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Story of Brominated Flame Retardants:
Substance Flow Analysis of PBDEs from Use to Waste
By
Golnoush Abbasi
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy,
Graduate Department of Geography, University of Toronto
© Copyright by Golnoush Abbasi, 2015
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Story of Flame Retardants: Substance Flow Analysis of PBDEs
from Use to Waste
Golnoush Abbasi Doctor of Philosophy
Graduate Department of Geography, University of Toronto 2015
Abstract
The main goal of this study was to understand the fate of brominated flame retardants (BFRs),
particularly PBDEs, during the life cycle of BFR-containing products. PBDEs were added to the
Stockholm Convention list of chemicals to be eliminated. The migration of BFRs from products
and their partitioning to dust results in human exposure through dust ingestion and inhalation.
Moreover, during the use of BFR-containing products, direct contact with these products can
lead to human exposure. With the proliferation of BFRs as PBDE alternatives, identifying the
product source of these chemicals is essential to minimize the risk associated with the exposure.
In this research, a rapid and non-destructive method was developed to identify and to some
extent quantify BFRs used in consumer products.
The next step towards the management of these chemicals is to estimate the time course by
which these chemicals will remain in use. Based on consumption patterns of PBDE-containing
products, the time-dependent stock of PBDEs contained in in-use products was estimated for the
U.S. and Canada from 1970 to 2020. Considering only the first lifespan of products, the stock of
PBDEs was estimated to be ~120,000 t in 2014 and it is estimated that by 2020, ~ 60% of this
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stock will remain in products in the use phase. Although the flow of PBDE-containing products
to the waste phase started to decline following 2008, this flow will continue as these products
reach their end of life and enter the waste phase. As these products leave the first use phase,
their accumulation in storage and waste phases will continue to act as sources of PBDEs to the
surrounding environment with annual emission rate of 0.3-4 tonnes·y-1 between 1970 and 2020.
Thus, the management of BFR-containing products deserves more attention as the
mismanagement of these products, especially waste electronics, has led to undesirable and
irreversible global environmental consequences. The results of this dissertation suggest that
current waste management programs in the U.S. and Canada are challenged to deal with influx of
e-waste in the near future.
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Acknowledgment
This thesis is the result of four years of collaborative projects with regional and international environmental research groups, field research, industry interviews, literature reviews and soliciting feedback from the brightest minds in environmental research through presenting at international conferences. I will not be able to name all the great individuals and organizations that made this possible, but I would like to express my gratitude to a few who in my mind made significant contributions: Special mention goes to my supervisor, Professor Miriam Diamond. My PhD has been an extraordinary journey and I thank Miriam, not only for her academic support, enthusiastic help and constantly introducing fresh ideas, but also for encouraging me during this journey. I would also like to extend my gratitude to all my committee members, Dr. D. Muir, V. MacLaren, S. Easterbrook, H. MacLean, C. Kennedy who improved the quality of the this work by providing constructive feedback. I would like to thank Dr. L. Jantunen and Prof. R. Hale for reviewing my thesis as internal and external examiners. Dr. Andreas Buser from the international project team deserves a special mention for his superb and timely feedback all along. He brought a very unique and scientifically informed perspective that tremendously improved the overall quality of this thesis. Along with Andreas, I would also like to thank Anna Soehl and Dr. Mike Murray from my project team who provided good suggestions and helped with collecting data, without which this thesis would not be possible. I would also like to extend my gratitude to Prof. George Arhonditsis who always brought a positive energy to my research and provided me with valuable advice in statistical analysis. From Diamond Group, special thanks go to Aman Saini and Joe Okeme (Dr. to be) for their unconditional friendship and moral support all through these years. Without Aman’s hidden stash of delicious snacks how could I have endured working past midnight in the office?! And if Joe hadn’t graciously accepted the dual role of spiritual- and cheerleader for the team, how could I have survived all the mental and emotional pressures all along?! I will be remiss not mentioning former members of the team, Fe de Leon, for her constant support and inspiration. Dr. Emma Goosey, who helped me in setting up my experiment during her post-doc in our team. I would also like to thank Dr.s Lisa Melymuk and Suzie Csiszar for providing guidance through sharing their experiences of completing and finalizing their thesis. Finally, I would like to thank the new team members: Clara, Congciao, Jimmy, Yuchao and Atousa for their continuously offering their help and support any time I needed an extra hand or a fresh set of eyes. This acknowledgement will be missing its soul if I don’t mention my loving husband Omid and family (Mahnoosh, Hadi, Hanoosh, Ali and Shaliz) and great circle of supporting friends who constantly and unconditionally gave me love and hope to march on to the end. My personal life was an emotional roller coaster during the past couple of years. I lost people that I loved and found new love. There were many moments that I was on the brink of giving it all up. If it wasn’t for them, this thesis would have been left unfinished. Thank you all from the bottom of my heart!
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Table of Contents Abstract ........................................................................................................................................... ii
Acknowledgment ........................................................................................................................... iv
Table of Figures ............................................................................................................................ vii
List of Acronyms ........................................................................................................................... ix
Chapter 1: Introduction .................................................................................................................. 1
1.1 Background and motivation ...................................................................................................... 1
1.2 Research Goal and Objectives .................................................................................................. 7
Chapter 2: Source of Flame Retardants in Canadian House Dust ................................................ 12
2.1 Introduction ............................................................................................................................. 12
2.2 Materials and methods ............................................................................................................ 16
2.2.1 Sampling from homes .................................................................................................. 16
2.2.2 Dust sampling .............................................................................................................. 16
2.2.3 XRF measurements ...................................................................................................... 17
2.2.4 Wipe samples ............................................................................................................... 17
2.2.5 Sample analysis ............................................................................................................ 18
2.2.6 Quality Assurance& Quality Control (QA/QC) .......................................................... 19
2.2.7 Data analysis ................................................................................................................ 19
2.3 Results ..................................................................................................................................... 20
2.3.1 XRF .............................................................................................................................. 20
2.3.2 FR levels in product wipes ........................................................................................... 21
2.3.3 Comparison of Results from XRF and Product Wipes ................................................ 23
2.3.4 FR levels in dust samples ............................................................................................. 24
2.3.5 Association between product wipes and dust .............................................................. 26
2.4 Implications ............................................................................................................................. 30
2.5 Uncertainties and Limitations ................................................................................................. 32
Supporting Information ................................................................................................................. 34
Chapter 3: Stock and Flows of PBDEs in Products from Use to Waste in U.S. and Canada from 1970 to 2020 ................................................................................................................................. 40
3.1 Introduction ............................................................................................................................. 40
3.2 Methods................................................................................................................................... 43
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3.3 Results and Discussion .......................................................................................................... 46
3.3.1 Stocks of CRT TVs and decaBDE ............................................................................... 46
3.3.2 Stock of Commercial Mixtures of PBDEs ................................................................... 49
3.3.3 Stock and Flows of PBDEs .......................................................................................... 51
3.3.4 From Stocks to Emissions ............................................................................................ 54
Supporting Information ................................................................................................................. 58
S 3.1 Methods ....................................................................................................................... 58
S3.1.1 Statistical Methods..................................................................................................... 60
S3.1.2 Time Dependent Stock of PBDE-containing Products ............................................. 61
S3.2. Results and Discussion ............................................................................................... 68
S3.3 Uncertainties ................................................................................................................. 73
Chapter 4: PBDEs in the waste stream; A case of e-waste .......................................................... 75
4.1 Introduction ............................................................................................................................. 75
4.2 Methods................................................................................................................................... 79
4.2.1 Stock and flow of ICT Products ................................................................................... 79
4.2.2 After the first use phase .............................................................................................. 80
4.2.3 Uncertainty Estimation of Input and Transition Coefficient Parameters ..................... 87
4.3 Results ..................................................................................................................................... 89
4.3.1 Stock and Flow of ICT Products and Display Devices in the First Use Stage ............ 89
4.3.2 Stock and Flow of ICT Products and Display Devices in the Second Use Phase and Waste Phase Under Different Scenarios ............................................................................... 92
4.4 Concluding Considerations ................................................................................................... 100
Supporting Information ............................................................................................................... 102
S4.1. Material Flow Analysis after First Life Stage ........................................................... 103
Chapter 5: Conclusion ................................................................................................................ 109
5.1. Major implications of this research .............................................................................. 109
5.2 Recommendations for future work ............................................................................... 113
References ................................................................................................................................... 116
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Table of Figures
Figure 2.1: Percentage contributions of PBDEs and NFRs in product wipes. ............................ 23 Figure 2.2: Percentage contributions of PBDEs and NFRs in house (n=35) and office (n=10) dust. ............................................................................................................................................... 26 Figure 2.3: Correlation between logarithms of the geomean concentrations of FRs in product wipes and dust samples. Blue diamonds represent compounds with lower molecular weight (MW <600 g/mol), black dots represent heavier compounds (MW >600 g/mol). ................................. 27 Figure 2.4: Analysis of FRs in product wipes and dust by means of Principal Components Analysis. Pc 1 and 2 account for 68% of variability in dataset. Five clusters were identified using K-means partitioning and ssi. Crosses “x” represent dust samples and dots represent product wipe samples. Cluster A, was dominated by pentaBDE and its replacements (TDCPP, EH-TBB and BEHTBP), cluster B was dominated by deca- and octaBDE, cluster C by DBDPE and OBIND (decaBDE replacements), cluster D. ........................................................................ 29
Figure 4.1: Material flow analysis of selected ICT products and display devices from the use phase to the waste phase within the U.S. and Canada; use phase comprises of the first and second use stages (reuse and/or storage). EoLE enter the waste phase where they can be disposed of in landfills, incinerated or recovered for the purpose of domestic or offshore recycling and reuse...............................................................................................................................................82
Figure 4.2: Time trend of the mass of in-use ICT products and display devices in million tonnes (Mt) in the U.S. and Canada from 1970 to 2020, (a) PCs, laptops, CRT monitors, flat screen monitors and hardcopy devices in the first use phase, and (b) CRT TVs, flat screen TVs and the total of all products considered in this study.................................................................................90
Figure 4.3: Time trend of the annual mass flow of ICT products and display devices leaving the first use phase in the U.S. and Canada from 1970 to 2020, (a) PCs, laptops, CRT and flat monitors and hardcopy devices, and (b) CRT TVs, flat screen TVs and total ICT products and display devices...............................................................................................................................91
Figure S4.1: Annual transfer coefficients under scenario B for residential products: a) TCs of ICT products and display devices at the end of first use, b) TCs of residential ICT products at the end of second use, c) TCs of residential ICT products at the end of storage.............................. 104
Figure S4.2: Annual transfer coefficients under scenario C: a) TCs of products at the end of first use, b) TCs of products at the end of second use, c) TCs of products at the end of storage …………………..........................................................................................................................105
Figure S4.3: Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario A (Matthews et al. 1997). The stocks
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(oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another ......................................................................................................................................................106
Figure S4.4: Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario B (US EPA 2007, 2011; Babitt et al. 2011). The stocks (oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another …………………………………………………………………………....................107
Figure S4.5: Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario C (based on per capita data from various sources). The stocks (oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another …………………………………………………………………..……..…108
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List of Acronyms
aDP: anti-Dechlorane Plus ATE : allyl-2,4,6-tribromophenyl ether BEHTBP or TBPH: bis(2-ethyl-1-hexyl)tetrabromophthalate BFR: Brominated Flame Retardants c-decaBDE: Commercial decaBDE c-octaBDE: Commercial octaBDE c-pentaBDE: Commercial pentaBDE DBDPE: Decabromodiphenylethane EH-TBB or TBB: 2-ethylhexyl-2,3,4,5-Tetrabromobenzoate EoL: End of Life EoLE: End of Life Electronics EPR: Extended Producer Responsibility ESM: Environmentally Sound Management E-waste: electronic waste FR: Flame Retardants HBB: Hexabromobenzene HFR: Halogenated Flame Retardants HHA: Household Appliance ICT: Internet and Communication Technology IDL: Instrumental Detection Limit LOD: Limit of Detection NFR: Novel Flame Retardants OBIND: Octabromotrimethylphenylindane OPFR: Organophosphate Flame Retardants PBBz : 1,2,3,4,5-Pentabromobenzene PBDEs: Polybrominated diphenyl ethers PBEB: 2,3,5,6-Pentabromoethyl benzene PBT: Pentabromotoluene POP: Persistent Organic Pollutant sDP: syn-Dechlorane Plus TDCPP: Tris(1,3-dichloro-2-propyl)phosphate WEEE: Waste Electrical and Electronic Equipment XRF: X-ray fluorescence
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Chapter 1: Introduction
1.1 Background and motivation The ultimate goal of this project was to understand the fate of brominated flame retardants
(BFRs), particularly polybrominated diphenyl ethers (PBDEs), during the use and disposal of
BFR-containing products. BFRs have been used in products to delay the spread of fire. PBDEs,
a type of BFR, have been used extensively in a wide variety of products since the 1970s. Given
that PBDEs and some other BFRs are typically not chemically bound to plastics, foam, fabrics,
and other materials to which they are added, they are prone to migrate from products into indoor
(Ali et al., 2012; Hazrati & Harrad, 2006; Zhang et al. 2011) and ultimately outdoor
environments (Bjorklund et al., 2012; Csiszar et al. 2013; de Wit, 2002). This, in turn, can result
in direct human exposure to these substances as well as indirect exposure via contaminated soils,
and food supplies (Diamond and Harrad 2009). Concerns about the potential health effects of
PBDEs have arisen from in vitro and in vivo experimental evidence (e.g. Alm et al., 2010;
Stapleton et al., 2006). Recent epidemiological evidence has found associations between PBDE
exposure and altered concentrations of thyroid hormones, decreased fertility in adults and
lowered IQ in children (Eskenazi et al., 2013; Meeker et al., 2009; Turyk et al., 2008).
Three main commercial PBDE mixtures, commonly referred to as c-penta- or penta-, c-octa- or
octa-, and c-deca- or decaBDE came into widespread use in North America in the 1970s. Each
mixture consists of various congeners of PBDEs with different number of bromine atoms, which
some of them are overlapped in c-penta and c-octaBDE mixtures. These congeners are named
based on the number and position of bromine atoms on the diphenyl ether.
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PentaBDE concentrations were reported to be about 10-fold greater in indoor dust collected in
the United States and Canada than New Zealand and the United Kingdom (Harrad et al. 2008).
PBDE concentrations in U.S. and Canadian sewage sludge were measured at least 10-fold
greater than European concentrations (Hale et al., 2002). Within the United States, pentaBDE
concentrations in California household dust exceeded those in other states (Zota et al., 2008).
Although there has been lots of variation in consistent measurement of PBDEs in indoor dust at
each location, the differences in PBDE concentrations amongst jurisdictions are consistent with
the specific jurisdictional requirements of flammability standards for consumer products.
Due to increasing concern regarding the human exposures to PBDEs, the European Union (EU)
first banned the marketing and new use of PBDE-containing products with PBDE levels higher
than 0.1% (RoHS level) of materials in 2003. In Canada, the production and new use of penta-
and octaBDE was banned in 2009. The export of decaBDE to Canada was voluntarily ceased by
three manufacturers in 2010, however, decaBDE may be present in imported products and in-use
products (EC 2015). In early 2000s, some U.S. states (e.g. California, Main) banned the new use
of penta- and octaBDE in consumer products. Following this, the production of these
compounds was voluntarily phased out by industries in the U.S. in 2004. In the U.S., the new
use of decaBDE in products, with some exceptions (e.g. military uses) ceased in 2013. Table 1.1
summarizes restrictions on the production and use of PBDEs.
In 2009, the Stockholm Convention, a global environmental treaty aimed at eliminating and
restricting the production and use of persistent organic pollutants (POPs) to reduce human and
ecosystem exposures to these chemicals, included tetra- to heptaBDE congeners in the Annex of
chemicals to be eliminated. Under the provision of the Stockholm Convention, developed
countries are required to provide resources to eliminate the production and use of POPs,
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eliminate unintentionally produced POPs, and manage and dispose of wastes containing POPs in
an environmentally sound management (ESM).
Table 1.1: Restrictions and regulations on the production and use of PBDEs in Canada, U.S. and Europe
Regulation Penta- & OctaBDE DecaBDE
Canada - Never been manufactured
- Production and new use banned in 2009
- Never been manufactured
- Export to Canada and sale of decaBDE was voluntarily phased out by the main US manufacturer in 2010
United States - Voluntarily phase out of production by industries in 2004
- New use requires of significant new use notice to USEPA 90 days before use.
- Production is assumed to be discontinued as of 2013; some applications such as military uses could be exempted
Europe - New use was discontinued in various countries since 2000
- Restriction on the use of products containing PBDEs higher than RoHS** level
- Listed as a substance of very high concern under REACH*
International - Added to the list of Stockholm Convention in 2009
- Proposed (by Norway) to be added to the list of Stockholm Convention in 2013
*REACH is the Regulation on Registration, Evaluation, Authorisation and Restriction of Chemicals, which was entered into force in 2007. It streamlines and improves the former legislative framework on chemicals of the European Union (EU) **Restriction of Hazardous Substances, Directive 2002/95/EC, 2011/65/EU
Penta- and octaBDE, like other POPs, degrade slowly in the environment, bioaccumulate
through the food web, and undergo long-range atmospheric transport and therefore can be
4
deposited far from their source of release. In 2009, less brominated PBDE congeners (tetra-
through heptaBDE) were added to the list of Stockholm Convention of chemicals to be
eliminated by 2030. Although PBDEs were manufactured in a few countries (mainly in U.S.,
Israel and Germany) and now China, their extensive use in a wide variety of products in the
global market has led to their worldwide distribution. These products can still be in use or have
entered the end of life (EoL) stage. In such cases, the stock of PBDEs in products continues to
act as a source of PBDEs to the surrounding environments. Thus, the elimination of PBDEs
depends upon the elimination of PBDE-containing products.
In addition to concerns regarding the management of their current stock, the phase out of PBDEs
has led to the increased use of other flame retardants to meet flammability requirements in
consumer products. Like PBDEs, alternative BFRs can migrate from products through
volatilization and abrasion processes and accumulate in dust particles. Even at the low
concentrations and low migration rates from products, the extensive use of BFRs in a large stock
of materials and products has led to their elevated concentrations in indoor dust (Dodson et al.,
2012; Shoeib et al.,2012; Stapleton et al., 2012, Watkins et al., 2011). Depending on the
physico-chemical properties of these chemicals, people are exposed to BFRs via inhalation,
ingestion and/or direct contact with contaminated products (Jones-Otazo et al. 2005; Lorber
2008; Stapleton et al., 2012; Watkins et al., 2011). Such exposures are enhanced by the longer
period of time spent indoor (U.S. EPA 1989).
Given the ubiquitous presence of PBDE-containing products, many studies have attempted to
establish correlations between concentrations of PBDEs in indoor air and dust, and the number
of PBDE-containing products that may potentially act as sources of PBDEs (Allen et al., 2008;
Bjorklund et al., 2012; Hazrati & Harrad, 2006; Kang et al., 2011; Zhang et al., 2011). In
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general, these studies found that the number of PBDE-containing products was positively related
to PBDE concentrations in indoor environment, especially in dust. The first goal of my doctoral
research was to ascertain whether there is a correlation between the products containing BFRs
and BFR concentrations in dust in Canadian indoor environments. This goal was achieved by
developing a method to identify the products that act as sources of these chemicals and
correlating the concentrations of chemicals in products to their concentrations in associated dust.
The existing stock of products containing PBDEs is a source of these chemicals to the outdoor
environment (Batterman et al. 2009, Csiszar et al. 2013). For example, the geographic pattern of
outdoor air concentrations was shown to reflect the inventory of PBDE-containing products in
the city of Toronto (Melymuk et al., 2012). As such, the highest outdoor air concentrations
occurred in downtown Toronto where the greatest stock of PBDE-containing products was
located (Melymuk et al. 2012). Thus, estimating the current stock of PBDE-containing products
and the rate at which this stock will decrease following the phase out of PBDEs could provide
valuable information on the time course over by which the Stockholm Convention goal to
eliminate these chemicals could be achieved.
Reliable data on the production and use of PBDEs and alternative FRs are scarce. The Bromine
Science and Environmental Forum (BSEF) occasionally reported the market demand of selected
BFRs (BSEF 2001). These numbers were used to estimate the mass of BFRs production or use
and to establish a time trend in consumption and release of PBDEs in Europe (Alcock et al.,
2003, Prevedouros et al., 2004, Earnshaw et al., 2013). However, due to the lack of historical
data and assumptions used in these models, these time trends bear considerable uncertainty.
6
Chemical inventories or mass balance analyses have provided valuable insights into trends of
chemical emissions, such as PCBs, over time (Breivik et al. 2002; Diamond et al. 2010; Csiszar
et al. 2013). If trustworthy data on the historical use of PBDEs were available, the stock of
PBDEs in products could be used as a proxy to estimate future trends in PBDE environmental
concentrations. The second goal of my thesis was to establish a dynamic stock of PBDEs using
historical data on the consumption of products containing these chemicals.
Morf et al. (2003) completed a substance flow analysis of PBDE and tetrabromobisphenol-A
(TBBPA) in Switzerland to estimate the time period over which these chemicals would remain in
use. Later, Morf et al. (2008) completed a dynamic substance flow analysis of BDE-47,
decaBDE, and HBCD (hexabromocyclododecane) from 1980 to 2020 in Switzerland to estimate
the increase and decrease of the stock of these FRs as a result of changes in consumption patterns
of products containing these compounds. To achieve my second goal, I used the approach of
Morf et al. (2008) in combination with statistical models to apply available data for the U.S. and
Canada from 1970 to 2020.
It is expected that a large quantity of PBDE-containing products have accumulated in landfills as
these products reached the EoL stage. Deposition of durable goods in landfills has historically
been the most common way of disposing of solid waste in the U.S. and Canada (U.S.EPA 2012,
StatCAN 2012). This, in turn, has resulted in landfills becoming large sinks of PBDEs (Danon-
Schaffer 2010). Environmental concerns regarding the release of anthropogenic contaminants,
such as PBDEs, from landfills have mainly focused on surface or groundwater contamination via
leachate (Danon-Schaffer 2010). Although it is not clear how anthropogenic contaminants are
released from landfills to terrestrial ecosystems, higher concentrations of PBDEs in European
starling eggs nesting close to landfills, compared with those that nested further away, suggests
7
that landfills are acting as a source of PBDEs and alternative BFRs to terrestrial ecosystems
(Chen et al. 2013). In addition to domestic landfilling, a portion of used and waste PBDE-
containing products are exported to developing countries where conventional landfilling and
waste processing are contaminating the ecosystem (BAN 2005; Nnorom and Osibanjo 2008;
Gullett et al. 2007) and local populations (Labunska et al., 2014; Xu et al., 2015; Xu et al., 2013).
