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Life Cycle Assessment of POLYLACTIDE (PLA) A comparison of food packaging made from NatureWorks ® PLA and alternative materials Final Report IFEU Heidelberg July 2006 Commissioned by NatureWorks LLC

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Page 1: Life Cycle Assessment of P LACTIDE (PLA) - ifeu zu PLA erstellt fuer...Life Cycle Assessment of PLA A comparison of food packaging made from NatureWorks® PLA and alternative materials

Life Cycle Assessment of POLYLACTIDE (PLA)

A comparison of food packaging made from NatureWorks® PLA and alternative materials

Final Report

IFEU Heidelberg

July 2006

Commissioned by

NatureWorks LLC

Page 2: Life Cycle Assessment of P LACTIDE (PLA) - ifeu zu PLA erstellt fuer...Life Cycle Assessment of PLA A comparison of food packaging made from NatureWorks® PLA and alternative materials
Page 3: Life Cycle Assessment of P LACTIDE (PLA) - ifeu zu PLA erstellt fuer...Life Cycle Assessment of PLA A comparison of food packaging made from NatureWorks® PLA and alternative materials

Life Cycle Assessment of PLA

A comparison of food packaging made from

NatureWorks® PLA and alternative materials

Final Report

Authors

Andreas Detzel

Martina Krüger

IFEU GmbH, Heidelberg, July 2006

Wilckensstraße 3; D-69120 Heidelberg

Tel.: +49 - 6221-47670, Fax: +49 - 6221-476719

E-mail: [email protected]

Page 4: Life Cycle Assessment of P LACTIDE (PLA) - ifeu zu PLA erstellt fuer...Life Cycle Assessment of PLA A comparison of food packaging made from NatureWorks® PLA and alternative materials
Page 5: Life Cycle Assessment of P LACTIDE (PLA) - ifeu zu PLA erstellt fuer...Life Cycle Assessment of PLA A comparison of food packaging made from NatureWorks® PLA and alternative materials

IFEU-Heidelberg LCA for food packaging from PLA and alternative materials

Final Report

CONTENTS

ABBREVIATIONS

SUMMARY.............................................................................................................................................I

1 GOAL AND SCOPE DEFINITION ............................................................................................ 1

1.1 BACKGROUND AND OBJECTIVES.............................................................................................. 1 1.1 ORGANISATION OF THE STUDY................................................................................................ 3 1.2 CRITICAL REVIEW PROCESS..................................................................................................... 4 1.3 USE OF THE STUDY AND TARGET GROUPS ............................................................................... 4 1.4 PRODUCT FUNCTION / FUNCTIONAL UNIT ............................................................................... 4 1.5 SYSTEM BOUNDARIES.............................................................................................................. 5 1.6 DATA GATHERING AND DATA QUALITY .................................................................................. 6 1.7 MODELLING AND CALCULATION OF INVENTORIES.................................................................. 7 1.8 ENVIRONMENTAL IMPACT ASSESSMENT AND INTERPRETATION ............................................. 8 1.9 ALLOCATION AND CREDITING PROCEDURE........................................................................... 11

2 PACKAGING SYSTEMS AND SCENARIOS UNDER STUDY ........................................... 16

2.1 PACKAGING SPECIFICATIONS................................................................................................. 16 2.2 END OF LIFE SETTINGS........................................................................................................... 17 2.3 SCENARIOS EXAMINED .......................................................................................................... 20

3 DESCRIPTION OF SELECTED INVENTORY DATA......................................................... 29

3.1 POLYMER PRODUCTION ......................................................................................................... 29 3.2 CONVERSION OF POLYMER PELLETS INTO CLAM SHELLS ...................................................... 36 3.3 RECOVERY AND RECYCLING OF USED CLAM SHELLS ............................................................ 36 3.4 BACKGROUND DATA.............................................................................................................. 39

4 RESULTS..................................................................................................................................... 41

4.1 BASE SCENARIOS................................................................................................................... 43 4.2 PLA SCENARIO VARIANTS .................................................................................................... 52

5 EVALUATION............................................................................................................................ 69

5.1 DETERMINATION AND EVALUATION OF SIGNIFICANT PARAMETERS..................................... 69 5.2 SENSITIVITY ANALYSIS ......................................................................................................... 71 5.3 LIMITATIONS AND DATA QUALITY ISSUES............................................................................. 89

6 DISCUSSION............................................................................................................................... 92

REFERENCES .................................................................................................................................... 96

APPENDIX A: DESCRIPTION OF IMPACT CATEGORIES ................................................... 100

A.1 GLOBAL WARMING ................................................................................................................... 100 A.2 PHOTO-OXIDANT FORMATION (PHOTOSMOG OR SUMMER SMOG) ............................................ 101 A.3 EUTROPHICATION AND OXYGEN-DEPLETION............................................................................ 103 A.4 ACIDIFICATION ......................................................................................................................... 104

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LCA for food packaging from PLA and alternative materials IFEU-Heidelberg

Final Report

A.5 RESOURCE CONSUMPTION ........................................................................................................ 105 A.6 HUMAN TOXICITY..................................................................................................................... 109 A.7 REFERENCES ............................................................................................................................. 111

APPENDIX B: EXAMPLES FOR NORMALISATION AND RANKING ................................. 113

B.1 NORMALISATION ...................................................................................................................... 113 B.2 RANKING ................................................................................................................................... 117

APPENDIX C: REPRINT OF THE REVIEW REPORT FOR PLA DATASETS (2005 AND 2008) ................................................................................................................................................... 120

APPENDIX D: STATEMENT OF NATUREWORKS .................................................................. 122

APPENDIX E: SOIL CARBON SEQUESTRATION DURING CORN PRODUCTION ........ 124

APPENDIX F: NUMERICAL PRESENTATION OF THE RESULT GRAPHS OF THE SCENARIOS INVESTIGATED ...................................................................................................... 128

APPENDIX G: CRITICAL REVIEW REPORT.......................................................................... 138

APPENDIX H: SHORT INFORMATION ABOUT THE CRITICAL REVIEWERS.............. 146

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials

Final Report

ABBREVIATIONS

BP Biobased Polymers

CED Cumulative energy demand

COD Chemical Oxygen Demand

DKR German company for plastics recycling

DSD Dual System Germany AG

GPPS General Purpose Polystyrene

HBEFA Handbook of Emission Factors

IFEU Institut für Energie- und Unweltforschung GmbH Heidelberg

LA Lactic Acid

LCA Life Cycle Assessment

NCPOCP Nitrogen-Corrected Photochemical Ozone Creation Potential

MBA Mechanical-Biological Treatment

MPF Mixed Plastics Fraction

MSWI Municipal Solid Waste Incineration

NMVOC Non-Methane Volatile Organic Compounds

NOx Nitrogen Oxides

PET Polyethylene Terephthalate

PLA Polylactide

PM 10 Particulate matter with a diameter smaller 10 µm

POCP Photochemical Ozone Creation Potential

PP Polypropylene

PS Polystyrene

UBA Umweltbundesamt (German Federal Environmental Agency)

REC Renewable Energy Certificate

REQ Resident Equivalent

R-PET Recycled PET

SVZ Secondary raw material recovery centre

VOC Volatile Organic Compounds

V-PET Virgin PET

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) I

Final Report

SUMMARY POLYLACTIDE (PLA) is a new polymer family and currently the only commercial biopolymer made completely from renewable feedstock. Today NatureWorks LLC is the only large scale producer of PLA. The acronym “PLA”, in the context of this document, only refers to Nature-Works® PLA. The acronym “PLA5” refers to NatureWorks® PLA production in the year 2005.

NatureWorks LLC decided to commission a Life Cycle Assessment (LCA) in order to obtain comprehensive information about the environmental performance of packaging made from NatureWorks PLA under the framework of German conditions. Clam shells have been cho-sen as the packaging application to be examined.

Clam shells are small volume containers, consisting of a body and a lid like e.g. the sample shown in fig-ure 1. The clam shells addressed in this study are rigid thermoformed, transparent, have a volume of 500 ml and typically serve to pack food ready for take-away at the retail outlet.

Figure 1: Example for a clam shell

At the time of this study clam shells on the German market are usually made from polypro-pylene (PP), oriented polystyrene (OPS) and polyethylene terephthalate (PET). Clam shells from PLA are in use in several EU countries, like France and Italy, but not yet in Germany.

The French packaging producer Vitembal participated in the project and delivered relevant data needed for the LCA, particularly packaging specifications and polymer conversion data. In this respect, the LCA presented here should be regarded as a case study.

The study was conducted by IFEU-Heidelberg in the period of August 2004 to May 2006 and included a comprehensive stakeholder participation in form of a project panel. The LCA was designed to comply with the requirements as described in the international standards DIN EN ISO 14040-14043. ISO conformity was confirmed during a critical review process according to ISO 14040 (1997), § 7.3.3.

The objectives of the LCA study are:

a) to compare clam shells made from NatureWorks PLA (referred to in the study as “PLA”or “PLA5”) with clam shells from alternative materials;

b) to examine the effect of purchasing renewable energy certificates by NatureWorks (referred to in the study as “PLA6”) as well as next generation PLA production (re-ferred to in the study as “PLA/NG”) on the overall environmental profile of packages made from NatureWorks PLA and;

c) to examine the potential effect of selected PLA waste treatment options on the overall environmental profile of packages made from NatureWorks PLA.

The target audiences are

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II LCA for food packaging from PLA and alternative materials (Summary) IFEU-Heidelberg

Final Report

• NatureWorks key customers and brand owners and

• Public authorities (particularly the German Environmental Ministry1 and the Federal Environment Agency2).

The functional unit of this LCA is defined as 1000 units of 500 ml clam shells which are in-tended to be filled with cold foodstuff, for instance take-away salad, and are available for the consumer at the point-of-sale3.

For the packaging performance of clam shells the material stiffness is a prominent feature. Here, the relatively high elasticity modulus of PLA is particularly favourable (table 2-2). Simi-larly performing PLA clam shells can be produced with a weight smaller than any of the al-ternative polymers. The packaging weights applied in this study are shown in table 1.

Table 1: Overview of packaging weights for clam shells

Parameter PET PLA PP OPS

Weight (g)* 19.9 12.2 16.9 15.2

*: weight includes the clam shell lid; data source: Vitembal

Eight impact category indicators have been used to describe the environmental impact pro-files of the four packaging systems:

• Fossil Resource Consumption (weighted with a scarcity factor of fossil fuel)

• Global Warming (Climate Change)

• Acidification

• Terrestrial Eutrophication (i.e. Eutrophication of soils by atmospheric emissions)

• Aquatic Eutrophication (i.e. Eutrophication of aquatic ecosystems by effluents)

• Summer Smog (Photo-Oxidant Formation)

• Human toxicity as PM10-equivalents and As-equivalents

They were supplemented by four indicators at the inventory level (use of nature; total, re-newable and non-renewable cumulative energy demand).

1 Ministry within the German Federal Government which is responsible for (leadmanaging) national

environmental policy. 2 The Federal Environment Agency is the scientific environmental authority under the jurisdiction of the

Environmental Ministry providing, amongst others, environmental analyses and recommendations to the public as well as for political decision-making.

3 The study is only applicable to clam shells of similar dimensions and with a top load strength of about 22 Newton. The top load strength specified is characteristic for clam shells designated for light filling goods and is sufficient to assure the integrity of the clam shells during transport and use.

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) III

Final Report

PLA packages are not yet on the German market which makes it difficult to predict what will happen to the packages after the consumer use phase. If no changes in the infrastructure and organisation of waste collection are assumed, PLA material will be found in the packag-ing waste stream together with other packaging materials. It is likely that PLA is routed into the mixed plastics fraction in the first period after market introduction.

The end-of-life settings applied in this study are shown in table 2. Information from Duales System Deutschland AG served as a source.

Table 2: Assumptions regarding collection and recovery of used clam shells

Parameter PET PP PS (OPS) PLA A. Collection Quota (% of used clam shells), of which

80% 80% 80% 80%

A.1 Kerbside collection (delivered to sorting facilities)

95% 95% 95% 95%

A.2 Collection via recycling centres 5% 5% 5% 5%

B. Sorting Fractions

B.1 at sorting facilities

B.1.1 Mixed Plastics (MPF) 85% 77% 59% 85% B.1.2 Polymer fraction 0% 8% 26% 0% B.1.3 Sorting residues 15% 15% 15% 15%

B.2 at recycling centres

B.2.1 Mixed Plastics (MPF) 100% 0% 0% 100% B.2.2 Polymer fraction 0% 100% 100% 0%

C. Recovery Quota = A * (A.1*(B1.1+B1.2) + A.2 * (B2.1+B2.2))

69% 69% 69% 69%

D. Recycling of MPF

D1. Mechanical recycling 39% 33% 33% 0% D2. Feedstock recycling 61% 67% 67% 100%

E. Recycling of polymer fractions

E1. Regranulation -- 100% 78% -- E2. Bulky products -- 0% 22% --

F. Mechanical Recovery Quota 27% 29% 39% 0%

Altogether, the numbers listed in tables 1 and 2 build the most important underlying settings for the implementation of the base scenarios examined in this study. Simplified mass flow diagrams of the base scenarios are shown in figure 2.

Explanations of the underlying assumptions are kept short in this summary. More details can be found in the main report.

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IV LCA for food packaging from PLA and alternative materials (Summary) IFEU-Heidelberg

Final Report

Figure 2: Selected material and energy flows in the clam shell packaging systems examined

1.00.90.90.81.92.6Substitution factor (SF)

Virgin PETVirgin PPVirgin PSVirgin polymerWoodCementSubstituted product

PP regranulate

PET regranulate

PS regranulate

Mixed plasticsregranulateBulky productsSecondary product

1.00.90.90.81.92.6Substitution factor (SF)

Virgin PETVirgin PPVirgin PSVirgin polymerWoodCementSubstituted product

PP regranulate

PET regranulate

PS regranulate

Mixed plasticsregranulateBulky productsSecondary product

TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T T

Collection and sorting

Methanol: 1.36 kgE (thermal): 91 MJE (electric): 9 MJ

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Mixed plasticsfraction

8.37 kg0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJ

TransportT TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T TT

Collection and sorting

Methanol: 1.36 kgE (thermal): 91 MJE (electric): 9 MJ

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Mixed plasticsfraction

8.37 kg0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJ

PS fraction

Material Flows: Clam Shell from PSMaterial Flows: Clam Shell from PSMSWI

Point of Sale/Consumer

Extrusion andForming

PSgranules T T

Collection and sorting

Transport

15.68 kg 15.2 kg

FU: 1000 Clam Shells

T

3.04 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

6.86 kg

3.57 kg

PS regranulate: 2.88 kgBulky products: 0.16 kg

E (thermal): 55 MJE (electric): 20 MJ

Regranulate: 0.65 kgBulky products: 0.29 kgMethanol: 1.4 kgE (thermal): 106 MJE (electric): 11 MJ

0.48 kg(process waste)

PS fraction

Material Flows: Clam Shell from PSMaterial Flows: Clam Shell from PSMSWI

Point of Sale/Consumer

Extrusion andForming

PSgranules T TT

Collection and sorting

Transport

15.68 kg 15.2 kg

FU: 1000 Clam Shells

T

3.04 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

6.86 kg

3.57 kg

PS regranulate: 2.88 kgBulky products: 0.16 kg

E (thermal): 55 MJE (electric): 20 MJ

Regranulate: 0.65 kgBulky products: 0.29 kgMethanol: 1.4 kgE (thermal): 106 MJE (electric): 11 MJ

0.48 kg(process waste)

PP fraction

Material Flows: Clam Shell from PPMaterial Flows: Clam Shell from PPMSWI

Point of Sale/Consumer

Extrusion andForming

PPgranules T T

Collection and sorting

Transport

17.43 kg 16.9 kg

FU: 1000 Clam Shells

T

3.38 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

9.92 kg

1.68 kg

PP regranulate: 1.45 kgBulky products: 0.08 kg

E (thermal): 52 MJE (electric): 19 MJ

Regranulate: 1.83 kgBulky products: 1.2 kgMethanol: 1.75 kgE (thermal): 130 MJE (electric): 13 MJ

0.53 kg(process waste) PP fraction

Material Flows: Clam Shell from PPMaterial Flows: Clam Shell from PPMSWI

Point of Sale/Consumer

Extrusion andForming

PPgranules T TT

Collection and sorting

Transport

17.43 kg 16.9 kg

FU: 1000 Clam Shells

T

3.38 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

9.92 kg

1.68 kg

PP regranulate: 1.45 kgBulky products: 0.08 kg

E (thermal): 52 MJE (electric): 19 MJ

Regranulate: 1.83 kgBulky products: 1.2 kgMethanol: 1.75 kgE (thermal): 130 MJE (electric): 13 MJ

0.53 kg(process waste)

Material Flows: Clam Shell from PETMaterial Flows: Clam Shell from PETMSWI

Point of Sale/Consumer

Extrusion andForming

PETgranules T T

Collection and sorting

E (thermal): 43 MJE (electric): 15 MJ

Regranulate: 2.99 kgBulky products: 1.98 kgMethanol: 1.62 kgE (thermal): 114 MJE (electric): 11 MJ

20.52 kg 19.9 kg

FU: 1000 Clam Shells

TransportT

3.98 kg

15.92 kg

2.27 kg(sorting residues)

Mixed plasticsfraction

13.66 kg

0.72 kg(process waste)

Material Flows: Clam Shell from PETMaterial Flows: Clam Shell from PETMSWI

Point of Sale/Consumer

Extrusion andForming

PETgranules T TT

Collection and sorting

E (thermal): 43 MJE (electric): 15 MJ

Regranulate: 2.99 kgBulky products: 1.98 kgMethanol: 1.62 kgE (thermal): 114 MJE (electric): 11 MJ

20.52 kg 19.9 kg

FU: 1000 Clam Shells

TransportT TransportT

3.98 kg

15.92 kg

2.27 kg(sorting residues)

Mixed plasticsfraction

13.66 kg

0.72 kg(process waste)

23333918Lower heating value [MJ/kg]

PETPPPSPLAPolymer

23333918Lower heating value [MJ/kg]

PETPPPSPLAPolymer

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) V

Final Report

In this summary the presentation of result graphs in form of bar charts is restricted to the base scenarios (figures 3 to 5) and selected scenarios for waste management options (fig-ures 6 to 8). The stacked bars in the figures consist of the contributions of the identified life cycle steps to the overall packaging system results. The life cycles steps are;

• the production of primary PLA, PS, PP, PET pellets (“plastics production”);

• the transport of primary polymer pellets to the polymer processor (“transport plas-tics”);

• the production of clam shells by extrusion and thermoforming (“clam shell produc-tion”);

• the recycling of used packaging materials, including transport to recycling sites (“re-cycling”) and;

• the disposal of used packaging materials, including transport to disposal sites (“dis-posal”).

