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Supporting information
Deducing targets of emerging technologies based on ex
ante life cycle thinking by a deductive life cycle assess-
ment approach: case study on a chlorine recovery
process for polyvinyl chloride wastes
Jiaqi Lu a, Shogo Kumagai a, *, Hajime Ohno b, Tomohito Kameda a, Yuko Saito a, Toshiaki Yoshioka a,
Yasuhiro Fukushima b, *
aGraduate School of Environmental Studies, Tohoku University, 6-6-07 Aoba, Aramaki-aza, Aoba-ku,
Sendai, Miyagi 980-8579, Japan
bGraduate School of Engineering, Tohoku University, 6-6-07 Aoba, Aramaki-aza, Aoba-ku, Sendai,
Miyagi 980-8579, Japan
5 tables
7 figures
21 pages
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Figure S1 Advanced Cl recovery process for polyvinyl chloride (PVC) waste treatment via
dechlorination in an NaOH/ethylene glycol (EG) solution, followed by electrodialysis of the spent
NaCl/EG solution (Kumagai et al., 2018).
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Table S1. List of the data sources used this study.
Inventory SourceCommercial
database
Literature
data
Organization
report
PVC resin production (CEC, CGE)PWMI (2014)
O
Mixed plastic waste treatments (CEC, CGE) O
NaCl production (CEC, CGE) Ecoinvent version 3.2 (Wernet et al.,
2016)
O
Transoceanic shipping (CEC, CGE) O
Slaked lime (Ca(OH)2) production (CEC, CGE)IDEA v2 (Tahara et al., 2010)
O
GHG emission coefficient of electricity in Japan in 2014 O
Chemical production (PEC)Ecoinvent version 2.0 Report No.8
(Frischknecht et al., 2004)O
Desalination by electrodialysis (PEC)AQWATEC (Colorado School of
Mines), Tanaka (2003)O O
Distance of NaCl transportation (sea-distances.org) O
Pretreatment of NaCl (CEC, CGE) PlasticsEurope (2013) O
Electrolysis of NaCl (PEC) JSIA (2017) O
Abbreviations: CEC, cumulative energy consumption; CGE, cumulative GHG emission; GHG, greenhouse gas; PEC, process electricity consumption; PVC, polyvinyl chloride
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S1.1 Inventory analysis for obtaining specific data for PVC waste treatments from report on over-
all plastic waste treatments
The inventory data of MR offset, ER and FR are provided only based on the treatments of mixed
plastic waste (PWMI, 2014). Therefore, specific values on PVC waste must be estimated based on the
inventory data for mixed plastic waste. Firstly, MR offset can be replaced by the burden of a life cycle
of PVC. During other waste treatments, the recycling efficiency are varied with the type of treatment
and technology. In ER, the recycling efficiency implies the ratio of heat recovery from mixed plastic
waste, whereas it implies the ratio of recovered hydrocarbon from mixed plastic waste in FR process.
Thus, the recycling efficiencies for each type of treatment (i.e., ER and FR) in the recycling of mixed
plastic waste are determined first, and then the inventory of each kind of plastic recycling in the
treatments are estimated individually based on the determined recycling efficiencies. And then the
allocation of ER offset, FR offset and GHG emission can be applied according to calorific value,
hydrocarbon content and combustion emission of different kinds of plastics respectively. The
mathematic expression and parameters for different items are shown in Equation S1 and Table S1.
I jM=η j(∑i∈P
ωi I ji +c j) （S1）
Where I jM represents the inventory of mixed plastic wastes in terms of an evaluation target j (ER
offset, FR offset and GHG emission), and the set P contains 5 types of resins such as PVC, PE, PP, PET
and PS. The η j means the conversion ratio from wastes into recycled products or GHG emission. η j is
the unknown for ER offset and FR offset while it is set to 1 for GHG emission. ω represents the weight
percent of different waste plastics. I ji represents the calorific value, hydrocarbon content and combustion
emission of each kind of plastic as indexes. The constant c j is only nonzero in calculating GHG
emission as unknown because it represents the emission from the other sources such as fossil fuels for
igniting and utilities. By putting the known I jM , ωiand I j
i into the equation, the unknown η j for ER and
FR offset as well as c j for GHG emission can be calculated out. Finally, the specific inventory for PVC
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waste is generated by setting the c j with 1.
