PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
v>EPA
United States
Environmental Protection Agency
Office of Chemical Safety and
Pollution Prevention
Draft Risk Evaluation for
Cyclic Aliphatic Bromides Cluster
(HBCD)
Supplemental Information on General Population,
Environmental and Consumer Exposures
CASRN
NAME
25637-99-4
Hexabromocyclododecane
3194-55-6
1,2,5,6,9,10-Hexabromocyclododecane
3194-57-8
1,2,5,6-Tetrabromocy clooctane
June, 2019
1
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Table of Contents
1 Overview of the Systematic Review Process 9
1.1 Data Extraction Methods and Approach 9
1.2 Data Integration Methods and Approach 9
2 Overview of Key Studies and Data Quality Ratings 10
2.1 Fish 11
2.1.1 North America 11
2.1.1.1 Chen ct al. (2011) 11
2.1.2 Europe 12
2.1.2.1 Pomaetal. (2014) 12
2.1.2.2 Jenssen et al. (2007) 12
2.2 Avian 13
2.2.1 North America 13
2.2.1.1 Chen el al. (2012) 13
2.2.2 Europe 13
2.2.2.1 Sellstrom et al. (2003) 13
2.2.2.2 Esslinger et al. (2011) 14
2.3 Vegetation/Diet 14
2.3.1 North America 14
2.3.1.1 Schecter et al. (2012) 14
2.3.2 Europe 15
2.3.2.1 Goscinny etal. (2011) 15
2.3.3 Asia 15
2.3.3.1 Harghiet al. (2016) 15
2.4 Surface Water 16
2.4.1 North America 16
2.4.1.1 Venieretal. (2014) 16
2.4.2 Europe 16
2.4.2.1 Harrad et al. (2009) 16
2.4.3 Asia 17
2.4.3.1 Ichiharaetal. (2014) 17
2.4.3.2 He etal. (2013) 17
2.4.3.3 Oh etal. (2014) 17
2.5 Sediment 18
2.5.1 North America 18
2.5.1.1 LaGuardiaetal. (2012) 18
2.5.1.2 Yang etal. (2012) 18
2.5.2 Australia 18
2.5.2.1 Drage etal. (2015) 18
2.6 Soil 19
2.6.1 Europe 19
2.6.1.1 Remberger et al. (2004) 19
2.6.2 Asia 19
2.6.2.1 Wang etal. (2013) 19
2.6.2.2 Wang et al. (2009) 19
2.6.2.3 Li etal. (2016) 20
2.7 Ambient Air 20
2.7.1 North America 20
2.7.1.1 Hoh and Hites (2005) 20
2.7.1.2 Shoeib etal. (2014) 21
2.7.2 Asia 21
2.7.2.1 Li etal. (2016) 21
2
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
2.8 Indoor Dust 21
2.8.1 North America 21
2.8.1.1 Stapleton et al. (2014) 21
2.8.1.2 Allgoodetal. (2016) 21
2.8.2 Europe 22
2.8.2.1 D'Hollanderetal. (2010) 22
2.8.2.2 Sahlstrom et al. (2015) 22
2.8.3 Asia 22
2.8.3.1 Qietal. (2014) 22
2.9 Indoor Air 23
2.9.1 Europe 23
2.9.1.1 Abdallah et al. (2008) 23
2.9.2 Asia 23
2.9.2.1 Hong etal. (2016) 23
2.10 Human Milk 24
2.10.1 North America 24
2.10.1.1 Carignanetal. (2012) 24
2.10.2 Europe 24
2.10.2.1 Tao etal. (2017) 24
2.10.2.2 Antignac etal. (2016) 25
2.11 Human Serum 25
2.11.1 Europe 25
2.11.1.1 Kalantzietal. (2011) 25
3 Overview of Human Biomonitoring 25
3.1 Blood 26
3.1.1 Blood ng/g chart 26
3.1.2 Blood (ng/g) Summary Statistics 26
3.1.3 Human Blood (ng/g): Supporting Data 26
3.2 Breast Milk 28
3.2.1 Breast milk Chart 28
3.2.2 Breast Milk Summary Statistics 29
3.2.3 Breast Milk: Supporting Data 30
3.2.4 North America 32
3.2.5 Europe 33
3.2.6 Asia 34
3.2.7 Australia 34
3.2.8 Africa 34
4 Overview of Wildlife Biota Summary 35
4.1 Fish 35
4.1.1 Wildlife Biota 35
4.1.1.1.1 Fish Chart 35
4.1.1.1.2 Fish Summary Statistics 37
4.1.1.1.3 Fish: Supporting Data 39
4.1.1.1.4 North America 47
4.1.1.1.5 Europe 47
4.1.1.1.6 Asia 48
4.2 Birds 49
4.2.1 Birds Chart 49
4.2.2 Birds Summary Statistics 50
4.2.3 Birds: Supporting Data 53
4.2.4 North America 61
4.2.5 Europe 63
4.2.6 Asia 65
4.2.7 Africa 65
3
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
5 Overview of Environmental Monitoring Data 66
5.1 Surface Water 66
5.1.1 Environmental Media 66
5.1.1.1.1 Surface Water (ng/g) Chart 66
5.1.1.1.2 Surface Water (ng/g) Summary Statistics 66
5.1.1.1.3 Surface Water (ng/g): Supporting Data 66
5.1.1.1.4 Surface Water (ng/L) Chart 67
5.1.1.1.5 Surface Water (ng/L) Summary Statistics 67
5.1.1.1.6 Surface Water (ng/L): Supporting Data 68
5.1.1.1.7 Surface Water Summary 69
5.2 Sediment 71
5.2.1 Sediment Chart 71
5.2.2 Sediment Summary Statistics 72
5.2.3 Sediment: Supporting Data 74
5.2.3.1.1 North America 78
5.2.3.1.2 Europe 79
5.2.3.1.3 Asia 79
5.2.4 Soil 80
5.2.4.1.1 Soil Chart 80
5.2.4.1.2 Soil Summary Statistics 80
5.2.4.1.3 Soil: Supporting Data 81
5.2.4.1.4 Europe 83
5.2.4.1.5 Asia 83
5.2.5 Indoor Dust 84
5.2.5.1.1 Indoor Dust Chart 84
5.2.5.1.2 Indoor Dust Summary Statistics 85
5.2.5.1.3 Indoor Dust: Supporting Data 87
5.2.5.1.4 North America 91
5.2.5.1.5 Europe 92
5.2.5.1.6 Asia 93
5.2.6 Indoor Air 94
5.2.6.1.1 94
5.2.6.1.2 94
5.2.6.1.3 Indoor Air (ng/m3) Chart 94
5.2.6.1.4 Indoor Air (ng/m3) Summary Statistics 94
5.2.6.1.5 Indoor Air (ng/m3): Supporting Data 95
5.2.6.1.6 Europe 96
5.2.6.1.7 Asia 96
5.2.7 Ambient Air 97
5.2.7.1.1 Ambient Air (ng/m3) Chart 97
5.2.7.1.2 Ambient Air (ng/m3) Summary Statistics 98
5.2.7.1.3 Ambient Air (ng/m3): Supporting Data 99
5.2.7.1.4 Ambient Air (ng/g) Chart 101
5.2.7.1.5 Ambient Air (ng/g) Summary Statistics 101
5.2.7.1.6 Ambient Air (ng/g): Supporting Data 101
5.2.7.1.7 North America 101
5.2.7.1.8 Europe 103
5.2.7.1.9 Asia 103
5.2.8 Dietary Monitoring 104
5.2.8.1.1 Daily Chart 104
5.2.8.1.2 Dairy Summary Statistics 104
5.2.8.1.3 Dairy: Supporting Data 105
5.2.8.1.4 Fruit Chart 107
5.2.8.1.5 Fruit Summary Statistics 107
5.2.8.1.6 Fruit: Supporting Data 108
4
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
5.2.8.1.7 Grain Chart 108
5.2.8.1.8 Grain Summary Statistics 109
5.2.8.1.9 Grain: Supporting Data 109
5.2.8.1.10 Meat Chart 110
5.2.8.1.11 Meat Summary Statistics 110
5.2.8.1.12 Meat: Supporting Data Ill
5.2.8.1.13 Other Foods Chart 114
5.2.8.1.14 Other Foods Summary Statistics 114
5.2.8.1.15 OtherFoods: Supporting Data 115
5.2.8.1.16 Seafood Chart 117
5.2.8.1.17 Seafood Summary Statistics 117
5.2.8.1.18 Seafood: Supporting Data 118
5.2.8.1.19 Vegetable Chart 121
5.2.8.1.20 Vegetable Summary Statistics 121
5.2.8.1.21 Vegetable: Supporting Data 121
5.2.9 Sewage Sludge 123
5.2.9.1.1 Sewage Sludge andBiosolids Summary 123
5.2.9.1.2 North America 123
5.2.9.1.3 Europe 124
5.2.9.1.4 Asia 124
6 Overview of Doses Estimated by Others and Comparison with EPA doses 127
6.1 Overview of Modeling Approaches Used 127
6.1.1 IECCU 127
6.1.1.1.1 Typical" residential home 127
6.1.1.1.2 "Typical" passenger vehicle 128
6.1.1.1.3 Temperature in the vehicle 128
6.1.1.1.4 HBCD source 129
6.1.1.1.5 Settled dust 129
6.1.1.1.6 Estimation of key parameters 129
6.1.1.1.7 Model parameters 131
6.1.2 IIOAC 132
6.1.3 WWM-PSC 134
6.2 Overview of Indoor SVOC Exposure, Fate, and Transport 135
6.2.1 Chemical Mass Transfer from Source to Particles 138
6.2.2 Chemical Mass Transfer from Source to Skin 139
6.2.3 Transfer to Dust by source fragmentation and direct source-dust contact 139
6.2.4 Fate and Transport of Chemical Substances within Indoor Environments 140
6.2.5 Chemical Mass Transfer between Air and Particles 140
6.2.6 Chemical Mass Transfer between Air and Sinks 141
6.2.7 Relationship between prevalence in media and physical-chemical properties 141
6.2.8 Estimating Exposure and Relevant Exposure Pathways for SVOCs 142
6.2.9 Ingestion of Suspended Particles, Settled Dust, and Mouthing 142
6.2.10 Dermal Contact with Source, Airborne SVOCs, and Sinks 143
6.3 Age-Specific Exposure Factors and Activity Patterns Used in this Assessment 144
5
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Abbreviations
Mg/kg
(im
AMEM
APCI
BFR
BEED
bw/day
CHirP
CHMS
cm
cm/year
CMI-CWF
dw
EC
ECNI
EDI
EFSA
EPA
EPS
ESB
ESI
GC/ECD
GC-MS
GFF
GLHGMP
ha
HBCD
microgram per kilogram
micrometer
Arthur D. Little Migration Estimation Model
Atmospheric Pressure Chemical Ionization
Brominated Flame Retardants
Breast milk, Environment, Early-life, and Development
body weight per day
Chemicals Health and Pregnancy
Canadian Health Measures Survey
centimeter
centimeters per year
Clean Michigan Initiative-Clean Water Fund
dry weight
European Commission
electron capture negative ionization
Estimated Dietary Intake
European Food Safety Authority
Environmental Protection Agency
expanded polystyrene
German Environmental Specimen Bank
electrospray ionization mode
gas chromatography with electron capture detection
gas chromatography-mass spectrometry
glass fiber filters
Great Lakes Herring Gull Monitoring Program
gas-phase mass transfer coefficient
hexabromocyclododecane
6
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HPLC high performance liquid chromatography
HPLC MS/MS high performance liquid chromatography with triple quadrupole mass
spectrometry
hr/day hours per day
IIOAC Integrated Indoor-Outdoor Air Calculation
Kd linear sorption coefficient
kg/m3 kilograms per cube meter
km kilometer
Koc organic carbon portioning linear coefficient
LC-ESI-MS/MS liquid chromatography-electrospray ionization-tandem mass spectrometry
LC-MS/MS liquid chromatography-tandem mass spectrometry
LOD limit of detection
LOQ limit of quantification
lw lipid weight
m meter
mg/m2/hr milligram per meter squared per hour
mL/day milliliter per day
m meter
mg/m2/hr milligrams per square meter per hour
mL/day milliliter per day
MLOD method limit of detection
MLOQ method limit of quantification
NAAQS National Ambient Air Quality Standards
ND non-detect
NESI negative electrospray ionization mode
ng/g nanogram per gram
ng/L nanogram per liter
ng/m3 nanogram per cube meter
NICNAS National Industrial Chemicals Notification and Assessment Scheme
NSSS National Sewage Sludge Survey
7
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
OPPT
PBT
Pg
PM
POP
POPUP
PSC
PUF
SIM
SVOC
TOC
TSoverall
UPLC-APPI-MS/MS
UPLC-ESI-MS
UPLC-MS/MS
VVWM
WW
WWTP
XPS
Office of Pollution Prevention and Toxics
persistent bioaccumulative toxic
picogram
particulate matter
persistent organic pollutants
Persistent Organic Pollutants in Uppsala Primiparas
point source calculator
polyurethane foam
selected ion monitoring
semi-volatile organic compounds
total organic carbon
overall time spent
ultra-performance liquid chromatography with tandem mass spectrometry
detection using atmospheric pressure photoionization
ultra-performance liquid chromatography coupled to electrospray ionization
and mass spectrometry
ultra-performance liquid chromatography with tandem mass spectrometry
variable volume water module
wet weight
wastewater treatment plant
extruded polystyrene
8
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
1 Overview of the Systematic Review Process
EPA completed a comprehensive literature search for hexabromocyclododecane (HBCD) along with the
first 10 chemicals. EPA also completed supplemental searches that incorporated additional articles from
the following sources: references cited in public comments, references identified as part of earlier efforts
to assess exposure to HBCD and other flame retardants, and references identified in EPA's Exposure and
Use Assessment for Persistent Bioaccumulative Toxic (PBT) chemicals. Many of the articles that reported
information for DecaBDE (one of the PBT5 chemicals) also reported information for HBCD.
After all references from all sources were cross-walked and screened, remaining articles were evaluated
and extracted. For an article to pass screening, it had to be cover any part of the conceptual model
describing potential exposures across the lifecycle of HBCD. It is also worth noting, that additional non-
chemical specific sources such as model user guides, guidance documents, or articles that generally
discuss exposure pathways of interest for chemicals like HBCD (semi-volatile organic compounds) are
also referenced in this exposure assessment and supplemental file but are not part of the "count" of the
universe of articles that went through EPA/OPPT's systematic review process.
1.1 Data Extraction Methods and Approach
Studies that were determined to be of sufficient data quality at the data quality evaluation stage that also
contained primary quantitative monitoring data, modeled media data, or modeled intake or dose data were
selected for extraction.
For environmental monitoring and biomonitoring studies values describing the overall range of data
(minimum, maximum, mean, median, and frequency of detection) were extracted for each media
presented in the study. Extracted data were further annotated with salient details such as population
characteristics, species, location by country, sampling dates, sample media phase (e.g. gas versus
particulate phase in air), weight fraction (e.g. lipid, wet or dry weight), tissue type, and location type (e.g.
residential, commercial or vehicle for indoor environments and background or near facility for outdoor
environments).
For studies that contained modeled estimates of intake or dose a similar approach was taken to capture the
range of data; however, model estimates tended to either be point estimates or present a central tendency
and high end. In all cases, the study data were extracted along with receptor characteristics, country, and
pathways considered.
1.2 Data Integration Methods and Approach
Extracted study data required further processing to allow for the standardization and integration of HBCD
data across all studies.
Where studies reported isomers of HBCD (alpha, beta, gamma) separately, these values were summed
and total HBCD was recorded. For studies that reported a frequency of detection of less than 100%, that
is, that HBCD was not detected in all samples, a value of one-half the limit of detection was imputed as
the minimum value for each study and media combination. Reported intakes were converted into average
daily doses based on exposure factors describing media intake rates by receptor (cite exposure factors.)
All data were converted to a common unit and aggregated to determine the overall range (lowest reported
value to highest reported value) and the range of central tendencies (means and medians) reported for
9
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
each study, media, and location type. The plots in sections 3-5 of this supplement contain a data summary
plot for each media presenting all studies containing relevant data. These are presented first by location
type and then, where applicable, by sample media phase or weight fraction. Within each location type,
monitoring data from the US are presented first, followed by data from other countries in alphabetical
order by country code, followed by modeled data where available. For each country, data are presented
from newest to oldest, based on latest year of sampling. Differentiation by species and tissue type are not
shown in these summary plots. The lighter region of each bar represents the overall range of data and the
darker region represents the range of central tendency reported in each study. For dose data estimated
from modeled intake, each bar represents the mean and high-end central tendency estimates based on the
assumptions of the exposure factor.
2 Overview of Key Studies and Data Quality Ratings
Table 2-1 provides the key studies and their overall data quality evaluation score for various media.
Summaries are also provided in subsequent sections of this supplemental file. Additional details about the
data quality evaluation of each study in Table 2-1 are provided in the Systematic Review Supplemental
File for the TSCA Risk Evaluation: Data Quality Evaluation for Data Sources on Consumer, General
Population and Environmental Exposure.
Figure 2-1. Key studies for the Evaluation of Environmental and Human Exposures
Media
HERO ID
Short Citation
Data Quality
Rating
Fish
1927627
Chen etal. (2011)
High
2343698
Poma et al. (2014)
High
1927762
Jenssenefo/. (2007)
High
Avian
1851195
Chen et al. (2012)
Medium
999339
Sellstrom et al. (2003)
High
1927650
Esslinger et al. (2011)
High
Vegetation/Diet
1401050
Schecter et al. (2012)
High
787666
Goscinny et al. (2011)
High
3350483
Barglii et al. (2016)
High
Surface Water
2695212
Venier etal. (2014)
High
1927694
Harrad et al. (2009)
High
2343678
Ichihara el at. (2014)
High
1927551
He etal. (2013)
High
2343704
Oh etal. (2014)
High
Sediment
1927601
La Guardia etal. (2012)
High
1927611
Yang etal. (2012)
High
10
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Media
HERO ID
Short Citation
Data Quality
Rating
3350544
Drage et al. (2015)
High
Soil
1927826
Rcmbcrgcr el al. (2004)
Medium
1927586
Wang et al. (2013)
Medium
1927688
Wang et al. (2009)
High
3546008
Li et al. (2016)
High
Ambient Air
999242
Hoh and Hites (2005)
Medium
3019586
Shoeib et al. (2014)
Medium
3355687
Li et al. (2016)
Medium
Indoor Dust
2343712
Stapleton et al. (2014)
Medium
3455810
Allgood et al. (2016)
High
1578505
D'Hollander et al. (2010)
High
3012178
Sahlstrom et al. (2015)
High
2528328
Qi et al. (2014)
High
Indoor Air
1079114
Abdallahetal. (2008)
High
3227425
Hong etal. (2016)
High
Human Milk
1927577
Carignan etal. (2012)
High
3862906
Tao et al. (2017)
High
3449916
Antignac et al. (2016)
High
Human Serum
1927656
Kalantzi et al. (2011)
Medium
3809262
Peters (2004)
High
2.1 Fish
2.1.1 North America
2.1.1.1 Chen etal. (2011)
Chen et al. (2011) sampled fish in southeastern Virginia and northeastern North Carolina, a region known
historically as a center for textile production. Sample collection of 189 individual adult fish via
electrofishing from sites in the Hyco, Dan and Roanoke Rivers occurred from May to October 1999-2002
and 2006-2007. The five species sampled were common carp (Cyprinus carpio), flathead catfish
(Pylodictus olivaris), channel catfish (Ictalurus punctatus), redhorse sucker (Moxostoma sp.), and gizzard
shad (Dorosoma cepedianum). Fish were filleted and both individual fish fillets and single species
composites of fillets from multiple individuals were analyzed by ultra-performance liquid
chromatography coupled to electrospray ionization and mass spectrometry (UPLC-ESI-MS).
11
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Concentrations varied between rivers, but mean total HBCD concentrations increased at all rivers
between the 1999-2002 sampling interval (ND-22 ng/g lw) and 2006-2007 sampling interval (13 to 4,640
ng/g lw). The Hyco River generally had the highest concentrations of HBCD. The Hyco watershed is
predominately agricultural and forested, but three of the Hyco samplings sites are located downstream of
a known BFR-using site (textile related) and a receiving wastewater treatment plant (WWTP). The Dan
and Roanoke are large rivers with multiple small towns located within their watersheds, with historical
textile and furniture operations. In addition, Chen et al. (2011) conducted a meta-analysis of their present
study and seventeen other studies to see if near facility concentrations in fish differed from fish samples
collected further away from facilities. The authors report that concentrations in fish sampled near point
sources were generally 1 to 2 orders of magnitude higher than fish located further away from sources. For
fish located near points sources, Chen et al. (2011) reported concentrations in fish from near point sources
ranging from 38 to 6,660 ng/g lw and concentrations in fish from more remote areas ranging from 0.1 to
51.5 ng/g lw.
2.1.2 Europe
2.1.2.1 Poma et al. (2014)
Poma et al. (2014) studied whether HBCD can bioaccumulate in a pelagic food web of a large and deep
subalpine lake (Lake Maggiore, Northern Italy), whose catchment is a highly populated area with many
manufacturing plants. Zooplankton, shad (Alosa agone) and whitefish (Coregonus lavaretus) were
sampled from Lake Maggiore from May 2011 to lanuary 2012 in four different seasons and at different
locations and depths within the pelagic lake. Fish muscle and liver samples and zooplankton were
analyzed by gas chromatography-mass spectroscopy (GC-MS) for total HBCD. Levels of detection
(LODs) were estimated for each compound as 0.1 ng/g dry weight in biological samples. For
zooplankton, minimum = 29 ng/g lw; maximum = 167 ng/g lw. For fish muscle (n=16), minimum = 13
ng/g lw; maximum = 792 ng/g lw. For fish liver (n=16), minimum = 27 ng/g lw; maximum = 1,232 ng/g
lw. Results confirmed that HBCD can biomagnify within food webs. The study discusses the variability
in lipid content of fish across seasons, isotope analysis differences, and uncertainty regarding human use
of HBCDs.
2.1.2.2 Jenssen et al. (2007)
lenssen et al. (2007) studied HBCD in fish in North-East Atlantic coastal marine ecosystems along a
latitudinal gradient from southern Norway to Spitsbergen, Svalbard, in the Arctic. Atlantic cod (Gadus
morhua) from Oslofjord and Froan and polar cod (Boreogadus saida) from Bear Island and Spitsbergen
were collected in 2003. Homogenized whole fish samples were analyzed using GC-MS. Detection limits
were set to about 3 times the noise level. For Oslofjord. Atlantic cod (n=21): mean = 25.6 ng/g lw; st.dev.
= 13.4 ng/g lw. For Froan, Atlantic cod (n=18): mean = 18.7 ng/g lw; st.dev. = 10.5 ng/g lw. For Bear
Island, polar cod (n=6): mean = 11.7 ng/g lw; st.dev. = 7.2 ng/g lw. For Spitzbergen, polar cod (n=7):
mean =1.8 ng/g lw; st.dev. = 0.58 ng/g lw. When comparing levels of HBCD in the two cod species from
all four locations, levels of HBCD were Osloijord ~ Froan > Bear Island » Spitsbergen, i.e. levels of
HBCD generally decreased as a function of increasing latitude, reflecting distance from release sources.
The use and leakage of brominated flame retardants (BFRs) into the environment is higher in urbanized
areas along the Norwegian coast than in the almost unpopulated Spitsbergen. High levels of BFRs have
been reported in sewage and because of their semi volatile properties, HBCD are subject to long-range
atmospheric transport likely the origin of the BFRs detected in endemic Arctic biota.
12
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
2.2 Avian
2.2.1 North America
2.2.1.1 Chen et al. (2012)
Chen et al. (2012) studied eggs of four gull species (Laridae) from Canadian marine and freshwater
ecosystems collected from a total of 26 colonies spanning Pacific to Atlantic Canada, including the Great
Lakes basin. Gulls are top predators in their respective ecosystems and ideal for monitoring halogenated
contaminants. Herring gull eggs from fifteen Great Lakes colony sites were collected from late-April to
early-May of 2008. For each colony site, 10 tol3 individual eggs from different nests were pooled on an
equal wet-weight basis. In addition, individual eggs (n=10) from different nests of glaucous-winged
(Larus glaucescens), California (Larus californicus), ring-billed (Larus delawarensis) or herring gulls
were also collected in early-May to early-July of 2008 from each of 11 additional colonies spanning the
Pacific to the Atlantic coast of Canada. The pooled and individual eggs were homogenized and stored at -
40 C at Environment Canada's National Wildlife Specimen Bank prior to chemical analysis. HBCD was
analyzed for using GC-MS-in electron capture negative ionization (ECNI). Method blanks were
processed to monitor interferences and contamination and method limit of quantification (MLOQ) = 1.1
ng/g and MLOD (method limit of detection) = 0.28 ng/g. In the marine ecosystem (n=6 pooled samples):
minimum median = 0.5 ng/g ww; maximum median = 4.5 ng/g ww; minimum arithmetic mean = 2.2 ng/g
ww; maximum arithmetic mean = 9 ng/g ww. For the non-Great Lakes freshwater ecosystem (n=5 pooled
samples): minimum median = 4.4 ng/g ww; maximum median = 11.7 ng/g ww; minimum arithmetic
mean = 6.7 ng/g ww; maximum arithmetic mean = 16.6 ng/g ww. For the Great Lakes ecosystem (n = 15
pooled samples): minimum of pooled samples = 2.0 ng/g ww; maximum of pooled samples = 12 ng/g
ww. Gulls breeding in regions with higher human population densities likely incurred greater flame
retardant exposure. This study also contains an analysis of stable isotopes as dietary tracers in relation to
flame retardants.
2.2.2 Europe
2.2.2.1 Sellstrom et al. (2003)
Sellstrom et al. (2003) conducted a temporal trend study of HBCD concentrations in individual and/or
pooled Guillemot bird eggs collected between 1969 and 2001 from Stora Karlso, an island off Sweden's
west coast in the Baltic Sea. The study is partly based on the analysis of eggs archived and stored in the
Swedish Environmental Specimen Bank. Guillemot eggs have previously been shown to be a very
important matrix for studies of persistent environmental contaminants, as Guillemots are stationary within
the Baltic the entire year, they nest far away from local sources in the central part of the Baltic Proper,
and they feed exclusively on pelagic fish that migrate within the Baltic. In this investigation, egg
sampling was constrained to early laid eggs to avoid an important source of within-year variation.
Samples were analyzed using GC-MS run in the chemical ionization mode, measuring the negative ions
formed (ECNI). Quality control measures taken included analysis of duplicate or triplicate calibration
curves, laboratory blanks, recovery samples, and the use of laboratory reference material (herring
homogenate) extracted and analyzed in parallel with the guillemont eggs. Specifically, one pooled sample
of 10 archived eggs was analyzed per study year between 1969 and 1992 (no eggs from 1970, 1974, 1979,
1984, and 1991 were studied) and 10 eggs were analyzed individually per study year between 1993 and
2001. Additionally, the uncertainty of the results obtained from the pooled samples was investigated by
analyzing individual eggs from 1976 and 1992; the pooled egg concentrations were within the range of
the individual egg concentrations. For HBCD, the analysis indicates a steady and significant (p < 0.001)
increase in concentrations over time up to recent periods, although there are indications of a minor peak
during the mid-1970s or a decrease in concentrations during 1978-1985. The concentrations of HBCD
13
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
have approximately doubled during the study period, but this increase seems to have leveled out since the
mid-1990s. For 1969-1992 samples (n=18 pooled samples): minimum = 34 ng/g lw; maximum = 140
ng/g lw. For 1993-2001 samples (n=l 19 individual samples): minimum = 54 ng/g lw; maximum = 300
ng/g lw; minimum annual arithmetic mean =110 ng/g lw; maximum annual arithmetic mean =170 ng/g
lw.Verreault et al. reported four studies over four years that reported concentrations of HBCD in various
tissues of glaucous gulls.
2.2.2.2 Esslinger et al. (2011)
Esslinger et al. (2011) sampled herring gull eggs from the islands Mellum and Trischen in the German
Wadden Sea and from the island Heuwiese at the German Baltic Sea coast from 1998 to 2008. Between
35 and 140 eggs were collected annually and the whole content of all eggs from a given site and year
were pooled and archived by the German Environmental Specimen Bank (ESB). Egg powders as received
from the ESB were homogenized and stored at -20 C until further processing. The 26 egg pool samples
were analyzed by high performance liquid chromatography with triple quadrupole mass spectrometry
(HPLC-MS/MS) where the LOD for the six stereoisomers ranged between 0.13 and 0.26 pg/g and limit of
quantification (LOQ) between 0.48 and 0.93 pg/g. Herring gull eggs are excellent indicators of
contaminant exposure in the environment, herrings maintain stable population dynamics, and their
feeding habits are well known. Results are reported as six stereoisomers for a-, (3-, y-HBCD, where a-
HBCD was detected as the dominant diastereoisomer. Results for total HBCD: Mellum island, 1988-
2008, (n=10 pooled samples): minimum = 4.17 ng/g lw; maximum = 107 ng/g lw; Trischen island, 1988-
2008, (n=10 pooled samples): minimum = 13.8 ng/g lw; maximum = 74.8 ng/g lw. Heuwiese island,
1998-2008, (n=6 pooled samples): minimum = 25.1 ng/g lw; maximum = 98.7 ng/g lw. The average
contamination levels at the three locations are relatively close but nevertheless significantly different from
each other. The increase in concentration of HBCD in eggs between 1994 and 2000 might reflect the
steady rise in demand of HBCD during this period. Esslinger et al. (2011) also examined temporal trend
data on HBCD from bird eggs from other locations from 1970 to 2004. The concentrations in the current
study were in the middle range and similar to gull and guillemot eggs elsewhere in Europe. The trends in
the reported secondary data varied, including increases in bird eggs from 1983-2003 in Northern Norway,
no increases from guillemot eggs from a Swedish Baltic Sea between 1991 and 2001, and slight decreases
in peregrine falcon eggs from Greenland between 1986 and 2003 and tawny owl eggs from Central
Norway between 1986 and 2004.
2.3 Vegetation/Diet
2.3.1 North America
2.3.1.1 Schecter et al. (2012)
Schecter et al. (2012) measured HBCD stereoisomers (alpha-, beta-, gamma-HBCD) in a variety of
common, lipid-rich U.S. foods purchased from supermarkets in Dallas, TX in 2010. Thirty-six individual
food samples, generally consisting of fish, poultry, pork, beef and peanut butter, were analyzed by liquid
chromatography-tandem mass spectrometry (LC-MS/MS). QA/QC measures included multipoint
calibration curves, blanks, duplicates, and reference samples. Total HBCD in the individual food samples
ranged from 0.010-1.366 ng/g ww, after setting values
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
present study an association between higher lipid levels and higher HBCD levels were noted. In addition,
ten pooled samples collected and analyzed in 2009 by GC-MS for total HBCD (from previous study,
Schecter et al., 2009) were reanalyzed for stereoisomers by LC-MS/MS in 2010 as part of the current
study, Schecter et al. (2012). These previously analyzed samples were known to contain detectable levels
of HBCD. The median concentration of total HBCD in reanalyzed pooled samples (reported as sum of
stereoisomers) was 0.116 ng/g ww. Schecter et al. (2012) also compared the total HBCD concentrations
to levels from other studies. Reported concentrations from studies in Scotland, Japan and the Netherlands
were higher, whereas reported concentrations from Romania, Sweden, UK, Norway were lower. Schecter
et al. (2012) discussed various possible reasons for differences, such as the lipid content of food, dust
contamination during food preparation, transfer of HBCD from soil to vegetables, livestock raising and
husbandry practices, and differences in sources, handling, ingredients, and packaging.
2.3.2 Europe
2.3.2.1 Goscinny et al. (2011)
Goscinny et al. (2011) assessed dietary exposure of the adult Belgian population by measuring HBCD
diastereoisomers (a-, (3-, and y-HBCD) by ultra-performance liquid chromatography with tandem mass
spectrometry (UPLC-MS/MS) in foods common to the Belgian diet. Food samples from 5 major food
groups (dairy, meat, eggs, fish and other food products such as breads, oils and pastries) were purchased
in autumn 2008 from supermarkets, fish and butcher shops in Brussels (n=549 individual food samples,
combined into 43 composite samples). QA/QC measures were consistent with ISO 17025 and included
in-house method validation, method blanks and spiked fish oil samples. HBCDs were detected in 80% of
the composite food samples (35 out of 43 samples). HBCD diastereoisomer concentrations were summed
and reported in the study as total HBCD, which for the lower, medium and upper bound concentrations
ranged from 0-14.652, 0.150-14.652, and 0.550-14.652 ng/g lw, respectively. [For samples in which
HBCD was not detected, concentration levels for the diastereoisomers were assigned as follows: lower
bound=0, medium bound=l/2 LOD, upper bound=LOD. For samples with HBCD levels between LOD
and LOQ, concentration levels for the diastereoisomers were assigned as follows: lower bound=LOD,
medium bound=(LOD + LOQ)/2 and upper bound=LOQ.] a-, (3-, and y-HBCD were detected in all food
groups; a-HBCD was predominant in fish, while y-HBCD was predominant in dairy products and meat.
Estimated dietary intake (EDI) was based on medium bound total HBCD concentrations from this study
and consumption data from the Belgian national food consumption survey of 2004. The total average
dietary intake (medium bound) = 0.991 ng/kg bw/day, with SD=0.374 ng/kg bw/day. Total average
EDI's for adults in other countries (UK, China, Sweden, the Netherlands, Japan) determined in other
studies were also provided, and except for China, were greater than the Belgian values.
2.3.3 Asia
2.3.3.1 Barghi et al. (2016)
Barghi et al. (2016) monitored HBCD concentrations in foods common to the Korean diet and determined
dietary exposure to the Korean population. Food samples of 57 food items from 8 major food groups
(fish, shellfish, meat, egg, dairy products, vegetables, fruit and cereal/rice) were purchased from
supermarkets and local markets in five Korean cities from 2012-2014 (n=521 individual food samples).
HBCD diastereoisomers (a-, (3-, and y-HBCD) were measured by LC-MS/MS. QA/QC measures
included multipoint calibration curves, method blanks, recovery standards and certified reference
materials. HBCDs were detected in >80% of all study samples; total HBCD concentrations ranged from
ND (non-detect) (<0.006 ng/g ww)-7.91 ng/g ww in the 521 individual samples. HBCD levels were
highest in the fish and shellfish groups (mean of 1.66 ng/g ww and 0.268 ng/g ww, respectively; median
of 0.248 ng/g ww and 0.090 ng/g ww, respectively). Of the fish species, herring, halibut, and chub
15
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
mackerel contained the highest mean HBCD concentrations: 4.91 ng/g ww (range ND (<0.006 ng/g ww)-
7.91 ng/g ww), 2.43 ng/g ww (range 0.762-4.84 ng/g ww), and 1.66 ng/g ww (range 0.405-3.09 ng/g
ww), respectively. Diastereoisomer profiles were provided for the various food groups; alpha-HBCD was
predominant in animal-based foods, and gamma-HBCD was predominant in plant-based foods. The EDI
of total HBCD for the general Korean population and specific subgroups was calculated based on the
HBCD concentration data from this study and food consumption rates from nationwide surveys and
statistics for Korea (KHIDI, 2013 and KNHANES, 2011). The average dietary intake of HBCD was
estimated to be 0.82 ng/kg bw/day in the general population and 2.89 ng/kg bw/day in children up to 5
years of age. Comparison with studies of dietary exposure for other countries showed adult EDI's within
the same order of magnitude for China, Norway, Sweden, the UK, the Netherlands, and Belgium. Using
the European Food Safety Authority (EFSA) method for risk assessment, it was determined that there is
no health concern for the Korean population from the current dietary exposure.
