.71 (0.38-0.79)
1.86 (1.42-2.65)
2017-2018
MHBP
Children
Unknown income
316
316(80.7%)
1.1 (0.5-1.4)
5.9 (2.4-23.3)
1.05 (0.82-1.35)
7.78 (1.84-18.49)
2017-2018
MHBP
Children
White non-Hispanic
258
258 (83.72%)
1.2(1.1-1.5)
4 (2.9-5.2)
1.15 (0.78-1.78)
3.83 (2.87-5.37)
2017-2018
MnBP
Adults
All adults
1,896
1,896 (99.26%)
9.4 (7.7-10.6)
35 (30.5-42.1)
8.63 (7.92-9.26)
34.4 (29.74-38.02)
2017-2018
MnBP
Adults
At or above poverty level
467
467(99.14%)
9(6.7-11)
34.2 (26.6-42.1)
8.5 (7.5-9.36)
30.63 (26.76-34.4)
2017-2018
MnBP
Adults
Below poverty level
337
337(99.41%)
9.8(5.6-13.4)
54.9(31.2-84.3)
10.75 (9.41-12.73)
44.48 (39.52-56.27)
2017-2018
MnBP
Adults
Black non-Hispanic
438
438 (99.54%)
14.2(10.9-18.4)
56.6 (34.8-71.5)
8.83 (8.15-9.52)
41 (30.96-57.26)
Page 105 of 113
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PUBLIC RELEASE DRAFT
May 2025
NHANES
Cycle
Metabolite
Age
Group
Subset
Sample
Size
Detection
Frequency
50th Percentile
(95% CI) (ng/mL)
95th Percentile (95%
CI) (ng/mL)
Creatinine
Corrected 50th
Percentile (95%
CI) (ng/mL)
Creatinine Corrected
95th Percentile (95%
CI) (ng/mL)
2017-2018
MnBP
Adults
Females
952
952 (99.16%)
11.5 (8.2-14)
43.4 (33-54.6)
11.67(10-12.69)
38 (33.18^12.05)
2017-2018
MnBP
Adults
Males
944
944 (99.36%)
9 (7.5-10.6)
35 (30.2^13.6)
7.41 (6.69-8.11)
29 (26.5-34.17)
2017-2018
MnBP
Adults
Mexican American
278
278 (100%)
8.3(5.6-11.7)
31 (18.7-36.3)
9.2 (7.44-10.66)
30 (26.25-38.89)
2017-2018
MnBP
Adults
Other
532
532 (98.87%)
7.8(5.8-10.7)
35.8(30.7-51.7)
9.64 (8.09-11.23)
46.5 (37.77-67.67)
2017-2018
MnBP
Adults
Unknown income
840
840 (99.4%)
9.2 (6-11)
36.2 (22.8-69.4)
7.93 (6.84-11.09)
39.38 (29.43-83.68)
2017-2018
MnBP
Adults
White non-Hispanic
648
648 (99.07%)
8.2 (6.1-10.9)
32.9 (24.3^17.4)
8.32 (7.47-9.02)
32.27 (28.08-36.5)
2015-2016
MHBP
Adults
All adults
1,880
1,880 (72.71%)
0.7(0.5-0.8)
3.8(2.8^1.8)
0.89 (0.8-0.97)
4.11 (3.64^1.67)
2015-2016
MHBP
Adults
At or above poverty level
461
461 (74.4%)
0.7(0.5-0.8)
3.7(2.6^1)
0.87 (0.8-0.93)
3.6(3.06^1)
2015-2016
MHBP
Adults
Below poverty level
399
399 (76.94%)
0.9(0.7-1.2)
4.6 (2-11.9)
1.08 (0.97-1.26)
5.97(4.86-6.93)
2015-2016
MHBP
Adults
Black non-Hispanic
427
427 (74.24%)
1 (0.8-1.2)
3.6 (2-5.3)
0.72 (0.67-0.85)
5.26(4.15-6.8)
2015-2016
MHBP
Adults
Females
984
984 (74.59%)
0.8(0.7-1.1)
4.7(3.5-6.6)
1.27(1.1-1.38)
4.77 (4.29-5.26)
2015-2016
MHBP
Adults
Males
896
896 (70.65%)
0.6 (0.5-0.8)
3.8(2.7^1.9)
0.73 (0.65-0.8)
3.37(2.89-3.85)
2015-2016
MHBP
Adults
Mexican American
342
342 (70.76%)
0.6 (0.28-0.7)
3.7(2.3-6.8)
1.03 (0.93-1.08)
5 (4-6.15)
2015-2016
MHBP
Adults
Other
540
540 (72.59%)
0.6 (0.5-0.8)
3.3 (2.6^.8)
0.8 (0.73-0.96)
4.19(3.5^1.73)
2015-2016
MHBP
Adults
Unknown income
833
833 (68.91%)
0.7(0.28-1.6)
5.3(1.2-7.5)
0.88 (0.69-1.14)
5.19(3.23-6.14)
2015-2016
MHBP
Adults
White non-Hispanic
571
571 (72.85%)
0.7(0.5-0.8)
3.9(2.9-5.9)
0.9(0.8-1)
3.75 (3.09^1.34)
2015-2016
MHBP
Children
Adolescents (11 to <16
years)
284
284 (85.21%)
7.3(5.4-10.3)
61.8(38.7-80.6)
1.1 (0.79-1.4)
3.38 (2.88-3.84)
2015-2016
MHBP
Children
Adolescents (11 to <16
years)
284
284 (85.21%)
7.3(5.4-10.3)
61.8(38.7-80.6)
1.1 (0.79-1.4)
3.81 (3.04^1)
2015-2016
MHBP
Children
All children
1,095
1,095 (87.67%)
1.2(1.1-1.4)
5.5(4.7-6.1)
1.36(1.24-1.54)
5 (4.29-6.09)
2015-2016
MHBP
Children
At or above poverty level
282
282 (89.01%)
1.2(1.1-1.4)
5.4 (3.6-7.2)
1.33 (1.16-1.46)
4.41 (3.81-5.65)
2015-2016
MHBP
Children
Below poverty level
329
329 (85.71%)
1.4(1.2-1.8)
8.3 (4-12.5)
1.44(1.24-1.72)
8.33 (4.76-11.24)