Table S2 Parameters for inventory calculation
Evaluation target η(ratio) I (index) c(constant)
j
ER offset Efficiency Calorific value 0
FR offset Efficiency CxHy mass ratio 0
GHG emission 1 Combustion emission Treatment emission
Figure S2 Net energy consumption of overall plastics (a) and specific PVC (b) waste treatments.
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a. Overall plastics waste treatments
b. Specific PVC waste treatments
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Figure S3 Net GHG emission of overall plastics (a) and specific PVC (b) waste treatments
Based on the data of overall plastics waste treatment and mentioned method, the specific net energy
consumption and GHG emission were calculated out in Figure S2 (b) and S3 (b), compared with the
balances of overall plastic waste treatment in Figure S2 (a) and S3 (a). The classification of treatment
methods is: FR (Blast furnace, coke oven, gasification and liquefaction), ER (electricity generation, heat
utilization and Refused Derived Plastic and Paper Fuel (RPF)) and final disposal (incineration without
ER, landfilling). The detailed process flow of each treatment can be found at website of Japan Plastic
Waste Management Institute (http://www.pwmi.or.jp/ei/plastic_recycling_2016.pdf).
Because PWMI used the GHG emission coefficient in 2005 (PWMI, 2014) and the coefficient has
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a. Overall plastics waste treatments
b. Specific PVC waste treatments
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changed a lot after the big earthquake in 2011, the inventories of current waste treatments should be
modified with latest data. Firstly, all the sources of inventories were found in The Japan Containers and
Packaging Recycling Association (The Japan Containers and Packaging Recycling Association, 2007)
and New Energy and Industrial Technology Development Organization (New Energy and Industrial
Technology Development Organization, 2007). Then for the energy inputs of electricity, recalculate the
GHG emission with the emission coefficient from IDEA V2 (Tahara et al., 2010). Finally, the updated
inventories for this study was obtained.
Table S3 Distribution of current PVC waste treatments (PWMI, 2014)
Treatment method Replaced materialProportion of gross
Industrial Municipal
MR PVC resin 27.90% 0.00%
Blast furnace Coke 0.00% 0.11%
Coke oven Coal 0.02% 0.81%
Gasification Syngas 1.72% 0.27%
Liquefaction Petroleum 0.01% 0.00%
Power generation Fossil fuels 17.11% 8.61%
Heat recovery Fossil fuels 9.58% 1.46%
RPF Solid fuel 12.98% 1.09%
Incineration - 4.37% 3.03%
Landfill - 9.58% 1.33%
The net energy consumption (Ecurrentnet ) and GHG emission (C current
net ) of treating 1 kg PVC waste by
weighted mean can be calculated by:
Ecurrentnet =∑
k∈Tωk ((1−X ) E k+Ek
offset) （S2）
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C currentnet =∑
k∈Tωk (C k+C k
offset) （S3）
Where T represent all the treatment methods in Table S3;ωk is the proportion of each treatment based
on scenario; Ek ,C k , Ekoffsetand C k
offset are the energy consumption, GHG emission, energy offset and GHG
emission offset of specific PVC waste treatments by Equation S1. Setting X=0 and using the proportion
of treatments in Table S3, the net energy consumption and GHG emission of current PVC waste
treatment as benchmark are -14.2 MJ/kg PVC waste and 0.003 kg CO2-e/kg PVC waste.
S1.2 Data quality and uncertainty
During the data sorting, we noticed that the value (46.06MJ, 1.45kg CO2-e) (PWMI, 2014) of
the accumulative energy consumption and GHG emission from cradle to PVC resin in Japan is a little
lower compared with the data reported by Plastic EU (60.7MJ, 1.78 kg CO2-e) (PlasticsEurope, 2013).
