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Tackling the Downcycling Issue—A Revised Approach to Value-Corrected Substitution in Life Cycle Assessment of Aluminum (VCS 2.0)

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For some metals, downcycling appears when scrap is polluted with undesirable elements or mixed with lower quality scrap grades in a way that the material displays a change in inherent properties when recycled. The article recommends the use of different scrap class prices instead of a solitary secondary alloy price to represent the level of downcycling inflicted on aluminum over a product's life cycle. The price ratio between scrap price and primary aluminum price is shown to be stable across all available scrap classes for the years 2007–2010. While the revised approach to value-corrected substitution (VCS) puts a stronger emphasis on the creation of high-quality scrap by penalizing its pollution more than the original version, its key limitation is the correct identification of the appropriate point of substitution along the scrap value chain. If relevant sorting or pre-treatment steps are omitted, the substitution factor would be overcorrected, which is why it is crucial to establish the scrap value right before the scrap is either mixed with scraps from other product systems or right before it enters the remelting step.
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Sustainability 2013, 5, 4546-4560; doi:10.3390/su5114546
sustainability
ISSN 2071-1050
www.mdpi.com/journal/sustainability
Article
Tackling the Downcycling IssueA Revised Approach to
Value-Corrected Substitution in Life Cycle Assessment of
Aluminum (VCS 2.0)
Christoph Koffler 1,* and Julia Florin 2
1 PE International, Inc., 344 Boylston St, Boston, MA 02116, USA
2 PE International AG, Hauptstraße 111-113, Leinfelden-Echterdingen 70711, Germany;
E-Mail: j.florin@pe-international.com
* Author to whom correspondence should be addressed; E-Mail: c.koffler@pe-international.com;
Tel.: +1-617-247-4477 (ext. 101); Fax: +1-617-236-2033.
Received: 24 June 2013, in revised form: 12 September 2013 / Accepted: 4 October 2013 /
Published: 25 October 2013
Abstract: For some metals, downcycling appears when scrap is polluted with undesirable
elements or mixed with lower quality scrap grades in a way that the material displays a
change in inherent properties when recycled. The article recommends the use of different
scrap class prices instead of a solitary secondary alloy price to represent the level of
downcycling inflicted on aluminum over a products life cycle. The price ratio between
scrap price and primary aluminum price is shown to be stable across all available scrap
classes for the years 20072010. While the revised approach to value-corrected substitution
(VCS) puts a stronger emphasis on the creation of high-quality scrap by penalizing its
pollution more than the original version, its key limitation is the correct identification of
the appropriate point of substitution along the scrap value chain. If relevant sorting or
pre-treatment steps are omitted, the substitution factor would be overcorrected, which is
why it is crucial to establish the scrap value right before the scrap is either mixed with
scraps from other product systems or right before it enters the remelting step.
Keywords: End-of-Life; allocation; life cycle inventory (LCI); material selection;
design for environment (DfE); environmental decision making
OPEN ACCESS
Sustainability 2013, 5 4547
1. Introduction
The discussion of recycling in attributional Life Cycle Assessment (LCA)and of metal recycling
in particular—has been mostly around two approaches: the ―avoided burden‖ approach, also called
―End-of-Life (EoL) recyling‖, and the ―recycled content‖ approach, also called ―cut-off method [19].
Both approaches represent variants of an EoL allocation, where the burden of primary material
production is distributed between the first and the subsequent life cycle [10]. The avoided burden
approach includes the full burden of EoL recycling (i.e., collecting, sorting, remelting and casting) in
the first life cycle and then allocates as much of the primary material burden to the subsequent life
cycle as secondary material can be recovered. The recycled content approach, on the other hand, draws
the system boundary at the point of scrap generation and allocates all burden of primary material
production to the first life cycle [1].
In 2007, seventeen major metal associations officially endorsed the avoided burden approach as
recommended practice for metal recycling in LCA [11]. Yet, this endorsement did not directly address
the problem of downcycling, which can be frequently observed in open-loop recycling systems,
―where the material is recycled into other product systems and the material undergoes a change to its
inherent properties‖ [10].
Downcycling appears when scrap is either polluted with undesirable elements or mixed with lower
quality scrap grades in a way that the secondary material displays a change in inherent properties,
such as reduced mechanical performance. A common example is the open-loop recycling of mixed,
post-consumer aluminum scraps to secondary cast alloys without any significant dilution with primary
material. The resulting secondary alloy could not substitute primary cast alloys in any application due
to its inherent impurities (e.g., Fe, Zn, Cr) and less tight chemistry limits, which would ultimately lead
to lower mechanical performance [12]. Automotive engine blocks are a common example of such
bottom reservoirs for low quality alloys [13].