2015-2016
MHBP
Children
Black non-Hispanic
271
271 (86.72%)
1.3(1-1.9)
5.9(4.6-11.8)
1.2 (0.88-1.53)
9.09 (4.76-11.24)
2015-2016
MHBP
Children
Children (6 to <11 years)
346
346 (90.75%)
10.4 (8.1-13.3)
81.3 (64.8-173.9)
2(1.67-2.35)
4.93 (4.4-6)
2015-2016
MHBP
Children
Children (6 to <11 years)
346
346 (90.75%)
10.4 (8.1-13.3)
81.3 (64.8-173.9)
2(1.67-2.35)
8.18 (6.07-10.98)
2015-2016
MHBP
Children
Females
517
517(87.81%)
1.2(1-1.4)
5.6 (5-7.1)
1.43 (1.29-1.61)
6.06 (4.67-8.18)
2015-2016
MHBP
Children
Males
578
578 (87.54%)
1.3(1.1-1.5)
5.7(3.7-7.7)
1.29(1.03-1.58)
4.41 (3.81-5.65)
2015-2016
MHBP
Children
Mexican American
253
253 (85.77%)
1.2(1-1.5)
5.3(4.2-11.3)
1.34(1.14-1.61)
5.65 (4.23-8.33)
2015-2016
MHBP
Children
Other
280
280 (88.57%)
1.2(1-1.6)
4.7(3.6-5.4)
1.34(1.04-1.72)
4.35 (3.26-5.25)
2015-2016
MHBP
Children
Toddlers (3 to <6 years)
465
465 (86.88%)
6.8(4.2-13.8)
55.3 (20.8-77.8)
0.49 (0.35-0.69)
1.53 (1.27-2.43)
2015-2016
MHBP
Children
Toddlers (3 to <6 years)
465
465 (86.88%)
6.8(4.2-13.8)
55.3 (20.8-77.8)
0.49 (0.35-0.69)
2.06 (0.98-5.65)
2015-2016
MHBP
Children
Unknown income
388
388 (87.89%)
1.6(0.8-2.4)
4.6 (2.3-19.8)
1.82(1.11-2.12)
4.71 (3.5-15.59)
Page 106 of 113
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PUBLIC RELEASE DRAFT
May 2025
NHANES
Cycle
Metabolite
Age
Group
Subset
Sample
Size
Detection
Frequency
50th Percentile
(95% CI) (ng/mL)
95th Percentile (95%
CI) (ng/mL)
Creatinine
Corrected 50th
Percentile (95%
CI) (ng/mL)
Creatinine Corrected
95th Percentile (95%
CI) (ng/mL)
2015-2016
MHBP
Children
White non-Hispanic
291
291 (89.35%)
1.3(1-1.8)
5.6 (4.2-7.7)
1.39(1.23-1.67)
4.62 (4-6.22)
2015-2016
MnBP
Adults
All adults
1,880
1,880 (99.04%)
9.5(7.9-10.9)
44.9 (32.7-53.8)
9.94 (8.95-10.63)
36.02 (34.44-38.2)
2015-2016
MnBP
Adults
At or above poverty level
461
461 (99.57%)
9.2 (7.6-10.3)
39 (32.5^14.9)
9.24 (8.64-10.11)
32.89 (28.94-36.06)
2015-2016
MnBP
Adults
Below poverty level
399
399 (99%)
12.4 (9.1-15.8)
55.4(24.8-157.6)
12.5 (10.97-14.39)
56.3 (41.41-76.07)
2015-2016
MnBP
Adults
Black non-Hispanic
427
427 (99.06%)
13.5 (9.6-19.2)
46.6(27.4-114.6)
10.4 (9.38-11.3)
47.37 (40.2-74.42)
2015-2016
MnBP
Adults
Females
984
984 (98.88%)
10.5 (9.1-12)
44.5 (37.9-65.1)
13.52(11.88-15.23)
43.85 (37.64^16.84)
2015-2016
MnBP
Adults
Males
896
896 (99.22%)
9.6(7.7-10.9)
44.9(31.6-55.1)
8.4 (7.89-8.93)
31.14(26.62-34.95)
2015-2016
MnBP
Adults
Mexican American
342
342 (98.54%)
9.6(6.7-11.6)
55.1 (35.3-111.7)
10.82(10.05-12.15)
48.61 (36.92-67.65)
2015-2016
MnBP
Adults
Other
540
540 (99.26%)
11.7 (7.5-15.7)
37.5 (29.9^15.1)
10.13 (9.32-10.97)
37.04 (33.52^15.23)
2015-2016
MnBP
Adults
Unknown income
833
833 (98.68%)
11.7 (6.2-20.4)
55.6(14.1-68)
11.6 (8.6-14.92)
46.55 (28.92-72.21)
2015-2016
MnBP
Adults
White non-Hispanic
571
571 (99.12%)
8.4 (6.8-10)
44.9 (22.8-55.6)
9.24 (8.57-10.6)
34.52 (29.71-36.25)
2013-2014
MnBP
Adults
All adults
2,040
2,040 (98.28%)
10.2 (9.4-11.3)
44.6 (37-50.5)
8.93 (8.25-9.54)
34.63 (29.89^12.93)
2013-2014
MnBP
Adults
At or above poverty level
484
484 (98.14%)
9.6(8.5-11.4)
40 (32-50.5)
8.77 (8.09-9.37)
33.86 (28.33^15.24)
2013-2014
MnBP
Adults
Below poverty level
454
454 (98.9%)
11.8(9.1-17.3)
49.5 (38.9-72.6)
10.65 (9.53-12.1)
42.22 (29.94-52.86)
2013-2014
MnBP
Adults
Black non-Hispanic
442
442 (98.64%)
12.3 (10.2-16.8)
66.7(44.7-74.1)
8.9 (8-9.78)
32.89 (28.36-38.72)
2013-2014
MnBP
Adults
Females
1,076
1,076 (97.86%)
10.9(9.1-12.6)
53.2 (42.6-75)
11.18(10.27-12.26)
46 (34.37-64.21)
2013-2014
MnBP
Adults
Males
964
964 (98.76%)
