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Decabromodiphenyl Ether (DecaBDE) in Electrical and Electronic Equipment in Japan: Stock, Emission, and Substitution Evaluation Mianqiang Xue, Liang Zhou, Naoya Kojima, Takashi Machimura, and Akihiro Tokai Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03656 • Publication Date (Web): 20 Oct 2017 Downloaded from http://pubs.acs.org on October 23, 2017
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Environmental Science & Technology
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Decabromodiphenyl Ether (DecaBDE) in Electrical and
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Electronic Equipment in Japan: Stock, Emission, and
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Substitution Evaluation
4
Mianqiang Xue∗ Liang Zhou, Naoya Kojima, Takashi Machimura, Akihiro Tokai
5
Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering,
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Osaka University, 2-1 Yamadaoka, Suita, Osaka 565 0871, Japan
7 8
TOC art
9 10
ABSTRACT
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DecaBDE has been widely used as flame retardant in electrical and electronic equipment
12
(EEE). It has recently been listed in Annex A of the Stockholm Convention. The time series
13
flow, stock, and emission of DecaBDE in EEE in Japan were quantified. On this basis, a
14
risk/risk trade-off analysis of substituting DecaBDE with triphenyl phosphate (TPhP) that is
Corresponding author: Mianqiang Xue, Tel:+81 06 68797677; Fax:+81 06 68797677; E-mail:
[email protected] -1-
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one possible phosphorus-based alternative was conducted. The stock of DecaBDE reached a
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maximum of ~42,000 t in 1995. Even though the demand flow was negligible in 2030, the
17
stock was modelled to be still ~470 t. The outflow of DecaBDE, from the use phase to the
18
disposal phase, peaked at ~4,500 t/yr. in 2001. The DecaBDE emission to atmosphere was
19
mainly derived from the production phase before 1990. The use phase became the largest
20
contributor to the total emission from 1995 to 2000. Whereas the disposal phase dominated
21
the total emission from 2000 onwards. In the substitution analysis, a trade-off between human
22
and ecological health effect was revealed in case of replacing DecaBDE with TPhP. This
23
study attempted to give an overall picture of DecaBDE application at national level providing
24
insights into relevant environmental policy making.
25
1. INTRODUCTION
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Polybrominated diphenyl ethers (PBDEs) have been widely used as flame retardants in a
27
variety of products since 1970s. There are primarily three technical formulations of PBDEs:
28
PentaBDE, OctaBDE and DecaBDE
29
the Stockholm Convention in 2009 and have been phased out worldwide
30
just listed in Annex A of the Stockholm Convention in 2017 with specific exemptions for
31
production and use
32
mixture still being used today (4). More than one million tons of DecaBDE was produced from
33
1970 to 2010 globally
34
maximum of 10,000 t/yr. in 1990 (6). Since then, it decreased due to voluntary phase down by
35
the industry sector. DecaBDE is ubiquitous in the environment because of its widespread use
36
(7)
(1)
. PentaBDE and OctaBDE were added to Annex A of (2)
. DecaBDE was
(3)
. It might bioaccumulate in wildlife and human and is the only PBDEs
(5)
. The domestic consumption of DecaBDE in Japan reached a
and thus much concern has been raised (8, 9).
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(1)
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About 70% of DecaBDE is used in electrical and electronic equipment (EEE)
.
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DecaBDE, locked in EEE with a long lifespan, has a long residence time in society. Stock of
39
DecaBDE in the use phase results in disconnection between the inflow and outflow of a
40
system in one year
41
materials. It can be released throughout the life cycle of EEE to all environmental
42
compartments including the atmosphere, hydrosphere and pedosphere. Stocks and flows of
43
PBDEs in products in the U.S. and Canada from 1970 to 2020 were estimated based on the
44
consumption pattern, PBDE content and product lifespan
45
analysis of brominated flame retardants was performed for Switzerland from 1980 to 2020 (12).
46
Flows of DecaBDE and other flame retardants in a waste EEE treatment plant was
47
characterized
48
employing a population balance model considering future regulation (14). Besides, atmospheric
49
emissions of DecaBDE were calculated using emission factors derived from field study
50
The knowledge of DecaBDE flows and stocks is essential for identifying major sources and
51
final sinks. Source identification and emission quantification of DecaBDE serve as a good
52
basis for subsequent risk assessment. It is thus significant for improving strategies and
53
revealing opportunities for DecaBDE sound management. Nevertheless, only limited
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comprehensive information is available regarding emissions of DecaBDE in EEE to all
55
environmental compartments.