To stem hazardous waste contamination locally and globally, programs and policies have been
implemented to attempt to ensure that products containing BFRs and other hazardous substances
undergo ESM. However, these products are still being shipped to other countries illegally
(ChinaDaily 2014). Evaluating the effectiveness of implemented programs has been challenging
as limited reliable and historical data are available on the generation and disposition of waste
containing BFRs. Considering the extensive use of PBDEs in North America (Ceresana 2014),
partly because of flammability requirements in the U.S. and Canada, understanding the fate of
PBDE-containing products in the waste phase is essential to devise an effective chemical
management plan. The third goal of my doctoral research was to investigate the fate of
electronics that could contain PBDEs once these products reach the EoL stage.
1.2 Research Goal and Objectives
A large quantity of PBDE-containing products has been used in the U.S. and Canada. Although
penta- and octaBDE have been slated for the global elimination by Stockholm Convention, and
the production and new use of decaBDE has been restricted, the existing stock of PBDEs in in-
use products and their accumulation in the waste phase will continue to act as sources of these
chemicals into the surrounding environment. Management plans are necessary in order to
8
minimize the human and ecosystem exposures to these substances and this can only be achieved
if the source and quantity of these chemicals in product sources are known. The overall goal of
this research was to better understand the fate of PBDEs and alternative novel flame retardants
(NFRs) during the use and disposal of products. The objectives of this doctoral research were to:
1) identify products that act as sources of PBDEs and their replacements, 2) estimate the stock of
PBDEs in in-use products containing PBDEs and the flow of these products to the waste phase,
3) investigate the fate of internet and communication technology (ICT) products and display
devices, a group of products known to contain PBDEs, as they move from use to in the waste
phase at their End-of-Life (EoL).
Chapter 2: Sources of flame retardants in Canadian house dust1
FRs can migrate out of products through volatilization and abrasion processes during the use of
associated products (Rauert et al., 2014). The goal of this chapter was to identify products that
act as sources of PBDEs and their alternatives in Canadian indoor environments. It was
hypothesized that the concentrations of these chemicals in indoor dust is correlated to their
concentrations in products. To test this hypothesis, the relationship between FRs in dust and the
surfaces of hard polymer casings of electronic products suspected of containing FRs was
examined. Concentrations of 10 polybrominated diphenyl ethers (PBDEs) and 12 halogenated
replacements were analyzed in dust samples collected from 35 homes and 10 offices in Toronto
1 Submitted to Science for the Total Environment as: Abbasi, Golnoush, Amandeep Saini, Emma Goosey,
Miriam L. Diamond. I conducted data collection and data analysis for this paper. A. Saini and E. Goosey helped me in sampling and data collection. All coauthors provided me valuable advice throughout the project and edited the final version of the manuscript.
9
(ON, Canada). At each location, Br content, an indicator of presence of brominated flame
retardants, was measured using a portable X-‐ray fluorescence (XRF) analyzer at the surface of
hard polymer casings of products. Products with higher Br content were sampled by alcohol
wipes to identify BFRs in these products. The concentrations of BFR compounds in product
wipes and dust were then used to investigate the correlation between these two media
Chapter 3: Stocks and flows of PBDEs in products from use to waste in U.S. and Canada2
Despite the discontinuation in PBDE use in new products, the stock of in-use PBDE-containing
products continue to act as a source of these chemicals to the indoor and ultimately outdoor
environments. Under the Stockholm Convention, PBDEs are subject to global elimination by
2030. As a step towards this goal, estimating the stock of PBDE-containing products and the
rate by which this stock will decrease in the future is essential. PBDEs have been used in
electrical and electronic equipment (EEE), automobiles, construction materials, large
transportation vehicles, and foam and textile sectors. The consumption patterns of products in
each sector vary widely. In this chapter, the time-dependent stock of PBDE-containing products
was estimated based the consumption patterns and sales data of PBDE-containing products (all
sectors mentioned, except for construction materials and large transportation vehicles) in the
U.S. and Canada from 1970 to 2020. Further, a Weibull distribution model was used to estimate
2 Published as: Abbasi, Golnoush, Andreas M Buser, Anna Soehl, Michael W Murray, and Miriam L Diamond. 2014. “Stocks and Flows of PBDEs in Products from Use to Waste in the U . S . and Canada from 1970 to 2020.” doi:10.1021/es504007v. I conducted all analysis of the paper in consultation with Dr. Andreas Buser. Anna Soehl helped me to collect data by contacting industries. All coauthors provided suggestions throughout the study. I was responsible for writing the initial draft of paper. All coauthors were involved with editing and improving the manuscript.
10
distribution of these products in the use phase, based on the lifespan of each product. Our results
demonstrated that the total stock of PBDEs in the use phase peaked in 2008. Considering only
the first use of associated products (no reuse), all the stock of penta- and octaBDE will have
entered the waste phase by 2020. However, 60% of the stock of decaBDE in 2014 will remain in
use phase by 2020. Since the management of PBDE-containing products requires substantial
planning, results of this study could be used to improve the regulatory framework regarding the
management of contaminated waste.
Chapter 4: PBDE-containing products in the waste phase: case study of EEE3
Under the Stockholm Convention, PBDE-containing products at EoL stage are required to
undergo ESM to minimize the release of PBDEs during disposal processes. Each year, a large
quantity of these products become obsolete in the U.S. and Canada. The elevated concentrations
of PBDEs in terrestrial ecosystems adjacent to landfills (Chen et al., 2013) and the export of
waste PBDE-containing products, including EoL electronics and vehicles to developing
countries, (Nnorman and Osibanjo 2008) corroborate the mismanagement of these products in
the waste phase in the U.S. and Canada. As a step towards ensuring ESM of waste PBDE-
containing products, estimating the mass of these products and their fate in the waste phase is
required. This chapter focuses on internet and communication (ICT) products and display
devices, because of the extensive use of PBDEs and other BFRs, the rapid turnover rate of these
products, and increasing concerns regarding the recycling of materials from these products into
new products. The quantity of waste ICT products and display devices in the U.S. and Canada
from 1970 to 2020 was estimated followed by estimates of these products at each stage of waste 3 To be submitted to Waste Management as: Abbasi, Golnoush, Andreas M Buser, Fe De Leon, Miriam L Diamond. I did all the analysis of this study in consultation with my coauthors. They provided suggestions and were involved in editing of the manuscript.
11
management. These estimates were used to identify uncertainties and knowledge gaps in waste
product disposition and to comment on the ability of the waste management system to meet ESM
objectives.
12
Chapter 2: Source of Flame Retardants in Canadian House Dust
2.1 Introduction Polybrominated diphenyl ethers (PBDEs) have been widely used as flame retardants (FRs) in
various consumer products since the 1970s. Elevated concentrations of PBDEs are well
documented in indoor (Allen et al., 2008; Harrad et al., 2008; Harrad et al., 2010; Zhang et al.,
2011; Shoeib et al., 2012) and outdoor environments (de Wit, 2002; Hites, 2004; Melymuk et al.,
2012), and have resulted in human and ecosystem exposure (Buttke et al., 2013; Siddique et al.,
2012; Schecter et al., 2003; Crimmins et al., 2012; Hites, 2004). Exposure to PBDEs continues
to raise concerns due to increasing evidence of adverse health effects of these chemicals (Lyche
et al., 2015; Eskenazi et al., 2013; Slotkin et al., 2013; Meeker et al., 2009; Turyk et al., 2008).
PBDEs were generally used under three main commercial mixtures of c-PentaBDE, c-OctaBDE
and c-DecaBDE in products4. As a result of health concerns and persistence, the congeners of c-
Penta- and c-OctaBDE were added to the list of chemicals to be eliminated under Stockholm
Convention in 2009 (UNEP, 2010). The production of c-Penta- and c-OctaBDE was voluntarily
phased out by industries in the U.S. in 2004. Canada banned the production and new use of c-
Penta- and c-OctaBDE in 2008. DecaBDE was listed for authorization under REACH5 in 2010,
meaning that DecaBDE will be progressively replaced by alternative flame retardants in new
products. In 2013, Norway nominated DecaBDE for inclusion as a POP under the Stockholm
Convention (UNEP, 2013). As of 2010, three main U.S. manufacturers of decaBDE started to
4 Congeners of each mixture considered in this study: c-‐PentaBDE: BDE-‐17, -‐28, -‐71, -‐47, -‐99, -‐100, -‐154, -‐153 c-‐OctaBDE: BDE-‐153, -‐ 154, -‐183 c-‐DecaBDE: BDE-‐209 5 REACH is the Regulation on Registration, Evaluation, Authorisation and Restriction of Chemicals. It entered into force in 2007. It streamlines and improves the former legislative framework on chemicals of the European Union (EU).
13
voluntarily phase out the export and sale of decaBDE for certain applications in Canada (EC,
2013). In Canada, there are no specific controls on PBDEs in products (EC, 2015). The
production, importation and sales of decaBDE were expected to be discontinued in the U.S.
following 2013 (USEPA, 2015). Despite the cessation in production and new uses in North
America and Europe, the stock of PBDEs in in-use products, which was estimated to be
~120,000 tonnes in the U.S. and Canada in 2014 (Abbasi et al., 2015), remains a source of
PBDEs to the indoor and ultimately outdoor environments.
The replacement of PBDEs with "novel flame retardants" (NFRs) has resulted in a proliferation
of other brominated flame retardants (BFRs) and halogenated and non-halogenated
organophosphate flame retardants (OPFRs) (Ceresana, 2014). PBDEs and many NFRs are
additive flame retardants – they are added but not chemically bonded to the polymer to which
they have been added. Consequently, they can migrate from products to surrounding
environments. A growing literature is documenting the levels of these compounds in indoor dust
(Ali et al., 2011; Cao et al., 2014; Cequier et al., 2014; de Wit et al., 2012; Newton et al., 2015;
Shoeib et al., 2012; Shoeib et al., 2013; Stapleton et al., 2012) and outdoor environments (Ma et
al., 2012; Ma et al., 2013; Salamova and Hites 2011; Salamova and Hites 2013).
Exposure to FRs can occur through ingestion and inhalation of contaminated house dust (Jones-
Otazo et al., 2005; Lorber, 2008). For example, several studies have correlated concentrations of
PBDEs in house dust with those in serum and breast milk (Björklund et al., 2012; Johnson et al.,
2010; Wu et al., 2007; Watkins et al., 2011) . However, rather than, or in addition to dust
inhalation and ingestion being the main exposure pathway, PBDE transfer via hands may be the
actual method of exposure given the stronger correlation between PBDEs in hand wipes than
dust, and serum (Watkins et al., 2011). Similar results of exposure via hands are now emerging
14
for NFRs (Stapleton et al., 2014). Direct contact with FR-containing products and FR-
contaminated dust are the two suggested sources of FRs to hands (Stapleton et al., 2014;
Stapleton et al., 2008).
For exposure via direct contact with FR-containing products or FR-contaminated dust, the source
needs to be traced back to those products with the FR highest release rate or mobility. Studies
that have sampled dust from specific locations within a room have found that specific products,
such as electronics, contribute to FR concentrations in dust (Muenhor and Harrad, 2012; Harrad
et al., 2009). By assessing patterns across rooms, several studies have found correlations
between FRs in dust and the prevalence of electronic equipment or PUF-containing furniture
(Hazrati and Harrad, 2006; de Wit et al., 2012). In contrast, several studies have failed to find
such a correlation (Kang et al., 2011; Kefeni & Okonkwo, 2012). Upon failing to find a
correlation between PBDEs in house dust and the number of products likely to have contained
PBDEs, Allen et al. (2008) used X-ray fluorescence (XRF) to identify products containing
bromine (Br) as an indicator of PBDEs. The correlation became significant when PBDE dust
concentrations were regressed against XRF-identified Br-containing products. Recently Li et al.
(2015) found a strong positive correlation between the power consumption of electronics and
PBDE levels in a large room, which was explained by the fact that the heat generated from in-use
electronics enabled the release of FRs.
Three hypotheses have been proposed to account for the migration of additive FRs from products
or more specifically, the polymer to which they have been added, to dust: (1) volatilization from
the polymer followed by air-dust partitioning, (2) abrasion of the polymer surface causing the
release of FR-enriched particles or fibres, and (3) direct transfer of FRs from the FR-containing
polymer to dust (Kemmlein et al., 2003; Takigami et al., 2008; Webster et al., 2009; Rauert et
15
al., 2014, inter alia). As discussed by Rauert et al. (2014b), volatilization is expected to be the
main mechanism for the release of more volatile compounds whereas abrasion is more likely for
less volatile compounds.
As noted above, Allen et al. (2008) identified the likely sources of PBDEs in house dust by
measuring Br levels in products using X-ray fluorescence (XRF) followed by quantification of
PBDE levels in products by means of GC-MS detection. Their results suggested that XRF could
be used as a reliable method for identifying PBDE-containing products. It should be taken into
consideration that this conclusion by Allen et al. (2008) was made before the proliferation of
NFRs. Recently, Gallen et al. (2014) used XRF to identify Br-containing products along with
product surface wipes to identify PBDE congeners and TBBPA in products. Then they selected
products, for which wipes indicated the presence of PBDEs or TBBPA, for destructive chemical
analysis using GC-MS analyser. Their results illustrated that XRF alone cannot be used as a
reliable tool for identifying the PBDE-containing products as the Br content of products
measured by XRF could represent the presence of other BFRs that are used as PBDE
alternatives. However, the combination of XRF and product surface wipes could provide
reliable information on the identity and, in some cases, the quantity of BFRs used in products
(Gallen et al. 2014).
Our main goal was to identify which products act as a source of PBDEs and NFRs to indoor dust
in the context of human exposure. We hypothesized that the higher the concentration of PBDEs
and their alternatives in products, the higher their concentrations in associated dust. Second, we
aimed to develop further the rapid and non-destructive technique of product wipe testing to
identify the wide assortment of NFRs used in products.
16
2.2 Materials and methods
2.2.1 Sampling from homes Dust and product wipe samples were collected from 35 homes and 10 offices in the Greater
Toronto Area, Canada, in August 2012. During site visits, the Br content of selected products
that were thought to be treated with FRs was measured by means of XRF. Dust, products wipe
samples, and XRF measurements of products were taken from the most commonly used room,
which in most cases was the TV room. In open concept homes where the kitchen was attached
to the living room, Br readings were also taken of kitchen appliances. Participants were selected
based on a sample of convenience. The University of Toronto Ethics Board authorized all
aspects of this study and all participants gave informed consent prior to sample collection from
their homes.
2.2.2 Dust sampling Dust samples were collected from carpet or hardwood floor using a conventional vacuum
cleaner. Dust samples were collected in pre-cleaned nylon socks (XUTRECHT02 Vacuum Bag;
Allied Filter Fabrics ltd., Australia) attached to the end of the vacuum cleaner hose, which was
cleaned by iso-propanol prior to each sampling. An average area of 2×2m2 from the center of
floor of the most used room was vacuumed. If insufficient dust was obtained, a larger area was
sampled and the area was noted. Study participants were requested to not vacuum these areas for
at least 1 week prior to our sampling to ensure sufficient dust accumulation for collection.
Following collection, samples were stored in the refrigerator prior to being sieved. Samples
were sieved (150 µm) using a pre-baked sieve (at 250°C for at least 3h) to produce a fine dust
fraction. One person sieved all the dust samples to minimize variability in dust preparation. The
fine dust samples were stored in pre-cleaned glass vials in at -20°C and then thawed at room
temperature prior to chemical analysis.
17
2.2.3 XRF measurements Br content was measured by a hand-held Niton-XL3t XRF analyzer (Thermo-Scientific, Canada)
in 553 products such as upholstered furniture, electrical and electronic equipment (EEE), and
selected plastic products in homes and offices. XRF provides a non-destructive estimate of the
heavy elements in a matrix by illuminating a sample with high-energy photons, dislodging
electrons and counting the resultant release of X-rays. Each element in a sample produces a
characteristic signature of scattered X-rays. XRF measures the scattered X-rays from which the
concentration of each element is calculated based on a calibration of the instrument. Prior to
sampling at each location, the XRF device was calibrated in plastic testing mode against a
polymer bead with known elemental content. To remove dust contamination, plastic products
were wiped with kimwipes before screening. Three readings at different locations on each
product were taken to obtain an average value. Readings were also taken from couches with
multiple seat and back cushions. Where possible, the inner part of the cushion was screened in
addition to the seat cover with upholstery. The Br content was measured at the exterior of EEE
casings, plastic and upholstered items. At least one reading from EEE products was taken from
the area close to the fan, circuit board or motherboard, given that these parts were most likely to
be treated with BFRs. If the products had various types of plastic, readings were taken from
each part (e.g. front and back of TVs).
2.2.4 Wipe samples Products were selected for product wipe testing when Br content of products was at least 10
times higher than 0.1% (RoHS level)6. An average area of 5×5 cm2 was wiped for 1 minute.
Prior to sampling, dust from the surface of products was removed with pre-cleaned Kimwipes.
6 The RoHS directive aims to restrict certain dangerous substances commonly used in electronic and electronic equipment.
18
Products were wiped with isopropanol-wetted medical wipes (Health Care Plus, Canada). Blank
medical wipes had levels of PBDEs and NFRs <LOD (listed in Table S2.1). Wipe samples were
stored in pre-cleaned glass vials in a freezer (-20°C) and thawed at room temperature prior to
chemical analysis.
2.2.5 Sample analysis All dust and wipe samples were analyzed for 10 PBDE congeners and 12 NFRs: BDE-17, -28, -
47, -71, -99, -100, -154, -153, -183 and -209 and allyl-2,4,6-tribromophenyl ether (ATE),
1,2,3,4,5-pentabromobenzene (PBBz), 2,3,5,6-pentabromoethyl benzene (PBEB),
hexabromobenzene (HBB), syn-dechlorane Plus (syn-DP), anti-dechlorane Plus (anti-DP), 2-
ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB or TBB), bis(2-ethyl-1-
hexyl)tetrabromophthalate (BEHTBP or TBPH) , octabromotrimethylphenylindane (OBIND),
decabromodiphenylethane (DBDPE), pentabromotoluene (PBT), tris(1,3-dichloro-2-
propyl)phosphate (TDCPP).
To determine recoveries, samples were spiked with surrogate 14C-labelled standards (mPPBz,
mHBB, mBDE-28, mBDE-154, and mBDE-183) prior to sample extraction. Approximately
0.1g of dust and whole product wipe (0.5g) samples were extracted in hexane: DCM (1:1,v/v)
(HPLC grade, Fischer Scientific) via pressurised liquid extraction using an Accelerated Solvent
Extractor (ASE; Dionex ASE350). Extracts were cleaned up using pre-cleaned alumina (5g) and
sodium sulfate (10g) added to ASE cells as described by Saini et al. (submitted). Each extract
was concentrated to 0.75 mL under a steady stream of nitrogen in a Zymark Turbovap, then
transferred to 1.5 mL GC vials and further reduced using Nitrogen. The final volume was made
to 0.5 mL using Isooctane (HPLC grade, Fischer Scientific). Samples were analysed using GC-
MS (Agilent 6890N/5975C), equipped with DB-5 15m column and MS operated in negative
chemical ionisation (NCI) mode, using methane as the reagent gas. Quantification was
19
performed using a 5-point calibration curve obtained from a PBDE standard mixture
(Accustandard, USA) and individual standard of each NFR (Wellington Laboratories, Canada).
2.2.6 Quality Assurance& Quality Control (QA/QC) QA/QC of chemical analysis was monitored by measuring recoveries and blanks. Field blanks
for dust and wipes were taken at one in 10 sampling locations. Dust field blanks consisted of 1
gm Na2SO4 on pre-cleaned aluminium foil placed on the floor of the most used room and then
vacuumed using the same method as for dust collection. Product wipe blanks consisting of
medical wipes were exposed to air in the most used room for approximately 1 minute.
Laboratory and field blanks were extracted and analysed (spiked with surrogate standards and
internal standard) in every batch of 10 samples. Surrogate standards were added to each sample
prior to extraction to check recoveries throughout the extraction and preparation processes. .
The data were quantified using BDE-118 as an internal standard which was added to the final
volume of the extract samples prior to injection. Laboratory blanks spiked with surrogate
standards prior to extraction were analysed with every batch of 6 samples. Further details on
method validation and detection limits are provided in SI.
2.2.7 Data analysis Statistical analyses were performed using Statistica (Six Sigma, version 7) and included
descriptive statistics, Pearson and Spearman correlations, and multivariate regression with
statistical significance defined at α=0.05. For compounds not detected at the concentrations >
LOD, LOD divided by square root of two was assigned for statistical analysis. Dust and product
wipe concentrations were transformed to their natural log prior to principal component analysis
(PCA) analysis. PCA and K-mean partitioning analysis on log-transformed data were performed
in open source “R” software.
20
2.3 Results
2.3.1 XRF The XRF results were used as an indicator of brominated compounds in numerous product types
in home and office environments (Table 2.1). Out of 553 products in offices and homes that
were screened for Br, 45% (217) of products had a Br content >0.1% or 1,000 µg/g. Considering
that FRs must be added to products at a minimum level of 2% in order to effectively retard the
spread of fire (Weil & Levchik 2009), we found that only 13% of the products met this criterion
with respect to BFRs. It is possible that products also contained non-Br flame retardants. The
back casings of televisions (both flat screen and cathode ray tube (CRT)) consistently had Br
contents of >100,000 µg/g. Other products that had relatively high Br content were the plastic
casing of power bars, chargers for electronic goods and batteries, internet routers (cable and
wireless), power surge protectors, DVD players and microwaves. The highest Br content among
all products was measured in a 2-year old food dehydrator (~160,000 µg/g). The highest inter-
variability (variability within a product) was observed in furniture and carpet padding which
could be related to the heterogeneous nature of PUF and therefore uneven disposition of FRs in
PUF products and/or the inability of XRF to provide reliable measurements for soft materials.
In comparison to the 45% of products found to exceed 0.1% of Br, Gallen et al. (2014), who
sampled products available in the Australian market in 2012 (same year as sampling conducted
here), found that the 28% out of 1714 products screened by means of XRF exceeded this value.