Depending on the scenario settings concerning waste management, certain secondary prod-ucts are obtained through recovery processes of used packaging materials. Typically, poly-mers that undergo mechanical recycling processes may substitute virgin polymer materials or non-plastics in various applications. The packaging system under investigation provides these secondary materials for use in subsequent system. The avoided burden has been taken into consideration by the means of credits based on the environmental loads of the substituted material.

The credits are shown as separate bars (see stacks with negative values) in figure 3 to 8. Two types of credits were distniguished:

• credit for mechanical recycling (such as regranulation) (“credit mechanical recy-cling”) and

• credit for feedstock recycling (replacing e.g. fossil fuels) (“credit feedstock recy-cling”).

Each impact category graph shows 3 bars for each of the clamshell systems investigated:

• sectoral results of the packaging system itself (stacked bar) “gross system results”;

• credits given for secondary products leaving the system (negative stacked bar) “credits” and;

• net results (grey bar) as a result of the subtraction of credits from overall environ-mental loads “net results”.

All graphs shown refer to the functional unit of 1000 clam shells available for the consumer at the point of sale.

In the main report the results are given for PLA6 (which is based on the utilization of wind energy) and PLA/NG (which is based on next generation process technology in combination with wind energy). Further the main report discusses a series of sensitivity analysis to evalu-ate the influence of certain variables on the study results.

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VI LCA for food packaging from PLA and alternative materials (Summary) IFEU-Heidelberg

Final Report

Result graphs of base scenarios

Figure 3 Base scenarios for the clam shells examined. Categories Fossil Resource Consump-tion, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication

Fossil Resource Consum ption

-15

-10

-5

0

5

10

15

20

25

30

kg c

rude

oil e

quiv

. per

100

0 cl

amsh

ells

PLA 5 PS PP PET

Fossil Resource ConsumptionFossil Resource Consum ption

-15

-10

-5

0

5

10

15

20

25

30

kg c

rude

oil e

quiv

. per

100

0 cl

amsh

ells

PLA 5 PS PP PETPLA 5 PS PP PET

Fossil Resource Consumption

)

-505

Gnet results

Credit feedstock recycling

Credit mechanical recycling

Disposal

Recycling

Clam shell production

Transport plastics

Plastics production

Terrestrial Eutrophication

-10

-5

0

5

10

15

20

25

30

g PO

4 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Terrestrial Eutrophication

PLA 5 PS PP PET

Terrestrial Eutrophication

-10

-5

0

5

10

15

20

25

30

g PO

4 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Terrestrial Eutrophication

PLA 5 PS PP PETPLA 5 PS PP PET

Acidification

-0,20

-0,10

0,00

0,10

0,20

0,30

0,40

kg S

O2 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Acidification

PLA 5 PS PP PET

Acidification

-0,20

-0,10

0,00

0,10

0,20

0,30

0,40

kg S

O2 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Acidification

PLA 5 PS PP PETPLA 5 PS PP PET

Sum m er Sm og (POCP)

-20

0

20

40

60

80

100

g et

hene

equ

ival

ents

per

100

0 cl

amsh

ells

Summer Smog (POCP)

PLA 5 PS PP PETPLA 5 PS PP PET

-60

-40

-20

0

20

40

60

80

100

120

140

kg C

O2 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Global Warming

PLA 5 PS PP PET-60

-40

-20

0

20

40

60

80

100

120

140

kg C

O2 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Global Warming

PLA 5 PS PP PETPLA 5 PS PP PET

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) VII

Final Report

Figure 4 Base scenarios for the clam shells examined. Categories Human Toxicity, Aquatic Eu-trophication and additional indicator Farm Land

Aquatic Eutrophication

-1

0

1

2

3

4

5

6

g PO

4 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Aquatic Eutrophication

PLA 5 PS PP PET

Aquatic Eutrophication

-1

0

1

2

3

4

5

6

g PO

4 e

quiv

alen

ts p

er 1

000

clam

shel

ls

Aquatic Eutrophication

PLA 5 PS PP PETPLA 5 PS PP PET

-5,0

0,0

5,0

10,0

15,0

20,0

25,0

30,0

mg

As e

quiv

alen

ts p

er 1

000

clam

shel

ls

PLA 5 PS PP PET

Human Toxicity: Carcinogenic Risk

-5,0

0,0

5,0

10,0

15,0

20,0

25,0

30,0

mg

As e

quiv

alen

ts p

er 1

000

clam

shel

ls

PLA 5 PS PP PETPLA 5 PS PP PET

Human Toxicity: Carcinogenic Risk

)

-505

G

net results

Credit feedstock recycling

Credit mechanical recycling

Disposal

Recycling

Clam shell production

Transport plastics

Plastics production

0

5

10

15

20

25

m²/y

ear p

er 1

000

clam

she

lls

Use of Nature: Farm Land

PLA 5 PS PP PETPLA 5 PS PP PET

-0,10

-0,05

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

kg P

M 1

0 eq

uiv.

per

100

0 cl

amsh

ells

Human Toxicity: PM 10

PLA 5 PS PP PET-0,10

-0,05

0,00

0,05

0,10

0,15

0,20

0,25

0,30

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kg P

M 1

0 eq

uiv.

per

100

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amsh

ells

Human Toxicity: PM 10

PLA 5 PS PP PETPLA 5 PS PP PET

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VIII LCA for food packaging from PLA and alternative materials (Summary) IFEU-Heidelberg

Final Report

Figure 5 Base scenarios for the clam shells examined. Additional indicator cumulative primary energy demand (CED). Non-renewable primary energy is comprised of fossil and nu-clear energy. Total primary energy is the sum of renewable and non-renewable primary energy.

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

GJ

per 1

000

clam

shel

ls

PLA 5 PS PP PETPLA 5 PS PP PET

CED (renewable)

)

-505

G

net results

Credit feedstock recycling

Credit mechanical recycling

Disposal

Recycling

Clam shell production

Transport plastics

Plastics production-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

GJ

per 1

000

clam

shel

ls

CED (total)

PLA 5 PS PP PETPLA 5 PS PP PET

-1,0

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) IX

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System Comparison

A numerical comparison of the net environmental impact indicator results (shown as grey bars in figures 3 to 5) for PLA and the alternative clam shell packaging systems under investigation is given in table 3.

Table 3 Pair-wise comparison of alternative clam shell systems with PLA clam shells [Green fields mean an advantage for PLA, red fields mean a disadvantage for PLA.]

Impact Category PS PP PET Fossil Resource Consumption 211% 243% 317%

Global Warming 60% 30% 93%

Summer Smog (POCP) 31% 62% 440%

Acidification 85% 147% 15%

Terrestrial Eutrophication 114% 137% 14%

Carcinogenic Risk 2115% 129% 6145%

Human Toxicity (PM10) 106% 160% 3%

Aquatic Eutrophication 1140% 14% 540%

Note: Percentage values are calculative differences derived from the net indicator results with the smaller value being the mathematical denominator.

The comparison of the PLA packaging system with the alternative systems revealed that:

• The PLA system shows advantages compared to all three packaging systems using conventional polymers, in the categories Fossil Resource Consumption, Global Warming and Summer Smog. Similar results regarding Human Toxicity (Carcinogenic Risk) are of limited reliability due to existing data quality issues.

• For the remaining impact categories, comparisons of the PLA system with the alter-native systems do not show a clear trend. The LCA results for Acidification, Terres-trial Eutrophication and Human Toxicity (PM10) show disadvantages of PLA when compared to PS and PP systems.

• Comparing PLA with PET, PLA only shows disadvantages for terrestrial and aquatic Eutrophication. However, the latter observation has been found to depend on the choice of PET inventory dataset.

• For Aquatic Eutrophication PLA shows environmental advantages if compared to PP and disadvantages in comparison with PS and PET.

These conclusions proved to be quite robust. Similar patterns were found in the various sen-sitivity analyses performed. Merely the choice PET inventory data shows a high sensitivity for the final comparison of PLA clam shells versus PET clam shells.

A public PET inventory dataset is available from PlasticsEurope. An alternative dataset has been developed within a PETCORE LCA project available for use in this current LCA. With PlasticsEurope PET data in the base scenario the environmental advantages of PLA clam shells over PET are predominant. With the application of “Petcore PET” data, the advantages of PLA over PET in the categories Acidification and Human Toxicity (PM10) turn into disad-

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X LCA for food packaging from PLA and alternative materials (Summary) IFEU-Heidelberg

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vantages. In this latter case the ranking of PLA against PET would be rather similar to that al-ready found in the comparison of PLA against PS and PP.

Altogether, the comparative results show a pattern of environmental advantages and disad-vantages of PLA according to the individual environmental category considered. The funda-mental message here is that there is a trade-off which does not allow for a clear overall pref-erence of any particular system in the first place.

Waste Management

One should be aware of the fact that once sufficient volumes are available, sorting of PLA into a separate polymer fraction with subsequent chemical (or mechanical) recycling can be-come of interest for the recycling industry.

Consequently, the question of the appropriate waste management is nonetheless an impor-tant issue PLA. Related results are shown in figures 6 to 8.

Chemical recycling of source-separated PLA packaging waste would provide a considerable improvement in most impact categories examined. A shift from mixed plastics to polymer sorting and recycling would improve the environmental impact profile of the PLA packaging system in all impact categories examined in this study.

In Germany there is already an extended infrastructure for collection and treatment of source-separated biowaste, mainly in industrial composting facilities. However, comparing the different PLA waste management options it seems that composting is not the preferred treatment for PLA packaging waste based on the indicators used. All environmental impacts are rather similar or higher than in the PLA base case. The effect of a net increase in envi-ronmental impacts, particularly Summer Smog and Global Warming, is related to air emis-sions released during the composting process and the quite small credits to be obtained.

Anaerobic digestion seems a more promising option than composting. The advantage of the digestion option when compared to the composting alternative is mainly related to electricity generation with the obtained biogas and the related electricity credits for displacement of grid electricity.

However, to date little is known about the behaviour of PLA when undergoing anaerobic di-gestion. An improvement of respective knowledge by future research is desirable.

It shall be mentioned here, that in the PET clam shell system too, an increased sorting into a polymer fraction with subsequent recycling would provide considerable improvements re-garding the overall life cycle impact profile.

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) XI

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Figure 6 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terres-trial Eutrophication

)

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Figure 7 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Categories Human Toxicity, Aquatic Eutrophication and additional indicator Farm Land

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials (Summary) XIII

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Figure 8 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Additional indicator cumulative primary energy demand (CED). Non-renewable primary energy is comprised of fossil and nuclear energy. Total primary energy is the sum of renewable and non-renewable primary energy.

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Conclusions

In the framework of this LCA study PLA clam shells proved to be competitive with the con-ventional counterparts from an environmental perspective. Still, decision-makers in the politi-cal and trade area should be well aware that the results of this study do not allow for general-ized conclusions regarding the comparison of biopolymers in general or PLA in particular against petrochemical polymers. This should be clear in any political statement that makes reference to this LCA study.

On the other hand, this study shows that political decision makers are well advised to en-courage optimized packaging production (e.g. against the current trends on the market which show a tendency to increased packaging weights). Consequently, trade companies should commit to optimized packages using as less material as possible and define respective crite-ria towards their suppliers.

The stakeholders involved in the PLA product chain should support the implementation of an appropriate infrastructure for the management of used PLA packaging. Though used PLA packaging is principally compatible with the treatment routes existing within the German waste management systems, the respective results of this LCA study should be taken into consideration. While the mixed plastics route shows some environmental benefits, the option of choice seems to be a selective treatment via chemical recycling.

Yet, it is worthwhile to mention, that PLA is a relatively new material. PP, PS and PET are commodities produced in large scale plants which have been optimized during many years of commercialization. PLA certainly still is at a much earlier phase of market development and process optimization.

The PLA process technology improvements planned have been examined in a separate sce-nario (PLA/NG). The results show considerable potential improvements in the majority of the impact categories studied such as Fossil Resource Consumption, Global warming, Summer Smog, Acidification, Terrestrial Eutrophication and Human Toxicity (PM10).

At the time of this LCA study, short term innovations have already been put into practice by NatureWorks through the utilization of wind power via the purchase of Renewable Energy Certificates since the start of the year 2006 resulting in considerable reductions of Fossil Resource Use, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication and Human Toxicity(PM10) This scenario is referred to in the LCA as “PLA6”.

The new approach of NatureWorks to offset the greenhouse gas emissions caused by PLA production by the purchase of renewable energy certificates is a huge step towards producer responsibility for the achievement of environmental improvements on a company level. This attitude should be acknowledged by both stakeholders and decision makers in the trade as well as at the political level.

In parallel, NatureWorks should continue its efforts towards increased process efficiency and reduced direct process emissions in both, own facilities and – through appropriate company policies - those of suppliers, including farming practices.

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials 1

Final Report

1 Goal and scope definition

1.1 Background and objectives Biobased polymers (BP) are made from annually renewable resources, such as corn, and are normally biodegradable or compostable on industrial composting sites. During the last years they have seen a growing field of potential applications.

In the past, there has been considerable scepticism towards these new materials4. This scepticism was probably valid for the first generation of biobased polymers. Today biobased polymers comply with standard product specifications and usually can be converted to (packaging) end products using the standard machinery for thermoplastics. In addition, bio-based polymers can increasingly compete concerning costs with their traditional fossil-based counterparts.

The acceptability of biobased packaging to consumers was studied in Germany during a consumer survey in the autumn of 2001. The so-called Kassel trial5 showed that BPs have high consumer acceptance. Positive results were also obtained by the dm drugstore chain during a field test.

Like conventional polymers, BPs can be used for an enormous variety of products. Conse-quently, a number of different types of BPs are now available on the market and the con-sumption of BPs products in the European Union in 2005 is estimated at 50,0006 to 120,0007 tonnes. Currently, it seems that further advances are mainly occurring in the packaging and fibre sectors.

Polylactide (PLA) is one of the main drivers of the advances of biobased polymers on the marketplace. PLA is a new polymer family and currently the only commercial biopolymer made completely from renewable feedstock. It is also one of the most versatile materials and - in contrast to most other available BPs – is also suitable for more sophisticated applications like beverage and food packaging.

Regarding the fate of PLA materials after being used, available test results suggest that PLA wastes are suitable for landfill, incineration, composting and chemical recycling. They thus principally fit into the waste management systems existing in Germany and other EU coun-tries.