2.4 Surface Water
2.4.1 North America
2.4.1.1 Venier et al. (2014)
Venier et al. (2014) measured background concentrations of HBCD in a large group of organic chemicals,
including flame retardants, in surface water samples collected from 18 stations distributed throughout the
five Great Lakes (Erie, Huron, Michigan, Ontario, and Superior) in 2011 and 2012 using XAD-2 resin
absorption. Surface water samples were collected using the PopCart, a sampling technique customized by
Environment Canada, and were analyzed for the flame retardants including total HBCD using GC-MS
with ECNI. The method detection limit was not reported. Total HBCD was detected in approximately
61% of the samples (14 of 23). Mean concentrations of total HBCD in surface water ranged from
0.00026 ng/L (SD = 0.00025 ng/L) to 0.00208 ng/L (SD = 0.00228 ng/L) for the five Great Lakes (n=23),
with the highest concentrations observed in Lake Ontario.
2.4.2 Europe
2.4.2.1 Harrad et al. (2009)
Harrad et al. (2009) measured background concentrations of HBCD in surface water from nine English
freshwater lakes during spring and autumn 2008 and winter 2009. The nine lakes included: Wake Valley
Pond, Holt Hall Lake, Chapman's Pond, Crag Lough, Marton Mere, Slapton Ley, Fleet Pond, Edgbaston
Pool, and Thoresby Lake. The authors were not aware of any major point source inputs (e.g., wastewater
treatment plants) to any of the nine lakes monitored. At each lake three grab samples were collected from
50 cm below the surface (at the deepest point of each lake) during spring and autumn 2008 and winter
2009. Samples were analyzed for individual isomers (alpha-, beta-, and gamma-HBCD) and total HBCD
using LC-MS/MS detection operating in the electrospray ionization mode (ESI). The limit of detections
(LODs) were not provided. Total HBCD (sum of particulate and dissolved phases) was detected in 100%
of the surface water samples ranging from a minimum average concentration of 0.08 ng/L (SD = 0.0073
ng/L) from Thoresby Lake to a maximum average concentration of 0.270 ng/L (SD = 0.031 ng/L from the
Edgbaston Pool and SD = 0.018 ng/L from Slapton Ley). According to Harrad et al. (2009) the low
standard deviations for the three samples at each site is indicative of no obvious seasonal variability.
16
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
2.4.3 Asia
2.4.3.1 Ichihara et al. (2014)
Ichihara et al. (2014) measured HBCD in surface water samples from 19 sampling locations in the Yodo
River Basin in western Japan during 2012 and 2013. The upper reach of the basin consists of forests,
paddy fields, and city areas whereas the watershed of the lower reach is highly urbanized and
industrialized. Water flow in the study area is dominated by tidal action. Multiple samples were
collected per sampling location at ebb tide and were analyzed by UPLC-MS/MS detection operating in
the negative electrospray ionization mode (NESI) to determine the HBCD stereoisomers (alpha-, beta-,
gamma-, delta-, and epsilon-HBCD) and total HBCD. The method limit of quantification for alpha-,
beta-, gamma-, delta-, and epsilon-HBCD were 10, 10, 10, 20, and 10 pg, respectively. The annual mean
values were reported by sampling location and by river. Across all 19 sampling locations, annual mean
surface water concentrations of total HBCD ranged from 0.19 ng/L (SD = 0.2 ng/L) to 14 ng/L (SD = 12
ng/L). Delta- and epsilon-HBCD were not detected in any of the river samples. Average concentrations
in the Kanzaki River, Yodo River, and Yamato River were 0.91, 0.76, and 6.7 ng/L. The authors also
reported flow rates and estimated pollutant loads. It is noteworthy, that the lowest flow river, the Yamato
River, had the highest HBCD concentration.
2.4.3.2 He et al. (2013)
He et al. (2013) measured background concentrations of HBCD in surface water from a river running
through a highly industrialized area in the Pearl River Delta of South China during 2010. Five surface
water samples were collected from the Dongjiang River catchment with a grabber 50 cm below the
surface of the water and were analyzed for individual isomers (alpha-, beta-, and gamma-HBCD) and
total HBCD using LC-MS/MS detection operating in the NESI. The reported LODs for individual HBCD
isomers were 1.7 pg for alpha-HBCD, 0.5 pg for beta-HBCD, and 1.4 pg for gamma-HBCD. In the
dissolved phase, total HBCD was detected in 100% of the surface water samples (n=5) ranging from
0.0095 ng/L to 0.0825 ng/L ww (mean = 0.0397 ng/L). In the particulate phase, total HBCD ranged from
ND (0.0036 ng) to 0.0113 ng/g dw (mean = 0.008 ng/g dw). According to He et al. (2013) little
information is available for the partition of HBCD between the dissolved and particulate phases. In this
study the average proportion of dissolve phase HBCDs were reported as 27% and may be controlled by
various factors (e.g., suspended particle content, dissolved organic matter content, and particle organic
matter).
2.4.3.3 Oh et al. (2014)
Oh et al. (2014) measured background concentrations of HBCD in surface water from three Japanese
rivers (Tsurumi River, Yodo River, and Kuzuryu River) with different HBCD emission sources during
2011. Tsurumi River flows through the two most highly populated areas in Japan (Tokyo and Kanagawa
prefecture) with seven municipal wastewater treatment plants located in the river basin; it is ranked as one
of the worst in Japan because of the rapid urbanization in the basin. Yodo River flows out of the largest
lake in Japan (Lake Biwa), flows through three prefectures (Shiga, Kyoto, and Osaka), and has the most
tributaries in Japan. The flow of Yodo River consists of mainly of effluents from industries including
expanded polystyrene (EPS) and extruded polystyrene (XPS) production, and household wastewater.
Kuzuryu River flows through Fukui prefecture where many dyeing and textile processing factories are
located. Surface water samples were collected at 17 sampling sites from the 3 rivers (Tsurumi River; n=4
sites, Yodo River; n=6 sites, and Kuzuryu River; n=7 sites) using a grab sampler and were analyzed for
individual isomers (alpha-, beta-, and gamma-HBCD) and total HBCD using HPLC-MS/MS detection
operating in the NESI. The LODs were not provided. Total HBCD was detected in 100% of the surface
water samples ranging from 6.6 ng/L to 57 ng/L (mean = 21.2 ng/L) for the Tsurumi River (n = 4), 2.5
17
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
ng/L to 19 ng/L (mean = 9.3 ng/L) for the Yodo River (n = 6), and 180 ng/L to 2100 ng/L (mean = 642.9
ng/L) for the Kuzuryu River (n = 7). The highest concentrations of total HBCD were observed at the
Kuzuryu River followed by the Yodo and Tsurumi Rivers. According to Oh et al. (2014) the different
emission sources have direct influence on the behavior of HBCDs for each basin.
2.5 Sediment
2.5.1 North America
2.5.1.1 La Guardia et al. (2012)
La Guardia et al. (2012) studied sediment samples collected at a WWTP outfall along the Yadkin River in
North Carolina. The WWTP is owned and operated by a local textile and treats up to 16 million liters per
day (~92% industrial process wastewater and ~8% domestic sewage). Treatment includes bar and fine
screening, aeration, dual clarifiers, aerobic digesters, and sludge drying beds. Sediment was sampled 16.8
km, 25.2 km and 44.6 km downstream of the outfall, at the outfall, and 0.2 km upstream from the WWTP
in July 2009. Samples were collected in precleaned 1 L glass jars with Teflon lids and stored at <4 °C.
For total HBCD (a-, (3- and y-HBCD) samples were analyzed by UPLC-MS/MS. In the outfall sediment,
total HBCD was the most abundant brominated flame retardant at 390,000 ng/g total organic carbon
(TOC). Total HBCD was also detected at every collection site downstream from the outfall, ranging from
88,300 to 12,200 ng/g TOC. However, HBCD was not detected (LOD=l ng/g, dry weight) at the
upstream site. The biota sampled in these same areas had total HBCD concentrations among the highest
reported to date worldwide.
2.5.1.2 Yang et al. (2012)
Yang et al. (2012) studied 16 sediment cores from all five Great Lakes. Most of the sites are in
depositional zones where chemical input is likely to be dominated by atmospheric deposition. Sediment
sampling was conducted from August 1 to 25, 2007 on Lake Superior (4 cores), Lake Michigan (4 cores),
Lake Huron (3 cores), Lake Erie (2 cores), and Lake Ontario (3 cores). A total of 223 segments were
collected from 16 cores. Samples were analyzed by GC-MS ECNI. The detection frequency for total
HBCD was 82% for samples dated 1950 or later. The surface sediment concentration of total HBCD was
in the range of 0.04 to 3.1 ng/g dw. According to the author, this is within the concentration range (<10
ng/g dw) worldwide at locations dominated by diffuse sources, but orders of magnitude lower than those
near point sources. Chronologically, HBCD appeared in the sediment around the mid-1980s, and
increased in nonmonotonic patterns in subsequent years. At most locations, a decrease in input flux was
observed in the top sediment segments. Specifically, concentrations ranged from 0.04 to 1.2 ng/g dw for
Lake Superior (n=4 pooled samples); 0.09 ng/g dw to 1.0 ng/g dw for Lake Michigan (n=4 pooled
samples); 0.27 to 1.4 ng/g dw for Lake Huron (n=3 pooled samples); 0.77 to 1.0 ng/g dw for Lake Erie
(n=2 pooled samples); and 0.84 ng/g to 3.1 ng/g dw for Lake Ontario (n=3 pooled samples).
2.5.2 Australia
2.5.2.1 Drage et al. (2015)
Drage et al. (2015) studied surficial sediment samples and sediment cores from four locations within the
Sydney estuary, Australia. Sediment cores were taken in 1998/99 in shallow-water areas in locations close
to storm water drains which have been previously identified as sources of storm water contaminants (Iron
Cove, Burns Bay, and North Harbor). Each core was subsampled at 2 cm intervals to 10 cm depth, and
thereafter subsampled at intervals of 10 cm. Sediment age was determined using dating techniques and
sedimentation rates (cm/year) were calculated from sediment thickness and age. In May 2014, the
investigators collected four surficial sediment samples, extracted the top 5 cm, and pooled the material.
18
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Samples were analyzed by HPLC-MS/MS. HBCD was detected in low levels in sediments deposited as
early as 1950-1960s, average = 0.59 ng/g dry wt. Large increases in concentrations were observed for
total HBCD between 1980 and 2014. HBCD peaked in sediment representative of 1997 (4.5 ng/g dry wt)
and declined to 2.6 ng/g dry wt in surficial sediment from 2014. After a sharp increase in the 1990s,
HBCD concentrations peaked at an average of 3.5 ng/g dry wt (1.8-5.3 ng/g dry wt) in surficial samples.
These patterns are consistent with commercial use of HBCD in Australia - importation of HBCDs and its
containing products into Australia peaked in 2006-07 (90 tons) but decreased to approximately 60 tons in
2010.
2.6 Soil
2.6.1 Europe
2.6.1.1 Remberger et al. (2004)
Remberger et al. (2004) investigated the possible emission pathways and determined the environmental
occurrence of HBCD in soil collected near a potential point source (XPS producing facility) in Sweden
during 2000. The factory was located southwest of Aspvreten and manufactures flame retarded XPS
plastics treated with HBCD during a period of two weeks per year. Soil samples were collected from the
upper 3 cm of low moraine ridges from three different directions at a distance of 300, 500, and 700 m
from the factory. All samples were analyzed by gas chromatography with electron capture detection
(GC/ECD). The limit of detection was not reported for this media. Concentrations of total HBCD ranged
from 140 ng/g dw (ridge approximately 700 m NW of factory) to 1300 ng/g dw (ridge 300 m S of
factory). According to Remberger et al. (2004) concentrations decreased with increasing distance from
the facility.
2.6.2 Asia
2.6.2.1 Wang et al. (2013)
Wang et al. (2013) investigated the presence and distribution of HBCD in farm soils in the Tongzhou
region in southeast Beijing, China during 2010 and 2011. The region was predominantly mixed semi-
rural and farm lands with increasing urbanization due to the rapid expansion of urban Beijing towards the
outskirts. Surface soil sampling was conducted at three types of sites based on the irrigation source. Soil
samples were collected from farms adjacent to the Liangshui River (7 sites) which receives treated waste
water from WWTPs and effluents from various local industries. Each sample consisted of five
subsamples. Additional samples were collected from farmlands (3 sites) that were further away from the
river and utilized both wastewater and groundwater as an irrigation source. At two sites farmland that
used only groundwater as a source of irrigation were chosen as controls. All samples were analyzed by
HPLC-MS/MS detection operating in the atmospheric pressure chemical ionization (APCI) negative ion
mode. The reported LODs for individual HBCD isomers were 8 pg for alpha-HBCD, 4 pg for beta-
HBCD, and 2 pg for gamma-HBCD. Total HBCD was detected in 100% of the soil samples (n=120)
ranging from 0.17 ng/g dw to 34.5 ng/g dw (median = 2.97 ng/g dw). According to Wang et al. (2013)
there were no significant differences of HBCD levels among the different irrigation sources; however, the
levels of HBCD were significantly higher in samples collected in 2011 than those collected in 2010.
2.6.2.2 Wang et al. (2009)
Wang et al. (2009) reported the presence of HBCD in topsoil in northeastern China during 2006 covering
spatial variation between a range of urban and background locations. Soil samples were collected at 17
sites in and around Harbin City which included urban sites (9), suburban sites (4), rural sites (3), and
background (1 site). At each site five topsoil subsamples were taken to a depth of 20 cm and combined
19
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
into one sample. All samples were analyzed by GC-MS detection operating in the ECNI. The alpha-
HBCD concentrations representing the total HBCD were detected HBCD, because beta-HBCD and
gamma-HBCD residues in the samples were most likely thermally isomerized to alpha-HBCD and/or
degraded in the GC injection port. The reported LOD for total HBCD was 0.340 ng/g. The detection
frequency was not reported. Concentrations of total HBCD in topsoil samples ranged from ND (0.340
ng/g dw to 7.66 ng/g dw (median = 0.534 ng/g dw; mean = 1.750 ng/g dw). The highest concentrations
of HBCD were found at suburban sites (school playground and new residential area). Although suburban
sites, the source of the high levels may be due to emission from polyurethane foam (PUF)-containing
furniture. According to Wang et al. (2009) HBCD was a dominant congener which was consistent with
its high production volume in China. HBCD was not detected in background soils indicating urban areas
as the source.
2.6.2.3 Li et al. (2016)
Li et al. (2016) investigated the levels, spatial distributions, and mass inventories of HBCD in paddy soils
from the Liaohe River Basin in northeast China during 2010. Paddy soil samples were collected at 17
sampling sites using a stainless-steel scooper. All samples were analyzed by HPLC-MS/MS detection
operating in the electrospray negative ionization mode. The reported LOQs for individual HBCD isomers
were 0.07, 0.03, and 0.08 ng/g dw for alpha-HBCD, beta-HBCD, and gamma-HBCD, respectively.
Concentrations of total HBCD ranged from ND (<0.08 ng/g dw) to 3.40 ng/g dw. According to Li et al.
(2016) the spatial distributions of HBCD in paddy soils indicate that the local point-input was the major
source. In addition, it was found that irrigation with river water was not the major transportation pathway
of HBCD in paddy soils.
2.7 Ambient Air
2.7.1 North America
2.7.1.1 Hoh and Hites (2005)
Hoh and Hites (2005) studied spatial trends of total HBCD in outdoor air through the analysis of samples
collected at five US sites for two years (2002 to 2003). The sites included an urban site in Chicago,
Illinois, a semi-urban site in Indiana, an agricultural site in Arkansas, and remote sites in Michigan and
Louisiana. Air samples were collected for 24-hours every 12 days. Gas- and particle-phase samples were
collected using high-volume samplers fitted with either XAD-2 resin and a quartz fiber filter (Chicago
site only) or with a PUF adsorbent and glass fiber filter (other four sites). All samples were analyzed
using GC-MS operated in the ECNI mode. Total HBCD was detected in approximately 76% of the
samples (120 of 156), in only in the particle phase. Total HBCD concentrations in outdoor air ranged
from ND (<0.00007 ng/m3) to 0.011 ng/m3 (mean = 0.0012 ng/m3; median = 0.0005 ng/m3) at the
remote Michigan site, from ND (<0.00013 ng/m3) to 0.0096 ng/m3 (mean = 0.0045 ng/m3; median =
0.0042 ng/m3) at the urban Chicago site, from ND (<0.00007 ng/m3) to 0.0036 ng/m3 (mean = 0.001
ng/m3; median = 0.00075 ng/m3) at the semi-urban Indiana site, from ND (<0.00013 ng/m3) to 0.011
ng/m3 (mean = 0.0016 ng/m3; median = 0.0004 ng/m3) at the agricultural Arkansas site, and from ND
(<0.00013 ng/m3) to 0.0062 ng/m3 (mean = 0.0006 ng/m3; median = ND) at the remote Louisiana site.
The highest mean and median values were from the Chicago site, suggesting that urban areas are the
source of this compound. The highest individual concentration of total HBCD occurred at the Arkansas
site, which could be attributed to manufacturing areas in southern Arkansas, as investigated using four-
day backward air trajectories. The percent HBCD isomer composition of seven samples was variable.
20
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
2.7.1.2 Shoeib et al. (2014)
Shoeib et al. (2014) measured flame retardants in air samples collected from a semi-urban location
(Environment Canada field site) located in Toronto, Canada, between 2010 and 2011. A total of 70
outdoor air samples (gas and particle phases) were collected using PS-1 type sampler and the sampling
train consisted of a glass-fiber filter for collecting the particulate phase. Air samples were collected over a
24-hour sampling period and were analyzed for total HBCD using GC-MS using negative ion chemical
ionization mode. Total HBCD was detected only in the particulate phase in 67% of the samples (n = 70)
with concentrations that ranged ND (<0.00144 ng/m3) to 0.00469 ng/m3 (mean = 0.00139 ng/m3; median
= 0.00097 ng/m3). According to Shoeib et al. (2014) these results were similar to mean observed in the
east-central United States in 2002-2003 (Hoh and Hites, 2005).
2.7.2 Asia
2.7.2.1 Li et al. (2016)
Li et al. (2016) studied the occurrence and temporal trends of total HBCD in outdoor air for six
consecutive years (2008 to 2013) through the analysis of samples collected in a typical urban atmosphere,
Harbin, the capital city of Hcilongjiang Province in the Northeastern China. During the multi-year
sampling period construction of a subway system was ongoing. Air samples were collected nearly every
week using high-volume air samplers with PUF applied to collect gas-phase samples and glass fiber
filters (GFFs) applied to collect particle-phase samples. A total of 222 pair of gas-phase and particle-
phase samples were collected. All samples were analyzed using GC-MS operated in the ECNI mode.
The method detection limits ranged from 0.0027 to 0.0056 ng/m3. Total HBCD was detected in
approximately 94% of the samples, in the gas-phase plus particle phase. Total HBCD concentrations in
outdoor air ranged from ND to 3.4 ng/m3 (mean = 0.36 ng/m3; SD = 0.630 ng/m3; median = 0.088
ng/m3). The doubling times for HBCD increased rapidly in gas-phase (1.5 ± 0.63 years) and particle-
phase (0.89 ± 0.05 years). According to Li et al. (2016) this increasing trend might be attributed to the
increasing local usage of HBCD since the phase out of commercial PBDEs and/or because of long range
atmospheric transport. Another explanation for the rapid increasing trend was the construction of the
subway system which coincided with the sampling period. During the construction of the subway system
thermal insulation building materials and electronics containing HBCDs may have been used.
2.8 Indoor Dust
2.8.1 North America
2.8.1.1 Stapleton et al. (2014)
Stapleton et al. (2014) measured flame retardants in hand wipe and house dust samples collected from 30
homes located in North Carolina during the spring of 2012. Dust samples were collected on both
hardwood and carpeted floors by using a vacuum cleaner with a cellulose thimble inserted in the hose
attachment. Samples were analyzed for flame retardants using GC-MS. Total HBCD was detected in all
samples (n = 30), with concentrations ranging from 77.6 to 2,658 j^ig/kg (geometric mean = 338 jj.g/kg).
The results for hand wipes are provided in the Hand Wipe section in this Appendix.
2.8.1.2 Allgood et al. (2016)
Allgood et al. (2016) measured flame retardants in dust samples collected from elevated surfaces and
floors at various locations on the campus of the University of California, Irvine during 2013. The
microenvironments sampled included a bus, scientific laboratory, computer laboratory, gymnasium, and
two each of domestic apartments, classrooms, and offices. The dust samples were collected by vacuum
21
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
cleaner using a crevice tool equipped with a cellulose thimble from elevated surfaces (i.e., sofas, book
cases, desks, tables, chairs, and counter tops which were approximately 2 feet or higher from the floor)
and strictly the floor. All samples were analyzed by ultra-performance liquid chromatography with
tandem mass spectrometry detection using atmospheric pressure photoionization (UPLC-APPI-MS/MS).
The reported detection limit was 1 ng/g. Total HBCD was detected in 100% of the elevated surface dust
samples (n=10) and floor dust samples (n=10). Total HBCD concentrations ranged from 89 ng/g dw to
799 ng/g dw (median = 393 ng/g dw) in elevated surface dust and from 104 ng/g dw to 636 ng/g dw
(median = 326 ng/g dw) in floor dust. Allgood et al. (2016) compared median concentrations of total
HBCD in elevated surface dust and floor dust and reported a median ratio of 1.02 indicating similar
elevated surface and floor dust concentrations. These findings were a notable exception to other flame
retardant chemicals where median elevated surface dust concentrations were higher than floor dust
concentrations. The authors indicated that these results should be interpreted cautiously because of the
small sample size.
2.8.2 Europe
2.8.2.1 D'Hollander et al. (2010)
D'Hollander et al. (2010) measured flame retardants in dust samples collected from 43 homes (living
room, bedroom, kitchen, and work area) and ten offices in Flanders, Belgium during 2008. The dust
samples were collected from the bare floor or carpet by vacuum cleaner using a nylon sock mounted in
the furniture attachment of the vacuum. All samples were analyzed by LC-MS/MS in the electrospray
negative ionization mode. The reported LOQ was 5 ng/g for individual HBCD isomers. Total HBCD
was detected in 100% of the house dust samples (n=43) and office dust samples (n=10). Total HBCD
concentrations ranged from 5 ng/g dw to 42,692 ng/g dw (median = 130 ng/g dw; mean = 1,735 ng/g dw)
in house dust and from 256 ng/g dw to 1153 ng/g dw (median = 367 ng/g dw; mean = 592 ng/g dw) in
office dust. The 95th percentile HBCD concentration was reported as 4,447 ng/g dw in house dust and
1,092 ng/g dw in office dust. The HBCD pattern in both house and office dust is characterized by alpha-
HBCD as the major isomer (59-72%), followed by gamma-HBCD (15-29%) and beta-HBCD (12-13%).
2.8.2.2 Sahlstrom et al. (2015)
Sahlstrom et al. (2015) measured flame retardants in dust samples collected from Swedish homes of first-
time mothers that had participated in the Persistent Organic Pollutants in Uppsala Primiparas (POPUP)
study during 2009-2010. The mothers were re-contacted when their children were about 11 months old
and asked to participate in a follow-up study. House dust samples were collected on surfaces at least 1
meter above the floor in the living room, bedroom, kitchen, and/or hallway by vacuum cleaner using
cellulose filters in styrene-aerylonitrile holders installed in the nozzle. All samples were analyzed by
UPLC-MS/MS to determine the three major HBCD stereoisomers (alpha-, beta-, and gamma-HBCD).
The method detection and quantification limit for HBCD were not reported. The individual HBCD
isomers (alpha-, beta-, and gamma-HBCD) were each detected in 100% of the house dust samples (n=27).
Total HBCD concentrations ranged from 20 ng/g dw to 6,000 ng/g dw (median =110 ng/g dw; geometric
mean =161 ng/g dw) in house dust.
2.8.3 Asia
2.8.3.1 Qi et al. (2014)
Qi et al. (2014) measured flame retardants in 81 indoor dust samples collected from 45 residential homes
(combination of living rooms, bedrooms, and kitchens) and 36 public places (libraries, offices,
classrooms, supermarkets, and laboratories) in 23 provinces across China during the winter of 2010.
Sample locations were considered urban (n=55) or rural (n=26). The dust samples were collected by
22
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
sweeping the floor with pre-cleaned brushes under desks, shelves, and beds, avoiding the influences of
resident activities and sunlight. All samples were analyzed using GC-MS operated in the ECNI mode.
The reported method detection limit was 2.7 ng/g. Total HBCD was detected in 98.8% of the indoor dust
samples (n=81). Total HBCD concentrations ranged from ND (2.7 ng/g dw) to 6,100 ng/g dw (median =
120 ng/g dw; mean = 410 ng/g dw; SD = 830 ng/g dw) in indoor dust. The 5th and 95th percentile HBCD
concentrations were reported as 9.6 ng/g dw and 1,600 ng/g dw, respectively. The three highest
concentrations were found in an office in Beijing (6,100 ng/g dw), a warehouse in Jilin (3100 ng/g dw),
and a school office in Harbin (2,100 ng/g dw). According to Qi et al. (2014) a relatively higher
concentration of HBCD was found in public indoor dust samples than in residential indoor dust samples
(p <0.05). In addition, Qi et al. (2014) estimated the indoor dust ingestion dose, dermal absorption dose,
and total daily exposure dose of total HBCD in indoor dust in China for five age groups (infants, toddlers,
children, teenagers, and adults).
2.9 Indoor Air
2.9.1 Europe
2.9.1.1 Abdallah etal. (2008)
Abdallah et al. (2008) measured HBCD diastereoisomer and total HBCD concentrations in indoor air
from homes, offices, and public microenvironments in Birmingham U.K from February 2007 to
December 2007. Passive air samplers (i.e., PUF disks) were employed to provide a time-integrated
sample over a 30 day sampling period. Samples were analyzed for HBCD isomers using LC-MS/MS and
summed to provide total HBCD. Quality control measures taken included replicate analysis, field blanks,
and procedural blanks. Total HBCD concentrations in indoor air ranged from 0.067 ng/m3 to 1.30 ng/m3
(mean = 0.250 ng/m3; st dev.=0.240 ng/m3, median = 0.180 ng/m3) for homes (n=33; taken from living
rooms), 0.070 ng/m3 to 0.460 ng/m3 (mean = 0.180 ng/m3; st dev.=0.090 ng/m3, median = 0.170 ng/m3)
for offices (n=25), and 0.820 ng/m3 to 0.960 ng/m3 (mean = 0.900 ng/m3; st dev.=0.060 ng/m3, median
= 0.900 ng/m3) for public microenvironments (n=4; three pubs and one restaurant). Estimated human
exposure to HBCDs via air inhalation based on concentrations reported in this study are based on the
assumption that inhalation occurs pro-rata to typical activity patterns, i.e., for adults 63.8% home, 22.3%
office, and 5.1% public microenvironments; fortoddlers (6-24 months) 86.1% home and 5.1% public
microenvironments. In the absence of data, 100% absorption of intake of HBCDs was assumed. For adult
intake from air: 5th percentile=2.3 ng/day; average=5.0 ng/day; median=3.9 ng/day; 95th percentile=10.4
ng/day. For toddler intake from air: 5th percentile=0.5 ng/day; average=1.0 ng/day; median=0.8 ng/day;
95th percentile=2.1 ng/day.
2.9.2 Asia
2.9.2.1 Hong et al. (2016)
Hong et al. (2016) measured HBCD diastereoisomer and total HBCD concentrations in indoor and
outdoor air samples collected from different locations within two industrialized cities (Guangzhou and
Foshan) in Southern China. According to Hong et al. (2016), the HBCD production capacity in China
was 7500 tonnes in 2007. A total of 37 indoor air samples (gas and particle phases) were collected from
homes (n=12), offices (n=5), and other workplaces (n=10) between October 2004 and April 2005. Gas-
phase samples were collected using a high-volume sampler and particle-phase samples were collected
using PUF plugs. Indoor air samplers were placed at floor level. HBCD diastereoisomer determination
was made using LC-MS/MS in electrospray ionization negative ion mode with multiple reaction
monitoring. Quality control measures taken included duplicate sample collection, field blanks, procedural
23
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
blanks, and recovery experiments at multiple concentration levels. The gas- and particle-phase
concentrations for alpha-, beta-, and gamma-HBCD and total HBCD in indoor air were calculated using a
six-point calibration standard curve. Total HBCD mean concentrations (including gas- and particle-phase)
were 0.00543 ng/m3 (0.00089-0.00847 ng/m3) and 0.00821 ng/m3 (0.00405-0.0160 ng/m3) for homes
and offices, respectively. The total HBCD mean concentration for other workplaces (workplace type not
specified) was significantly higher at 0.0482 ng/m3 (0.010-0.125 ng/m3). According to Hong et al.
(2016), these total HBCD mean concentrations were slightly higher than or comparable with levels
reported in remote or urban sites within the United States and are significantly lower than those reported
in the European atmosphere. Further examination of the diastereoisomer profiles indicated that alpha-
HBCD was the dominant isomer with a relative abundance ranging from 56.3% to 83.0% (mean value
73.6%) and that airborne HBCDs were predominantly present in the particulate phase. The study noted
that the variation in HBCD distribution in the gas and particulate phases was greater in indoor air samples
than outdoor samples. The study concluded with estimating average daily human exposure to HBCDs via
inhalation of indoor and outdoor air using the measured indoor and outdoor total HBCD concentrations
from this study.
2.10 Human Milk
2.10.1 North America
2.10.1.1 Carignan et al. (2012)
Carignan et al. (2012) studied the levels of HBCD in human milk samples collected 43 first-time mothers,
18 years or older, who had lived in the Greater Boston, Massachusetts area for at least 3 years at the time
of delivery. Each participant provided a single human milk sample 2 to 8 weeks postpartum between
April 2004 and January 2005. Most of the women used an electric or manual milk pump to collect the
sample. Once the samples were collected, they were stored at -20 °C until they were shipped to the
University of Birmingham in 2010 and subsequently analyzed by liquid chromatography-electrospray
ionization-tandem mass spectrometry (LC-ESI-MS/MS) for HBCDs (the a, (3, and y diastereomers).
Concentrations detected in milk were lipid-adjusted and IHBCD was calculated as the sum of a-, (3-, and
y-HBCD. Levels of ZHBCDs ranged from 0.360 to 8.10 j^ig/kg lw (geometric mean = 1.02 j^ig/kg lw)
where a-HBCD was the dominant diastereomer. The participants filled out a questionnaire that was used
to identify possible predictors of exposure to HBCD. The number of stereo and video electronics (e.g.,
TVs, CD player, DVD player, stereos, etc.) in the home was positively associated with body burdens of
IHBCDs. The HBCDs levels detected in the milk of first-time mothers in this study were comparable to
those measured in several other countries. The results suggest that the estimated body burdens are related
to lifestyle factors, potentially including diet and domestic electronics.
2.10.2 Europe
2.10.2.1 Tao et al. (2017)
Tao et al. (2017) studied the levels of HBCD in human milk samples collected from two groups of
women. The first group of samples (n=25) were collected in 2010 and later obtained from an archived
milk bank at Birmingham Women's Hospital. The milk came from primiparous mothers during their first
three months of lactation. The second group of samples (n = 10) were collected between August 2014 and
May 2015 from mothers during their first three months of lactation and living in Southhampton, UK. The
second group of mothers were participating in the Breast milk, Environment, Early-life, and Development
(BEED) study. Each sample from both groups comprised of approximately 50 mL of milk, was freeze
dried, and remained in frozen storage (-20oC) until prepped for analysis by GC-MS operated in ECNI
24
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
mode. Measured concentrations of IHBCD in human milk ranged from 1.04 to 22.4 jj.g/kg lw (mean =
5.95 (ig/kg lw, median = 3.83 j^ig/kg lw) and 0.69 to 7.1 jj.g/kg lw (mean = 3.2 j^ig/kg lw; median = 2.9
(ig/kg lw) for groups 1 and 2, respectively. The study authors indicated that levels of HBCD found in the
human milk samples exhibited a similar downward trend to UK indoor air and dust samples collected
between 2006 and 2007 (similar period for group 1) and samples collected between 2013 and 2015
(similar period for group 2). The authors estimated the dietary intake for a 1 month old infant using the
group 2 milk samples and compared those results to the previously reported dietary intake of nursing
infants from the first group. The comparison resulted in no substantial differences between the two intake
values.
2.10.2.2 Antignac et al. (2016)
Antignac et al. (2016) studied the presence of a number of persistent organic pollutants (POPs) in human
milk collected from French (n= 96), Danish (n= 438), and Finnish women (n= 22). The French women
participating in a study from 2011 to 2014, provided milk samples collected between 1 and 2 months
postnatally. The Danish and Finnish women participating in two separate cohort studies from 1997 and
2002, provided milk samples collected 1 to 3 months postnatally. The Danish and Finnish milk samples
were collected as several small aliquots. All of the samples were stored frozen at -20 C until analyzed
for HBCD isomers by LC-MS/MS. French women were found to have higher levels (approximately 2-
fold) of a-HBCD (from 0.22 to 4.21 |ag/kg lw; median = 0.56 j^ig/kg lw) compared to Danish women
(from 0.02 to 28.7 j^ig/kg lw; median = 0.31 jj.g/kg lw) or Finnish women (from 0.03 to 2.19; median =
0.31 (ig/kg lw). Although the women had a similar age at the time of sampling, due to differing sampling
periods, on average, the French women were born approximately 10 years later than the other women.
2.11 Human Serum
2.11.1 Europe
2.11.1.1 Kalantzi et al. (2011)
Kalantzi et al. (2011) investigated the levels of HBCD in human serum of 61 individuals (27 females and
34 males, 20-65 years old) residing in the Attika region of Greece between June and October 2007.
Serum samples were collected from full-time computer clerks of a large computer company (n=30) and
from a separate population (n=31) with no computer use. All samples were analyzed using GC-MS
operated in the ECNI mode. The reported limit of quantification was 1.0 ng/g lw. Quality control
measures taken included duplicate sample collection, field blanks, procedural blanks, and recovery
experiments at multiple concentration levels. HBCD was detected in 70% of the samples (43 of 61).
HBCD concentrations in human serum ranged from 0.49 j^ig/kg lw to 38.8 ng/g lw (mean = 3.39 jj.g/kg
lw; median = 1.32 jj.g/kg lw; SD=6.85 jj.g/kg lw). There was a significant difference between males and
females with regards to HBCD (p=0.044) but females from both groups had lower HBCD concentrations
than males (median of 0.71 jj.g/kg lw, compared to 1.44 j^ig/kg lw for males).
3 Overview of Human Biomonitoring
EPA/OPPT summarized data from human biomonitoring in various matrices. HBCD has been reported in
many matrices in many countries overtime.
25
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3.1 Blood
3.1.1 Blood ng/g chart
Genera!