10.1 (9.3-11.4)
42.6 (33.6-50.5)
7.67 (6.97-8.38)
28.76 (22.69-35.76)
2013-2014
MnBP
Adults
Mexican American
282
282 (98.23%)
8.6(5.8-11.8)
53.5 (20.7-78.7)
9.71 (7.85-11.34)
36.71 (27.96^15.78)
2013-2014
MnBP
Adults
Other
496
496 (98.99%)
10.6 (9-14)
49.7(37-77.8)
10(9.21-11.16)
38.04 (31.25^5.24)
2013-2014
MnBP
Adults
Unknown income
921
921 (97.94%)
9.2 (5.6-15.3)
29.3 (26.6-74.2)
7.69 (6.48-9.75)
26.95 (19.52-36.32)
2013-2014
MnBP
Adults
White non-Hispanic
820
820 (97.68%)
9.6(8.7-11.5)
32 (26-50.2)
8.68 (7.67-9.54)
33.1 (24.03-55.5)
2011-2012
MnBP
Adults
All adults
1,894
1,894 (93.66%)
9.2 (8.2-10.6)
46.9(37.3-61.3)
8.93 (8.13-9.8)
42.27 (32.22-54.75)
2011-2012
MnBP
Adults
At or above poverty level
449
449 (93.32%)
9.2 (8-11.1)
46.3 (35.3-61.3)
8.73 (7.96-9.51)
38.89 (29.71-51.79)
2011-2012
MnBP
Adults
Below poverty level
441
441 (95.01%)
10(6.3-15.8)
58.6(43.1-99.7)
9.67 (8.29-11.28)
50.88 (36.74-66.42)
2011-2012
MnBP
Adults
Black non-Hispanic
499
499 (95.79%)
14.1 (10.7-17.3)
63.3 (47.5-96.2)
11 (9.55-11.92)
43.5 (34.42-55.77)
2011-2012
MnBP
Adults
Females
933
933 (93.46%)
9.4 (7-11.8)
58.5 (41.7-129.3)
11.31 (9.77-13.33)
47.44 (42.09-54.75)
2011-2012
MnBP
Adults
Males
961
961 (93.86%)
9.2 (8.2-10.7)
46.7(36.4-61.3)
8.06 (7.54-8.85)
34.58(24.13-55.19)
2011-2012
MnBP
Adults
Mexican American
186
186 (96.24%)
8.8(6.8-12.5)
35.8(23.5^16.4)
10.24 (8.62-12.21)
41.18(32.47-55.6)
2011-2012
MnBP
Adults
Other
545
545 (92.48%)
9.5(8.2-11.6)
52.2 (38.5-68.5)
10.88 (9.8-11.69)
50 (46.16-73.28)
2011-2012
MnBP
Adults
Unknown income
821
821 (92.94%)
10(5.7-13.3)
37(17.1-64.3)
9.86 (6.43-12.72)
54.64 (22.86-2863.14)
2011-2012
MnBP
Adults
White non-Hispanic
664
664 (92.32%)
8.6(7.9-10.1)
44.3 (26.7-76.3)
8.03 (7.43-9.02)
34.62 (27.94-54.75)
2009-2010
MnBP
Adults
All adults
2,127
2,127(99.44%)
14.59(12.94-16.33)
70.32 (61.73-82.47)
13.82(13.04-14.87)
56.11 (49.62-65.82)
2009-2010
MnBP
Adults
At or above poverty level
550
550 (99.45%)
13.91 (12.25-16.11)
65.27 (54.59-70.34)
13.42(12.6-14.33)
49.83 (45.17-55.02)
Page 107 of 113
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PUBLIC RELEASE DRAFT
May 2025
NHANES
Cycle
Metabolite
Age
Group
Subset
Sample
Size
Detection
Frequency
50th Percentile
(95% CI) (ng/mL)
95th Percentile (95%
CI) (ng/mL)
Creatinine
Corrected 50th
Percentile (95%
CI) (ng/mL)
Creatinine Corrected
95th Percentile (95%
CI) (ng/mL)
2009-2010
MnBP
Adults
Below poverty level
469
469 (99.36%)
15.04(12.11-16.48)
133.91 (71.74-161.63)
16.09(13.55-18.89)
79.91 (63.41-107.08)
2009-2010
MnBP
Adults
Black non-Hispanic
400
400 (99.75%)
19.61 (16.86-27.12)
105.11 (65.27-193.05)
14.81 (12.97-18.14)
52.32 (43.98-73.54)
2009-2010
MnBP
Adults
Females
1,040
1,040 (99.33%)
19.38(14.12-22.7)
83.85 (60.63-123.12)
17.69(15.34-18.89)
70.96 (53.78-89.24)
2009-2010
MnBP
Adults
Males
1087
1087 (99.54%)
14.29(12.65-16.33)
70.34 (61.41-82.63)
12.81 (11.76-13.57)
45.2 (39.66-53.78)
2009-2010
MnBP
Adults
Mexican American
393
393 (99.49%)
15.77(11.4-21.88)
55.77(43.56-82.63)
14.13 (13.28-15.57)
87.68 (59.71-99.03)
2009-2010
MnBP
Adults
Other
336
336 (99.7%)
13.5 (11.63-17.39)
160.59 (52.99^118.4)
15.08(11.96-20.14)
81.52 (48.38-362.56)
2009-2010
MnBP
Adults
Unknown income
905
905 (99.34%)
17.045 (12.67-31.19)
322.68 (40.3-322.68)
17.21 (13.39-20.04)
70.96 (28.63-1933.78)
2009-2010
MnBP
Adults
White non-Hispanic
998
998 (99.2%)
13.46(10.85-16.85)
69.53 (54.75-81.95)
13.46(12.79-14.45)
50.85 (44.79-57.8)
2007-2008
MnBP
Adults
All adults
2,021
2,021 (99.16%)
18.8(16-20.9)
80.8 (63.8-99.4)
17.47(15.94-19.16)