4 BP are said to have e.g. high production costs, high material requirements in terms of mass per

product, bad convenience due to low durability, poor recyclability, negative effects on composting processes

5 http://www.Modellprojekt-kassel.de 6 IBAW data, refer to 2003; www.ibaw.org 7 Estimation of CSEMP (French Packaging Industry Association)

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Interestingly, the German Packaging Ordinance exempts compostable biobased packaging from the regulation and the related licence fees until the end of the year 2012. In the mean-time industry is requested to develop appropriate disposal solutions.

Despite the situation described, the decisive step for the future success of biobased packag-ing on the market remains their acceptance and handling as branded products in particular and their application in standard mass products by retailers in general. Here, a positive over-all ecological performance of PLA and packaging products made of it could be an important argument to gain support from decision makers and foster its dissemination in the market.

Before this background NatureWorks LLC decided to commission a Life Cycle Assessment (LCA) in order to obtain comprehensive information about the environmental performance of packaging made from NatureWorks PLA under the framework of German conditions. For this purpose clam shells have been chosen as the packaging application to be examined. The choice had to be made in order to keep the study within a reasonable scope.

Clam shells are small volume containers, consisting of a body and a lid like e.g. the sample shown in figure 1-1.

Figure 1-1: Example for a clam shell

The clam shells addressed in this study are rigid thermoformed, transparent, have a volume of 500 ml and typically serve to pack food ready for take-away at the retail outlet. At the time of this study clam shells on the German market are usually made from polypropylene (PP), oriented polystyrene (OPS) and polyethylenterephtalate (PET). Clam shells from PLA are in use in several EU countries, like e.g. France, but not yet in Germany.

The objectives of the LCA are:

d) to compare packaging applications made from NatureWorks PLA with packaging ap-plications from alternative materials under German conditions

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IFEU-Heidelberg LCA for food packaging from PLA and alternative materials 3

Final Report

e) to examine the effect of purchasing renewable energy certificates by NatureWorks as well as next generation PLA production on the overall environmental profile of pack-ages made from NatureWorks PLA

f) to examine the potential effect of selected PLA waste treatment options on the overall environmental profile of packages made from NatureWorks PLA

The latter point partly picks up a long standing discussion regarding the appropriate end-of-life option for biodegradable polymers. It shall help to identify possible action required by NatureWorks in this area. It also might help to provide further knowledge to the discussion as to whether the biobin should be opened for compostable packaging materials in Germany and other countries and thereby make the study usable for a larger range of target groups.

The French packaging producer Vitembal could be gained for participation in the project. Relevant data needed for the LCA were provided by Vitembal. Therefore, the LCA presented here can be regarded as a case study particularly concerning packaging specifications and polymer conversion data (i.e. production of clam shells from polymer granules).

The study was designed to comply with the requirements of the ISO standard as described in the international standards DIN EN ISO 14040-14043 [DIN EN ISO 14040 (1997), 14041 (1998), 14042 (2000), 14043 (2000)]. The study also underwent a critical review process.

It should be regarded that the acronym “PLA”, in the context of this study, only refers to NatureWorks® PLA.

1.1 Organisation of the study The study has been commissioned by NatureWorks LLC in August 2004 and was conducted by IFEU-Heidelberg. The study included a comprehensive stakeholder participation in form of a project panel. Members of the project panel were:

• Mr. Erwin Vink – NatureWorks LLC

• Mr. Martin Lichtl – Sustainability Communications

• Dr. Jürgen Bruder – IK (Industrieverband Kunststoffverpackungen)

• Mr. Hans-Jürgen Garvens (Packaging and packaging recycling expert)

• Dr. Harald Kaeb – IBAW (Interessensverband Bioabbaubare Werkstoffe)

• Mr. Jöran Reske – IBAW (Interessensverband Bioabbaubare Werkstoffe)

• Mrs. Verena Böttcher – HDE (Hauptverband des deutschen Einzelhandels)

• Mr. Andreas Detzel – IFEU

• Mrs. Martina Krüger – IFEU

• Mr. Axel Ostermayer – IFEU

The project panel met four times, on August 8th, 2004; October 20th, 2004; October 25th, 2005 and March 13th, 2006. The meetings took place in the HDE building in Berlin.

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Mr. Thierry Grossetete from the French producer Vitembal was invited to the third meeting. He delivered in-depth background and technical information on plastics packaging materials and their properties.

Dr. Michael Heyde from Dual System Germany AG (DSD AG) was participating in the project via e-mail and phone communication. DSD AG delivered information on the polymer-specific end-of-life material flows.

1.2 Critical review process The study has been critically reviewed according to ISO 14040 (1997), § 7.3.3. The review-ers

• Mr. Stefan Schmitz (chairman), Berlin

• Dr. Andreas Ciroth (co-reviewer), GreenDeltaTC GmbH, Berlin

have been interactively participating in the project since the second project panel meeting. One separate meeting between the reviewers, NatureWorks, and IFEU was held in Heidel-berg on December 13th, 2004. For more information on the reviewers see appendix

1.3 Use of the study and target groups With the LCA study NatureWorks wants to examine the environmental benefits of packages made from PLA in comparison with packages made from traditional polymers, using the ex-ample of clam shells. This shall provide a basis to get a positive endorsement to accelerate the adoption of NatureWorks® PLA food packaging in Germany.

The target audiences in Germany are

• NatureWorks key customers and brand owners

• Public authorities (particularly the German Federal Ministry responsible for national environmental policy and the related scientific body, the German Federal Environ-ment Agency)

NatureWorks intends to use the study as an information source to get the support from opin-ion leaders as well as a marketing instrument. The findings of the study might further be used for information purposes in other European countries.

1.4 Product function / Functional unit The functional unit of this LCA is defined as 1000 units of 500 ml clam shells which are in-tended to be filled with cold foodstuff, for instance take-away salad, and are available for the consumer at the point-of-sale. The study is only applicable to clam shells of similar dimen-sions and with a top load strength of about 22 Newton.

The top load strength specified is characteristic for clam shells designated for light filling goods and is sufficient to assure the integrity of the clam shells during transport.

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Point-of-sale here refers to broadly accessible retail outlets like e.g. supermarkets. Clam shells as such could also be used for foods consumed in canteens and festivals etc. How-ever, this field of application has to be regarded as a niche market and is not covered in this study.

1.5 System boundaries The study is a “cradle-to-“grave LCA. This means, that it principally covers all relevant proc-ess steps from raw material sourcing to the final waste treatment or recycling of the used packaging. However, those life cycle steps and material components which are the same across the packaging systems examined have been excluded.

A general simplified process flow diagram is given in figure 1-2, including an indication of the system boundaries for the packaging systems studied. The processes excluded from LCA calculations are marked by dotted lines.

Figure 1-2: System boundaries applied in this study (simplified diagram)

As can be seen from the flow chart the system boundaries comprise the following life cycle steps:

• Polymer production (starting from crude oil extraction and crop farming respectively up to the final polymer)

• Transportation of polymers to the clam shell production plant

• Extrusion of sheets and forming of the final clam shells

• Waste collection of used clam shells

Life Cycle Steps ComprisedLife Cycle Steps Comprised

MSWI

Raw Material Production

Displacedenergy

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creditscredits

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T Transport

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Area, CO2 Water Emissions to air and water Wastes

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• Final disposal (municipal solid waste incineration)

• Recovery and recycling of used clam shells

• Production and disposal of process chemicals, as far as not excluded by the cut-off criteria (see below)

After the consumer use phase the packaging is collected for recovery and final waste treat-ment respectively. The related routes will differ according to the packaging material exam-ined (for more details see chapter 2). Waste collection and waste treatment is included within the system boundaries. For recycling and recovery routes the system boundaries are defined by the point where a secondary product is obtained.

Not included within the system boundaries are:

• Retail of the clam shells

• Production and transport of secondary and tertiary packaging

• Production of the food stuff

• Production and disposal of the infrastructure (machines, transport media, roads etc) and their maintenance

• Environmental effects directly related to the activities of the consumer

• Environmental effects from accidents

In order to maintain the study within a feasible scope a limitation of detail in system modelling was necessary. Therefore, so-called cut-off criteria were used.

For datasets modelled by IFEU, chemicals and process material pre-chains with an input of less than 1% of the total output of a considered process were excluded if process data for these materials where not available. However, total cut-off was not to be more than 5% of in-put materials as referred to the functional unit.

For the PLA inventory, according to NatureWorks, inputs of less than 0.1% by mass were excluded. As for the Plastics Europe ecoprofiles, it seems, that in case of lacking pre-chains, data for a similar materials are used rather than applying cut-off criteria [Plastics Europe 2005d].

1.6 Data gathering and data quality The datasets used in this study will be addressed in chapter 3. The general requirements for the datasets are described in the subsequent paragraphs.

Geographic reference

The geographic boundaries of the datasets to be used are basically determined by the in-tended packaging application on the German market.

For PP, OPS and PET it has been assumed that the polymers are produced at different sites in Europe. This is in line with the available datasets which intend to represent European av-

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erage data. NatureWorks PLA production is located in the US. The data provided by NatureWorks intend to reflect the regional and in part site-specific conditions of production.

It has further been assumed that the converting sites are located in Germany. Any possible import/export-relationships of finished clam shells have not been taken into consideration.

For waste collection and waste treatment, data for waste material flows and waste treatment processes are representative for the situation in Germany (also see chapter 2).

Time reference

At the start of the project a reference period between 2002 and 2004 had been aimed at for the core datasets and assumptions. The reference period of the final report is as follows:

A major part of the datasets taken from literature – this includes the inventory datasets for PP, OPS and PET polymers - have a reference period between the late 1990s and 2003 (see table 3-1). The PLA dataset reflects the status of the production process in 2005 (PLA 5). The data for polymer conversion refer to a period around 2004/2005.

The datasets for transportation, energy generation and disposal operations, which have been taken from the IFEU database, are representative for a period around 2002.

For final disposal settings the mass flow model was adjusted to reflect a situation mandated in German since June 2005 (i.e. it was assumed that no material is landfilled without prior treatment). The material-specific settings on recovery and recycling of packaging waste are valid for a period around 2003/2004.

At the time of this LCA study, there were practically no PLA packages on the German mar-ket. Thus, prospective assumptions were necessary for system modelling of PLA packages especially when simulating the fate of PLA in the post-consumer waste streams.

The study also includes a dataset for NatureWorks PLA production in 2006 (PLA 6) as well as next generation technologies (PLA/NG) for NatureWorks PLA production. The related data are calculations/projections done by NatureWorks and have been made available for use in this study.

Technical reference

The process technology underlying the datasets used in the study should reflect process configurations as well as technical and environmental levels which are typical for process operation in the reference period.

The converting process data represent the technology implemented at the Vitembal site in France. The converting machines are standard machinery similar to those installed at poly-mer converting sites in Germany.

1.7 Modelling and calculation of inventories For the implementation of the system models the computer tool Umberto® (version 5.0) was used. Umberto® is standard software for mass flow modelling and LCA. It has been devel-

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oped by the institute for environmental informatics (ifu) in Hamburg, Germany in collaboration with IFEU, Heidelberg.

All system models and the related module processes were implemented into mass-flow sce-narios. Calculation of input/output balances was scaled to the defined functional flow. In-put/output balances are composed of elementary and non-elementary flows. Elementary flows are materials or energy entering the system being studied, which have been drawn from the environment without previous human transformation or materials and energy re-spectively leaving the system, which is discarded into the environment without subsequent human transformation. The materials listed in the input/output balances are compiled into environmental profiles.

1.8 Environmental impact assessment and interpretation

1.8.1 Impact assessment

The environmental categories addressed below have been selected in order to assess the environmental performance of the packaging systems examined. These indicators stand for environmental issues generally perceived to be relevant. They are widely used in LCA prac-tice across Europe. For a more detailed description of the individual impact categories see appendix A.

A) Categories related to resources

• Fossil Resource Consumption (weighted with a scarcity factor of fossil fuel)

B) Categories related to emissions

• Global Warming (Climate Change)

• Acidification

• Terrestrial Eutrophication (i.e. eutrophication of soils by atmospheric emissions)

• Aquatic Eutrophication (i.e. eutrophication of aquatic ecosystems by effluent re-leases)

• Summer Smog (Photo-Oxidant Formation)

• Human toxicity as PM10-equivalents

• Human toxicity as As-equivalents

The choice of impact categories also covers the range of indicators used in the approach for “environmental evaluation in LCA” applied by the German Environment Agency [UBA 1999]. NatureWorks, when working with LCA, usually works with a smaller set of environmental in-dicators such as total fossil energy use, contribution to climate change and renewable re-sources. The “NatureWorks indicators” are also comprised by the choice presented above.

In table 1-1 the inventory parameters (i.e. the input/output data calculated in the mass flow models) classified within individual indicators are shown.

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The inventory parameters are ‘translated’ into equivalent units, which serve as representative values for the environmental impact in the concerned category. For instance all emissions in the inventory which have a global warming potential are calculated in CO2-equivalents and subsequently summed-up. This leads to one value in mass of CO2-equivalents for the se-lected packaging system. These values in ISO 14040 language are referred to as “indicator results”.

This may enable a better understanding of the cause-relationships underlying the impact categories. In order to assure reliability of results symmetry of the listed parameters across all processes was attempted throughout the study.

Additional indicators for information purposes at the inventory level examined in this study are the cumulative primary energy demand (CED) and the agricultural area.

The CED is a parameter to measure the primary energy consumption of a system independ-ent of the type of energy source. It is calculated by adding the energy content of all used fos-sil fuels, nuclear and renewable energy (including biomass).

The use of agricultural area is an indicator for the use of nature by agro-industrial production; in the case of this study, more precisely by corn growing for PLA production. The use of na-ture at IFEU usually is assessed by evaluating the ecological quality of the land use. For this purpose the areas used are grouped within a so-called nature proximity classification scheme. In the context of this LCA, the agricultural area of interest is located in the US and no information on the ecological quality of the agricultural areas used for NatureWorks PLA could be gathered within the scope of this study. The related LCA results for this reason only indicate the agricultural land area as such as calculated from the life cycle inventory.

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Table 1-1: Classification of inventory data according to the selected impact categories and inven-tory indicators

Cum

ulat

ive

Ener

gy D

eman

d

Res

sour

ce

cons

umpt

ion

Clim

ate

Cha

nge

(Glo

bal W

arm

ing)

Sum

mer

smog

(P

OC

P/N

CPO

CP)

Eutr

ophi

catio

n 1)

Aci

dific

atio

n

Hum

an T

oxic

ity

(As-

Equi

vale

nts)

Hum

an T

oxic

ity

(PM

10-E

quiv

alen

ts)

Use

of N

atur

e

CED fossil Crude oil CO2 fossil CH4 NOx NOx As PM10 Area

CED nuclear Natural gas CH4 NMVOC NH3 NH3 B(a)P SO2 Farm Land

CED renewable Brown coal N2O Benzene COD SO2 Cd NOx

Hard coal C2F2 Formaldehyde N-Comp. TRS Cr 2) NH3

CF4 Ethyl acetate P-Comp. HCl Ni NMVOC

C2F6 VOC HF Dioxin

CCl4 C-total H2S Benzene

R22 Ethanol PCB

NOx

MJ kg crude oil

equivalent

kg CO2

equiva-

lent

kg ethene

equivalent

kg PO4

equivalent

kg SO2

equivalent

kg As

equivalent

kg m2/year

1) NOx (calculated as NO2) and NH3 => terrestrial eutrophication; COD, N, P => aquatic eutrophication

2) as Chromium VI

Some of the potential environmental effects associated with agriculture as well as crude oil extraction and processing have not been taken into consideration.

For agriculture examples are biodiversity, human toxicity, ecotoxicity and soil fertility being affected by pesticides, heavy metals contained in fertilizers and the use of genetically modi-fied crop plants.

For petrochemical activities examples are the marine, soil and air environment affected by crude oil and gas losses during production and transportation (by ship and pipeline) or air quality affected by fugitive emissions at refineries with unknown chemical composition and emission pathways.

These effects are difficult to examine in LCAs due to the lack of data or appropriate methods. Substantial effort will be needed to improve this situation. Within the scope of this study it was not possible to address these aspects at more detail.

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1.8.2 Optional elements

ISO 14043 provides three optional elements for impact assessment which can be used de-pending on the goal and scope of the LCA:

1. Normalization: calculating the magnitude of category indicator results relative to ref-erence information.

2. Grouping: sorting and possibly ranking of the impact categories.

3. Weighting: converting and possibly aggregating indicator results across impact cate-gories using numerical factors based on value-choices (not allowed for comparative assessments disclosed to public)

The use of these optional elements also implies the introduction of value-based judgements. Within the project panel no agreement for the handling of individual value-based choices could be achieved. As a consequence, it was decided to do the evaluation and interpretation of the results of this study at the level of indicator results without any priority-setting or rank-ing of the indicators presented in chapter 1.8.1.

Furthermore, indicator results were kept separated and no weighting across them was per-formed.