Gallen et al. (2014) reported that the maximum Br content in EEE products exceeded 100,000
µg/g in comparison to our finding of one product with Br content of ~160,000 µg/g.
21
Table 2.1: Mean, geometric mean (geomean), minimum and maximum values of Br content (µg/g) of products screened using XRF.
Product
Total
number of
products
% of
Product
with [Br]
>0.1%
% of
Product
with [Br]
>2%
Mean Geomean Min Max
Flat screen TV
(front) 25 80% 64% 73,500 4,900 10 113,000
Flat screen TV
(rear) 25 60% 28% 25,000 225 10 99,500
CRT TV 6 100% 100% 103,500 103,200 85,700 120,000
PC (laptop &
desktop) 62 29% 4% 2,800 0.5 <LOD 116,000
Flat screen Monitors 9 44% 0% 340 3 <LOD 2000
CRT Monitors 5 20% 25% 21,500 1 <LOD 85,000
Audio/Video 76 36% 15% 10,400 35 <LOD 145,000
Fax/ printer/ copier 20 40% 5% 4500 10 <LOD 90,000
Small HHA 148 43% 14% 12,500 10 <LOD 160,000
Large HHA 49 24% 6% 4000 0.2 <LOD 70,000
PUF Furniture 98 36% 2% 2000 2 <LOD 21,500
Carpet 30 23% 0% 500 1 <LOD 5000
2.3.2 FR levels in product wipes A total of 65 wipe samples was taken mainly from products with high Br content (>10,000 µg/g).
The profile of FRs in product wipes is shown in Figure 2.1. Congeners of c-pentaBDE (BDE-47,
100, 99, 153, 154) were measured in all wipes taken from personal computers (PCs) and most
small household appliances (HHA). The highest c-pentaBDE concentrations were detected on
the surfaces of PCs, audio/video devices and large HHA at ~450, 200 and 150 ng/wipe,
22
respectively. The highest concentration of c-octaBDE congeners was ~5000 ng/wipe which was
measured in small HHA followed by audio/video devices (~250 ng/wipe). DecaBDE (BDE-209)
was found in all wipes of CRT TV casings with the geomean and highest concentration of
~100,000 and ~120,000 ng/wipe, respectively. DecaBDE was also detected in most small HHA
wipe samples, with its concentration ranging from <LOD up to 30,000 ng/wipe. PBDE
concentrations were in the same range as those of Gallen et al. (2014) of 600 to 20,000 ng/wipe.
Among all NFRs, DBDPE was measured in ~60% of flat screen TVs with the highest
concentration of ~6,000 ng/wipe and a geomean of ~2 ng/wipe. We note that the results
specifically for DBDPE are generally uncertain due to high analytical variability (Melymuk et al.
resubmitted). BEHTBP was measured in all PCs and small HHAs and most flat screen TVs
(85%) sampled here at geomean values of ~7.5, 1.5 and 0.5 ng/wipe, and with the highest
concentrations of ~200, 14, 75 ng/wipe, respectively. EH-TBB was measured in all PCs and
most audio/video devices (80%) at geomean values of ~50 and 2 ng/wipe, and with a maximum
concentration of 1,000 ng/wipe. TDCPP was also detected in flat screen TVs and large HHAs at
maximum concentrations of 200 and 500 ng/wipe, respectively. The concentrations of PBBz,
PBT, PBEB and OBIND ranged from <LOD up to 30 ng/wipe in various product samples. ATE
and DPs were detected at concentrations less than or close to the LOD in most product wipes.
23
Figure 2.1: Percentage contributions of PBDEs and NFRs in product wipes.
2.3.3 Comparison of Results from XRF and Product Wipes No relationship was observed between Br content measured by XRF and Br content measured in
product wipes (Figure S2.2). Moreover, XRF-measured Br content tended to be at least 10 to
1000 times greater than that measured using product wipes. For example, in 56% of product
wipes, the total Br content ranged from 2 to 80 ng/wipe with geomean of 13 ng/wipe whereas
their Br content measured using XRF ranged from 1,000 to 145,000 µg/g with geomean of
50,000 µg/g. In 27% of product wipes, the total Br content ranged between 80 and 800 ng/wipe
with a geomean of 180 ng/wipe, while the Br content measured by XRF ranged from 1,000 to
160,000 µg/g with a geomean of ~25,000 µg/g. In the remaining samples (17%), the total Br
content ranged from ~800 to 50,000 ng/wipe and a geomean of ~3,800 ng/wipe, while the Br
content measured by XRF ranged between ~70,000 and 110,000 µg/g with a geomean of
~90,000 µg/g.
Allen et al. (2008) found that XRF could be used to reliably identify the Br content of foam and
electronic products destructively analyzed for PBDEs by means of GC-MS. However, given
0% 50% 100%
Flat screen TV
CRT TV (n=4)
Audio/Video (n=20)
PC (n=10)
Small HHA (n=11)
Large HHA (n=7) BDE-‐17
BDE-‐28
BDE-‐47
BDE-‐71
BDE-‐99
BDE-‐100
BDE-‐153
BDE-‐154
BDE-‐183
BDE-‐209 0% 50% 100%
Flat screen TV
CRT TV (n=4)
Audio/Video (n=20)
PC (n=10)
Small HHA (n=11)
Large HHA (n=7) ATE
PBBz
PBT
PBEB
TDCPP
HBB
EH-‐TBB
BEHTBP
OBIND
DBDPE
24
they conducted their sampling effort in the mid-2000s, and since then more of BFRs are being
used in products, it is more challenging to link XRF-determined Br with that determined by
destructive GC-MS. Gallen et al. (2014) found that XRF poorly approximated Br content of hard
plastic products determined by GC-MS destructive analysis; however they analyzed for only
PBDEs and TBBPA. Our results are consistent with concerns about the reliability of screening
products for BFRs by means of XRF.
2.3.4 FR levels in dust samples PentaBDE congeners (BDE-47, -99) were the most abundant PBDEs in dust samples. BDE-47
and 99 ranged from <LOD to ~5,000 and 12,000 ng/g dust with geomeans of ~170 and 190 ng/g
dust, respectively (Figure 2.2, Table S2.2). DecaBDE (BDE-209) was detected in most dust
samples from houses (97%). Concentrations of BDE-209 ranged from ~0.01 to 12,000 ng/g with
a geomean of 148 ng/g dust. The concentration of c-pentaBDE and c-octaBDE in this study
were in the same range as those reported by Shoeib et al. (2012) for dust from 116 houses
sampled in Vancouver in 2007-2008 and Wilford et al. (2005) for dust from 68 houses sampled
in Ottawa, Canada in 2002-2003. However, BDE-209 was a factor of 4 lower in this study in
comparison to Shoeib et al. (2012). The presence of pentaBDE congeners in dust samples,
despite their curtailment in new products since 2005, reflects the continuous release of these
compounds from in-use PBDE-containing products (Abbasi et al. 2015). The lower
concentration of decaBDE in our dust samples compared to those measured by Shoeib et al.
(2012) may reflect the retirement of the large numbers of CRT TVs and other older EEE in late
2000s that contained high concentrations of decaBDE (Abbasi et al., 2015).
25
The geomeans of BDE-47,-100 and -99 were 10 times higher in office dust samples than those of
homes. This may be due to more stringent flammability requirements applied to office and
public spaces than residences, such as California Technical Bulletin 133 that pertains to PUF
furniture. DecaBDE concentrations in office samples were within the same range as house
samples (0.012-1610 ng/g dust) with a median of ~250 ng/g dust. The geomean of c-PentaBDE
concentrations from offices measured in this study (~7,000 ng/g dust) was three times higher
than those measured from the U.S. offices by Watkins et al. (2011). However, the geomean of
the DecaBDE concentration was a factor of 20 lower than that reported by Watkins et al. (2011).
These differences are not likely comparable as only 10 offices were included in present study.
TDCPP was detected in more than 80% of house dust samples, with the highest concentrations of
all FRs measured. Concentrations ranged from <LOD to 45,000 ng/g dust with geomean of
~700 ng/g and median of 1,700 ng/g, which was 20 times higher than that reported from New
Zealand, Belgium and Spain (Ali et al., 2012; Van den Eede et al., 2011; García et al., 2007).
Stapleton et al. (2014) reported a range of 620 to 13,000 ng/g dust of TDCPP in the U.S. dust
sampled from 30 houses in 2012. In office samples, TDCPP concentrations ranged from <LOD
to 200,000 ng/g dust, with a geomean of ~8,700 ng/g dust or more than twice that for houses.
EH-TBB was measured in more than 90% of dust samples from houses and offices with a
median concentration of ~500 ng/g and range of ~0.015 to 7,000 ng/g dust, with no significant
differences between these two microenvironments. The median concentrations of BEHTBP in
house and office dust samples were ~100 and 200 ng/g dust, respectively, which is lower than
EH-TBB levels. However, the maximum BEHTBP concentration (~50,000 ng/g) measured in
one office sample was ~7 times higher than those of EH-TBB. The measured concentrations of
EH-TBB and BEHTBP are in good agreement with those reported by Shoeib et al. (2012) and
26
Stapleton et al. (2014) for house dust from Canada and the U.S., respectively. DPs (anti & syn)
were detected in almost 97% of samples with concentrations ranging from <LOD to ~200 ng/g
dust, which is in the same range reported for Canadian dust by Shoeib et al. (2012) and Zhu et al.
(2007).
Figure 2.2: Percentage contributions of PBDEs and NFRs in house (n=35) and office (n=10) dust.
2.3.5 Association between product wipes and dust As it is shown in Figure 2.3, concentrations (log of the geometric mean) of BFRs in dust were
positively correlated with those in product surface wipes (r2=0.53, p=0.002). Stronger
correlations were obtained for each group of chemicals with molecular weight < and > 600 g/mol
(Figure S2.3). In general, the higher the concentration of each compound in product wipes, the
higher their concentrations in dust. The lack of correlation between FRs in dust and Koa, as a
measure of volatility (Figure S2.4), could suggest that abrasion and weathering processes were
the migration pathways of these chemicals from products to dust (Webster et al., 2009, Rauert et
al., 2014a). However, another explanation is that the higher concentrations of octa- and
decaBDE, and DBDPE in dust could be related to the higher and longer power usage of
associated products with higher concentrations of these chemicals, such as TVs, which generate
0% 20% 40% 60% 80% 100%
Home
Office
BDE-‐17
BDE-‐28
BDE-‐47
BDE-‐71
BDE-‐99
BDE-‐100
BDE-‐153
BDE-‐154
BDE-‐183
BDE-‐209 0% 50% 100%
Home
Office
ATE PBBz HBB PBT TDCPP PBEB EH-‐TBB BEHTBP DBDPE OBIND s-‐DP a-‐DP
27
heat and consequently could increase volatilization of these chemicals (Li et al., 2015). A
correlation between the number of electronics containing PBDEs, in particular display devices,
and PBDE levels in indoor dust has been demonstrated in previous studies (de Wit et al., 2012,
Allen et al., 2008, Harrad et al,. 2004). TVs have been also identified as the main source of other
FRs, such as HBCD, in indoor environments (Harrad et al., 2009).
Figure 2.3: Correlation between logarithms of the geomean concentrations of FRs in product wipes and dust samples. Blue diamonds represent compounds with lower molecular weight (MW <600 g/mol), black dots represent heavier compounds (MW >600 g/mol).
ATE, PBBz and PBT, the more volatile compounds amongst FRs included in this study, were
found in lower concentrations in product surface wipes and dust. The elevated concentrations of
PentaBDE and its replacements (TDCPP, EH-TBB and BEHTBP) in dust samples compared to
product wipes could reflect their presence of PUF products that could not be wiped (but that
were screened using XRF), such as foam furniture and baby foam products (Stapleton et al.,
Y=0.7x + 1.4 r2=0.54
28
2011). However, pentaBDE, TDCPP, EH-TBB and BEHTBP were also measured in wipes from
of EEE casings including audio/video devices, PCs and small HHAs. The differences among the
ratio of EH-TBB:BEHTBP in dust (~10), product wipes (~25) and Firemaster 550 (~3)
(Stapleton et al. 2014), suggest that these compounds are either released from products at
different rates or that they do not necessarily originate from products treated with Firemaster
550. Overall, these results suggest that PCs and audio/video devices, in addition to PUF
furniture, could act as sources of pentaBDE and its replacements in indoor environments. We
used PCA to further investigate the relationship between BFRs in product wipes and dust
samples. Principal components (Pc) 1 and 2 explained 68% of the variation in our dataset
(Figure 2.4).
Five clusters were delineated using k-means partitioning and simple structure index (ssi) methods
(Figure S2.5). PCA identified several clusters that grouped dust and product wipe samples
together rather than by sample type, consistent with the positive correlation between their
concentrations in product wipes and dust. Cluster A consisted of dust samples (>80%) and some
wipe samples that had elevated concentrations of pentaBDE and its replacements TDCPP, EH-
TBB and BEHTBP. DPs in dust were also included in this cluster. Since DPs were not detected
in any product wipes, we concluded that building materials or wire coating (Shoeib et al., 2012),
which were not sampled in this study, could be their potential sources to dust samples.
29
Figure 2.4: Analysis of FRs in product wipes and dust by means of Principal Components Analysis. Pc 1 and 2 account for 68% of variability in dataset. Five clusters were identified using K-means partitioning and ssi. Crosses “x” represent dust samples and dots represent product wipe samples. Cluster A, was dominated by pentaBDE and its replacements (TDCPP, EH-TBB and BEHTBP), cluster B was dominated by deca- and octaBDE, cluster C by DBDPE and OBIND (decaBDE replacements), cluster D.
Cluster B was dominated by product wipes and dust containing high concentrations of octa- and
decaBDE. This grouping, and the finding of high concentration of DecaBDE in CRT TVs,
followed by the relatively high concentrations of octa- and decaBDE in audio/video devices,
small HHAs and PCs, suggested that these products could act as sources of octa- and decaBDE
to dust. Cluster C was dominated by those dust and wipe samples with high concentrations of
DBDPE and OBIND (decaBDE replacements). DBDPE was measured mainly in flat screens,
followed by audio/video devices and small and large HHA. OBIND was measured in the same
products but at lower concentrations than DBDPE. Cluster D was dominated by mainly product
wipes with high PBEB and PBT. These compounds were measured in product wipe samples at
PBT
PBEB
DecaBDE
OctaBDE
HBB
sDPaDPTBB
DBDPEOBIND
TBPHPentaBDE
A
B
C
D
E
x
x
x
x
x
xx
x
x xx
x
x
xx
xx
xx x
x
x
xxx
x
x
x
x
x
x
xTDCPP
DustProduct wipe
x
30
lower concentrations in comparison to other FRs. The low concentrations (<LOD) of PBEB and
PBT in dust samples could suggest that these compounds tend to stay in gas phase after release
or that current concentrations in products are too low for them to contribute significantly to dust
concentrations. Cluster E was comprised of those wipe and dust samples that had the least
concentrations of the FRs targeted in this study.
2.4 Implications These results have several implications. First, the use of product wipes to screen for BFRs
merits further investigation. We were able to detect a wide range of BFRs in product wipes and
those levels were related to concentrations measured in dust. Our results support those of Gallen
et al. (2014) who found that surface wipes provided a reasonable approximation of
concentrations of PBDEs in electronic products, as compared to destructive analysis by means of
GC-MS. Our results and those of Gallen et al. (2014) confirm that screening products using
XRF may provide unreliable results regarding the presence of BFRs in products. We recommend
that more research should be conducted to optimize the consistency and efficiency of product
wipe method to develop a rapid, reliable and non-destructive testing technique to quantify these
additive flame retardants in consumer products.
Second, in terms of exposure, the ability of medical alcohol wipes to remove BFRs from
products surfaces, even at the low concentrations, suggests that these chemicals can be easily
transferred to hands while handling products due to the tendency of BFRs to partition into lipids,
i.e., the natural oils on skin. As well, direct transfer of BFRs from products to dust has been
hypothesized as one of the migration pathways of these chemicals from products (Rauert et al.,
2014). Watkins et al. (2011) illustrated that PBDEs can be transferred to hands via direct contact
31
with contaminated dust. Contact with products containing Firemaster 550, a PentaBDE
replacement in PUF products, was also recognized as an exposure pathway to EH-TBB and
BEH-TEBP (Stapleton et al., 2014). Once on hands, FRs can enter the body via incidental
ingestion including hand-to-mouth activity (Stapleton et al., 2012; Stapleton et al., 2014) or
transdermal uptake (Weschler & Nazaroff, 2012).
Third, our results showed that the concentration of FRs in dust was related to their concentrations
in product surface wipes regardless of the volatility of the compounds. These results are
consistent with abrasion and weathering as the main processes by which BFRs, especially less
volatile compounds, migrate from products into dust (Webster et al., 2009; Rauert et al., 2014).
We did not test for the relationship between the power usage of products and the release of FRs,
as was found by Li et al. (2015). The alternative hypothesis of greater release as a function of
power usage due to volatilization from heated plastic or greater release from abrasion of heated
plastics, is also possible.
Fourth, in order to be effective, FRs must be within the range of 2 to 25% of the weight of the
final polymers, depending on the nature of materials used in products (Weil and Levchik, 2009)
and the flammability standard for each product type. Only 13% of products (mainly TVs) that
were screened by means of XRF in this study, had a Br content of >2%, however, 45% had a Br
content of >0.1%. Several explanations can be offered for these results. The products may
contain non-halogenated FRs such as organophosphate flame retardants (OPFRs) (Ceresana,
2014) and/or inorganic FRs. Another explanation is that either BFRs were not added to products
at sufficient levels to inhibit the spread of fire or some of these products were made of recycled
plastics that inadvertently contain BFRs (Ionas et al. 2014). Notwithstanding the environmental
and economic benefits of plastic recycling, the increasing rate of BFR-containing EEE entering
32
the waste stream and the growing market demand for waste plastic in Asia (PlasticsEurope,
2013), means that more PBDEs and other FR-containing products from recycled polymers are
expected to enter the global market. These products could also constitute a source of exposure to
these chemicals.
Finally, our results confirm that a variety of FRs is used in consumer products. The atmospheric
concentrations of EH-TBB and BEHTBP (PentaBDE replacements) are increasing to levels close
to those of PBDEs in the Great Lakes air (Ma et al., 2012). Some DecaBDE replacements such
as TBBPA-dbpe (tetrabomobisphenol-A-bis(2,3-dibromopylether), and TBBP-A-ae
(tetrabomobisphenol-A-bis(allyl ether), have been found to bioaccumulate in the herring gull
food chain and transfer from gull to egg (Letcher and Chu, 2010). The shift towards the use of
OPFRs in products to meet the flammability requirements is causing increasing levels of OPFRs
in indoor (Stapelton et al., 2014) and outdoor environments (Salamova et al., 2014). Quantifying
the in-use stock of these chemicals is an important step towards devising long-term chemical
management schemes. However, establishing the stock of in-use NFRs, as was established for
PBDEs (Abbasi et al., 2015), will be very difficult given the large number of NFRs and their
varied uses in consumer products.
2.5 Uncertainties and Limitations To better interpret results of our study, several uncertainties and limitations need to be
considered, for example: (1) product wipes could not be taken from all FR-containing products
at each location, notably couches and other foam products, (2) either product wipes were unable
to remove all FR compounds from product surfaces that were measured in dust samples (i.e.,
DPs, HBB) or not all products containing BFRs could be sampled (i.e., electrical cables, building
33
insulation), and (3) inconsistencies and possible human errors during the sampling procedure,
such as the pressure applied while taking wipe samples, duration and area of sampling (Gallen et
al., 2014) could contribute to variability.
Uncertainties associated with our study included: (1) sample locations did not represent houses
with a variety of socio-economic status, (2) product wipe results could have been confounded by
the heterogeneous distribution of BFRs in polymers, and (3) a single, centrally located dust
sample may not be representative of the room sampled (Muenhor and Harrad, 2012).
Gallen et al. (2014) discussed two major sources of errors when using product wipes to identify
FRs in products. Contamination of products with dust containing-BFRs from other sources
could generate false positives, which could result in falsely identifying BFRs in products.
Conversely, false negatives could be generated when product wipes could not remove BFRs at
the surface of product despite their presence in products. Quantifying false positives and
negatives was beyond the scope of this study, and as such we assumed that removing dust from
the surface of products prior to sampling could minimize the occurrence of false positives.
However, another explanation rather than product wipe contamination by surface dust, is that
BFRs not intentionally added to polymers will partition from indoor air into any polymer as a
function of the physico-chemical properties of the BFR and polymer. In fact, the partitioning of
any semi-volatile compound present in air (e.g., as released from other products) into a polymer
would be expected and thus, the product wipe reflecting this surface sorption would not in fact
be providing a “false” positive, but would not be indicative of FRs intentionally added to
products. As screening products using this wiping method shows promise, further investigation
is needed to improve product wipe testing techniques.
34
Supporting Information
QA/QC: All samples were blank corrected using the following criteria: no correction if sample
concentration was <5% of blank concentration, blank correction if sample was between 5-35% of
blank concentration, and sample discarded if concentration was >35% of blank concentration.
The instrumental limits of detection (IDL) were calculated as per Newton et al. (2015). For
compounds detected in the blanks, method detection limit or LOD was calculated as the average
of 8-10 lab blank levels plus 3 standard deviations. The values of IDL and LOD of each
compound are given in Table S1.
Analytical methods for flame retardants were validated for their reproducibility using certified
reference material (NIST SRM-2585-organic contaminants in house dust). Five CRM/SRM
replicates were analyzed in every batch of 10 samples and the measured values for PBDEs were
compared to certified values of SRM (recoveries ranged from 90 to 115%). Except for BDE-
209, PBDE congeners showed good reproducibility with relative standard deviation (RSD) of
individual congener ranging from 2 to 12% as compared to RSD range of 1-13% for certified
values. Accuracy performance of BDE-209 was ±25% (Figure S2.1). Except OBIND and
DBDBE, spike recoveries of NFRs were >75% and good reproducibly with RSD ranged between
7-15%. FR concentrations in dust and product wipes were reported in units of ng FR/g dust and
ng FR/wipe, respectively.
35
Table S2.1: Limit of detection (LOD) and instrumental detection limit (IDL) for NFRs and PBDEs included in this study.