High exposed population
US - Butt et al. 2016
AU - Drage et al. 2017
BE - Roosens et al. 2009
CA - Rawn et al. 2014
DE - Fromme et al. 2016
MX - Lopez 2004
NL-Weiss 2017
NL - Meijer et al. 2008
SE - Bjermo et al. 2017
SE - Darnerud et al. 2015
NO - Thomsen et al. 2008
SE - Weiss et al. 2006
o
>
o
o
o
o
o
o
10 100
Concentration (ng/g)
3.1.2 Blood (ng/g) Summary Statistics
HERO
ID
Central
Central
Study Name
Min
Max
Tendency
(low)
Tendency
(high)
3350486
{Butt, 2016, 3350486}
0.042
3
3545935
{Drage, 2017,3545935}
0.05
36
0.88
3.1
787720
{Roosens, 2009, 787720}
0.25
11.3
1.7
2.9
2238553
{Rawn, 2014, 2238553}
0.33
8.9
0.85
1
3127742
{Fromme, 2016, 3127742}
8
15
3986475
{Lopez, 2004, 3986475}
0.7
2.5
1.2
1.2
3969313
{Weiss, 2017,3969313}
0.08
6.9
0.32
2.4
787696
{Meijer, 2008, 787696}
0.0004
7.4
0.2
0.7
3545919
{Bjermo, 2017, 3545919}
0.0085
77
0.1
0.1
2936564
{Darnerud, 2015,2936564}
0.265
0.78
0.28
0.28
1927761
{Thomsen, 2008, 1927761}
0.0024
52
2.6
9.6
787751
{Weiss, 2006, 787751}
0.12
3.4
0.46
0.46
3.1.3 Human Blood (ng/g): Supporting Data
26
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoDDL (ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Butt, 2016,
3350486}
US
General
2008 -
2010
43
0.07
0.084
1.9
Medium
{Drage, 2017,
3545935}
AU
General
2002-
2015
63
0.73
N/R
1.4
High
{Roosens, 2009,
787720}
BE
General
2007
9
0.56
0.5
1.4
High
{Rawn, 2014,
2238553}
CA
General
2007-
2009
57
1
0.004
1.3
High
{Fromme, 2016,
3127742}
DE
General
2013
42
0.09
16
1.8
Medium
{Lopez, 2004,
3986475}
MX
General
2003
5
N/R
N/R
2.1
Medium
{Weiss, 2017,
3969313}
NL
General
2004
90
N/R
0.16
1.6
High
{Meijer, 2008,
787696}
NL
General
2001 -
2002
81
0.89
0.0016
1.8
Medium
{Bjermo, 2017,
3545919}
SE
General
2010-
2011
170
0.61
0.5
1.6
High
{Darnerud, 2015,
2936564}
SE
General
1996-
2010
36
0.11
0.48
1.8
Medium
{Thomsen, 2008,
1927761}
NO
High exposed
population
2004-
2005
49
0.75
0.0048
1.5
High
{Weiss, 2006,
787751}
SE
High exposed
population
2000
50
N/R
0.24
1.4
High
Rawn et al. (2014b) used surplus blood serum samples orisinallv coll
iected as part of the Canadian Health
Measures Survey (CHMS) to prepare composite pooled serum samples to increase the number of samples
with detectable levels of a number of classes of POPs, including flame retardants. Approximately 5,000
individual serum samples collected between 2007 and 2009 were used to form 59 composite pooled
samples. The pooled samples were categorized by sex and five age groups ranging from 6 to 79 years.
Overall, total HBCD concentrations ranged 0.33-8.9 j^ig/kg lw (mean =1.0 (ig/kg lw; geometric mean =
0.85 (ig/kg lw). Study authors reported that there were no differences in total HBCD concentration
associated with age or sex.
27
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3.2 Breast Milk
3.2.1 Breast milk Chart
US - Carignan ct al. 2012
AU - Toms et al. 2012
BE - Colles et al. 2008
BE - Roosens et al. 2010
CA - Ryan et al. 2006
CA; US - Ryan and Rawn 2014
CH - Gerecke et al. 2008
CN - Shi et al. 2013
CN-Shi et al. 2017
CN - Shi et al. 2009
ES - Eljarrat ct al. 2009
FR - Antignac ct al. 2008
GB - Tao et al. 2017
GB - Abdallah and Harrad 2011
GH - Asantc ct al. 2011
IN - Devanathan ct al. 2012
JP - Kakimoto ct al. 2008
MX; SE - Lopez 2004
NO - EggesbA. et al. 2011
NO - Thomscn ct al. 2010
NO - Thomsen et al. 2003
NO - Polder ct al. 2008
PH - Malarvannan et al. 2013
PH - Malarvannan ct al. 2009
RU - Polder et al. 2008
SE - Darnernd et al. 2015
SE - BjA^rklund et al. 2012
SE - Glynn et al. 2011
SE - Ligncll et al. 2003
TZ-MA'/nier ct al. 2016
0.001
VN-Tuc et al. 2010
ZA - Darnerud et al. 2011
IN - Devanathan ct al. 2012
PH - Malarvannan et al. 2009
VN-Tueetal. 2010
VN-Tue et al. 2010
0.001
0.01
0.1
10
100
1000
Concentration ( ng/g ) (pt l)
g General
I High exposed population
I Occupational
1
Concentration (ng/g ) (pt 2)
28
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3.2.2 Breast Milk Summary Statistics
Central
Central
HERO ID
Study Name
Min
Max
Tendency
(low)
Tendency
(high)
1927577
{Carignan, 2012, 1927577}
0.36
8.1
1.02
1.02
1927589
{Toms, 2012, 1927589}
1.9
19
10.2
10.2
1061439
{Colles, 2008, 1061439}
1.5
1.5
1927679
{Roosens, 2010, 1927679}
1.05
5.7
3445832
{Ryan, 2006, 3445832}
0.4
19
1.6
3.8
2343679
{Ryan, 2014, 2343679}
0.05
28.2
0.2
2.4
1927965
{Gerecke, 2008, 1927965}
0.026
2.3
1927559
{Shi, 2013, 1927559}
1.52
78.28
2.4
4.29
3828886
{Shi, 2017, 3828886}
6.83
10.1
1927708
{Shi, 2009, 1927708}
0.857
2.776
0.857
1.209
1927715
{Eljarrat, 2009, 1927715}
0.6
188
27
47
787643
{Antignac, 2008, 787643}
2.5
5
3862906
{Tao, 2017, 3862906}
0.69
22.37
2.9
5.95
787631
{Abdallah, 2011, 787631}
1.04
22.37
3.83
5.95
1927640
{Asante, 2011, 1927640}
0.005
18
0.27
2.3
1927618
{Devanathan, 2012,
1927618}
0.025
3.6
0.025
0.38
787682
{Kakimoto, 2008, 787682}
0.2
4
3986475
{Lopez, 2004, 3986475}
0.3
5.4
1.1
2.1
787656
{EggesbA/A,, 2011,
787656}
0.1
31
0.54
1.1
1927695
{Thomsen, 2010, 1927695}
0.1
31
0.86
1.7
3809230
{Thomsen, 2003, 3809230}
0.1
31
0.86
1.7
786310
{Polder, 2008, 786310}
0.13
0.13
1927568
{Malarvannan, 2013,
1927568}
0.005
0.91
0.19
0.21
116881
{Malarvannan, 2009,
116881}
0.15
3.2
0.31
1
1061432
{Polder, 2008, 1061432}
0.2
1.67
0.45
0.71
2936564
{Darnerud, 2015,2936564}
0.07
1
0.22
0.22
1927616
{BjA/AHrklund, 2012,
1927616}
0.32
1.5
1061450
{Glynn, 2011, 1061450}
0.09
10
0.3
0.4
3809248
{Lignell, 2003, 3809248}
0.185
1.5
0.35
0.42
3350490
{M A/A'/tiler, 2016,
3350490}
0.0485
28.1
1927687
{Tue, 2010, 1927687}
0.07
1.4
0.33
0.33
787654
{Darnerud, 2011,787654}
0.115
1.4
0.34
0.55
1927618
{Devanathan, 2012,
1927618}
0.0025
13
0.61
2.2
29
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
116881
{Malarvannan, 2009,
116881)
0.13
2
0.52
0.98
1927687
{Tue, 2010, 1927687}
0.11
3.3
0.36
0.42
1927687
{Tue, 2010, 1927687}
1.4
7.6
2
2
3.2.3 Breast Milk: Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Carignan, 2012,
1927577}
US
General
2004-
2005
43
1
0.036
1.2
High
{Toms, 2012,
1927589}
AU
General
1993 -
2009
13
0.69
3.8
1.8
Medium
{Colles, 2008,
1061439}
BE
General
2008
1
1
N/R
2.6
Low
{Roosens, 2010,
1927679}
BE
General
2006
22
0.27
2.1
1.8
Medium
{Ryan, 2006,
3445832}
CA
General
2002-
2003
8
N/R
N/R
2.1
Medium
{Ryan, 2014,
2343679}
CA; US
General
1989 -
2005
109
0.78
0.1
1.8
Medium
{Gerecke, 2008,
1927965}
CH
General
2003 -
2007
36
N/R
N/R
1.8
Medium
{Shi, 2013,
1927559}
CN
General
2011
103
N/R
N/R
1.6
High
{Shi, 2017,
3828886}
CN
General
2011
29
1
0.01
1.8
Medium
{Shi, 2009,
1927708}
CN
General
2007
24
0.92
N/R
1.6
High
{Eljarrat, 2009,
1927715}
ES
General
2006-
2007
33
0.91
3.8
1.3
High
{Antignac, 2008,
787643}
FR
General
2004-
2005
23
0.3
N/R
1.6
High
30
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Tao, 2017,
3862906}
GB
General
2010-
2015
35
N/R
N/R
1.1
High
{Abdallah, 2011,
787631}
GB
General
2010
34
1
N/R
1.6
High
{Asante, 2011,
1927640}
GH
General
2004-
2009
67
N/R
0.01
1.8
Medium
{Devanathan,
2012, 1927618}
IN
General
2009
17
N/R
0.05
1.9
Medium
{Kakimoto, 2008,
787682}
JP
General
1973 -
2006
18
0.83
0.4
1.3
High
{Lopez, 2004,
3986475}
MX; SE
General
2003
12
N/R
N/R
2.1
Medium
{EggesbA/A„
2011,787656}
NO
General
2003 -
2006
193
0.68
N/R
2.0
Medium
{Thomsen, 2010,
1927695}
NO
General
2003 -
2005
310
0.57
0.2
1.4
High
{Thomsen, 2003,
3809230}
NO
General
2003 -
2005
310
0.57
0.2
1.9
Medium
{Polder, 2008,
786310}
NO
General
2000-
2002
10
0.1
0.05
1.7
Medium
{Malarvannan,
2013, 1927568}
PH
General
2008
30
N/R
0.01
1.8
Medium
{Malarvannan,
2009,116881}
PH
General
2004
11
1
N/R
1.3
High
{Polder, 2008,
1061432}
RU
General
2000
37
0.3
N/R
1.8
Medium
{Darnerud, 2015,
2936564}
SE
General
2010
30
0.97
N/R
1.8
Medium
{BjA/AHrklund,
2012, 1927616}
SE
General
2008 -
2009
18
0.17
N/R
1.9
Medium
31
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Glynn, 2011,
1061450}
SE
General
2000-
2004
295
0.77
N/R
1.7
Medium
{Lignell, 2003,
3809248}
SE
General
2002-
2003
30
0.8
0.37
2.1
Medium
{MA/A%ller,
2016,3350490}
TZ
General
2012
1
0.4
N/R
1.9
Medium
{Tue, 2010,
1927687}
VN
General
2007
9
N/R
N/R
1.8
Medium
{Darnerud, 2011,
787654}
ZA
General
2004
14
0.93
0.006
1.6
High
{Devanathan,
2012, 1927618}
IN
High exposed
population
2009
8
1
0.05
1.9
Medium
{Malarvannan,
2009,116881}
PH
High exposed
population
2004
22
1
N/R
1.3
High
{Tue, 2010,
1927687}
VN
High exposed
population
2007
24
N/R
N/R
1.8
Medium
{Tue, 2010,
1927687}
VN
Occupational
2007
9
N/R
N/R
1.8
Medium
3.2.4 North America
As reported in NICNAS (2012) and EC (2008). Lopez et al. (2004) measured HBCD in human
milk samples from seven indigenous women in Mexico (date of sampling not specified). Total
HBCD concentrations ranged from 0.8 to 5.4 pg/kg lw (mean = 2.1 pg/kg lw).
HBCD was measured in human milk samples collected 2004-2005 from 43 first-time mothers in
the Greater Boston, Massachusetts area (Carignan et al.. 2012). The participants were 18 years of
age or older, lived in the Greater Boston area for at least 3 years, spoke Spanish or English, and
had pregnancies that were healthy and singlet. One sample was collected from each participant 2-
8 weeks postpartum. Samples were analyzed for HBCD using HPLC-MS/MS with ESI in the
negative mode. In human milk, total HBCD was detected in all analyzed samples in concentrations
ranging from 0.360 to 8.10 pg/kg lw (geometric mean = 1.02 pg/kg lw).
32
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Ryan and Raw measured flame retardants in human milk samples collected from
individuals residing in various regions across Canada, between 1992 and 2005. In addition,
comparative milk samples were collected in the United States from residents of Austin, TX in 2002
and 2004. The U.S. samples were collected in 2002 (n = 10) and 2004 (n = 25) from the mother's
milk bank at Austin, TX. The milk samples (n = 18) from Ontario, obtained in 2002 as well as
samples in 2005 (n = 34), all originated from the hospital clinic at McMaster University, Hamilton,
Ontario. Samples were analyzed for the flame retardants using either isotope dilution GC-MS or
LC-MS/MS with ESI in the negative mode. Total HBCD ranged from ND to 2.2 |ig/kg lw in 2002
and 2004 samples (n = 35) from the United States and from ND to 28.2 |ig/kg lw in 2002 and 2005
samples (n = 52) from Canada.
3.2.5 Europe
The Australian risk assessment (NICNAS. 2012) provided a relatively comprehensive compilation
of HBCD concentrations in human milk samples collected in Europe, as reported from fourteen
studies ("Eggesbo et at. 11. ; -jilvnn eta'L 201.1; Abdallah and Harrad. 201.0; Thomsen et at. <1. < >;
Eliarrat et. at. 2009; Pokier et. at. 2008b; Polder et at. 2008.n; ». ¦ •lies ei .II <*•?; II igstrom et at.
2008; Lignell et at. 20'>1 ; II ¦ -pez et at. 2004; Lignell et at. 20^ •; I llionrisen et at. 2003; Anne et
at. 2001). The studies encompass six countries (Belgium, Norway, Russia, Spain, Sweden, and
the United Kingdom) with sampling dates ranging from 1980 to 2009. Some of these studies are
also summarized in the other international risk assessments. One of the European studies
Fangstrom et at (2008). examined HBCD concentrations over time in human milk pooled from
15-116 Swedish subjects. The results show mean concentrations of total HBCD ranging from
0.084 |ig/kg lw in 1980 to 0.39 |ig/kg lw in 2004. The peak HBCD concentration of 0.60 |ig/kg lw
was observed in 2002. The study generally shows that HBCD levels have increased since HBCD
began to be widely used as a brominated flame retardant in the 1980s. The highest concentrations
were observed in the study by Eliarrat et at (2009). in which HBCD was measured in milk samples
collected from women in Spain (Catalonia) in 2006 to 2007 (ND to 188 |ig/kg lw, mean = 47 |ig/kg
lw; median = 27 |ig/kg lw). High concentrations were also observed in the United Kingdom from
the Abdallah and Hani study (1.04 to 22.37 |ig/kg lw; mean = 5.95 |ig/kg lw; median =
3.83 |ig/kg lw). ' Ik 1 ¦ ¦ ""I "i selected the 75th percentile (6.9 |ig/kg lw) and 95th percentile
(16.0 |ig/kg lw) from the Abdallah ami " i .u.m ¦ <",.1, data to represent typical and worst-case
values, respectively. In Russia (Polder et at. 2008b). HBCD was detected in human milk samples
collected in 2000 and 2002 from 37 subjects at 0.20 to 1.67 |ig/g (means = 0.47-0.71 |ig/g; medians
= 0.45-0.62 |ig/g). For the remaining studies, HBCD concentrations in human milk collected since
the year 2000 ranged from ND to 31 |ig/kg lw (means/medians = ND-1.5 |ig/kg lw).
Additionally, Law i <. <>, lb reported the results of the Roosens et ¦> study, which
measured HBCD in 22 pooled human milk samples collected from mothers in Belgium in 2006.
Total HBCD ranged from ND to 5.7 |ig/kg lw.
HBCD was measured in human milk samples collected 2010-2011 from 10 first-time mothers from
Birmingham, United Kingdom (Harrad and Ab> ). The participants were between 18
and 35 years of age. One sample was collected from each participant per month for the 12-month
duration of the study. Samples were analyzed for HBCD using LC-MS/MS with ESI in the
negative mode. In human milk, total HBCD was detected in all analyzed samples (n = 120) in
concentrations ranging from 1.46 to 20.65 |ig/kg lw.
33
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3.2.6 Asia
Kakimoto et at (2008). as cited in NICNAS (2012). examined the level of total HBCD in pooled
breast milk from 13 to 35 Japanese subjects aged 25-29 years and/or 30+ years per year between
1973 and 2006. HBCD was not detected in samples from 1973, 1978 or 1983. Mean HBCD
concentrations ranged from 0.43 to 4.0 |ig/kg lw between 1988 and 2006. The results did not show
a consistent pattern of increase or decrease of HBCD concentration with maternal age. As cited in
NICNAS (201.2). levels of HBCD were measured in 33 mother's milk samples collected in 2004
in the Philippines (Malarvannan et at. 2009). Total HBCD concentrations ranged from 0.13 to 3.2
|ig/kg lw (mean = 0.86 |ig/kg lw; median = 0.62 |ig/kg lw). 12) also reported HBCD
levels from samples collected near e-waste recycling and dismantling sites in Vietnam (Tue et at.
201.0). Reference site samples showed HBCD concentrations of 0.070 to 1.4 |ig/kg lw (median =
0.33 |ig/kg lw) in nine samples. Concentrations from workers and non-workers at e-waste sites
ranged from 0.11 to 7.6 |ig/kg lw (median = 0.36 to 2.0 |ig/kg lw) in 24 samples.
As cited in Law et .. <>, !«, the median HBCD concentration from 30 mother's milk samples
collected in 2008 the Philippines was 0.19 |ig/kg lw (Malarvannan et at.: ).
3.2.7 Australia
Toms et at (201.2) measured levels of HBCD in 12 pooled mother's milk samples collected 1993-
2009 for time trends in Australia. As cited in Law et at (201.4). total HBCD residues ranged from
ND to 19.0 |ig/kg lw. HBCD concentrations in human milk showed no temporal trend.
3.2.8 Africa
Asante et at (2011) and Darnerud et measured levels of total HBCD in mother's milk
samples from Ghana and South Africa in 2004-2009. As cited in Law i .. >1. h, median levels
of total HBCD were 0.62-1.0 and 0.3 |ig/kg lw, respectively. No significant increases of HBCD
concentrations were observed from 2004-2009 in human milk samples from Ghana.
34
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
4 Overview of Wildlife Biota Summary
Over 100 studies have reported HBCD concentrations in wildlife biota. In this section
concentrations are reported in terms of lipid weight (lw) when provided. Dry weight (dw) or wet
weight (ww) units may also be reported available for some studies but are not provided below.
4.1 Fish
4.1.1 Wildlife Biota
4.1.1.1.1 Fish Chart
I Background
CN-Zhuetal. 2013
FR - Miege et al. 2012
SE - Remberger et al. 2004
US - Chen et al. 2011
US - Klosterhaus et al. 2012
US - Shaw et al. 2009
US - Johnson-Restrcpo et al. 2008
BE - Rooscns et al. 2010
BE - Roosens et al. 2008
CA - Tomy et al. 2009
CA - Law et al. 2006
CA - Tomy et al. 2008
CH - Cheaib et al. 2009
CH - Gerecke et al. 2008
CN-Zhuetal. 2017
CN - He et al. 2013
CN-Xiaetal. 2011
CN - Wu et al. 2010
DK - Granby 2007
GB - Harrad et al. 2009
GB; BE; NL - Morris et al. 2004
ID - Ilyas et al. 2013
IT - Poma et al. 2014
IT - Poma et al. 2014
IT - Luigi et al. 2015
KP - Jeong et al. 2014
LA - Sudaryanto et al. 2007
Multiple - Frederiksen et al. 2007
Multiple - Ueno et al. 2006
0.001
1 10 100
Concentration ( ng/g ) (pt 1)
35
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
gj Background
I Near facility
Multiple - Rembergcr et al. 2004
NO - Bustnes et al. 2012
NO - Koppen et al. 2010
NO - Jenssen et al. 2007
NO - Sormo et al. 2006
PL - Reindl and Falkowska 2014
SE - Sellstrom et al. 1998
TZ-Polder ct al. 2014
ZA - Chokwe ct al. 2015
US-WSDE2016
CA - Ismail et al. 2009
CA - Tomy et al. 2004
CN - Zcng et al. 2014
CN - Meng et al. 2012
CZ - Hlouskova et al. 2013
CZ - Hradkova et al. 2012
CZ - Hajslova et al. 2007
CZ - Pulkrabova ct al. 2007
DK - Vorkamp ct al. 2014
DK - Granby 2007
ES - Guerra et al. 2009
ES - Eljarrat et al. 2005
GB - Mchugh et al. 2010
GB - Allchin and Morris 2003
JP - Kakimoto et al. 2012
KP - Barghi ct al. 2016
KP - Son ct al. 2015
LV-Zacsctal. 2014
LV-Zacs et al. 2014
0.001
NL - van Leeuwen and de Boer 2008
NO - Bustnes et al. 2010
SG - Zhang et al. 2015
ES - Eljarrat et al. 2004
N/A-ECIIA 2017
0.001
1 10 100
Concentration ( ng/g ) (pt 2)
lii Background
i Near facility
Modeled
1 10 100
Concentration (ng/g ) (pt 3)
36
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
4.1.1.1.2 Fish Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1927543
{Zhu, 2013, 1927543}
0.0565
1.31
0.26
0.26
1441147
{MiA'ge, 2012, 1441147}
1.94
790.6
1927826
{Remberger, 2004, 1927826}
65
1800
1927627
{Chen, 2011, 1927627}
13
5010
1443796
{Klosterhaus, 2012, 1443796}
2.5
24.7
6
6.5
1443830
{Shaw, 2009, 1443830}
2.4
38.1
17.2
17.2
1927767
{Johnson-Restrepo, 2008,
1927767}
1.83
413
54.5
77.7
1927683
{Roosens, 2010, 1927683}
16
4397
73
394
1927747
{Roosens, 2008, 1927747}
390
12100
4500
4500
1279130
{Tomy, 2009, 1279130}
0.9
11.8
999306
{Law, 2006, 999306}
66.18
170.61
1443836
{Tomy, 2008, 1443836}
0.42
2
1927722
{Cheaib, 2009, 1927722}
49
324
115
168
1927965
{Gerecke, 2008, 1927965}
44
250
120
120
3546047
{Zhu, 2017,3546047}
14.9
67.8
45.9
45.9
1927551
{He, 2013, 1927551}
17.5
832
58.3
361
1927654
{Xia, 2011, 1927654}
0.57
10.1
3.7
3.7
1927678
{Wu, 2010, 1927678}
129
868
3986479
{Granby, 2007, 3986479}
0.005
110
1927694
{Harrad, 2009, 1927694}
0.014
0.29
1927817
{Morris, 2004, 1927817}
0.7
690
43
184
2149566
{Ilyas, 2013,2149566}
1.6
3.3
2.45
2.45
2343685
{Poma, 2014, 2343685}
31
31
2343698
{Poma, 2014, 2343698}
13
1232
2919854
{Luigi, 2015,2919854}
1.2
166.3
38.94
38.94
2343722
{Jeong, 2014, 2343722}
1.7
7.2
4158939
{Sudaryanto, 2007, 4158939}
0.02
12
0.24
7
3575380
{Frederiksen, 2007, 3575380}
0.56
1.82
1927796
{Ueno, 2006, 1927796}
0.003
45
1927826
{Remberger, 2004, 1927826}
21
180
1927591
{Bustnes, 2012, 1927591}
3.74
13.9
1927674
{KAKppen, 2010, 1927674}
218.9
30316.8
1295.9
6845.9
1927762
{Jenssen, 2007, 1927762}
1.8
25.6
1927787
{SA.rmo, 2006, 1927787}
1.38
2.87
1.73
1.89
2528326
{Reindl, 2014, 2528326}
11.68
20
1715539
{Sellstrom, 1998, 1715539}
100
8000
100
100
2343683
{Polder, 2014, 2343683}
0.015
6.2
1.2
2.4
37
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3350535
{Chokwe, 2015,3350535}
10
13
3982306
{WSDE, 2016,3982306}
0.242
0.362
0.242
0.243
1443833
{Ismail, 2009, 1443833}
2
4
1927822
{Tomy, 2004, 1927822}
0.09
4.51
0.28
1.68
2343681
{Zeng, 2014, 2343681}
0.7
6.5
1927604
{Meng, 2012, 1927604}
0.00675
0.194
0.0157
0.0157
1927549
{HlouAjkovAj, 2013, 1927549}
0.04
11.6
0.44
0.44
1927635
{HrAjdkovAj, 2012, 1927635}
0.01
1.8
0.04
1.7
1927955
{Hajslova, 2007, 1927955}
0.8
158
2.1
27
1927763
{PulkrabovAj, 2007, 1927763}
0.1
15.55
2343732
{Vorkamp, 2014, 2343732}
0.006
0.056
3986479
{Granby, 2007, 3986479}
0.005
16.7
3575325
{Guerra, 2009, 3575325}
90
7813
1927819
{Eljarrat, 2005, 1927819}
72.8
1643
172
1501
1927686
{Mchugh, 2010, 1927686}
1.2
15
2.2
7
3809206
{Allchin, 2003, 3809206}
1.2
10275
20.3
3216
1927593
{Kakimoto, 2012, 1927593}
0.01
21.9
3.64
3.64
3350483
{Barghi, 2016,3350483}
0.24883
7.91491
0.24883
1.66372
3350528
{Son, 2015,3350528}
1.02
1.78
2528323
{Zacs, 2014, 2528323}
0.206
0.597
0.291
0.312
2343713
{Zacs, 2014, 2343713}
0.39
3.82
1.59
1.59
1927756
{van, 2008, 1927756}
0.1
230
1274407
{Bustnes, 2010, 1274407}
0.02
29.4
1.75
5.24
3350497
{Zhang, 2015, 3350497}
0.061
0.061
999290
{Eljarrat, 2004, 999290}
89.5
554.4
3970753
{ECHA, 2017,3970753}
280
2800
38
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
4.1.1.1.3 Fish: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality Level
dry
{Zhu, 2013,
1927543}
CN
Background
(Oxygymnocypris
stewartii,
Schizopygopsis
younghusbandi,
Schizothorax
macropogon,
Schizothorax
o'connori,
Schizothorax
waltoni,
Gymoncypris
waddellii,
Gymoncypris
przewalskii and
Racoma tibetanus
2007 -
2011
52
0.65
0.11
1.3
High
{MiA'ge,
2012,
1441147}
FR
Background
Barbel, common
bream, white
bream and chub
(whole specimen)
2008 -
2009
32
1
0.36
1.7
Medium
{Remberger,
2004,
1927826}
SE
Background
Pike (muscle)
2000
4
1
N/R
1.8
Medium
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
lipid
{Chen, 2011,
1927627}
US
Background
Common carp (fish
fillet)
1999 -
2007
9
N/R
0.2
1.4
High
{Klosterhaus,
2012, 1443796}
US
Background
White croaker (whole
specimen); Shiner
surfperch (whole
specimen)
2006
14
N/R
N/R
1.7
Medium
39
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
lipid
{Shaw, 2009,
1443830}
US
Background
Silver hake, white
hake, Atlantic
herring, American
plaice, alewife, winter
flounder, Atlantic
mackerel
2006
12
0.87
N/R
1.1
High
{Johnson-
Restrepo, 2008,
1927767}
US
Background
Bull shark (muscle);
Atlantic sharpnose
shark (muscle)
1993 -
2004
16
1
0.0013
1.9
Medium
{Roosens, 2010,
1927683}
BE
Background
European eel
2000 -
2006
50
1
2
1.5
High
{Roosens, 2008,
1927747}
BE
Background
Multiple fish species
and Eel (whole
fish/eel)
2006
35
1
2
2.0
Medium
{Tomy, 2009,
1279130}
CA
Background
Arctic cod; Pacific
herring; Arctic cisco
2004 -
2005
29
N/R
N/R
2.4
Low
{Law, 2006,
999306}
CA
Background
Walleye, whitefish,
emerald shiner,
burbot, white sucker,
and goldeye (muscle)
2000 -
2002
28
1
0.08
1.2
High
{Tomy, 2008,
1443836}
CA
Background
Redfish; Arctic cod
2000 -
2001
10
N/R
0.0036
1.7
Medium
{Cheaib, 2009,
1927722}
CH
Background
Lake trout
2004
9
1
N/R
1.6
High
{Gerecke, 2008,
1927965}
CH
Background
Trout
2003
25
1
N/R
1.8
Medium
{Zhu, 2017,
3546047}
CN
Background
Grass carp
2012 -
2013
5
1
N/R
3.0
Low3
{He, 2013,
1927551}
CN
Background
Mud carp; Nile
Tilapia; Suckermouth
catfish
2009
34
N/R
N/R
1.3
High
40
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
lipid
1927654
CN
Background
Yellow croaker and
silver pomfret (fillet)
2008
46
1
0.3
1.7
Medium
1927678
CN
Background
Carp; Crucian carp;
Snakehead; Water
snake
2006
23
0.7
3
2.0
Medium
3986479
DK
Background
Salmon, trout,
herring, eel
2002 -
2006
59
0.94
0.01
3
Low3
{Harrad, 2009,
1927694}
GB
Background
Multiple species
(muscle)
2008
30
1
0.25
1.7
Medium
{Morris, 2004,
1927817}
GB; BE;
NL
Background
Cod; Eels
1999 -
2000
32
N/R
1.2
2.3
Low
{Ilyas, 2013,
2149566}
ID
Background
Nile tilapia
2008
2
1
N/R
1.4
High
{Poma, 2014,
2343685}
IT
Background
Rutilus rutilus
2011 -
2012
5
1
0.01
1.9
Medium
{Poma, 2014,
2343698}
IT
Background
Shad, whitefish
(muscle); Shad,
whitefish (liver)
2011 -
2012
26
1
0.1
1.2
High
{Luigi, 2015,
2919854}
IT
Background
Common carp,
bream, sander, and
sheatfish (liver)
2010
10
1
0.011
1.9
Medium
{Jeong, 2014,
2343722}
KP
Background
Crucian carp
(muscle); Crucian
carp (eggs)
2010
15
1
0.02
1.3
High
{Sudaryanto,
2007,4158939}
LA
Background
Snakehead (muscle);
Tilapia (muscle);
Carp (muscle)
2005
30
N/R
0.02
1.9
Medium
{Frederiksen,
2007, 3575380}
Multiple
Background
Shorthorn sculpin
(Liver)
2006
2
0.5
1.1
2.1
Medium
{Ueno, 2006,
1927796}
Multiple
Background
Skipjack tuna
(muscle)
1997 -
2001
62
0.95
0.001
1.5
High
41
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
lipid
{Remberger,
2004, 1927826}
Multiple
Background
Herring (muscle)
1999 -
2000
6
1
N/R
1.8
Medium
{Bustnes, 2012,
1927591}
NO
Background
Saithe; Cod
2007
80
1
0.01
1.2
High
{KA^ppen, 2010,
1927674}
NO
Background
Multiple species
2006
5
1
0.006
1.9
Medium
{Jenssen, 2007,
1927762}
NO
Background
Atlantic Cod (whole
body); Atlantic cod
(whole body); Polar
cod (whole body)
2003
52
N/R
N/R
1.6
High
{SA^rmo, 2006,
1927787}
NO
Background
Polar cod
2003
7
N/R
0.3
2.2
Medium
{Reindl, 2014,
2528326}
PL
Background
Herring (Whole
Fish); Herring
(Herring Muscle);
Herring (Herring
Liver)
2009 -
2010
24
1
1.4
2.2
Medium
{Sellstrom, 1998,
1715539}
SE
Background
Pike (muscle)
1995
15
0.33
N/R
2.0
Medium
{Polder, 2014,
2343683}
TZ
Background
Tilapia (muscle)
2011
13
0.78
0.03
1.8
Medium
{Chokwe, 2015,
3350535}
ZA
Near
facility
Carp (muscle)
2013
12
1
0.48
1.6
High
3 Study evaluation score was downgradec
from medium to low
based on professional judgement.
42
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{WSDE, 2016,
3982306}
US
Background
Multiple
species
2014
44
0.27
100
1.1
High
{Ismail, 2009,
1443833}
CA
Background
Lake trout
(whole
specimen)
1979-
2004
29
1
N/R
1.8
Medium
{Tomy, 2004,
1927822}
CA
Background
Lake trout;
Forage fish
2002
85
1
N/R
2.0
Medium
{Zeng, 2014,
2343681}
CN
Background
Carp,
snakehead
(serum)
2010
6
1
0.004
1.8
Medium
{Meng, 2012,
1927604}
CN
Background
Tilapia,
bighead carp,
bluntsnout
bream, grass
carp,
northern
snakehead,
largemouth
bass, and
mandarin
fish;
snubnose
pompano,
crimson
snapper, red
drum, hairtail
and gold
thread
(muscle)
2004-
2005
60
0.7
0.003
1.3
High
43
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{HlouAjkovAj,
2013, 1927549}
CZ
Background
Freshwater
river fish:
common
breams,
European
chubs,
roaches,
crucian carp,
European
perch,
gudgeon,
grayling,
common
carp,
rainbow trout
and rudd
(muscle)
2010
48
0.79
0.08
1.7
Medium
{HrAjdkovAj,
2012, 1927635}
CZ
Background
Chub (fillet);
Common
bream
(fillet);
Roaches
(fillet)
2008 -
2009
38
0.82
0.02
1.2
High
{Hajslova, 2007,
1927955}
CZ
Background
Bream;
Chub; Perch
2005
80
1
0.02
2.0
Medium
{PulkrabovAj,
2007,1927763}
CZ
Background
Chub, barbel,
bream, perch
(muscle);
Trout (whole
body)
2001 -
2003
136
0.87
0.1
2.0
Medium
{Vorkamp, 2014,
2343732}
DK
Background
Multiple
freshwater
and seawater
fish
2012
11
0.9
0.012
2.0
Medium
44
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Granby, 2007,
3986479}
DK
Background
Salmon,
trout,
herring, eel
2002-
2006
59
0.94
0.01
3
Low3
{Guerra, 2009,
3575325}
ES
Background
Barbels,
Bleaks, and
Southwestern
Nases (whole
fish (bleaks
and nases);
muscle and
liver
(barbels))
2002-
2004
73
N/R
7
2.0
Medium
{Eljarrat, 2005,
1927819}
ES
Background
Bleak
2002
15
1
N/R
1.7
Medium
{Mchugh, 2010,
1927686}
GB
Background
European eel
2005
5
1
N/R
2.2
Medium
{Allchin, 2003,
3809206}
GB
Background
Brown trout
and eel
(muscle)
2003
10
1
1.2
2.1
Medium
{Kakimoto, 2012,
1927593}
JP
Background
Multiple
species
2011
18
0.9
0.02
1.6
High
{Barghi, 2016,
3350483}
KP
Background
Multiple
species
2012-
2014
40
1
0.0029
1.3
High
45
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Son, 2015,
3350528}
KP
Background
Mackerel,
cod, halibut,
pacific saury,
herring,
anchovy,
gray mullet
(whole
organism,
entrails
removed);
Catfish
(whole
organism,
entrails
removed)
2012-
2013
39
N/R
0.0029
1.6
High
{Zacs, 2014,
2528323}
LV
Background
Eel (Muscle)
2013
24
1
0.045
3
Low
{Zacs, 2014,
2343713}
LV
Background
Salmon
(fillets)
2012
25
1
0.006
1.2
High
{van, 2008,
1927756}
NL
Background
Multiple
freshwater
fish, marine
fish, and
shellfish
species
2003
44
N/R
N/R
1.5
High
{Bustnes, 2010,
1274407}
NO
Background
Saithe; Cod
2007
155
N/R
0.01
1.7
Medium
{Zhang, 2015,
3350497}
SG
Background
Marine
catfish
(tissue)
2014
11
0.36
0.0054
1.7
Medium
{Eljarrat, 2004,
999290}
ES
Near
facility
Barbel fish
(muscle);
Barbel fish
(liver)
2002
22
1
N/R
1.8
Medium
46
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{ECHA, 2017,
3970753}
N/A
Modeled
N/A
N/A
N/A
N/A
N/A
2
Medium
"Study evaluation score was downgraded
bStudy evaluation score was downgradec
I from medium to low based on professional
I from high to medium based on professiom
[judgement,
il judgement.