For interested parties, examples for a normalisation of the indicator results of this study as well as a short overview on the ranking approach used by the German Environment Agency can be found in appendix B.

1.9 Allocation and crediting procedure For dealing with the matter of allocation, two systematic levels must be distinguished be-tween: Allocation may be necessary at the level of individual processes within the studied product system or between the studied product system and upstream or downstream product systems.

For process-related allocations, a distinction is made between multi-input and multi-output processes. The matter of system-related allocation occurs when a product system has addi-tional benefits on top of the actual benefit given by the functional unit. This is the case if the product system generates energy and material flows for other product systems or recy-cled waste to be used as secondary raw materials in other product systems.

1.9.1 Process-related allocation

Multi-output processes

For data sets prepared by the authors of this study, the allocation of the outputs from coupled processes is generally carried out via the mass. For some data sets taken from the literature, the calorific value or market value is used as the allocation criterion. The respective alloca-tion criteria are documented in the description of the data in case they are of special impor-tance for the individual data sets. For literature data, only the source is generally referred to.

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Multi-input processes

Multi-input processes occur especially in the area of disposal. Relevant processes are mod-elled in such a way that the partial material and energy flows due to disposal of the used packaging materials can be apportioned in a causal way. The modelling of packaging mate-rials that have become waste in a waste incineration plant is a typical example of multi-input allocation. The allocation for e.g. emissions arising from such multi-input processes has been carried out according to physical and/or chemical cause-relationships (e.g. mass, heating value, stoichiometry, etc.)

Transport processes

In packaging LCAs of the German Environment Agency an allocation between the packaging and contents was carried out for the transport for distributing the filled packages. Such an al-location has not been required in the present study because the retail of the finished pack-ages was outside the system boundaries.

1.9.2 System-related allocation

The approach chosen for system-related allocation is explained with the help of the graphs shown in figure 1-3 and figure 1-4. Both graphs show two examplary product systems, re-ferred to as product system A and product system B. System A shall represent systems un-der study in this LCA.

In figure 1-3 (upper graph) in both, system A and system B, a virgin polymer is produced, converted into a product which is used and finally disposed of via MSWI.

A different situation is shown in the lower graph of figure 1-3. Here product A is recovered af-ter use and supplied as a raw material to system B avoiding thus the environmental loads re-lated to the production (“PP-B”) of the virgin polymer and the disposal of product A (“MSWI-A”).

Now, if the system boudaries of the LCA are such that only product system A is examined it is necessary to decide as to how the possible environmental benefits and loads of the poly-mer material recovery and recycling shall be allocated (i.e. accounted) to system A. In LCA practice several allocation methods are found.

The two allocation methods used in this study are shown in figure 1-4. In order to do the allo-cation consistently, besides the virgin polymer production (“PP-B”) and the disposal of prod-uct A (“MSWI-A”) already mentioned above, the recovery process “Rec” has to be taken into consideration. This has been highlighted in figure 1-4 by placing these processes in between system A and B.

Furthermore, there is one important premise to be complied with by any allocation method chosen: The mass balance of all inputs and outputs of system A and system B after alloca-tion must be the same as the inputs and outputs calculated for the sum of systems A and B before allocation is performed.

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Allocation with the 100%-method (figure 1-4, upper chart)

In this method the principal rule usually applied by LCA practitioners is that system A gets all benefits for displacing the virgin polymer and the involved production process „PP-B“. At the same time, all loads for producing the secondary raw material via „Rec“A are assigned to system A. In addition, also the loads that would have been generated by treatment of product A in „MSWI-A“ is charged to system A.

One should be aware that in such a case any LCA focusing on system B would then have to assign the loads associated with the production process „PP-B“ to the system B (otherwise the mass balance rule would be violated). However, system B would not be charged with loads related to „Rec“ as the loads are already accounted for system A. At the same time, „MSWI-A“ is subtracted from system B (again a requirement of the mass balance rule).

Allocation with the 50%-method (figure 1-4, lower chart)

In this method, benefits and loads of „PP-B“, „Rec“ and „MSWI-A“ are equally shared be-tween system A and B (50/50 method). Thus, system A, from its viewpoint, receives a 50% credit.

The 50/50 method is the standard approach applied in the packaging LCAs commissioned by the German Environment Agency (UBA). However, the 50/50 method is particularly complex in the case of PLA because the PLA inventory dataset contains implicit credits for CO2 fixa-tion which also have to be included into the overall allocation steps between the PLA pack-age system (i.e. system A) and the systems making use of recovered PLA package waste (i.e. system B). More details on this point can be found in section 6.2.4.

In this study the 100% allocation has been used as the main approach in order to facilitate communication and improve comparability with other ongoing LCAs with participation of NatureWorks. The sensitivity of this decision on the final LCA results has been examined by application of the 50/50 approach (see section 6.2.4.). This might also help a better accep-tance of the LCA results by UBA.

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Figure 1-3: Additional system benefit through recycling (schematic flow chart)

MSWI(MSWI-A)

PolymerProduction

(PP-B)

MSWI(MSWI-B)MSWI

(MSWI-B)

System A:PP-A + Pr-A

System B:Pr-B+ MSWI-B

Coupled systems (system expansion)

Recovery(Rec)

Recovery(Rec)

Burden System A + B:PP-A + Pr-A + Pr-B + MSWI-B+ RecAvoided Burden:MSWI-A + PP-B

Polymer Production

(PP-A)

Polymer Production

(PP-A)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

MSWI(MSWI-A)MSWI

(MSWI-A)

PolymerProduction

(PP-B)

PolymerProduction

(PP-B)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

MSWI(MSWI-B)MSWI

(MSWI-B)

System A:PP-A + Pr-A + MSWI-A

System B:PP-B + Pr-B+ MSWI-B

Uncoupled systems

PolymerProduction

(PP-A)

PolymerProduction

(PP-A)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

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Figure 1-4: Principles of 100% and 50/50 allocation (schematic flow chart)

+50% -50%

Polymer Production

(PP-A)

Polymer Production

(PP-A)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

MSWI(MSWI-A)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

MSWI(MSWI-B)MSWI

(MSWI-B)

System A:PP-A + Pr-A + Rec-A – PP-B+ MSWI-A

System B:PP-B + Pr-B + MSWI-B – MSWI-A

Allocation: 100% approach

Recovery(Rec-A)

Recovery(Rec-A)

-100%

+100%

-100%

MSWI(MSWI-A)MSWI

(MSWI-A)

Polymer Production

(PP-A)

Polymer Production

(PP-A)

MSWI(MSWI-A)

MSWI(MSWI-B)MSWI

(MSWI-B)

System B:0.5 PP-B + 0.5*Rec-A + Pr-B + MSWI-B - 0.5*MSWI-A

Allocation: 50%/50% approach

Recovery(Rec-A)

Recovery(Rec-A)

-50% +50%

+50% +50%

MSWI(MSWI-A)MSWI

(MSWI-A)

System A:PP-A + Pr-A + 0.5*Rec-A - 0.5*PP-B + 0.5*MSWI-A

Processing &Production

(PP-B)

Processing & Production

(PP-B)

Processing & Production

(PP-B)

Processing &Production

(PP-B)

Processing & Production

(PP-B)

Processing & Production

(PP-B)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

+100%

+100%

+0%

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2 Packaging systems and scenarios under study

2.1 Packaging specifications In general terms packaging systems can be defined by their composition regarding primary, secondary and tertiary materials. The focus in this study is on the primary material. Secon-dary and tertiary packaging materials like cardboard trays, stretch and shrink foils and pallets have been assumed to be the same for each of the packaging systems and have not been included within the system boundaries of this study.

The packages under examination are small volume (500 ml) thermoformed clam shell con-tainers made from PET, PLA, PP and OPS respectively. Typically they are rigid and trans-parent. Body and lid usually are made from the same polymer material.

The production process is basically a two-step procedure. In the first step the polymers are extruded to sheets and in the second step the sheets are formed into the final package shape through a deep-drawing process. The same machine and forming technique is used for both, body and lid production.

The clam shell weights applied in this study are shown in table 2-2 by each individual poly-mer type. For PET, PLA and PP the data represent the current status of packages produced by the French converter Vitembal [Vitembal 2005b]. Vitembal does not produce clam shells from OPS. The OPS data therefore are an estimate based on the background of Vitembal’s experience [Vitembal 2005b].

Table 2-1: Overview of packaging weights for clam shells

Parameter PET PLA PP OPS

Weight (g)* 19.9 12.2 16.9 15.2

*: weight includes the clam shell lid; data source: Vitembal

It is important to point out that 500 ml clam shells are produced with various shapes and weights depending on the individual converter as well as the individual customer in the retail business. Indeed, samples of clam shells (from PET, PP, OPS) collected in German retail outlets showed a large range of weights between different brands even if made from the same polymer (see table 2-2, data below line “C”).

As a cross-check the available weight data have been scrutinized on the ground of charac-teristic packaging material properties. For this purpose, it has been assumed that the final packages should have a similar stiffness in order to comply with the requirements from the market. The properties of interest here are material density and elasticity modulus. These properties determine the package weight that is required to achieve a certain stiffness of the package. The respective data are listed in table 2-2 (under heading “A. Material Properties”).

A (relative) weight factor for PLA, PP and PS can been derived from the density and elastic-ity modulus when normalized to PET. The weight factor has been used to calculate (theo-

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retic) package weights relative to PET containers if these have an assumed weight of 20 g (table 2-2, data under heading “B”).

The closest relationship is between the calculated weights and the data of Vitembal (~producer 1). It is obvious, that the large ranges found in the available weight data cannot be explained by the material properties. Particularly the PLA data of producers 2 and 3 seem to be relative high. On the other hand, some weights are smaller and will probably not meet the top-load strenght requirements (see section 1.4)

The table also shows that, based on the calculated weight data, the weight applied for the OPS clam shell (table 2-1) can be regarded as a reasonable estimate.

Table 2-2: Range of weights of 500 ml clam shells from different sources

PET PLA PP PS

A. MATERIAL PROPERTIES

Density [g/cm3] 1.33 1.23 0.9 1.05

Elasticity modulus [N/mm2] 2200 3500 1600 3000

Weight Factor (relative to PET) 1 0.58 0.93 0.58

B. CLAM SHELLS, calculated weight relationships:

Calculated weights 20 11.6 18.6 11.6

C. CLAM SHELLS SAMPLES (converter data and measurements for market outlets)

Weight (producer 1) [g] 19.9 12.2 16.9 -

Weight (producer 2) [g] 18.5 17.1 - 14.4

Weight (producer 3) [g] 20.5 16.5 - -

Weight (collected samples) [g] 18.7-22 11.3-18 - 13.8-15.7

2.2 End of life settings It is assumed that the clam shells after use are disposed of by the consumer via the local municipal solid waste management systems. Post-consumer packaging waste in Germany is separated into yellow bins for kerbside collection or dropped off at local recycling stations. The collection of the yellow bins is organized by Dual Systems8 which are responsible for compliance with the recovery quota set by the German Packaging Ordinance.

At an average the share between collection is 95% via yellow bins and 5% via recycling sta-tions. Not all the packaging waste is separated at source by the consumer and a part of it ends up in the grey bin.

In this study it has been attempted to break down the recovery of the waste packages into collection and sorting quota. The main source for this type of information are the mass flow verification data produced and maintained by DSD AG as required under the German Pack-aging Ordinance and samples taken by DSD AG at sorting plants.

The model assumptions applied for the base scenarios in this study are listed in table 2-3

8 E.g. „Duales System Deutschland AG (DSD)“ and „das Duale System INTERSEROH“

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Packages made from PET, PS and PP have been on the market for some time and are typi-cal components present in the collection and sorting schemes of Dual Systems operating in Germany. Clam shells from these materials will mainly be sorted into polymer fractions desti-nated for mechanical recycling and the mixed plastics fraction respectively. Due to the instal-lation of PS separators in the sorting plants, the polymer fraction for PS packaging is consid-erably higher when compared with other polymers.

The mixed plastics fraction undergoes mechanical and feedstock recycling processes. Me-chanical recycling of the mixed plastics fraction produces plastics regranulate. This regranu-late may be used instead of virgin plastics or may substitute non-polymer applications such as cement or wood palisades, wooden pallets, cement sewers, noise protection barriers amongst others. A part of the mixed plastics fraction is recovered by feedstock recycling. It is mainly recovered in blast furnaces or processed into methanol in the SVZ plant. A smaller part is used as a secondary fuel in cement kilns.

The assumptions and settings described in the previous paragraphs of this chapter are based on DSD [2004, 2005 and 2006].

Assumptions regarding the expected waste recovery routes of PLA packages are not so straight forward. The revised German Packaging Ordinance from May 2005 exempts com-postable biobased packaging from the regulation and the related licence fees until the end of the year 2012. On the other hand, the industry concerned has the task to develop appropri-ate disposal solutions.

This exempted compostable biobased packaging will be labeled, after certification according to EN13432 by the European Bioplastics biodegradable polymer packaging symbol as given below. This symbol on the packaging enables the consumers to make a clear distinction be-tween PLA and the fossil based packaging.

Since today it is not clear how PLA packaging will be handled by the German consumer, it is assumed in the study that PLA will end up in the same collection scheme together with other packaging.

What will be the fate then in the waste stream of the sorting plants? PLA in principle could be sorted into polymer fractions as well, however, due to the relatively small volumes to be ex-pected right after market introduction, PLA will most probably be routed only into the mixed plastics fraction. This assumption forms the basis for the model settings shown in table 2-3. However, it is likely and technically feasible that PLA will be sorted into a polymer fraction with subsequent e.g. chemical recycling once sufficient volumes will become available on the German market. This option has been investigated as a variant scenario with respect to waste management (see section 2.3.2).

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Of course similar considerations apply for PET. Before the compulsory deposit on one-way PET bottles for water and soft drinks entered into force in 2003, PET packaging was sorted into a PET fraction together with PET bottles. As a consequence of the deposit the amounts of PET bottles collected via the Dual Systems decreased drastically and along with that the sorting of PET into PET fractions.

Currently PET bottles are gaining market shares in non-deposit drink sectors like juices and milk. Thus, sorting of PET fractions is expected to increase in the future. For the reason of symmetry also here a variant scenario considering such a situation (see section 2.3.2) was analyzed.

As a general setting in the base scenarios, it is assumed that 20% of the used clam shells are collected in the grey bin and go to MSW incinerators. Generally spoken, final treatment by MSWI is applied for all process and packaging waste flows which are not separated at the source as well as for sorting residues generated at the sorting plant. This reflects the situa-tion in place since the phase-out of landfilling without pre-treatment, legally enforced in Ger-many (as of June 2005) through the Landfill Ordinance.

Most German waste incineration plants convert part of the waste’s energy content to useful energy. Based on [ITAD 2002] it is assumed that on average 10% of the net calorific value are transformed to electricity and additionally 30% to thermal energy.

For pre-treatment a small fraction of municipal solid waste is also subjected to mechanical-biological treatment (“MBA”). Due to different (and changing) plant operating concepts it has not been possible to model representative MBA process data within this study. The exclusion of MBA treatment in the life cycle model is not expected to considerably affect the results.

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Table 2-3: Assumptions regarding collection and recovery of used clam shells

Parameter PET PP PS (OPS) PLA A. Collection Quota (% of used clam shells), of which

80% 80% 80% 80%

A.1 Kerbside collection (delivered to sorting facilities)

95% 95% 95% 95%

A.2 Collection via recycling centres 5% 5% 5% 5%

B. Sorting Fractions

B.1 at sorting facilities

B.1.1 Mixed Plastics (MPF) 85% 77% 59% 85% B.1.2 Polymer fraction 0% 8% 26% 0% B.1.3 Sorting residues 15% 15% 15% 15%

B.2 at recycling centres

B.2.1 Mixed Plastics (MPF) 100% 0% 0% 100% B.2.2 Polymer fraction 0% 100% 100% 0%

C. Recovery Quota = A * (A.1*(B1.1+B1.2) + A.2 * (B2.1+B2.2))

69% 69% 69% 69%

D. Recycling of MPF

D1. Mechanical recycling 39% 33% 33% 0% D2. Feedstock recycling 61% 67% 67% 100%

E. Recycling of polymer fractions

E1. Regranulation -- 100% 78% -- E2. Bulky products -- 0% 22% --

F. Mechanical Recovery Quota 27% 29% 39% 0%

Sources: DSD 2004, DSD 2005, DSD 2006

2.3 Scenarios examined

2.3.1 Base scenarios

For each clam shell packaging system a basic scenario has been developed based on the data shown in table 2-1 and table 2-3. These scenarios represent as closely as possible the situation in the reference period of the study or, in case of the PLA material, the most prob-able situation resulting after market introduction.