In such cases, crediting 100% of the burden of primary aluminum as the avoided burden does not
seem appropriate as the secondary material is not capable of substituting its primary counterpart in all
those applications that exhibit low tolerances towards these impurities such as load-carrying
automotive parts in the chassis or body [14]. In addition, giving the full credit regardless of this quality
loss indirectly advocates the creation of low-quality scraps, which over time degrades the global
aluminum material pool and increases the overall effort to maintain the standard quality of aluminum
products [15]. Value-Corrected Substitution (VCS) has been identified as one feasible way to account
for quality losses over a product’s life cycle.
The aim of this paper is to revise the existing VCS methodology in order to eliminate its remaining
shortcomings. To achieve this goal, Section 2 critically evaluates the current approach and summarizes
the basic approach as well as its advantages and shortcomings. Section 3 then continues by proposing a
method revision that is essentially based on a different system boundary and the use of scrap prices
instead of a solitary secondary material price to address downcycling. Section 4 then shows the results
of a statistical price data analysis and discusses the remaining particularities and limitations of the
revised approach before Section 5 gives a brief summary.
Sustainability 2013, 5 4548
2. Critical Evaluation of the Current Approach to Value-Corrected Substitution
The original Value-Corrected Substitution (VCS) methodology has been discussed in various
publications [1618]. In 2002, the Swiss EMPA published a research report which gives the most
complete and in-depth description of the method [19]. The European Aluminium Association (EAA)
today allows the use of Value-Corrected Substitution if ―the inherent properties are changed‖ and if
the market value analysis shows a difference between the market value of the primary material and
the market value of the corresponding recycled material obtained at the End-of-Life[20]. It has
further been referenced in various publications [2123].
According to the original approach, substitution is only partial if the inherent material properties are
changed over a products life cycle in the sense of downcycling. The environmental interventions
(i.e., the life cycle inventory) of the substituted product system are then multiplied by a correction
factor β that reflects the value of the secondary output material in relation to the value of the primary
input material. The same logic is applied to any secondary inputs to the primary production process
using a correction factor α (Equations (13)).
Epp(Pn) = α x Epp − β x Epp = (α − β) x Epp
(1)
α = (pIM/pPM)
(2)
β = (pOM/pPM)
(3)
with
Epp: environmental interventions related to primary production
Pn: product n
α: price ratio of input material into primary production to output material
β: price ratio of secondary output material to primary output material
pIM: price of input material
pPM: price of primary material
pOM: price of output material
The difference β) hence expresses the degree of downcycling. Since α = 1 for products made
from 100% primary aluminum, formula (1) can be reduced to:
Epp(Pn) = (1 β) x Epp
(4)
The correction factor β is established by dividing the London Metal Exchange (LME) quotation for
secondary Al alloys (pOM) by the LME price for primary Al99.7 (pPM), resulting in a correction factor of
β = 0.9, which is shown to be robust towards market fluctuations over time. The subsequent
application to a case study of two different Al window frames (Al and Al(Zn)) is then performed by
matching the alloy composition of the product scrap (incl. steel, brass, and (Zn)Al components) to
the alloy compositions of the LME grades. Based on similarity, the choice is then made between a
value-corrected substitution (β = 0.9) and a full substitution (β = 1).
The described procedure displays some notable benefits which shall be summarized shortly:
It emphasizes re-collection and re-processing.
It supports decisions towards closing material cycles that preserve high material quality.
Sustainability 2013, 5 4549
It incentivizes applications that allow an efficient and value-preserving recycling.
The two LME quotes are readily available, their ratios stability over time has been
demonstrated, and they are easy-to-use for practitioners.
But there are also some shortcomings which need to be taken into account:
In practice, the scrap composition does not necessarily correspond to the composition of the
product under study. While scrap and product composition may have been identical in the
original case study of window frames [19], the described approach is not applicable to products
or components which are part of and/or recycled in conjunction with other products or
components of a different and unknown composition, e.g., home appliances, consumer
electronics, End-of-Life vehicles, etc., which may lead to the pollution of the aluminum fraction
with undesirable elements and cause a change in the inherent properties of the material.
The LME Al alloy quotation only represents a limited array of secondary alloys, which are very
similar in composition (Al-Si-Cu according to DIN 1725-5:1986 GBD-AlSi9Cu3, AA A380.1,
ASTM B179, JIS H2118-1976 D12S). These workhorse alloys do not necessarily represent the
actual quality loss in any given situation, i.e., the product-specific pollution with undesirable
elements. This rather rough and hypothetical one-price-fits-all approach, which addresses
downcycling as a digital yes-or-no-decision, therefore lacks the granularity to account for
different levels of downcycling as they may occur in practice.