(10)
. DecaBDE is an additive since it is not chemically bound to host
(11)
. A dynamic substance flow
(13)
. PBDEs stock and atmospheric emissions in Japan were evaluated by
(6)
.
56
Due to curtailed use of DecaBDE in Japan, other alternative flame retardants have been
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used to reduce the risk of DecaBDE while still meeting fire safety standards. Triphenyl
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phosphate (TPhP), a phosphorus flame retardant, has been identified as one possible
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(15, 16)
. However, the substitute is also problematic
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(17, 18)
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substitute for DecaBDE
and has
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recently been included in the community rolling action plan (CoRAP) in the EU as a
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suspected endocrine disruptor
62
exposure and reduced fertility
63
countervailing risks at the same time. The countervailing risk could partially or completely
64
offset reductions in the target risk (21, 22). The cases in which substituting chemicals pose more
65
adverse impacts to humans and the environment than the substituted chemicals are
66
unacceptable. Sound decision-making process with uncertainty requires examinations of
67
DecaBDE replacement in EEE and always attempts to mitigate risk/risk trade-offs.
(19)
. A recent study indicated a relationship between TPhP
(20)
. Efforts to reduce one risk might create new or exacerbate
68
In the present study, we investigated the time dependent flows, stocks, emissions and
69
effects of DecaBDE in EEE in Japan. Further, we conducted risk/risk trade-off analysis in
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terms of substituting DecaBDE with TPhP based on scenario analysis. The main objectives of
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this work are (1) to provide a holistic picture of DecaBDE application from which lessons can
72
be learned for analogous chemicals management; and (2) to conduct relative evaluation of
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DecaBDE substitution based on the flow and stock model exploring challenges of preferable
74
alternatives identification.
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2. MATERIALS AND METHODS
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2.1 Flow and Stock Modeling
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Figure 1 illustrates the research framework for modelling the flows, stocks, emissions
78
and effects of DecaBDE in EEE. The geographic boundary is Japan and the time period is
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from 1976 to 2030. First, the flow and stock of DecaBDE were calculated using dynamic
80
substance flow analysis taking into account changes over time. In principle, the life cycle of
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DecaBDE is divided into the production, use and disposal phase. The production phase
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consists of DecaBDE and EEE production process. The use phase means usage of EEE
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containing DecaBDE. The disposal phase includes recycling, incineration, sewage and
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landfilling. Second, DecaBDE emissions from each life cycle process to each environmental
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compartment were investigated on the basis of the foregoing flow and stock analysis. Third,
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effects of released DecaBDE were quantified using LIME2 (23), the Japanese life cycle impact
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assessment approach. By means of transforming effects into one common indicator, a risk/risk
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trade-off analysis was conducted in case of replacing DecaBDE with TPhP. The concrete
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methods will be presented in detail below.
90 91
Figure 1. Research framework for modelling the flows, stocks, emissions and effects of DecaBDE in
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EEE in Japan.
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DecaBDE accompanying with EEE flows into the use phase and accumulates as stock.