FR LOD (ng) IDL (pg) Blank
ATE 0.015 1.9 0.01
PBBz 0.13 0.8 0.1
HBB 0.03 0.9 0.02
PBT 0.965 1.4 0.1
TDCPP 0.195 40 0.2
PBEB 14.21 1.1 8.2
TBB 0.045 15 0.04
TBPH 0.28 15 0.3
s-DP 0.145 9.3 0.14
a-DP 0.155 9.2 0.13
DBDPE 0.025 10 0.02
OBIND 1.82 34 1.80
BDE-17 0.005 0.5 0.005
BDE-28 0.415 3.2 0.42
BDE-71 0.025 4.5 0.025
BDE-47 0.64 4.6 0.60
BDE-100 0.025 5 0.025
BDE-99 0.685 6.8 0.7
BDE-154 0.01 5.3 0.01
BDE-153 0.75 8.5 0.7
BDE-183 0.075 24 0.07
BDE-209 1.18 4.1 1.2
36
Figure S2.1: Comparison of measured and certified PBDE values of NIST-SRM 2585 (error bars indicate relative standard deviation)
Figure S2.2: Correlation between Br content in product wipes (ng/wipe) and Br levels measured by XRF (µg/g).
1
10
100
1000
10000 Co
ncen
tra)
on (n
g/g)
Congener
Measured values
Cerffied values
1
10
100
1000
10000
100 1000 10000 100000 1000000
Br con
tent (n
g/wipe)
Br content (µg/g)
37
Table S2.2: Descriptive statistics for FRs measured in home and office dust (ng/g dust); Percentage of samples containing FRs, mean, median and range of FRs in home and office dust samples
Home Office
% Detect Mean Geomean Range % Detect Mean Geomean Range ATE 40% 1.5 0.0 <LOD -30 60% 6.0 0.3 <LOD -30 PBBz 37% 0.9 0.0 <LOD -16 50% 2.2 0.0 <LOD -10 HBB 80% 5.9 0.4 <LOD - 42 90% 95 25 <LOD -540 PBT 3% 1.2 0.0 <LOD - 41 40% 39 0.1 <LOD -270
TDCPP 83% 3463 690 <LOD - 46,000 90% 33260 8687 <LOD -190,000
PBEB 3% 4.3 0.0 <LOD -150 0% 1.0 0.0 <LOD
EH-TBB 97% 963 215 <LOD -7500 90% 1192 543 0<LOD - 6200
BEHTBP 97% 672 77 <LOD -10,000 80% 7676 156 <LOD -52,000
DBDPE 69% 221 0.5 <LOD -5500 90% 20.6 1.6 <LOD -110 OBIND 43% 158 0.1 <LOD -3600 90% 296 2.7 <LOD -1000 s-DP 97% 13 0.7 <LOD -150 98% 44 31 <LOD -130 a-DP 97% 29 7.9 <LOD -130 98% 98 79 <LOD -200
BDE-17 91% 2.3 0.8 <LOD -11 90% 22 7.1 <LOD -120 BDE-28 69% 23 0.6 <LOD -245 60% 89 2.3 <LOD -500
BDE-47 89% 429 53 <LOD -5300 90% 11112 2097 <LOD -72,100
BDE-71 89% 20 6.5 <LOD -85 90% 76 59 <LOD -200
BDE-99 89% 836 74 <LOD -12,500 90% 19766 3840 <LOD -120,000
BDE-100 94% 132 22 <LOD -2000 90% 3640 663 <LOD -22,000
BDE-153 66% 261 2.4 <LOD -2100 90% 272 51 <LOD -1400
BDE-154 91% 58 7.3 <LOD -950 90% 2387 510 <LOD -12,500
BDE-183 80% 30 2.1 <LOD -340 90% 300 99 <LOD -1400 BDE-209 97% 805 44 <LOD-12,000 90% 486 195 0.02 -1600
38
Figure S2.3: Correlations between logarithms of the geomean concentrations of FRs in products and dust samples; a) lighter compounds with molecular weight < 600, b) heavier compounds with molecular weight > 600.
Y=1.5x + 1.17 r2 =0.8
Y=0.35x + 1.9 r2 =0.73
a
b
39
Figure S2.4: Concentrations of FRs in house and office dust arranged according to increasing Koa. Each point represents the concentration of each compound in dust sample at each location.
Figure S2.5: K-mean partitioning and Simple Structure Index of criterion
40
Chapter 3: Stock and Flows of PBDEs in Products from Use to Waste in U.S. and Canada from 1970 to 2020
3.1 Introduction
Prior to being banned or phased out in Europe, Canada, and the U.S., polybrominated diphenyl
ethers (PBDEs) were used as flame retardants (FRs) in a variety of products. Since they are not
chemically bound to plastics, foam, fabrics and other materials to which they were added,
PBDEs migrate from products into indoor and outdoor environments (Zhang et al., 2011,
Batterman et al., 2010, Takigami et al., 2008, Hazrati et al., 2006). This, in turn, has resulted in
human exposure as well as the contamination of soils, wastewater, waterbodies, biota, and
consequently food supplies. Many in vitro and in vivo animal studies have demonstrated a range
of adverse effects from PBDE exposure (Madia et al., 2004, Coburn et al., 2008, Alm et al.,
2010, Buttke et al., 2013). Further, epidemiological evidence has found associations between
PBDE exposure and altered concentrations of thyroid hormones, decreased fertility in adults and
lowered IQ in children exposed to ambient levels (Eskenazi et al., 2013, Meeker et al. 2009,
Turyk et al., 2008).
The marketing and use of products containing more than 0.1% of the commercial mixture of
penta- and octaBDE (c-penta and c-octaBDE) was first banned by European Union (EU) in
2003, in part because of concerns about rising levels of these compounds in human breast milk.
The EU then banned the use of the commercial mixture of decaBDE (c-decaBDE) in electrical
and electronic equipment (EEE) in 2008. In Canada, the homologues in c-penta- and c-octaBDE
were declared toxic in 2006 under the Canadian Environmental Protection Act, after which their
production and use in new products was banned in 2009, while a ban on the use of c-decaBDE in
41
EEE was proposed in 2011. In the U.S., starting in the early 2000s, regulations banning the use
of PBDEs were adopted by individual states (e.g., Washington, Maine). At the federal level,
U.S. manufacturers agreed to voluntarily phase out the production of c-penta- and c-octa- before
the end of 2004 and c-decaBDE after 2013. Also, U.S. manufacturers and importers of c-penta-
and c-octaBDE are required to submit a significant new use notice to the U.S. Environmental
Protection Agency 90 days prior to their manufacture, import or use. Neither U.S. nor Canada
regulations pertain to imported finished products that contain PBDEs.
At the global scale, tetra- to heptaBDE congeners were added to the list of chemicals targeted for
global elimination from production and use under the Stockholm Convention on Persistent
Organic Pollutants in 2009 (Stockholm Convention 2009). In 2013, Norway filed a petition to
add c-decaBDE to the list of POPs under the Stockholm Convention (UNEP.2013).
The bans and restrictions noted above do not specifically address existing stocks of PBDE-
containing products that are still in use or have entered the waste phase. In addition, penta- and
octaBDE in recycled plastics have been exempted from the controls placed on these two
commercial mixtures by the Stockholm Convention (UNEP 2010, Chen et al., 2010). Since
PBDE contained in in-use products will presumably continue to be a source of human and
environmental exposure to PBDEs, our first goal was to develop time-dependent estimates of the
stocks of penta-, octa- and decaBDE commercial mixtures in in-use products and to estimate the
magnitude and the rate at which the PBDEs in these products enter the waste stream in the U.S.
and Canada. A second goal was to estimate PBDE emissions to air from the stock of PBDEs in
the use phase. The stock for the period from 1970 to 2020 was based mainly on consumption
patterns of PBDE-containing products over time and their residence time in the use phase. The
42
projected changes in the stock of PBDEs are intended to provide insight into the effectiveness of
control measures aimed at reducing levels of PBDEs in the environment.
The use of decaBDE in the transportation sector started prior to 1970 (Bullock 2013). Limited
reporting of production values of most PBDE commercial mixtures began in 1970 (ATDSR
2004) however reliable information on use is scarce. PBDE formulations have been produced by
three major commercial manufacturers, two of them in the U.S. (Chemtura, previously Great
Lakes Chemical Corporation, and Albermarle), and Israel Chemicals Limited (ICL).
Additionally, PBDEs were also produced in Europe (Germany and Netherland), China, and
Japan (ATDSR 2004).
The Bromine Science and Environmental Forum (BSEF), of which Chemtura, Albermarle, and
ICL are members, reported the 1999 and 2001 market demand for PBDE commercial
formulations (Renner 2000, BSEF 2003), which can be roughly translated into sales data (Table
S3.1 in Supporting Information). These values have been widely and repeatedly reported (Alaee
et al., 2003, Alcock et al., 2003, Hites 2004, Morf et al., 2005) and used to estimate the time-
dependent consumption of PBDEs and PBDE emissions in Europe and/or North America
(Alcock et al., 2003, Morf et al., 2005, Prevedouros et al., 2004).
UNEP (2010) reported that ~100,000 tonnes of pentaBDE have been manufactured globally
since 1970. Using the 2001 BSEF data and some other sources, Alcock et al.(2003) estimated
that about 85% of the total pentaBDE was used in North America and the remainder in Europe.
Total consumption of octaBDE was estimated at ~110,000 tonnes (UNEP 2010) with ~40% used
in North America, ~40% in Asia, and ~15% in Europe (at least in 2001). The total global
production of decaBDE was estimated at ~1,100,000 to 1,250,000 tonnes from 1970 to 2005
43
(UNEP 2010), of which ~44% was expected to be consumed in North America in 2001 (BSEF
2003). By 2005, production of decaBDE was estimated to have exceeded 60,000 tonnes per year
with over 40% of the total global production used in North America (Illinois EPA 2006). The
consumption of decaBDE in North America may have increased due to the curtailed use of
penta- and octaBDE but there is no firm evidence of this. Assuming constant annual
consumption of decaBDE from 2005 to 2013, the total amount of decaBDE consumed in North
America from 1970 to 2013 can be estimated at ~700,000 tonnes. It needs to be emphasized that
all these estimates bear considerable uncertainty, even if this is not specified in the data sources.
Below, we present our estimates of the use of each commercial mixture in the U.S. and Canada
according to product usage, as well as PBDE emissions to air from 1970 to 2020.
3.2 Methods According to the Stockholm Convention technical guidance (UNEP 2012), the inventory of
PBDEs comprises the stock of PBDEs in products in-use and in the waste stream, in stockpiles
and potentially contaminated sites. The product categories we considered are listed in Table
S3.2 and those excluded, due to a lack of data, are listed in Table S3.3. A major gap in our study
is the amount of decaBDE used in building insulation and other construction materials. With one
exception noted below, the approach we used was based on balancing the mass of all time-
dependent inputs (annual consumption) into the system (use phase) and the mass of all outputs
from the system (to the waste stream) plus a storage time (stock) that considers accumulation in
the system (e.g., PBDE-containing products that are “hibernating” – not in use but not
discarded).
44
The products were assumed to enter the waste phase at the end of their first use or lifespan; the
uncertainty associated with a product's lifespan is covered in the uncertainty analysis. Detailed
methods for each product category are provided in SI (Section 1).The flow of PBDEs in in-use
products to the system was estimated based on consumption patterns and sales data of PBDE-
containing products (mostly in the U.S.) from 1970 to 2010, and projections to 2020. Where the
number of products entering the use phase (e.g., sales data) was available or could be
extrapolated based on a consumption pattern or production rate, a “top-down” approach (Müller
et al. 2014) was used, as described below. For the casings of all electrical and electronic
equipment (EEE), polyurethane foam (PUF) slabstock used in furniture (e.g., couch cushions and
non-molded chairs), and plastic pallets, the mass of PBDEs in products entering the use phase in
a given year was added to those remaining in the use phase from previous years calculated using
a Weibull statistical distribution. The Weibull distribution was used to estimate the probability
distribution of products purchased in a given year entering the waste phase in subsequent years
according to their specific lifespans. Equations and further details are provided in the SI.
Annual vehicle registration and vehicle age data were used to estimate the stock of PBDEs in
cars and light trucks. A “bottom-up” approach was used for PBDEs in textiles for which no data
were available on annual product sales, the percentage of textile products treated with PBDEs, or
the PBDE concentrations in those products. In this case, the stock was estimated from the
aggregated annual consumption of PBDEs and the overall percentage of PBDEs used to treat
textiles (US EPA 2014).
For those products for which the stock was estimated using a Weibull distribution (Eq S1-S6),
the shape parameter k (expressing the relative likelihood of products leaving the use phase over
time) was 2.4 for most EEE (Oguchi et al., 2008) and 3.5 for CRT displays (Tasaki et al., 2004).
45
The lifespan of each product-type T was based on a U.S. national survey of the age of household
products (US EPA 2011). The numbers of products of any one type entering the use phase in a
given year were translated into product mass, MTotal (tonnes), using the average weight of each
product (US EPA 2011). The mass of PBDEs in each product in the use phase, MPBDE (tonnes),
was calculated as
𝑀!"#$ = 𝑀!"#$% ∙ 𝐹! ∙ 𝐹!" ∙ 𝐶!"#$ (Eq 1)
Where Fp, is the mass fraction of that product comprised of a particular polymer to account for
products that are comprised of multiple types of materials of which only some may have been
treated with PBDEs, FFR is the fraction of that product treated with PBDE to account for
products for which only some were treated with PBDEs, and CPBDE (tonne/tonne) is the
concentration of PBDEs in the polymer fraction of each product. Values of Fp were taken from
Morf et al. (2005) and Wäger et al. (2011). FFR was taken from a screening of the Br content of
~1,000 products estimated by means of X-ray fluorescence (XRF) analyzer (Table S3.4 for
EEE). A Br content of 0.1% (Restriction of Hazardous Substances or RoHS European Union)
was used as a threshold to discriminate between products with purposefully added and those
without PBDEs. CPBDE was obtained from several sources including a companion study in which
120 products spanning a range of manufacturing years were analyzed for their congener-specific
PBDE concentrations by GC-MS (Tables S3.4, S3.6). Since penta- and octaBDE were phased
out in 2004 and the production of decaBDE was expected to be discontinued after 2013, we
assumed that no products containing penta- or octaBDE entered the use phase after 2004 and for
decaBDE, after 2013.
46
A Monte Carlo analysis with 10,000 runs was performed to evaluate the uncertainty of the
estimated stock and the sensitivity of the result to the most important and uncertain parameters
(Table S3.8). All variables used in this study were assumed to be independent and to have a log
normal distribution (Wäger et al., 2012) defined according to a confidence factor listed in Table
S3.8. The 2.5% and 97.5% percentiles of the probability distributions were calculated for each
year to obtain the 95% confidence interval for the mass of PBDEs in the use phase. Details on
the uncertainty analysis are described in SI (Section 2.3).
3.3 Results and Discussion
3.3.1 Stocks of CRT TVs and decaBDE The dynamic stocks of cathode ray tube televisions (CRT TVs) and PBDEs in the CRT TV
casings in the U.S. and Canada from 1970 to 2020 is used to illustrate results for those products
analyzed using a “top-down” approach and the Weibull distribution (Figure 3.1). Each color
band in Figure 3.1a represents the mass of CRT TVs (sales data multiplied by average weight)
that entered the use phase in a given year multiplied by its probability of staying in the use phase
over time (Weibull shape parameter k=3.5). The increase in the stock of CRT TVs in the use
phase from early 1980s to early1990s was associated with an increase in market demand for
these products followed by a moderate increase in late 1990s until a peak of ~7 million tonnes
was reached in 2000 (Figure 3.1a). The stock of the in-use CRT TVs then declined gradually
from 2000 to 2010 due to the replacement of these products with lighter LCD and/or LED TVs.
The change in the accumulation rate of CRT TVs in the use phase occurred as the lifespan of
47
CRT TVs dropped from 14 to 9 years after 1990. The large flow of retired CRT TVs to the
waste phase resulted in a rapid decline in the stock of CRT TVs in the use phase after 2010.
The stock of decaBDE in CRT TV casings peaked in the use phase at ~35,000 tonnes in 2000
which corresponds to the largest stock of CRT TVs in the use phase (Figure 3.1b). Due to
restricted use in Europe and impending controls in North America, use of decaBDE in new
products was assumed to be zero following 2013. By 2020, we estimated that almost all
decaBDE in the casing of CRT TVs would have left the use phase.
The substantial flow of decaBDE in CRT TVs to the waste phase started in the late 1970s, almost
10 years after their first use. This is shown in Figure 3.1c where the peak (or maximum
thickness) of each individual color band corresponds to the year in which the greatest mass of
decaBDE in CRT TVs purchased in any specific year entered the waste phase. The sharp
increase in the flow of decaBDE from mid-1990s to mid-2000s reflects the increase in the use
and discarding of CRT TVs that entered the use phase from early 1980s to 2000. The flow of
decaBDE in CRT TV casings to the waste phase started to decline in 2004, four years after the
peak in the use phase, and will continue until 2020.
Section S2.1 contains details of similar Weibull distributions that were generated to estimate the
stocks and flows of the three PBDE commercial mixtures in the casings of other EEE, wiring,
PUF used in furniture, plastic pallets and textiles. The time trend of the stock of vehicles was
estimated based on available information about registered vehicles and their age distribution
from 1970 to 2010 (SI Section 1.2.5)
48
Figure 3.1: Stock of decaBDE in CRT TV casing in the U.S. and Canada from 1970 to 2020: (a) stock of CRT TVs in the use phase (million tonnes), (b) stock of decaBDE used in CRT TV casings in the use phase (kilo tonnes), and (c) flow of decaBDE used in CRT TV casings in the use phase (kilo tonnes), and (c) flow of decaBDE used in CRT TV casings to the waste phase (kilo tonnes/year).
0
2
4
6
8
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of CRT
TV (M
t) a
0 5
10 15 20 25 30 35 40
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of decaB
DE in
CRT TV
s (kt)
b
0
1
2
3
4
5
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020 Flow
of d
ecaB
DE in CRT
TVs to
waste phase (kt/y)
c
49
3.3.2 Stock of Commercial Mixtures of PBDEs A total mass of 46,000 tonnes (95% confidence interval or CI: 8,000-76,500 tonnes, Table S3.7)
of pentaBDE was estimated to have entered the use phase in the U.S. and Canada from 1970 to
2004 with 65% in PUF furniture, 33% in automotive vehicles, and 2% used in EEE (Figure
3.2a). PentaBDE use in vehicle seating began in the early 1970s, and in PUF furniture and EEE
in the mid-1970s. By the 1990s, pentaBDE in vehicle seating was replaced with mainly
chlorinated flame retardants, while the amount of PUF furniture treated with pentaBDE
increased by a factor of three. The contribution of pentaBDE in the casings of electronic devices
was estimated to be minimal. It should be noted that the estimated use of PBDEs in EEE
includes only the casing of products and did not include PBDEs that may have been used in other
parts such as motherboards and other interior components of these products.
The main use of pentaBDE in PUF slabstock used in furniture (e.g., couch cushions, other non-
molded PUF furniture components) peaked at ~17,000 (6,000-70,000 tonnes) in 2004 in the U.S.
and Canada (Figure 3.2a). The fastest annual growth rate of ~10% occurred from 1980 to 1988.
Considering only the first lifespan of products, most of the pentaBDE stock in these products
was estimated to leave the use phase by 2020. In comparison, by doubling the lifespan of PUF
furniture from 15 to 30 years (i.e., use of second-hand furniture), the peak of pentaBDE in these
products in the use phase would increase by 30% from ~13,000 to 20,000 tonnes and about 35%
of the peak pentaBDE stock in these products in 2004 would remain in the use phase in 2020
(Figure S3.2).
50
Figure 3.2: Stock of each PBDE commercial mixture in in-use products in the U.S. and Canada from 1970 to 2020, (a) pentaBDE in EEE, automotive vehicles and PUF slabstock used in furniture, (b) octaBDE in automotive vehicles and EEE, and (c) decaBDE in plastic pallets, textiles, EEE and automotive vehicles.
The total mass of 25,000 (4,000-45,000, Table S3.7) tonnes of octaBDE was estimated to have
entered the use phase in the U.S. and Canada from the mid-1970s to 2004, with 80% used in the
casings of EEE (CRT TV and computers) and 20% used to flame retard soft plastics in vehicles
(Figure 3.2b). The stock of octaBDE increased rapidly from 1980 to 2000 due to strong
consumer demand for these products, especially for CRT TVs. The total stock of octaBDE in the
use phase peaked in 2004 at ~4,000 (1,000-50,000) tonnes after which no new use was assumed.
By 2020, almost all octaBDE was estimated to have left the use phase.
0
4
8
12
16
20
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of pen
taBD
E (kt) Total pentaBDE
PUF slabstock Automofve EEE
a
0
1
2
3
4
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of octaB
DE (kt) Total octaBDE
EEE
Automofve
b
0
40
80
120
160
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of decaB
DE (kt) Total decaBDE
EEE Automofve Texfles Plasfc pallets
c
51
DecaBDE was used most extensively of the three commercial mixtures. A total of 380,000
(70,000-650,000, Table S3.7) tonnes was estimated to have entered the use phase from 1970 to
2013, with 35% in vehicle seating, and 35% in the casings of EEE, wire and cables, ~20% in
textiles, and 10% used in plastic pallets (Figure 3.2c). The main application of decaBDE prior to
1970 was to coat textiles used in vehicle seating and after that, in plastics and foams used in the
interior of vehicles (Gearhart et al., 2009). However, its main use shifted in the 1980s to casings
for EEE largely because of demand for CRT TVs.
DecaBDE stock peaked in 2008 at ~140,000 (40,000-300,000) tonnes. The stock of decaBDE in
EEE casings peaked around 2005 at ~50,000 tonnes after which CRT TVs and heavy desktop
computers were replaced by lighter alternatives. The peak of decaBDE in the automotive sector
occurred in 2008 at ~45,000 tonnes, just before the U.S. recession reduced market demand for
new vehicles. Due to controls and restrictions, we assumed that decaBDE was not used in new
products following 2013. Approximately 70,000 tonnes of decaBDE was estimated to remain in
the use phase by 2020, mostly in vehicles followed by plastic pallets, textiles, and EEE.