4.1.1.1.4 North America
Four studies were identified which report HBCD concentrations in fish from the United States.
Johnson-Restrepo et al. (2008) reported total HBCD concentrations of 1.83 to 413 |ig/kg lw (n =
16) in bull shark and Atlantic sharpnose shark muscle from samples collected in the coastal waters
of Florida from 1991 to 2004 [as cited in EC/HC (2011)1. Larsen et al. (2005) reported total HBCD
concentrations ranging from ND to 73.9 |ig/kg lw in various fish species collected in 2003 from
the Chesapeake Bay (detection in 50 of 52 samples) and Shaw et al. (2009) reported total HBCD
concentrations ranging from 7.6 to 23 |ig/kg lw (means) from various fish species collected off the
Maine coast [as cited in EC/HC (2011)1. Chen et al. (2011) reported a rise in total HBCD
concentrations from 13 to 4,640 |ig/kg lw (means) in carp collected from the Hyco River in
Virginia between 1999 and 2007 [as cited in Law et al. (2014)1.
Other studies reported HBCD concentrations in fish from Canada, including from lakes and the
arctic region. Total HBCD concentrations were observed at levels up to 92 |ig/kg lw. One study
(Ismail et al.. 2009). reported total HBCD concentrations of 16 to 33 |ig/kg lw in archived trout
from Lake Ontario, with total HBCD decreasing significantly over the 25 years between 1979 and
2004 [as cited in NICNAS (2012) and EC/HC (2011)1.
Tomy et al. (2009) measured the three major isomers of HBCD across eight species in a Canadian
Arctic food web. Isomer specific distribution across trophic levels was noted by the authors. Total
HBCD levels were derived by using method detection limits and dividing those by two when
values were not reported. The P-isomer was not detected across any species. Sample size was five
for each species with the exception of arctic cod with eight. Levels of total HBCD in red fish
ranged from 0.51 to 4.4 ug/kg lw with geometric mean of 2.0 ug/kg lw and in Arctic cod ranged
from 0.002 to 1.45 lw with geometric mean of 0.42.
4.1.1.1.5 Europe
Numerous European studies have examined HBCD concentrations in fish. HBCD concentrations
in fish collected in Europe appear to be higher than those collected in North America. For example,
Allchin and Morris (2003). as reported in EC/HC (2011). report total HBCD concentrations
ranging from ND to 10,275 |ig/kg ww in eel and trout of rivers in the United Kingdom (sampling
year and number of samples not reported). The highest concentration reported was 160,905 |ig/kg
47
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
lw, which was found in trout samples collected in 2002 downstream of a HBCD manufacturing
plant. The plant is no longer producing HBCD [Gems et al., 2006, as cited in EC (2008)1.
Total HBCD has been detected in fish collected in remote arctic areas. As noted by 8),
two studies report detection in polar cod (whole fish) collected in 2003 from the Norwegian arctic,
with central tendency values of 1.73 and 11.7 |ig/kg lw. 38) also provided statistical
summaries of fish data presented in 08). For freshwater muscle, they report total HBCD
concentrations ranging from 0.52 to 160,095 |ig/kg lw, with a median of 120 |ig/kg lw and a mean
of 5,223 |ig/kg lw (n =151). They note that concentrations in whole fish can be higher. For marine
fish muscle, 1} reported median concentrations of 13 |ig/kg lw (n = 100) in Western
Europe, 11.5 |ig/kg lw (n = 38) in the Baltic Sea, 107 |ig/kg lw (n = 16) in the Western Scheldt,
and 63 |ig/kg lw (n = 300) in the UK.
4.1.1.1.6 Asia
In Asia, only a limited number of studies have investigated HBCD levels in fish, including Ueno
et at (2006) and Xian et at (2008). as reported in EX . These studies reported
concentrations ranging from ND to 160 |ig/kg lw in samples collected between 1997 and 2006.
Law et at C reported results from an additional two studies conducted in China and Japan
(sampling dates not reported). In Xia et at (2011). the average total HBCD concentration was 3.7
|ig/kg lw in marine fish and in Nakagawa t the median total HBCD concentrations
ranged from 0.12 to 2.1 |ig/kg lw in wild and farmed fish.
A more recent study, Son et .. <>, i, analyzed various fish and marine invertebrate species
purchased from conventional fish markets in South Korea in 2012 (five locations) and in 2013 (six
locations). Eight fish species consisting of seven marine species (mackerel, halibut, pacific saury,
herring, anchovy, gray mullet) and one freshwater species (catfish) were monitored for total HBCD
in samples of muscle (fillet) with the exception of anchovy. Samples were analyzed for total HBCD
using LC-MS/MS with ESI in the negative mode. Total HBCD (sum of a- and y-HBCD)
concentrations varied between the different species, but mean concentrations in marine and
freshwater fish were 1.78 and 1.02 (J,g/kg ww, respectively.
48
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
4.2 Birds
4.2.1 Birds Chart
i—i Background
BE - Covaci et al. 2009
BE; FR - Eulaers et al. 2014
DE - Schwarz et al. 2016
US - Klosterhaus et al. 2012
¦
BE - Covaci et al. 2009
BE - Jaspers et al. 2005
BE; FR - Eulaers et al. 2014
CA - Braune etal. 2015
CA - Miller et al. 2014
CA - Braune et al. 2007
¦
CA; ES - Guerra et al. 2012
CN - Sun et al. 2012
CN-Yu etal. 2014
CN-Zheng et al. 2012
1
CN-Yu etal. 2013
DE - Esslingcr et al. 2011
GB - Leslie et al. 2011
GB - Law et al. 2006
GB - de Boer et al. 2004
GL - Vorkamp et al. 2012
GL - Vorkamp et al. 2005
IS - Jorundsdottir et al. 2013
JP - Hashikawa et al. 2011
KP-Hong et al. 2014
Multiple - Fredcriksen et al. 2007
NL; GB - Morris et al. 2004
NO - HaukA¥s et al. 2009
NO - Helgason et al. 2009
NO - Jenssen et al. 2007
0.001 0.01 0.1
o
o
o
o
o
o
o
>
0
>
01
Concentration (ng/g ) (pt 1)
49
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
I Background
I Near facility
NO - Murvoll ct al. 2006
NO - Murvoll et al. 2007
NO - Murvoll ct al. 2006
NO - Sormo et al. 2011
PL - Rcindl and Falkowska 2014
SE - Nordlof ct al. 2010
SE - Lundstedt-Enkel et al. 2006
SE - Sellstrom ct al. 2003
SE - Lundstedt-Enkel et al. 2005
SE - Johansson et al. 2009
SE - Lindbcrg ct al. 2004
CN-Zheng et al. 2012
NO - Haukas et al. 2010
US - Miller et al.
US - Henny ct al.
US - Venier et al.
CA - Gilchrist ct al.
CA - Gentes et al.
CA - Plourde et al.
CA - Chen et al.
GL - Vorkamp et al.
NO - Verreault et al.
NO - Verboven et al.
NO - Bustncs et al.
NO - Verreault et al.
NO - Murvoll et al.
NO - Murvoll et al.
NO - Verreault et al.
NO; RU - Miljeteig et al.
1 10 100
Concentration ( ng/g ) (pt 2)
10A5
Background
US, CA-Su et al. 2015
0.001
0.01
0.1
1 10 100
1000 10A4
10A5
Concentration (ng/g ) (pt 3)
4.2.2 Birds Summary Statistics
HERO
ID
Study Name
Min
Max
Central Tendency
(low)
Central Tendency
(high)
787649
{Covaci, 2009, 787649}
0.05
23.9
0.06
2.63
2343720
{Eulaers, 2014,
2343720}
0.02
333
0.16
4.06
50
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
3449771
{Schwarz, 2016,
3449771}
1.5
1000
1443796
{Klosterhaus, 2012,
1443796}
21.6
39
37.4
37.4
787649
{Covaci, 2009, 787649}
0.2
62
0.4
8.52
1927816
{Jaspers, 2005,
1927816}
20
50
2343720
{Eulaers, 2014,
2343720}
0.38
785
8.61
28.8
3350522
{Braune, 2015,
3350522}
16.2
100
2528327
{Miller, 2014,
2528327}
0.5
213.3
2.6
213.3
1412405
{Braune, 2007,
1412405}
2.1
3.8
1927628
{Guerra, 2012,
1927628}
0.9
15000
100
3700
1927580
{Sun, 2012, 1927580}
0.52
1700
2.8
380
2343702
{Yu, 2014, 2343702}
0.68
1100
2.8
51
1927597
{Zheng, 2012,
1927597}
105
105
1927541
{Yu, 2013, 1927541}
6.5
1100
6.6
260
1927650
{Esslinger, 2011,
1927650}
4.17
107
1927659
{Leslie, 2011,
1927659}
71
2360
3969307
{Law, 2006, 3969307}
22
19200
3986474
{de Boer, 2004,
3986474}
71
19000
1927578
{Vorkamp, 2012,
1927578}
7.5
230
38
38
1927805
{Vorkamp, 2005,
1927805}
0.05
230
2.4
17
2149610
{JA"rundsdA3ttir. 2013,
2149610}
0.54
370
1.3
41
3809208
{Hashikawa, 2011,
3809208}
480
1300
480
480
2149601
{Hong, 2014,2149601}
9
3970
3575380
{Frederiksen, 2007,
3575380}
2.3
44.33
1927817
{Morris, 2004,
1927817}
138
7100
796
1501
1927703
{HaukA/A¥s, 2009,
1927703}
4
300
11
190
1927723
{Helgason, 2009,
1927723}
12
142
1927762
{Jenssen, 2007,
1927762}
4.62
36.4
51
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
1414571
{Murvoll, 2006,
1414571}
100
335
1927774
{Murvoll, 2007,
1927774}
0.75
35.4
35.4
35.4
1927797
{Murvoll, 2006,
1927797}
417
417
1927631
{SA^rmo, 2011,
1927631}
9.5
698
17.3
100.32
2528326
{Reindl, 2014,
2528326}
65.02
326.91
26.72
319.17
1927660
{NordlAKf, 2010,
1927660}
40
480
60
180
1927794
{Lundstedt-Enkel,
2006, 1927794}
64.7
138
999339
{SellstrAKm, 2003,
999339}
54
300
34
170
1927804
{Lundstedt-Enkel,
2005,1927804}
62.7
66.7
1927734
{Johansson, 2009,
1927734}
5.5
1900
92
270
1927824
{Lindberg, 2004,
1927824}
4
2400
150
520
1927597
{Zheng, 2012,
1927597}
44.2
350
1927667
{HaukA¥s, 2010,
1927667}
4
280
19
170
2528324
{Miller, 2014,
2528324}
0.57
15.5
1927712
{Henny, 2009,
1927712}
0.0025
69.2
1927677
{Venier, 2010,
1927677}
0.03
0.56
0.05
0.13
2149396
{Gilchrist, 2014,
2149396}
0.6
2.2
3283561
{Gentes, 2012,
3283561}
0.055
19.8
5.22
5.22
4160319
{Plourde, 2013,
4160319}
0.055
19.8
4.45
4.45
1851195
{Chen, 2012, 1851195}
0.5
16.6
3015562
{Vorkamp, 2015,
3015562}
0.83
3.36
1.49
1.49
1927771
{Verreault, 2007,
1927771}
0.295
63.9
1.73
19.8
1927975
{Verboven, 2009,
1927975}
2.7
19.8
1927758
{Bustnes, 2007,
1927758}
0.015
36.5
0.22
2.21
1927809
{Verreault, 2005,
1927809}
0.07
1.24
0.32
0.34
52
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
1927774
{Murvoll, 2007,
1927774}
6.23
6.23
1927797
{Murvoll, 2006,
1927797}
28.5
28.5
531779
{Verreault, 2007,
531779}
0.51
292
3.29
117
1274420
{Miljeteig, 2009,
1274420}
14
272
38.1
136
3345569
{Su, 2015,3345569}
0.015
41.4
7.17
19.8
4.2.3 Birds: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Covaci,
2009,
787649}
BE
Background
Chickens
(feces)
2006-
2007
20
0.6
N/R
1.8
Medium
{Eulaers,
2014,
2343720}
BE; FR
Background
Barn owl
(feathers)
2008 -
2009
73
1
N/R
2.0
Medium
{Schwarz,
2016,
3449771}
DE
Background
Peregrine
falcon
(Egg
contents)
2006-
2011
50
0.5
3
2.2
Medium
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Klosterhaus,
2012, 1443796}
US
Background
Double-crested
cormorant
(eggs)
2008
3
1
N/R
1.7
Medium
53
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Covaci, 2009,
787649}
BE
Background
Chicken
(eggs);
Chickens
(eggs)
2006 -
2007
20
0.55
0.4
1.8
Medium
{Jaspers, 2005,
1927816}
BE
Background
Little owls
1998 -
2000
40
0.05
5
2.2
Medium
{Eulaers, 2014,
2343720}
BE; FR
Background
Barn Owl
(muscle); Barn
Owl (liver
tissue); Barn
Owl (gland
tissue); Barn
owl (adipose
tissue); Barn
owl (muscle);
Barn owl (liver
tissue); Barn
owl (gland
tissue)
2008 -
2009
88
1
N/R
2.0
Medium
{Braune, 2015,
3350522}
CA
Background
Glaucous gull
(eggs); Black-
legged
kitiwake
(eggs)
2008 -
2013
51
N/R
1
1.9
Medium
{Miller, 2014,
2528327}
CA
Background
Rhinoceros
auklets (eggs);
Leach's storm-
petrel (eggs);
Ancient
murrelet
(eggs)
1990 -
2011
26
0.69
1
1.9
Medium
{Braune, 2007,
1412405}
CA
Background
Ivory gull
(eggs)
1976 -
2004
24
1
0.3
2.0
Medium
{Guerra, 2012,
1927628}
CA; ES
Background
Peregrine
falcon (eggs)
2003 -
2009
25
0.8
N/R
1.8
Medium
54
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Sun, 2012,
1927580}
CN
Background
Bulbul
(muscle);
Shrike
(muscle);
Oriental
magpie-robin
(muscle)
2009 -
2011
69
0.99
1
1.9
Medium
{Yu, 2014,
2343702}
CN
Background
Tree sparrow
(muscle);
Common
magpie
(muscle)
2009 -
2011
68
1
1.6
1.9
Medium
{Zheng, 2012,
1927597}
CN
Background
Hens
2010
8
1
4.7
1.9
Medium
{Yu, 2013,
1927541}
CN
Background
Common
kestrel; Eagle
owl; Eurasian
tree sparrow
2005 -
2007
87
1
0.67
2.0
Medium
{Esslinger, 2011,
1927650}
DE
Background
Herring gulls
(eggs)
1988 -
2008
26
N/R
0.00092
1.7
Medium
{Leslie, 2011,
1927659}
GB
Background
Peregrine
falcon (eggs);
Sparrow hawk
(muscle)
1973 -
2002
127
0.16
N/R
1.7
Medium
{Law, 2006,
3969307}
GB
Background
Falcon (eggs);
Sparrowhawk
(muscle)
1973 -
2002
21
0.2
N/R
1.8
Medium
{de Boer, 2004,
3986474}
GB
Background
Falcon (eggs);
Sparrowhawk
(muscle)
1973 -
2002
116
0.18
N/R
1.9
Medium
{Vorkamp, 2012,
1927578}
GL
Background
Gulls
1994 -
2010
8
1
0.76
2.1
Medium
{Vorkamp, 2005,
1927805}
GL
Background
Falcon (eggs)
1986 -
2003
33
0.88
0.1
2.0
Medium
55
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{JA"rundsdA3ttir.
2013,2149610}
IS
Background
Guillemot
(eggs); Fulmar
(eggs); Arctic
tern (eggs);
Common eider
(eggs); Gulls
(eggs); Great
skua (eggs)
2002 -
2004
63
0.89
4.7
2.0
Medium
{Hashikawa,
2011, 3809208}
JP
Background
Common
Cormorants
(muscle)
1993 -
2077
41
N/R
N/R
3.0
Low
{Hong, 2014,
2149601}
KP
Background
Gull (muscle);
Pigeon
(muscle); Loon
(muscle);
Heron, egrets
(muscle)
2009
15
1
N/R
1.9
Medium
{Frederiksen,
2007, 3575380}
Multiple
Background
Black
Guillemot
(Egg); Black
Guillemot
(Liver); Fulmar
(Liver); Fulmar
(Subcutaneous
fat)
2006
8
0.75
4.6
2.1
Medium
{Morris, 2004,
1927817}
NL; GB
Background
Tern (eggs);
Cormorant
(liver)
1999-
2001
15
1
1.2
2.3
Low
{HaukA/A¥s,
2009, 1927703}
NO
Background
Common
eider; Great
black backed
gull
2006-
2007
74
1
0.05
1.9
Medium
{Helgason, 2009,
1927723}
NO
Background
Herring (eggs);
Kittiwake
(eggs); Puffin
(eggs)
1983-
2003
89
1
N/R
1.7
Medium
56
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Jenssen, 2007,
1927762}
NO
Background
Common terns
(eggs); Arctic
terns (eggs)
2003
30
N/R
N/R
1.6
Medium
{Murvoll, 2006,
1414571}
NO
Background
North Atlantic
kittiwake (yolk
sac)
2002
37
N/R
1.5
2.1
Medium
{Murvoll, 2007,
1927774}
NO
Background
Brunnich's
guillemot (yolk
sac); Common
eider (yolk
sac)
2002
23
0.43
1.5
2.1
Medium
{Murvoll, 2006,
1927797}
NO
Background
European
shag (yolk
sac)
2002
30
1
1.5
2.1
Medium
{SA^rmo, 2011,
1927631}
NO
Background
Herring gulls
(liver)
1998
16
1
N/R
1.8
Medium
{Reindl, 2014,
2528326}
PL
Background
African
penguin
(Whole Egg);
African
penguin (Egg
Yolk); African
penguin (Egg
Albumen);
African
penguin
(Muscle);
African
penguin
(brain); African
penguin
(Liver); African
penguin
(Adipose)
2008-
2010
21
1
1.4
2.2
Medium
JNordlA' f. 2010,
1927660}
SE
Background
Sea eagle
(eggs)
1992-
2005
44
1
13
1.9
Medium
57
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Lundstedt-Enkel,
2006, 1927794}
SE
Background
Baltic Sea
guillemot
(eggs); Baltic
Sea guillemot
(muscle)
2000-
2002
50
N/R
N/R
2
Medium
{ScllstrA'm.
2003,999339}
SE
Background
Guillemot
(eggs)
1969-
2001
137
1
N/R
1.8
Medium
{Lundstedt-Enkel,
2005, 1927804}
SE
Background
Guillemot
2000
10
N/R
N/R
2
Medium
{Johansson, 2009,
1927734}
SE
Background
Peregrine
falcons (eggs)
1991 -
1999
34
0.95
11
1.7
Medium
{Lindberg, 2004,
1927824}
SE
Background
Falcon
1987-
1999
21
0.81
N/R
2
Medium
{Zheng, 2012,
1927597}
CN
Near facility
Hens
2010
33
1
4.7
1.9
Medium
{HaukA¥s, 2010,
1927667}
NO
Near facility
Great
blackbeaked
gull (whole
seabird eggs
without shell);
Common eider
(whole seabird
eggs without
shell)
2006-
2007
55
1
N/R
1.9
Medium
58
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Hero ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Rounded
Evaluation
Score
wet
{Miller,
2014,
2528324
}
US
Backgrou
nd
Double-
crested
cormora
nt (egg);
Great
blue
heron
(egg)
2003-
2012
50
N/R
1
2.2
Medium
{Henny,
2009,
1927712
}
US
Backgrou
nd
Osprey
(eggs);
Cormor
ant
(eggs)
2002-
2007
119
0.11
0.005
2.0
Medium
{Venier,
2010,
1927677
}
us
Backgrou
nd
Bald
eagle
2005
15
0.47
N/R
1.7
Medium
{Gilchris
t, 2014,
2149396
}
CA
Backgrou
nd
Tree
swallow
s (eggs)
2007-
2010
87
N/R
N/R
1.9
Medium
{Gentes,
2012,
3283561
}
CA
Backgrou
nd
Ring-
billed
gull
(plasma
); Ring-
billed
gull
(liver)
2010
58
0.43
0.11
1.4
High
{Plourde,
2013,
4160319
}
CA
Backgrou
nd
Gulls
(liver)
2010
21
0.9
0.11
1.8
Medium
{Chen,
2012,
1851195
}
CA
Backgrou
nd
Gulls:
glaucou
s-
winged,
Californi
a, ring-
billed,
herring
2008
26
N/R
1.1
1.9
Medium
59
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Hero ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Rounded
Evaluation
Score
wet
{Vorkam
p, 2015,
3015562
}
GL
Backgrou
nd
Glaucou
s gull
(liver)
2012
4
1
N/R
1.2
High
{Verreau
It, 2007,
1927771
}
NO
Backgrou
nd
Glaucou
s gulls
(blood
plasma);
Glaucau
s gull
(blood
plasma);
Glaucau
s gull
(egg
yolk)
2006
80
0.76
0.59
1.6
High
{Verbov
en, 2009,
1927975
}
NO
Backgrou
nd
Gulls
(eggs);
Gulls
(plasma
)
2006
42
N/R
N/R
1.9
Medium
{Bustnes
, 2007,
1927758
}
NO
Backgrou
nd
Owl
(eggs)
1986 -
2004
139
0.24
0.03
1.8
Medium
{Verreau
It, 2005,
1927809
}
NO
Backgrou
nd
Gulls
2004
27
1
0.03
1.4
High
{Murvoll
, 2007,
1927774
}
NO
Backgrou
nd
Commo
n eider
(yolk
sac)
2002
14
0.07
1.5
2.1
Medium
{Murvoll
, 2006,
1927797
}
NO
Backgrou
nd
Euro pea
n shag
(yolk
sac)
2002
30
1
1.5
2.1
Medium
60
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Hero ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Rounded
Evaluation
Score
wet
{Verreau
It, 2007,
531779}
NO
Backgrou
nd
Glaucou
s gulls
(blood);
Glaucou
s gulls
(liver);
Glaucou
s gulls
(whole
body
homoge
nate
with
feathers
);
Glaucou
s gulls
(whole
body
homoge
nate
without
feathers
)
2002
57
1
N/R
1.6
High
{Miljetei
g, 2009,
1274420
}
NO; RU
Backgrou
nd
Ivory
gull
(eggs)
2006-
2007
35
N/R
N/R
1.4
High
{Su,
2015,
3345569
}
US, CA
Backgrou
nd
Herring
gull
(eggs)
2012-
2013
130
0.97
0.03
1.3
High
4.2.4 North America
Law et al. (2014) reported total HBCD concentrations in avian samples collected in Montreal,
Canada, including liver samples from ring-billed gulls (Gentes et al.. 20121 unknown tissue
samples from peregrine falcons (Fernie and Letcher. 2010). and unhatched eggs from peregrine
falcons (Guerra et al.. 2012). Total HBCD concentrations were 5.22 |ig/kg wet weight (mean) in
61
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
avian liver, ND to 0.03 |ig/kg wet weight in an unknown avian tissue, and ND- 14,600 |ig/kg lipid
weight (mean of 3,700 |ig/kg lipid weight) in unhatched eggs.
Gilchrist et e studied the reproduction of tree swallows (Tachycineta bicolor) nesting near
WWTPs in Canada between 2007 and 2010. The breeding colonies were located near two WWTPs
and near a reservoir for a wildlife conservation area that was selected as a reference area. One of
the first three eggs in each clutch was collected, and a subset of 30 eggs from approximately 10
nests per site was used for chemical analysis. The eggs were analyzed for PCBs, organochlorine
pesticides, and flame retardant chemicals including total HBCD. Analysis consisted of an
accelerated solvent extraction method followed by GC-MS with ECNI. The mean total HBCD
concentrations were 2.2 |ig/kg ww (n = 71) for eggs collected near both WWTPs and 0.6 |ig/kg
ww (n = 16) for eggs collected near the reservoir.
Braune t analyzed samples of eggs of two seabird species (thick-billed murre (Uria
lomvia) and northern fulmer (Fulmarus gacialis) collected annually from Prince Leopold Island
Migratory Bird Sanctuary in Lancaster Sound, Nunavut, Canada from 2003 and 2005-2014. Eggs
were analyzed for total HBCD by GC-MS with ECNI using a method in which the P- and y-isomers
are converted to a-HBCD in the injection port. Egg samples were analyzed as pooled (composite)
samples, with each pool consisting of three individual egg samples (2005-2014) or five individual
egg samples (2003). The mean concentrations of total HBCD in eggs (n = 330 eggs; 106 pools)
ranged from ND to 27.9 |ig/kg lw.
Braune et at (200?) also analyzed ivory gull eggs to examine temporal trends. From 1976 to 2004,
24 samples were collected. Concentrations of HBCD in 1976 were 3.8 ng/g lw, 3.0 ng/g lw in
1987, and 2.1 ng/g lw in 2004. Overall, pooled samples had a mean concentration ranging from
2.1 to 3.8 ng/g lw.
Su ei analyzed samples of herring gull (Larus argentatus) eggs collected from 20
colonies within both US and Canada waters of the Laurentian Great Lakes basin from 2012 to
2013. Eggs were collected in 2012 from 15 colonies under Canada's Laurentian Great Lakes
Herring Gull Monitoring Program (GLHGMP) and in 2012-2013 from 5 colonies under Clean
Michigan Initiative-Clean Water Fund (CMI-CWF). For the GLHGMP sites, 1 pooled sample
(comprised of 13 individual eggs) was analyzed for each colony, and for the US CMI-CWF sites,
20 individual eggs were analyzed for each colony. Samples were analyzed for total HBCD by GC-
MS using a method in which the P- and y-isomers are converted to a-HBCD in the injection port.
The mean concentrations of total HBCD residues in 15 egg pools collected 2012 from the
GLHGMP colonies ranged from 86.5 to 225 |ig/kg lw. Concentrations of total HBCD residues in
eggs (n = 100 eggs) collected in 2012 and 2013 from the 5 CMI-CWF colonies ranged from ND
to 557 |ig/kg lw (90.5 to 197 |ig/kg lw mean); the limit of detection was reported as 0.03 |ig/kg
ww.
Gauthier et at (200?) analyzed samples of herring gull egg pools from six locations in the Great
Lakes. Alpha-HBCD was detected in 5 of 6 six sites, Gamma-HBCD was detected in 2 sites, and
beta HBCD was not detected. Overall HBCD levels across isomers and sites ranged from ND to
20 ug/kg wet weight.
Chen et al. (2012) studied eggs of four gull species (Laridae) from Canadian marine and freshwater
ecosystems collected from a total of 26 colonies spanning Pacific to Atlantic Canada, including the Great
62
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Lakes basin. Gulls are top predators in their respective ecosystems and ideal for monitoring halogenated
contaminants. Herring gull eggs from fifteen Great Lakes colony sites were collected from late-April to
early-May of 2008. For each colony site, 10 tol3 individual eggs from different nests were pooled on an
equal wet-weight basis. In addition, individual eggs (n=10) from different nests of glaucous-winged
(Larus glaucescens), California (Larus californicus), ring-billed (Larus delawarensis) or herring gulls
were also collected in early-May to early-July of 2008 from each of 11 additional colonies spanning the
Pacific to the Atlantic coast of Canada. The pooled and individual eggs were homogenized and stored at -
40 C at Environment Canada's National Wildlife Specimen Bank prior to chemical analysis. HBCD was
analyzed for using GC-MS-in ECNI. Method blanks were processed to monitor interferences and
contamination and MLOQ =1.1 ng/g and MLOD = 0.28 ng/g. In the marine ecosystem (n=6 pooled
samples): minimum median = 0.5 ng/g ww; maximum median = 4.5 ng/g ww; minimum arithmetic mean
= 2.2 ng/g ww; maximum arithmetic mean = 9 ng/g ww. For the non-Great Lakes freshwater ecosystem
(n=5 pooled samples): minimum median = 4.4 ng/g ww; maximum median = 11.7 ng/g ww; minimum
arithmetic mean = 6.7 ng/g ww; maximum arithmetic mean = 16.6 ng/g ww. For the Great Lakes
ecosystem (n = 15 pooled samples): minimum of pooled samples = 2.0 ng/g ww; maximum of pooled
samples = 12 ng/g ww. Gulls breeding in regions with higher human population densities likely incurred
greater flame retardant exposure. This study also contains an analysis of stable isotopes as dietary tracers
in relation to flame retardants.
4.2.5 Europe
As cited in Law et ,» ' -1. ! i, liver samples from herring gulls from Norway Soroto et <. <1,
eggs from white-tailed sea eagles and peregrine falcons from Sweden, the Netherlands, and the
UK (Leslie et at. ; ' rdlof et at. 2010). and muscle samples from sparrowhawk from
Sweden, the Netherlands, and the UK were analyzed (Leslie ). Overall, total HBCD
residues ranged from 10-698 |ig/kg lipid weight in avian liver and 84-19,000 |ig/kg lipid weight
in avian muscle. In avian eggs, reported total HBCD concentrations ranged from 71-1,200 |ig/kg
lipid weight in the Leslie study and reported means of total HBCD concentrations
ranged from 60-150 |ig/kg lipid weight in the Nordlof et at (2010) study.
Bustnes et at (200?) reported HBCD concentrations in the eggs of tawny owls from 1986 to 2004.
HBCD was detected in 34 of 139 samples with concentrations reported from 0.04 to 36.5 ug/kg
lw and mean concentration of 2.21 ug/kg lw.
Three studies of HBCD in birds were reported in Stockholm Conventions Persistent Organic
Pollutants Review Committee's risk profile of HBCD. reported HBCD in glaucous
gulls {Larus hyperboreus) and great black-backed gulls {Larus marinus) found dead in the
Norwegian Arctic between 2003-2005. The a-HBCD concentrations in the brain samples of
glaucous gulls ranged from 5.1 ng/g lw to 475 ng/g lw and from 195 ng/g lw to 15,027 ng/g lw in
the liver. HBCD levels in two great black-backed gulls were 44.7-44.8 ng/g lw in the brain and
1,881 - 3,699 ng/g lw in the liver. A similar study, (K.LIF. 2005) reported HBCD levels in egg
samples from three bird species in 1983, 1993, and 2003, and found that median levels increased
from 7.9-110 ng/g lw in herring gulls, 8.4-72.3 ng/g lw in Atlantic puffins and 15.9 - 161.3 ng/g
lw in black-legged kittiwakes, and 25.3-81.4 ng/g lw in glaucous gulls ( )05).
Milieteig et at (2009) reported HBCD levels ranging from 14 to 272 ng/g lw in ivory sea gull eggs
at four Arctic sites in Norway and Russia.
63
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Esslinger et al. (2011) sampled herring gull eggs from the islands Mellum and Trischen in the German
Wadden Sea and from the island Heuwiese at the German Baltic Sea coast from 1998 to 2008. Between
35 and 140 eggs were collected annually and the whole content of all eggs from a given site and year
were pooled and archived by the German Environmental Specimen Bank (ESB). Egg powders as received
from the ESB were homogenized and stored at -20 C until further processing. The 26 egg pool samples
were analyzed by HPLC-MS/MS where the LOD for the six stereoisomers ranged between 0.13 and 0.26
pg/g and LOQ between 0.48 and 0.93 pg/g. Herring gull eggs are excellent indicators of contaminant
exposure in the environment, herrings maintain stable population dynamics, and their feeding habits are
well known. Results are reported as six stereoisomers for a-, (3-, y-HBCD, where a-HBCD was detected
as the dominant diastereoisomer. Results for total HBCD: Mellum island, 1988-2008, (n=10 pooled
samples): minimum = 4.17 ng/g lw; maximum = 107 ng/g lw; Trischen island, 1988-2008, (n=10 pooled
samples): minimum = 13.8 ng/g lw; maximum = 74.8 ng/g lw. Heuwiese island, 1998-2008, (n=6 pooled
samples): minimum = 25.1 ng/g lw; maximum = 98.7 ng/g lw. The average contamination levels at the
three locations are relatively close but nevertheless significantly different from each other. The increase in
concentration of HBCD in eggs between 1994 and 2000 might reflect the steady rise in demand of HBCD
during this period. Esslinger et al. (2011) also examined temporal trend data on HBCD from bird eggs
from other locations from 1970 to 2004. The concentrations in the current study were in the middle range
and similar to gull and guillemot eggs elsewhere in Europe. The trends in the reported secondary data
varied, including increases in bird eggs from 1983-2003 in Northern Norway, no increases from guillemot
eggs from a Swedish Baltic Sea between 1991 and 2001, and slight decreases in peregrine falcon eggs
from Greenland between 1986 and 2003 and tawny owl eggs from Central Norway between 1986 and
2004.
Sellstrom et al. (2003) conducted a temporal trend study of HBCD concentrations in individual
and/or pooled Guillemot bird eggs collected between 1969 and 2001 from Stora Karlso, an island
off Sweden's west coast in the Baltic Sea. The study is partly based on the analysis of eggs archived
and stored in the Swedish Environmental Specimen Bank. Guillemot eggs have previously been
shown to be a very important matrix for studies of persistent environmental contaminants, as
Guillemots are stationary within the Baltic the entire year, they nest far away from local sources
in the central part of the Baltic Proper, and they feed exclusively on pelagic fish that migrate within
the Baltic. In this investigation, egg sampling was constrained to early laid eggs to avoid an
important source of within-year variation. Samples were analyzed using GC-MS run in the
chemical ionization mode, measuring the negative ions formed (ECNI). Quality control measures
taken included analysis of duplicate or triplicate calibration curves, laboratory blanks, recovery
samples, and the use of laboratory reference material (herring homogenate) extracted and analyzed
in parallel with the guillemont eggs. Specifically, one pooled sample of 10 archived eggs was
analyzed per study year between 1969 and 1992 (no eggs from 1970, 1974, 1979, 1984, and 1991
were studied) and 10 eggs were analyzed individually per study year between 1993 and 2001.
Additionally, the uncertainty of the results obtained from the pooled samples was investigated by
analyzing individual eggs from 1976 and 1992; the pooled egg concentrations were within the
range of the individual egg concentrations. For HBCD, the analysis indicates a steady and
significant (p < 0.001) increase in concentrations over time up to recent periods, although there
are indications of a minor peak during the mid-1970s or a decrease in concentrations during 1978-
1985. The concentrations of HBCD have approximately doubled during the study period, but this
increase seems to have leveled out since the mid-1990s. For 1969-1992 samples (n=18 pooled
samples): minimum = 34 ng/g lw; maximum = 140 ng/g lw. For 1993-2001 samples (n=119
individual samples): minimum = 54 ng/g lw; maximum = 300 ng/g lw; minimum annual arithmetic
64
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
mean =110 ng/g lw; maximum annual arithmetic mean = 170 ng/g lw. Verreault et al. reported
four studies over four years that reported concentrations of HBCD in various tissues of glaucous
gulls. Verreault et al. (2004) reported a range of 20-774 ug/kg lw (142 mean) in glaucous gull
eggs, 6.13 to 108 ug/kg lw (37 mean) in the plasma of male glaucous gulls, and 19-122 ug/kg lw
(52 mean) in the plasma of female glaucous gulls. Verreault et al. (2005) reported 0.07-1.24 ug/kg
ww in the blood plasma of glaucous gulls. Verreault et al (2007a) reported 7.23- 63.9 ug/kg HBCD
in glaucous gull eggs and 1.73-2.07 ug/kg ww in plasma. Finally, v i reault et i. ' - "07b) reported
an average of 3.29 ug/kg ww in glaucous gull blood, an average of 75.6 ug/kg ww in glaucous gull
liver, and a range of 38.4 to 194 ug/kg ww in whole body (no feathers) HBCD concentrations
(mean 91).