As shown in Figure 1, the two processes of primary alloy production from unalloyed aluminum
and secondary alloy production from Al scraps are directly comparable in terms of their
function, i.e., they both produce a technical Al alloy from aluminum-rich raw materials. It then
seems questionable to compare the price of the primary raw material input (unalloyed Al99.7) to
the price of the secondary material output (technical Al alloy) if the goal is to compare market
values at the point of substitution.
Also shown in Figure 1, the value (and burden) added to the product scrap by mixing it with
other scraps, primary Al or other alloying elements in the recycling process then needs to be
accounted for specifically for the product scrap under study. Since most practitioners will use
the readily available inventory data published by industry to model the recycling, this introduces
a bias to the calculation of the product-specific degree of downcycling as these represent
industry-average, but not product-specific additions of primary aluminum, other product scraps,
and/or alloying elements.
In summary, it can be said that the Value-Corrected Substitution approach in use today focuses on
product composition instead of the actual scrap flow composition, that it lacks the ability to distinguish
different levels of downcycling due to the use of a solitary secondary alloy price, that the chosen prices
do not properly reflect the point of substitution, and that it disregards the scrap-specific addition of
recycling inputs which may occur in order to create marketable secondary alloys from the product
scrap under study. It is therefore worthwhile to investigate whether the method can be revised to avoid
these shortcomings in future LCA studies.
Sustainability 2013, 5 4550
Figure 1. System boundary in the original value-corrected substitution (VCS) method.
3. Method Revision
3.1. Redefining the Point of Substitution
According to the original VCS method, one of the key prerequisites for the application of
Value-Corrected Substitution is that the price ratio of primary material and further material grades
must be determinable for similar (re-)processing stages. As argued in the previous section and
indicated by the gray rectangle in Figure 2, the recycling process of re-melting and alloying
closely corresponds to the production of primary alloys. In both processes, an aluminum-rich
raw material input is supplemented by additional alloy input(s) to create a material output of a
desired specification. Note that the LME primary aluminum price and available inventory datasets
represent Al99.7, which is rarely found in technical applications without further alloying.
Following the original VCS method, one would use the price of the secondary material output
(technical Al alloy) as the indicator to quantify the quality loss inflicted upon the primary raw material
input (unalloyed Al99.7) which can be causally assigned to the product under study. To properly
reflect the point of substitution, it seems much more reasonable to either compare the prices of the two
inputs into alloy making (i.e., the price of unalloyed Al99.7 to the price of the product-specific scrap
flow under study), or the prices of the two outputs from alloy making (i.e., the price of the primary
technical Al alloy to the price of the secondary technical Al alloy).
Note that ISO 14044, Section 4.3.4.3.4 is not entirely clear on this issue as it gives both the market
value of the scrap material as well as that of the recycled material in relation to market value of the
primary material as an example for an economic allocation [10]. This language actually covers all
three variants (input-input, output-output, input-output comparison) depending on whether one's
interpretation of the term primary material includes or excludes an intermediate material such as
Al99.7.
To avoid the bias introduced by any additional alloying or scrap mixing before or during remelting,
which is not properly captured by industry-average inventories on scrap remelting, it appears best to
assess the quality loss over the products life cycle by comparing the market values of the two input
materials into alloy making, i.e., those of primary aluminum Al99.7 and aluminum product scrap.
Sustainability 2013, 5 4551
Note that ISO 14044, Section 4.3.4.3.4 explicitly allows the use of the market value of scrap materials
whenever physical properties are not possible or appropriate [10].
The above requires an adjustment of the system boundary: the remelting and alloying process is not
considered part of the product system under study anymore, but rather considered to be the
manufacturing process of the secondary materials subsequent life cycle (Figure 2). The remaining
scrap flow is then credited using a value-correction factor γ that is based on its market price:
γi = pi/pPM
(5)
with
pi: price of scrap class i
pPM: price of primary material
Figure 2. System boundary adjustment in the revised VCS method.
By using the scrap value instead of the secondary material value, the actual, product-specific scrap
quality is accounted for. Note that the scrap price directly accounts for the subsequent effort to turn the
scrap back into a marketable alloy, i.e., clean scraps that can be directly remelted without any
addition of primary materials or other scraps would have a much higher value than heavily polluted
ones that require mixing with higher quality scraps and/or dilution with primary aluminum. As a
result, the bias introduced to the assessment of the product-specific degree of downcycling by the
industry-average addition of any primary aluminum and/or other alloys or scraps before or during
remelting can be avoided. At the same time, the methodology does not depend on a single price point
for secondary Al alloy as available from LME anymore, and is therefore opened up to account for
various degrees of downcycling as they appear in practice.