Due to a lack of data, the estimated stock of PBDEs in the transportation sector did not include
PBDEs in large vehicles and public transportation (e.g., trucks, buses, trains, aircrafts) and
construction materials (e.g., insulation foam) (U.S. EPA 2010). These products likely contribute
significantly to the total stock of decaBDE (US EPA 2014) based on the requirements of
flammability standards (e.g. 14 CFR Part 25, 49 CFR Part 238). Further details concerning
uncertainties contained in this analysis are discussed in SI (Section 2.3).
3.3.3 Stock and Flows of PBDEs The stock of sum of the three commercial PBDE mixtures in all products considered in the use
phase from 1970 to 2020 in the U.S. and Canada was estimated by summing the stocks of
52
pentaBDE, octaBDE, and decaBDE (Figure 3.3a). PBDE stock peaked in 2005 at ~160,000
(50,000-330,000) tonnes (Figure 3b). Prior to that from 1980 to 2004, the stock of in-use PBDEs
increased by 3-15% annually (a doubling time of 4-24 y) with the fastest rate occurring between
1974 and 1986. In comparison, Hites (2004) estimated a doubling time of ~5 years in human
tissues and marine mammals between 1970 and 2001 (mostly of penta- and octaBDE), which is
consistent with our doubling time of 4-7 years for the inventory of penta- and octaBDE from
1970 to 2004. The rate decreased to 2-5% annually between 2004 and 2013 due to the
discontinued use of pentaBDE in 2004 and fewer vehicle registrations from 2008 to 2013.
Assuming no new use of decaBDE after 2013 and a single use of products, ~120,000 (40,000-
300,000) tonnes of PBDEs (95% decaBDE) was estimated to remain in the use phase in 2014.
After that, the stock is anticipated to decrease annually at 5-15% from 2013 to 2020 (halving
time of 4-14 y). The decrease is mainly attributable to decaBDE-containing EEE and vehicles
entering the waste phase. Approximately 60% of the total mass of PBDEs in the use phase in
2014 or ~70,000 (10,000 - 180,000) tonnes, which is mainly decaBDE, is expected to remain in
the use phase by 2020 mostly in vehicles. As noted above, these projections assumed only a
single lifespan of product use and neglected the possible storage time of waste products prior to
being discarded. Moreover, construction materials, large vehicles and aircraft that have
considerable longer lifespans (at least 20 years) were not included in this study and will prolong
the stock of PBDE remaining in use. Thus, our estimates account for the minimum of the total
usage and an expedited timeline for the retirement of PBDEs contained in in-use products.
The flow of PBDEs in products to the waste phase was calculated using the probability density
function of the Weibull distribution (Eq S4), except for PBDEs in the automotive sector for
which a Weibull distribution was not used. Although PBDEs were in use since the 1970s, the
53
flow of PBDEs to the waste phase was not appreciable until the mid-1980s (Figure 3.4). The
largest flow of PBDEs to the waste phase in all products excluding automotive sector, occurred
between 2005 and 2008 with the annual flow of ~10,000 tonnes, mainly due to the retirement of
CRT displays. Assuming that new products would not contain penta- and octaBDE after 2004
and decaBDE after 2013, we estimated that PBDEs entering the waste phase will decline at 4-
12% annually after 2013.
Morf et al. (2008) estimated that the stock of pentaBDE in Switzerland increased at 10-20%
annually based on the production and the total consumption of pentaBDE and pentaBDE-
containing products in Switzerland from 1980 onwards, with a peak of 8 tonnes in 1994. The
production and consumption of pentaBDE declined dramatically in Europe in 1990s
(Prevedouros et al., 2004, Alcock et al., 2003). Morf et al. (2008) estimated that 30% of the
stock of pentaBDE in 1990s in Switzerland would remain in the use phase until 2020. The
longer residence time of the stock of pentaBDE in the use phase estimated by Morf et al. (2008)
than in this study is likely due to the longer lifespan of consumer products in Switzerland than
the U.S. and Canada and, more importantly, the longer residence time of pentaBDE-containing
construction materials in the use phase that was not included in our study. Earnshaw et al.
(2013) estimated that the stock of decaBDE in Europe peaked at ~80,000 (60,000-110,000)
tonnes in early 2000s. The stock of decaBDE in in-use products in Japan was estimated to be
~60,000 tonnes in 1990s based on the production rate and importation of PBDE-containing
products (Sakai et al., 2006).
We estimated the per capita use of PBDEs in the U.S. and Canada as 10-250, 10-150 and 200-
2000 g·capita-1·y-1 for penta-, octa-, and decaBDE, respectively, from 1970 to 2020. These
values compare reasonably well with Csiszar et al. (2013) who estimated an equivalent of 50
54
g·capita-1·y-1 consumption in 2007 of penta- and octaBDE in Toronto according to statistics and
census data. Using the PBDE consumption estimates of Morf et al. (2008) and Earnshaw et al.
(2013) respectively, we derived a per capita use of pentaBDE in Switzerland and decaBDE in
Europe of 5-10 g·capita-1·y-1, and 250-350 g·capita-1·y-1, respectively. The higher consumption
of PBDEs in the U.S. and Canada is consistent with relatively high reported concentrations of
these chemicals in household dust and human tissues in these countries (Betts 2002, Hites 2004,
Harrad et al., 2008, Zota et al., 2008), which is associated with the specific requirements of the
flammability standards in the U.S. and Canada.
3.3.4 From Stocks to Emissions As noted above, the stock of PBDE-containing products in the use phase provides an on-going
source of PBDE emissions to the environment (Sakai et al., 2006, Csiszar et al., 2013, Cousin et
al., 2014, Björklund et al, 2012). Csiszar et al. (2013) estimated, by means of mass balance
modeling, that approximately 0.01% of the inventories of penta- and octaBDEs were emitted to
air in Toronto in 2007. This estimate was derived by reverse modeling from measured air
concentrations by Melymuk et al. (2012) to obtain the emission rate necessary to support those
measured concentrations. This value is less than the annual emission factor of 0.7% estimated
by Palm et al. (2002) and emissions from controlled chamber experiments of tetra- and
pentaBDE congeners from TVs and PC monitors of 0.1 and 0.4% measured by Ball et al. (cited
by Alcock et al. 2003). However, it is similar to the estimates of Alcock et al. (2003) based on
KOA-corrected values developed for PCBs by Breivik et al. (2002). Csiszar et al. (2013) also
estimated an atmospheric emission rate of ~0.002% for decaBDE inventory in Toronto in 2007
(unpublished data). Sakai et al. (2006) estimated an annual atmospheric emission factor of
decaBDE of between 0.0003 and 0.003% of the decaBDE inventory in Japan (170-1800 kg·y-1
55
relative to 60,000 tonnes of decaBDE stock). Using ranges in the annual emission factors of
0.01-0.1% annually for penta- and octaBDE stocks and 0.0003-0.003% annually for the stock of
deca-BDE, we estimated that the atmospheric emissions in the U.S. and Canada could be 0.4-4
tonnes·y-1 for penta- and octaBDE, and 0.35-3.5 tonnes·y-1 for decaBDE in 2014 when the
respective stocks would be 4,000 and 120,000 tonnes. Summing emissions from the stocks of all
PBDEs in each year from 1970-2020, gives an estimate of 70-700 tonnes total atmospheric
emissions.
In future, we estimate that PBDE levels in air will decline at a rate proportional to the stock of
PBDE-containing products, since secondary emissions of PBDEs from contaminated soils and
surface waters have been estimated to be negligible in comparison to primary emissions (Csiszar
et al., 2014). Landfills could also be a source of PBDEs to air, but evidence for the importance of
this emission source is inconclusive (Weinberg et al., 2011). The best case scenario of the rate of
decline of the total PBDE stock and hence air concentrations would be ~5-10% annually or a
halving time of 7-14 y until 2020. The stocks of penta- and octaBDE were estimated to drop
more quickly with an annual rate of 15-20% (halving time of 3-5 y) after 2004 due to what is
likely an underestimation of the actual lifespan of PUF containing products (given our
assumption of the single use of these products). These estimates are close to the measured
halving time of ~6 y in air (vapor, particle, and precipitation) of pentaBDE congeners (BDE-47
and -99) in the Great Lakes region from 2005 to 2009 (Salamova & Hites 2011). In comparison,
the decaBDE stock declined gradually from 2006 to 2012 at an average rate of 1-3%, after which
a sharp decline is expected after 2013 at an average rate of 4-10% (7-17 y half-life). These
projections are consistent with the lack of a significant change in Great Lakes air concentrations
of decaBDE from 2005 to 2009 (Salamova & Hites 2011). However, recently Ma et al. (2013)
56
reported more puzzling temporal trends in Great Lakes air concentrations based on data from
2005 to 2011: BDE-47 concentrations in vapor and particle phases were halving every 5-9 y in
Chicago and Cleveland, but had doubling times at rural sites of 7-11 y in the vapor phase and 2-4
y in precipitation, with no systematic changes in decaBDE concentrations. Concentrations of
pentaBDE in Lake Ontario trout have shown halving times of 5-13 y Crimmins et al., 2012, EC
2013) which overlaps with the range estimated here.
Overall, estimates of the rate of decline of the stock of products containing PBDEs, along with
decreases in measured PBDE concentrations in environmental media, suggest that PBDE control
measures have been effective thus far in reducing PBDE environmental burdens in the U.S. and
Canada. However, as PBDE-containing products continue to accumulate in the waste stream,
waste management policies need to ensure that PBDEs are not emitted to the surrounding
environment. Also, any reuse of PBDE-containing materials should only follow a successful
PBDE separation and removal from these materials. Finally, it should be pointed out that in
order to meet flammability standards, PBDEs have been replaced with other flame retardants,
which only now are being assessed for their potential persistence and/or toxicity and which are
being detected in various environmental media (Ma et al., 2013). It is thus important to consider
potential ecological and human health effects associated with the use of flame retardants when
developing or updating flammability regulations, standards, codes, or requirements.
57
Figure 3.3: Stock of PBDEs in in-use products in the U.S. and Canada from 1970 to 2020, (a) “best” estimate of pentaBDE, octaBDE, and decaBDE and their total, and (b) 2.5 and 97.5 percentiles of the stock of total PBDEs in the use phase estimated using a Monte Carlo analysis.
Figure 3.4: Flow of PBDEs to the waste phase in the U.S. and Canada from 1970 to 2020 (PBDEs in the automotive sector were excluded).
0
40
80
120
160
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of PBD
Es (kt)
Total PBDE Total decaBDE Total pentaBDE Total octaBDE
a
0 50
100 150 200 250 300 350
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of PBD
Es (kt)
b
0
2
4
6
8
10
12
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Flow
to waste phase (kt/y) Total pentaBDE
Total octaBDE Total decaBDE Total PBDE
58
Supporting Information
Table S3.1: Total market demand of PBDE mixtures by region in tonnes in 2001
PBDEs Americas Europe Asia The Rest of the World Total
DecaBDE 24,500 7,600 23,000 1,050 56,100 OctaBDE 1,500 610 1,500 180 3,790 PentaBDE 7,100 150 150 100 7,500 Data source: BSEF 2001.
S 3.1 Methods Table S3.2: Products included in this study and the estimation methods used.
Sector Type of products
Type of data Estimation method
Data Source
EEE TV (CRT & flat)
- Consumption pattern (1970–1980) - Annual sales data (1980–2010)
Weibull distribution model (Top-down approach)
U.S. EPA 2011, Oguchi et al. 2008 Tasaki et al. 2004
Monitor (CRT & flat)
- Consumption pattern (1970–1980) - Annual sales data (1980–2010)
Weibull distribution model (Top-down approach)
U.S. EPA 2011, Oguchi et al. 2008
PC (desktop & laptop)
- Consumption pattern (1970–1980) - Annual sales data (1980–2010)
Weibull distribution model (Top-down approach)
U.S. EPA 2011, Oguchi et al. 2008
Hardcopy devices (printer & fax)
- Consumption pattern (1970–1980) - Annual sales data (1980–2010)
Weibull distribution model (Top-down approach)
U.S. EPA 2011, Oguchi et al. 2008
Audio/ video (video, DVD player & cassette player)
- Consumption pattern (1970–1980) - Annual sales data (1980–2010)
Weibull distribution model (Top-down approach)
U.S. EPA 2011, Oguchi et al. 2008
59
Wires & cables
- Total annual mass of decaBDE used in wire and cable in the U.S. for selected years between 1990 to 2010
Weibull distribution model (Top-down approach)
Harriman 2012 (Unpublished data)
PUF slabstock
Residential & non-residential furniture
- Total mass of PUF slabstock manufactured annually (1987–2008) - Exponential increase in foam production (1970–1987)
Weibull distribution model (Top-down approach)
Luedeka & Knudtson 2012, personal communication
Plastic products
Pallets - Total number of plastic pallets produced annually (1990–2010) - Annual increase rate in decaBDE consumption
Weibull distribution model (Top-down approach)
Pure Strategies 2010
Automotive Passenger vehicles
- Total number of cars registered annually from (1970–2020) and their age distribution
Registered vehicles and age distribution
FHWA 2011, Davis, 2001
Light trucks - Total number of trucks registered annually from (1970–2020)
Registered vehicles and age distribution
FHWA 2011, Davis et al. 2001
Textiles Textile and fabric
- An average of 22% of the total annual decaBDE consumption in other sectors was assumed to be used for textiles and fabrics
Weibull distribution model (Bottom-up approach)
U.S. EPA, 2014
60
Table S3.3: Products containing PBDEs not included in this study
PBDE Products PentaBDE Non-furniture foam, construction materials (insulation, paint coatings), potting
compounds in electronics, textile coatings, public transportation (buses, trains, airplanes), off-road vehicles
DecaBDE Building materials, remote controls, capacitor films, internal E&E components, circuit breakers, coils of bobbins, electrical wiring and equipment used in transportation, public transportation (buses, trains and airplanes), small household appliances, interior components of EEE (e.g. motherboards, hard drives, batteries), carpet cushion and recycled plastic products.
Data source: Scherrer 2012.
S3.1.1 Statistical Methods The probability distribution of one product type remaining in the system over time, in this case the use
phase, was assumed to follow the complimentary cumulative probability function of the Weibull
distribution. Specifically, the distribution provides the probability over time of one product entering the
use phase in a specific year and remaining in the use phase in the subsequent years. The equation for the
complimentary cumulative Weibull function can be written as
𝑊′ 𝑡 = 1 −𝑊 𝑡 = 𝑒!!!!!!
!
(Eq 1)
W(t) is the cumulative Weibull function, whereas W’(t) is the complementary Weibull function
that defines the fraction that remains in the use phase over time. t is the calendar year, adjusted
by putting t in the middle of the year for each year (i.e. t = 2013.5 for the year 2013); t0 is the
calendar year when the mass entered the use phase; T is the average lifespan of a given product
type (also known as the scale parameter); k is the distribution parameter (also known as the shape
parameter) defining the shape of the Weibull function. The initial total mass M0 of one type of
product entering the use phase in a specific year was obtained by multiplying the total number of
products of one type purchased in a given year with their average mass. The mass of these
61
products that remain in the use phase over time M(t) was then calculated by multiplying W’(t)
with M0.
𝑀 𝑡 = 𝑀! ∙𝑊! 𝑡 (Eq 2)
The stock of products of one type remaining in the use phase over multiple years was built by
adding the complimentary cumulative probability functions for the mass of products of that type
entering the use phase in each year considered
𝑀!"#$% 𝑡 = 𝑀(𝑡, 𝑖)!"!"!!!"#$ (Eq 3)
Where MTotal(t) is the total mass (tonnes) of products of one type over time from, in this case,
1970 to 2020. i is the calendar year in which a product was purchased.
The probability density function w(t) (Eq 4), the first derivative of the cumulative distribution
function (Eq 1), was multiplied by M0 to estimate the annual mass flow of products of one type
that were accumulated in the use phase in each year entering the waste phase over subsequent
years (Eq 5)
𝑤 𝑡 = 𝑘𝑇 ∙𝑡−𝑡0𝑇
𝑘−1∙ 𝑒−
𝑡−𝑡0𝑇
𝑘
(Eq 4)
𝑚 𝑡 = 𝑀! ∙ 𝑤 𝑡 (Eq 5)
The total annual mass flow to waste management, m(t)(tonnes/y) was obtained in an analogous
manner as for the total mass in products in Eq 3 above.
𝑚!"#$% 𝑡 = 𝑚(𝑡, 𝑖)!"!"!!!"#$ (Eq 6)
S3.1.2 Time Dependent Stock of PBDE-‐containing Products
S 3.1.2.1 Electrical and Electronic Equipment or EEE EEE products included in this study and data required to estimate the stock of PBDEs are
summarized in Table S3.4. Sales data were used to estimate the total number of EEE entering
62
the use phase from 1980 to 2012 according to product category (U.S. EPA 2011). In the absence
of data from 1970 to 1979, the number of products entering the use phase was assumed to
increase exponentially. The number of products entering the use phase from 2013 onwards was
estimated as a continuation of the empirical rate of increase or decrease from 2005 or 2007 to
2010. EEE sales data were used in a Weibull distribution model with the shape parameter 3.5 for
CRT-TVs (Tasaki et al. 2004) and 2.4 for other EEEs (Oguchi et al. 2008). The lifespan of
products and their weight were taken from a U.S. EPA survey (U.S. EPA 2011). The stock of
PBDEs in EEE was estimated assuming that PBDEs were only used in exterior plastic parts of
the equipment since TBBPA or other reactive FRs were most likely used in interior parts of EEE
(e.g., motherboard, hard drive, battery) (Alaee et al. 2003, Muchongong et al. in prep.). We
noted that by including only the plastic casing of EEE, but not other components of computers
such as motherboards and fans of computers that were found to contain certain levels of PBDEs,
especially pentaBDE (Greenpeace 2006), we could be underestimating the use of PBDEs to
some extent. The percentage of products containing PBDEs was estimated based on the total
number of products with Br level higher than 2% (minimum level of intentional addition of
BFRs to exhibit fire retardancy behavior). More than 1000 in-use and waste products that was
suspected to be treated with FRs, such as electronics and furniture, were screened by means of
XRF (details of XRF screening method described in 2.2.3).
S3.1.2.2 Wires and Cables The annual usage of decaBDE used in wires and cables in the U.S. from 1990 to 2010 was
provided by Harriman (2012). Although wires and cables can be used in construction and
building materials with an average lifespan of 20 years (http://www.costmodelling.com), the
same lifespan as other EEE was assumed for their application. The temporal trend in the stock
63
was derived based on the annual use of decaBDE in this sector and a Weibull distribution with
the shape (k) and scale parameters (T) of 2.4 and 10, respectively.
Table S3.4: Electrical and electronic equipment (EEE) products and the concentration of PBDEs in these products used to estimate the total mass of PBDEs in the casing of EEE
Products
Lifespan ( y )1 Percentage of Products Treated with PBDEs (FFR)2
PBDEs [µg/g] 3
1970–1990
1990–2020 Penta Octa Deca
CRT-TV 14 11 86% 300 2,000 40,000 Flat-TV - 8 54% 40 200 7,000 CRT-Monitor 9 9 66% 170 1,300 100 Flat-Monitor 6 6 40% 150 1,500 100 Desktop computers
12.5 9.5 26% 80 1,500 100
Laptop 6 4 Same as Desktop computers
80 1,500 100
Hardcopy devices
9 8 40% 10 100 100
Wires and cables
10 10 NA Annual total consumption4
Data sources: 1U.S. EPA 2011 2Screering of more than 1000 products by means of XRF for the purpose of this study 3Muchongong et al. in prep.
4Harriman 2012
S3.1.2.3 Polyurethane Foam (PUF) in Furniture & Other Products The largest use of pentaBDE (90–95%) was for the treatment of flexible, slabstock PUF, most of which is
used in furniture such as couches and chairs. Some of the pre-consumer slabstock waste from furniture
production is recycled into carpet cushion. Other types of PUF that are used for moulded furniture
seating, bedding and packaging, were assumed not to be treated with PBDEs (Leudeka & Knudtson
2012). The stock of pentaBDE in slabstock PUF furniture products was estimated as
64
𝑀!"#$ = 𝑀!! ∙ 𝐹!" ∙ 𝐹!"#$ (Eq 8)
Where MPBDE (tonnes) is the total mass of PBDEs used in slabstock PUF in the furniture industry
MSS (tonnes) is the annual mass of PUF slabstock used in furniture industry, FFR is the annual
fraction of PUF slabstock treated with PBDEs, and FPBDE is the average PBDE fraction used in
PUF slabstock treated with PBDEs.
The annual mass of PUF slabstock manufactured for upholstered furniture and the approximate
percentage treated with PentaBDE from 1987 to 2004 is summarized in Table S3.5 (Luedeka &
Knudtson 2012). Since reliable data on the yearly production and use of pentaBDE prior to 1987
were not available, an exponential increase in the mass of PentaBDE used in slabstock foam in
furniture industry was assumed from 1975 to 1987.
Table S3.5: Total PUF slabstock production and the estimated percentage of PUF slabstock treated with pentaBDE from 1987 to 2004
Year Slab stock PUF Production (million pounds)
Slab stock PUF Production (MSlabstock) (tonnes)
% of Slabstock PUF Treated with PentaBDE (FRSslabstock with PBDEs)
1987 321.6 145,883.4 11 1988 326.1 147,924.7 11 1989 344.3 156,180.5 11 1990 342.7 155,454.8 11 1991 341.7 155,001.1 11 1992 340.2 154,320.7 11 1993 381.2 172,919.0 11 1994 415.6 188,523.5 11 1995 408.2 185,166.7 11 1996 402.2 182,445.0 11 1997 397.4 180,267.6 11 1998 405.1 183,760.5 12 1999 410.2 186,073.9 15 2000 419.3 190,201.9 18
65
Year Slab stock PUF Production (million pounds)
Slab stock PUF Production (MSlabstock) (tonnes)
% of Slabstock PUF Treated with PentaBDE (FRSslabstock with PBDEs)
2001 381.8 173,191.2 21 2002 396.7 179,950.1 24 2003 409.9 185,937.9 27 2004 442.2 200,589.7 30
Data source: Luedeka & Knudtson 2012
The concentration of FRs added to PUF slabstock to meet the fire safety requirements depends
on the PUF density. Lower density PUF required higher pentaBDE concentrations of ~ 6% by
weight and conversely higher density foam required a lower PentaBDE concentration of ~2.5%
by weight to meet California TB-117 code for residential foam furniture (Luedeka & Knudtson
2012). However, to meet more stringent flammability requirements for furniture in public
spaces, such as California TB-133, concentrations of up to 18% of pentaBDE were used in PUF
products (ESWI 2011).