In order to ensure the quality of database, we also investigate the reasons of the difference. We conclude
that the investigation method, allocation method and basic database of two data provider account for the
difference.
(1) Investigation Method
Firstly, the system boundary of the report from PWMI contains raw material production,
transportation, electrolysis of salt, oil refinery and resin synthesis. This doesn’t have big difference with
the Plastic EU’s system boundary. From the Eco-profile of VCM and PVC production provided by
Plastic EU (PlasticsEurope, 2013), the data was collected by vertical averaging as far as possible. This
means that the data was collected from previous production chain where upstream providers are
specified. However, all of data was calculated by horizontal method in PMWI reports because actually it
is hard to separate the products form complex processes such as oil refinery and electricity
generation(PWMI, 2014). A simple example is assumed in Figure S4 to illustrate the difference of two
methods.
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Figure S4 Example of the different averaging methods for the data collection
In this example situation of ethylene supply, the energy consumption per kg ethylene for PVC
production would result in: 0.25×10+0.75×15=13.75 MJ/kg (vertical), 0.5×10+0.5×15=12.5 MJ/kg
(horizontal). It is hard to judge which method is better as it is only a calculation difference. The vertical
method can carry out more specific value of environmental burdens from related supply chain. On the
other hand, the horizontal method can represent the average situations of various manufactures in the
industry. However, if the supply distribution of different providers is changed, the result of vertical
averaging should be correspondingly changed while the result of horizontal averaging would be same.
(2) Allocation
Generally, production processes in the chemical and plastic industry have several valuable products
and by-products. Thus, allocation methods are necessary to distribute the energy consumption and
environmental burdens of a multi-products process to all products. One of the key allocations in PVC
industries is for the electrolysis of salt which mainly produces NaOH, chlorine and H 2. Plastics Europe
used allocation in the report (Plastics Europe 2013) while the method applied by PMWI was based on
mass distribution and using hydrogen to generate electricity (PWMI, 2014). Because the molecular mass
of 2NaOH is greater than the Cl2, less value is allocated to chlorine by mass averaging method in
comparison with the stoichiometry allocation.
Two more important facts on the inventory of electrolysis of salt reported by Narita et al. (2002) are
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that the chlor-alkali industry in Japan has their in-house electricity generation and low electricity
consumption due to the use of membrane method to produce chlorine. According to the annual
electricity consumption report (JSIA, 2017), about 68% electricity was generated by themselves for
electrolysis of salt. Therefore, the waste heat can be reused in some processes and the energy burden of
electricity can be reduced from 10.03 MJ/kWh to 6.13 MJ/kWh. Secondarily, the advance of membrane
method can be proved by other references. In Japan, all the electrolysis process is based on membrane
method (Japan Soda Industry Association, 2015) while the proportion in Europe was 54% in 2006
(PlasticsEurope, 2013). However, this method requires high purity of NaCl, which leads to the low
efficiency of salt utilization.
(3) Basic database
Although every detail of calculation couldn’t be accessed, some important differences has been
mentioned in the reports. Firstly, PMWI and Plastics Europe cited different calorific values of fossil
fuel. Taking crude oil as example, which is used for energy and raw materials in industry, the values
used by PWMI (PWMI, 2014) and Plastics Europe (PlasticsEurope, 2013) are 44.9 and 45. MJ/kg,
respectively. There are two possible reasons that could result in this gap and would have different
impacts on the data for PVC production. One is that it is the actual calorific value difference caused by
different types of resources produced in various locations. Another is that the measuring method is
different. The conclusion could be drawn that the first reason won’t affect the energy consumption
calculation because for certain demand of energy, if the calorific value is low, it must cause more in
mass. Nevertheless, the second reason will cause difference as the actual value is same. Secondarily, the
GHG emission from power generation is decided by the resource structure of countries. Because
European Union consists of many countries which have different situations of power supply
(PlasticsEurope, 2013), the data represents the average technology levels. In the case of Japan, as the
decrease of nuclear power plant after big earthquake, the proportion of electricity produced by fossil
fuels has increased. Therefore, the emission has risen to 0.556 kg CO2-e/kWh (Federation of Electric
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Power Companies, 2015). The value used by PWMI was 0.420 kg CO2-e/kWh in 2005 (PWMI, 2014).