Nevertheless, Formula 5 is not yet complete. There are some scrap classes that only need to contain
relatively low percentages of aluminum alloys, which in turn reduces their market value (in this paper,
the term ―aluminum alloy‖ refers to all traded forms of aluminum from ingot to semi-finished goods
made from aluminum alloys, and is not to be confused with the pure Al content reported in elementary
analyses). For all cases where the aluminum alloy content of the product under study significantly
exceeds the required minimum alloy content of the scrap class that it is traded in, its value would
actually be over-corrected. In order to align the aluminum alloy contents of the product scrap under
study with the respective scrap class for such cases, the value correction factor γi would need to be
Sustainability 2013, 5 4552
supplemented by an alloy content correction factor cp,i, which adjusts the aluminum alloy content
of the scrap class to that of the product under study (Equation (6)). That way, a higher-than-necessary
(or lower-than-necessary) contribution of aluminum alloy to the traded scrap class by the product
under study can be properly accounted for.
γ*p,i = γi x cp,i = γi x ap/amin,i
(6)
with:
γ*p,i: content-corrected value correction factor of product p in scrap class i
γi: value correction factor from Equation (5)
cp,i: alloy content correction factor of product p in scrap class i
ap: alloy content of product p as it enters scrap class i
amin,i: minimum permitted alloy content of scrap class i
Note that the content-correction constitutes a what-if scenario at this point. In practice, it is
reasonable to assume that product scraps will be traded in a scrap class that corresponds either to their
specific product category or to their material contents, or that they will undergo separation steps until
such waste fractions are created. It is only in those cases where this is not the case, that a content
correction would become necessary.
3.2. Price Data Analysis
Another key prerequisite for the application of Value-Corrected Substitution is that the price ratio of
primary material and further material grades must be stable over time in a developed market.
Availability of scrap prices has been limited in the past, but due to increasingly global and competitive
scrap metal markets and advances in online trading systems, it has improved significantly over the last
couple of years. ScrapIndex.com, for example, is a business-to-business web platform which tracks the
prices of a multitude of different scrap classes based on actual transactions between scrap sellers and
scrap buyers. For the US market, it distinguishes over 25 scrap classes for aluminum alone which
generally follow the Institute of Scrap Recycling Industries (ISRI) classifications [24].
In order to assess the stability of the price ratios for use in Value-Corrected Substitution, the
available historical US scrap price data (based on gross scrap masses) was procured in 2011 for the
years 2007 to 2010 (no data was available for prior years), and analyzed together with the
corresponding LME data on primary aluminum (cash buyer monthly averages). In addition, price data
for the scrap class Automotive Aluminum Fragments was purchased for the time period of August
2010 to September 2011 and analyzed together with the corresponding LME data as no prior data was
available for this more recently added scrap class.
ScrapIndex.com further distinguishes between prices for truck load (TL) and
less-than-truck-load (LTL) quantities. Since truck load prices are the higher ones and therefore closer
to the true material value, they were chosen to eliminate the bias of the delivery quantity from
the analysis.
Sustainability 2013, 5 4553
4. Results and Discussion
4.1. Price Data Analysis Results
Figure 3 shows the results regarding the average price ratio per scrap class, the corresponding
standard deviation, and the coefficient of correlation.
Figure 3. Results of aluminum price analysis for US scrap prices 20072010.
Table 1 shows that the scrap prices display a very strong correlation with the primary LME price.
The lowest correlation ρi to be found is 97.9% (Aluminum Auto Fragments), and the highest 99.91%
(Aluminum Nodules, Utensil Aluminum Scrap, Old Mixed Scrap Aluminum, and Scrap Auto
Transmissions). In fact, all scrap classes except Aluminum Auto Fragments show a correlation greater
99% as this value represents an outlier due to the limited availability of data (14 instead of 48 data
points). The minimum correlation across 48 months for all other scrap classes is 99.75%. The average
price ratio (i.e., the proposed correction factor γi) varies between 10% (Scrap Low Grad Irony
Aluminum and Scrap Paperbacked Aluminum Foil) and 109% (Aluminum Nodules) with very low
standard deviations between 0.2% and 1.1%.
Sustainability 2013, 5 4554
Table 1. Correlation factor ρ, value correction factor γ, minimum permissible alloy content
amin, maximum content correction factor cmax and maximum content-corrected value
correction factor γ*max per scrap class i.