The average percentage of pentaBDE used in PUF slabstock for TB-117 compliance estimated
by the Polyurethane Foam Association and used in this study was 4% of total PUF weight with a
range of 2.4–6%. This value agrees with Stapleton et al. (2012) who analyzed more than 100
samples of foam products. Mochungong et al. (in prep), who analyzed 20 samples, reported a
range of pentaBDE of 1.1–5%. Average concentrations of pentaBDE used in various PUF
furniture products were reported to have a larger range of 1% to 18% in the European
Commission Technical Report (ESWI 2011).
To estimate the stock of PBDEs in PUF slabstock furniture products in the use phase over time,
the annual PBDE usage in slabstock (MPBDE) was used in a Weibull distribution model with a k
value of 2.4 which is used for municipal solid waste (Tasaki et al. 2004). The lifespan of these
products was assumed to be 15 and 10 years prior to and following 1990, respectively
66
(www.apartmenttherapy.com, www.network54.com). These are single use life spans and thus do
not include second-hand furniture use.
S3.1.2.4 Plastic Pallets In the early 1990s, the Grocery Manufacturers Association (GMA) published specifications
aimed at bringing uniformity to the design of grocery pallets to ensure that pallets used for
shipping would meet fire safety standards (Pure Strategies Inc. 2010). As of 2010,
approximately three billion shipping pallets made of wood, plastic and metals were in use in the
U.S. Of the different types of pallets, 10% are made of plastic with an annual growth rate of
2.4% in the total number of plastic pallets (Pure Strategies Inc. 2010). The average weight of a
standard plastic pallet was reported to be ~22.6 kg with a maximum lifespan of 15 years (Pure
Strategies Inc. 2010). About 5–10% of plastic pallets were expected to be treated with decaBDE
to meet flammability requirements (Pure Strategies Inc. 2010). Since no data were available for
the concentration of decaBDE in plastic pallets, a conservative assumption of 0.1% (RoHS level)
in plastic material was applied to estimate the total stock of decaBDE in these products.
S3.1.2.5 Automotive Sector The automotive vehicles included in this study were cars and light trucks. The stock was
established based on the annual vehicle registration data for the United States from 1970 to 2010
(Davis 2001, U.S. DOT 2013). Based on the U.S. national household travel survey for 2009,
vehicles were categorized into five age groups to estimate the age distribution of registered
vehicles per year from 1970 to 2010 (U.S. DOT 2013). A constant rate of increase in the number
of registered cars from 2009 to 2012 was used for 2013 onwards to estimate the number of
vehicles in use and their assumed age distribution from 2013 to 2020. An average vehicle
weight of 1.8 tonnes was assumed for all makes from 1970 to 2020 (U.S. EPA 2010). Plastic
67
components were estimated to be approximately 9% of total mass of vehicles
(greenvehicledisposal.com), and within that 14% of the mass was assumed to be used in
dashboards as mixed polymers and 10% in seat foam (http://certipur.com). About 9% by mass
of the plastic components and 6% of total foam materials used in automotive sector in North
America were expected to be flame retarded with BFRs (Gearhart & Posselt 2009).
Fabrics used in vehicles were treated with decaBDE to meet the U.S. MVSS302 flammability
requirements that have been in place since the 1950s (Bullock 2012). This flammability
requirement was assumed to pertain to vehicles sold in Canada as well. The use of decaBDE in
vehicles began when leather and wool materials were being replaced with nylon fabrics in the
late 1950s and its use increased over time as polyester became the main fabric used in vehicles
by the 1970s (Bullock 2012). Fabrics comprise approximately 1% of the total weight of vehicle.
The average amount of fabric required in vehicles is about 8 yards (6.1 m2) per vehicle and each
yard can be treated with approximately 50 g of decaBDE (Bullock 2012).
Table S3.6 summarizes the percentage of automotive parts treated with BFRs and the average
concentrations of each PBDE mixture in foam and plastic components of vehicles (Gearhart
2012). Although carpets in vehicles made from polyester materials that required about the same
amount of decaBDE as seat covers to meet MVSS 302 requirements from 1980 onward, these
materials were not included in this study because of a lack of data. Since the Weibull
distribution was not used, we were unable to estimate the flow of PBDEs in vehicles to the waste
phase. Due to a lack of data, this study did not include heavy duty trucks, off-road vehicles,
trains, buses, and airplanes, where the latter are known to contain high levels of FRs (Allen et al.
2013).
68
Table S3.6. The percentage of foam, plastic and fabric treated with BFRs and the concentrations of PBDEs in each material used in the automotive sector in North America
Products FFR 1 PBDE [µg/g]2
Penta Octa Deca Foam 2–17% 750 70 6,400 Plastic components 6–9% 170 5 2,600 Fabric 25–50% 900 5 4,000 Data source: 1Gearhart & Posselt 2009 2Mouchangang et al. in prep.
S3.1.2.6 Textiles and Fabrics Textiles and fabrics treated with decaBDE included curtains in public spaces, military tents
and/or upholstery textiles (U.S. EPA, 2014). About 20–25% of total global decaBDE production
(approximately 300,000 tonnes) was applied to textiles from 1970s to 2013 (IllinoisEPA 2007).
As noted above, since annual sales data were not available for textiles and fabrics likely to be
treated with PBDEs, we based our stock estimates on the percentage of total annual decaBDE
used to treat textiles. Thus, we used a “bottom-up” approach (Muller et al. 2014). An average of
22% of the total annual decaBDE consumption was assumed to be a reasonable estimation of
decaBDE used for textiles and fabrics (U.S. EPA 2014).
S3.2. Results and Discussion
S3.2.1 Product Inventories The cumulative, dynamic stock of the mass of desktop computers was illustrated as an example
of the stock of products with a shape parameter of 2.4 (Figure S1a). The sharp increase in the
mass of desktop computers in the use phase from early 1990s to 2007 was associated with an
increase in market demand for these products. The mass of desktops in the use phase declined
69
after 2007 as lighter desktops, laptops and/or tablets, etc. replaced older and heavier desktops. In
other words, the market share of desktops dropped in favor of lighter devices.
The cumulative, dynamic stock of decaBDE in the plastic casings of desktop computers in the
use phase in the U.S. and Canada from 1970 to 2020 showed that decaBDE use in desktop
computers peaked in the use phase at ~100 tonnes in 2007 (Figure S1b). This peak corresponds
to the year when the mass of desktop computers in the use phase peaked. Due to the restriction
of decaBDE use, its incorporation in new desktops was assumed to be zero following 2013.
Thus, the mass of decaBDE in the use phase declined more rapidly than the mass of desktop
computers. By 2020, ~30% of the maximum decaBDE used in desktop computers in 2007 was
estimated to remain in the use phase. As mentioned above, these estimates reflect PBDEs mostly
used in the casings of desktop computers and do not include PBDEs that might have been added
to microprocessors and other components of EEE (Greenpeace 2006). The large stock of
decaBDE in the use phase in CRT TVs, emphasizes the much higher use of these chemicals in
CRT TVs compared to other EEE (Sindiku et al. in prep, Mochungong et al. in prep).
0
1
2
3
4
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of desktop
com
puters
(Mt)
a
70
Figure S3.1: Cumulative dynamic stock in the U.S. and Canada from 1970 to 2020 of (a) the mass of desktop computers in the use phase (million tonnes), (b) the mass of decaBDE in desktop computers in the use phase (tonnes), (c) annual mass flow of decaBDE in desktop computers leaving the use phase to enter the waste phase in the U.S. and Canada from 1970 to 2020 (tonnes/year).
The substantial mass flow of desktop computers to the waste phase started in the early 1980s,
almost 10 years after their first use (Figure 3.1c). Each color band corresponds to the temporal
trend in the mass of desktop computers entering the waste phase that was purchased in a given
year. The peak (or maximum thickness) of each color band corresponds to the year in which the
greatest mass of decaBDE in desktop computers purchased in any year entered the waste phase.
The sharp increase from late 1990s to 2014 reflects the increase in the use and discarding of
desktop computers that entered the use phase from early 1990s to 2007. The mass of desktops
0
20
40
60
80
100
120
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020 Stock of decaB
DE in desktop
compu
ter (t)
b
0
2
4
6
8
10
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020 Flow
of d
ecaB
DE in desktop
compu
ters to
waste phase (t/
y)
c
71
entering the waste phase starts to decline after 2014, seven years after the peak in the use phase.
The flow of decaBDE used in desktop computers to the waste phase will continue long after
2020.
The stock of pentaBDE in foam products is illustrated in Figure S3.2a. With only the first
lifespan of foam products considered, the stock of pentaBDE in PUF furniture in the use phase
peaked at ~ 12,000 tonnes in 2004. By 2020, almost all pentaBDE in these products will have
entered the waste management phase as the products reach the end of life stage. By doubling the
lifespan of products, the stock of pentaBDE in the use phase peaked at ~19,000 tonnes in 2004,
and by the end of 2020, almost 30% of the stock of pentaBDE in 2004 will remain in the use
phase (S2b).
0
4
8
12
16
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020 St
ock of pen
taBD
E in PUF
furnitu
re in th
e use ph
ase (kt)
a
72
Figure S3.2: The effects of changing lifespan on the stock of pentaBDE in PUF furniture, (a) one lifespan of products considered, (b) the first lifespan of products was doubled to consider the second use of products.
S3.2.2 Stock of Commercial Mixture of PBDEs The range in the total consumption of PBDEs in the U.S. and Canada with 95% confidence
interval is illustrated in Table S3.7. The ranges were obtained using a Monte Carlo analysis.
Table S3.7: The range of total mass of PBDEs (tonnes) used in various product types in the U.S. and Canada from 1970 to 2020 (95% Confidence Interval).
Products PentaBDE OctaBDE DecaBDE
Foam 5,000–50,000 - -
Electronics 500–1,500 1,000–10,000 25,000–225,000
Vehicles 2,500–25,000 3,000–35,000 25,000–225,000
Textiles - - 14,000–140,000
Plastic pallets - - 6,000–60,000
Total 8,000–76,500 4,000–45,000 70,000–650,000
0
4
8
12
16
20
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Stock of pen
taBD
E in PUF frinitu
re
in th
e use ph
ase (kt) b
73
S3.3 Uncertainties The large uncertainty was associated with the data and parameters values used in our model
which includes: (i) the number of products annually entering the use phase, (ii) the fraction of
polymers in each product, (iii) the percentage of products treated with PBDEs, (iv) the average
PBDE concentration in the polymer of the treated products as well as, (v) the shape parameter
and (vi) the scale parameter (lifespan) of the Weibull distribution. The number of products
entering the use phase was calculated according to the sales data or consumption patterns for
most products. Not all PBDE-containing products could be included in our study due to a lack of
data on the materials and substances used in products. The fraction of polymers and PBDEs,
respectively, in products were based on the measurements of limited number of samples. The
fractions of products treated with PBDEs were assumed based on the experimentally determined
percentage of products with Br levels higher than 0.1% (RoHS levels) as an indicator of PBDEs
in products (Mochungung et al. in prep.). Products with high Br levels (>0.1%) could have also
been treated with other brominated compounds. The concentrations of PBDEs in different
products were measured in a companion study based on a limited number of products
(nTotal=120). The shape parameter k in the Weibull distribution model was assumed the same as
values of k as derived by Oguchi et al. (2008) for products in Japan in 2003. The same value of k
was used for most EEE and wires and cables, however, in reality these numbers vary according
to product type (Oguchi et al. 2008). Another source of uncertainty was the lifespan (scale
parameters in the Weibull model) assumed for each product type. For instance, whereas we
assumed that wires and cables have the same 10-year lifespan as that of EEE, but in reality, those
used in construction would have a much longer lifespan. However, since wire and cables
constituted less than 1% of the estimated total decaBDE stock, this uncertainty was assumed to
have a negligible effect on the overall stock. The confidence factors used for each parameter
74
and the sensitivity of the model output to the variance in the parameters are summarized in Table
S3.8.
Table S3.8. Parameters varied in the Monte Carlo Analysis of the Weibull distribution estimates in the cumulative dynamic PBDE stock and the sensitivity of model to each parameter.
Parameter Confidence factor Sensitivity to Variance
Products entering the use phase 1.5 15% Fp Fraction of polymers in each product 1.5 9% FFR Fraction of products treated with PBDEs 1.5 12% Fraction of PBDE in each products 3 54% Shape parameter (k) 1.5 4% Scale parameter (lifespan) 1.5 6%
Products that were not included in this study despite knowledge that they contained PBDEs
(Scherrer 2012) were summarized previously in Table S3.3. Although previous studies have
measured PBDEs in foam products other than furniture made of slab foam, including baby
products (Stapleton et al. 2011), carpet cushion (Digangi et al. 2011) and mattress padding
(Blum 2013), these products were not included because of a lack of data on product numbers and
the percentage of products treated with PBDEs. Off-road vehicles and public transportation
including buses, trains, and airplanes that could account for substantial usage of PBDEs were
also neglected due to a lack of data. More importantly, PBDEs in construction materials that
contribute to about 25% of the total PBDE usage in North America (U.S. EPA 2014) were not
included in this study. We see this as a gap in our study since these products are subject to
particular flammability requirements.
As mentioned earlier, we considered only the first lifespan of products in this study. A longer
lifespan would lead to a concomitant delay in products reaching the waste phase.
75
Chapter 4: PBDEs in the waste stream; A case of e-‐waste
4.1 Introduction The rapid growth of the technological innovation and demand for internet and communication
technology (ICT) products has led to the exponential increase of electronic and electrical
equipment (EEE) production (Lundgren, 2012). The incompatibilities of new products with
older ones, the decreasing lifespan of products and the high cost of repair are factors accelerating
the global growth of end of life electronics (EoLE). EoLE refers to electronic products after
their first life span that could be reused and/or kept in storage before the disposal of these
products. In comparison, waste EEE (WEEE) and electronic waste (e-waste) are the most
commonly used terms to describe EoLE that are non-functional and not suitable for reuse and
have discarded or ready to be discarded. Generally, WEEE includes or refers to obsolete
appliances that use electricity such as large and small household appliances (HHA), while the
term e-waste is mainly used for waste ICT products and display devices (Robinson, 2009). E-
waste has become the fastest growing waste stream in the industrialized world with an estimated
~4–8% growth per year (Schluep et al., 2009; Widmer et al., 2005), three times higher than other
municipal waste stream (Arensman, 2000). Although e-waste comprises a small fraction of total
municipal waste in comparison to other durable waste (U.S. EPA, 2014), it is expected that
~70% of the metals in the waste stream originates from e-waste (McCormick, 2002).
The impacts of the rapid growth of ICT products on economic growth and societal change have
concealed the environmental consequences of manufacturing and disposal of these products
(Willams, 2011). E-waste contains a wide range of hazardous substances and metals such as
flame retardants, Be, Cd and Hg, and also valuable metals including Au, Ag and Ti (Robinson,
2009). To avoid environmental impacts and to facilitate effective recovery of valuable elements,
76
environmentally sound management (ESM) practices are necessary (Williams, 2011). High
labor costs and stringent environmental regulations in developed countries have led to the
externalization of the handling of these products in countries with low labor cost and lax human
rights and environmental regulations. This brought economic incentives for both developed and
developing countries to process globally generated e-waste in developing countries (Zhang et al.,
2012). In 2013, the revenue of e-waste trade was estimated to be ~1.5 billion dollars for the U.S.
(USICT, 2013). At the same time, the demand for metals and raw materials in developing
countries with growing manufacturing sector, such as China, created a substantial e-waste market
and job opportunities in these countries (Zhang et al., 2012). Despite socio-economic benefits of
e-waste trade, this trade is of concern mainly because of permanent environmental damages
where e-waste is being processed (Zhang et al., 2012). Inappropriate e-waste handling practices
including dumping in open landfills, open-burning and acid-recovery of metals is causing on
going health hazards from exposure to toxins in receiving countries (BAN, 2005; Babayemi et
al., 2014; Gullett et al., 2007; Osibanjo & Nnorom, 2007; Wu et al., 2015, Labunska et al., 2014;
Xu et al., 2015; Xu et al., 2013).
In response to worldwide concern regarding the global transboundary movement and disposal of
hazardous waste in countries with lack of adequate infrastructure to process e-waste, the Basel
Convention was introduced in 1989 and entered into force in 1992. The Convention aims at
minimizing the generation and the movement of hazardous waste and hazardous recyclable
materials among countries, and ensuring the disposal of these materials using ESM practices. As
of 2014, 180 states and the European Union were parties to the Convention. The U.S. is one of
the few countries that has signed but not ratified the Convention. Under the Basel Convention,
the hazardous characteristics of waste can be defined by provision of the national law of each
77
country. This has created a loophole in the Convention allowing licit global trade or
transboundary movement of e-waste, as these products may not be deemed hazardous waste and
rather can be traded under the guise of “functional used” products.
Due to global public outrage concerning evidence of unsafe e-waste handling in developing
countries, the Basel Ban Amendment was introduced in 1995 to prevent the transboundary
movement of hazardous waste for any purposes, including product reuse and recycling, from
OECD member states (mainly developed countries), the European Union and Liechtenstein to
non-OECD countries (mainly developing and countries in transition).7
Ironically, the transboundary movement of e-waste, in the form of international trade of used
electronic products and e-waste traffic, has dramatically increased since the introduction of the
Basel Convention and Basel Ban Amendment in 1995 (Lepawsky, 2014). In 2002, Basel Action
Network (BAN) and Silicon Valley Toxic Coalition (SVTC) reported that 50 to 80% of e-waste
collected for recycling in the U.S. is exported to developing countries or countries in transition
(BAN & SVTC, 2002). These estimates provoked considerable controversy. A decade later, the
U.S. International Trade Commission (USITC) reported in 2012 that up to 17% of e-waste
generated annually in the U.S. is exported (USICT, 2013). By using monetary values of
exported products to discriminate between the total amounts of used versus new products, Duan
et al. (2013, 2014) estimated that the mass flow of used computers and televisions (TVs) was
~8.5% of the collected EoLE in the U.S. in 2010. In comparison, Breivik et al. (2014) estimated
that 17%−34% of e-waste generated in OECD countries is exported to non-OECD countries.
7 The amendment has been ratified by 79 countries but has not entered into force because of insufficient signatories Ratification is required by 3/4 of the member states to the Convention; US and Canada did not ratify the amendment.
78
While these studies provide valuable estimates of the range of e-waste exported from developed
to developing countries, these values may in fact be underestimates of the actual flow because of
the extent of the misclassification of products by exporters and the export of large quantities of e-
waste with no economic value along with used but functional products to other countries
(Schmidt, 2006).
Underlying the uncertainty in estimates of e-waste export is the uncertainty in the mass of e-
waste generated, and obscurity in the management of e-waste in developed countries which
contribute the most to the global e-waste generation (Robinson, 2009). The objective of this
study was to estimate the amount of e-waste generation in the U.S. and Canada with the aim of
providing a qualitative framework to understand whether current e-waste management programs
in these countries are successful in dealing with the influx of e-waste. Common problems with
estimating e-waste generation are the lack of a common definition of what constitutes e-waste
and hence the inclusion of different products, lack of high quality data, and the use of different
accounting practices (Baldé et al., 2015). Therefore, we focused only on ICT products and
display devices, in part because of availability of reliable data, the rapid turnover rate of these
products and concerns regarding hazardous substances within these products which can be
recycled into new products including toys and kitchen utensils (Ionas et al., 2014; Samsonek &
Puype, 2013).
In the absence of reliable data, various approaches have been used to estimate the amount of e-
waste generation (Wang et al., 2013, Araújo et al., 2012; Chung, 2012; Yu et al., 2010 inter
alia). Wang et al. (2013) classified methods used for estimating e-waste generation into four
groups: disposal related analysis, time-series analysis, factor models and Input-Output analysis.
By comparing data quality and assumptions made for each method which reflect the accuracy,
79
reliability and completeness of the results of the model, they concluded that using a multivariate
approach and multiple resources can provide the most reliable time trend estimates of the
quantity of e-waste generation (Wang et al., 2013). These resources include historical data and
the distribution of in-use products based on the time-varying lifespan of products.
Using the same approach as Wang et al. (2013), a time-dependent estimate of the stock of in-use
ICT products and display devices in the U.S. and Canada from 1970 to 2020 was established in
this study. These analyses were extended to examine the disposition of ICT products and display
devices leaving the first use phase with options to enter the second use phase (reuse or storage),
or to enter the waste management phase. Three scenarios were developed based on the literature
and available data to obtain a range of the quantity of products at different use and waste stages
of the life cycle of ICT products and display devices.
4.2 Methods
4.2.1 Stock and flow of ICT Products Products included in this study were personal computers (PCs; desktops and laptops), display
devices (TVs and monitors), and hardcopy devices (Table S4.1). As described in chapter 3, sales
data from 1980 to 2010 for the U.S. (US EPA 2011) were used to estimate the number of
products entering the use phase. In the absence of sales data for Canada, per-capita sales data
from the U.S. were used. An exponential increase in the number of ICT products and display
devices was assumed from 1970 to 1979. The number of products entering the first use phase
from 2010 to 2020 was estimated as a continuation of the empirical rate of increase or decrease
from 2005 or 2007 (depending on available data) to 2010. The complementary cumulative
Weibull function (W(t)) was used to estimate the probability distribution of each type of product
80
remaining in the first use phase over time (Eq 4.1). The first derivative of Weibull distribution
(w(t)), (Eq 4.2) was used to estimate the probability distribution of products purchased in a given
year leaving the first use phase in subsequent years according to their specific lifespans (Tasaki
et al., 2004; Wang et al., 2013; Abbasi et al., 2015),
𝑊 𝑡 = 1− 𝑒!!!!!!
!
(Eq 4.1)
𝑤 𝑡 = !!∙ !!!!
!
!!!∙ 𝑒!
!!!!!
!
(Eq 4.2)
where t is the calendar year, adjusted by putting t in the middle of the year for each year; t0 is the
calendar year when products were purchased or entered the first use phase; T is the average
lifespan of a given product type (also known as the scale parameter) which was obtained from
U.S. EPA (2011) (Table S4.1); and k is the distribution or shape parameter that defines the shape
of the Weibull function. Values of k were 3.5 for CRT displays and 2.4 for other ICT products
and display devices (Oguchi et al., 2008; Tasaki et al., 2004).