4.2.6 Asia
Eggs and unspecified muscle samples from cormorant chicks and adults from Lake Biwa, Japan
were analyzed in Hashikawa et al (2011). As cited in Law et al (2014). the average concentration
of total HBCD residues in muscle of adults was 480 |ig/kg lipid weight.
4.2.7 Africa
Eggs of eight bird species were analyzed and HBCD was detected in three of them. The sample
size varied across species with 43 samples collected overall. Across 14 African darter egg samples
HBCD levels ranged from ND to 11 ug/kg lw. In two sacred ibis egg samples HBCD levels were
4.8 and 71 ug/kg lw. In one crowned plover egg sample, HBCD was detected at 1.6 ug/kg lw.
HBCD was not detected in reed cormorant, cattle egret, little grebe, white-fronted plover, kelp gull
eggs.
65
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
5 Overview of Environmental Monitoring Data
5.1 Surface Water
5.1.1 Environmental Media
5.1.1.1.1 Surface Water (ng/g) Chart
CN - He et al. 2013
Background
1
10
Concentration (ng/g)
100
5.1.1.1.2 Surface Water (ng/g) Summary Statistics
HERO
ID
Study Name
Min
Max
Central Tendency
(low)
Central Tendency
(high)
1927551
{He, 2013, 1927551}
8
11.3
8
8
5.1.1.1.3 Surface Water (ng/g): Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
{He, 2013,
1927551}
CN
Background
2009
5
N/R
N/R
1.3
High
66
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
5.1.1.1.4 Surface Water (ng/L) Chart
¦¦¦ Background
Near facility
Modeled
US - Venier et al. 2014
AQ - Zhang et al. 2016
AQ - Zhang et al. 2016
CA - Robson et al. 2013
CN - He et al. 2013
CN - Wu et al. 2010
1
DK - Vorkamp et al. 2014
GB - Harrad et al. 2009
JP - Ichihara et al. 2014
JP - Oh et al. 2014
KP - Kim et al. 2016
NL - Peters 2003
I
PL - Kowalski and Mazur 2014
¦
JP - Ichihara et al. 2014
ZA - Chokwe et al. 2015
N/A-ECHA 2008
N/A-ECHA 2017
o
o
<
o
100 10A4 10A6
Concentration ( ng/L )
5.1.1.1.5 Surface Water (ng/L) Summary Statistics
HERO ID
Study name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
2695212
{Venier, 2014,
2695212}
0.00043
0.0042
3350551
{Zhang, 2016,
3350551}
0.48
1.54
3350551
{Zhang, 2016,
3350551}
0.13
1.16
2182416
{Robson, 2013,
2182416}
0.36
60
2
2
1927551
{He, 2013,
1927551}
0.0095
0.0824
0.0397
0.0397
1927678
{Wu, 2010,
1927678}
0.06
0.06
2343732
{Vorkamp,
2014, 2343732}
0.096
2.9
1927694
{Harrad, 2009,
1927694}
0.08
0.27
2343678
{Ichihara, 2014,
2343678}
0.19
14
2343704
{Oh, 2014,
2343704}
2.5
2100
9.3
642.9
67
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Study name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
3545985
{Kim, 2016,
3545985)
0.0256
0.166
3809261
{Peters, 2003,
3809261)
1835
1835
1835
1835
2343691
{Kowalski,
2014, 2343691)
1330
3100
2343678
{Ichihara, 2014,
2343678)
0.39
400
3350535
{Chokwe, 2015,
3350535)
510
1770
3970747
{ECHA, 2008,
3970747)
28
370000
3970753
{ECHA, 2017,
3970753)
0.52
600
5.1.1.1.6 Surface Water (ng/L): Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/L)
Data
Quality
Evaluation
Score
Overall
Quality
Level
{Venier, 2014,
2695212}
US
Background
2011 -
2012
23
0.61
N/R
1.7
Medium
{Zhang, 2016,
3350551}
AQ
Background
2013 -
2014
8
1
N/R
1.8
Medium
{Zhang, 2016,
3350551}
AQ
Background
2013 -
2014
4
1
N/R
1.8
Medium
{Robson, 2013,
2182416}
CA
Background
2004 -
2010
443
0.73
N/R
1.4
High
{He, 2013,
1927551}
CN
Background
2009
5
N/R
N/R
1.3
High
{Wu, 2010,
1927678}
CN
Background
2006
3
0.5
N/R
2.0
Medium
{Vorkamp, 2014,
2343732}
DK
Background
2012
5
1
0.012
2.0
Medium
68
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/L)
Data
Quality
Evaluation
Score
Overall
Quality
Level
{Harrad, 2009,
1927694}
GB
Background
2008 -
2009
27
1
N/R
1.7
Medium
{Ichihara, 2014,
2343678}
JP
Background
2012 -
2013
19
1
N/R
1.4
High
{Oh, 2014,
2343704}
JP
Background
2011
17
1
N/R
1.4
High
{Kim, 2016,
3545985}
KP
Background
2010
16
1
N/R
1.4
High
{Peters, 2003,
3809261}
NL
Background
2003
50
0.02
15
1.7
Medium
{Kowalski, 2014,
2343691}
PL
Background
2014
15
N/R
950
3.0
Low
{Ichihara, 2014,
2343678}
JP
Near facility
2012
30
1
N/R
1.4
High
{Chokwe, 2015,
3350535}
ZA
Near facility
2013
12
1
200
1.6
High
{ECHA, 2008,
3970747}
N/A
Modeled
N/A
N/A
N/A
N/A
1.3
High
{ECHA, 2017,
3970753}
N/A
Modeled
N/A
N/A
N/A
N/A
2
Medium
5.1.1.1.7 Surface Water Summary
North America
Venier et al. (2014) measured a large group of organic chemicals, including flame retardants, in
surface water samples collected from 18 stations distributed throughout the five Great Lakes (Erie,
Huron, Michigan, Ontario, and Superior) in 2011 and 2012 using XAD-2 resin absorption. Surface
water samples were collected using the PopCart, a sampling technique customized by Environment
Canada, and were analyzed for the flame retardants including total HBCD using GC-MS with
ECNI. Mean concentrations of total HBCD in surface water ranged from 2.0e-7 to 4.4e-6 |ig/L for
the five Great Lakes (n=24), with the highest concentrations observed in Lake Ontario.
Robson et al. (2013) investigated the temporal and spatial trends of brominated flame retardants
including total HBCD in wet deposition in the Great Lakes Basin. Precipitation samples were
collected at 9 sites (Burlington, Rock Point, St. Clair, Point Pelee, Grand Bend, Point Petre, Sibley,
69
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Peer Review Draft- Do not Cite or Quote.
Turkey Lakes, and Burnt Island) in the Canadian Great Lakes between 2004 and 2010. One sample
was collected from each site every month using an automated wet deposition sampler. HBCD was
detected in 63-86% of 443 samples. Total HBCD concentrations ranged from ND to 0.06 |ig/L
(mean = 0.002 |ig/L; median = 0.00036 |ig/L). Mean concentrations of total HBCD ranged from
0.0004 to 0.0048 ug/L.
The Canadian risk assessment (EC/HC. 2011) includes one study performed by Law et at (2006b)
of dissolved phase water in the south basin of Lake Winnipeg in 2004. For a-HBCD only,
concentrations ranged from 0.000006 to 0.000013 |ig/L (mean = 0.000011 |ig/L). The researchers
commented that detection of only a-HBCD in the samples was consistent with its much greater
aqueous solubility.
Backus et at (2005) investigated HBCD levels in precipitation samples from the Great Lakes
Basin. As cited in , total HBCD concentrations ranged from ND to 0.035 |ig/L. The
average distribution of a-, P- and y-HBCD, respectively, was 77%, 15% and 8%. The number of
samples and sampling year was not reported.
Europe
There are very limited surface water monitoring data reported in available assessments of HBCD.
The few measurements reported in freshwater environment are associated with measurements
within and/or in the vicinity (upstream & downstream) of a production facility in the United
Kingdom as reported in both the Canadian risk assessment ("EC/HC. 2011) and the EU RAR (EC.
2008). The primary source for these reports is the same, Deuchar (2002). Surface water
concentrations as high as 1.52 ug/L were reported at a tributary which receives surface water from
an industrial estate before combining with STP effluent and fugitive releases to surface water.
The Australian Priority Existing Chemical Assessment Report states that no Australian monitoring
data for HBCD in water are available (NICNAS. 2012).
Two European studies measured HBCD levels in precipitation, as cited in EC/HC ( . In the
Peters (2003) study conducted in the Netherlands in 2003, total HBCD was detected in one of 50
samples at 1.835 ug/L. In the Remberger et at (2004) study, also cited as Sternbeck et at (2001)
in 008). total HBCD in deposition ranged from 0.00002 |ig/m3 in a remote area of Sweden
to 0.366 |ig/m3 in an urban area of Sweden (n = 4). In Finland, total HBCD in deposition ranged
from 0.0051 and 0.013 |ig/m3 (n = 2).
Asia
Ichihara measured HBCD in surface water samples from 19 sampling locations in the
Yodo River basin in Japan. Multiple samples were collected per sampling location and the mean
values were reported by sampling location and by river. Across all 19 sampling locations, surface
water concentrations ranged from 1.9e-4 ug/L to 1.4e-2 ug/L with an average concentration of
3.3e-3 ug/L. Average concentrations in the Kanzaki River, Yodo River, and Yamato River were
9.1e-4, 7.6e-4, and 6.7e-3 ug/L, respectively. The authors also reported flow rates and estimated
pollutant loads. It is noteworthy, that the lowest flow river, the Yamato River, had the highest
HBCD concentration.
70
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2 Sediment
5.2.1
Sediment Chart
US - Klosterhaus ct al. 2012
US-Yang ct al. 2012
AU - Anim et al. 2017
AU - Dragc ct al. 2015
CA - Moralcs-Caselles et al. 2017
CH - Kohler ct al. 2008
CN - Wang ct al. 2017
CN-Tang etal. 2015
CN - Xu ct al. 2013
CN - Feng et al. 2012
CN-Su ct al. 2015
CN-Li etal. 2016
CN-He et al. 2013
CN-Wang et al. 2016
CN-Li et al. 2013
CZ - Hlouskova et al. 2014
ES - Guerra ct al. 2010
ES - Guerra et al. 2009
GB-Yang etal. 2016
GB - Harrad et al. 2009
ID - Ilyas et al. 2011
IT - Poma et al. 2014
IT - Luigi et al. 2015
JP-Oh etal. 2014
JP - Japanese Ministry of Environment 2003
JP - Minh ct al. 2007
KP - Jcong et al. 2014
KP - Al-Odaini ct al. 2015
KP-Lee et al. 2015
KP - Ramu ct al. 2010
0.001
Background
1 10 100 1000
Concentration (ng/g ) (pt 1)
10A4
10A5
10A6
71
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
KW - Lyons et al. 2015
NL - Brandsma et al. 2014
NL - Klamer et al. 2005
NL; BE; GB - Morris et al. 2004
NO - HaukA¥s et al. 2009
NO - Evenset et al. 2007
SE - Remberger et al. 2004
SE - Sellstrom et al. 1998
SG - Zhang et al. 2015
US, CA - Letcher et al. 2015
US, CA - Marvin et al. 2006
ZA - Chokwe et al. 2016
ZA - La Guardia et al. 2013
US - La Guardia et al. 2012
CZ - Stiborova et al. 2017
ES - Eljarrat et al. 2004
ID - Ilyas et al. 2013
K.P - Al-Odaini et al. 2015
NO - Haukas et al. 2010
SE - Remberger et al. 2004
ZA - Olukunle and Okonkwo 2015
CN - Wu et al. 2010
ZA - Chokwe et al. 2015
N/A-ECHA 2008
N/A-ECHA 2017
0.001
I Background
I Near facility
Modeled
0.01
¦
0.1
1 10 100
Concentration (ng/g ) (pt 2)
1000
10A4
10A5
10A6
5.2.2 Sediment Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1443796
{Klosterhaus, 2012,
1443796)
0.1
1.7
0.3
0.3
1927611
{Yang, 2012, 1927611}
0.04
3.1
3828881
{Anim, 2017, 3828881}
0.04
9.9
0.96
1.2
3350544
{Drage, 2015,3350544}
0.056
5.3
1.8
5.3
3982731
{Morales-Caselles, 2017,
3982731}
0.0257
27.682
1927729
{Kohler, 2008, 1927729}
0.4
2.5
3546093
{Wang, 2017,3546093}
0.0365
20.25
6.31
6.31
3350536
{Tang, 2015, 3350536}
0.01
13.7
2.04
3.41
1927542
{Xu, 2013, 1927542}
0.0718
2.56
0.95
0.95
72
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1927606
{Feng, 2012, 1927606}
0.03
31.6
0.21
6.892
3350531
{Su, 2015,3350531}
0.05
25.8
0.15
3.74
3546008
{Li, 2016, 3546008}
0.43
4.02
0.43
0.43
1927551
{He, 2013, 1927551}
0.07
53.1
5.3
8.5
3350514
{Wang, 2016,3350514}
0.168
2.66
0.336
1.22
1927554
{Li, 2013, 1927554}
0.2
206.102
2343734
{FtlouAjkovAj, 2014,
2343734}
1.905
39
1040997
{Guerra, 2010, 1040997}
6.75
1873
3575325
{Guerra, 2009,3575325}
9
2430
3350516
{Yang, 2016, 3350516}
0.0025
29.5
1927694
{Harrad, 2009, 1927694}
0.88
4.8
1927663
{Ilyas, 2011, 1927663}
0.002
5.4
0.03
0.59
2528332
{Poma, 2014, 2528332}
0.005
23.7
2919854
{Luigi, 2015,2919854}
0.22
10.41
3.128
3.128
2343704
{Oh, 2014, 2343704}
5.7
7800
12.4
1526.7
4296220
{Japanese, 2003, 4296220}
11.5
140
1927778
{Minh, 2007, 1927778}
0.056
2.1
2343722
{Jeong, 2014, 2343722}
0.19
13
3.2
3.2
3350546
{Al-Odaini, 2015, 3350546}
0.09
49.9
3.94
3.94
3350542
{Lee, 2015, 3350542}
0.11
19
947611
{Ramu, 2010, 947611}
0.39
59
3350521
{Lyons, 2015, 3350521}
0.09
1.35
2528319
{Brandsma, 2014, 2528319}
0.22
90.2
683627
{Klamer, 2005, 683627}
0.1
6.9
0.8
5.2
1927817
{Morris, 2004, 1927817}
0.2
1680
3.2
199
1927703
{HaukA/A¥s, 2009,
1927703}
10
18000
35
9000
469357
{Evenset, 2007, 469357}
4.31
4.31
1927826
{Remberger, 2004,
1927826}
0.2
1.5
1715539
{Sellstrom, 1998, 1715539}
11
7000
11
11
3350497
{Zhang, 2015, 3350497}
0.071
0.525
3350541
{Letcher, 2015, 3350541}
0.0375
1.6
1927800
{Marvin, 2006, 1927800}
0.0375
3.65
3545930
{Chokwe, 2016, 3545930}
16
54
42
42
1927534
{La Guardia, 2013,
1927534}
0.3
27500
349
1800
1927601
{La Guardia, 2012,
1927601}
12192
389700
3546060
{Stiborova, 2017,3546060}
0.4
11.57
7.04
7.04
999290
{Eljarrat, 2004, 999290}
89.7
513.6
2149566
{Ilyas, 2013, 2149566}
0.049
0.52
0.049
0.14
3350546
{Al-Odaini, 2015, 3350546}
2.07
17.98
73
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1927670
{HaukA¥s, 2010, 1927670}
190
85000
300
40000
1927826
{Remberger, 2004,
1927826}
0.05
25
3016112
(Olukunle, 2015,3016112}
0.0125
186
33
33
1927678
{Wu, 2010, 1927678}
169
169
3350535
{Chokwe, 2015, 3350535}
15
52
3970747
{ECHA, 2008, 3970747}
0.013
170000
3970753
{ECHA, 2017, 3970753}
0.018
56
5.2.3 Sediment: Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality
Level
dry
{Klosterhaus,
2012, 1443796}
US
Background
2007
10
1
N/R
1.7
Medium
{Yang, 2012,
1927611}
US
Background
2007
16
N/R
N/R
1.6
High
{Anim, 2017,
3828881}
AU
Background
2014 -
2015
48
N/R
N/R
1.3
High
{Drage, 2015,
3350544}
AU
Background
1850 -
2014
30
0.8
N/R
1.7
Medium
{Morales-
Case lies, 2017,
3982731}
CA
Background
2011
7
0.58
0
1.8
Medium
{Kohler, 2008,
1927729}
CH
Background
1974 -
2001
5
1
N/R
1.9
Medium
{Wang, 2017,
3546093}
CN
Background
2016
23
0.96
0.073
1.9
Medium
{Tang, 2015,
3350536}
CN
Background
2012
40
1
N/R
1.4
High
{Xu, 2013,
1927542}
CN
Background
2010
12
0.83
0.14
1.8
Medium
{Feng, 2012,
1927606}
CN
Background
2009 -
2010
121
N/R
N/R
1.8
Medium
74
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality
Level
dry
{Su, 2015,
3350531}
CN
Background
2010
40
N/R
0.003
1.7
Medium
{Li, 2016,
3546008}
CN
Background
2010
17
N/R
0.08
1.4
High
{He, 2013,
1927551}
CN
Background
2009
80
N/R
N/R
1.3
High
{Wang, 2016,
3350514}
CN
Background
2009
26
N/R
0.003
1.9
Medium
{Li, 2013,
1927554}
CN
Background
2003 -
2004
34
0.59
0.4
1.4
High
{HlouAjkovAj,
2014, 2343734}
cz
Background
2010
31
0.96
3.8
1.7
Medium
{Guerra, 2010,
1040997}
ES
Background
2006
7
0.71
14
1.6
High
{Guerra, 2009,
3575325}
ES
Background
2002 -
2006
12
N/R
9
2
Medium
{Yang, 2016,
3350516}
GB
Background
2011 -
2012
74
0.76
0.005
1.9
Medium
{Harrad, 2009,
1927694}
GB
Background
2008 -
2009
9
1
N/R
1.7
Medium
{Ilyas, 2011,
1927663}
ID
Background
2008
33
0.94
N/R
2.0
Medium
{Poma, 2014,
2528332}
IT
Background
2011 -
2012
17
0.9
0.01
1.6
High
{Luigi, 2015,
2919854}
IT
Background
2010
5
1
0.011
1.9
Medium
{Oh, 2014,
2343704}
JP
Background
2011
17
1
N/R
1.4
High
{Japanese, 2003,
4296220}
JP
Background
2003
1
0.07
23
2.6
Low
75
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality
Level
dry
{Minh, 2007,
1927778}
JP
Background
2002
9
1
0.01
2.1
Medium
{Jeong, 2014,
2343722}
KP
Background
2010
12
1
0.02
1.3
High
{Al-Odaini, 2015,
3350546}
KP
Background
2010
19
1
N/R
1.9
Medium
{Lee, 2015,
3350542}
KP
Background
2009
24
1
0.006
1.6
High
{Ramu, 2010,
947611}
KP
Background
2005
29
1
N/R
1.4
High
{Lyons, 2015,
3350521}
KW
Background
2013 -
2014
29
1
N/R
1.4
High
{Brandsma, 2014,
2528319}
NL
Background
2008
6
1
0.5
2.0
Medium
{Klamer, 2005,
683627}
NL
Background
2000
10
0.9
0.2
2.1
Medium
{Morris, 2004,
1927817}
NL; BE;
GB
Background
1999 -
2002
77
N/R
1.2
2.3
Low
{HaukA/A¥s,
2009, 1927703}
NO
Background
2006 -
2007
25
1
0.005
1.8
Medium
{Evenset, 2007,
469357}
NO
Background
2001
1
1
0.06
2.2
Medium
{Remberger,
2004, 1927826}
SE
Background
1943 -
1997
6
1
0.1
1.8
Medium
{Sellstrom, 1998,
1715539}
SE
Background
1995
9
0.78
N/R
2.0
Medium
{Zhang, 2015,
3350497}
SG
Background
2014
12
1
0.007
1.7
High
{Letcher, 2015,
3350541}
US, CA
Background
2004
37
0.35
0.075
1.7
Medium
76
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality
Level
dry
{Marvin, 2006,
1927800}
US, CA
Background
2001
63
0.67
0.075
1.8
Medium
{Chokwe, 2016,
3545930}
ZA
Background
2013
6
1
N/R
1.7
Medium
{La Guardia,
2013, 1927534}
ZA
Background
2011
45
0.69
0.6
1.9
Medium
{La Guardia,
2012, 1927601}
US
Near facility
2009
5
N/R
1
1.7
Medium
{Stiborova, 2017,
3546060}
cz
Near facility
2016
12
0.58
0.8
1.7
Medium
{Eljarrat, 2004,
999290}
ES
Near facility
2002
2
N/R
N/R
1.8
Medium
{Ilyas, 2013,
2149566}
ID
Near facility
2008
5
0.8
N/R
1.4
High
{Al-Odaini, 2015,
3350546}
KP
Near facility
2010
10
1
N/R
1.9
Medium
{HaukA¥s, 2010,
1927670}
NO
Near facility
2007
8
1
270
1.9
Medium
{Remberger,
2004, 1927826}
SE
Near facility
2000
8
0.38
0.1
1.8
Medium
{Olukunle, 2015,
3016112}
ZA
Near facility
2013
18
0.2
N/R
1.8
Medium
77
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Wu, 2010,
1927678}
CN
Background
2006
3
0.5
N/R
2.0
Medium
{Chokwe,
2015,
3350535}
ZA
Near facility
2013
12
1
0.48
1.6
High
{ECHA,
2008,
3970747}
N/A
Modeled
N/A
N/A
N/A
N/A
1.3
High
{ECHA,
2017,
3970753}
N/A
Modeled
N/A
N/A
N/A
N/A
2
Medium
5.2.3.1.1 North America
The Canadian and Australian risk assessments (NICNAS. 2012; EC/HC. 2011) summarized
sediment data from two studies conducted in North America. Law et al. (2014) reported sediment
concentrations of 0.05 |ig/kg dw from four sites in Lake Winnipeg. In this study, y-HBCD was
detected (Law et al.. 2006b). Marvin et al. (2006) measured HBCD in suspended sediments from
nine locations in the Detroit River, noting an association between magnitude of concentration and
proximity to urban and industrial areas. HBCD concentrations ranged from ND to 3.7 (J,g/kg dw,
with the highest levels being found downstream of the urban region surrounding the city of Detroit.
Mean concentrations ranged from 0.012 to 1.14 (J,g/kg dw (Marvin et al.. 2006).
Yang et al. (2012) measured brominated flame retardants in 16 sediment core samples collected
from the Great Lakes (Superior, Michigan, Huron, Erie, and Ontario) during August 2007.
Samples were analyzed for total HBCD using GC-MS. Total HBCD concentrations ranged from
0.04 to 3.1 |ig/kg dw in all sediment samples (n = 16). The detection rate for total HCBD was 82%
for samples deposited 1950 or later.
Letcher etal. (2015) measured HCBD in bottom sediment samples collected from the Detroit River
and Lake Erie (western, central, and eastern basins) and sludge from two Windsor, Ontario
WWTPs that feed into the Detroit River, between May and June 2004. Sediment subsamples (n =
37) were obtained from the "top" 10 cm of a 30-cm core sample from Lake Erie (n = 18 sites) and
the Detroit River (n = 17 sites) and were analyzed for total HBCD using LC-MS/MS with ESI in
the negative mode. Total HBCD concentrations ranged from ND to 1.60 |ig/kg dw in all sediment
samples (n = 37).
78
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
La Guardia < measured HBCD in river sediment, bivalve, and gastropod at the outfall
and downstream from a textile facility in North Carolina. Sediment concentrations decreased with
distance from the outfall. HBCD concentrations ranged from 389,700 ug/kg at the outfall to 12,192
ug/kg 44 kilometers downstream.
5.2.3.1.2 Europe
The Australian, Canadian, UNEP, and EU risk assessments (' 1" * , " . ; « hn , < " , ;
UNEP. 2010; EC. 2008) summarized sediment data from sixteen studies conducted in Europe. As
discussed in the EU RAR ("EC. 2008). total HBCD concentrations ranged over several orders of
magnitude, from ND in unpolluted areas to over 30,000 |ig/kg in areas where HBCD is produced
and used. The average HBCD concentrations calculated in EC (2008) for areas near point sources
was 338 ug/kg, while the average HBCD concentration for areas not impacted by point sources
was 31 |ig/kg. For areas impacted by point sources, 90th percentile and maximum HBCD sediment
concentrations were reported as 270 ug/kg and 33,500 ug/kg, while for areas not impacted by point
sources, 90th percentile and maximum HBCD sediment concentrations were reported as 100 |ig/kg
and 511 ug/kg, respectively. High-end sediment concentrations are likely below the maximum and
above the 90th percentile. A 95th percentile value or similar estimate of high-end sediment
concentrations was not reported.
5.2.3.1.3 Asia
The UNEP assessment and Law et at (2014) summarized Asian sediment data from four studies,
shown in the table below. Overall, total HBCD concentrations ranged from ND to 634 |ig/kg dw.
Studies in Asia and in other locations report a correlation between proximity to sources emitting
HBCD and elevated levels in sediment. Sampling locations upstream from or further away from
point sources generally reported lower levels of HBCD in sediment (Law et at. ). Sediment
dwelling organisms such as mussels, oysters, and other bivalves are additional potential human
exposure pathways in addition to fish consumption.
Surface sediment from Jinhae Bay and Masan Bay on the southeastern coast of South Korea was
investigated by Al-Odaini for the presence of HBCD in samples collected in March
2010. Sediment samples were collected from industrialized areas, sewage effluent-receiving areas,
urbanized areas, a shipbuilding yard, and aquaculture farms and were analyzed for total HBCD
using LC-MS/MS with APCI. Total HBCD surface concentrations ranged from 0.09 to 49.9 |ig/kg
dw (3.94 |ig/kg dw median) in all sediment samples (n = 19). The highest surface sediment
concentrations (25.6 to 49.9 |ig/kg dw) were measured at sites near the aquaculture farm. In
addition, to evaluate whether a WWTP that feeds into Masan Bay could be a point source of
HBCD, 10 sediment samples were collected from three transects originating from the plant outfall.
Total HBCD surface sediment concentrations ranged from 2.07 to 17.98 |ig/kg dw in all sediment
samples from the transects (n = 10).
79
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.4 Soil
5.2.4.1.1 Soil Chart
BE - Covaci et al. 2009
Background
Near facility
Modeled
CN - Tang et al. 2014
CN - Wu et al. 2016
CN - Wang et al. 2013
CN - Li et al. 2016
CN - Meng et al. 2011
CN-Zhuetal. 2014
CN - Yu et al. 2008
CN - Wang et al. 2009
ID - Ilyas et al. 2011
KH; IN; ID; MY; VN - Eguchi et al. 2013
SE - Newton et al. 2015
CN - Tang et al. 2014
CN - Gao et al. 2011
ID - Ilyas et al. 2011
KH; IN; ID; MY; VN - Eguchi et al. 2013
SE - Rembergcr et al. 2004
N/A- EC HA 2008
N/A- ECHA 2017
0.001 0.01 0.1
10 100 1000 10A4 10A5
Concentration (ng/g )
5.2.4.1.2 Soil Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
787649
{Covaci, 2009,
787649)
0.05
6.6
0.18
1.67
2343699
{Tang, 2014,
2343699)
0.01
37.8
7.75
31.8
3223093
{Wu, 2016,
3223093)
0.3
249
1.87
12.1
1927586
{Wang, 2013,
1927586)
0.17
34.5
1.56
5.5
3546008
{Li, 2016,
3546008)
0.09
3.4
1058212
{Meng, 2011,
1058212)
0.0067
0.0938
0.0233
0.0233
2343705
{Zhu, 2014,
2343705)
0.3
280
5.91
5.91
80
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1049627
{Yu, 2008,
1049627)
1.7
5.6
1927688
{Wang, 2009,
1927688}
0.17
7.66
0.534
1.76
1927642
{Ilyas, 2011,
1927642)
0.04
1.8
1927572
{Eguchi, 2013,
1927572}
0.005
1.4
0.05
0.54
2911989
{Newton, 2015,
2911989}
0.35
12
1.6
1.7
2343699
{Tang, 2014,
2343699}
6.27
103
37.9
67.4
1927645
{Gao, 2011,
1927645}
0.03
29.9
0.31
9.99
1927642
{Ilyas, 2011,
1927642}
0.016
1.4
1927572
{Eguchi, 2013,
1927572}
0.0025
2.4
0.04
1.1
1927826
{Remberger, 2004,
1927826}
140
1300
3970747
{ECHA, 2008,
3970747}
1.7
91000
3970753
{ECHA, 2017,
3970753}
0.45
2.2
5.2.4.1.3 Soil: Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g
)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Covaci, 2009,
787649}
BE
Background
2006-
2007
20
0.75
0.1
1.8
Medium
{Tang, 2014,
2343699}
CN
Background
2012
90
0.92
0.02
1.6
High
{Wu, 2016,
3223093}
CN
Background
2012
37
1
0.03
1.6
High
{Wang, 2013,
1927586}
CN
Background
2010-
2011
72
1
N/R
1.9
Medium
{Li, 2016,
3546008}
CN
Background
2010
17
N/R
0.08
1.4
High
81
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g
)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Meng, 2011,
1058212}
CN
Background
2009
22
0.86
0.013
1.3
High
{Zhu, 2014,
2343705}
CN
Background
2008
38
N/R
0.003
1.8
Medium
{Yu, 2008,
1049627}
CN
Background
2006
3
N/R
N/R
3
Low3
{Wang, 2009,
1927688}
CN
Background
2006
17
N/R
0.34
1.4
High
{Ilyas, 2011,
1927642}
ID
Background
2008
17
0.88
N/R
1.7
Medium
{Eguchi, 2013,
1927572}
KH; IN;
ID; MY;
VN
Background
1999-
2007
24
N/R
0.005
1.4
High
{Newton, 2015,
2911989}
SE
Background
2012
8
1
N/R
2.0
Medium
{Tang, 2014,
2343699}
CN
Near facility
2012
90
0.92
0.02
1.6
High
{Gao, 2011,
1927645}
CN
Near facility
2006-
2008
32
1
0.011
1.4
High
{Ilyas, 2011,
1927642}
ID
Near facility
2008
6
1
N/R
1.7
Medium
{Eguchi, 2013,
1927572}
KH; IN;
ID; MY;
VN
Near facility
1999-
2007
42
N/R
0.005
1.4
High
{Remberger,
2004, 1927826}
SE
Near facility
2000
3
1
N/R
1.8
Medium
{ECHA, 2008,
3970747}
N/A
Modeled
N/A
N/A
N/A
N/A
1.3
High
{ECHA, 2017,
3970753}
N/A
Modeled
N/A
N/A
N/A
N/A
2
Medium
3 Study evaluation score was downgraded from medium to low based on professional judgement.
82
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.4.1.4 Europe
As cited in the secondary source international risk assessments (I 1" *, " . ; < : ;
UNEP. 2010; EC. 2008). six studies present HBCD concentrations in soil collected from industrial
sites in the United Kingdom and Sweden. Overall, total HBCD concentrations ranged from 10 to
89,600 |ig/kg dw. The highest concentration was observed at a flame retardant
formulator/compounder plant, followed by a backcoater (up to 61,000 |ig/kg dw), under cellular
plastic of railway embankments (up to 45,000 |ig/kg dw), and at XPS-producing facilities (up to
23,200 |ig/kg dw).
5.2.4.1.5 Asia
The Canadian risk assessment identified one study ( at. 2008a) which measured HBCD in
soil samples collected in China in 2006. Total HBCD concentrations ranged from 1.7 to 5.6 |ig/kg
dw in three samples.
Law identified four studies conducted in Asia. Total HBCD concentrations from
samples collected in rural, urban, agricultural and industrial areas of China and Indonesia ranged
from ND to 35 |ig/kg dw, with the exception of a maximum value of 284 |ig/kg dw from an e-
waste recycling site. Reported central tendency values were 3.0 |ig/kg dw (median) for farms in
southeast Beijing, 0.22 to 0.79 |ig/kg dw (means) for industrial areas in south China, and 0.31 to
10 |ig/kg dw (means) in e-waste areas of south China.
Tang et e collected 90 samples from the Ningbo Region in China. Land-use was explicitly
considered as soil samples were collected from six different land-uses. There are likely differences
between countries regarding the overall magnitude of HBCD concentrations in soil. However, the
differences across HBCD concentrations by land use categories may be similar across countries.
The overall range of soil concentrations reported was ND (farmland areas) to 103 |ig/kg (industrial
areas) with land-use highly influencing the overall magnitude of reported soil concentrations.