In order to illustrate the material flows in the packaging systems, simplified flow diagrams were prepared for each base scenario (figure 2-1). The indicated values come from computer calculations and were taken from Umberto®. The material flow data end at the system boundary set for this study (see section 1.5).

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Figure 2-1: Selected material and energy flows in the clam shell packaging systems examined

1.00.90.90.81.92.6Substitution factor (SF)

Virgin PETVirgin PPVirgin PSVirgin polymerWoodCementSubstituted product

PP regranulate

PET regranulate

PS regranulate

Mixed plasticsregranulateBulky productsSecondary product

1.00.90.90.81.92.6Substitution factor (SF)

Virgin PETVirgin PPVirgin PSVirgin polymerWoodCementSubstituted product

PP regranulate

PET regranulate

PS regranulate

Mixed plasticsregranulateBulky productsSecondary product

TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T T

Collection and sorting

Methanol: 1.36 kgE (thermal): 91 MJE (electric): 9 MJ

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Mixed plasticsfraction

8.37 kg0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJ

TransportT TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T TT

Collection and sorting

Methanol: 1.36 kgE (thermal): 91 MJE (electric): 9 MJ

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Mixed plasticsfraction

8.37 kg0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJ

PS fraction

Material Flows: Clam Shell from PSMaterial Flows: Clam Shell from PSMSWI

Point of Sale/Consumer

Extrusion andForming

PSgranules T T

Collection and sorting

Transport

15.68 kg 15.2 kg

FU: 1000 Clam Shells

T

3.04 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

6.86 kg

3.57 kg

PS regranulate: 2.88 kgBulky products: 0.16 kg

E (thermal): 55 MJE (electric): 20 MJ

Regranulate: 0.65 kgBulky products: 0.29 kgMethanol: 1.4 kgE (thermal): 106 MJE (electric): 11 MJ

0.48 kg(process waste)

PS fraction

Material Flows: Clam Shell from PSMaterial Flows: Clam Shell from PSMSWI

Point of Sale/Consumer

Extrusion andForming

PSgranules T TT

Collection and sorting

Transport

15.68 kg 15.2 kg

FU: 1000 Clam Shells

T

3.04 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

6.86 kg

3.57 kg

PS regranulate: 2.88 kgBulky products: 0.16 kg

E (thermal): 55 MJE (electric): 20 MJ

Regranulate: 0.65 kgBulky products: 0.29 kgMethanol: 1.4 kgE (thermal): 106 MJE (electric): 11 MJ

0.48 kg(process waste)

PP fraction

Material Flows: Clam Shell from PPMaterial Flows: Clam Shell from PPMSWI

Point of Sale/Consumer

Extrusion andForming

PPgranules T T

Collection and sorting

Transport

17.43 kg 16.9 kg

FU: 1000 Clam Shells

T

3.38 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

9.92 kg

1.68 kg

PP regranulate: 1.45 kgBulky products: 0.08 kg

E (thermal): 52 MJE (electric): 19 MJ

Regranulate: 1.83 kgBulky products: 1.2 kgMethanol: 1.75 kgE (thermal): 130 MJE (electric): 13 MJ

0.53 kg(process waste) PP fraction

Material Flows: Clam Shell from PPMaterial Flows: Clam Shell from PPMSWI

Point of Sale/Consumer

Extrusion andForming

PPgranules T TT

Collection and sorting

Transport

17.43 kg 16.9 kg

FU: 1000 Clam Shells

T

3.38 kg

13.52 kg

1.93 kg(sorting residues)

Mixed plasticsfraction

9.92 kg

1.68 kg

PP regranulate: 1.45 kgBulky products: 0.08 kg

E (thermal): 52 MJE (electric): 19 MJ

Regranulate: 1.83 kgBulky products: 1.2 kgMethanol: 1.75 kgE (thermal): 130 MJE (electric): 13 MJ

0.53 kg(process waste)

Material Flows: Clam Shell from PETMaterial Flows: Clam Shell from PETMSWI

Point of Sale/Consumer

Extrusion andForming

PETgranules T T

Collection and sorting

E (thermal): 43 MJE (electric): 15 MJ

Regranulate: 2.99 kgBulky products: 1.98 kgMethanol: 1.62 kgE (thermal): 114 MJE (electric): 11 MJ

20.52 kg 19.9 kg

FU: 1000 Clam Shells

TransportT

3.98 kg

15.92 kg

2.27 kg(sorting residues)

Mixed plasticsfraction

13.66 kg

0.72 kg(process waste)

Material Flows: Clam Shell from PETMaterial Flows: Clam Shell from PETMSWI

Point of Sale/Consumer

Extrusion andForming

PETgranules T TT

Collection and sorting

E (thermal): 43 MJE (electric): 15 MJ

Regranulate: 2.99 kgBulky products: 1.98 kgMethanol: 1.62 kgE (thermal): 114 MJE (electric): 11 MJ

20.52 kg 19.9 kg

FU: 1000 Clam Shells

TransportT TransportT

3.98 kg

15.92 kg

2.27 kg(sorting residues)

Mixed plasticsfraction

13.66 kg

0.72 kg(process waste)

23333918Lower heating value [MJ/kg]

PETPPPSPLAPolymer

23333918Lower heating value [MJ/kg]

PETPPPSPLAPolymer

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In the graph there is also a table below the actual flow diagrams that shows what primary raw materials are substituted by the secondary products that are produced. Determining the ac-tual amount of primary raw material that has been substituted, is carried out by means of a substitution factor. The substitution factor expresses to what degree the secondary material substitutes a primary raw material or primary material. The substitution factors were made available by the DSD AG in the context of a previous study [IFEU 2004]. The lower table in figure 2-1 summarizes the lower heating values applied for modelling energy recovery proc-esses. The heating values are taken from [IFEU 1999] in case of PLA and from the Ecoin-vent database [ECOINVENT 2005] for the fossil-based polymers.

There is one relevant assumption in the PLA scenario that should be mentioned at this place: At the time being, the PLA process waste from thermoforming cannot be recycled onsite to the same degree as in the case of the fossil based polymers, for which internal recycling of process waste is an well-established technique. However, Vitembal is confident to solve the recycling problem by the end of the year 2006 [Vitembal 2006]. The current situation with re-gard to process waste has been considered by means of a sensitivity analysis (section 2.3.3)

In the PLA base scenario a working on-site recycling has already been implemented (see figure 2-2). Given the “prospective” character of the PLA settings in this LCA this assumption seems reasonable. Still, it has to be taken into consideration in the final interpretation of the LCA.

Figure 2-2: Handling of PLA process waste from converting A) current situation found at Vitembal; B) situation assumed in the PLA base scenario

The base scenarios and the respective LCA results provide the main focus for the compari-son of the ecological profiles of the individual packaging systems.

Extrusion andthermoforming

12.58 g

6.1 g 0.39 g

12.2 g

to MSWI

Extrusion andthermoformingExtrusion andthermoforming

12.58 g

6.1 g 0.39 g

12.2 g

to MSWI

A: situation at Vitembal: B: base scenario:

Extrusion andthermoforming

15.0 g

3.7 g 2.4 g

12.2 g

on stock to MSWI

0.39 g

Extrusion andthermoforming

15.0 g

3.7 g 2.4 g

12.2 g

on stock

Extrusion andthermoformingExtrusion andthermoforming

15.0 g

3.7 g 2.4 g

12.2 g

on stock to MSWI

0.39 g

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In this report scenarios are partly referred to using abbreviations. Table 2-4 gives an over-view regarding the base scenarios. PLA 5 refers here to current (2005) PLA pellet produc-tion.

Table 2-4: Base scenarios of clam shell packaging systems

Base Scenario Short Name PLA clam shell, 12.2 g; PLA production 2005 PLA 5 OPS clam shell, 15.2 g PS PP clam shell, 16.9 g PP PET clam shell, 19.9 g (PET PlasticsEurope Data) PET

2.3.2 Variant scenarios

Several variants of the PLA base scenario (PLA 5) have been examined in this study in order to determine the environmental (dis-)advantages related to PLA production per 2006 (PLA 6), PLA production using next generation technology (PLA/NG) and PLA specific waste management options. In addition, one variant of the PET base scenario with respect to end-of-life routes for PET has been examined.

Area: 2006 and next generation PLA production

PLA 6. This case represents the current, 2006, cradle-to-factory gate PLA production sys-tem, including the purchase of Renewable Energy Certificates to replace the non renewable energy based electricity utilized in all Cargill/NatureWorks controlled processes with electric-ity produced by wind turbines. In addition, certificates were purchased by NatureWorks to offset the remaining (among others non-Cargill/NatureWorks electricity-related) cradle-to-factory-gate greenhouse gases.

PLA/NG. This case represents the future or next generation cradle-to-factory gate PLA pro-duction system. This production system is expected to be introduced in a few years and is based on new fermentation and recovery technology in combination with the utilization of wind power or renewable energy certificates for electricity requirements in the Car-gill/NatureWorks controlled processes [Vink 2006b].

For more details on the PLA production data see section 3.1.5. The LCA results related to both areas are documented in section 4.2.1.

Area: Alternative recovery routes for PLA packaging waste

In the future it might be possible to direct PLA packaging waste into waste routes designed for biowastes. This would require a collection via the biobin or a separation from the mixed packaging waste at the sorting plants. Biological treatment of PLA, i.e. composting and an-aerobic digestion, has therefore been examined as alternative end-of-life options for PLA packaging wastes. Besides the biological treatment options, also a chemical recycling option is investigated in this study with respect to its environmental impacts.

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Composting

In order to model the composting route it has been assumed that 80% of used PLA clam shells are separated into the biobin. This is based on the assumption that the efficiency of user behavior for a selective collection of PLA waste via the biobin will be in the same range as for the selective collection of packaging waste in the yellow bin. For practical reasons it is further assumed that of the PLA waste 10% still end up in the yellow bin and 10% will be found in the grey bin.

Anaerobic Digestion

Currently the majority of all biodegradable waste collected via the biobin is treated by com-posting, a collection via the yellow bin has been considered to be appropriate for the anaero-bic digestion scenario. The PLA would then have to be separated from the mixed packaging waste for a subsequent anaerobic digestion.

Like in the base scenario it is assumed that 80% of used PLA clam shells are collected via the yellow bin while the remaining 20% end up in the grey bin. As a simplification it has fur-ther been assumed that the PLA waste collected with the yellow bin will be fully sorted into a PLA fraction suitable for anaerobic digestion.

Chemical Recycling

Chemical recycling mainly consists in a hydrolysis process that separates the polyester into its monomers, the lactic acid. The lactic acid obtained by chemical recycling can either be fed into the polymerisation process again to produce PLA polymer. Alternatively, lactic acid may be used for other applications. For the purpose of the variant scenario presented here it has been assumed that the lactic acid obtained by chemical recycling substitutes lactic acid from sugar fermentation as an input for the PLA polymerisation process.

Like in the base scenario it is assumed that 80% of used PLA clam shells are collected via the yellow bin while the remaining 20% end up in the grey bin. As a simplification it has fur-ther been assumed that the PLA waste collected with the yellow bin will be fully be sorted into a PLA fraction suitable for the chemical recycling process. The PLA clam shell in this variant scenario consists of around 50% of chemically recycled PLA.

For more information on these end-of-life options see sections 3.3.4 and 3.3.5. The LCA re-sults related to both areas are documented in section 4.2.2.

The resulting mass flows are shown in figure 2-3.

Combined Variants: Assessment of PLA 6 and PLA/NG in combination with the alternative recovery routes for PLA packages

The combined variants were requested by NatureWorks in order to provide further supportive information for the development of future strategies concerning end-of-life management of used PLA packaging. The related results are described and presented in section 4.2.3.

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Figure 2-3 Material flows and recovery routes in composting, anaerobic digestion and chemical recycling scenarios

Area: Alternative recovery route for PET packaging waste

In this scenario it has been assumed that used PET clam shells will be fully sorted into a PET polymer fraction and recycled into PET flakes (see chapter 2.2). Recycled PET flakes have been credited with the displacement of virgin amorphous PET.

All variant scenarios are summarized in table 2-5 along with their short names that will be used throughout the report.

1.04 kgTransportT TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T TT

Collection and sorting

Methanol: 0.17 kgE (thermal): 11 MJE (electric): 1 MJ

12.58 kg 12.2 kg

FU: 1000 Clam Shells

1.22 kg

9.76 kg

Mixed plasticsfraction0.39 kg

(process waste)

E (thermal): 8 MJE (electric): 8 MJVariant: composting

TransportT TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T TT

Collection and sorting

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Anaerobicdigestion

8.37 kg

0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJVariant: anaerobic digestion

Collection via biobin

1.22 kg

0.18 kg(sorting residues)

Com-posting9.76 kg

TransportT TransportT

Material Flows: Clam Shell from PLAMaterial Flows: Clam Shell from PLAMSWI

Point of Sale/Consumer

Extrusion andForming

PLAgranules T TT

Collection and sorting

12.58 kg 12.2 kg

FU: 1000 Clam Shells

2.44 kg

9.76 kg

1.39 kg(sorting residues)

Chemicalrecycling

8.37 kg0.39 kg(process waste)

E (thermal): 21 MJE (electric): 8 MJVariant: chemical recycling

Compost: 0.82 kg

Compost: 0.69 kg

PLA: 6.34 kg

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Table 2-5: Variant scenarios of clam shell packaging systems from PLA and PET

Variant Short name

Area: PLA production

Basis: PLA clam shell, 12.2 g; PLA production 2005 Variant => Offset of greenhouse gas emissions using RECs

PLA 6

Basis: PLA clam shell, 12.2 g; PLA production 2005 Variant => New fermentation process technology + RECs

PLA / NG

Area: PLA end-of-life options

Basis: PLA clam shell, 12.2 g; PLA production 2005 Variation => Composting of PLA packaging waste

PLA (Composting)

Basis: PLA clam shell, 12.2 g; PLA production 2005 Variation => Anaerobic digestion of PLA packaging waste

PLA (Digestion)

Basis: PLA clam shell, 12.2 g; PLA production 2005 Variation => Chemical Recycling of PLA packaging waste

PLA (ChemR)

Combined variations: PLA production and PLA end-of-life options

Basis: PLA clam shell, 12.2 g; PLA production 2006 Variation => Composting of PLA packaging waste

PLA 6 (Compo-sting)

Basis: PLA clam shell, 12.2 g; PLA production 2006 Variation => Anaerobic digestion of PLA packaging waste

PLA 6

(Digestion)

Basis: PLA clam shell, 12.2 g; PLA production 2006 Variation => Chemical Recycling of PLA packaging waste

PLA 6

(ChemR)

Basis: PLA clam shell, 12.2 g; PLA/NG production Variation => Composting of PLA packaging waste

PLA/NG (Compo-sting)

Basis: PLA clam shell, 12.2 g; PLA/NG production Variation => Anaerobic digestion of PLA packaging waste

PLA/NG

(Digestion)

Basis: PLA clam shell, 12.2 g; PLA/NG production Variation => Chemical Recycling of PLA packaging waste

PLA/NG

(ChemR)

Area: alternative PET end-of-life options

Basis: PET clam shell, 19.9 g; PET dataset from PlasticsEurope Variation => Mechanical Recycling of PET packaging waste

PET (MechR)

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2.3.3 Sensitivity analysis of the base scenarios

Sensitivity scenarios have been applied to check the relevance of the data chosen and as-sumptions made in the base scenarios. Analysis of the following areas was deemed neces-sary:

Area: Treatment of PLA process waste from converting

At the time of this study, about 10% to 20% of PLA polymer input ends up as converting process waste that cannot be used for further mechanical recycling appliances. Still, in the base scenario model this has been regarded a temporary problem and a fully working inter-nal recycling of PLA waste has been assumed.

The uncertainty involved with this approach has been examined in section 5.2.1

Area: Selection of PET inventory data

Two alternative inventory datasets for PET production are available. The influence of the choice of one out of these datasets on the outcome of the LCA presented in this study has been examined by means of a sensitivity analysis in section 5.2.2.

Area: Accounting of carbon sequestration in agricultural soils

There is an uncertainty related to the question as to whether, and if yes, how soil carbon se-questration should be accounted directly to products of agricultural activities. The influence of the credits related to carbon sequestration by soils has been examined by a sensitivity analysis presented in section 5.2.4.

Area: Balancing of CO2-equivalents regarding carbon dioxide uptake in biomass during plant growth

There are different possible approaches as to how to calculate CO2 equivalents in LCA if dealing with products from renewable feedstock. However, in a cradle-to-grave setting, LCA results should be the same regardless the application of individual approaches. This hy-pothesis has been checked by comparing the results of alternative approaches in section 5.2.5.