Scrap class i
γi
amin,i
cmax,i
γ*
max,i
Scrap Low Grade Irony Aluminum
10% (±0.2%)
50%
2.0
20%
Scrap Paperbacked Aluminum Foil
10% (±0.2%)
n/a
n/a
n/a
Painted Aluminum Insulated Scrap
15% (±0.2%)
n/a
n/a
n/a
Aluminum Auto Fragments
21% (±0.5%)
50%
2.0
42%
Scrap Auto Transmissions
22% (±0.2%)
n/a
n/a
n/a
Aluminum Turnings
25% (±0.3%)
90%
1.1
28%
Scrap Mixed Irony Aluminum
25% (±0.3%)
70%
1.4
35%
Scrap Aluminum Auto Rads
32% (±0.3%)
n/a
(1.0)
32%
Old Mixed Scrap Aluminum
35% (±0.3%)
99%
1.0
35%
Scrap Clean Painted Aluminum
40% (±0.4%)
n/a
(1.0)
40%
Utensil Aluminum Scrap
45% (±0.4%)
99%
1.0
45%
Used Beverage Cans (UBC loose)
50% (±0.6%)
n/a
(1.0)
50%
Scrap Insulated Aluminum Wire
50% (±0.5%)
n/a
n/a
n/a
Scrap Supported Aluminum Cable
58% (±0.6%)
n/a
n/a
n/a
Scrap Aluminum Foil
60% (±0.6%)
n/a
(1.0)
60%
Remelt Aluminum Ingot
69% (±0.7%)
n/a
(1.0)
69%
Scrap Coated Aluminum
70% (±0.7%)
n/a
(1.0)
70%
Scrap Aluminum Auto Wheels
70% (±0.7%)
n/a
(1.0)
70%
Remelt Aluminum Sows
72% (±0.7%)
n/a
(1.0)
72%
Shredded UBC
75% (±0.7%)
n/a
(1.0)
75%
Baled UBC
78% (±0.8%)
n/a
(1.0)
78%
Briquetted UBC
80% (±0.8%)
n/a
(1.0)
80%
New Beverage Can Stock Scrap
84% (±0.8%)
n/a
(1.0)
84%
Scrap Cast Aluminum
89% (±0.9%)
98%
1.0
89%
Scrap Bare Aluminum Wire
89% (±0.9%)
99%
1.0
89%
Scrap Litho Sheets
92% (±1.0%)
n/a
(1.0)
92%
Scrap Low Copper Aluminum
93% (±0.9%)
99%
1.0
93%
Scrap Aluminum Extrusions
94% (±0.9%)
n/a
(1.0)
94%
Aluminum Nodules
109% (±1.1%)
99%
1.0
109%
The ascertained price ratios also demonstrate the general correlation between material quality and
scrap price, which is one of the basic assumptions behind this method. Alloy content, pollution with
copper or iron, and mixing of alloy groups all lower the economic value of the scrap classes. In order
to produce a marketable secondary alloy, these scraps would have to be either mixed with higher
quality scraps or diluted with primary aluminum. It therefore seems appropriate that lower value scraps
are also awarded a lower substitution factor. Note that this does not necessarily mean that the resulting
secondary material made from these scraps displays a higher degree of downcycling, but vice versa
that the effortand environmental burdento return to the same (primary) material quality as
expressed by the Al 99.7 LME quotation would be higher for the lower-value scraps.
For all cases where a content correction as outlined in Section 3.1 should become necessary, Table 1
additionally shows the minimum aluminum alloy content amin,i ascertained from scrap class
Sustainability 2013, 5 4555
specifications (where applicable), the corresponding maximum content correction factor cmax,i (which
assumes a product aluminum alloy content of 100%), and the resulting maximum content-corrected
value correction factor γ*max,i according to Equation (6).
4.2. Discussion
4.2.1. Remaining Data Gaps
For some scrap classes, the specifications do not explicitly state the minimal required aluminum
alloy content, but they can be regarded as pure aluminum alloy scraps based on the given
descriptions where any non-aluminum alloy contents below a total of 2% of mass are considered
negligible [24,25]. In those cases, Table 1 denotes cmax,i as (1.0). Only 5 out of 29 scrap class
specifications do not specify minimum aluminum alloy contents, but are likely to contain significant
amounts of foreign materials: Scrap Paperbacked Aluminum Foil, Painted Aluminum Insulated Scrap,
Scrap Auto Transmissions, Scrap Insulated Aluminum Wire, and Scrap Supported Aluminum Cable.