To sum up, except uncertain technology factor, the investigation and calculation method account for
the main difference of database between PMWI and Plastic EU. However, the current situation of GHG
emission may be a little higher than the data used in the report from PWMI.
In this study, there is uncertainty in some inventories. Firstly, the location of salt production is Rest
of World so that it may cause uncertainty. Then, for the lack of detailed specific port and sea route, the
transportation distance of salt importation is a minimum calculation by shortest distance between two
countries. The data of salt purification, despite a simple process, is in Europe and it may include the
treatment for product purification. Thus, the real environmental impacts for salt purification would be
lower. Consequently, in the offset of salt production, there is uncertainty caused by specific location,
minimum transportation and overestimated purification process. As the Cl flow is unclear during the
thermal treatments of PVC wastes mixed with other Cl sources of wastes, it is hard to distinguish the
final fate of Cl. All Cl in PVC wastes after thermal treatments were assumed to be absorbed by slaked
lime, while the other routes such as fly ash and dioxin were not considered. Therefore, the benefit of Cl
recovery process was underestimated.
S1.3 Benchmark of net energy consumption and GHG emission based on current PVC waste
treatment system
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Figure S5 Net energy consumption (left) and GHG emission (right) of current PVC waste treatment
The net energy consumption and GHG emission of treating 1kg PVC waste, shown in Figure
S5, are calculated by the weighted mean of all PVC waste treatments based on the Scenario (a) in
Section 2.5. The baseline zero means consumption/emission and offset are balanced for 1 kg PVC waste
treatment. The energy consumption of the current treatments (sum of MR, FR, ER and disposal) is low
because the major treatments such as ER and incineration require few additional material and energy
inputs. However, if the Cl treatment in tail gas by Ca(OH)2 is taken into consideration, the energy
consumption should be higher. The energy offset is mainly from MR, even if MR only accounts for
28% of overall treatments, as this treatment can save the all virgin materials and process consumption
for PVC resin production. The low energy offset from the cumulative energy consumption of fossil fuels
substituted by PVC in ER/FR is caused by low recovery efficiency from mixed wastes and relative low
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calorific value of PVC resin compared with other plastics both reported by PWMI (2014). The net
energy consumption is -14.2 MJ/ kg PVC waste which means that energy could be saved through
overall PVC waste treatments.
From the net GHG emission in the right of Figure S5, the current PVC waste treatment emit
large quantity of GHG which is mainly from thermal processes including FR, ER and the incineration in
final disposal. Because during these processes, the carbon contained in PVC resin completely becomes
CO2 as GHG emission. The use of slaked lime will bring extra GHG emission because during the
production of slaked lime, the limestone (CaCO3) becomes quick lime (CaO) by calcination and then
quick lime is hydrated with water (Gutierrez et al., 2012). For treating the Cl from 1kg PVC waste by
thermal processes in principle, the GHG emission from the using of slaked lime is 0.62 kg which is
equal to 41% of GHG emission from the complete combustion of PVC. The situation and reason of
GHG emission offset is similar with the situation and reason of energy offset. The net GHG emission is
0.003 kg CO2-e/ kg PVC waste so that current PVC waste treatment doesn’t help too much in GHG
reduction.
In summary, quantitative net energy consumption and GHG emission of current PVC waste
treatment is clarified. It will be regarded as the benchmark in the following result for developing the
new Cl recovery process. The existent treatments are beneficial in terms of energy saving while fails to
reduce the GHG emission. The Cl treatment in thermal processes accounts for considerable energy
consumption and GHG emission. As a result, the advanced Cl recovery process has big potential to
improve the current PVC waste treatment.