Area: Choice of allocation method for crediting secondary materials

Since crediting is not strictly based on scientific considerations the uncertainty regarding sys-tem allocation is scrutinized by using an alternative crediting procedure. In a sensitivity analysis the four package systems under examination are calculated with the allocation pro-cedure according to the 50/50 method (see section 5.2.3).

The scenarios studied in the sensitivity analyses together with the abbreviations used in the graphical results are summarised in table 2-6.

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Table 2-6: Scenarios used for sensitivity analysis of the base scenarios

Sensitivity Short name

Area: Data for PLA converting

Basis: PLA clam shell, 12.2 g; PLA production 2005 Sens. Analysis => Treatment of PLA process waste for energy recovery (cement kiln)

PLA 5 (cem. kiln)

Basis: PLA clam shell, 12.2 g; PLA production 2005 Sens. Analysis => Chemical recycling of PLA process waste

PLA 5 (chem. rec.)

Area: PET datasets

Basis: PET clam shell, 19.9 g (PET PlasticsEurope Data) Sens. Analysis => PET inventory data from Petcore-Study

PET (Petcore)

Area: System allocation

Basis: PLA clam shell, 12.2 g; PLA production 2005; 100% credit for sec. products Sens. Analysis => 50% credit for secondary products

PLA 5 (Alloc 50%)

Basis: PP clam shell, 16.9 g; 100% credit for sec. products Sens. Analysis => 50% credit for secondary products

PP (Alloc 50%)

Basis: OPS clam shell, 15.2 g; 100% credit for sec. products Sens. Analysis => 50% credit for secondary products

PS (Alloc 50%)

Basis: PET clam shell, 19.9 g (PET PlasticsEurope Data); 100% credit for sec. products Sens. Analysis => 50% credit for secondary products

PET (Alloc 50%)

Area: Modelling of CO2-equivalents

Basis: PLA clam shell, 12.2 g; PLA production 2005 Sens. Analysis => Alternative modelling and evaluating of CO2 uptake in biomass

PLA 5 (Alt. CO2)

Basis: PLA clam shell, 12.2 g; PLA production 2005 Sens. Analysis => no accounting of agricultural soil as a carbon sink

PLA 5 (soil C)

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3 Description of Selected Inventory Data

3.1 Polymer production The following polymers are used as packaging raw materials for the clam shell systems:

• Polylactide (PLA)

• Polypropylene (PP)

• Polystyrene, general purpose (GPPS)

• Polyethylene terephthalate, amorphous (PET)

For PP, GPPS and PET inventory datasets have been published by PlasticsEurope [Plas-ticsEurope 2005a-c]. The datasets were compiled by Dr. Ian Boustead by combining data collected directly among European plastic and upstream intermediate product producers with background data from his own database. The overall quality of PP, GPPS and PET inventory data was assured by the consultant Dr. Ian Boustead. However as far as known to the authors of this LCA there is no independent third party review of the Plastics Europe inventory datasets.

The PLA inventory data have been developed by NatureWorks in analogy to the Plas-ticsEurope datasets. The core data for corn wet milling, lactic acid and polymer production have been collected directly at the Cargill / NatureWorks facilities. The fossil fuel based electricity data were obtained from the direct supplier, the wind power based electricity was taken from a peer reviewed LCA on wind power production [Vestas 2005], the data for the most important process chemicals were obtained from a direct supplier [Vink 2006a] or taken from the Eco-invent database. The dataset was approved by Dr. Boustead (see Appendix C).

For PET an alternative dataset is available which has been developed by IFEU on behalf of Petcore9 [IFEU 2004]. It is the standard dataset used by IFEU to assess products from PET in LCAs. The data were approved by an independent third party review.

The application of the PET data from PlasticsEurope in the base scenarios was done on the explicit wish of NatureWorks (see Appendix B). In a sensitivity analysis the influence of this choice on the LCA results has been examined.

All polymer datasets mentioned in the preceding paragraphs cover the processes from cradle to polymer factory gate. The PlasticsEurope datasets are publicly available, both the PLA and Petcore PET are currently not.

Table 3-1 gives an overview on the polymer datasets used in this study.

9 PETCORE: www.petcore.org

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Table 3-1 Overview on datasets for polymers used in this LCA study

Polymer type Publication date

Calculation date Reference year (polymerisation)

Number of plants inc-luded

Plastics Europe / Boustead

PP 2005 March 2005 1999 28

PS (GPPS) 2005 December 2005 2002 20

PET (amorphous) 2005 March 2005 1999 7

NatureWorks / Boustead

PLA Not published yet

January 2006 2005 1

Petcore / IFEU

PET Not published yet

May 2004 2002-2003 5

3.1.1 Polypropylene

The underlying LCA study utilises data published by PlasticsEurope10 [Plastics Europe 2005b]. The dataset covers the production of PP from the cradle to the polymer factory gate. The polymerisation data refer to the 1999 time period and were acquired from a total of 28 polymerisation plants producing 5,690,000 tonnes of PP annually. The total PP production in Western Europe in 1999 was 7,395,000 tonnes. The Plastics Europe data set hence rep-resented 76.9% of PP production in Western Europe.

3.1.2 General purpose polystyrene

The underlying LCA study uses the data published by PlasticsEurope11 [Plastics Europe 2005c]. The dataset covers the production of GPPS from the cradle to the polymer factory gate. The polymerisation data refer to the 2002 time period and were acquired from a total of 20 polymerisation plants producing 1,340,000 tonnes of GPPS annually. The total PS production in Western Europe in 2002 was 2,600,000 tonnes (includes general purpose and high impact polystyrene without expandable or modified grades). The Plastics Europe dataset hence represented 51.5% of PS production in Western Europe

3.1.3 Polyethylene Terephtalate (PlasticsEurope)

The underlying LCA study uses the ecoprofile data published by PlasticsEurope 12 [Plastics Europe 2005a]. The dataset covers the production from the cradle to the polymer factory gate.

10 http://www.lca.plasticseurope.org/index.htm 11 http://www.lca.plasticseurope.org/index.htm 12 http://www.lca.plasticseurope.org/index.htm

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The PET and upstream intermediates production data have been gathered directly from Euro-pean producers and compiled by Dr. Ian Boustead. The final results were approved by the par-ticipating companies organized in PlasticsEurope.

The data refer to the 1999 time period and were acquired from 7 polymerisation plants pro-ducing 570,000 tonnes of PET (amorphous) annually. The total PET production in Western Europe in 1999 was 1,560,000 tonnes. The Plastics Europe data set hence represented 36.5% of PET (amorphous) production in Western Europe in the respective reference year.

3.1.4 Polyethylene Terephtalate (Petcore)

Polyethylene terephthalate (PET) is produced by direct esterification and melt polycondensa-tion of purified terephthalic acid and ethylene glycol. Production data for the esterification, polycondensation and for terephthalic acid production had been collected by IFEU within a LCA study on one-way PET bottles [IFEU 2004], commissioned by Petcore13. Supplemented with available production data on upstream operations (e.g. refinery processes), a data set including all process steps starting from oil and gas extraction until the PET polymer granu-late had been developed.

The data refer to the 2002/2003 time period and were acquired from 5 polymerisation plants producing 631,000 tonnes of PET annually. The total production in Europe in 2002 was 1,775,000 tonnes. The Petcore data set hence represented 35.5% of PET production volume in Western Europe in the respective reference period.

The PET life cycle data had been gathered directly from European PET producers and com-piled by Prof. Rieckmann (FH Cologne) in collaboration with IFEU. The newly acquired data covered very modern as well as older plants. The dataset was qualified by PET experts with an overview on the PET plants existing in Europe as representative for the current Western European production.

The overall data quality of this dataset was approved by the external critical review panel which reviewed the PETCORE LCA according to [DIN EN ISO 14040 (1997)] series as well as by the project panel members.

3.1.5 Polylactide

Polylactide (PLA) is produced from lactic acid by ring-opening polymerisation through the lac-tide intermediate. The dataset provided by NatureWorks covers corn growing, corn wet mill-ing, lactic acid production as well as lactide and polylactide production.

Today NatureWorks LLC is the only large scale producer of PLA. The PLA data are repre-sentative for an annual production capacity of 140,000 tonnes.

13 PET containers recycling Europe: www.petcore.org

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The PLA inventory dataset refers to the year 2005 (referred to as PLA 5) and was provided by NatureWorks in a completely aggregated input/output data format. Additional information about PLA processing and properties [Vink et al. 2003, Vink et al. 2004a, Gruber 2002], about corn production and corn wet milling [Vink et al. 2004b,c] and about PLA 6 and PLA/NG [Vink 2005/2006] [Vink 2006b] has been documented by NatureWorks.

Corn production

Corn production includes corn growing, harvesting, drying and transportation to a corn wet mill. Therefore the corn production dataset does not only comprise the processes related to corn growing but also pre-chains of material and energy supply such as fertilizer and fuel production.

The corn production dataset generated by NatureWorks is based on a farmer survey carried out for the year 2000 which was supplemented with literature data. The environmental bur-dens of the corn production system are allocated between the corn and the corn stover fol-lowing an economic allocation procedure based on corn and corn stover prices.

Typical materials taken from the ecosphere are crude oil, gas and coal for energy supply as well as water, carbon dioxide and solar energy for the photosynthesis process. Besides emissions linked to energy use also agriculture-specific emissions released from the corn field into the air (i.e. N2O) and water (i.e. NO3

-) are also taken into account.

According to NatureWorks, most emissions from the corn field (i.e. N2O and NOx emissions) considered in the PLA inventory dataset have been estimated based on the DAYCENT model, a daily-time version of the CENTURY model14. However, emissions related to agricul-ture largely depend on surrounding conditions such as soil properties and weather conditions and vary considerably. Consequently, emission factors for agricultural emissions show rather wide ranges. For the setup of the PLA inventory individual emission factors were selected by NatureWorks.

Corn wet milling

The corn wet mill modelled in the calculation of the PLA inventory by NatureWorks produces five products. Besides dextrose, which is the raw material for the subsequent lactic acid fer-mentation also germ, corn gluten meal, corn gluten feed and steep water are products leav-ing the corn wet mill. An allocation between these products has been carried out based on the dry mass of intermediate and final products. It should be noted that for PLA production, the dextrose is an unrefined 32% solution as opposed to other commercial dextrose sources which are typically concentrated up to 71% solids for shipping purposes.

According to NatureWorks, the corn wet mill is representative for a large modern facility.

Lactic acid fermentation

Dextrose is converted into lactic acid by fermentation followed by purification. The fermenta-tion process requires process energy use such as steam and electricity and contributes sub-

14 The CENTURY model is a general model for predicting the long-term dynamics of soil carbon, ni-

trogen , phosphorus and sulphur in farmer, plant and soil systems.

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stantially to the fossil energy demand of PLA15. Sulphuric acid and calcium hydroxide are re-quired operating supplies. Data on energy and process chemical use have been collected by NatureWorks at their lactic acid fermentation facility and refer to the year 2005.

Polymerization

The manufacture of PLA from lactic acid occurs in two steps.

The first step is the conversion of lactic acid into the cyclic dimer lactide with subsequent pu-rification by distillation. In a second step the polymerization of lactide to polylactide takes place in the presence of a tin catalyst via a ring-opening polymerization. Data on energy use and process chemical demand for the lactide and polylactide production have been collected by NatureWorks at their PLA plant and refer to the year 2005.

Carbon fixation during corn growing

During corn growing, carbon dioxide is taken up by the plant and converted into sugars that are subsequently transformed into starch and finally PLA. Carbon dioxide is also used to grow the corn plant and after harvesting partly sequestered as soil carbon. The carbon diox-ide uptake by the plant that is allocated to the PLA product is included in the PLA inventory data provided by NatureWorks and mathematically expressed as a negative carbon dioxide emission.

The carbon dioxide fixation from the atmosphere that has been allowed for and allocated in the NatureWorks inventory model includes the following three pathways:

Carbon fixed in the PLA product

Carbon fixed by soil carbon sequestration

Carbon fixed in a landfill via disposal of PLA production waste

The carbon fixed in the PLA product corresponds to 1.833 kg CO2 / kg PLA; calculated from the theoretical C content in the polymer. This is the predominant pathway and accounts for 94% of the carbon dioxide fixation.

The amount of carbon fixed by soil carbon sequestration has been calculated by Nature-Works based on literature data combined with farm land management practices (i.e. conser-vation tillage) as specified in a farmer survey. It amounts to 59 g CO2/m2/year or 0.102 kg CO2 / kg PLA. It corresponds to roughly 5% of the carbon dioxide fixation. A background document with more details on the data used and the assumptions made by NatureWorks is given in Appendix E.

A minor part (~0.3%) of the carbon dioxide fixed by the corn plant ends up in PLA production waste that is disposed of in a landfill. As PLA is considered to be practically inert under land-fill conditions, this carbon is fixed in the landfill.

15 According to Vink et al. (2003) in a range around 50%

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Figure 3-1 Carbon dioxide emissions related to the PLA 5 inventory dataset

Figure 3-1 illustrates how the carbon dioxide fixation during corn growing is considered in the PLA 5 inventory dataset. The overall bar indicates the amount of carbon dioxide emissions generated during cradle to polymer factory gate production of 1 kg PLA. The hatched bar in-dicates the amount of carbon dioxide fixed in the PLA product, in soil and in landfill. The black bar indicates the net carbon dioxide emissions on a per kg PLA basis as presented in the NatureWorks PLA 5 dataset.

Offset of greenhouse gas emissions / Optimization of PLA production

In this LCA study, two additional PLA inventory datasets have been applied in order to exam-ine the effects of activities implemented by NatureWorks seeking improvements in the PLA lifecycle. Both additional PLA datasets have been provided by NatureWorks in the same (ag-gregated) data format as for the PLA 5 inventory dataset.

PLA 6

The PLA 6 inventory dataset refers to the period 2006 and on. The main differences be-tween the PLA 6 and the base case PLA 5 are discussed below.

In the Cargill/NatureWorks facilities (corn wet mill, lactic acid fermentation, polymerization) electricity is required to drive the processes. This electricity is imported from the regional public grid and is mainly produced from fossil resources (hard coal). Electricity production is an important source for carbon dioxide, nitrogen and sulphur oxides emissions in the cradle-to-factory gate inventory data. Other sources of air emissions are the use of thermal energy (natural gas for steam boilers) and upstream production and transportation of operating sup-plies.

As of January 1st, 2006, NatureWorks acquired renewable energy certificates (RECs) to off-set greenhouse gas emissions related to PLA production. One REC represents the environ-mental benefits created when one megawatt-hour of electricity is generated from renewable resources instead from fossil fuel sources. The benefits include avoided air emissions such as carbon dioxide and particulate matter from conventional fossil-fired power plants as well

0

1

2

3

4

PLA 5

kg C

O2 e

mis

sion

s pe

r kg

PLA

CO2 fixationNet CO2 emissionsof PLA inventory data set

PLA5

Kg C

O2

emis

sion

spe

r kg

PLA

+ PLA cradle-to-gateCO2-emissions

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as the avoided use of fossil fuels [Vink 2006b]. The amount of avoided fuel and emissions depends on the reference power generation chosen.

In order to calculate the RECs needed, in a first step wind power certificates have been pur-chased for the same amount of electricity consumed in the Cargill/NatureWorks facilities. However, even if all electricity used in the PLA production process steps is set-off by wind power electricity, still some greenhouse gas emissions remain. Those originate from e.g. natural gas boilers on-site and external production processes of operating supplies.

Therefore, in a second step, NatureWorks has purchased additional wind power certificates in order to offset the remaining greenhouse gas emissions. Mathematically, the amount of the additional wind power certificates is determined by the sum of all remaining greenhouse gas emissions (CO2, N2O, CH4) expressed as carbon dioxide equivalents. Those carbon di-oxide equivalents are divided by the amount of avoided carbon dioxide emission per one unit of wind power certificate (e.g. per MJ wind power electricity) which gives the units of wind power certificate to be additionally purchased.

For the PLA 6 dataset, the regional electricity grid that actually supplies electricity to the Car-gill/NatureWorks facilities has been selected by NatureWorks to serve as a reference. It should be noted here that avoided emissions are for a good part related to emissions origi-nating from electricity generation based on hard coal.

Due to the allowance for avoided emissions, the effect of the wind power certificates is simi-lar to a credit given within the inventory dataset, leading to reduced (e.g. SOx and NOx) or even negative total emissions (e.g. HCl and HF) associated with PLA production.

The REC's are perceived by NatureWorks as a useful financial vehicle for the transaction, because of the certification process. The certificates ensure that the same amount of elec-tricity as bought by NatureWorks is actually produced by wind power.

For 2006 the wind power underlying the RECs purchased by NatureWorks is produced in the Great Plains16. For 2007 NatureWorks intends to arrange a deal for Nebraska wind17.