83
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.5 Indoor Dust
5.2.5.1.1 Indoor Dust Chart
g Commercial
I Industrial
I Mixed use
Residential
BE - D'Hollander ct al. 2010
BE - Roosens ct al. 2010
CN-Caoctal. 2015
CN-Ni and Zeng 2013
EG - Hassan and Shoeib 2014
GB - Abdallah ct al. 2008
GB - Abdallah and Harrad 2009
GB - Abdallah ct al. 2008
JP - Takigami et al. 2009
Multiple - Santillo et al. 2001
SE - Newton et al. 2015
SE - Thuresson et al. 2012
CN-Zcng et al. 2016
US - Allgood et al. 2016
BE - Al Bitar 2004
CN - Qi ct al. 2014
JP - Takigami et al. 2008
US - Stapleton ct al. 2014
US - Schreder and La Guardia 2014
US - Dodson etal. 2012
US - Stapleton et al. 2008
US - Johnson ct al. 2013
BE - D'Hollander ct al. 2010
BE - Roosens et al. 2010
BE - Roosens ct al. 2009
CA- Shoeib ct al. 2012
CH - Gerecke ct al. 2008
CS - Kalachova et al. 2012
DE - Kopp etal. 2012
DE - Fromme et al. 2014
100 1000 10M
Concentration ( ng/g ) (pt 1)
84
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Residential
School
Vehicle
EG - Hassan and Shoeib 2014
GB - Abdallah et al. 2008
GB - Abdallah et al. 2008
GB - Abdallah and Harrad 2009
GB; CA; US - Abdallah et al. 2008
GB; Multiple - Santillo et al. 2003
GB; Multiple - Santillo et al. 2003
JP - Mizouchi et al. 2015
JP - Takigami et al. 2009
Multiple; US - Abb et al. 2011
NZ-Alietal. 2012
PT - Coelho et al. 2016
RO - Dirtu et al. 2012
RO - Dirtu and Covaci 2010
SE - Sahlstrom et al. 2012
SE - Newton et al. 2015
SE - Sahlstrom et al. 2015
SE - Bjorklund et al. 2012
SE - Thuresson et al. 2012
VN-Tueetal. 2013
CN-Caoetal. 2015
GB - Harrad et al. 2010
JP - Mizouchi et al. 2015
SE - Newton et al. 2015
US - Allen et al. 2013
CS - Kalachova et al. 2012
GB - Harrad and Abdallah 2011
GB - Abdallah et al. 2008
GB - Abdallah and Harrad 2009
0.1
100 1000 10M
Concentration ( ng/g ) (pt 2)
5.2.5.1.2 Indoor Dust Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1578505
{D'Hollander, 2010, 1578505}
256
1153
367
592
1927685
{Roosens, 2010, 1927685}
1288.73
5836.79
1288.73
1288.73
3016880
{Cao, 2015, 3016880}
360
1140
1927552
{Ni, 2013, 1927552}
652
122973
2621
7276
2528318
{Hassan, 2014, 2528318}
19
37
1079114
{Abdallah, 2008, 1079114}
90
6600
760
2700
787630
{Abdallah, 2009, 787630}
279
4004
1079430
{Abdallah, 2008, 1079430}
90
3600
650
1400
1927720
{Takigami, 2009, 1927720}
72
1300
740
740
85
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1003986
{Santillo, 2001, 1003986}
1.25
1400
19.5
19.5
2911989
{Newton, 2015,2911989}
17
2900
100
270
1927620
{Thuresson, 2012, 1927620}
6.8
5700
54
340
3350480
{Zeng, 2016, 3350480}
0.6
57000
55
5700
3455810
{Allgood, 2016, 3455810}
89
799
326
393
1007825
{AlBitar, 2004, 1007825}
10
57554
4805
4805
2528328
{Qi, 2014, 2528328}
1.35
6100
120
410
1927735
{Takigami, 2008, 1927735}
2800
2800
2343712
{Stapleton, 2014, 2343712}
77.6
2658
2528320
{Schreder, 2014, 2528320}
0.5
3160
2557649
{Dodson, 2012, 2557649}
39
6800
160
190
697789
{Stapleton, 2008, 697789}
2.25
130200
144
354
1676758
{Johnson, 2013, 1676758}
107
1999
197
246
1578505
{D'Hollander, 2010, 1578505}
5
42692
130
1735
1927685
{Roosens, 2010, 1927685}
140.33
4092.74
140.33
140.33
787720
{Roosens, 2009, 787720}
33
758
114
160
1927609
{Shoeib, 2012, 1927609}
20
4700
270
450
1927965
{Gerecke, 2008, 1927965}
800
1400
1100
1100
1927573
{Kalachova, 2012, 1927573}
0.15
949.5
92.6
177.7
1928011
{Kopp, 2012, 1928011}
295.03
295.03
2343719
{Fromme, 2014, 2343719}
53
4041
345
620
2528318
{Hassan, 2014, 2528318}
6
6
1079114
{Abdallah, 2008, 1079114}
140
140000
1300
8300
1927749
{Abdallah, 2008, 1927749}
50
111000
150
150
787630
{Abdallah, 2009, 787630}
228
140774
1079430
{Abdallah, 2008, 1079430}
64
110000
390
6000
1006146
{Santillo, 2003, 1006146}
790
6900
895
3250
3809265
{Santillo, 2003, 3809265}
790
6900
3158
3250
3015040
{Mizouchi, 2015, 3015040}
28.033
851.84
70
183.366
198241
{Takigami, 2009, 198241}
140
13000
787629
{Abb, 2011, 787629}
30
15000
166
945
1927602
{Ali, 2012, 1927602}
20
4100
190
460
3350460
{Coelho, 2016, 3350460}
16
2000
150
380
1927581
{Dirtu, 2012, 1927581}
4
2190
325
420
1061566
{Dirtu, 2010, 1061566}
30
365
190
190
1927594
{SahlstrAUm, 2012, 1927594}
100
4100
246
246
2911989
{Newton, 2015,2911989}
23
110
57
57
3012178
{SahlstrAUm, 2015, 3012178}
20
6000
110
161
1927616
{BjATjrklund, 2012, 1927616}
5.9
95000
8.9
110
1927620
{Thuresson, 2012, 1927620}
3
2400
45
100
1927567
{Tue, 2013, 1927567}
0.99
61
8.05
8.05
3016880
{Cao, 2015, 3016880}
1260
1260
1076646
{Harrad, 2010, 1076646}
72
89000
4100
8900
86
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
3015040
{Mizouchi, 2015, 3015040}
20.33
2334.465
180
507.427
2911989
{Newton, 2015,2911989}
380
640
1597662
{Allen, 2013, 1597662}
180
1100000
7600
10000
1927573
{Kalachova, 2012, 1927573}
0.15
241.4
32.7
56.6
1082335
{Harrad, 2011, 1082335}
288
23722
1300
9200
1079114
{Abdallah, 2008, 1079114}
190
69000
13000
19000
787630
{Abdallah, 2009, 787630}
194
55822
5.2.5.1.3 Indoor Dust: Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{D'Hollander,
2010, 1578505}
BE
Commercial
2008
10
1
N/R
1.6
High
{Roosens, 2010,
1927685}
BE
Commercial
2008
10
1
N/R
1.5
High
{Cao, 2015,
3016880}
CN
Commercial
2012
65
N/R
1.5
1.8
Medium
{Ni, 2013,
1927552}
CN
Commercial
2009
56
N/R
N/R
1.4
High
{Hassan, 2014,
2528318}
EG
Commercial
2013
14
N/R
N/R
2.0
Medium
{Abdallah, 2008,
1079114}
GB
Commercial
2006 -
2007
32
1
0.1
1.3
High
{Abdallah, 2009,
787630}
GB
Commercial
2007
21
1
0.3
1.2
High
{Abdallah, 2008,
1079430}
GB
Commercial
2006
6
1
N/R
1.8
Medium
{Takigami, 2009,
1927720}
JP
Commercial
2006
8
1
20
1.7
Medium
{Santillo, 2001,
1003986}
Multiple
Commercial
2000 -
2001
7
0.7
2.5
2
Medium
87
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Newton, 2015,
2911989}
SE
Commercial
2012
21
1
N/R
2.0
Medium
{Thuresson, 2012,
1927620}
SE
Commercial
2006
37
N/R
N/R
1.7
Medium
{Zeng, 2016,
3350480}
CN
Industrial
2013
48
0.92
1.2
1.2
High
{Allgood, 2016,
3455810}
US
Mixed use
2013
20
1
1
1.3
High
{A1 Bitar, 2004,
1007825}
BE
Mixed use
2003
23
0.26
20
3.0
Low
{Qi, 2014,
2528328}
CN
Mixed use
2010 -
2011
81
0.99
2.7
1.4
High
{Takigami, 2008,
1927735}
JP
Mixed use
2005
15
0.2
0.4
1.8
Medium
{Stapleton, 2014,
2343712}
US
Residential
2012
30
1
N/R
1.8
Medium
{Schreder, 2014,
2528320}
us
Residential
2011 -
2012
20
0.95
1
2.0
Medium
{Dodson, 2012,
2557649}
us
Residential
2006 -
2011
32
1
5
1.4
High
{Stapleton, 2008,
697789}
us
Residential
2006
35
0.95
4.5
2.1
Medium
{Johnson, 2013,
1676758}
us
Residential
2002 -
2003
38
0.97
N/R
2.1
Medium
{D'Hollander,
2010, 1578505}
BE
Residential
2008
43
1
N/R
1.6
High
{Roosens, 2010,
1927685}
BE
Residential
2008
43
1
N/R
1.5
High
{Roosens, 2009,
787720}
BE
Residential
2007
16
1
N/R
1.4
High
88
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Shoeib, 2012,
1927609}
CA
Residential
2007 -
2008
116
1
N/R
2.0
Medium
{Gerecke, 2008,
1927965}
CH
Residential
2003 -
2007
3
1
N/R
1.8
Medium
{Kalachova,
2012, 1927573}
CS
Residential
2008
24
0.88
0.3
1.7
Medium
{Kopp, 2012,
1928011}
DE
Residential
N/R
5
1
3
1.8
Medium
{Fromme, 2014,
2343719}
DE
Residential
N/R
20
1
1
2.0
Medium
{Hassan, 2014,
2528318}
EG
Residential
2013
17
N/R
N/R
2.0
Medium
{Abdallah, 2008,
1079114}
GB
Residential
2006 -
2007
45
1
0.1
1.3
High
{Abdallah, 2008,
1927749}
GB
Residential
2007
37
1
0.2
1.7
Medium
{Abdallah, 2009,
787630}
GB
Residential
2007
21
1
0.3
1.2
High
{Abdallah, 2008,
1079430}
GB; CA;
US
Residential
2006
52
1
N/R
1.8
Medium
{Santillo, 2003,
1006146}
GB;
Multiple
Residential
2002
12
1
2.5
1.6
High
{Santillo, 2003,
3809265}
GB;
Multiple
Residential
2002
102
1
13
2.2
Medium
{Mizouchi, 2015,
3015040}
JP
Residential
2009 -
2010
10
1
20
1.9
Medium
{Takigami, 2009,
198241}
JP
Residential
2006
2
N/R
N/R
1.9
Medium
{Abb, 2011,
787629}
Multiple;
US
Residential
2011
28
1
N/R
1.9
Medium
89
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Ali, 2012,
1927602}
NZ
Residential
2008
50
1
N/R
1.9
Medium
{Coelho, 2016,
3350460}
PT
Residential
2010 -
2011
28
1
0.23
2.0
Medium
{Dirtu, 2012,
1927581}
RO
Residential
2010
47
1
6
1.3
High
{Dirtu, 2010,
1061566}
RO
Residential
2007
18
1
N/R
2.6
Low
{SahlstrA'm.
2012,1927594}
SE
Residential
2012
6
1
N/R
1.9
Medium
{Newton, 2015,
2911989}
SE
Residential
2012
4
1
N/R
2
Medium
{SahlstrA'm.
2015, 3012178}
SE
Residential
2009 -
2010
27
1
N/R
1.7
Medium
{BjA'rklund.
2012, 1927616}
SE
Residential
2008 -
2009
37
0.87
9
1.9
Medium
{Thuresson, 2012,
1927620}
SE
Residential
2006
54
N/R
3
1.7
Medium
{Tue, 2013,
1927567}
VN
Residential
2008
13
1
N/R
1.9
Medium
{Cao, 2015,
3016880}
CN
School
2012
2
N/R
1.5
1.8
Medium
{Harrad, 2010,
1076646}
GB
School
2007 -
2008
36
0.83
N/R
2.0
Medium
{Mizouchi, 2015,
3015040}
JP
School
2009 -
2010
18
1
20
1.9
Medium
{Newton, 2015,
2911989}
SE
School
2012
4
1
N/R
2.0
Medium
{Allen, 2013,
1597662}
US
Vehicle
2010
40
1
0.12
2.1
Medium
90
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Kalachova,
2012, 1927573}
CS
Vehicle
2008
26
0.97
0.3
1.7
Medium
{Harrad, 2011,
1082335}
GB
Vehicle
2009
42
1
N/R
2.0
Medium
{Abdallah, 2008,
1079114}
GB
Vehicle
2006 -
2007
20
1
0.1
1.3
High
{Abdallah, 2009,
787630}
GB
Vehicle
2007
12
1
0.3
1.2
High
5.2.5.1.4 North America
NICNAS (2012) and EC (2008) provided HBCD measurements in home and office dust samples
from three studies conducted in the United States and Canada (Abdallah et al.. 2008a; Stapleton et
al.. 2008; Stapleton et al.. 2004). Stapleton et al. (2004) analyzed settled dust particles <1000 |j,m
collected from 17 houses in the United States. Total HBCD concentrations ranged from ND to 925
|ig/kg (median = 140 |ig/kg). Stapleton et al. (2008) analyzed dust samples from the living room
of homes in the US (n = 16). Total HBCD concentrations ranged from ND to 130,200 |ig/kg
(geometric mean = 354 ng/kg, median = 230 |ig/kg). Bedrooms and home vacuum bags were also
sampled in Stapleton et al. (2008). but results were not reported in the secondary sources. Abdallah
et al. (2008a) measured HBCD in the dust vacuumed from 13 US homes and 8 Canadian homes.
Total HBCD concentrations in the US homes ranged from 110 to 4,000 |ig/kg (mean = 810 |ig/kg;
median = 390 |ig/kg). In the Canadian homes, total HBCD concentrations ranged from 64 to 1,300
|ig/kg (mean = 670 |ig/kg; median = 640 |ig/kg).
Stapleton et al. (2009) investigated levels of flame retardants in household dust collected between
2002 and 2007. The dust samples (n = 50) were collected from home vacuum cleaner bags in
Boston, Massachusetts. Sieved dust samples were extracted using pressurized fluid extraction and
then analyzed for brominated flame retardants using GC-MS in ECNI. Total HBCD was detected
in 92% of the samples and ranged from ND to 2,750 |ig/kg (geometric mean = 166 |ig/kg).
Dodson et al. (2012) measured flame retardants in dust samples collected in 16 California homes
in 2011. This study was a repeat of a previous study that was conducted in 2006 at the same 16
homes. The samples were collected, from surfaces in the living areas, using a vacuum equipped
with a cellulose extraction thimble and analyzed by HPLC-MS/MS with ESI. Results were similar
across time periods. Total HBCD was detected in 100% of the dust samples and ranged from 82
to 6,800 |ig/kg (median = 190 |ig/kg) in 2006 and from 39 to 1,800 |ig/kg (median = 160 |ig/kg)
in 2011.
91
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Shoeib et at (201.2) measured flame retardants in dust samples collected from homes located in
Vancouver, Canada, between 2007 and 2008 as part of the Chemicals Health and Pregnancy
(CHirP) study. Dust samples, obtained by sampling either vacuum cleaner bags or canisters from
bag-less or central vacuums, were analyzed for the flame retardants using GC-MS with ECNI.
Total HBCD was detected in all samples (n = 116) with concentrations that ranged from 20 to
4,700 |ig/kg (mean = 450 |ig/kg; median = 270 |ig/kg). According to the study authors, HBCD
was the second most abundant flame retardant found in the dust samples.
Allen et investigated the potential for exposure to flame retardant chemicals from dust
found within airplanes. Because flame retardants are used in the manufacture of materials found
on airplanes to slow the propagation of fire within an aircraft, exposure to high levels of flame
retardants was expected. A total of 40 dust samples were collected between November and
December of 2010 from carpeted floors and low-lying air return vents located on the walls of 19
commercial airplanes that were parked overnight at an unidentified international airport in the
United States. The samples were collected using a canister vacuum equipped with a cellulose
extraction thimble, extracted using a pressurized solvent extraction method, and analyzed by GC-
MS. Samples collected from floor and vent displayed similar range and central tendencies. Total
HBCD was detected in 100% of the dust samples and ranged from 180 to 1,100,000 |ig/kg (median
= 7,600-10,000 |ig/kg).
Johnson studied the correlation between flame retardants in house dust and men's
hormone levels. Serum hormone data used in this study were taken from a separate ongoing study
on environmental exposures and male reproductive health. A subset of the men from the study,
recruited between 2002 and 2003, provided used vacuum bags from their homes. Dust from these
vacuum bags was analyzed for the brominated flame retardants using GC-MS with ECNI. Total
HBCD concentrations in the dust samples (n = 38) ranged from ND to 1,999 |ig/kg (mean = 246
|ig/kg; geometric mean =197 |ig/kg).
Schreder and La Guard measured flame retardants in house dust samples and in domestic
sewage (laundry wastewater) collected from homes located in Vancouver and Longview,
Washington state in 2011 and 2012. Dust samples were obtained using a vacuum fitted with a
cellulose filter held in the crevice tool with a stainless-steel ring. Samples were analyzed for the
flame retardants using UPLC-MS/MS with atmospheric pressure photoionization (APPI). Total
HBCD was detected in all but one of the samples (n = 20) with concentrations that ranged from
ND to 3,160 |ig/kg (mean = 649 |ig/kg; median = 300 |ig/kg).
Stapleton et at (2014) measured flame retardants in hand wipe and house dust samples collected
from homes located in North Carolina during the spring of 2012. Dust samples were collected on
both hardwood and carpeted floors by using a vacuum cleaner with a cellulose thimble inserted in
the hose attachment. Samples were analyzed for flame retardants using GC-MS. Total HBCD was
detected in all samples (n = 30) with concentrations that ranged from 77.6 to 2,658 |ig/kg
(geometric mean = 338 |ig/kg). The results for hand wipes are provided in the Hand Wipe section
in this Appendix.
5.2.5.1.5 Europe
provided a relatively comprehensive compilation of HBCD concentrations in
indoor dust samples collected in Europe, as reported from eight studies (D'Hollander et at. <1. < >;
92
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Dirtu and Covaci. 2010; Harracl et at. 2010; Abdallah et al.. 2008a; Santillo ei .l>; antillo
et. al.. 2003a; Leonards et al. 2001; Santillo et al.. 2001). The results for some of these studies
were also reported in EC/HC ( and 08). The studies sampled dust from homes, office
buildings, schools, and daycare centers from 12 countries (United Kingdom, Belgium, France,
Romania, Spain, Germany, Italy, Austria, Denmark, Finland, Sweden and the Netherlands).
Samples were generally collected using a vacuum cleaner and were analyzed as individual or
pooled samples by HPLC or GC-MS. Particle sizes of the dust samples analyzed varied. Overall,
total HBCD concentrations in these dust samples ranged from ND to 110,000 |ig/kg (means = 225
to 8,900 |ig/kg; medians = 130 to 4,100 |ig/kg). HBCD was detected in the majority of the samples.
As noted in ' 1" <>¦ ,, there is a large variation of measured HBCD levels, with a few
extreme residues observed in both UK and US samples (discussed above). NICNAS (
combined the UK dust samples from Abdallah et al. (2008a) and Harrad et al. (201.0). and
determined the data exhibit a log normal distribution. N 31.2) selected the 75th percentile
(5,450 ng/kg) and 95th percentile (35,630 |~ig/kg) to represent typical and worst-case values,
respectively.
Two additional studies were conducted in the United Kingdom (Abdallah et al.. 2008b) and
Belgium (Roosens et al.. 2009). as reported in EC/HC (201.1). The dust samples were collected
from homes, offices, cars, and public microenvironments. Results were similar to those presented
in . Overall, total HBCD concentrations in the 113 dust samples of this dataset
ranged from 33 to 140,000 |ig/kg (means = 160 to 19,000 |ig/kg; medians = 114 to 13,000 |ig/kg).
HBCD was detected in all samples.
Results from an additional study in Belgium (Al Bitar. 2004) was also reported in )8). In
this study, 23 dust samples (individual and pooled) were analyzed from homes and offices.
Concentrations of total HBCD ranged from ND to 58,000 |ig/kg, with detection in only 6 samples.
The study concluded that homes and offices were equally contaminated.
As cited in Law et ,u ' !«, HBCD was measured in dust samples collected from homes in
Czechoslovakia. Total HBCD residues ranged from ND to 950 |ig/kg.
5.2.5.1.6 Asia
Ni and Zens measured total HBCD in air conditioning filter dust samples from an office
building in Shenzhen, China in March 2009. The dust samples were collected by brushing the air
conditioner fiberglass filters, which trapped particles over 0.3 pm. Total HBCD concentrations in
the 56 dust samples, determined by LC-MS with ESI in the negative mode, ranged from 652 to
122,973 |ig/kg (mean = 7,276 |ig/kg; geometric mean = 3,246 |ig/kg; median = 2,621 |ig/kg). The
study authors noted that since smaller particles may be more likely to blow through the filter or to
remain on the filter after brushing, HBCD concentrations observed in the study may be
underestimated.
Cao et. al. (201.5) attempted to determine seasonal and particle size dependent variations of total HBCD in
settled dust from five microein ironment categories (offices, hotels, kindergartens, dormitories, and roads)
from Beijing. China. Individual dust samples were collected in 2012 from 22 offices, 3 hotels. 2
kindergartens. 40 dormitories, and 10 sites on main roads using a vacuum. Samples from each
microein ironment were pooled and homogenized into one composite sample, and each of the five
composite samples was fractionated into nine fractions according to particle size. Total HBCD
93
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
concentrations in settled floor dust from 45 size-segregated samples ranged from 5.3 (road dust) to 2,580
(ig/kg (dormitories). In addition, indoor dust samples from two offices were collected between March
2012 and August 2012 (Office A) at weekly intervals, and March 2012 and December 2012 (Office B) at
biweekly intervals, to study seasonality of HBCD in indoor dust. Mean concentrations of total HBCD
were 1,310 and 1,210 (.ig/kg. respectively, for Office A (n = 23) and Office B (n = 17).
5.2.6 Indoor Air
5.2.6.1.1 Indoor Air (ng/m3) Chart
Commercial
Mixed use
Residential
CN -Hongetal. 2016
GB - Abdallah et al. 2008
JP - Saito et al. 2007
SE - Thuresson et al. 2012
CN - Hongetal. 2016
SE - Newton et al. 2015
CN-Hongetal. 2016
GB - Abdallah et al. 2008
JP - Takigami et al. 2009
JP - Takigami et al. 2007
JP - Saito et al. 2007
SE - Thuresson et al. 2012
VN-Tueetal. 2013
i
10A-4 0.001 0.01 0.1
10 100
Concentration (ng/m3 )
5.2.6.1.2 Indoor Air (ng/m3) Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
3227425
{Hong, 2016,
3227425)
0.00405
0.016
0.0064
0.00821
1079114
{Abdallah, 2008,
1079114}
0.07
0.96
0.17
0.9
1927779
{Saito, 2007,
1927779}
0.6
29.5
1927620
{Thuresson, 2012,
1927620}
0.0016
0.035
3227425
{Hong, 2016,
3227425}
0.01
0.125
0.0396
0.0482
2911989
{Newton, 2015,
2911989}
0.00065
0.019
0.0013
0.0031
94
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
3227425
{Hong, 2016,
3227425)
0.00089
0.00847
0.0054
0.00665
1079114
{Abdallah, 2008,
1079114}
0.067
1.3
0.18
0.25
198241
{Takigami, 2009,
198241)
0.0067
0.28
4197589
{Takigami, 2007,
4197589}
0.0084
0.22
1927779
{Saito, 2007,
1927779}
0.6
24
1927620
{Thuresson, 2012,
1927620}
0.0016
0.033
0.002
0.002
1927567
{Tue, 2013, 1927567}
0.0066
5.2.6.1.3 Indoor Air (ng/m3): Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data
Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Hong, 2016,
3227425}
CN
Commercial
2004-
2005
5
N/R
N/R
1.6
High
{Abdallah, 2008,
1079114}
GB
Commercial
2007
29
1
0.0033
1.3
High
{Saito, 2007,
1927779}
JP
Commercial
2001
14
N/R
1.2
1.9
Medium
{Thuresson, 2012,
1927620}
SE
Commercial
2006
20
N/R
0.0016
1.7
Medium
{Hong, 2016,
3227425}
CN
Mixed use
2004-
2005
10
N/R
N/R
1.6
High
{Newton, 2015,
2911989}
SE
Mixed use
2012
13
0.15
0.0013
2.0
Medium
{Hong, 2016,
3227425}
CN
Residential
2004-
2005
12
N/R
N/R
1.6
High
{Abdallah, 2008,
1079114}
GB
Residential
2007
33
1
0.0033
1.3
High
95
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data
Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Takigami, 2009,
198241}
JP
Residential
2006
4
N/R
N/R
1.9
Medium
{Takigami, 2007,
4197589}
JP
Residential
2006
4
1
N/R
2.2
Medium
{Saito, 2007,
1927779}
JP
Residential
2001
32
N/R
1.2
1.9
Medium
{Thuresson, 2012,
1927620}
SE
Residential
2006
54
N/R
0.0016
1.7
Medium
{Tue, 2013,
1927567}
VN
Residential
2008
1
0.25
N/R
1.9
Medium
5.2.6.1.4 Europe
EC/HC (2011) reported HBCD measurements in indoor air from one study (Abdallah et al.. 2008b)
which was conducted in the United Kingdom. Median HBCD concentrations were 0.000180 |ig/m3
in homes (n = 33), 0.000170 |ig/m3 in offices (n = 25), and 0.000900 |ig/m3 in public
microenvironments (n = 4).
5.2.6.1.5 Asia
Hong et al. (2013) measured HBCD diastereoisomer and total HBCD concentrations in indoor and
outdoor air samples collected from different locations within two industrialized cities (Guangzhou
and Foshan) in Southern China. According to Hong et al. (2016), the HBCD production capacity
in China was 7500 tonnes in 2007. A total of 37 indoor air samples (gas and particle phases) were
collected from homes (n=12), offices (n=5), and other workplaces (n=10) between October 2004
and April 2005. Gas-phase samples were collected using a high-volume sampler and particle-
phase samples were collected using PUF plugs. Indoor air samplers were placed at floor level.
HBCD diastereoisomer determination was made using LC-MS/MS in electrospray ionization
negative ion mode with multiple reaction monitoring. Quality control measures taken included
duplicate sample collection, field blanks, procedural blanks, and recovery experiments at multiple
concentration levels. The gas- and particle-phase concentrations for alpha-, beta-, and gamma-
HBCD and total HBCD in indoor air were calculated using a six-point calibration standard curve.
Total HBCD mean concentrations (including gas- and particle-phase) were 0.00543 ng/m3
(0.00089-0.00847 ng/m3) and 0.00821 ng/m3 (0.00405-0.0160 ng/m3) for homes and offices,
respectively. The total HBCD mean concentration for other workplaces (workplace type not
specified) was significantly higher at 0.0482 ng/m3 (0.010-0.125 ng/m3). According to Hong et al.
96
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
(2016), these total HBCD mean concentrations were slightly higher than or comparable with levels
reported in remote or urban sites within the United States and are significantly lower than those
reported in the European atmosphere. Further examination of the diastereoisomer profiles
indicated that alpha-HBCD was the dominant isomer with a relative abundance ranging from
56.3% to 83.0% (mean value 73.6%) and that airborne HBCDs were predominantly present in the
particulate phase. The study noted that the variation in HBCD distribution in the gas and particulate
phases was greater in indoor air samples than outdoor samples. The study concluded with
estimating average daily human exposure to HBCDs via inhalation of indoor and outdoor air using
the measured indoor and outdoor total HBCD concentrations from this study.
Using measured HBCD concentrations in air conditioning filter dust samples collected from an
office building in Shenzhen, China, Ni and Zeng (2013) calculated HBCD concentrations in the
particulate phase of indoor office air, using an equation described in Ni and Zeng (2013). HBCD
concentrations from 56 offices were estimated to range from 13.5 to 1,099 pg/m3 (505 pg/m3 mean;
516 pg/m3 median) in PM2.5 (representing dust with particle diameter of 0.4-2.2 (j,m) and from
18.4 to 2,274 pg/m3 (1,001 pg/m3 mean; 1,091 pg/m3 median) in PM10 (representing dust with
particle diameter of 2.5-8.9 (j,m).
5.2.7 Ambient Air
5.2.7.1.1 Ambient Air (ng/m3) Chart
US - Hoh and Hites 2005
CN-Lietal. 2016
CN - Hu et al. 2011
CN - Yu et al. 2008
Multiple - Lee et al. 2016
N/A - EC HA 2008
N/A- ECHA 2017
I Background
Modeled
I Near facility
CA - Shoeib et al. 2014
CN-Zhuetal. 2014
CN - Qi et al. 2014
CN - Yu et al. 2008
CN-Lietal. 2012
CN - Hong et al. 2016
CZ - Okonski et al. 2014
GB - Abdallah et al. 2008
GL - Vorkamp et al. 2015
JP - Takigatni et al. 2009
NO-KLIF 2010
SE - Newton et al. 2015
SE; Multiple - Remberger et al. 2004
UG - Arinaitwe et al. 2014
SE - Remberger et al. 2004
10A-6
0.01 1
Concentration (ng/m3 )
97
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.7.1.2 Ambient Air (ng/m3) Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
999242
{Hoh, 2005, 999242}
6.50E-05
0.011
0.0004
0.0045
3355687
{Li, 2016, 3355687}
0.0028
3.4
0.088
0.36
1927637
{Hu, 2011, 1927637}
0.2
1.8
0.39
0.39
1058394
{Yu, 2008, 1058394}
0.00028
0.00392
0.00066
0.00321
3350487
{Lee, 2016, 3350487}
5.00E-05
0.19
3970747
{ECHA, 2008,
3970747}
0.047
2600
3970753
{ECHA, 2017,
3970753}
0.084
12
3019586
{Shoeib, 2014,
3019586}
0.00097
0.00469
0.00097
0.00139
2343682
{Zhu, 2014, 2343682}
1.00E-05
0.00284
1.00E-05
0.00025
2343693
{Qi, 2014, 2343693}
0.0039
6.7
0.02
0.15
1049627
{Yu, 2008, 1049627}
0.0012
0.0018
0.0014
0.0014
1927607
{Li, 2012, 1927607}
0.0225
0.0719
3227425
{Hong, 2016, 3227425}
0.00869
0.0853
0.0242
0.0333
2528316
{Okonski, 2014,
2528316}
0.00025
0.0532
1079114
{Abdallah, 2008,
1079114}
0.034
0.04
0.037
0.037
3015562
{Vorkamp, 2015,
3015562}
5.60E-06
0.000228
3.46E-05
3.46E-05
198241
{Takigami, 2009,
198241}
0.013
0.015
3809228
{KLIF, 2010, 3809228}
0.00014
0.02302
0.00415
0.00654
2911989
{Newton, 2015,
2911989}
1.30E-05
0.00058
1927826
{Remberger, 2004,
1927826}
0.0005
0.61
2343716
{Arinaitwe, 2014,
2343716}
0.00015
0.00619
0.00015
0.00061
1927826
{Remberger, 2004,
1927826}
0.013
1070
98
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.7.1.3 Ambient Air (ng/m3): Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data Quality
Evaluation
Score
Overall
Quality
Level
gas and particulate
{Hoh,
2005,
999242}
US
Background
2002 - 2004
120
0.82
0.00013
2.0
Medium
{Li, 2016,
3355687}
CN
Background
2008 -2013
222
0.94
0.0056
1.8
Medium
{Hu,
2011,
1927637}
CN
Background
2011
28
1
0.024
1.2
High
{Yu,
2008,
1058394}
CN
Background
2004
64
0.95
N/R
1.8
Medium
{Lee,
2016,
3350487}
Multiple
Background
2005 - 2006
160
0.56
le-04
1.8
Medium
{ECHA,
2008,
3970747}
N/A
Modeled
N/A
N/A
N/A
N/A
1.3
High
{ECHA,
2017,
3970753}
N/A
Modeled
N/A
N/A
N/A
N/A
2.0
Medium
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Shoeib,
2014,
3019586}
CA
Background
2010 -2011
70
0.67
N/R
2.0
Medium
{Zhu, 2014,
2343682}
CN
Background
2010 -2011
36
0.56
N/R
1.3
High
99
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Qi, 2014,
2343693}
CN
Background
2007 - 2008
57
N/R
0.0029
2.1
Medium
{Yu, 2008,
1049627}
CN
Background
2006
4
N/R
N/R
3.0
Low
{Li, 2012,
1927607}
CN
Background
2006
25
N/R
N/R
1.8
Medium
{Hong,
2016,
3227425}
CN
Background
2004 - 2005
9
N/R
N/R
1.6
High
{Okonski,
2014,
2528316}
cz
Background
2009-2010
24
0.75
5e-04
1.2
High
{Abdallah,
2008,
1079114}
GB
Background
2007
5
1
0.0033
1.3
High
{Vorkamp,
2015,
3015562}
GL
Background
2012
36
0.69
1.4e-05
1.2
High
{Takigami,
2009,
198241}
JP
Background
2006
2
N/R
N/R
1.9
Medium
{KLIF,
2010,
3809228}
NO
Background
2007
26
N/R
N/R
1.4
High
{Newton,
2015,
2911989}
SE
Background
2012
12
0.25
2.6e-05
2.0
Medium
{Remberger,
2004,
1927826}
SE;
Multiple
Background
2000 - 2001
14
0.86
0.001
1.8
Medium
{Arinaitwe,
2014,
2343716}
UG
Background
2008 -2010
56
0.29
3e-04
1.4
High
100
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/m3)
Data Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Remberger,
2004,
1927826}
SE
Near facility
2000 - 2001
3
1
0.001
1.8
Medium
5.2.7.1.4 Ambient Air (ng/g) Chart
Background
10~-6 10~-5 1CT-4
Concentration ( ng/g )
5.2.7.1.5 Ambient Air (ng/g) Summary Statistics
HERO ID
Study Name
Min
Max
Central Tendency
(low)
Central Tendency
(high)
2343682
{Zhu, 2014,
2343682}
1.00E-05
0.00029
1.00E-05
4.00E-05
5.2.7.1.6 Ambient Air (ng/g): Supporting Data
HERO ID
Country
Location
Type
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
particulate
{Zhu, 2014,
2343682}
CN
Background
2010-2011
36
0.56
N/R
1.3
High
5.2.7.1.7 North America
The Canadian and Australian risk assessments (NICNAS. 2012; EC/HC. 2011) summarized
outdoor air data from three studies conducted in North America. In remote arctic areas of Canada,
total HBCD levels from samples collected between 1994 and 2007 ranged from ND to 0.000003
|ig/m3 (Xiao etal.. 2010; Alaee et al.. 2003). The 12 samples from Alaee etal. (2003) were reported
as less than 0.0000018 |ig/m3. In the United States, total HBCD levels collected in 2002-2003 from
156 samples ranged from ND to 0.000011 |ig/m3, with detection in 120 samples (Hoh and Hites.
2005). The samples were collected in east central states from urban, semi-urban, agricultural, and
remote areas.
101
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Hoh and Hites (2005) studied spatial trends of total HBCD in outdoor air through the analysis of
samples collected at five US sites for two years (2002 to 2003). The sites included an urban site
in Chicago, Illinois, a semi-urban site in Indiana, an agricultural site in Arkansas, and remote sites
in Michigan and Louisiana. Air samples were collected for 24-hours every 12 days. Gas- and
particle-phase samples were collected using high-volume samplers fitted with either XAD-2 resin
and a quartz fiber filter (Chicago site only) or with a PUF adsorbent and glass fiber filter (other
four sites). All samples were analyzed using GC-MS operated in the ECNI mode. Total HBCD
was detected in approximately 76% of the samples (120 of 156), in only in the particle phase.
Total HBCD concentrations in outdoor air ranged from ND (<0.00007 ng/m3) to 0.008 ng/m3
(mean = 0.0012 ng/m3; median = 0.0005 ng/m3) at the remote Michigan site, from ND (<0.00013
ng/m3) to 0.0096 ng/m3 (mean = 0.0045 ng/m3; median = 0.0042 ng/m3) at the urban Chicago site,
from ND (<0.00007 ng/m3) to 0.0036 ng/m3 (mean = 0.001 ng/m3; median = 0.00075 ng/m3) at
the semi-urban Indiana site, from ND (<0.00013 ng/m3) to 0.011 ng/m3 (mean = 0.0016 ng/m3;
median = 0.0004 ng/m3) at the agricultural Arkansas site, and fromND (<0.00013 ng/m3) to 0.0062
ng/m3 (mean = 0.0006 ng/m3; median = ND) at the remote Louisiana site. The highest mean and
median values were from the Chicago site, suggesting that urban areas are the source of this
compound. The highest individual concentration of total HBCD occurred at the Arkansas site,
which could be attributed to manufacturing areas in southern Arkansas, as investigated using four-
day backward air trajectories. The percent HBCD isomer composition of seven samples was
variable.
Shoeib e measured flame retardants in air samples collected from a semi-urban location
(Environment Canada field site) located in Toronto, Canada, between 2010 and 2011. A total of
70 outdoor air samples (gas and particle phases) were collected using PS-1 type sampler and the
sampling train consisted of a glass-fiber filter for collecting the particulate phase. Air samples were
collected over a 24-hour sampling period and were analyzed for total HBCD using GC-MS using
negative ion chemical ionization mode. Total HBCD was detected only in the particulate phase in
67% of the samples (n = 70) with concentrations that ranged ND (<0.00144 ng/m3) to 0.00469
ng/m3 (mean = 0.00139 ng/m3; median = 0.00097 ng/m3). According to Shoeib et al. (2014) these
results were similar to mean observed in the east-central United States in 2002-2003 (Hoh and
Hites, 2005).
102
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.7.1.8 Europe
The Australian, Canadian, UNEP, and EC risk assessments (NICNAS. 2012; EC/HC. ;
II' 1 ¦12008) summarized outdoor air data from seven studies conducted in Europe.
Overall, total HBCD concentrations in remote areas ranged from ND to 0.00028 |ig/m3. In urban
and rural areas, total HBCD concentrations ranged from 0.000002 to 0.00061 |ig/m3. In industrial
areas, total HBCD concentrations ranged from 0.000013 to 1.07 |ig/m3. The highest concentrations
(0.280 and 1.07 |ig/m3) were from the vicinity of XPS production plants in samples collected prior
to 2001.