For these scrap classes, estimates for ranges of aluminum alloy content could be established on a
case-specific basis in collaboration with respective industry members or from published literature. For
Scrap Auto Transmissions, for example, it is known that the aluminum alloy content of disassembled
auto transmissions with a cast aluminum housing is roughly between 20% and 30% depending on
whether they have been drained or not [26]. Using this range, a sensitivity analysis can be carried out
on the content correction factor for an aluminum transmission housing (ap = 100%) in that scrap class.
In general, though, one should aim to model the EoL pathway up to the point of separation of ferrous
metals, plastics, oils and other foreign materials in order to avoid the uncertainty introduced by this
type of estimation.
4.2.2. Substitution Factors Greater 100%
Table 1 shows that the maximum possible value correction factor is 109% for the scrap class
Aluminum Nodules. Aluminum Nodules consist of ―clean aluminum wire recovered from a
chopping operation and being free of iron, copper and brass wire, aluminum hair wires and free of dirt,
oil and foreign materials‖ [25]. This corresponds to the Aluminum Associations (AA) alloy grades
1350, 8030, and 8176. The original VCS method discussed the possibility of a correction factor greater
one hundred percent for secondary alloys due to price fluctuations and markets distortions in the
original method, and recommended the use of other allocation methods in this case.
For the adjusted system boundary at hand, a correction factor greater one is nevertheless reasonable
since the processing into the alloys for nodule production adds additional value to the original LME
raw material grade (Al99.7). If this value is preserved along the life cycle and results in a high-quality
(i.e., high-value) aluminum scrap, then a credit greater 100% primary Al99.7 is fully justified if
(and only if) the additional burden of producing these alloys from Al99.7 is likewise accounted for in
the manufacturing phase to avoid creating an overall net-negative burden.
Sustainability 2013, 5 4556
4.2.3. Key Limitations
Economic allocation is often applied in lack of better allocation keys and therefore only the
second-best option to solve the allocation problem in End-of-Life recycling (see ISO 14044,
Section 4.3.4.3.4). Scrap prices in particular are influenced by a wide array of aspects like supply
and demand, delivery form and quantity, transportation distances, moisture or lubricant content,
pre-treatment and re-melting technologies, etc., which do not influence the actual material quality in terms
of their inherent properties.
Considering the logistical effort to collect the scrap, it is obvious that this will skew the scrap price
with regard to the actual material quality. Small scrap quantities that are highly dispersed over a large
area would drive the logistical costs of collection and delivery upwards. However, the scrap price data
displayed in Figure 3 and Table 1 are averages based on real-life transactions, hence representing an
average (i.e., a moderate) logistical scenario rather than an extreme one. Also, they are explicitly based
on truck load quantities (as opposed to less-than-truck-load (LTL) quantities), hence already excluding
the costly collection of scattered scraps in low quantities.
With regard to the necessary pre-treatment and remelting technologies, the different scrap classes
and prices of used beverage cans (UBC) demonstrate that the system boundary needs to be set with
caution. Note that while UBCs demonstrate how delivery form will affect the scrap price, in practice,
they don’t lend themselves to Value-Corrected Substitution as they represent a closed-loop recycling
situation where a conventional avoided burden approach is sufficient. As can be seen from Table 1, the
process steps of collecting, shredding, baling and briquetting used beverage cans (UBCs) each add
value to the scrap without altering the material quality in a sense that would be relevant in terms of
downcycling (i.e., pollution with undesirable elements, mixing of alloy groups, etc.). Any scrap
treatment that represents an upcycling measure in terms of scrap value therefore needs to be included
in the assessment. This means that the system boundary needs to be drawn right before the scrap is
either mixed with scraps from other product systems or right before it enters the remelting step. This
final scrap value then best corresponds to the product-specific scrap quality and serves as an
indicator of the hypothetical effortand environmental burdento return the material to its original,
primary quality. While inventory data for any additional treatment steps may not be readily available
as some secondary smelters perform these on-site without any separate accounting of energy or
material consumptions and their additional environmental burden may be neglected from a cradle-to-
grave perspective, the value added to the scrap by them cannot be disregarded.
For the case of the UBCs, after it would have been shredded and decoated prior to remelting [27],
the scrap would once again qualify as Scrap Low Copper Aluminum with a value-correction factor of
93%. So the actual material value exceeds what is captured by all four dedicated UBC scrap classes
as the scrap preparation is not entirely accounted for by these values. It is important to note that a
value-correction factor of 93% closely corresponds to the magnitude of the net credit across key
impact categories when applying a closed-loop avoided burden approach, where the benefit of the
avoided burden of 100% primary aluminum is reduced by the additional burden of aluminum scrap
recycling [28]. As UBCs are a prime example of closed-loop recycling and would be modeled using a
closed-loop avoided burden approach, having the two approaches come to comparable results speaks
Sustainability 2013, 5 4557
to the feasibility of the described approach if (and only if) the scrap value is established at the
appropriate point of substitution.