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At the end of lives of EEE, DecaBDE flows out and are treated in the disposal phase. The
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inflow of DecaBDE was calculated by employing data on domestic demand of DecaBDE in
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Japan (domestic production + import - export) (24, 25). These data can be found in Table S1-2 in
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the Supporting Information (SI). DecaBDE began to be used for EEE in Japan in 1977 (24). In -5-
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the present study, the Weibull statistical distribution was used for describing the lifespan of
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EEE as shown in Eq. (1) (26):
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α p(t , t0 ) = ⋅ (t − t0 )α − 1 ⋅ e α β
−(
t − t0
β
)α
(1)
101
where p (t, t0) is the probability of EEE to be obsoleted in the evaluation year t for those
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purchased in historical year t0; α is the shape parameter; β is the scale parameter; The shape
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parameter is 3.7 and the scale parameter is 11.2 for EEE (24). t is the evaluation year; t0 is the
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historical year in which EEE were purchased. Then, the stock of DecaBDE in the use phase
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over time can be calculated by Eq. (2): T
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T
S1977 I1977 1 − P(1977 ,1977 ) 1 − P(1978 ,1977 ) L 1 − P( t ,1977 ) S I 1 − P(1978,1978) K 1 − P( t ,1979 ) 1978 1978 O L M M = × 1 − P(t ,t 0 ) St It M M M 0 L S 2030 I 2030
L 1 − P( 2030,1977 ) L 1 − P( 2030 ,1978 ) L L L L O L 1 − P( 2030, 2030 )
(2)
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where St is the stock of DecaBDE in year t; It is the inflow of DecaBDE in year t; P(t, t0) is the
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cumulative Weibull distribution; 1- P(t, t0) is the complementary Weibull distribution, i.e., the
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probability that EEE containing DecaBDE remains in the use phase in evaluation year t for
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those purchased in historical year t0. Based on the law of mass conservation, the outflow of
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DecaBDE into the disposal phase over time can be obtained by Eq. (3):
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Ot = It − (St − St −1 )
(3)
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where Ot is the outflow of DecaBDE in year t; It is the inflow of DecaBDE in year t; St and
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St-1 are the stock of DecaBDE in year t and t-1, respectively.
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2.2 Emission Inventory
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DecaBDE can be emitted from each life cycle process (DecaBDE production, EEE
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production, use, recycling, sewage, incineration and landfill) to each environmental
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compartment (atmosphere, hydrosphere and pedosphere). Emissions of DecaBDE were
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quantified by Eq. (4):
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Eij=A . EFij
(4)
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where Eij is the emission of DecaBDE from the life cycle process i to the environmental
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compartment j; A is the activity associated with emission of DecaBDE which is usually a
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mass flow; EFij is the emission factor from the life cycle process i to the environmental
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compartment j. In particular, the activities in the DecaBDE production, EEE production and
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use process are corresponding to the domestic production flow, domestic demand flow and
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in-use stock, respectively. During the DecaBDE and EEE production, DecaBDE in waste
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water will be transferred to sewage system whereas solid waste containing DecaBDE will be
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treated as industrial waste. Outflows from the use phase to the disposal phase were mainly
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managed by four approaches: export, recycling, treated as general waste and industrial waste
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(27)
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appliances recycling law was put into force in Japan (28). In the years before 2001, 70% of the
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outflow was treated as general waste. After 2001, 50% of the outflow was recycled and the
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left 20% was treated as industrial waste. For general waste, 84% was disposed by incineration
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while 16% was disposed by landfill. For industrial waste, 38.1% was disposed by incineration
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while 61.9% was disposed by landfill
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cycle are represented in Figure 1. The emission and transfer factors of DecaBDE are
137
presented in Table S3.
138
. Basically, 30% of the outflow was exported to other countries. In 2001, the home
(24)
. The transfer routes of DecaBDE through its life
In practice, emission factors are usually supposed to be representatives of the average
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emission rate. Lack of understanding about emission factors might result in erroneous
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inferences. The two-dimensional probabilistic technique enables us to quantify variability and
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uncertainty simultaneously, providing additional insights into environmental decision-making
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(29)
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evaluating its central tendency and dispersion, as described in SI. Then, a parametric
144
probability distribution was selected to fit to the data for denoting variability in the emission
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factor. The parameters of the distribution were determined using the maximum likelihood
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estimation. Afterwards, uncertainty in the distribution was quantified using parametric
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bootstrap simulation (30), a numerical approach for estimating confidence intervals on the basis
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of simulation of random sampling error. This method is particularly applicable in the case of
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small sample size and skewed data. It was assumed that the emission factors were continuous
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random variables. A random sample of the same size as the original dataset was simulated
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from sampling this fitted model. It was done with replacement. The bootstrapping was
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repeated for 2000 times making it sufficient to obtain accurate confidence intervals (31).
. For a set of data, it was firstly visualized by the method of “plotting position” for
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To identify the most highly sensitive input variables responsible for variability and
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uncertainty in the system, an initial sensitivity analysis was carried out. The sensitivity ratios
155
were calculated by Eq. (5) (32):
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Y2 − Y1 Y1 SR = X2 − X1 X1
(5)
157
where X1 is the reference value of one input variable; X2 is 115% of X1 in this study; Y1 and Y2
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are the output variables with X1 and X2 as input variables, respectively.