S1.4 Life cycle impact assessment (LCIA) of Cl recovery process at X = 0.88, P/K = 4.0
To investigate the comprehensive environmental impacts of Cl recovery process assuming the
fixed variables (X and P/K), an individual LCIA was carried out. The consumption of electricity for
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dechlorination process and electrodialysis, the consumption of NaOH, the avoided production of NaCl,
and the waste treatment of dechlorinated PVC by energy recovery were considered. Ecoinvent V3.2 was
used as the databased for the calculation with OpenLCA 1.7.4 (Ciroth, 2007). The methodology of eco-
indicator 99 (H) (Goedkoop, 1999) was chosen. The results of LCIA are shown in Table S4.
Table S4 Environmental impacts of Cl recovery process for treating 1 kg PVC wastes
Category Environmental impacts Unit Value
Ecosystem quality
Land conversion PDFa*m2 2.49E-07
Land occupation PDF*m2*year 4.13E-07
Acidification and eutrophication PDF*m2*year 3.60E-02
Ecotoxicity PDF*m2*year 6.67E-05
Subtotal PDF*m2*year 3.60E-02
Human health
Carcinogenics DALYb -7.41E-08
Climate change DALY 7.74E-03
Ionising radiation DALY 3.38E-09
Ozone layer depletion DALY 8.67E-10
Respiratory effects caused by inorganic substances
DALY 3.89E-06
Respiratory effects caused by organic substances
DALY 8.81E-10
Subtotal DALY 7.75E-03
Resources depletion
Fossil fuels MJ surplus energy 1.75E+00
Minerals MJ surplus energy -7.00E-05
Subtotal MJ surplus energy 1.75E+00aPotentially Disappeared Fraction of species over m2 of land in a year, representing the damage on ecosystem (Humbert et al., 2005).bDisability-Adjusted Life Years measuring the burdens on human health caused by respective environ-mental impacts (Murray, 1994).
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S1.5 Sensitive analysis on the uncertain factors in material flow
Because the Cl recovery process is an emerging technology on lab scale the assumed material
flow of potential PVC waste treatment has large uncertainty. To determine if the uncertainties in the
material flow will significantly affect the environmental impacts, the sensitive analysis was carried out.
Some factors are defined in the Table S3. With the fixed variables mentioned in Section 3.4, the change
of energy consumption and GHG emission with an 1% increase in the factors in Table S5 are shown in
Figure S6.
Table S5 Definition of uncertain factors in material flow of potential PVC waste treatment
Factor Definition
Implementation rate of Cl recovery
The weight of PVC wastes treated by Cl recovery process divided by the weight of total PVC wastes except ones treated by mechanical recycling (sum of PVC wastes treated by final disposal, energy recovery and feedstock recycling).
Excess rate of NaOH The excess weight of input NaOH divided by the minimum weight of NaOH to be reacted with PVC in stoichiometry.
Utilization rate of NaCl Utilized weight of NaCl from Cl recovery process divided by the assumed output weight of NaCl from Cl recovery process.
Utilization rate of dechlorinated PVCUtilized weight of dechlorinated PVC from Cl recovery process divided by the assumed output weight of dechlorinated PVC from Cl recovery process.
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Figure S6 The change of energy consumption (a) and GHG emission (b) with an 1% increase in the
value of factors defined in Table S3
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S1.6 Sensitivity analysis on the uncertain factors in the LCA model
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Figure S7 Sensitivity analysis by applying partial derivative of net energy consumption (Epotentialnet ) and
GHG emissions (C potentialnet ) with respect to the parameters in Equation 4: (a)
∂ E potentialnet
∂(P /K ) at X=0.88, c=0.3;
(b) ∂C potential
net
∂(P /K ) at X=0.88, c=0.3; (c) ∂ E potential
net
∂ X at P/K=4.0, c=0.3; (d) ∂C potential
net
∂ X at P/K=4.0, c=0.3; (e)
∂ E potentialnet
∂ c at P/K=4.0, X=0.88; (f) ∂C potential
net
∂c at P/K=4.0, X=0.88.
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