The application of the proposed approach in practice is therefore limited by the knowledge of the
LCA practitioner with regard to the scrap class that is the most appropriate for the product scrap under
study at the point of substitution. To properly address the above limitations, the practitioner should
perform the following steps when applying the methodology:
(1). Investigate whether closed-loop recycling systems exist for the product(s) under study. Like for
the discussed case of used beverage cans (UBCs), these products should be modeled using a
conventional avoided burden approach rather than the proposed methodology.
(2). If the product is recycled in an open-loop recycling system, ascertain the most likely scrap
class(es) that the product scrap will be traded in. The corresponding descriptions from
ScrapIndex.com and the Institute of Scrap Recycling Industries (ISRI) will be helpful when
doing so.
(3). Investigate whether the scrap stream will undergo any additional pre-treatment steps prior to
being mixed with scraps from other product systems or entering the remelting step. If any such
upcycling takes place, establish the appropriate higher-value scrap class that best matches the
resulting scrap stream.
(4). If the aluminum alloy content of the product(s) under study is significantly different from the
minimum alloy content of the chosen scrap class (see Table 1), perform a content-correction
as described in Section 3.1.
(5). Use the resulting value-correction factor(s) to substitute primary aluminum (Al99.7) with the
scrap quantity in question.
(6). Perform a sensitivity analysis to test the influence of varying substitution factors on the
final results of your study. This should include conventional cut-off and avoided burden
scenarios.
For a critically reviewed, comparative case study applying the outlined procedure to establish the
effect of this choice on the overall study results, please refer to www.alcoawheels.com/LCA.
5. Conclusions
The ratio of LME primary Al price and Al scrap prices has been shown to be a feasible measure to
assess the level of aluminum downcycling over a products life cycle, if (and only if) the point of
substitution is identified appropriately. The main advantages of the revised Value-Corrected
Substitution Procedure can be summarized as follows:
a. It incentivizes the creation of high-quality scrap in a more stringent way than the original
approach by significantly increasing the penalty for the pollution of the aluminum scrap stream
with undesirable elements or the mixing with lower grade scraps.
b. The use of different scrap classes provides more granularity and allows for the proper
appraisal of Design-for-Recycling measures, as well as of additional upcycling measures in the
End-of-Life phase, which is the basis for more informed decisions about costs and benefits of
different recycling options.
Sustainability 2013, 5 4558
The developed procedure displays all the benefits of the original Value-Corrected Substitution
procedure in terms of appropriateness, practicability, and ISO-compliance while avoiding its main
pitfalls: the one-price-fits-all approach, the consideration of product instead of scrap composition,
the comparison of input to output material prices, and the inclusion of additional material inputs into
alloy recycling which cannot be causally assigned to the product under study. It can therefore be
recommended to inform decision making for all cases where downcycling of aluminum is known to be
an issue.
Its key limitation remains the correct identification of the appropriate point of substitution along the
scrap value chain. If relevant pre-treatment steps are omitted, the substitution factor would be
overcorrected, which is why it is crucial to establish the scrap value right before the scrap is either
mixed with scraps from other product systems or right before it enters the remelting step.
While aluminum has been the prime case study for the Value-Corrected Substitution procedure in
the past, the general approach can in principle be applied to other materials which encounter
downcycling issues provided the available price data allows for it. Typical examples for such materials
are steel, which is especially sensitive to pollution with copper, and plastics that end up in mixed scrap
fractions which prevent a high-quality recycling of technical polymers. Especially in comparative
studies, it is essential that the same allocation procedure is applied to account for downcycling effects
of either material.
In concluding, it should be noted that the presented procedure is not meant to be the only viable
solution to modeling downcycling of aluminum. Instead, it provides the LCA practitioners with an
additional tool in their toolbox in cases where downcycling is known to be an issue. The procedure can
therefore be recommended as part of a comprehensive analysis using different EoL allocation
approaches to facilitate more informed decisions.
Acknowledgments
The authors would like to thank Christian Leroy (European Aluminum Association), Kurt Buxmann
(LCA consultant to the International Aluminum Association), and J. Marshall Wang (Aluminum
Association) for the open discussion and critical feedback. Please note that this acknowledgement does
not imply an endorsement by any of the affiliated organizations.