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2.3 Substitution Scenarios and Risk/risk Trade-off Analysis
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Substitution scenarios were developed as a basis for risk/risk trade-off analysis,
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investigating how the countervailing risk offset the target risk reduction. In the present study,
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three scenarios were developed: Scenario A was the best estimation of flows, stocks,
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emissions and effects of DecaBDE. It was estimated as close to the actual situation as possible
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employing currently available data, seen in Section 2.1. Whereas Scenario B and C were
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designed with a purpose of comparison. Specifically, Scenario B assumed a case in which
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there was no substitution for DecaBDE. The domestic demand of DecaBDE would remain the
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same since 1990. Scenario C was a case in which DecaBDE (difference between Scenario A
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and Scenario B) was substituted with TPhP. The amount of TPhP was calculated according to
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the ratio of TPhP and DecaBDE contents in EEE
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scenarios intuitively. Then, the risk/risk trade-off can be analyzed by comparing Scenario
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A+C with Scenario B. Table 1 shows the properties of DecaBDE and TPhP. We notice the
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difference in use and emission patterns. Emission factors in preparing plastics with TPhP for
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EEE and in the use phase were supposed to be in proportion to the vapor pressure. In the
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recycling process, it was in proportion to its content in plastics. Other factors without
175
information were assumed to be identical to that of DecaBDE seen in Table S3.
(27)
. Figure S1 illustrates these substitution
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In each scenario, the fates, exposures and effects of DecaBDE and TPhP were signified
177
by damage factors. The effects were expressed in the Eco-indicator after integration. The
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Eco-indicator with a unit of Japanese Yen was calculated by Eq. (6):
179
EI=Ei . DFij . IFij
(6)
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where EI is the Eco-indicator; Ei is the emission of chemical i; DFij is the damage factor of
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chemical i emissions to the environmental compartment j; IFij is the corresponding integration
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factor. The damage and integration factors used in this study can be seen in Table S4. Table 1. The Physical Properties of DecaBDE and TPhP a
Chemicals
a
CAS number
Molecular mass
Vapor pressure
Water solubility
(g/mol)
(Pa)
(mol/m3)
Structure
DecaBDE
1163-19-5
959
4.63E-06
1.04E-07
TPhP
115-86-6
326
8.37E-04
5.82E-03
The vapor pressure and water solubility were taken from Watanabe et al. (27)
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3. RESULTS AND DISCUSSION
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3.1 Flow and Stock of DecaBDE
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Figure 2 illustrates the time series flow and stock of DecaBDE in EEE in Japan. It
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represents a typical flow pattern of a chemical substance that was phased down because of
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health risk concerns. The domestic demand flow of DecaBDE increased sharply until a peak
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of 8000 t/yr. was reached in 1990. Since then, DecaBDE was phased down progressively and
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the demand flow decreased rapidly. Compared with the domestic demand flow, the domestic
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production flow was small indicating a large portion of importation of DecaBDE.
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In regard to the stock of DecaBDE, it appeared in a same trend with demand flow. Two
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distinct features were observed. One was that the stock of DecaBDE was huge. It reached a
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maximum of ~42,000 t in 1995. The other was that the peak year of stock was delayed for
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five years. Even though the demand flow was negligible in 2030, the stock was modelled to
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be still ~470 t. It indicated that the role of stock is significant in risk management of
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thousands of chemicals used in our society from the life cycle perspective.
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The outflow of DecaBDE, from the use phase to the disposal phase, increased firstly
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followed by a smooth decline with a peak value of ~4,500 t/yr. in 2001. Results of the stock
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and outflow provide insights into consumer exposure risk appraisal and strategic planning for
200
waste management.
201 202 203
Figure 2. Flow and stock of DecaBDE in EEE in Japan from 1976 to 2030.
3.2 Emissions of DecaBDE
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Based upon the foregoing analysis of flow and stock, emissions of DecaBDE were
205
quantified. From a static perspective, a snapshot of DecaBDE emission with a time scale of
206
one year was studied to identify the emissions from which life cycle process to which
207
environmental compartment. As an example, Figure 3 presents the DecaBDE emission in
208
2003 in Sankey diagram, in which the width of the arrow is proportionally to the flow
209
quantity. The total emission of DecaBDE was 157 t in 2003. The emissions were primarily
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from the production phase to hydrosphere.