77.12(61.63-90)
2007-2008
MnBP
Adults
At or above poverty level
505
505 (99.41%)
19.1 (16-22.5)
79.5 (55.6-95.7)
16.82(15.24-18.68)
72.26 (59.5-84.47)
2007-2008
MnBP
Adults
Below poverty level
392
392 (99.23%)
19.3 (15.4-24.1)
110.2 (63.8-156.9)
22.41 (18.75-26.15)
102.06 (77.12-159.63)
2007-2008
MnBP
Adults
Black non-Hispanic
434
434 (99.54%)
21.4(17.8-26.8)
110.2 (57.4-338.3)
17.31 (14.79-20)
78.11 (51.6-125.23)
2007-2008
MnBP
Adults
Females
1,030
1,030 (99.03%)
23 (18.9-28.9)
114.2 (83.7-161.7)
24.54(21.12-27.52)
100.64 (80-144.88)
2007-2008
MnBP
Adults
Males
991
991 (99.29%)
18.9(15.9-21.3)
79.1 (61.6-99.4)
14.69(13.33-16.27)
55.2 (45.93-65.22)
2007-2008
MnBP
Adults
Mexican American
371
371 (99.73%)
19.6(14.7-27.6)
92.2 (61.8-141.1)
19.8(15.19-25.48)
100.32 (59.5-193.03)
2007-2008
MnBP
Adults
Other
294
294 (99.66%)
19.2(12.6-31.7)
61.2 (50-168.5)
19.03 (14.21-24.44)
89.5 (55.04-103.41)
2007-2008
MnBP
Adults
Unknown income
948
948 (98.84%)
14.8(11^10.8)
63.4 (33.3-84.1)
16.79 (14.67-26.25)
73.33 (51.87-158.45)
2007-2008
MnBP
Adults
White non-Hispanic
922
922 (98.59%)
18.8(15-21.5)
73.5 (53.4-94.5)
16.8(15.41-18.77)
71.83 (57.43-84.17)
2005-2006
MnBP
Adults
All adults
1,831
1,831 (99.67%)
21.2(19-24)
86 (66.2-118.1)
18.07(16.41-19.71)
73.38 (62.58-94.78)
2005-2006
MnBP
Adults
At or above poverty level
436
436 (99.08%)
20.9 (18.4-24)
78.9(63.8-104.9)
17.73 (15.91-19.62)
66.69 (53.73-84.64)
2005-2006
MnBP
Adults
Below poverty level
340
340 (99.71%)
25.4 (18-35.3)
124.4(101.2-222.8)
20.48(18.25-23.09)
99.24 (76.72-115.98)
2005-2006
MnBP
Adults
Black non-Hispanic
464
464 (100%)
24.9(21.6-27.2)
111.7(84.3-139)
17.3 (15.07-19.76)
70.56 (51.28-100.56)
2005-2006
MnBP
Adults
Females
935
935 (99.57%)
22.8 (19.7-26.6)
113.2 (97.1-132.6)
25.38(20.53-30.36)
111.55 (78.54-139.17)
2005-2006
MnBP
Adults
Males
896
896 (99.78%)
20.7(18.5-23.9)
86 (63.8-118.7)
15.42(14.22-16.41)
51.02 (46.1-65.61)
2005-2006
MnBP
Adults
Mexican American
390
390 (99.49%)
22.6 (15.8-27.6)
105.8(74.3-127.5)
18.07(15.13-21.23)
99.46 (69.86-161.41)
2005-2006
MnBP
Adults
Other
131
131 (100%)
28 (22-54.2)
176.2 (51.9-1063.6)
21.89(15.63-29.61)
73.38 (47.75-178.24)
2005-2006
MnBP
Adults
Unknown income
955
955 (99.9%)
18.8(8.6-38.7)
98.8(38.7-170.5)
19.35 (13.48-29.16)
108.6 (50.5-177.4)
2005-2006
MnBP
Adults
White non-Hispanic
846
846 (99.53%)
18.8(17.6-20.7)
72.6 (55.4-112.8)
17.9(16.22-19.53)
67.35 (56.44-95.7)
2003-2004
MnBP
Adults
All adults
1,889
1,889 (99.42%)
20.7 (16.9-24.3)
80.7(64.2-109.1)
17.84(16.25-19.62)
83.64 (68.28-110)
2003-2004
MnBP
Adults
At or above poverty level
474
474 (99.58%)
19.6(16-24)
70.2 (60.6-97.9)
17(15.53-18.47)
78.1 (62.31-100.95)
2003-2004
MnBP
Adults
Below poverty level
393
393 (99.24%)
23.9(17.9-31.4)
105.9(67.5-172.1)
22.5 (20.35-24.2)
129.78 (98.84-141.7)
2003-2004
MnBP
Adults
Black non-Hispanic
423
423 (99.76%)
30.3 (26.5-32.6)
118.9(88.9-135)
20.93 (18.47-24.37)
87.43 (70.11-100.27)
2003-2004
MnBP
Adults
Females
980
980 (99.69%)
25.2 (22.7-31)
127.4(101.7-163.7)
25.27(22.44-29.69)
121.21 (83.64-143.14)
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PUBLIC RELEASE DRAFT
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NHANES
Cycle
Metabolite
Age
Group
Subset
Sample
Size
Detection
Frequency
50th Percentile
(95% CI) (ng/mL)
95th Percentile (95%
CI) (ng/mL)
Creatinine
Corrected 50th
Percentile (95%
CI) (ng/mL)
Creatinine Corrected
95th Percentile (95%
CI) (ng/mL)
2003-2004
MnBP
Adults
Males
909
909 (99.12%)
20.6 (16.6-24.3)
75.8 (62.9-104.2)
14.84(13.61-16.03)
59.43 (50.31-81.5)