4.2.2 After the first use phase
The disposition of ICT products and display devices leaving the first use phase was estimated
using a material flow analysis (MFA) (Figure 4.1). After the first use phase, a product either
enters the second use or waste phase. ICT products and display devices are designated as e-
waste once enter the waste phase. The second use phase consists of domestic reuse or storage
(stored in attics or basements before disposal). Waste management options include landfilling,
incineration and recovery. Recovered e-waste could undergo domestic recycling or dismantling.
81
E-waste export for the purpose of recycling, reuse or landfilling offshore could occur after
recovery or by diverting products destined for landfills.
In absence of reliable data on the disposition of ICT products and display devices after their first
use, three scenarios were developed to characterize the lower and upper boundaries of stocks and
flows of products in the second use and waste phases. Based on each scenario, transfer
coefficients (TCs) were assigned to quantify the fraction of products that move from one stage to
another in each scenario (Brunner and Rechberger 2004).
Scenario A was based on the assumptions of Matthews et al. (1997) of the historical sales of
PCs in the U.S and consumer behavior with regards to obsolete devices. Although this model
focuses only on PC’s sales data, it includes the reuse and storage parameters for used devices,
which reflects the delay entry of devices into waste stream. The values used for PCs in the U.S.
were assumed to pertain to Canada and to other ICT products and display devices. In this
scenario, the disposition of PCs at the end of first use was as follows: 45% reused, 45% stored,
5% recovered for recycling, and 5% landfilled. These percentages were used as static TCs to
estimate the disposition of the mass flow of products leaving the first use phase (Table 4.1). We
assumed that the lifespan of products in the reuse and storage phases followed the same
complimentary cumulative Weibull distribution as the first use phase with the same shape
parameter but the lifespan during the reuse (second use) was assumed to be half of the first
lifespan. The storage lifespan was considered to be the same as the initial lifespan (Sabbaghi et
al., 2015). For instance, laptops with the lifespan of 6 years would be reused for an average of 3
years or remain in storage for further average of 6 years. At the end of the second use phase,
50% of products were stored, again for the same time period as the reuse lifespan, 40%
recovered and the 10% landfilled (Matthews et al., 1997). Incineration was not considered in
82
this scenario. Finally, the TCs for recovery and landfilling of stored products were 75% and
25%, respectively (Matthews et al., 1997).
Figure 4.1: Material flow analysis of selected ICT products and display devices in the use and waste phases within the U.S. and Canada; use phase comprises the first and second use stages (reuse and/or storage). EoLE enter the waste phase where they can be disposed of in landfills, incinerated or recovered for the purpose of domestic or offshore recycling and reuse.
To discover the fate of residential and non-residential products, scenario B was developed based
on the survey analyses of the U.S. EPA (2008, 2011) and Babbitt et al. (2011) on the disposition
of electronic devices after the first use. Products were divided into residential and non-
residential categories (Table S4.2). In the absence of data for Canada, U.S. data were used. A
total of 70% of computers, monitors and hardcopy devices was expected to be used in non-
residential sectors (U.S. EPA 2011). Due to a lack of data, all CRT TVs were assumed to be
83
used as residential products and 25% of total flat screen TVs were assumed to be used in non-
residential sectors. Based on these assumptions, the total mass of non-residential products
(including TVs) was about 35% of the total ICT products and display devices. As with Scenario
A, the distribution of products remaining in and leaving the second use phase was estimated
using the complementary cumulative Weibull and the first derivative of the Weibull distribution,
respectively, with half the lifespan for reused products and the same lifespan for stored products
as for the first lifespan.
TCs for residential products were obtained from U.S. EPA (2008, 2011) and for non-residential
products from Babbitt et al. (2011). According to U.S. EPA (2008), ~50% of products are
stored and/or reused domestically after the first use. We assumed that 25% of residential
products included in this study were reused (TCU-RU) and another 25% were stored (TCU-S) at the
end of first use. These TCs were assumed to be constant from 1970 to 2020. The rate of EoLE
recovery increased from 20% in 2005 to 27% in 2010 with an annual rate of increase of 1–2%
(U.S. EPA 2011). We used the 2% annual rate of increase in recovery to assign TCU-R prior to
2005 and following 2010. Thus, TCU-R was at 0 prior to 1997 and increased to 0.44 in 2020.
Further, we assumed that as the TCU-R increased, the quantity of e-waste destined to landfills
would decrease. Consequently, TCU-L for landfilling was 0.5 from 1970 to 1995, and started to
decline in 1996, reaching 0.06 in 2020 (Figure S4.1).
At the end of second use stage, 10% of residential products were assumed to be stored (TCRU-S)
(U.S. EPA, 2011), and the remainder had the same time-varying TCs as those for recovery and
landfilling (TCRU-R and TCRU-L) as for products at the end of the first use phase. At the end of
storage, again, the same time-dependent TCs were assigned for recovery and landfilling (TCS-R
and TCS-L) as those for the end of the first use phase.
84
Babbitt et al. (2011) estimated the disposition of EoL institutional desktop computers and laptops
in 2008, from which we assigned TCs for all non-residential ICT products and display devices
for scenario B. According to Babbitt et al., an average of 25% of desktop computers and laptops
were reused domestically, 30% of products were recovered for recycling, 25% were sent
offshore for resale, ~15% could have been sent to metal dealers, and the fate of the remaining of
products was unknown. Since it was not clear whether metal recovery was occurring within or
outside of the U.S., we assumed that a total of 20% had an unknown fate (TCUn). The TCs for
the non-residential sector were assumed to be constant over time. Babbitt et al. (2011) did not
specify products going to landfills. Since products were assumed to be reused domestically in
the residential sector, the TCs for reuse to recovery and landfill (TCRU-R and TCRU-L) and storage
to recovery and landfill (TCS-R and TCS-L) were taken from the residential sector. In order to
establish a scenario based on the quantity of products that have been recovered (under registered
programs) from waste stream, scenario C was developed based on per-capita consumption
behavior and management of ICT products and display devices. The per-capita quantity of
products in storage was estimated based on Saphores et al. (2009). The annual recovery rates of
ICT devices and display devices were obtained from electronic product stewardship Canada
(EPSC) and e-cycle clearing house websites. We assumed that 25% of ICT products and display
devices were reused in the U.S. after the first use phase (U.S. EPA 2008). The same rate was
assumed for Canada. As with the other two scenarios, a lifespan of half of the first lifespan was
assumed for reusable products. Saphores et al. (2009) estimated that the quantity of e-waste
stored in U.S. households in 2007 was at least 470 million units. This number translated into
~15 kg/capita by assuming an average weight of 12 kg for small e-waste (U.S. EPA 2011) and
that ~60% of the total small household e-waste was comprised of TVs and ICT devices (U.S.
85
EPA, 2002). The TC for ICT products and display devices leaving the first use phase and
entering storage (TCU-S) was thus 0.15 which was assumed to be constant over time and to
pertain to the U.S. and Canada. The remainder of products entered the waste phase.
Limited data are available on the historical per-capita recovery rate of e-waste in the U.S. and
Canada. Depending on a state's legislation, the rate of e-waste recovery varies between 0 to 4
kg/capita (ecycleclearinghouse, n.d.). In Ontario, the recovery rate was 2.5 kg/capita in 2009 and
increased to 5.6 kg/capita in 2014 (EPSC, 2013). Recovery rates vary greatly amongst
provinces. To obtain an average recovery rate for the U.S. and Canada, we assumed that
recovery rate of ICT products and display devices increased from ~2.5 kg/capita in 2009 to 4.5
kg/capita in 2014. These numbers were translated to TCU-R of 0.18 and 0.28 in 2009 and 2014,
respectively. The same rate of increase from 2009 to 2014 was assumed prior to 2009 and
following 2014. Thus, TCU-R increased from 0 in 1999 to 0.4 in 2020 (Figure S4.2).
86
Table 4.1: Transfer coefficients (TCs) that quantify the fraction of the flow of ICT products and display devices leaving one process and entering another under three scenarios. Single values refer to static TCs whereas ranges represent time-variant TCs (Time-variant TCs are shown in Figure S1 and S2).
From To Symbol Scenario A Scenario B Scenario C Residential Non-residential Use Reuse TCU-RU 0.451 0.252 0.252 0.252 Use Storage TCU-S 0.451 0.252 -- 0.156 Use Recovery TCU-R 0.051 0–0.443* 0.35 0–0.47 Use Landfill TCU-L 0.051 0.06–0.54 -- 0.05–0.48 Use Incineration TCU-I -- -- -- 0.01–0.059 Use Offshore TCU-O -- -- 0.255 -- Use Unknown TCU-Un -- -- 0.25 -- Reuse Storage TCRU-S 0.51 0.12 0.12 0.156 Reuse Recovery TCRU-R 0.41 0–0.443 0–0.443 0–0.47 Reuse Landfill TCRU-L 0.11 0.06–0.54 0.06–0.54 0.05–0.48 Reuse Incineration TCRU-I -- -- -- 0.01–0.059
Storage Recovery TCS-R 0.751 0–0.443 0–0.443 0–0.47 Storage Landfill TCS-L 0.251 0.06–0.54 0.06–0.54 0.05–0.48 Storage Incineration TCS-I -- -- -- 0.01–0.059
U: Use, RU: Reuse, S: Storage, R: Recycle, L: Landfill, I: Incineration, O: Offshore, Un: Unknown 1: Matthews et al. (1997) 2: U.S EPA (2008) 3: U.S EPA (2011); * Recovery rate from 2005 to 2010 was obtained from U.S EPA (20011).
(Same increase rate from 2005 to 2010 was assumed for prior to 2005 and following 2010). 4: Obtained from subtraction of the sum of the annual TCs for other sectors in this Scenario 5: Babbitt et al. (2011) 6: Obtained from Saphores et al. (2009) 7: EPSC (2013), ecycleclearinghouse (n.d.); * Recovery rate from 2009 to 2012 was obtained from EPSC (20013) for Canada and from 2007 to 2012 was obtained from ecycleclearinghouse (n.d.) for the U.S. (Same increase rate was assumed for prior to starting date of recovering and following 2012). 8. Obtained from subtraction of the sum of the annual TCs for other sectors in this Scenario 9. U.S. EPA (2012), STATCAN (2012)
87
Incineration of durable solid waste is <5% in the U.S. and Canada (U.S. EPA 2012, STATCAN
2012). For this scenario we assumed that the TC for incineration (TCU-I) increased from 0.01 to
0.05 between 1970 and 2014. The TCs from reuse and storage phases to waste phases were
assigned the same TCs as those from the first use stage. The TCs for landfilling were obtained
by subtracting the total of the other TCs, and supported by evidence that 10 kg/capita of
consumer electronics entered landfills in 2014 in the U.S. (US EPA 2014).
4.2.3 Uncertainty Estimation of Input and Transition Coefficient Parameters
Uncertainties associated with the data and parameters used in this studies can be summarized as;
(i) the quantity of products entering the use phase annually, (ii) the quantity of products leaving
the first use phase and entering the second use or waste phase, (iii) transfer coefficients from one
sector to the other. The quantity of products entering the use phase was calculated according to
products’ sales data (U.S. EPA, 2011). The quantity of products leaving the use phase was
calculated based on Weibull distribution model using shape and scale parameters obtained from
Oguchi et al. (2008) and U.S. EPA (2011), respectively. The uncertainty of these parameters was
discussed in details in chapter 3. Transfer coefficients were defined based on available data and
previous studies to estimate the disposition of products after the first use. To estimate the
uncertainty of results of each scenario, a confidence factor (Cf) based on authors’ judgment was
assigned for each parameter assuming that all parameters are log-normally distributed with Cfs
representing the measure of relative variance. Cfs ranged from 1 to 3, with 1 representing the
most certain and 3 the most uncertain value. Where TCs were estimated based on reliable data,
the assigned Cf was closer to 1 (e.g. number of products entering the use phase). Where TCs
88
were estimated based on assumptions (e.g. scenario 1), the Cf was given a value closer to 3. TCs
with medium certainty level were given the value of 2 or 2.5 (with 2 being most certain than
2.5). Each Cf implies that 95% of all values in the distribution lie between 1/Cf and Cf times the
median, which defines the extent of deviation from median (MacLeod et al., 2002). The Cf used
for each parameter is summarized in Table 4.2.
Table 4.2: Assumed confidence factors (Cfs) for each parameter used in this study. Cfs range is between 1 and 3. The value of 1 represents parameters with the lowest uncertainty, 2 medium level of uncertainty and 3 the highest uncertainty. Parameters were ranked based on the quality of data used for each scenarios.
Parameter Scenario A Scenario B Scenario C Residential Non-residential Products entering the use phase 1.5 1.5 1.5 1.5 Products leaving the first use phase 2 2 2 2 TCU-RU 3 2.5 2.5 2.5 TCU-S 3 2.5 -- 2.5 TCU-R 3 2.2 2.5 2.5 TCU-L 3 3 -- 2.5 TCU-I -- -- -- 2.5 TCU-O -- -- 3 -- TCU-Un -- -- 3 -- TCRU-S 3 2.5 2.5 2.5 TCRU-R 3 2.5 2.5 2.5 TCRU-L 3 3 3 2.5 TCRU-I -- -- -- 2.5
TCS-R 3 2.5 2.5 2.5 TCS-L 3 3 3 2.5 TCS-I -- -- -- 2.5
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4.3 Results
4.3.1 Stock and Flow of ICT Products and Display Devices in the First Use Stage
The mass of PCs in their first use stage peaked at ~3.5 Mt in 2008 (Figure 4.2a). The decline
after 2008 reflected the substitution of these products with laptops and other lighter alternatives.
The widespread use of laptop computers started in the 1990s and increased until 2009 with a
peak of 0.4 Mt, after which the use of lighter laptops and other alternatives such as netbooks and
tablets increased. The peak in the mass of CRT monitors occurred in 2002 at ~4 Mt while the
mass of flat screen monitors and hardcopy devices continues to increase to 2020, assuming the
current consumption rate (Figure 4.2a). Among all ICT products and display devices considered
in this study, TVs contributed most to the total mass of in use products (Figure 4.2b). The use of
CRT TVs increased rapidly in the 1980s, followed by a slower increase in the 1990s with a peak
stock of ~7 Mt in the early 2000s. Assuming no additional new use of CRT TVs, it is expected
that by 2020, ~0.7 Mt of CRT TVs will still be in the first use phase (Figure 4.2b). The use of
flat screen TVs started in the late 1990s and continues to grow exponentially (Figure 4.2b).
Based on recent trends, the total mass of ICT products and display devices in the first use stage
will continue to rise exponentially after 2014, mainly due to the rapid increase in consumption of
flat screen display devices.
The annual mass flow of laptops, PCs and CRT monitors leaving the first use phase peaked at
0.1, 0.3 and 0.5 Mt per year in 2013, 2012 and 2006, respectively (Figure 4.3a). By 2020, most
CRT monitors will be expected to have left the first use phase while the flow of PCs and laptops
leaving the first use phase will continue to decline at average annual rates of 5 and 10%,
respectively. Assuming no significant changes in the consumption of flat screen monitors and
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hardcopy devices, the flow of these products from the first use phase will continue to grow to
2020 at an annual rate of 5 and 1%, respectively.
Figure 4.2: Time trend of the mass of in-use ICT products and display devices in million tonnes (Mt) in the U.S. and Canada from 1970 to 2020, (a) PCs, laptops, CRT monitors, flat screen monitors and hardcopy devices in the first use phase, and (b) CRT TVs, flat screen TVs and the total of all products considered in this study.
0
1
2
3
4
5
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Mass o
f produ
cts in the
use phase (M
t)
PC
Laptop
CRT Monitor
Flat Monitor
Hardcopy Devices
0
20
40
60
80
100
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Mass o
f produ
ts in th
e use phase (M
t)
CRT TV
Flat TV
Total EEE
a
b
91
For those CRT TVs that entered the first use phase in the early 1970s, their annual flow to the
second use phase and/or waste phase started in late 1970s, almost one decade after their first use
(Figure 4.3b). The annual flow of CRT TVs leaving the first use phase increased substantially
until the peak at ~0.7 Mt in 2004, and declined at an average rate of 4 and 25% before and after
2014, respectively. The annual flow of flat screen TVs leaving the first use phase started in 2004
and will continue to increase exponentially to 2020. Overall, the annual flow of ICT products
and display devices leaving the first use phase increased at an average annual rate of 8−12% in
the 1990s, 5−10% from 2000 to 2015, and will increase at 15−25% from 2015 to 2020.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Mass fl
ow of E
EE leaving the
first u
se phase (M
t/ year) PC
Laptop
CRT Monitor
Flat Monitor
Hardcopy Devices
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Figure 4.3: Time trend of the annual mass flow of ICT products and display devices leaving the first use phase in the U.S. and Canada from 1970 to 2020, (a) PCs, laptops, CRT and flat monitors and hardcopy devices, and (b) CRT TVs, flat screen TVs and total ICT products and display devices.
4.3.2 Stock and Flow of ICT Products and Display Devices in the Second Use Phase and Waste Phase Under Different Scenarios
A total amount of ~60 Mt of ICT products and display devices considered in this study was
estimated to enter the use phase in the U.S. and Canada from 1970 to 2014. The stock of
products in the first use phase was ~25 Mt in 2014. About 35 Mt of products left the first use
phase between 1970 and 2014. A range of estimates based on available data and studies was
obtained for the disposition of products leaving the first use phase. Although all scenarios used
in this study bear considerable uncertainty, we expect that the estimated ranges of the disposition
of waste ICT products and display devices provide valuable information on historical and current
management of these products in the waste phase.
0
1
2
3
4
5
6
7
8
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Mass fl
ow of E
EE leaving the
first use phase (M
t/ year)
CRT TV
Flat TV
Total EEE
93
The results from the three scenarios are summarized in Table 4.3. The estimated range
represents 95% confidence interval of the quantity of products at each stage. In scenario A, of
the 35 (95% confidence interval or CI: 23˗52) Mt of products that have left the first use phase
since 1970, in 2014, ~4 (1.3˗12) and 20 (6˗60) Mt remained in reuse and storage phases,
respectively (Table 4.3, Figure S4.3). Of the remaining 11 (7˗16.5) Mt that entered the waste
phase since 1970, ~8 (2.5˗24) and 3 (1˗9) Mt were recovered (mainly for the purpose of
recycling) and landfilled, respectively. Although this scenario had the highest rate of recovery
among different scenarios, our results suggest that only ~13% of products entering the use phase
or ~20% of products that left the first use stage have been recovered and 5% of the total products
were landfilled, while 30% of products entering the use phase have remained in storage. Note
that this model did not include estimates for incineration and export of EoL ICT products and
display devices to other countries. As such it is suspected that the estimated amount of products
estimated to be recovered in this scenario could include products that have been sent offshore.
Matthews et al. (1997), upon which scenario A is based, estimated that by 2005, a total of ~12
Mt of computers would be sold in the U.S., according to sales data of computers in 1990s and the
assumption of a 15% growth rate. Their results suggested that 20% of total computers sold in the
U.S. would be recycled in the U.S., 8% were would be disposed of in landfills, and the remainder
would remain in use or storage by 2005. It should be noted that no data were available to
validate the assumptions made by Matthews et al. (1997) at the time of their study. Therefore,
their results may not be a realistic representation of the current state of e-waste disposition.
Based on the assumptions of Matthews et al., we estimated that ~10 Mt of desktop computers
entered the use phase by 2005, which under this scenario 80% remained in the use phase (first
and second use), ~15% were recycled and 5% were landfilled. Note that the longer lifespans of
94
products in the first and second use stages and longer storage time that were assumed in our
study could have contributed to the larger quantity of desktop computers in the second use phase
in comparison with those of Matthews et al. (1997).
The results of Scenario B suggested that in 2014, the stock of ICT products and display devices
in the first use stage was ~16 (10˗24) and 9 (6˗13) Mt in the residential and non-residential
sectors, respectively (Figure S4.4). A total of ~22 (15˗33) and 13 (8˗20) Mt of residential and
non-residential products, respectively, have left the first use stage from 1970 to 2014. In 2014,
~4 (1.6˗10) Mt of all products were reused and ~5 (2˗12.5) Mt stored. From 1970 to 2014, ~4.5
(2˗10) Mt was recovered and ~15.5 (5˗45) Mt discarded in landfills within the U.S. and Canada.
The recovery for both sectors was assumed to begin in 1997 and increase linearly over time. In
addition, ~4 (1.2˗12) Mt of non-residential products were estimated to be exported with another
~2 (0.6˗6) Mt having an unknown fate. Given that the results of non-residential sector were
obtained based on one educational institute in the U.S. (Babbitt et al., 2011), these results may
not reflect current disposition of all non-residential electronic waste as these products are likely
managed by private entities (Kahhat and Williams, 2010).
The export of residential ICT products and display devices could not be quantified under this
scenario since reliable data were not available. However, as mentioned above, it has been
reported that up to 70% of products recovered for domestic recycling in the U.S. could have been
exported to other countries (U.S. EPA 2008, BAN 2005). In addition, a large quantity of e-waste
could be diverted from products destined to landfills by unregulated private entities to be reused
or refurbished domestically or offshore (WDO 2014). Therefore, the amount of e-waste
estimated for recovery may not necessarily represent products that have been recycled
domestically and the estimated value for landfills in this scenario could be an overestimation.
95
The results of scenario C suggested that of the 35 (23˗52) Mt of ICT products and display
devices that have left the first use stage since 1970, ~3 (1.2˗7.5) and 5 (2.5˗10) Mt remained in
reuse and storage, respectively, in 2014 (Figure S4.5). Of the 27 (18˗40) Mt of products that
have entered the waste phase since 1970, ~20.5 (10˗40) entered landfills, ~1.5 (0.7˗3) Mt was
incinerated and 5 (2.5˗10) Mt was recovered. The estimated quantity of recovered products in
this scenario was based on the reported recovery rate by registered recycling programs in the
U.S. and Canada. Since the recovery rate varies substantially across different jurisdictions in the
U.S. and Canada, it is possible that the recovery rate assumed under this scenario provides an
overestimation of the actual recovery rate of waste ICT products and display devices for the
purpose of recycling. We suspect that the estimated amount of products destined for landfills is
highly uncertain and may include products diverted for offshore reuse or recycling, which are not
included in this scenario.