PLA/NG

The PLA/NG inventory datasets refers to the next generation PLA production technology. In comparison to the PLA 5 inventory dataset, the two most important differences are:

1. As in the PLA 6 dataset, all greenhouse gas emissions related to the Cargill/NatureWorks facilities are offset by wind power RECs.

16 (see http://www.thegreenpowergroup.org/pdf/20051201_project_summary.pdf ) 17 Additional information from NatureWorks: A consortium, including the regional electricity suppliers

Omaha Public Power District (OPPD) and Nebraska Public Power District (NPPD) as lead mem-bers, has built a wind power facility located in Ainsworth, Nebraska. It is operational now (http://www.nppd.org/About_Us/Energy_Facilities/default.asp ). For the year 2006 NatureWorks did not buy from this site because they were not able to complete the arrangements in time to meet the schedule they had set for.

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2. A more efficient technology is applied for the calculation of inventory data of lactic acid fermentation. Major improvements are achieved in thermal energy demand and the use of process chemicals (e.g. sulphuric acid)

The resulting PLA/NG inventory data show considerably reduced fuel use and air emissions when compared to PLA 5 inventory data. In case of carbon dioxide emissions, the gross emissions of the process chain in PLA production are lower than the amount of carbon diox-ide fixed by the corn plant during the growth phase. This leads to a negative total carbon di-oxide emission in the PLA/NG inventory dataset.

3.2 Conversion of polymer pellets into clam shells Polymer pellets are converted into clam shells by extrusion and a subsequent thermoforming process. The energy demand is mainly met by electricity. The electricity consumption de-pends on the polymer type, on the polymer mass determined by the weight of thermoformed packages as well as on converting machine model and capacity.

Data on PLA, PP and PET clam shell weights and on electricity demand for extrusion and thermoforming were provided by Vitembal. Vitembal also provided the required data for the PS clam shells, which are currently not produced by Vitembal. All information on the conver-sion processes refer to the year 2005. [Vitembal 2005a,b]

Conversion data are not shown in the underlying report because of confidentiality , but when compared to extrusion and thermoforming data obtained in earlier studies on fossil-based polymers or to literature values, they are within a comparable range.

3.3 Recovery and recycling of used clam shells

3.3.1 Collection and sorting of used clam shells

The clam shells collected via Dual Systems first undergo a sorting step along with other light-weight packaging materials. The composition of the resulting sorted fractions depends on the waste composition and the technical configuration of the plant.

The assumptions on which share of the individual package types is sorted to certain fractions for subsequent recovery are documented in chapter 2-2. For the sorting process data were taken from [UBA 2001].

3.3.2 Recycling of the mixed plastics fraction

A large part of the clam shells collected via Dual Systems ends up as mixed plastic fraction (MPF) in the sorting plants (see table 2-3). The MPF is first grinded, purified by air classifica-tion and then melted in a thermo-reactor (agglomerator) and finally pelletised. The data used to model this process originated from the DKR [UBA 2001].

In this study it is assumed that the MPF is used for feedstock recycling, energy recovery and mechanical recycling (see table 2-3). The related quotas are based on [DSD 2004] and refer to the year 2003/2004.

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Mechanical recycling

The mechanical recycling of the mixed plastic fraction is split up (about 50:50) between dry and wet methods. Both methods result in materials that can be used as a substitute for vir-gin plastic (substitution factor 0.84) and as a wood and concrete substitute (substitution factors of 1.88 and 2.60 respectively). Typical applications where mixed plastics regranu-late can replace wood are palisades, pallets, benches etc. Substituted cement products in-clude cement palisades, sewers, noise protection barriers, fence holders amongst others [IFEU 2004, Patel et al. 2000]. The substitution factors are taken from [Heyde 1999, IFEU 2004] and are applied on a mass basis. This means that e.g. 1 kg of recycled plastic used for palisades replaces 1.88 kg of wood for the same purpose. For more information on substitution factors see Heyde [1999].

The credit for the plastics substitute was calculated with the same polymer datasets used in the individual clam shell scenarios.

For the calculation of the credit related to the substitution of concrete, data on the manu-facture of concrete palisades were used. Information about this originated from internal re-ports of the German cement industry [Winkler 1997] and the support tool on mass flow ana-lysis of the Environmental Ministry of the federal state of Nordrhein-Westfalen [MUNLV 2000].

The datasets for the calculation of the credits (i.e. manufacture of wood palisades) associ-ated with the substitution of wood-based materials data were taken from [UBA 1998] and [Heyde 1999].

Feedstock recyclinq

Feedstock recycling includes plastics recovery in blast furnaces and other industrial co-combustion processes (e.g. cement kilns) as well as a gasification process.

The blast furnace process was considered based on confidential data from the steel indus-try. It was assumed that the mixed plastics replace heavy heating oil as a reducing agent in equivalence to its respective calorific value.

The gasification of the mixed plastics at the secondary raw material recycling centre “Se-kundärstoff-Verwertungszentrum” in Cottbus was considered using data from [UBA 2000a, IVV 2001]. Secondary products are methanol and electricity substituting methanol synthezised from primary fossil resources and grid electricity respectively.

The co-combustion process was modelled as the use of the plastics material as a secondary fuel in a cement kiln substituting hard coal as primary fuel.

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3.3.3 Recycling of the polymer fraction

Mechanical recycling of PP and PS polymers results in a regranulated material that can be used as a substitute for respective virgin plastics. Substitution factors of 0.90 and 0.98 have been used for PP and PS regranulate respectively [IFEU 2004]. In the case of PS clam shells regranulated polymer material may also be used as a wood and concrete substitute (substi-tution factors 1.88 and 2.60 respectively).

For calculation of credits for wood and concrete substitutes, the datasets described above (section 3.3.2) were applied.

3.3.4 Treatment of PLA waste via the biowaste routes

Composting

Composting of PLA is characterised by a two-step degradation process: first, hydrolysis breaks down the polymer into its basic building blocks (lactic acid), followed by the metaboli-zation by micro organisms into CO2 [Klauss 2004].

The composting model considered here refers to a medium commercial composting standard having an encapsulated system (container composting) for the main degrading step. The af-ter-composting step is modelled as a simple, roofed clamp composting process. The com-posting life cycle step comprises the conditioning stage and two composting steps leading to a mature compost product. According to [Kern et al. 1998], after-composting in Germany predominantly takes place as simple, roofed clamp composting processes.

The compost is assumed to serve as a soil amendment and to displace mineral fertilizers and peat. Relevant emissions are CO2, methane and other volatile organic compounds being generated in the degradation steps. Those emissions mainly originate from transformation of organic substance in the after-composting step. As the after-composting does not take place in an encapsulated system, they are directly released to the atmosphere. An overall degrada-tion rate of 95% has been assumed for PLA. Process data is taken from [IFEU 1999].

The composting model used here is not applicable for home or backyard composting, where PLA showed almost no degradation [Klauss 2004].

Anaerobic Digestion

Little is known about the behaviour of PLA during anaerobic digestion. The basic principle of degradation of organic compounds via hydrolysis and acidification and eventual conversion to mainly carbon dioxide and methane by micro organisms also applies for PLA. However, the extent of degradation is still in discussion.

In the model applied the same degradation rate as for composting, i.e. 95%, has been as-sumed. This corresponds to a generation rate of 0.84 m³ biogas/kg PLA degraded. The bio-gas is combusted in a gas-motor producing a certain amount of net electricity. For the calcu-lation of the credit a displacement of average German grid electricity is assumed. Process data is taken from [IFEU 1999].

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3.3.5 Chemical recycling of PLA waste

Chemical recycling takes currently place with PLA production process waste generated dur-ing polymerization of virgin PLA, but is also a possible future option for recovery of used post-consumer PLA packaging materials. Chemical recycling is understood as a hydrolysis process in a first step, followed by a purification step with lactic acid monomers being the fi-nal product of the recycling process. Those can be fed back into the PLA polymerization process.

Process data for the chemical recycling process of PLA to lactic acid monomers have been provided by NatureWorks and contain information on energy and water use for the process as well as lactic acid yields.

3.4 Background data The corresponding data represent the average situation in the years 2000 to 2003.

3.4.1 Transports

Transport operations are particularly relevant for transports of polymer pellets to the clam shell producer. In case of fossil-based polymers, the production takes place somewhere in Western Europe hence an average transport distance of 500 km by lorry has been assumed. PLA pellets are produced in Nebraska, USA. Transport of 2000 km by rail and 6000 km by ship was assumed for PLA pellets based on information obtained from NatureWorks. The distance from the seaport to the clam shell producer was assumed to be 500 km.

Lorry transport

The dataset used is based on standard emission data that were collated, validated, ex-trapolated and evaluated for UBA Berlin, UBA Vienna and the Bundesamt für Umweltschutz (BUWAL), Bern in the "Handbook of emission factors" [INFRAS 2004]. The "Handbook" is a database application and gives as a result the transport distance related fuel consumption and the emissions differentiated into lorry size classes and road categories. Data are based on average German fleet compositions within several lorry size classes. The emission factors used in this study refer to the year 2003.

Based on the above-mentioned parameters – lorry size class and road category - the fuel consumption and emissions as a function of the transport load and distance were deter-mined.

Rail transport

Due to the lack of representative data for the transport of PLA by rail in the US data on freight transport from Borken et al. [1999] have been used. The rail transport model repre-sents the situation of German freight transport by rail in the second half of the 1990ies. Direct emissions as well as consumption of secondary energy (diesel fuel, electricity) are consid-ered.

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Ship transport

This dataset represents freight transport with an overseas containership between 9000 and 23000 tonnes. Energy use is based on an average fleet composition of this ship category and is based on data taken from [Borken et al. 1999]. Emission factors based on fuel con-sumption have been applied. Heavy fuel oil is the fuel used in container ship transports and its elemental composition is based on international average values. Similar to other diesel-fuelled transport operations, CO2 and SO2 emissions are calculated based on elemental composition of heavy fuel oil. Other emission factors are related to fuel consumption.

3.4.2 Electricity generation

Modelling of electricity generation is particularly relevant for extrusion and thermoforming processes in clam shell production. Electricity generation was considered using the German mix of energy suppliers in the year 2003. Although information on converting originates from the French clam shell producer Vitembal, it is assumed that converting sites are lo-cated in Germany, therefore electricity is taken from the German public grid. The mix of energy suppliers to the German electricity network was determined by using data from the German electricity association “Verband der Elektrizitätswirtschaft” [VDEW 2003] (see table 3-2).

Table 3-2: German mix of energy resources in electricity production in 2003

Energy resource Share [%] Hard coal 23,9% Brown coal 26,1% Mineral oil 1,1% Natural gas 12,3% Nuclear energy 27,8% Hydroelectric (without pump or regenerative) 3,6% Wind power 3,3% Other 1,8%

The modelling of the power stations was carried out using measurement reports that were made available to IFEU by operators of German power stations. These data were supple-mented by literature data, in particular [GEMIS], [ETH 1996].

Note:

As described in chapter 3.1, electricity for polymer production was already included within the given polymer inventory datasets.

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4 Results In this section the LCA results are illustrated and discussed on the ground of the impact categories and additional indicators as described in chapter 1.8. Environmental impact indi-cator results for the base scenarios are shown in form of bar charts in figures 4-1 to 4-3. In addition, the stacked bar charts indicate the contributions of important life cycle steps to the packaging system results, which are:

• the production of primary PLA, PS, PP, PET pellets (“plastics production”)

• the transport of primary polymer pellets to the polymer processor (“transport plas-tics”)

• Production of clam shells by extrusion and thermoforming (“clam shell production”)

• the recycling of used packaging materials, including transports to recycling sites (“re-cycling”)

• the disposal of used packaging materials, including transports to disposal sites (“dis-posal”)

Depending on the scenario settings concerning waste management (see chapter 2.2 for more details), certain secondary products are obtained through recovery processes of used packaging materials. Typically, polymers that undergo mechanical recycling processes may substitute virgin polymer materials or non-plastics in various applications. As outlined in sec-tion 1.5, the packaging system under investigation provides these secondary materials for use in subsequent system. The avoided burden has been taken into consideration by the means of credits based on the environmental loads of the substituted material.

The credits are shown in form of separate bars in the LCA result graphs. They have been broken down into:

• Credit for mechanical recycling (such as regranulation) (“credit mechanical recy-cling”)

• Credit for feedstock recycling (replacing e.g. fossil fuels) (“credit feedstock recy-cling”)

Each impact category graph shows 3 bars for each of the clamshell systems under investiga-tion, namely the following (as seen from left to right):

• sectoral results of the packaging system itself (stacked bar) “gross system results”

• credits given for secondary products leaving the system (negative stacked bar) “credits”

• net results (grey bar) as a result of the subtraction of credits from overall environ-mental loads “net results”

All graphs shown refer to the functional unit of 1000 clam shells available for the consumer at the point of sale.

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Table 4-1 to 4-4 shows for each individual clam shell the contribution of the individual life cy-cle steps to the specific impact categories as a percentage that refers to the gross system results (see previous page). This helps a better system understanding and facilitates identifi-cation of most relevant life cycle steps.

In addition, a numerical comparison between alternative clam shell systems is given in a ta-ble following the indicator result graphs (for an example see section 4.1.2, table 4-5). All per-centage values are calculative differences and always refer to the clam shell system with the lowest environmental impact. They are pair-wise comparisons and in each case PLA is com-pared with the alternative polymer. An example to illustrate how those percentages given for base and sensitivity scenarios are to be understood is given in the following:

Assume that the PLA system shows an impact score of 30 and the alternative PS system shows one of 10. In this case the percentage score is calculated as follows: the absolute dif-ference between both systems is 20, the value of the PS system (10) is fixed at 100%. As a result the calculated difference is 200% with a disadvantage for PLA (in the tables marked by a red shading). In a different category PLA has a score of 10 and PS has one of 30. Also in this case the absolute difference is 20, but now the PLA score of 10 is fixed at 100%. In this case the difference would also be calculated as 200% but this time it is highlighted by a green shading, indicating an advantage for PLA18.

In the tables comparisons of packaging systems are only done for impact indicator results (but not for inventory indicator results).

It should be mentioned that impact indicator results obtained in LCA stand for potential im-pacts. For the ease of writing and reading this LCA characteristic is not continuously re-peated in the following text; i.e. global warming potential is referred to as global warming, acidification potential as acidification etc.

18 Percentages could also be read as a factor, according to the formula

%100%100%+

=Xfactor

With the above given example (difference 200%), the indicator value of the system with the higher en-vironmental impact would be 3 times the value of the system with the lower impact.

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4.1 Base Scenarios

4.1.1 System characteristics

The system characteristics of the clamshells under study are summarized in tables 4-1 to 4-4. The tables are followed by a description highlighting some important aspects of the life cy-cle steps.

Besides the environmental impact categories, the graphs of the base scenarios also show selected additional indicators at inventory level (figure 4-3). The cumulative primary energy demand (CED) serves as an indicator for the overall energy use and is shown separated for renewable and non-renewable CED.

PLA clam shell

The contributions of individual life cycle steps to the gross system results of the PLA clam shell are summarized in table 4-1.

Table 4-1 Contributions of life cycle steps to gross system results of PLA clam shell

Impact Category Plastics production

Transport plastics

Clam shell production

Recycling Disposal

Fossil Resource Consumption 79% 7% 8% 6% 0% Global Warming 37% 4% 13% 32% 14% Summer Smog (POCP) 90% 4% 2% 3% 1% Acidification 68% 22% 4% 4% 1% Terrestrial Eutrophication 70% 19% 3% 5% 2% Carcinogenic Risk 2% 24% 32% 29% 13% Human Toxicity (PM10) 72% 19% 4% 4% 2% Aquatic Eutrophication 99% 0% 0% 1% 0% Additional Indicators Farm Land 100% 0% 0% 0% 0% CED (renewable) 98% 0% 1% 0% 0% CED (non-renewable) 74% 4% 15% 7% 0% CED (total) 80% 3% 12% 5% 0%

The plastics production step is predominant in the environmental impacts of the PLA system.

The transport of PLA pellets to the clam shell producer has less influence on the indicator re-sults, however contributions can be seen especially in the impact categories Acidification, Terrestrial Eutrophication, Human Toxicity (Carcinogenic Risk) and Human Toxicity (PM 10)19.

19 Transport distances are high for PLA pellets since they are imported from the US. Transport dis-

tances for the raw materials for the fossil based polymers are roughly similar, – crude oil from middle east– but they are incorporated in the aggregated datasets for the plastic production sec-tor.

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Contributions of the conversion of PLA pellets into clam shells are mainly seen in the cate-gory Human Toxicity (carcinogenic risk).

The waste management steps recycling and disposal are especially visible in the categories Global Warming and Human Toxicity (Carcinogenic Risk).