2003-2004
MnBP
Adults
Mexican American
423
423 (99.29%)
21.1 (16.6-32.7)
73 (60.9-107.7)
20.13 (16.63-24.61)
109.13 (80.75-149.83)
2003-2004
MnBP
Adults
Other
142
142 (100%)
23 (13.4-38.1)
172.1 (36-3191.3)
20.39 (16.67-27.36)
123.33 (83.8^15.06)
2003-2004
MnBP
Adults
Unknown income
904
904 (99.34%)
26.8 (15.7-52.7)
99.1 (34.5-124.1)
22.15 (13.19-29.14)
86.81 (41.96-155)
2003-2004
MnBP
Adults
White non-Hispanic
901
901 (99.22%)
18.8(14.5-22.8)
66.7 (52.7-94)
16.82(15.27-18.63)
73.35 (58.09-99.23)
2001-2002
MnBP
Adults
All adults
2,004
2,004 (98.1%)
19.3 (16.3-21.5)
91.7(64.7-117.4)
16.46(15.29-17.53)
84.3 (72.35-103.08)
2001-2002
MnBP
Adults
At or above poverty level
463
463 (96.98%)
18.6(15.2-21.2)
79.6 (57.1-103.4)
15.71 (14.56-16.62)
76.21 (62.32-91.88)
2001-2002
MnBP
Adults
Below poverty level
361
361 (98.89%)
23.1 (16.1-29.4)
101.2 (59.1-143.1)
20.3 (17.58-24.02)
130.51 (72.31-220)
2001-2002
MnBP
Adults
Black non-Hispanic
414
414 (99.52%)
26.7(20.8-31.3)
93.9(67.3-143.6)
19.02(14.92-23)
84.3 (67.38-103.57)
2001-2002
MnBP
Adults
Females
1,019
1,019(98.14%)
22.4 (18.6-29.2)
105.5 (86.8-122)
23.62(21.18-26.6)
110.63 (90.71-138.18)
2001-2002
MnBP
Adults
Males
985
985 (98.07%)
19.3 (15.8-21.4)
87.5 (60.5-117.4)
13.68(12.92-14.86)
60 (50.32-78.39)
2001-2002
MnBP
Adults
Mexican American
445
445 (98.43%)
18.4(15.1-23.1)
88(47.8-313.5)
18.2(15.88-19.92)
84.47 (62.02-128.76)
2001-2002
MnBP
Adults
Other
162
162 (96.91%)
19.8(14.7-24.6)
83.7(47.8-111.9)
16.07(12.61-19.43)
59.02 (48.83-74.17)
2001-2002
MnBP
Adults
Unknown income
1,052
1,052 (98.29%)
21.8(14.5^1.2)
180.3 (40.6-322.1)
15.59(9.55-23.78)
103.57(50.32-135.85)
2001-2002
MnBP
Adults
White non-Hispanic
983
983 (97.56%)
18.2(14.3-21.2)
92.7(55.8-129.6)
15.88(14.38-17.31)
91.03 (70-115.26)
1999-2000
MnBP
Adults
All adults
1,827
1,827(98.69%)
23.1 (20.9-24.7)
111.1 (92.3-125.6)
20.81 (18.93-23.19)
93.17(75.98-114.08)
1999-2000
MnBP
Adults
At or above poverty level
412
412 (99.27%)
22.8 (20.6-25.3)
98.6 (85.2-114.1)
19.82(17.34-22.59)
93.02 (67.12-116.99)
1999-2000
MnBP
Adults
Below poverty level
377
377 (99.2%)
23.4 (14.5-33.5)
162.7(60.6-224.6)
25.15 (20.13-30.67)
105.44 (74.57-139.12)
1999-2000
MnBP
Adults
Black non-Hispanic
363
363 (99.17%)
30.9 (24-38.9)
114.1 (85.4-143.4)
24.9(19.69-29.39)
93.15 (73.11-113.04)
1999-2000
MnBP
Adults
Females
964
964 (98.65%)
32.6 (27.6-41.2)
155.9(98.9^12.1)
30.48 (27.74-34.29)
134.09 (99.53-196.13)
1999-2000
MnBP
Adults
Males
863
863 (98.73%)
22.7(20.5-24.1)
108 (91.1-120.8)
16.97(15.53-18.74)
64.7 (57.33-71.51)
1999-2000
MnBP
Adults
Mexican American
550
550 (98.91%)
23.5 (18.4-24.9)
104.8(63.8-117)
19.26(17.86-21.69)
94.15 (73.87-117.78)
1999-2000
MnBP
Adults
Other
176
176 (99.43%)
29.3 (19.6-33.5)
162.7(82.3-224.6)
24.44(18.93-30.46)
107.55 (71.51-196.13)
1999-2000
MnBP
Adults
Unknown income
798
798 (97.99%)
19.2 (8-33.4)
93.3 (50.6-140.4)
22.04(18.08-30.09)
83.15 (62.62-130.62)
1999-2000
MnBP
Adults
White non-Hispanic
738
738(98.1%)
20.7 (16.7-23.2)
96.2 (78.8-119.8)
20.11 (17.61-23.16)
92.27 (63.62-136.9)
2977
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2978 Table Apx G-3. Regression Coefficients and P-values for Statistical Analyses of DBP Metabolite Concentrations
Years
Metabolite
Group
Subset
Regression
Variable
Covariates
Regression
Coefficient, 50th
Percentile
P-value, 50th
Percentile
Regression
Coefficient, 95th
Percentile
P-value, 95th
Percentile
2015-2018
MHBP
Adults
All adults
Age
Sex race income
-
<0.001
-
<0.001
2015-2018
MHBP
Adults
All adults
Income
Age sex race