Based on our analysis, ~25 Mt or 40% of the total mass of ICT products that entered the use
phase (60 Mt) from 1970 to 2014 remained in the first use in 2014, with 5 to 10 % of the stock of
products leaving the use phase annually. Consequently, a total of 35 Mt of e-waste has entered
the second use and waste phases by 2014. Under all scenarios, 5−7% of the total mass of ICT
products and display devices that entered the first use phase since 1970 was reused within the
U.S. and Canada by 2014. Depending on the scenario, 5 to 20 Mt (8−30% of the 60 Mt) could
be in storage. The wide range estimated here is consistent with the results of Sabbaghi et al.
(2015) who found that consumer behavior over the past decade regarding the storage and
disposal of electronic products varied widely depending on the nature of these products.
96
Table 4.3: Disposition of ICT products and display devices at different stages of the product life cycle under three scenarios from 1970 to 2014 in million tonnes (Mt). Lower and upper boundaries represent the range of 95% confidence interval.
Scenario A1 Scenario B2 Scenario C3
Median Lower boundary
Upper boundary Median Lower
boundary Upper boundary Median Lower
boundary Upper boundary
Use
Phase
First use In-use 25 16 38 25 16 38 25 16 38
Second
use
Re-use 4 1.3 12 4 1.6 10 3 1.2 7.5
Storage 20 6 60 5 2 12.5 5 2.5 10
Waste
Phase
Landfill* 3 1 9 15.5 5 45 20.5 10 40
Incineration ˗ ˗ ˗ ˗ ˗ ˗ 1.5 0.7 3
Recovery*ӿ 8 2.5 24 4.5 2 10 5 2.5 10
Export ˗ ˗ ˗ 4 1.3 12 ˗ ˗ ˗
Unknown ˗ ˗ ˗ 2 0.6 6 ˗ ˗ ˗
Total 60 27 145 60 28 133 60 33 110
*The estimated numbers include the portion of products that could be destined for export ӿ Recovery rate assumed to represent recycling rate 1 Matthew et al. (1997) 2 U.S. EPA (2008, 2011) and Babbitt et al. (2011) 3 Scenario C (per-capita data)
The total amount of ICT products and display devices recovered from the waste phase ranged
from 5 to 8 Mt or 6−13% of the total ICT products that entered the use phase from 1970 to 2014.
Scenario A had the highest percentage of total recovery (Matthews et al. 1997), which translated
into 22% of the products that have left the first use stage since 1970. For scenarios B and C
which assumed that recovery started in the late 1990s and increased up to ~30% in 2014,
recovery from the waste stream was estimated to be ~15% of products that left the first use phase
from 1970 to 2014. Given that more than 35% of products that left the first use phase were CRT
TVs from 1990 to early 2000, we estimated that ~4.5 (1.75−7) Mt of CRT TVs remained in
97
storage in 2014. This estimate is ~30% lower than that of U.S. EPA (2011) of ~ 6.2 Mt of CRT
displays that remained to be disposed of in the U.S. in the next 10 years.
The greatest range in estimates based on the three scenarios was projected for waste products
destined for landfills; 3 to 20.5 Mt or 5 to 35% of products that entered the use phase from 1970
to 2014. The U.S. EPA (2014) reported that approximately 2 Mt of selected consumer electronic
waste8 entered the U.S. landfills in 2000 and that this amount increased by 60% to 3.2 Mt in
2010, and then remained almost constant from 2010 to 2012. These numbers were translated
into the total of ~40 Mt of selected consumer electronic products disposed of in landfills since
2000. The lower quantity of products destined for landfills estimated here in comparison with
that reported by U.S. EPA (2014) could be a result of inclusion of fewer product types in our
study. Despite the rapid increase in the generation of e-waste, no significant increase was
observed for the amount of e-waste that entered U.S. landfills from 2010 to 2012 (US EPA
2014), which could be the outcome of bans and restrictions on disposal of e-waste in landfills in
some U.S. states since 2010 (ecycleclearinghouse, n.d.).
Kahhat and Williams (2012) estimated that 17–21% of waste computers generated in the U.S. in
2010 were disposed of in landfills. Under different scenarios, we estimated that a range of
10−60% of ICT products and display devices that were generated since 1970 could have been
disposed of in landfills. The greater range of landfilling estimated in our study could reflect the
historical disposition of e-waste and also the inclusion of more products in our study than Kahhat
and Williams (2012), for which the disposal pathways may differ from computers. As
mentioned earlier, a large quantity of electronic products destined for landfills could be diverted
8 It is not clear what kind of electronic products were included in this report. Based on the classification of electronics we assumed that selected consumer electronics contain ICT and display devices.
98
by private entities and then sold for re-use or material recovery (WDO 2014). Although this
practice is known to occur, data on the amount of waste products diverted from landfills has not
been collected or at least is not publicly available. Therefore, the estimation of products
remaining in landfills or diverted by private entities is highly speculative.
The quantity of products exported to other countries was estimated only in scenario B for non-
residential products. The amount of exported products was ~4 Mt, which is about ~20% of non-
residential products that entered the waste phase since 1970. This is likely an underestimation of
total products exported as the exports from residential sector were not included under this
scenario. When incorporating the estimate from U.S. EPA (2008) and BAN (2005) of 70% of
recovered products that could be sent offshore, the estimated value could increase up to ~8.5 Mt
or ~30% of products that have entered the waste phase since 1970. Kahhat and Willams (2012)
estimated that 2–12 million units of used computers have been exported from U.S. to other
countries in 2010 (this translates to 0.02−0.12 Mt assuming an average weight of 10 kg per
computer). We estimated that ~0.03 Mt of computers was subject to export in 2010. Thus, our
estimate is closer to the lower end of the estimated range by Kahhat and Williams (2012).
Breivik et al. (2014) estimated that 17–34% of the total e-waste generated in developed countries
can be exported to developing countries. While documented evidence indicates that export
occurs (BAN 2005, ChinaDaily 2014), quantifying this export remains difficult, as data are not
available to validate these estimates.
Based on our analysis, ~9 kg/capita of ICT products and display devices have left the first use
phase in the U.S. and Canada in 2014. Considering that an average of 40% (20–60%) of
products leaving the first use phase remains in the second use phase (reuse or storage), the waste
generation of these products was estimated to be 5.4 (3.6–7.2) kg/capita in 2014. The estimated
99
amount of waste generation of ICT products and display devices in this study is in good
agreement with estimates of Baldé et al. (2015) and Duan et al. (2013) who used the same
approach of lifespan distribution to estimate the mass of e-waste generation globally and for the
U.S., respectively (Table 4.4). Using a mass balance model, Kahhat and Williams (2012)
estimated that ~0.4 Mt of waste computers have been generated in the U.S., which translates to
~1.2 kg/capita. We estimated that of the ~0.45 Mt of computers that left the first use phase in
2010, 0.6−1.1 kg/capita of computers have entered the waste phase, depending on different
scenarios.
We estimated that ~19 kg/capita of ICT products and display devices would leave the first use
phase in 2020, of which 40% will remain in the second use phase. Thus, ~12 kg/capita of waste
ICT products and display devices is estimated to enter the waste phase in 2020. If the recovery
rate increases at the current annual rate of 2–5%, in 2020 up to 7.5 kg/capita of these products
will be recovered from the waste stream. Considering further bans and restrictions on the
disposal of electronics would prevent the disposal of e-waste in landfills, the current e-waste
recovery rate must increase by 50% to contend with the amount of e-waste that will enter the
waste phase in the next five years. The wide range of quantity of e-waste at each stage of waste
management estimated in this study, reflects the obscurity in the management of e-waste in the
U.S. and Canada, which equally presents an opportunity and a challenge. An opportunity for
providing more effective recycling programs within and outside of the U.S. and Canada to better
reuse and recover valuable materials and also create job opportunities. A challenge for
regulators to curb entities looking to exploit policy loopholes in e-waste management system.
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Table 4.4: Comparison of annual per capita e-waste generation estimated in this study and reported in the literature.
Products included
Year Estimated for
E-waste generation/ year
Kg/capita Source Comments on data
ICT and display devices
2014 U.S. and Canada
~1.8 Mt ~5.4 This study
ICT and display devices
2014 U.S. and Canada
~1.6 Mt ~4.5 Baldé et al. 2015 ICT and display devices were assumed to make up to 23% of total e-waste based on available numbers in this study
ICT and display devices
2010 U.S. 1.6 Mt ~5 Duan et al. 2013 Unit of products was converted to mass of products based on weight of each product (USEPA 2011)
Personal computers
2014 U.S. and Canada
0.33 Mt ~1 This study
Personal computers
2010 U.S. 0.4 Mt ~1.2 Kahhat and Williams 2012
Weight of PC was assumed 10 kg
E-waste 2005 U.S. and Canada
8 Mt ~27 Breivik et al. 2014
4.4 Concluding Considerations
Our estimates suggest that the current waste management system will be challenged to deal with
the quantity of e-waste that is being generated and that will be discarded in future. Based on our
analysis, the estimate of ICT products and display devices leaving the use phase was ~9
kg/capita in the U.S. and Canada in 2014. An average of 3.6 (1.8–5.4) kg/capita may have
remained in the second use stages (storage and domestic reuse) with the remainder entering the
waste phase. Although the current programs have been successful in recovering e-waste from
the waste stream for certain product types in some U.S. states and Canadian provinces, our
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results suggest that these programs will be stressed to deal with influx of e-waste in coming
years. In jurisdictions with e-waste laws and programs in place, the rate of e-waste recovery has
increased by ~5% per year since 2006 (EPSC 2013, PSI 2014), while the flow of EoLE is
estimated to increase by 15−25% following 2014. Moreover, a large quantity of e-waste (8–24
Mt), mainly CRT TVs which has been stored in the U.S. and Canada over years, is expected to
enter the waste phase in the near future.
Due to a lack of federal mandates in the U.S. and Canada, reliable data have not been gathered to
evaluate e-waste recovering programs, and therefore, estimates on the reuse, storage and export
of used electronic devices are highly uncertain. A lack of federal regulation has also resulted in
an increasing number of unregulated private businesses that profit from improper handling of
these products. Thus, to confront the growing problem of e-waste, federal mandates are critical
to promote the recovery of e-waste from the waste stream, to prevent exploitation of policy
loopholes by unregulated stakeholders, and to encourage individual extended producer
responsibility (EPR). The current collective EPR program in the U.S. and Canada has led to a
reinforcing feedback loop by which the true cost and technical challenges of e-waste recovery
are not reflected back to the original producers. This, in turn, diminishes the incentive for
innovation and redesign of greener products.
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Supporting Information
Table S4.1. The lifespan of ICT products and display devices included in this study before and
after 1990.
Products
Lifespan ( y )1
1970–
1990
1990–
2020
CRT-TVs 14 11
Flat-TVs - 8
CRT-Monitors 9 9
Flat-Monitors 6 6
Desktop
computers
12.5 9.5
Laptops 6 4
Hardcopy
devices
9 8
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S4.1. Material Flow Analysis after First Life Stage
Table S4.2: Estimated split between residential and non-residential sectors of ICT products and display devices sold in U.S. from 1970 to 2010 (US EPA, 2011). The same percentage as 1990 to 2010 was used for 2010 to 2020.
Product Type Time Period Non-residential Share Residential Share
Desktop CPUs1 1970-1990 70% 30%
1990-2010 65% 35%
Laptops1 1970-1990 100% -
1990-2010 50% 50%
Hard-copy
devices1
1970-1990 90% 10%
1990-2010 65% 35%
CRT monitors1 1970-2010 65% 35%
Flat screen
monitors1
1970-1990 65% 35%
1990-2020 65% 35%
CRT TVs2 1970-1990 - 100%
1990-2010 - 100%
Flat screen
TVs2
1970-1990 - 100%
1990-2010 25% 75%
Data source: 1US EPA 2011, 2Assumed in this study.
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Figure S4.1: Annual transfer coefficients under scenario B for residential products: a) TCs of ICT products and display devices at the end of first use, b) TCs of residential ICT products at the end of second use, c) TCs of residential ICT products at the end of storage.
U: Use (first use), RU: Reuse (second use), S: Storage, R: Recover, L: Landfill
* TCs of non-residential sectors were assumed constant
0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
U-‐L
U-‐R
U-‐S
U-‐RU 0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
RU-‐L
RU-‐R
RU-‐S
0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
S-‐L
S-‐R
a b
c
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Figure S4.2: Annual transfer coefficients under scenario C: a) TCs of products at the end of first use, b) TCs of products at the end of second use, c) TCs of products at the end of storage.
U: Use (first life), RU: Reuse (second life), S: Storage, R: Recycle, L: Landfill, I: Incineration
0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
U-‐I
U-‐L
U-‐R
U-‐S
U-‐RU 0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
RU-‐L
RU-‐I
RU-‐R
RU-‐S
0%
20%
40%
60%
80%
100%
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
S-‐L
S-‐I
S-‐R
a
c
b
106
Figure S4.3: Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario A (Matthews et al. 1997). The stocks (oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another.
107
Figure S4.4: Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario B (US EPA 2007, 2011; Babbitt et al. 2011). The stocks (oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another.
108
Figure S4.5 Stock and flow of ICT products and display devices from use phase to waste phase in the U.S. and Canada from 1970 to 2014 under Scenario C (based on per capita data from various sources). The stocks (oval shape) represent the stock of products at different stages of the model in 2014. The flows (arrows) represent the total flow of products from 1970 to 2014 from one stage to another.
109
Chapter 5: Conclusion
5.1. Major implications of this research This thesis contributes to the overall goal of better understanding of the fate of brominated flame
retardants (BFRs) during the use and disposal of BFR-containing products, focusing on ICT
products and display devices. Given that FRs are added to products at various and unknown
concentrations, and the migration pathway of BFRs from products does not occur in a
predictable fashion according to physico-chemical properties of each chemical, identifying the
main sources of each chemical has been challenging. With the proliferation of “new” FRs and
growing usage of BFRs in a wide range of consumer products following restrictions on the usage
of PBDEs, identifying the sources and characterizing the release mechanisms of these chemicals
from products are critical for devising a long term chemical management plan to reduce human
and ecosystem exposures.
The first goal of my doctoral research (Chapter 2) was to identify the product sources of BFRs in
indoor environments. To address this goal, I developed a product wipe testing technique to
identify BFRs at the surface of products with plastic casings. The quality and quantity of BFRs
in product wipes were believed to be associated with the actual concentrations of these chemicals
in products. The presence of BFRs in house dust collected at each site confirms their migration
from products. The correlation obtained between the concentrations of BFRs in product wipes
and dust suggested that the higher concentrations of these chemicals in products could lead to
their higher concentrations in indoor dust. However, this correlation was not related to the
volatility of BFRs and thus suggested a mechanism of release other than that strictly related to
volatilization.
110
Another important finding of this study was that BFR concentrations in most products found to
contain Br were not at a sufficient level to delay the spread of fire (with the caveat that
organophosphate flame retardants were not considered here). This finding raises the questions of
whether BFRs are used in insufficient quantities in some consumer products to reduce
flammability or whether the presence of BFRs in products could be due to unintentional
manufacturing from recycling of BFR-containing polymers. The results also suggested that even
at the low concentrations, BFRs can migrate from products and partition into dust which could
then be a source of human exposure. Furthermore, the ability of alcohol wipes to remove BFRs
from the surface of polymer materials suggested that the direct transfer of chemicals from
products to skin could occur while handling of these products.
Moving from indoor to outdoor environments, the total amount of in-use BFRs is an indicator of
the environmental concentrations of these chemicals. As such the temporal trend in the mass of
in-use BFRs as a result of consumption of BFR-containing products can be used as a proxy to
anticipate the future trend in environmental concentrations of BFRs. My second goal (Chapter
3) was to estimate the stock of FRs in products based on the consumption patterns of associated
products over time. PBDE-containing products were used as a case study for establishing a time-
dependent stock of FRs in products. In this study, a total mass of 450,000 t of PBDEs was
estimated to have entered the use phase since 1970. The peak in the stock of PBDEs occurred at
160,000 t in 2005 when the largest number of associated products was in use. Assuming only
the first lifespan of products, and no new use of penta- and octaBDE following 2004 and
decaBDE following 2013, the total stock of PBDEs was estimated to be ~120,000 t (~95%
decaBDE) in 2014. This stock will start to decline annually at the rate of 5 to 15% as products
reach the EoL stage and leave the use phase. The similar rate of decline estimated in this study
111
as that estimated for the decline of PBDE outdoor concentrations suggests that PBDE controls
and restrictions have been effective in reducing environmental levels of PBDEs.
Based on the stock of PBDEs, the per capita consumption of penta-, octa- and decaBDE in the
U.S. and Canada was estimated to be up to 10 times higher than those values estimated for
Switzerland and Europe. The higher consumption of PBDEs in the U.S. and Canada is
consistent with relatively high concentrations of these chemicals in household dust and human
tissues in these countries which, in turn, is a result of the specific requirements of the
flammability codes in the U.S. and Canada. What we have learned from previous studies is that
the adverse impacts of exposure to chemicals are likely to be realized long after their extensive
use in consumer products, when their elimination from in-use products would be impossible.
Therefore, the consequences of flammability standards must be evaluated before introducing new
chemicals as FRs to the global market.
Moving from the use to the waste phase, EoL PBDE-containing products continue to act as a
source of these chemicals, unless they undergo environmentally sound management (ESM)
practices in the waste phase. To develop best practices and to ensure ESM of waste PBDE-
containing products, the quantity of PBDEs leaving the use phase and entering different stages of
waste phase must be estimated. Thus, my third goal (Chapter 4) was to estimate the mass of
PBDE-containing products leaving the use phase, and the fate of these products at different
stages of waste phase. From all PBDE-containing products, internet and communication
technology (ICT) products and display devices were selected, in part, because of the fast growing
market demand for new products, and growing concerns regarding the mismanagement of these
products in the waste phase within and outside of the U.S. and Canada.
112
The results of this study suggested that ~40% of the total mass of products (60 Mt) that entered
the use phase form 1970 to 2014 is still in the first use phase in 2014 and a total of 35 Mt of
waste ICT products and display devices has entered the second life and waste phases by 2014.
Of the 60 Mt, 5 to 20 Mt (8−30%) were in storage while a total of 3 to 20 Mt (5−30%) were
destined for landfills from 1970 to 2014. Since 2000, a total of 6-13% of the total products that
entered the use phase since 1970 was recovered from waste stream.
In this study, the per capita e-waste (ICT and display devices) generation was estimated to
increase from 9 kg/capita in 2014 to 19 kg/capita in 2020. If the recovery rate increases at the
current annual increase rate of 2−5%, by 2020 up to 7 kg/capita of these products will be
recovered from the waste stream. Considering bans and restrictions regarding the disposal of
electronic products that would prevent the disposal of e-waste in landfills, the current e-waste
recovery rate must increase by 50% to deal with the amount of e-waste estimated to enter the
waste phase in the next five years. Moreover, the large quantity of products that have been
stored since 1970 will leave the use phase by 2020. Thus, the e-waste management programs are
expected to be challenged to deal with influx of e-waste in the near future.
My doctoral research provided an overall picture of the flow of FRs from the use to the waste
phase. FRs are added to consumer products as a result of flammability requirements that are
developed mainly in developed countries. With global market demand for products that contain
FRs, these chemicals have been widely distributed around the world. Almost 25 years after the
first use of PBDEs in 1970s, the human and ecosystem exposures to these chemicals became of
concern. Growing evidence of risks associated with exposure to PBDEs resulted in the
discontinuation of their use in new consumer products in developed countries. As difficult as it
was for global environmental and health organizations to achieve these results, the successful
113
outcome of phasing out of PBDEs was ironically diminished by the replacement of NFRs of
which their environmental persistence and toxicological effects have yet to be established.
This doctoral thesis asserts that unless effective chemical management plans are put in place, the
existing stock of PBDEs and their alternatives will continue to contribute to human and
ecosystem exposure as long as associated products are in use. Considering that the elimination
of the stock of BFRs in products that are widely distributed is impossible, more effective
regulations are required preemptively to ensure that the risk imposed by “new” BFRs used in
consumer products is minimized.
5.2 Recommendations for future work
Moving forward, this thesis has raised several questions that need to be addressed for
improving our understanding regarding, in particular, the fate of FRs in products and chemical
management in general.
Ø This study linked BFRs present in our indoor environments to the specific sources of
these substances. Measuring BFRs and other FRs of concern in products requires
destructive testing methods. These methods are usually costly and time consuming.
With increasing use of PBDE alternatives in products and potentially a need for
increasing restrictions on the use of these substances, developing a qualitative method to
rapidly indentify them would be beneficial. The product wipe testing method,
developed in this study, has been a useful technique to identify whether BFRs are
present in consumer products. However, this technique requires more detailed
114
investigation to minimize the potential source of errors and to ensure that it provides
reliable results.
Ø As EoL PBDE-containing products can be recycled into new products, such as
children’s toys and kitchen utensils, these products will continue to act as a source of
PBDEs. Therefore, the concern regarding the human exposure to PBDEs from PBDE-
containing products manufactured from recycled materials deserves further
investigation.
Ø A time-dependent stock of PBDEs was successfully established. However, building and
construction materials were not included in this study, as reliable information on this
sector was not available. As well, large transportation vehicles such as aircraft, trains and
buses were not included, again due to a lack of data. Thus, the estimated stock could be
improved by adding these product categories which would necessitate knowing the extent
of PBDE use and concentrations, and their life spans.
Ø The flow of PBDEs in the automotive sector to the waste phase could not be estimated in
this study as these vehicles do not follow the same patterns as other PBDE-containing
products. Developing a statistical method to estimate the flow of vehicles to the waste
phase will provide valuable information for the management of substances of concerns in
vehicles at the EoL.
Ø The estimated quantity of waste ICT products and display devices at different stages of
waste phase are subject to high uncertainty. As such, further research is required to
reduce uncertainty and improve the quality of these results. Collecting more reliable data
on the disposition of these products in the waste phase could significantly improve the
accuracy of these estimates.
115
Ø This study aimed at investigating the fate of PBDE-containing products in the waste
phase. Due to lack of data, this study focused only on the fate of ICT products and
display devices in the waste phase as they are more likely to undergo recycling but also
the mismanagement compared to other products included in this study. Further research
is required to develop plans or programs to ensure that other PBDE-containing products
undergo ESM and will not continue to act as a source of these substances to the
environment.
Ø This study provided valuable information on the disposition of ICT products and display
devices from first use to waste management phases. In the absence of reliable data, this
information can be used as a framework to improve e-waste management practices in
order to confront the influx of e-waste to the waste phase in the near future.
116
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