Okonski et at ( collected outdoor air samples from two sites in the Czech Republic (one
urban site in central Brno and one rural site near the village of Telnice) between October 2009 and
October 2010 using a high-volume air sampler. For flame retardants, 12 samples were analyzed
from each site, with weekly samples grouped by season. Particle size and HBCD isomers were
differentiated. Samples were analyzed for HBCD (particulate phases) by HPLC-MS/MS with ESI
in the negative mode. Concentrations were reported for individual isomers (a, -P, and y-HBCD);
total HBCD was calculated herein by summing results for the individual isomers across all particle
sizes. Overall, concentrations of total HBCD ranged from 0.00000624 to 0.00005333 |ig/m3 in
ambient outdoor air (n=24), with higher concentrations observed in warm seasons at the rural site.
The study authors indicate that HBCD in outdoor air is largely particle-bound, even in warm
seasons, and thus seasonality in emissions rather than in gas-particle partitioning, governs particle-
phase concentrations, as seen for other novel flame retardants.
5.2.7.1.9 Asia
The Canadian and Australian risk assessments (NICNAS, 2012; EC/HC. 2011) summarized
outdoor air data from two studies conducted in China. In a method validation study, total HBCD
concentrations in air samples ranged from 0.0000012 to 0.0000018 |ig/m3 (Yu et at. 2008a). In
t at (2008b). total HBCD concentrations were measured in air in 2006 from two industrial
sites (means = 0.00000069 and 0.00000089 |ig/m3), one urban site (mean = 0.00000309 |ig/m3),
and one city mountaintop (mean = 0.00000167 |ig/m3). Between -70 and 95% of the residues
existed in the particle phase.
As cited in Law et at (201.4). two studies measured levels of HBCD in outdoor air samples
collected from industrial and urban locations in China (Shanghai and Beijing). Total HBCD
concentrations in outdoor air ranged from 0.00002 to 0.0018 |ig/m3 in Beijing (" in i u <>¦ ).
According to the Li et study, average total HBCD concentrations in Shanghai ranged
from 0.000023 |ig/m3 to 0.000072 |ig/m3.
Hong et. at (201.3) collected outdoor and indoor air samples from two industrialized cities (Guangzhou
and Foshan) in Southern China between October 2004 and April 2005. Total HBCD concentrations
(vapor and particulate phases) were determined by LC-MS/MS with ESI in the negative ion mode.
Concentrations in outdoor air (n=9) ranged from 0.00000869 to 0.0000853 (ig/m3 (mean = 0.0000333 ±
0.0000281 (ig/m3; median = 0.0000242 (ig/m3).
103
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.8 Dietary Monitoring
5.2.8.1.1 Dairy Chart
Background
GB - Driffield et al. 2008
I
BE - Goscinny et al. 2011
CN - Shi et al. 2017
ES - Eljarrat et al. 2014
SE - Remberger et al. 2004
i
FR - Riviere et al. 2014
GB - Fernandes et al. 2016
GB - Driffield et al. 2008
I
GB - FSA 2006
KP - Barghi et al. 2016
SE - Tornkvist et al. 2011
0.001 0.01 0.1
10
Concentration (ng/g)
5.2.8.1.2 Dairy Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1252276
{Driffield, 2008,
1252276)
0.56
0.56
787666
{Goscinny, 2011,
787666)
0.275
4.355
0.275
4.155
3975096
{Shi, 2017, 3975096)
1.82
5.29
1.82
1.98
2343701
{Eljarrat, 2014,
2343701)
0.32
1.35
0.78
0.78
1927826
{Remberger, 2004,
1927826)
1.8
1.8
2343707
{RiviA're, 2014,
2343707)
0.003
0.034
3350498
{Fernandes, 2016,
3350498)
0.03
0.165
0.03
0.04
1252276
{Driffield, 2008,
1252276)
0.24
0.24
4159524
{FSA, 2006, 4159524)
0.24
0.56
0.24
0.56
3350483
{Barghi, 2016,
3350483)
0.00145
0.50289
0.02318
0.06398
1927648
{TATjrnkvist, 2011,
1927648)
0.005
0.025
104
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.8.1.3 Dairy: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
dry
{Driffield,
2008,
1252276}
GB
Background
Milk
2004
1
N/R
N/R
1.4
High
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
lipid
{Goscinny,
2011,
787666}
BE
Background
Milk;
Cheese;
Butter;
Pizza
2008
132
N/R
1.1
1.6
High
{Shi, 2017,
3975096}
CN
Background
Milk
2011
20
0.95
N/R
1.3
High
{Eljarrat,
2014,
2343701}
ES
Background
Dairy
products
2009
7
1
0.2
1.8
Medium
{Remberger,
2004,
1927826}
SE
Background
Milk
1999
1
N/R
1
1.8
Medium
105
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{RiviA're,
2014,
2343707}
FR
Background
Milk; Dairy
products;
Cheese;
Butter;
Dairy-
based
desserts
2007 -
2009
170
N/R
N/R
1.7
Medium
{Fernandes,
2016,
3350498}
GB
Background
Dairy
Products
2013
13
N/R
0.01
1.3
High
{Driffield,
2008,
1252276}
GB
Background
Dairy
products
2004
1
N/R
N/R
1.4
High
{FSA, 2006,
4159524}
GB
Background
Dairy
products;
Milk
2004
2
0
0.56
2.0
Medium
{Barghi,
2016,
3350483}
KP
Background
Dairy
products
2012 -
2014
36
0.87
0.0029
1.3
High
106
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{TA'rnkvist.
2011,
1927648}
SE
Background
Milk
(61%), sour
milk
(16%),
yoghurt
"(8%),
cream and
sour cream
(5%),
cheese
(8%),
cottage
cheese
(2%);
Butter
(9%),
margarine
(46%), low
fat
margarine
(29%), oil
(9%),
mayonnaise
"(6%)
2005
142
N/R
N/R
1.8
Medium
5.2.8.1.4 Fruit Chart
Background
GB - Driffield et al. 2008
GB - Driffield et a
.2008
I
KP - Barghi et a
.2016
0.001
0.01
0.1
1
Concentration ( ng/g)
5.2.8.1.5 Fruit Summary Statistics
107
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO
ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1252276
{Driffield, 2008,
1252276)
0.273
0.75
1252276
{Driffield, 2008,
1252276)
0.15
0.15
3350483
{Barghi, 2016,
3350483)
0.0031
0.12758
0.01837
0.03004
5.2.8.1.6 Fruit: Supporting Data
HERO
ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL (
ng/g)
Data
Quality
Evaluation
Score
Overall
Quality Level
dry
{Driffield,
2008,
1252276}
GB
Background
Fruit;
Fruit
products
2004
2
N/R
N/R
1.4
High
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Driffield, 2008,
1252276}
GB
Background
Sugars
and
preserves
2004
1
N/R
N/R
1.4
High
{Barghi, 2016,
3350483}
KP
Background
Fruit
2012 -
2014
11
1
0.0029
1.3
High
5.2.8.1.7 Grain Chart
108
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
BE - Goscinny et al. 2011
Background
FR - Riviere et al. 2014
I
GB - Driffield et al. 2008
I
KP - Barghi et al. 2016
0.001
0.01
0.1
Concentration (ng/g)
1
10
5.2.8.1.8 Grain Summary Statistics
Central
Tendency (low)
Central
HERO ID
Study Name
Min
Max
Tendency
(high)
787666
{Goscinny, 2011,
787666)
0.909
2.441
1.11
2.241
2343707
{RiviA're, 2014,
2343707)
0.03
0.03
1252276
{Driffield, 2008,
1252276)
0.125
0.125
3350483
{Barghi, 2016,
3350483)
0.0031
0.06053
0.03375
0.03819
5.2.8.1.9 Grain: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Goscinny,
2011,
787666}
BE
Background
Croissant;
Cakes, pies,
pastry;
Cookies/biscuits
2008
80
N/R
1.1
1.6
High
109
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
( ng/g )
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{RiviA're,
2014,
2343707}
FR
Background
Sandwiches
and snacks
2007 -
2009
18
N/R
N/R
1.7
Medium
{Driffield,
2008,
1252276}
GB
Background
Bread;
Cereals
2004
2
N/R
N/R
1.4
High
{Barghi,
2016,
3350483}
KP
Background
White rice
2012 -
2014
10
1
0.0029
1.3
High
5.2.8.1.10 Meat Chart
Background
BE - Goscinny et al. 2011
CN-Shietal. 2017
CN - Shi et al. 2009
DE - Hiebl and Vetter2007
ES - Eljarrat et al. 2014
SE - Remberger et al. 2004
I
TZ - Polder et al. 2016
US - Schecter et al. 2012
CN - Hu et al. 2011
FR - Riviere et al. 2014
GB - Driffield et al. 2008
m
KP - Barghi et al. 2016
SE - Tornkvist et al. 2011
0.001 0.01 0.1
10 100 1000 10A4
Concentration ( ng/g)
5.2.8.1.11 Meat Summary Statistics
Central
Central
HERO ID
Study Name
Min
Max
Tendency
Tendency
(low)
(high)
110
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
787666
{Goscinny, 2011,
787666)
0.15
14.652
1927636
{Rawn, 2011, 1927636}
0.003
71.9
0.029
0.137
3975096
{Shi, 2017, 3975096}
1.26
14.9
1.26
2.52
1927708
{Shi, 2009, 1927708}
0.035
1.245
0.262
0.273
1927776
{Hiebl, 2007, 1927776}
30
2000
2343701
{Eljarrat, 2014,
2343701}
0.28
12.9
1.75
2.68
1927826
{Remberger, 2004,
1927826}
9.4
9.4
3347466
{Polder, 2016, 3347466}
0.015
63
0.97
13
1401050
{Schecter, 2012,
1401050}
0.01
0.51
1224355
{Hu, 2011, 1224355}
0.1
0.74
2343707
{RiviA're, 2014,
2343707}
0.026
0.141
1252276
{Driffield, 2008,
1252276}
0.188
0.378
3350483
{Barghi, 2016,
3350483}
0.02987
0.71033
0.05392
0.09064
1927648
{TATjrnkvist, 2011,
1927648}
0.005
0.005
5.2.8.1.12 Meat: Supporting Data
111
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Goscinny,
2011,
787666}
BE
Background
Beef; Veal;
Pork; Sheep;
Turkey; Horse;
Chicken; Duck;
Rabbit; Hind,
pheasant,
guinea hen, wild
boar, quail,
pigeon;
Sausages,
salami, pie,
meatloaf,
pudding, horse
filet; Liver of
veal, pork,
rabbit, foie gras;
Eggs
2008
181
N/R
1.1
1.6
High
{Rawn,
2011,
1927636}
CA
Background
Egg yolks
2005 -
2006
162
N/R
0.006
2.0
Medium
{Shi, 2017,
3975096}
CN
Background
Eggs; Meat
2011 -
2022
40
0.95
N/R
1.3
High
{Shi, 2009,
1927708}
CN
Background
Meat; Eggs
2007
24
0.54
0.07
1.6
High
{Hiebl,
2007,
1927776}
DE
Background
Eggs
2007
3
N/R
20
2.1
Medium
{Eljarrat,
2014,
2343701}
ES
Background
Meat; Eggs
2009
12
1
0.2
1.8
Medium
{Remberger,
2004,
1927826}
SE
Background
Egg yolk
1999
1
N/R
1
1.8
Medium
112
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Polder,
2016,
3347466}
TZ
Background
Eggs
2012
28
0.61
0.03
1.9
Medium
HERO ID
Country
Location
Type
Species
Samplin
g Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality Level
wet
{Schecter,
2012,
1401050}
US
Background
Smoked turkey
sausages; Fresh
deli sliced turkey;
Chili with beans;
Fresh deli sliced
ham; Smoked
turkey sausage;
Bacon; Fresh deli
sliced beef; Fresh
deli sliced
chicken;
Sausages; Sliced
turkey; Sliced
chicken breast;
Sliced ham;
Canned chili
2009-
2010
24
0.46
0.08
1.2
High
{Hu, 2011,
1224355}
CN
Background
Eggs
2011
3
0.1
0.2
2.3
Low
{RiviA're,
2014,
2343707}
FR
Background
Eggs; Meats;
Poultry and
game; Offal
2007-
2009
228
N/R
N/R
1.7
Medium
{Driffield,
2008,
1252276}
GB
Background
Meat; Offal
2004
2
N/R
N/R
1.4
High
113
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Samplin
g Year
No. of
Samples
FoD
DL
(ng/g)
Data Quality
Evaluation
Score
Overall
Quality Level
wet
{Barghi,
2016,
3350483}
KP
Background
Meat; Eggs
2012-
2014
142
1
0.0029
1.3
High
{TA'rnkvis
t, 2011,
1927648}
SE
Background
Beef (24%), pork
(23%), lamb
(1%), chicken
(12%), game
(2%), processed
meats except
pizza (38%);
Eggs
2005
136
N/R
N/R
1.8
Medium
5.2.8.1.13 Other Foods Chart
Background
CN - Shi et al. 2009
GB - Fernandes et al. 2016
US - Venier and Hites 2011
US - Schecter et al. 2012
I
BE - Roosens et al. 2009
FR - Riviere et al. 2014
¦
GB - FSA 2006
NO - Knutsen et al. 2008
PT - Coclho et al. 2016
0.001
0.01
0.1
1
10
Concentration ( ng/g)
5.2.8.1.14 Other Foods Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1927708
{Shi, 2009, 1927708}
0.085
9.208
0.114
2.224
3350498
{Fernandes, 2016,
3350498)
0.045
0.75
0.045
0.44
1927638
{Venier, 2011, 1927638}
0.005
0.008
0.005
0.005
114
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1401050
{Schecter, 2012,
1401050)
0.116
0.116
787720
{Roosens, 2009,
787720}
0.005
0.35
0.1
0.13
2343707
(RiviA're, 2014,
2343707)
0.037
0.044
4159524
{FSA, 2006, 4159524)
0.28
0.68
1927755
(Knutsen, 2008,
1927755}
0.38
3350459
(Coelho, 2016,
3350459}
0.017
1.2
0.021
0.079
5.2.8.1.15 Other Foods: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Shi,
2009,
1927708}
CN
Background
Aquatic food
2007
12
0.92
0.13
1.6
High
HERO ID
Country
Location Type
Species
Sampling
Year
No. of
Sample
s
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Fernandes
,2016,
3350498}
GB
Background
Other Foods,
edible portion;
Processed Foods,
edible portion;
Composite feeds
for animals;
Animal Feed-Fish
Feeds; Animal
feed-Oilseeds
and cereals
2013
61
N/R
0.01
1.3
High
115
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location Type
Species
Sampling
Year
No. of
Sample
s
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Venier,
2011,
1927638}
US
Background
Dog food
2010
16
1
N/R
1.9
Medium
{Schecter,
2012,
1401050}
US
Background
Processed and
fresh foods
2009
10
1
N/R
1.2
High
{Roosens,
2009,
787720}
BE
Background
Duplicate diet for
each participant
on each day
2007
13
0.08
0.01
1.4
High
{RiviA're,
2014,
2343707}
FR
Background
Mixed dishes;
Seasonings and
sauces
2007-
2009
64
N/R
N/R
1.7
Medium
{FSA,
2006,
4159524}
GB
Background
Combined food
groups
2004
19
0.47
0.56
2.0
Medium
{Knutsen,
2008,
1927755}
NO
Background
Various foods
(including
vegetable oil, ice
cream, biscuit,
and banana).
2002-
2006
12
N/R
N/R
1.8
Medium
{Coelho,
2016,
3350459}
PT
Background
Multiple food
types
2016
21
N/R
N/R
1.4
High
116
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.8.1.16 Seafood Chart
¦¦¦ Background
CN-Shietal. 2017
DE - Hiebl and Vetter2007
ES - Eljarrat et al. 2014
Multiple - Aznar-Alemany et al. 2016
SE - Remberger et al. 2004
US - Schecter et al. 2012
BE - Goscinny et al. 2011
CN - Hu et al. 2011
ES - Ortiz et al. 2011
FR - Riviere et al. 2014
I
GB - Fernandes et al. 2016
GB - Driffield et al. 2008
GB - FSA 2006
I
JP - Nakagawa et al. 2010
SE - Tornkvist et al. 2011
I
0.001 0.01 0.1
10 100
Concentration (ng/g)
5.2.8.1.17 Seafood Summary Statistics
HERO
ID
Central
Central
Study Name
Min
Max
Tendency
(low)
Tendency
(high)
3975096
{Shi, 2017, 3975096}
2.55
25.6
2.55
4.29
1927776
{Hiebl, 2007,
1927776)
40
70
2343701
{Eljarrat, 2014,
2343701)
1.91
23.4
11.6
11.6
3454553
{Aznar-Alemany,
2016, 3454553}
1
54.4
1927826
{Remberger, 2004,
1927826}
6.7
51
1401050
{Schecter, 2012,
1401050}
0.01
1.366
0.012
0.114
787666
{Goscinny, 2011,
787666}
0.01
0.831
1224355
{Hu, 2011, 1224355}
0.2
1.43
1927653
{Ortiz, 2011,
1927653}
1.14
9.69
2343707
{RiviA're, 2014,
2343707}
0.135
0.141
3350498
{Fernandes, 2016,
3350498}
0.04
10.29
0.04
1.4
117
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
1252276
{Driffield, 2008,
1252276)
0.03
12
0.22
12
4159524
{FSA, 2006,
4159524}
0.3
0.3
1927668
{Nakagawa, 2010,
1927668)
0.03
77.3
1927648
{TATjrnkvist, 2011,
1927648}
0.145
0.145
5.2.8.1.18 Seafood: Supporting Data
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
lipid
{Shi,
2017,
3975096}
CN
Background
Fish
2011
20
0.95
N/R
1.3
High
{Hiebl,
2007,
1927776}
DE
Background
Whole;
Fillets;
Fillet
2007
3
N/R
20
2.1
Medium
{Eljarrat,
2014,
2343701}
ES
Background
Seafood
2009
22
1
0.2
1.8
Medium
{Aznar-
Alemany,
2016,
3454553}
Multiple
Background
Seafood
2014 -
2015
42
0.48
2
1.7
Medium
{Rember
ger, 2004,
1927826}
SE
Background
Seafood;
Salmon
1996 -
1999
3
N/R
1
1.8
Medium
118
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{Schecter, 2012,
1401050}
US
Background
Sardines in
water; Fresh
salmon;
Sardines in
olive oil;
Fresh
catfish;
Fresh
tilapia; Fish
sticks;
Processed
foods and
fresh fish;
Canned
sardines
2009 -
2010
90
0.48
0.08
1.2
High
{Goscinny, 2011,
787666}
BE
Background
Salmon;
Tuna; Cod;
Herring;
Sardine;
Mackerel;
Trout,
halibut, sole,
monkfish,
saithe, hake;
Crustaceans;
Molluscs;
Tuna salad,
crab salad,
fish salad,
surimi salad;
Fish stick,
surimi
2008
118
N/R
N/R
1.6
High
{Hu, 2011,
1224355}
CN
Background
Fish feed
2011
4
0.13
0.4
2.3
Low
{Ortiz, 2011,
1927653}
ES
Background
Fish oil
2011
22
1
0.03
1.4
High
119
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{RiviA're, 2014,
2343707}
FR
Background
Fish;
Crustaceans
and
mollusks
2007 -
2009
82
N/R
N/A
1.7
Medium
{Fernandes,
2016,3350498}
GB
Background
Fish, edible
portion;
Shellfish,
edible
portion
2013
56
N/R
0.01
1.3
High
{Driffield, 2008,
1252276}
GB
Background
Fish;
Oysters;
Mussels;
Scallops
2004
36
N/R
N/R
1.4
High
{FSA, 2006,
4159524}
GB
Background
Fish
2004
1
1
N/R
2.0
Medium
{Nakagawa,
2010, 1927668}
IP
Background
Seafood:
marine fish
and
invertebrates
2004 -
2008
64
N/R
0.02
1.4
High
{TA'rnkvist.
2011,1927648}
SE
Background
Fresh and
frozen lean
fish (26%),
fresh and
frozen fatty
fish (15%).
canned/
processed
products
(47%),
prawns
(12%)
2005
104
N/R
N/R
1.8
Medium
120
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.8.1.19 Vegetable Chart
Background
GB - Driffield et al. 2008
FR - Riviere et al. 2014
I
GB - Fernandes et al. 2016
GB - Driffield et al. 2008
1
KP - Barghi et al. 2016
0.001
0.01
0.1
1
Concentration ( ng/g )
5.2.8.1.20 Vegetable Summary Statistics
HERO ID
Study Name
Min
Max
Central
Tendency
(low)
Central
Tendency
(high)
1252276
{Driffield, 2008,
1252276}
0.108
0.51
2343707
{RiviA're, 2014,
2343707)
0.007
0.007
3350498
{Fernandes, 2016,
3350498)
0.065
0.22
1252276
{Driffield, 2008,
1252276}
0.325
0.325
3350483
{Barghi, 2016,
3350483}
0.0031
0.10455
0.01584
0.01584
5.2.8.1.21 Vegetable: Supporting Data
121
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
HERO
ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g )
Data
Quality
Evaluati
on Score
Overall
Quality
^evel
dry
{Driffield
, 2008,
1252276}
GB
Backgrou
nd
Green
vegetables;
Potatoes;
Other
vegetables;
Canned
vegetables
2004
4
N/R
N/R
1.4
High
HERO
ID
Country
Location
Type
Species
Sampling
Year
No. of
Samples
FoD
DL
(ng/g)
Data
Quality
Evaluation
Score
Overall
Quality
Level
wet
{RiviA'r
e, 2014,
2343707
}
FR
Backgrou
nd
Vegetables
2007 -
2009
3
N/R
N/R
1.7
Medium
{Fernand
es, 2016,
3350498
}
GB
Backgrou
nd
Grasses
2013
2
N/R
N/R
1.3
High
{Driffiel
d, 2008,
1252276
}
GB
Backgrou
nd
Nuts
2004
1
N/R
N/R
1.4
High
{Barghi,
2016,
3350483
}
KP
Backgrou
nd
Vegetables
2012 -
2014
12
0.41
0.0029
1.3
High
122
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
5.2.9 Sewage Sludge
5.2.9.1.1 Sewage Sludge and Biosolids Summary
Figure 5-1. HBCD Concentration in Sewage Sludge and Biosolids (pg/mg dw)
Range of Central Tendency
Hwang et al. (2012)
Kupperetal. (2008)
Fjeld et al. (2005)
Morris et al. (2004)
Morris et al. (2004)
de Boer etal. (2002a)
Nylund et al. (2002)
Sternbeck et al. (2001)
Sternbeck et al. (2001)
Sternbeck et al. (2001)
Institut Fresenius (2000a), Institut Fresenius (2000b)
Sellstrom (1999)
Deuchar(2002)
Sellstrom et al. (1999)
La Guardia et al. (2010)
Letcher et al. (2015)
Venkatesan and Halden (2014)
1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00
HBCD concentration (ng/mg dw)
*For studies reporting ND; 1/2 the lowest reported number for a given media was used as the lower limit for visualization purposes
5.2.9.1.2 North America
Venkatesan and Halden (2014) determined national baseline levels and release inventories of 77
traditional and novel BFRs including HBCD in biosolid composite samples (prepared from 110
samples) originally collected by the US EPA as part of the 2001 National Sewage Sludge Survey
(NSSS). Representative biosolid samples, reflecting processed sewage sludge intended for
disposal, were collected between February and March 2001 from 94 WWTPs in 32 US States and
the District of Columbia. Of the 94 WWTPs, 89 had a single system (either aerobic or anaerobic
digestion) and 5 had two systems for sludge treatment (both aerobic and anaerobic digestion).
Remaining samples were collected as duplicate samples from 14 facilities, amounting to 110
biosolid samples. Aliquots from each sample were pooled to obtain five composites, each
containing solids from between 21 and 24 individual samples. A mega-composite sample (mixture
of composites 1 through 5) was analyzed for total HBCD using LC-MS/MS. The mega-composite
sample contained 19.8 pg/kg dw total HBCD.
Letcher et al. (2015) measured HCBD in sludge, from two Windsor Ontario WWTPs that feed into
the Detroit River, and sediment samples collected from the Detroit River and Lake Erie, between
May and June 2004. Sewage sludge samples (n = 2) were analyzed for total HBCD using LC-
MS/MS with ESI in the negative mode. Total HBCD concentrations were 112 and 140 pg/kg dw
in sewage sludge samples (n = 2). The results for sediment are provided in the Sediment section.
The Canadian risk assessment (EC/HC. 2011) reported the results from one study conducted in the
mid-Atlantic region of the United States (La Guardia et al.. 2010). In this study secondary sewage
sludge samples were collected in 2002, 2005, 2007, and 2008 from one WWTP which treated
123
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
domestic and industrial waste. Total HBCD concentrations in the sewage sludge samples (n = 4)
ranged from 320 to 400,000 |ig/kg dw (geometric mean = 10,040 |ig/kg dw).
5.2.9.1.3 Europe
The EU RAR (EC. 2008) provides a relatively comprehensive summary of sewage sludge
sampling results from seven studies conducted in Europe. The Canadian risk assessment (EC/HC.
2011) provides results for an additional two studies not covered in the EU RAR. Overall, the
studies represent six countries (United Kingdom, Ireland, the Netherlands, Norway, Sweden, and
Switzerland) and sampling dates between 1997 and 2005. Total HBCD concentrations in the
sewage sludge samples ranged from ND to 942,000 |ig/kg dw, with means that ranged from 45 to
149 |ig/kg dw and medians that ranged from 14 to 1,439 |ig/kg dw (central tendency values were
not reported for all studies). The highest concentrations of 728,000 to 942,000 |ig/kg dw were
reported from a sewage treatment plant in the Netherlands which was located close to a production
plant (Institut Fresenius. 2000a). The next highest concentration was 9,120 |ig/kg dw from a
sewage treatment plant in Ireland (de Boer et al.. 2002). In one of the larger studies (Law et al..
2006a). the analysis of sewage sludge from 50 sewage treatment plants in Sweden in 2000 showed
that there was little variation between sewage treatment plants, with the exception of higher
concentrations (2 to 8 times) in samples with known or suspected point sources connected to them.
5.2.9.1.4 Asia
As cited in Law et al. (2014). concentrations of total HBCD ranged from 1.6 to 29,600 |ig/kg in
sewage sludge samples collected from both municipal and industrial sources in Ulsan city, Korea
(Hwang et al.. 2012).
Table 5.1: Sewage Sludge and Biosolids Concentrations
Location3
Site
Sludge
Type
Year
N (#
ND)b
Total HBCD
Concentration (jig/kg dw)
Reference
Rangec
Central
Tendencyd
North America
US, 32
states and
the District
of
Columbia
94 WWTPs
Biosolids
from
processed
sewage
sludge
intended
for disposal
2001
1 mega-
composi
te (0)
19.8
Venkatesan and Halden
(2014)
CA;
Windsor,
Ontario
Two WWTPs
along the
Detroit River
Sewage
sludge
2004
2(0)
112-140
NR
Letcher et al. (2015)
US, mid-
Atlantic
One WWTP
(domestic/ind
ustrial)
Secondary
sludge
2002-
2008
4
320-400,000
10,040
(geometric
mean)
La Guardia etol. (2010)
fas cited in EC/HC
(2011)1
Europe
SE
3 STPs
Sewage
sludge
NR
3(0)
19-54
NR
Sellstrom etal. (1999)
fas cited in EC (2008)1
124
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Location3
Site
Sludge
Type
Year
N (#
ND)b
Total HBCD
Concentration (jig/kg dw)
Reference
Rangec
Central
Tendencyd
UK
1STP
Sewage
sludge cake
NR
1(0)
9,547
—
Deuchar (2002) [as cited
in EC (2008)1
SE
STPs
Sewage
sludge
1997-
1998
4(0)
11-120
NR
Sellstrom (1999) [as
cited in EC/HC (2011)1
NL
1 STP (close
to production
plant)
Sewage
sludge
1999-
2000
3(0)
728,000-
942,000
NR
Institut Fresenius
(2000a), Institut
Fresenius (2000b) [as
cited in as cited in EC
(2008) and EC/HC
(2011)1
SE
1 STP
(receives
input from
textile
industry)
Sewage
sludge
2000
2(0)
30, 33
NR
Sternbeck etal. (2001)
[as cited in EC (2008)1
and
Remberger et ol. (2004)
[as cited in EC/HC
(2011)1
1 STP (urban
environment)
Primary
sewage
sludge
2000
1(0)
6.9
3 STPs (urban
environment)
Digested
sewage
sludge
2000
3(3)
ND
ND
SE
50 STPs
Sewage
sludge
2000
50 (0)
3.8-650
45 (mean)
Nylund etal. (2002) [as
cited in EC (2008)1
Law etol. (2006a) [as
cited in EC/HC (2011)
and NICNAS (2012)1
UK
5 STPs
Sewage
sludge
2002
5(0)
531-2,683
1,256
(median)
de Boer etol. (2002a)
[as cited in EC (2008)
and NICNAS (2012)1
Morris et ol. (2004) [as
cited in EC/HC (2011)1
IR
6 STPs
2002
6(0)
153-9,120
1,439
(median)
NL
10 STPs
2002
9(5)
ND-1,320
14 (median)
NO
4 STPs (urban)
Sewage
sludge
2004
6(5)
0.48-51
NR
Fjeld etal. (2005) [as
cited in EC (2008)1
CH
STPs
Sewage
sludge
2003
and
2005
19 (0)
39-597
149 (mean)
123 (median)
Kupper et ol. (2008 ) [as
cited in EC/HC (2011)1
Asia
KR
Municipal and
Industrial
Sources
Sewage
sludge
NR
NR (NR)
1.6-29,600
NR
Hwang etal. (2012) [as
cited in Law et al. (2014)1
NR = Not reported; ND = Non-detect values
a CA = Canada; CH = Switzerland; IR = Ireland; KR = Korea; NL = the Netherlands; NO =
Norway; SE = Sweden; UK = United Kingdom
125
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
b N refers to the number of samples, unless otherwise noted. The number of non-detect values is
reported in parenthesis.
c The range is the minimum and maximum values reported.
d The central tendency values sh ;e.
126
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
6 Overview of Doses Estimated by Others and Comparison with EPA
doses
6.1 Overview of Modeling Approaches Used
EPA/OPPT compiled monitoring data to derive exposure estimates for ecological and general
population exposure. However, modeled estimates were also used to inform weight of evidence,
assess site specific conditions, and derive environmental concentrations and doses given available
information, if measured data was less robust.
EPA/OPPT used the following modeling approaches to estimate environmental concentrations and
doses.
Estimation of ambient air concentrations
Estimation of indoor air concentrations
Estimation of indoor dust concentrations
Estimation of surface water concentrations
Estimation of sediment concentrations
6.1.1 IECCU
6.1.1.1.1 Typical" residential home
A three-zone configuration described by Bevington et al. (2017) was used to represent a generic
residential building, where the insulation is applied to both the attic and crawlspace. The baseline
ventilation and interzonal air flows are shown in Figure 1. The ventilation rates for the three zones are
shown in Table 1. In this work, EPA used the ventilation rates for the "vented" attic and crawlspace.
127
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Qo2 = 300 mJ/h (vented)
0(52 = 105 m3/h (unvented)
Qoi = 150 m'/h
supply air
HVAC
I-
Zone 2 (Attic)
V2= 150 m3
t.
I Q21 = 15 m3/h (vented)
Q21 = 5 m3/h (unvented)
Zone 1 (Living Space)
Vj = 300 m3
t Qsi = 15
Qsi = 5r
m3/h (vented)
m3/h (unvented)
Qflj = 150 m3yh (vented)
Qoj = 52.5 mVh (unvented) Zone 3 (Crawlspace)
V3 = 150 m3
Q30
Qjhl = 10 m3/h (leakage to the return flow duct)
Figure 1. The three-zone configuration for a generic residential setting and baseline ventilation and
interzonal air flows.
Table 1. Zone names, volumes, and baseline ventilation rates.
Zone name
Zone volume (m3)
Ventilation rate (Ir1)
Living space
300
0.5
Attic
150
2.0 (vented)
0.7 (unvented)
Crawlspace
150
1.0 (vented)
0.35 (unvented)
6.1.1.1,2
"Typical" passenger vehicle
EPA used 3.4 »r as the typical interior volume of a small SUY (passenger volume plus cargo volume).
The in-vehicle ventilation rate can be drastically different depending on factors such as whether the
vehicle is moving, how the AC operates, and vehicle type and age. A study by Ott et al. (2007) shows
that, with a vehicle moving, windows closed, and the ventilation system off (or the air conditioner set to
AC Max), the air change rate was less than 6.6 h"1 for speeds ranging from 20 to 72 mph (32 to 116
km/h).
In this work EPA assume the air change rate is 5 h for a moving vehicle with windows closed, and 0.5 h
1 for a stationary vehicle with windows closed.
6.1.1.1.3 Temperature in the vehicle
For a moving vehicle with the AC on, EPA assume the temperature inside the cabin is constant and at 21
°C.
128
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
For a stationary vehicle, EPA assume its temperature is subject to diurnal fluctuation, as defined by the
following parameters:
Daily average 20 °C
Daily fluctuation ±15 °C
Peak temperature occurrence 2:00 pm
6.1.1.1.4 HBCD source
The parameters EPA used to represent the HBCD sources in passenger vehicles are the same as those in
Table 2 except that the source area is 0.5 m2 and that the HBCD content in the polymer is 2.5%.
6.1.1.1.5 Settled dust
The parameters EPA used to represent the settled dust in passenger vehicles are the same as those in the
simulations for homes (Table 4).
6.1.1.1.6 Estimation of key parameters
Material/air partition coefficient (K)
EPA have been unable to find experimentally determined material/air partition coefficients for
HBCD in insulation boards. In this evaluation, EPA estimated K from Equation 7 (Guo, 2002):
In K = 9.76 - 0.785 In P (7)
where P is the vapor pressure, mm Hg.
The K values obtained from Equation 7 was then adjusted by the density of the foam material
(Equation 8):
K' = K — (8)
P 0
where
K' is the partition coefficient for the foam board, dimensionless,
K is the partition coefficient for the neat polymer, dimensionless,
p is the density of the foam, g/cm3,
po is the density of the neat polymer, g/cm3; po= 1.05 for polystyrene polymer.
The temperature dependence of the partition coefficient was estimated by the method proposed
by Tian et al. (2017):
ln!k = a^(±-±) (9)
R \T2 T^J v '
where
Ki, K2 are partition coefficients at temperatures Ti and l'i (dimensionless),
a is the absolute value of the slope for the ln(A")-ln(/') relationship, where P is vapor pressure.
129
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
AHV = vaporization enthalpy (J/mol),
Tu T2 = absolute temperature corresponding to Ki and K2 (K),
R = gas constant (J/mol/K).
Parameter a is reported to be between 0.753 and 1.05 for open-cell PU foam. In this work, EPA
used a = 0.9 and AHV = 8.14* 104 J/mol (Tian et al., 2017).
Solid-phase diffusion coefficient (I))
A QSAR model developed by Huang et al. (2017) was used to estimate the solid-phase diffusion
coefficient for the foam materials (Equation 10):
where
m is the molecular weight of the chemical, g/mol,
b is an empirical constant that reflects the material type,
r is an empirical constant that reflects the temperature effect,
T is temperature (K).
The values of b and x for polystyrene foams — including both XPS and EPS — are -8.323 and
1676, respectively. The difference between XPS and EPS is discussed in Section 1.2.6 of the
main risk evaluation document.
Aerosol/air partition coefficient (KP)
The aerosol/air partition coefficient was calculated from Equation 11 (Finizio et al., 1997):
where
m and b are constant for a given chemical,
Koa is the octanol-air partition coefficient (dimensionless).
In this work, EPA used Koa = 2.92 x 1010 for HBCD (from EPA's EPI Suite
(https://www.cim.gOv/tsca-scrccning-tools/epi-suitctm-cstimation-pros:ram-intcrfacc). The m and
b values for generic organic compounds are m = 0.55, and b = 8.23 (Finizio et al., 1997). The
resulting Kp is 3.36 x 109 for HBCD.