211
If we look at the emission sources, the production phase contributed most significantly to
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the total emission with a value of 63%. Likewise, the use and disposal phases contributed 9%
213
and 28%, respectively. For the disposal phase, the emission was largely attributed to the
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treatment methods of recycling (62%) and incineration (24%). If we look at the receiving
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environmental compartments, 59% of the total emissions were released into hydrosphere and
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38% into atmosphere. The left small fraction was released into pedosphere.
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Figure 3. Sankey diagram of DecaBDE emissions from each life cycle phase to each
219
environmental compartment.
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On the other hand, from a dynamic perspective, the time series emission of DecaBDE
221
from 1976 to 2030 was computed to investigate its changing behavior, as shown in Figure 4.
222
For the DecaBDE emission to atmosphere, it was mainly derived from the production phase
223
before the year 1990. Interestingly, the use phase became the largest contributor to the total
224
emission from 1995 to 2000. Whereas, it revealed that the disposal phase dominated the total
225
emission from 2000 onwards. This transformation of primary emission sources can be
226
explained by dynamics of the flow and stock. The emission from the production phase peaked
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at about 0.11 t/yr. in 1990. The emission from the use phase peaked at 0.031 t/yr. in 1995. The
228
emission from the disposal phase peaked at 0.041 t/yr. in 2002.
229
With respect to the DecaBDE emission to hydrosphere, the production always played a
230
dominant role over the time range of this study. The emission attributable to the production
231
phase was larger than 0.1 t/yr. from 1982 to 2000. In contrast, both of contributions from the
232
use and disposal phase were pretty small. In regard to the DecaBDE emission to pedosphere,
233
the disposal phase had absolute predominance compared with the production and use phase. -12-
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Figure 4. The emissions of DecaBDE in EEE in Japan from 1976 to 2030, breakdown by life
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cycle phase: (a) to atmosphere, (b) to hydrosphere, (c) to pedosphere.
237
DecaBDE emissions are subjected to both variability and uncertainty. Variability refers
238
to the real differences in values, whereas uncertainty is a lack of knowledge regarding the true
239
value. In the present work, we quantified variability and uncertainty simultaneously to better
240
understand the precision of the modelling.
241
In a first step, the sensitivity ratios were calculated. It was found that the sensitivity ratio
242
for the emission factor from the production phase to hydrosphere was the highest (0.61) in the
243
case of +15% error in variables. The sensitivity ratios for other emission factors were small.
244
For the emission factor from the production phase to hydrosphere, a set of data was collected
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and plotted in Figure 5. A lognormal probability distribution was fit to data points denoting
246
the variability. It indicated that 95% of the emission factors from the production phase to
247
hydrosphere range from 3.6E-05 to 3.1E-03. On the basis of the fitted distribution for
248
variability, the 50%, 90% and 95% confidence intervals were obtained by bootstrap
249
simulation to inspect the appropriateness. The results implied that 83% of the data points were
250
enclosed by the 50% confidence interval for the fitted distribution. And 100% of the data
251
points were enclosed by the 95% confidence interval.
252 253
Figure 5. Variability and uncertainty in the DecaBDE emission factor from the production
254
process to hydrosphere.
255
Through the two-dimensional probabilistic analysis, we can identify any percentile of the
256
factor with any confidence interval. The 95% confidence interval is usually of particular
257
interest and in this study all of the data points are enclosed by this confidence interval. As an
258
example, the total emission of DecaBDE was calculated using the 50 percentile of the
259
emission factor from the production phase to hydrosphere with the 95% confidence interval,
260
as shown in Figure 6. The total DecaBDE emission reached a maximum of 0.50 (0.31-1.13)
261
t/yr.in 1990. Prior to that from 1980 to 1990, the total emission increased with an average -14-
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annual rate of 66%. After that from 1990 to 2000, the total emission decreased with an
263
average annual rate of 6%.
264 265
Figure 6. Total emissions of DecaBDE in EEE in Japan from 1977 to 2030: line, mean value
266
of emission factors; shaded area, 2.5th and 97.5th percentiles.