Conflicts of Interest
The authors declare no conflict of interest.
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We consider interactions between life cycle emissions and materials flows when design options such as lightweighting are considered for next generation vehicles designed in response to government policies on greenhouse gas emissions. We establish a framework that can be utilized in future work to extend the considerations of rebound effects into the realm of materials supply chains: recognizing for instance that an intense demand for material in a major industrial sector could increase prices of the material, and help to defeat the design approach or increase burdens in other sectors. Such shifts can also impact the means or locations of material production, resulting in increased emissions from shifts to more carbon-intense sources, or decreased emissions due to economies of scale in a more mature recycling infrastructure. The research described in this paper lays the groundwork for this analysis, and is one of several new research activities associated with the first year of our recent award to study the optimization of greenhouse gas policies for the automotive sector within the NSF MUSES program. See: http://sitemaker.umich.edu/autopolicydesign/home
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To reach required product qualities with lowest costs, aluminum postconsumer scrap is currently recycled using strategies of downgrading and dilution, due to difficulties in refining. These strategies depend on a continuous and fast growth of the bottom reservoir of the aluminum downgrading cascade, which is formed by secondary castings, mainly used in automotive applications. A dynamic material flow model for the global vehicle system was developed to assess the likelihood, timing, and extent of a potential scrap surplus. The results demonstrate that a continuation of the above-mentioned strategies will lead to a nonrecyclable scrap surplus by around 2018 ± 5 if no additional measures are taken. The surplus could grow to reach a level of 0.4-2 kg/cap/yr in 2050, corresponding to a loss of energy saving potential of 43-240 TWh/yr electricity. Various intervention options for avoiding scrap surplus are discussed. Effective strategies need to include an immediate and rapid penetration of dramatically improved scrap sorting technologies for end-of-life vehicles and other aluminum applications.
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Allocation in LCA is defined as partitioning the responsibility for environmental burdens from the economic activities to a reference flow or a reference life cycle system in some proper shares. The result of LCA study involving a multi-input/output system or an open loop recycling system is affected significantly by the choice of the allocation method. For the case of allocation in a cascade recycling system, the quality of material as well as the material flow should be considered. Therefore, environmental burdens from the primary material production, the recycling process and the waste management process have to be allocated in proportion to the quality degradation of a material and to the quantity of a material used in each life cycle system. This paper proposes an allocation method for the cascade recycling system that considers both quality and quantity of a material used.
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Recycling of a product can lead to the same product or to other products. Within the Inventory Analysis of LCA, the first process is called closed-loop recycling and poses relatively small methodological problems, whereas the second, open-loop recycling, involves major allocation problems. Basically, open-loop recycling creates a new, larger system which should be treated as one system in the inventory analysis from a scientific point of view. Since this is frequently not possible, allocation rules have to be applied in order to treat one of the subsystems separately. In this review, the different allocation rules proposed are presented and discussed with respect to the criteria of mathematical neatness, feasibility and justice/incentive for both producers and users of secondary raw materials.
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Background In the years 2000 and 2002, the German Environment Agency in Berlin (UBA) published the results of a comprehensive LCA study on beverage containers comprising aluminium cans with volumes of 330 ml and 500 ml. Starting with the aluminium can scenarios and the respective results obtained during the UBA study, additional analyses were performed by IFEU in 2003, a German consultant having been a member of the project team working on the UBA study. The objective was to examine the influence of selected parameters on the LCA profile of carbonated soft drink containers. Data and method were in complete analogy with the LCI and LCA part of the UBA study. Materials In 2006, the aluminium industry commissioned a study on further influential factors that help determine the sale of certain types of beer, studying the effects of two selected parameter settings on the comparative results of the aluminium can against the refillable glass bottle. In this scenario, special attention was given to two influential factors, the distribution distance—distinguished by regional and nationwide distribution—and trippage rate. Results and discussion The results of the initial LCA from the years 2000 and 2002 showed, for the examined parameters container weight, rate of post-consumer recovery of used containers, degree of recycled content and quality of the recycling routes, that each had a considerable influence on the environmental impact profile of the aluminium can within the given framework. Can weight and recycling rate were sensitive factors in the impact categories of climate change, fossil resources, summer smog (POCP), acidification and terrestrial eutrophication. Can volume affected virtually all impact categories examined. Conclusions By now, individual improvement options have already been put into practice in Germany. The environmental profile of the average 330 ml aluminium can on the German market can be expected to be ahead of that of the aluminium can at the time of the UBA study. The introduction of a 500-ml can on the market denotes a fundamental step forward in improving LCA results of the aluminium can as a container for beverages.