-
0.0036
-
<0.001
2015-2018
MHBP
Adults
All adults
Race
Age sex income
-
<0.001
-
<0.001
2015-2018
MHBP
Adults
All adults
Sex
Age race income
-
<0.001
-
<0.001
2015-2018
MHBP
Adults
All adults
Years
Age sex race income
-0.0601
<0.001
-0.3351
<0.001
2015-2018
MHBP
Adults
All adults
Years
Age sex race income
-0.0601
<0.001
-0.3351
<0.001
2015-2018
MHBP
Adults
At or above poverty level
Years
Age sex race
0.02505
0.2319
0.05601
0.0758
2015-2018
MHBP
Adults
At or above poverty level
Years
Age sex race
0.02505
0.2319
0.05601
0.0758
2015-2018
MHBP
Adults
Below poverty level
Years
Age sex race
0.05588
0.1268
0.06424
0.0794
2015-2018
MHBP
Adults
Below poverty level
Years
Age sex race
0.05588
0.1268
0.06424
0.0794
2015-2018
MHBP
Adults
Black non-Hispanic
Years
Age sex income
0.03770
0.3541
-0.0619
0.1399
2015-2018
MHBP
Adults
Black non-Hispanic
Years
Age sex income
0.03770
0.3541
-0.0619
0.1399
2015-2018
MHBP
Adults
Females
Years
Age race income
-0.1028
<0.001
-0.3133
<0.001
2015-2018
MHBP
Adults
Females
Years
Age race income
-0.1028
<0.001
-0.3133
<0.001
2015-2018
MHBP
Adults
Males
Years
Age race income
-0.0057
0.7635
-0.108
<0.001
2015-2018
MHBP
Adults
Males
Years
Age race income
-0.0057
0.7635
-0.108
<0.001
2015-2018
MHBP
Adults
Mexican-American
Years
Age sex income
-0.0629
0.3873
0.67195
<0.001
2015-2018
MHBP
Adults
Mexican-American
Years
Age sex income
-0.0629
0.3873
0.67195
<0.001
2015-2018
MHBP
Adults
Other
Years
Age sex income
-0.0766
0.0866
-0.8002
<0.001
2015-2018
MHBP
Adults
Other
Years
Age sex income
-0.0766
0.0866
-0.8002
<0.001
2015-2018
MHBP
Adults
Unknown income
Years
Age sex race
-1.5314
<0.001
-4.2629
<0.001
2015-2018
MHBP
Adults
Unknown income
Years
Age sex race
-1.5314
<0.001
-4.2629
<0.001
2015-2018
MHBP
Adults
White non-Hispanic
Years
Age sex income
-0.1358
<0.001
0.26398
<0.001
2015-2018
MHBP
Adults
White non-Hispanic
Years
Age sex income
-0.1358
<0.001
0.26398
<0.001
2015-2018
MHBP
Children
All children (<16 years)
Age
Sex race income
-
<0.001
-
<0.001
2015-2018
MHBP
Children
All children (<16 years)
Income
Age sex race
-
0.0877
-
<0.001
2015-2018
MHBP
Children
All children (<16 years)
Race
Age sex income
-
0.0131
-
<0.001
2015-2018
MHBP
Children
All children (<16 years)
Sex
Age race income
-
0.9056
-
<0.001
2015-2018
MHBP
Children
Adolescents (11 to <16 years)
Years
Sex race income
0.22160
<0.001
-0.3986
<0.001
2015-2018
MHBP
Children
Adolescents (11 to <16 years)
Years
Sex race income
0.22160
<0.001
-0.3986
<0.001
2015-2018
MHBP
Children
Toddlers (3 to <6 years)
Years
Sex race income
0.22821
0.0773
0.19641
0.0885
2015-2018
MHBP
Children
Toddlers (3 to <6 years)
Years
Sex race income
0.22821
0.0773
0.19641
0.0885
2015-2018
MHBP
Children
Children (6 to <10 years)
Years
Sex race income
-0.1095
0.0533
-0.8971
<0.001
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Years
Metabolite
Group
Subset
Regression
Variable
Covariates
Regression
Coefficient, 50th
Percentile
P-value, 50th
Percentile
Regression
Coefficient, 95th
Percentile
P-value, 95th
Percentile
2015-2018
MHBP
Children
Children (6 to <10 years
Years
Sex race income
-0.1095
0.0533
-0.8971
<0.001
2015-2018
MHBP
Children
All children (<16 years
Years
Age sex race income
0.13948
<0.001
-0.6881
<0.001
2015-2018
MHBP
Children
All children (<16 years
Years
Age sex race income
0.13948
<0.001
-0.6881
<0.001
2015-2018
MHBP
Children
At or above poverty level
Years
Age sex race
-0.127
0.0043
-0.2311
<0.001
2015-2018
MHBP
Children
At or above poverty level
Years
Age sex race
-0.127
0.0043
-0.2311
<0.001
2015-2018
MHBP