267
3.3 Substitution and Risk/risk Trade-off
268
To compare the risk related usage of DecaBDE and its candidate substitution TPhP, a
269
risk/risk trade-off analysis was conducted based on substitution scenarios. Figure 7 presents
270
the Eco-indicators of DecaBDE and TPhP from EEE in Japan from 1976 to 2030. The
271
endpoints include both human and ecological health effects. It can be found that the
272
Eco-indicator decreased significantly since 1990 when DecaBDE was replaced with TPhP
273
from the standpoint of protection of humans and the environment. If DecaBDE was
274
continuously being used, the Eco-indicator would be 6.6E+07 Yen in 2030. If DecaBDE was
275
replaced with TPhP, the Eco-indicator would be 5.6E+06 Yen in 2030. In the case of replacing
276
DecaBDE with TPhP, the Eco-indicator was mainly attributable to the human health effect of
277
DecaBDE and the ecological health effect of TPhP.
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Figure 7. Eco-indicators of DecaBDE and TPhP in EEE in Japan from 1976 to 2030.
280
It is of importance to define the time frame to do trade-off analysis. In this study,
281
DecaBDE was firstly introduced for EEE in Japan in 1970s. It began to be replaced with
282
alternatives in 1990. Based on the developed scenarios, the trade-off of replacing DecaBDE
283
with TPhP in the year 2030 was demonstrated in Figure 8. The green color represented the
284
preferable area while the red color represented the undesirable area. It revealed that the
285
human health effects decreased whereas the ecological health effects increased at the same
286
time. Namely, a trade-off between human and ecological health effects was identified, which
287
was resulted from risk offset and transformation.
288 289 290
Figure 8. Risk/risk trade-off analysis of replacing DecaBDE with TPhP in the year 2030. In sum, the present study evaluated the stock, emission and substitution of DecaBDE in -16-
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EEE in Japan retrospectively and prospectively from 1976 to 2030. It attempted to give an
292
overall picture of DecaBDE application at national level providing support for chemical
293
management. First, the DecaBDE stock in EEE reached a maximum of ~42,000 t in 1995.
294
Even though the demand flow was negligible in 2030, the stock was modelled to be still ~470
295
t. It indicated that phasing out of a chemical with potential harm is just one important first
296
step, once it was being widely applied in products. The subsequent stock and waste
297
management also should be tackled with proper countermeasures. Second, a transformation of
298
the primary emission source of DecaBDE over time was identified. It suggested that
299
corresponding remedies in a timely manner were required in different periods from
300
introduction, through widely use, to phasing out of DecaBDE. Third, the two-dimensional
301
probabilistic analysis quantified both variability and uncertainty of the most sensitive
302
emission factor. It offered additional information about whether the modelling was good
303
enough for decision-making. Fourth, a broad decision framework is important regarding
304
chemical substitution to mitigate risk/risk trade-offs. Finally, combination of the dynamic
305
substance analysis and risk evaluation techniques enables us to evaluate the time-dependent
306
chemical substitution, which is very helpful for efficient and effective chemical management.
307
However, this study has some limitations. There are significant uncertainties in emission
308
factors from each life cycle process to each environmental compartment, calling for further
309
experiment and model based studies. The substitution evaluation conducted by LIME2 should
310
be understood as relative analysis, which is not suitable to answer the question whether or not
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the substitute is safe. It provides insights for screening level decisions rather than directly for
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laws and regulations. The elaborate fate process and exposure scenarios were out of the scope
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of this work and here they were addressed by integrating them into damage factors. It is also
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worth noting that the environmental risks of both DecaBDE and TPhP are still ongoing. Their
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effects on vulnerable populations and occupational workers should not be underestimated.
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ASSOCIATED CONTENT
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Supporting Information
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Additional details on the raw data and results. This information is available free of charge via
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the Internet at http://pubs.acs.org.
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Notes
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The authors declare they have no competing financial interest.
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ACKNOWLEDGMENTS
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This research was supported by the Environment Research Technology Development Fund
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(1-1501) of the Ministry of Environment, Japan. We express our appreciation to the members
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of the Risk Governance Project Expert Committee. We also thank the anonymous reviewers
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for their valuable suggestions to improve the quality of the paper.
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