Dust/air partition coefficient (Kd)
r—3486
log D = 6.39 — 2.49 log m + b H —
(10)
logtfp = m log Koa + b
(11)
The dimensionless dust/air partition coefficient was estimated with the empirical model
developed by Shoeib et al. (2005):
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Kd = 0.411 pfocKOA (12)
where
p is the density of the dust, g/cm3,
foe is the organic carbon content in the dust, fraction,
Koa is the octanol/air partition coefficient, dimensionless.
6.1.1.1.7 Model parameters
• HBCD sources - polystyrene foam boards
EPA assume that the source areas are 180 m2 in the attic and 120 m2 in the crawlspace (Bevington et al.,
2017). Other parameters are summarized in Table 1.
Table 2. Parameters for the HBCD sources.
Parameter
Value
Data source/method
Board thickness (cm)
10
FOAMULAR 400 specs
HBCD content
0.50%
EPA report (2014)
Board density (kg/m3)
28.9
FOAMULAR 400 specs
Partition coef. (K) at 21 °C
1.70 x 107
Guo (2002); adjusted by
foam density
K as a function of temperature
Equation 9
Tian et al. (2017)
Diffusion coef. (D) at 21 °C (m2/h)
3.20 x 10"12
Huang et al. (2017)
D as a function of temperature
Equation 10
Huang et al. (2017)
• HBCD sinks - gypsum board walls
The indoor sinks in the living space are represented by the gypsum board walls. Parameters used are
shown in Table 3.
Table 3. Parameters for the HBCD sinks.
Parameter
Value
Data source/method
Surface area (m2)
800
Bevington et al. (2017)
Thickness (m)
0.01 (-3/8 inch)
Product specs
Partition coefficient (dimensionless)
5.88 x 10s
Guo (2002)
131
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Diffusion coefficient (nr/h)
1.08 x 10"
Huang et al. (2017)
• Airborne PM
For airborne particulate matter, EPA used the following parameters:
- Particle size
- Mass concentration in ambient air
- Infiltration factor
- Aerosol/air partition coefficient
method)
- Deposition rate constant
- 0.60 for attic and crawlspace
- Settled dust
The parameters EPA used to model settled dust are presented in Table 4.
2.5 |im
30 |ig/m3
0.8
3.36 x 109 (by the Finizio et al. (1997)
0.68 h"1 for the living area
Table 4. Parameters for settled dust.
Parameter
Value
Data source/method
Average diameter (|_im)
50
Bevington et al. (2017)
Dust loading (g/m2)
10
Bevington et al. (2017
Partition coefficient
2.90 x 109
Shoeib et al. (2005)
Diffusion coefficient (m2/h)
1.0 x 10"13
Estimated [1]
[1] The reported diffusion coefficient values for aerosol particles vary significantly. The value EPA used is
in the middle.
6.1.2 IIOAC
EPA/O PPT's Integrated Indoor-Outdoor Air Calculation (IIOAC) was used to estimate ambient air
concentrations for highly exposed groups living near facilities. IIOAC is based on a set of pre-run
AERMOD dispersion scenarios at a variety of meteorological and land-use settings. For the source types
of interest in HBCD modeling, users are required to enter: (1) emission parameters - emission source type,
number of emission scenarios, number of releases per scenario, mass released per day, release duration,
number of release days, and release pattern; (2) system parameters - applicable only for fugitive sources
where an area must be specified; and (3) location parameters - urban or rural setting, particle size/vapor,
and climate region. IIOAC outputs of daily-averaged air concentration, annual-averaged air concentration,
and doses are provided as central tendency and high-end estimates at two distances: fenceline (100 m from
source) and community (averaged across 100 to 1,000 m from the source).
IIOAC calculates ambient air concentration based on the release duration and number of days of release
per year entered by the user (e.g., release occurs 4 hrs/day for 52 days in a year). An adjusted emission rate
is first calculated, as shown in Equation 1, to take into account the release duration and convert the user-
defined mass released per day into g/s.
132
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
ERadj=~- 0.2778 (1)
where ERadj = adjusted emission rate [g/s]
ER = user-defined mass released per day [kg/day]
h = emission duration [hrs/day]
0.2778 = conversion factor from kg/hr to g/s
Air concentrations are calculated in Equation 2 by scaling the post-processed AERMOD result, obtained
based on an emission of 1 g/s, by the adjusted emission rate. For fugitive sources, scaling by just the
adjusted emission rate gives an air concentration corresponding to an area size of 100 m2, the same as that
used in the AERMOD runs. To account for a different area size, an area size scaling factor, SFj, is
applied.
ER rt '
Coutdoor = —V"' SFj ' Postprocessed AERMOD result (2)
13 Is
where Coutdoor = outdoor air concentration | (.ig/ni11
ERadj = adjusted emission rate [g/s]
SFj = scaling factor for fugitive area size j [-]; set to 1 for point sources
For point and fugitive sources, three particle size scenarios are available:
• Fine particles (with a mass-mean aerodynamic diameter of 2.5 (j,m),
• Coarse particles (with a mass-mean aerodynamic diameter of 10 (j,m), and
• Vapor (no particles).
All calculated air concentrations of fine and coarse particles are capped by an upper limit equal to
the National Ambient Air Quality Standards (NAAQS) for particulate matter (PM) (US EPA
2016b). These limits are 35 and 150 [^m/m3 for fine and coarse particles (i.e., the NAAQS for
PM2.5 and PM10), respectively. For vapors, the chemical is released in gaseous form and therefore
there is no transfer from one phase to another. IIOAC currently does not set an upper limit for
point and fugitive sources in vapor form, air concentrations are then calculated by multiplying the
ambient air concentration by an indoor-outdoor ratio.
In modeling ambient air concentration for highly exposed groups living near facilities, twelve
emission scenarios were considered, based on the conditions of use defined in the engineering
assessment (EPA, 2019). For scenarios with site-specific information, this information was used
in the IIOAC model runs. When site-specific information was not unknown, the following default
parameters were used:
133
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
• Emission parameters:
o Source type: Both stack and fugitive,
o Emission duration: 24 hours.
o Release pattern: Conservative pattern of release was used for all runs.
• System parameters:
o Fugitive source area: 100 m2
• Location parameters:
o Population setting: Rural
o Particle size: Coarse - In the United States, standard grade HBCD powder is
defined as a mean particle size of 20 to 150 pm; therefore, coarse particles was
selected for use in the IIOAC runs,
o Climate region default: Three regions were used:
¦ West north central to obtain central tendency estimates for both air
concentration and particle deposition.
¦ South (coastal) to obtain high-end estimates when considering only air
concentration.
¦ East north central to obtain high-end estimates when considering both air
concentration and particle deposition.
6.1.3 WWM-PSC
The Point Source Calculator (PSC) is variation of the Variable Volume Water Model (VVWM) used by
the USEPA for chemical exposure in surface waters. Details of the VVWM are given in the model user
guide (EPA 2019). The PSC is similar to the SWCC and PFAM in that employs a user-friendly interface
that generates a VVWM input file, runs the VVWM, and processes the data. The differences in PSC,
SWCC, and PFAM are essentially in the user interface and in the post processing output. In the case of
the PSC, the user interface and post processing are intended to assess chemicals that flow directly into a
water body and to compare the chemical concentrations to levels of concern.
Inflow
Washout, Dispersion
Degradation doe to:
metabolism, hydrolysis,
photolysis, etc.
Water-Column-to- Benthic
Mass Transfer
Benthic Region
Figure 1. Depiction of the chemical processes in the Point
134
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
The conceptualization of the processes in the PSC is given by Figure 1. In this conceptualization, the
VVWM is used to represent a segment of a water body which receives a direct application of a chemical.
The chemical immediately mixes with the water column of the segment. The water column is coupled to a
sediment layer and chemical can move into the sediment by a first-order mass transfer process. Chemical
can degrade in the water column by user-supplied inputs of hydrolysis, photolysis, and general
degradation. Water column chemical can also volatilize according to chemical properties supplied by the
user. In the benthic region, the chemical can degrade by hydrolysis and a general benthic degradation rate
as supplied by the user. Partitioning to suspended sediment as well as benthic solids occurs according to
input values for either an organic carbon portioning linear coefficient (Koc) or a linear sorption coefficient
(Kc).
In all cases, the waterbody is modeled as a single segment (comprised of a water column and a benthic
region), with the appropriate segment being the one that receives the direct application of the chemical.
6.2 Overview of Indoor SVOC Exposure, Fate, and Transport
The indoor environment is complex. Research on emissions from sources and assessment of human
exposure to indoor pollutants is of increasing interest (Guo. 2'». i; laekouridis < i . '¦1. i; nuj. 201.3;
Salthammcr and Bahadir. 2009). A detailed understanding of most relevant chemical substances,
including their physical-chemical properties, sources, distribution among indoor media (such as the gas
phase, airborne particles and settled dust), and contact with receptors is needed to more accurately
estimate exposure. Sources may include building products, furnishings and other indoor materials that
often contain semi-volatile organic compounds (SVOCs) such as flame retardants and plasticizers. Many
studies have shown that the types of sources in residential and commercial indoor environments, the range
of emitted compounds and the duration of emission can vary widely [see for example (Sta.plet.on et. aL
200.5; Singer et. al.„ 2004; Zhao et. aL 2004)1.
SVOCs including flame retardants and plasticizers are commonly found in many products used in homes
or other indoor environments and have been detected in a wide variety of indoor air and dust samples [see
for example (Weschler and Nazaroff. 201.0; Allen et. aL 2008)1. Exposure may occur via inhalation,
dermal or oral pathways from several sources including indoor and ambient air, drinking water, soil, food,
indoor surfaces, and household dust. However, the relative contributions from various chemicals in these
media are not well characterized. Because products containing these chemicals are often retained in the
indoor environment for several years over their lifecycle, there is the potential for chronic exposures.
Error! Reference source not found, shows the process flow for SVOC emissions, fate, transport, and
ultimately exposure in the indoor environment.
135
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
II Transport between |H|
Emissionsfrom Source ^ IBM Exposure to Media by
.. .. Exposure Media and „ .
to Exposure Media _ II , _ Pathway
¦ Transformation ¦
Transformation
Flame retardant
concentration in sources
Flame retardant
concentration in
exposure media
Monitoring Data
Figure 6-1. Overview of indoor emission, fate, transport, and exposure to SVOCs.
Flame retardants or other SVOCs can enter indoor air by volatilization from the consumer articles; the
airborne SVOCs can be adsorbed or absorbed by settled dust, suspended particles and interior surfaces.
The dust may absorb SVOCs by direct contact with the article; and the article itself can be abraded such
that small pieces of the article become constituents of indoor dust. Human receptors in the indoor
environment can interact with the article via dermal contact (touching) or mouthing of the article itself.
Flame retardant additives can also be emitted/extracted from the article during cleaning, such as washing
textiles. These processes are presented graphically in Error! Reference source not found, and detailed
in the following sections.
Source to air
Source to water
(cleaning,
washing)
Source to receptor
saliva, skin, sweat)
Source to
dust in
direct
contact
Figure 6-2. Example emission pathways for flame retardants.
Chemical Mass Transfer from Source to Air: Flame retardant additives are SVOCs with low vapor
pressures (~1014 to 10"4 atm). Because SVOCs have a strong affinity to indoor surfaces and particles,
measuring their emission rates has been challenging. Given the low concentrations in air, methods with
detection limits in the pg/m3 range are required. Furthermore, SVOCs are often adsorbed to the sampling
apparatus itself, hindering the measurement (Liang and Xu, 2014; Liu et al., 2013; Katsumata et al.,
2008). It is important to note that, while the SVOC emissions are relatively slow the emissions can be
136
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
nearly constant overtime and last for years or even decades. Besides, indoor SVOC sources often cover
large surface areas.
Emission of flame retardants via volatilization can be described by the two-phase mass transfer theory
and depends on the chemical-polymer specific diffusion, partitioning, and mass transfer coefficients, as
shown in Equation 1. In the first phase of mass transfer the chemical diffuses through the article to the
surface. The chemical flux is described by the solid phase mass transfer coefficient (2D/L) and the
concentration gradient in the solid. In the second phase, at the surface of the article, the gas-phase mass
transfer coefficient (ha), along with gas-phase concentration gradient, is used to describe the rate of
chemical movement from the surface to the air. By combining the two resistances in series, the overall
gas-phase mass transfer coefficient (Hsource) can be estimated. (Guo, 2013)
1
Hsource
where:
^source = Overall gas-phase mass transfer coefficient for interior source (m/hr)
Ds = the SVOC solid-phase diffusion coefficient (m2/hr)
L = the thickness of the solid layer (m)
Ksource = the SVOC material-air partition coefficient (unitless)
ha = the SVOC gas-phase mass transfer coefficient (m/hr)
A simpler approach that may be used in a screening model is to assume a constant concentration of flame
retardant in the article (i.e., the flame retardant levels are not appreciably reduced by emissions). With this
approach, diffusion in solid phase can be ignored, and the emission factor is described as
E = ha x (y0 - y) (2)
where:
E = Emission factor (mg/m2/hr)
ha = the SVOC gas-phase mass transfer coefficient (m/hr)
y0 = the SVOC concentration in the air immediately adjacent to the article (mg/m3)
y = gas-phase SVOC concentration in bulk air (mg/m3)
This methodology relies upon measurement or estimation of V/,. In the absence of experimental data, Vt,
can be estimated by either the saturation concentration or the ratio of the SVOC concentration in the
article to the material-air partition coefficient. These methodologies will result in the upper-bound
estimates of the emission rates. (Xu et al., 2012; Xu et al., 2009; Xu and Little, 2006)
Emission rates have been measured for flame retardant article combinations, as shown in Table Error! No
text of specified style in document.. 1. In general, emission rates are on the order of micrograms per
hour, with whole house emission rates of various brominated flame retardants calculated on the order of
hundreds of milligrams per year (Batterman et al., 2010). While changes in relative humidity do not
appear to affect emissions appreciably (Clausen et al., 2004), increased temperatures are shown to
1^—+ t 0)
j source a
137
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
increase emissions (Kajiwara et al., 2013; Destaillats et al., 2008; Carlsson et al., 2000). This is of
importance as flame retardants are added to electronics, foam insulation, automobile interiors, and other
materials that could be exposed to heat while in use.
Table Error! No text of specified style in document..1. Measured emission rates of flame
retardants from articles
Flame Retardant
Article
Emission Factor
Source
HBCD
computer casing
0.4 ng/m2/hr
Kemmlein et al. (2003)
HBCD
textile
0-8,000 ng/m2/hr
Kajiwara et al. (2013)
insulation
0.1-30 ng/m2/hr
Kemmlein et al. (2003)
TCPP
computer casing
24 ng/unit/hr
Destaillats et al. (2008)
PUF / insulation
12-140,000 ng/m2/hr
Kemmlein et al. (2003)
6.2.1 Chemical Mass Transfer from Source to Particles
The transfer rates of flame retardants from the article surface directly to the dust in contact with the article
are difficult to measure and more research is needed (Liagkouridis et al., 2015). Currently, no models
exist to predict dynamic transfer rates directly to dust. Elevated levels of flame retardants have been
measured in dust found near or on flame retardant sources as compared to the whole house dust
(Brandsma et al., 2014). In the case of HBCD, the surface concentrations greater than 400 ng/m2 have
been measured on the surface of electronics (Di Napoli-Davis and Owens, 2013). HBCD has been
measured in the dust inside television casings at levels of 240 ng/g and 2.5 ng/g, respectively (Takigami
et al., 2008). In one study, the presence of dust on the surface of sources was shown to increase emission
rates for SVOCs by increasing the external concentration gradient above the surface of the substrate
(Clausen et al., 2004).
If the dust-air and source-air partition coefficients are known for the chemical of interest, the maximum
SVOC concentration that would be found in dust in direct contact with the surface of an article can be
described by the material-dust partitioning coefficient as shown in Equation 3.
Cd Kda
K — — —
"¦dm
(3)
where:
Kdm = the SVOC solid-solid partition coefficient between dust and source (unitless)
Cd = equilibrium SVOC concentration in dust (mg/m3)
138
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Cm = equilibrium SVOC concentration in source material (mg/m3)
Kda = the SVOC solid-air partition coefficient between dust and air (unitless)
Kma = the SVOC solid-air partition coefficient between source and air (unitless)
6.2.2 Chemical Mass Transfer from Source to Skin
Dermal exposure to flame retardants can occur via direct skin contact with the source article. While flame
retardants can partition into skin surface lipids and be subsequently absorbed, skin functions as a barrier
to xenobiotic chemicals. However, sweat on the surface of the skin can mediate this process. Migration
rates for TCPP from foam to simulated sweat have been measured upwards of 130 (.ig/cirr/hr (European
Commission, 2008).
In general, dermal absorption is described as a flux through the skin that is based on a chemical-specific
skin permeability coefficient (Weschler and Nazaroff, 2012). For more volatile compounds, a competing
evaporative flux away from the skin must also be considered. In general, the permeability is the rate-
limiting step rather than the mass of flame retardant available on the skin, which makes comparisons of
published data based on fraction absorbed challenging. Absorption rates of 2-20% have been reported for
HBCD (Abdallah et al., 2015a). Associated permeability coefficients for HBCD have been shown to be
on the order of 10"3 cm/hr; permeability coefficients for HBCD have been measured on the order of 10"4
cm/hr with associated fluxes ranging from approximately 0.5 to 1.5 ng/cm2/hr (Abdallah et al., 2015b).
Although measuring the flux through the skin is challenging, measurement of flame retardants on the skin
can provide evidence of transfer to the skin, making the chemical available for subsequent absorption.
Makinen et al. (2009) measured TCEP, TCPP, TDCPP, and HBCD residues on hands via wipe sampling
in occupational settings as a surrogate for dermal exposure and found the average levels ranging from 2 to
70 ng/2 hands. Keller et al. (2014) showed that touching tent fabrics resulted in a transfer of TDCPP to
the hands; less evidence of transfer of HBCD was presented.
6.2.3 Transfer to Dust by source fragmentation and direct source-dust contact
In addition to volatilization, the article itself can be abraded to the extent that small pieces of the article
are ground into dust. This portion of the dust would have elevated additive levels, equal to that of the
original source article. This pathway, though not well characterized, is believed to be a possible
explanation for underpredictions of flame retardant concentrations in dust from exposure models used to
characterize emissions. Rauert et al. (2014) mimicked physical abrasion of HBCD-treated textiles and
saw an increase of HBCD in deposited dust from 110 ng/g to 4,020-52,500 ng/g. Additionally, the dust
fibers were analyzed via microscopy and determined to be consistent with fragments of the source article.
These results are supported by (Cao et al., 2014; Cao et al., 2013; Cao et al., 2012; Suzuki et al., 2009),
who analyzed flame retardant levels in dust by particle size. Flame retardant concentrations were highest
in the finest particle range. This is hypothesized to be due to gas-phase partitioning. A second peak of
flame retardant concentration was found in dust particles in the mid-size range. These findings suggest
that the abrasion of materials such as upholstery that contain flame retardants plays an important role in
determining the levels of flame retardant in dust.
If dust is present on the surface of an article, a chemical can directly transfer from the source to the dust.
This process has been reported for HBCD-treated textiles in modified chambers (Rauert et al., 2016), and
for PCB treated primer and caulk in modified chambers (Liu et al., 2016). This pathway, though not well
characterized, can explain the high dust concentrations reported on the surfaces of some objects.
139
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
6.2.4 Fate and Transport of Chemical Substances within Indoor Environments
Once emitted to the indoor environment, flame retardants undergo a variety of fate and transport
processes, vapor-phase flame retardants can be transferred via diffusion and partitioning to particles or
other sinks, such as furnishings, building materials, or clothing. Sinks can also become secondary sources
of SVOCs. Airborne chemicals, either in the vapor phase or particle-bound, can then be removed from the
indoor environment (and released to the outdoor environment) via ventilation. Flame retardants in settled
dust can be removed via surface cleaning. Articles containing flame retardants can be disposed of via
trash or recycling, and flame retardants can be removed from articles via washing. These processes are
shown in Error! Reference source not found, and discussed in the following sections.
Ventilation
Ambient Partic
Airborne SVOC
^¦Photolysis
•••
Mass
transfer
to sinks &
receptors
SVOC emission
from source to air
Particles
Mass
transfer to _ _
Deposition &
particles & reSuspension
dust of particles
Out-
the-
window
Cleaning
Garbage
Recycling
*Not shown: Down-the-drain Dust
Figure 6-3. Relevant fate and transport processes in the indoor environment.
6.2.5
Chemical Mass Transfer between Air and Particles
Gas-phase SVOCs, including flame retardants, will partition between the gas-phase and airborne
and settled particles. The equilibrium concentration between the gas and particle phases is
described by the gas-particle partition coefficient. This is a function of the flame retardant itself,
the composition of the particles, and temperature. Particle-air partition coefficients are difficult to
measure and data is rare. Measured partition coefficients in the literature are summarized in Table
X. An empirical relationship for partitioning between air and particles is presented in Weschler
and Nazaroff (2010) and shown in Equation 12.
Kv=ft
omjpart
X
Kn
Ppart
(12)
where:
Kp = SVOC partition coefficient between air and TSP (Ktsp) or dust (Koust) (m3/mg)
fomjpart = volume fraction of organic matter in airborne particles (unitless)
Koa = octanol-air partition coefficient (unitless)
Ppart = density of airborne particles (mg/m3)
140
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
However, the gas and particle phases do not reach instantaneous equilibrium. The rate of transfer
between the air and gas phase is described by the gas-phase mass transfer coefficient. Available
measured mass transfer coefficients are presented. An empirical relationship between the
molecular weight and the gas phase mass transfer coefficient is presented in the Arthur D Little
Migration Estimation Model (AMEM) and is shown below. Recent research (U.S. EPA, 2007) has
shown that partitioning is dependent on the vapor pressure, temperature, particle size, indoor air
velocities, and can be described to varying degrees in relation to other partitioning coefficients,
including Henry's Law constant and the octanol-water partition coefficient (Liu et al., 2015;
Salthammer and Schripp, 2015; Guo, 2014; Liu et al., 2014)
ha = 46.8 X — ^ (12)
a (2.5+MW1/3) v '
where:
ha = gas phase mass transfer coefficient for SVOC between bulk air and surface (m/hr)
MW = molecular weight (g/mol)
6.2.6 Chemical Mass Transfer between Air and Sinks
The behavior that describes SVOC release from a source to the air can also be used to describe the
SVOC transfer between the air and the sink. In reality, SVOC transfer to particles is a special case
of transfer to a sink. The equilibrium concentrations are described by the material-air partition
coefficient, and the rate of transfer is described by the mass-transfer coefficient and fugacity
difference between the two phases. Common indoor sinks, such as furnishings and building
materials, have a much larger mass and volume than indoor particles, meaning that much more
SVOC mass can be absorbed by the sink before equilibrium is reached. In addition to the
concentration gradient, the rate of transfer will be determined by the room temperature and
properties of the sink itself (Bi et al., 2015; Guo, 2014, 2013; Stapleton et al., 2005). It is important
to note that after a primary source has been removed, lowering the air concentration of the SVOC
and reversing the concentration gradient, the sink can become a secondary source (Zhao et al.,
2004). A particular sink of emerging interest is clothing and bedding, which can absorb SVOCs
between washings and then, when used in close contact with a receptor, serve as a secondary source
of both inhalation and dermal exposures (Morrison et al., 2015)
Few data are available to describe the partitioning and mass transfer between the air and specific
sinks. The equations from Section 3.1.1.1 and 3.1.2.1 can be applied to sinks.
6.2.7 Relationship between prevalence in media and physical-chemical properties
The physical-chemical properties of HBCD can be found in Section 1.1 of the main risk evaluation
document.
The physical-chemical properties of chemical substances inform the exposure media a chemical is
likely to be found in and, therefore, affect indoor exposures. SVOC chemicals generally have
higher molecular weights, lower vapor pressures, higher boiling points, and higher log Koas than
VOCs. Therefore, SVOCs are more likely to be found sorbed to indoor particles or sinks than in
the gas-phase compared to VOCs. HBCD has a relatively low vapor pressure as an SVOC. In
141
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
addition, the log Koa for HBCD is relatively high compared to other SVOCs, indicating its strong
affinity to bind to particles in the indoor environment (Weschler and Nazaroff, 2010).
Measurements of physical-chemical properties can vary for a given chemical and estimates can be
uncertain (Salthammer and Schripp, 2015). However, measurement of physical-chemical
properties is important to accurately assess the fate, transport, and potential exposures to chemicals
in indoor environments.
6.2.8 Estimating Exposure and Relevant Exposure Pathways for SVOCs
Gas-phase SVOCs and SVOCs sorbed to suspended particles can be inhaled via indoor air.
Physiology, including age, gender, and body mass index, and activity level impact breathing rates
and directly impact exposure. Gas-phase SVOCs can result in higher exposures because they are
more readily absorbed by the body. SVOCs sorbed to particles, as HBCD is expected to be, can
have a longer residence time in the lung particularly for small particles that penetrate deep into the
lung. SVOCs sorbed to larger particles can be trapped in the upper airway and subsequently
coughed out or swallowed, resulting in ingestion exposures.
6.2.9 Ingestion of Suspended Particles, Settled Dust, and Mouthing
In addition to the ingestion of previously inhaled particles, as discussed in the previous section,
settled particles can also be ingested either due to hand-to-mouth or object-to-mouth transfer of
dust. This exposure is driven by the frequency and duration of hand-to-mouth and object-to-mouth
events, which is likely to be higher in young children. Small children also spend more time in
closer proximity to the floor which may explain their higher exposure through this pathway.
Reported dust ingestion rates are highly variable and expected to vary by person due to the age
and behaviors of the individual, such as handwashing, and the environmental conditions, such as
the dusty level of the environment.
Because SVOCs like HBCD may be found in consumer articles in which children come into
contact, mouthing, or directly licking or sucking, the HBCD-containing article can also contribute
Figure X. Inhalation of Vapor-Phase Air and Suspended Particles
142
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
to exposures. As with dust ingestion, mouthing exposure increases with the duration and frequency
of mouthing behavior, and is expected to be more relevant to children than adults. Mouthing
exposure is also highly dependent on the transfer of the SVOC, like HBCD, from the source to the
saliva, termed the migration rate. This is expected to be dependent on both the additive (HBCD)
and the polymer. Although migration rates can be determined experimentally through in-vitro
and/or in-vivo approaches, data have been scarce in the literature. Mouthing is discussed in detail
in Section 6.2.9.
Regardless of the pathway of ingestion, ingestion exposure depends on the ability of the chemical
Figure 6-4. Percentage of inhaled particles that are trapped in either the lung or nose by
particle diameter.
U.S. Bureau of Mines (1987)
6.2.10 Dermal Contact with Source, Airborne SVOCs, and Sinks
Chemicals can contact the skin by direct contact with sources, contact with dust on surfaces of
floors or objects, air deposition to the skin, or direct contact with secondary sources (sinks) with
or without adhered dust. Hand wipe samples and other methods that measure chemical loadings
on skin surface show that chemicals can remain on the skin. Additionally, it has been shown that
low vapor pressure compounds such as HBCD are more likely to be absorbed by the skin than
higher vapor pressure chemicals (Weschler and Nazaroff, 2014). Therefore, in addition to
ingestion exposure resulting from hand-to-mouth contact, dermal absorption should be considered.
The amount of chemical that is absorbed into the skin depends on the competing processes of a
chemical flux to and through the skin and chemical flux away from the skin, either by volatilization
or washing. Clothing, bedding, and other physical barriers may prevent or reduce chemical contact
with the skin or serve as vectors that increase exposure (Nazaroff and Goldstein, 2015).
Generally, dermal absorption rates tend to be lower than inhalation and ingestion rates and an
individual may need to spend more time in a microenvironment (on the order of hours) for dermal
exposure whereas inhalation and ingestion exposures occur more quickly. However, this pathway
may contribute to overall exposure even though it is not as well characterized.
143
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
6.3 Age-Specific Exposure Factors and Activity Patterns Used in this Assessment
Table Error! No text of specified style in document..2: Body Weights
Age Grouping
Males & Females
N
Mean
10th
Birth to <1 month
158
4.8
3.9
1 to<3 months
284
5.9
4.7
3 to<6 months
489
7.4
6.1
6to<12 months
927
9.2
7.5
1 to <2 years
1,176
11.4
9.3
2 to <3 years
1,144
13.8
11.5
3to<6years
2,318
18.6
14.4
6 to <11 years
3,593
31.8
21.3
11 to <16 years
5,297
56.8
37.2
16 to <21 years
4,851
71.6
52
21 to <30 years
3,232
78.4
54.7
30 to <40 years
3,176
80.8
57
40 to <50 years
3,121
83.6
58.8
50 to <60 years
2,387
83.4
59
60 to <70 years
2,782
82.6
59.8
U.S. EPA (2011). Chapter 8.
Table Error! No text of specified style in document..3: Body Weights Used in the Assessment
Age Grouping
Body weight Used
(kg)"
CT
HE
Infant (<1 year)
7.7
6.3
Young Toddler (l-<2 years)
11.1
9.1
Toddler (2-<3 years)
13.5
11.0
Small Child (3-<6 years)
18.3
14.3
Child (6-
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Table Error! No text of specified style in document..4: Dust and Soil Ingestion Rates by Age
Age Grouping
Dust Ingestion Rate (mg/day)
Soil Ingestion Rate (mg/day)
CT (mean)
HE (95th)
CT (mean)
HE (95th)
Infant (<1 year)
30.0
80.0
25.0
70.0
Young Toddler (l-<2 years)
50.0
100.0
40.0
90.0
Small Child (2-6 years)
30.0
100.0
30.0
90.0
Child (6-16
Table Error! No text of specified style in document..6: Generic Activity Patterns for Time
Spent Awake
Time Awake Spent
(hr/day)1
Fraction Awake Time Spent
(unitless)
Microenvironment
SAH Adult/
Child
Part-Time
School/
COF/
Work
Full-Time
School/
COF/
Work
SAH Adult/
Child
Part-Time
School/
COF/
Work
Full-Time
School/
COF/
Work
Comm/ Public/ Gov
/ School / COF
1
3
6
0.07
0.23
0.46
Outside
2
2
2
n/a
n/a
n/a
Automobile
1
2
2
0.07
0.15
0.15
Residences
11
8
5
0.84
0.62
0.38
U.S. EPA (2009). Informs Dust and Soil Ingestion as these activities only occur when awake. Assumed Sleep time is 9 hours per
day based on weighted average across age groups, and 15 hours are spent awake. Assume that all soil ingestion that would
occur, occurs while outdoors-no fraction of day is applied to soil ingestion exposure equation.
145
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Table Error! No text of specified style in document..7: Generic Activity Patterns for Total
Time Spent
Microenvironment
Time Spent Total
(hr/day)1
Fraction Time Spent Total
(unitless)
SAH Adult/
Child
Part-Time
School/
COF/
Work
Full-Time
School/
COF/
Work
SAH Adult/
Child
Part-Time
School/
COF/
Work
Full-Time
School/
COF/
Work
Comm/ Public/ Gov
/ School / COF
1
3
6
0.04
0.125
0.25
Outside
2
2
2
0.08
0.08
0.08
Automobile
1
2
2
0.04
0.08
0.08
Residences
20
17
14
0.83
0.71
0.583
U.S. EPA (2009). Informs Inhalation pathway as breathing occurs 24 hours per day.
These generic activity patterns were informed by an analysis of the CHAD database. The amount of time
that children and adults spend in different microenvironments is highly variable. It influences both the
magnitude of the concentration and the duration of exposure over which people are exposed. CHAD
contains the most robust human activity data available and contains activity-pattern information from
survey respondents who logged their location for one or multiple days. The database contains this
information for individuals on different days and for people ranging from young children to adults.
The database contains information from different surveys, and all data were used in the analysis. As a first
step, an initial quality control step was performed. The number of unique entries in the database was
determined to be 1,901,301. The number of unique entries in the database after removing entries where
field QCMiss > 60 (either activity or location is unknown for more than 1 hr/day) and field qcsleep is
missing (no sleep time entered) was 1,633,914. The corresponding unique number of activity days
captured in the database is 42,090. From here, percentile estimates of time spent by age group,
weekday/weekend, season, and overall microenvironment type were calculated. The following equation
was used to take a weighted average across seasons and weekends/weekdays for the overall time spent
(TSmerall).
TS0verall ~ 0.25 X X TSsummel—weekday y ^ ^^summei—weekend
G
(I
+ 0.75 X ( _ X TSnon-summei—weekday y ^ TSn0n-summei—weekend
The interquartile range, from the 25th to the 75th percentile, was used to inform the generic activity
patterns selected for the analysis. All the estimates in Table Error! No text of specified style in
document..6 and U.S. EPA (2009). Informs Dust and Soil Ingestion as these activities only occur when
awake. Assumed Sleep time is 9 hours per day based on weighted average across age groups, and 15
146
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
hours are spent awake. Assume that all soil ingestion that would occur, occurs while outdoors-no fraction
of day is applied to soil ingestion exposure equation.
147
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Table Error! No text of specified style in document..7 are generally within the interquartile ranges
identified below. While there is some variation across age groups, three generic activity patterns were
applied across all age groups.
Table Error! No text of specified style in document..8: Interquartile Range of Hours/Per day
in Microenvironments from CHAD
Residences
Schools
P&CB
Outside
Automobile
Age Group
25t
h
50t
h
75t
h
25t
h
50t
h
75t
h
25t
h
50t
h
75t
h
25t
h
50t
h
75t
h
25t
h
50t
h
75t
h
1:1&
under
19.
5
21.
6
23.
2
3.0
6.5
8.5
0.7
1.3
2.3
0.6
1.2
2.3
0.5
1.0
1.6
2:1 to 2
17.
3
20.
2
22.
5
2.8
5.7
7.1
0.6
1.3
2.2
0.9
1.8
3.1
0.5
1.0
1.5
3: 3 to 5
16.
1
18.
6
21.
3
2.9
5.0
6.7
0.6
1.2
2.3
0.9
1.9
3.3
0.5
1.0
1.5
4: 6 to 10
15.
1
16.
8
18.
7
4.7
5.4
6.0
0.6
1.4
2.5
1.2
2.1
3.6
0.5
1.0
1.5
5:11 to 15
14.
9
16.
9
19.
3
4.2
5.6
6.5
0.7
1.8
3.0
0.8
1.9
3.3
0.5
1.0
1.6
6:16 to 20
14.
1
16.
7
20.
3
3.9
5.4
6.2
1.0
2.7
5.1
0.6
1.5
2.9
0.5
1.0
2.0
7: 21 &
above
13.
8
16.
4
20.
6
0.7
2.4
5.9
1.4
4.2
7.6
0.6
1.3
3.1
0.9
1.4
2.1
U.S. EPA (2009)
Table Error! No text of specified style in document..9: Fish Ingestion Rates for General
Population
Age Grouping
Fish Ingestion Rate (g/day)
CT (mean)
HE (95th)
Infant (<1 year)
0.0
0.0
Young Toddler (l-<2 years)
0.6
4.7
Toddler (2-<3 years)
0.6
4.7
Small Child (3-<6 years)
0.7
5.8
Child (6-
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Young Toddler (l-<2 years)
70
Toddler (2-<3 years)
70
Small Child (3-<6 years)
70
Child (6-
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Teen (11-<16 years)
2.7
5.7
Adult (16-<21 years)
2.3
5
Adult (21-50 years)
2.1
4.6
Adult (50+)
1.7
3.6
Table 3.14. Fruit Ingestion Rates
Age Grouping
Fruit Ingestion Rate (g/kg day)
CT (mean)
HE (95th)
Infant (<1 year)
9.9
27.2
Young Toddler (l-<2 years)
9.8
24
Toddler (2-<3 years)
7.7
20.5
Small Child (3-<6 years)
5.8
16.4
Child (6-
-------
PEER REVIEW DRAFT - DO NOT CITE OR QUOTE
Child (6-
------- |