Children
Below poverty level
Years
Age sex race
0.33899
<0.001
-1.0209
<0.001
2015-2018
MHBP
Children
Below poverty level
Years
Age sex race
0.33899
<0.001
-1.0209
<0.001
2015-2018
MHBP
Children
Black non-Hispanic
Years
Age sex income
0.21667
0.0049
-0.8785
<0.001
2015-2018
MHBP
Children
Black non-Hispanic
Years
Age sex income
0.21667
0.0049
-0.8785
<0.001
2015-2018
MHBP
Children
Females
Years
Age race income
0.11178
0.0274
-0.0377
0.5194
2015-2018
MHBP
Children
Females
Years
Age race income
0.11178
0.0274
-0.0377
0.5194
2015-2018
MHBP
Children
Males
Years
Age race income
0.07433
0.1299
-0.9418
<0.001
2015-2018
MHBP
Children
Males
Years
Age race income
0.07433
0.1299
-0.9418
<0.001
2015-2018
MHBP
Children
Mexican-American
Years
Age sex income
-0.4431
<0.001
-0.5245
<0.001
2015-2018
MHBP
Children
Mexican-American
Years
Age sex income
-0.4431
<0.001
-0.5245
<0.001
2015-2018
MHBP
Children
Other
Years
Age sex income
0.06189
0.549
-0.1149
0.4289
2015-2018
MHBP
Children
Other
Years
Age sex income
0.06189
0.549
-0.1149
0.4289
2015-2018
MHBP
Children
Unknown income
Years
Age sex race
-
0.0123
-
<0.001
2015-2018
MHBP
Children
Unknown income
Years
Age sex race
-
0.0123
-
<0.001
2015-2018
MHBP
Children
White non-Hispanic
Years
Age sex income
0.11139
0.0311
0.43391
<0.001
2015-2018
MHBP
Children
White non-Hispanic
Years
Age sex income
0.11139
0.0311
0.43391
<0.001
2015-2018
MHBP
Women
All women of reproductive age
Age
Sex race income
-
<0.001
-
<0.001
2015-2018
MHBP
Women
All women of reproductive age
Income
Age sex race
-
0.1377
-
0.2221
2015-2018
MHBP
Women
All women of reproductive age
Race
Age sex income
-
0.1005
-
<0.001
2015-2018
MHBP
Women
All women of reproductive age
Sex
Age race income
-
<0.001
-
<0.001
2015-2018
MHBP
Women
All women of reproductive age
Years
Age sex race income
-0.0308
0.5852
1.42648
<0.001
2015-2018
MHBP
Women
At or above poverty level
Years
Age sex race
0.01807
0.8223
0.11482
0.7696
2015-2018
MHBP
Women
Below poverty level
Years
Age sex race
-0.1646
0.1681
-0.6382
0.1531
2015-2018
MHBP
Women
Black non-Hispanic
Years
Age sex income
-0.0315
0.8479
0.77272
0.0866
2015-2018
MHBP
Women
Females
Years
Age race income
-0.0308
0.5852
1.42648
<0.001
2015-2018
MHBP
Women
Mexican-American
Years
Age sex income
0.10197
0.3969
2.08916
<0.001
2015-2018
MHBP
Women
Other
Years
Age sex income
-0.0185
0.848
0.74702
0.0093
2015-2018
MHBP
Women
Unknown income
Years
Age sex race
0.29205
0.0681
2.21315
<0.001
2015-2018
MHBP
Women
White non-Hispanic
Years
Age sex income
-0.0244
0.8612
2.05854
0.0229
Page 111 of 113
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PUBLIC RELEASE DRAFT
May 2025
Years
Metabolite
Group
Subset
Regression
Variable
Covariates
Regression
Coefficient, 50th
Percentile
P-value, 50th
Percentile
Regression
Coefficient, 95th
Percentile
P-value, 95th
Percentile
1999-2018
MnBP
Adults
All adults
Age
Sex race income
-
<0.001
-
<0.001
1999-2018
MnBP
Adults
All adults
Income
Age sex race
-
0.1101
-
<0.001
1999-2018
MnBP
Adults
All adults
Race
Age sex income
-
<0.001
-
<0.001
1999-2018
MnBP
Adults
All adults
Sex
Age race income
-
<0.001
-
<0.001
1999-2018
MnBP
Adults
All adults
Years
Age sex race income
-0.5043
<0.001
-1.5193
<0.001
1999-2018
MnBP
Adults
At or above poverty level
Years
Age sex race
-0.7337
<0.001
-1.9643
<0.001
1999-2018
MnBP
Adults
Below poverty level
Years
Age sex race
-0.8590
<0.001
-2.304
<0.001
1999-2018
MnBP
Adults
Black non-Hispanic
Years
Age sex income
-0.3549
<0.001
-1.8314
<0.001
1999-2018
MnBP
Adults
Females
Years
Age race income
-0.3713
<0.001
-1.8329
<0.001
1999-2018
MnBP
Adults
Males
Years
Age race income
-0.5328
<0.001
-1.1366
<0.001
1999-2018
MnBP
Adults
Mexican-American
Years
Age sex income
-0.7860
<0.001
-2.2968
<0.001
1999-2018
MnBP
Adults
Other
Years
Age sex income
-0.6674
<0.001
-1.224
<0.001
1999-2018
MnBP
Adults
Unknown income
Years
Age sex race
-0.04
0.2986
-0.5050
<0.001
1999-2018
MnBP
Adults
White non-Hispanic
Years
Age sex income
-0.6614
<0.001
-1.8375
<0.001
1999-2018
MnBP
Children
All children (<16 years
Age
Sex race income
-
0.386
-
0.0073
1999-2018
MnBP
Children
All children (<16 years
Income
Age sex race
-
0.2985
-
0.5367
1999-2018
MnBP
Children
All children (<16 years
Race
Age sex income
-
<0.001
-
<0.001
1999-2018
MnBP
Children
All children (<16 years
Sex
Age race income
-
0.0012
-
<0.001
1999-2018
MnBP
Children
Adolescents (11 to <16 years
Years
Sex race income
-0.7676
<0.001
-1.5696
<0.001
1999-2018
MnBP
Children
Toddlers (3 to <6 years
Years
Sex race income
-1.4556
<0.001
-2.027
<0.001
1999-2018
MnBP
Children
Children (6 to <10 years
Years
Sex race income
-0.6346
<0.001
-0.8292
<0.001
1999-2018
MnBP
Children
All children (<16 years
Years
Age sex race income
-0.7062
<0.001
-1.0890
<0.001
1999-2018
MnBP
Children
At or above poverty level
Years
Age sex race
-1.3871
<0.001
-2.6951
<0.001
1999-2018
MnBP
Children
Below poverty level
Years
Age sex race
-0.7066
<0.001
-1.7833
<0.001
1999-2018
MnBP
Children
Black non-Hispanic
Years
Age sex income
-1.7075
<0.001
-4.8491
<0.001
1999-2018
MnBP
Children
Females
Years
Age race income
-0.9803
<0.001
-0.3950
<0.001
1999-2018
MnBP
Children
Males
Years
Age race income
-0.6468
<0.001
-1.7490
<0.001
1999-2018
MnBP
Children
Mexican-American
Years
Age sex income
-0.7349
<0.001
-0.3946
<0.001
1999-2018
MnBP
Children
Other
Years
Age sex income
-0.975
<0.001
-0.7710
<0.001
1999-2018
MnBP
Children
Unknown income
Years
Age sex race
-0.5003
<0.001
0.70492
<0.001
1999-2018
MnBP
Children
White non-Hispanic
Years
Age sex income
-0.4363
<0.001
-1.1186
<0.001
1999-2018
MnBP
Women
All women of reproductive age
Age
Sex race income
-
<0.001
-
<0.001
1999-2018
MnBP
Women
All women of reproductive age
Income
Age sex race
-
0.3669
-
<0.001
1999-2018
MnBP
Women
All women of reproductive age
Race
Age sex income
-
0.0068
-
<0.001
Page 112 of 113
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PUBLIC RELEASE DRAFT
May 2025
Years
Metabolite
Group
Subset
Regression
Variable
Covariates
Regression
Coefficient, 50th
Percentile
P-value, 50th
Percentile
Regression
Coefficient, 95th
Percentile
P-value, 95th
Percentile
1999-2018
MnBP
Women
All women of reproductive age
Sex
Age race income
-
<0.001
-
<0.001
1999-2018
MnBP
Women
All women of reproductive age
Years
Age sex race income
-1.1953
<0.001
-1.1005
<0.001
1999-2018
MnBP
Women
At or above poverty level
Years
Age sex race
-1.0600
<0.001
-3.9577
<0.001
1999-2018
MnBP
Women
Below poverty level
Years
Age sex race
-1.4453
<0.001
-3.7430
<0.001
1999-2018
MnBP
Women
Black non-Hispanic
Years
Age sex income
-1.6397
<0.001
-3.9001
<0.001
1999-2018
MnBP
Women
Females
Years
Age race income
-1.1953
<0.001
-1.1005
<0.001
1999-2018
MnBP
Women
Mexican-American
Years
Age sex income
-1.1381
<0.001
0.91770
<0.001
1999-2018
MnBP
Women
Other
Years
Age sex income
-1.4323
<0.001
-4.7382
<0.001
1999-2018
MnBP
Women
Unknown income
Years
Age sex race
-1.1137
<0.001
-0.2231
0.1547
1999-2018
MnBP
Women
White non-Hispanic
Years
Age sex income
-0.9298
<0.001
-2.7311
<0.001
2979
2980
2981
Page 113 of 113
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