PS clam shell

The contributions of individual life cycle steps to the gross system results of the PS clam shell are summarized in table 4-2.

Table 4-2 Contributions of life cycle steps to gross system results of PS clam shell

Impact Category Plastics production

Transport plastics

Clam shell production

Recycling Disposal

Fossil Resource Consumption 94% 1% 3% 2% 0% Global Warming 45% 0% 9% 25% 21% Summer Smog (POCP) 95% 1% 1% 2% 1% Acidification 79% 1% 7% 8% 5% Terrestrial Eutrophication 64% 3% 6% 14% 12% Carcinogenic Risk 89% 0% 3% 6% 2% Human Toxicity (PM10) 75% 2% 6% 9% 7% Aquatic Eutrophication 90% 0% 2% 8% 0% Additional Indicators Farm Land 0% 0% 0% 0% 0% CED (renewable) 31% 0% 47% 22% 0% CED (non-renewable) 83% 0% 10% 6% 0% CED (total) 83% 0% 11% 6% 0%

The plastics production step is also predominant in the environmental impacts of the PS sys-tem.

The transport of PS pellets to the clam shell producer is the sector with the lowest influence on the indicator results, because of the assumed short transport distances of polymers within Europe.20

Contributions of the conversion of PS pellets into clam shells are in the range of a few per-cent for most categories.

The waste management steps recycling and disposal are especially visible in the categories Acidification, Global Warming, Terrestrial Eutrophication, Human Toxicity (PM 10) and Hu-man Toxicity (Carcinogenic Risk).

20 see footnote No 16

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PP clam shell

The contributions of individual life cycle steps to the gross system results of the PS clam shell are summarized in table 4-3.

Table 4-3 Contributions of life cycle steps to gross system results of PP clam shell

Impact Category Plastics production

Transport plastics

Clam shell production

Recycling Disposal

Fossil Resource Consumption 92% 1% 4% 3% 0% Global Warming 35% 0% 14% 28% 23% Summer Smog (POCP) 95% 1% 1% 2% 1% Acidification 66% 2% 12% 11% 8% Terrestrial Eutrophication 53% 4% 10% 16% 17% Carcinogenic Risk 0% 3% 26% 48% 23% Human Toxicity (PM10) 63% 3% 11% 12% 10% Aquatic Eutrophication 0% 99% 0% 1% 0% Additional Indicators Farm Land 0% 0% 0% 0% 0% CED (renewable) 39% 0% 44% 16% 0% CED (non-renewable) 79% 0% 14% 7% 0% CED (total) 78% 0% 14% 7% 0%

The plastics production step is also predominant in the environmental impacts of the PP sys-tem.

The transport of PS pellets to the clam shell producer is the sector with the lowest influence on the indicator results, because of the assumed short transport distances of polymers within Europe.21

Contributions of the conversion of PP pellets into clam shells are relevant for Human Toxicity (carcinogenic risk) and Aquatic Eutrophication.

The waste management steps recycling and disposal are mostly visible in Global Warming, Carcinogenic Risk and Aquatic Eutrophication.

21 see footnote No 16

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PET clam shell

The contributions of individual life cycle steps to the gross system results of the PET clam shell are summarized in table 4-4.

Table 4-4 Contributions of life cycle steps to gross system results of PET clam shell

Impact Category Plastics production

Transport plastics

Clam shell production

Recycling Disposal

Fossil Resource Consumption 93% 1% 3% 3% 0% Global Warming 52% 0% 9% 23% 16% Summer Smog (POCP) 98% 0% 0% 1% 0% Acidification 86% 1% 4% 5% 3% Terrestrial Eutrophication 76% 3% 5% 9% 8% Carcinogenic Risk 96% 0% 1% 2% 0% Human Toxicity (PM10) 84% 2% 4% 6% 4% Aquatic Eutrophication 91% 0% 1% 8% 0% Additional Indicators Farm Land 0% 0% 0% 0% 0% CED (renewable) 48% 0% 34% 18% 0% CED (non-renewable) 83% 0% 10% 7% 0% CED (total) 83% 0% 10% 7% 0%

The plastics production step is also predominant in the environmental impacts of the PET system.

The transport of PS pellets to the clam shell producer is the sector with the lowest influence on the indicator results, because of the assumed short transport distances of polymers within Europe.22

Contributions of the conversion of PET pellets into clam shells are up to 9% for Global Warming.

The waste management steps recycling and disposal are visible in most categories.

Notes:

The blue stack for PLA in the bars representing Global Warming takes into account the fixa-tion of CO2 during corn production and therefore does not express the full extent of CO2 emissions from process operations (see section 3.1.5).

The relatively high contributions of the waste management sectors recycling and disposal to the category Global Warming are associated with carbon dioxide emissions generated when the used packaging material undergoes thermal treatment. CO2 emissions from thermal treatment are fully accounted for both PLA and fossil-based polymers.

Environmental impacts of the clam shell production step are mainly related to the use of elec-trical energy in extrusion and thermoforming processes.

22 see footnote No 16

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For the fossil-based clam shell systems PS, PP and PET, the blue polymer stack comprises the fossil feedstock and fossil fuel consumption, whereas for PLA it only includes the latter since no fossil feedstock is required.

The polymer stacks (blue) for PET production when compared to PS and PP production are explicitly large in the categories Summer Smog, Acidification, Terrestrial Eutrophication and Human Toxicity (carcinogenic risk). The latter are particularly small in the case of PP.

These differences can partly be explained looking at the differences in clam shell weight and polymer production systems. In the case of PS the production includes aromatic substances like benzene, ethyl benzene and styrene. Also in the PET production systems aromatics (xy-lenes) as well as other chemicals such as methanol, ethylene glycol and acetic acid are re-quired. Those chemicals are not used in the PP production system. After the production of Propylene the monomer is simply converted into the polymer.

It is a general problem that for highly aggregated datasets, like in the case of the available of the polymer data, it is not possible to fully understand and describe in a quantitative way the observed differences.

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Figure 4-1 Base scenarios for the clam shells examined. Categories Fossil Resource Consump-tion, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication

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Figure 4-2 Base scenarios for the clam shells examined. Categories Human Toxicity, Aquatic Eu-trophication and additional indicator Farm Land

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Figure 4-3 Base scenarios for the clam shells examined. Additional indicator cumulative primary energy demand (CED). Non-renewable primary energy is comprised of fossil and nu-clear energy. Total primary energy is the sum of renewable and non-renewable primary energy.

The numerical values of the scenarios illustrated in figure 4-1 to 4-3 are given in Appendix F.

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4.1.2 System comparison

A numerical comparison of the net environmental impact indicator results (shown as grey bars in figures 4-1 to 4-3) for PLA and the alternative clam shell packaging systems under investi-gation is given in table 4-5.

Table 4-5 Pair-wise comparison of alternative clam shell systems with PLA clam shells [Green fields mean an advantage for PLA, red fields mean a disadvantage for PLA.]

Impact Category PS PP PET Fossil Resource Consumption 211% 243% 317%

Global Warming 60% 30% 93%

Summer Smog (POCP) 31% 62% 440%

Acidification 85% 147% 15%

Terrestrial Eutrophication 114% 137% 14%

Carcinogenic Risk 2115% 129% 6145%

Human Toxicity (PM10) 106% 160% 3%

Aquatic Eutrophication 1140% 14% 540%

Note: Percentage values are calculative differences derived from the net indicator results. They refer to the sys-tem with the lower environmental impact.

The PLA system shows advantages compared to all three conventional polymers in the categories Fossil Resource Consumption, Global Warming, Summer Smog (POCP) and Human Toxicity (Carcinogenic Risk). Disadvantages of the PLA system are observed in the category Terrestrial Eutrophication.

For the remaining impact categories, comparisons of the PLA system with the alternative systems do not show a clear trend. The LCA results for Acidification and Human Toxicity (PM10) show disadvantages of PLA when compared to the PS and PP systems.

On the other hand, advantages in these categories are found when compared to the PET system.

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4.2 PLA Scenario Variants

4.2.1 Variants concerning PLA production

Background information about these scenarios is documented in section 2.3.2 and 3.1.5.

The environmental impacts of clam shells based on PLA 6 and PLA/NG are given in figure 4-4 to figure 4-6. A numerical comparison of the net environmental impact indicator results is given in table 4-6. Other than for the comparison of alternative clam shell systems, the calcu-lated percentage values here always refer to the PLA 5 base case. Consequently, green fields indicate improvement and red fields a change for the worse in the ecological profile. The numerical values of the scenarios as illustrated in figure 4-4 to 4-6 are given in Appendix F.

The carbon dioxide fixation during corn production is taken into account in the PLA inventory datasets provided by NatureWorks. In case of PLA 6 the greenhouse gas emissions from cradle-to-polymer are offset by RECs. This effect can be seen in the category Global Warm-ing – here the relative contribution of the polymer production step to the PLA system result approaches zero.

Due to less energy consuming fermentation technology and the accountancy of RECs, in case of PLA/NG, the global warming potential of the PLA production step becomes negative (see blue bars in category Global Warming in figure 4-4).

The improvement potential in the category Summer Smog (POCP) that can be seen when the net results of PLA 6 are compared with PLA 5 is mainly related to a reduction of VOC emissions. In the comparison of PLA/NG with PLA 5 additionally NMVOC, methane as well as ethanol emissions are considerably reduced.

The high increase of 158% and 86% for the category Human Toxicity (carcinogenic risk) in the comparison of PLA 6 and PLA/NG with PLA 5 can be traced back to chromium emissions to air The increase in chromium emissions are related to the wind power certificates, which have been considered in the NatureWork inventory dataset with data from [Vestas, 2005]. As for unsecified chromium in this current LCA study it is generally assumed that 10% of Cr emissions are considered as carcinogenic CrVI emissions (see appendix A, section A.6.1)

The relatively high improvement potentials in the category Fossil Resource Consumption can be traced back to a reduced demand of hard coal in case of PLA 6 and additionally to sav-ings in oil and natural gas use in the PLA/NG system. The latter is a result of reduced heat demand in the future fermentation process.

Considerable improvement of the ecological profile of PLA can also be observed in the cate-gories Acidification and Terrestrial Eutrophication. This effect can mainly be attributed to REC-based wind power electricity having typically lower air emissions (e.g. NOx, SOx) when compared to conventional power pools.

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Figure 4-4 Variant scenarios for the PLA clam shells concerning PLA production. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terrestrial Eu-trophication

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Figure 4-5 Variant scenarios for the PLA clam shell concerning PLA production. Categories Hu-man Toxicity, Aquatic Eutrophication and additional indicator Farm Land

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Figure 4-6 Variant scenarios for the PLA clam shell concerning PLA production. Additional indica-tor cumulative primary energy demand (CED). Non-renewable primary energy is com-prised of fossil and nuclear energy. Total primary energy is the sum of renewable and non-renewable primary energy.

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Table 4-6 Pair-wise comparison of PLA production variations PLA 6 and PLA/NG with PLA 5 base scenario [Green fields mean an improvement, red fields mean a change for the worse.]

Impact Category PLA 6 PLA/NG Fossil Resource Consumption 45% 90%

Global Warming 47% 69%

Summer Smog (POCP) 9% 58%

Acidification 42% 43%

Terrestrial Eutrophication 24% 34%

Human Toxicity (Carcinogenic Risk) 158% 86%

Human Toxicity (PM10) 39% 43%

Aquatic Eutrophication 0% 11%

Note: Percentage values are calculative differences derived from the net indicator results. They represent the re-duction or increase expressed as a percentage of the PLA 5 base case.

4.2.2 Alternative end-of-life options for treatment of PLA packaging wastes

Background information of these scenarios is documented in section 2.3.2, 3.3.4 and 3.3.5.

The environmental impacts of composting, anaerobic digestion and chemical recycling are visible in the results shown in figures 4-7 to 4-9. A numerical comparison of the net environ-mental impact indicator results is given in table 4-7. Other than for the comparison of alterna-tive clam shell systems, the calculated percentage values here always refer to the PLA 5 base case where recovered PLA undergoes feedstock recycling processes. Consequently, green fields indicate improvement and red fields a change for the worse in the ecological pro-file. The numerical values of the scenarios as illustrated in figure 4-8 to 4-10 are given in Ap-pendix F.

Relevant emissions released during the composting process are CO2, methane and other volatile organic compounds being generated in the degradation steps. Those emissions mainly originate from transformation of organic substance in the after-composting step. As the after-composting does not take place in an encapsulated system, they are directly re-leased to the atmosphere. Especially methane and VOC emissions cause the relatively high impact in the Summer Smog category (see also section 3.3.4).

In the case that source-separated PLA packaging waste undergoes anaerobic digestion in-stead of feedstock recycling (base case), the net environmental impacts are rather similar. In case of composting impacts tend to be higher, particularly for Fossil Resource Consumption, Global Warming and Summer Smog.

The latter, besides the above named process emissions, is due to the fact, that, the compost product does replace products with lower environmental loads when compared to the base case where PLA is used as a secondary fuel in a blast furnace substituting hard coal.

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The advantage of the digestion option compared to the composting alternative is mainly re-lated to the electricity generated with the obtained biogas. This electricity does replace grid electricity.

In the case that source-separated PLA packaging waste is chemically recycled, all impact categories show an improvement, except Fossil Resource Consumption and Human Toxicity (carcinogenic risk) which show increased indicator results. This observation can be attributed to additional recycling efforts as well as reduced credits for energy recovery of PLA.

Comparing the three alternative waste management options to the base case, only the chemical recycling route shows relevant improvement potentials concerning the net environ-mental impacts. This effect is mainly caused by savings in primary PLA polymer demand.

Table 4-7 Pair-wise comparison of PLA end-of-life variations with PLA 5 base scenario. [Green fields mean an improvement, red fields mean a change for the worse.]

Impact Category PLA (Composting)

PLA (Digestion)

PLA (ChemR)

Fossil Resource Consumption 77% 67% 31%

Global Warming 19% 0% 29%

Summer Smog (POCP) 879% 114% 27%

Acidification 2% 1% 42%

Terrestrial Eutrophication 1% 0% 42%

Human Toxicity (Carcinogenic Risk) 38% 3% 54%

Human Toxicity (PM10) 2% 1% 43%

Aquatic Eutrophication 14% 17% 39%

Note: Percentage values are calculative differences derived from the net indicator results. They represent the re-duction or increase expressed as a percentage of the PLA 5 base case.

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Figure 4-7 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terres-trial Eutrophication

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Figure 4-8 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Categories Human Toxicity, Aquatic Eutrophication and additional indicator Farm Land

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Figure 4-9 Variant scenarios for the PLA clam shell concerning PLA end-of-life options. Additional indicator cumulative primary energy demand (CED). Non-renewable primary energy is comprised of fossil and nuclear energy. Total primary energy is the sum of renewable and non-renewable primary energy.

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4.2.3 Combined Variants

Combination of PLA 6 with alternative end-of-life options

Background information of these scenarios is documented in sections 2.3.2, 3.1.5, 3.3.4 and 3.3.5.

The environmental impacts of composting, anaerobic digestion and chemical recycling of PLA 6 clam shells are visible in the results shown in figures 4-10 to 4-13.

The overall pattern of the comparison of alternative recovery routes with the PLA 6 case in all categories is very similar to the results of the variant scenarios of the PLA 5 base scenario with alternative recovery routes. The main difference is that the indicator results of PLA 6 are generally smaller than those of PLA 5 which also affects the net indicator results of the re-spective end-of-life options.

The numerical values of the scenarios as illustrated in figure 4-10 to 4-13 are given in Ap-pendix F.

Combination of PLA/NG with alternative end-of-life options

Background information of these scenarios is documented in sections 2.3.2, 3.1.5, 3.3.4 and 3.3.5. Additionally, for these variant scenarios, it is assumed that chemical recycling to lactic acid and polylactide production take place in a facility where wind power is used for all proc-esses requiring electricity. This assumption is in line with the conditions underlying the PLA 6 production dataset.

The environmental impacts of composting, anaerobic digestion and chemical recycling of PLA/NG clam shells are visible in the results shown in figures 4-12 to 4-13.

The overall pattern of the comparison of alternative recovery routes with the PLA/NG case in all categories is very similar to the results of the variant scenarios of the PLA 5 base scenario with alternative recovery routes. The main difference is that the starting point of PLA/NG is generally lower than of PLA 5. One exception here is the category Global Warming, where the chemical recycling options shows approximately the same environmental impacts as the PLA/NG case with the feedstock recycling option. This observation can be traced back to the PLA/NG dataset where PLA production shows a negative global warming potential. Conse-quently “savings” in environmental loads typically achieved by the avoidance of primary polymer production are not in effect here.

The numerical values of the scenarios as illustrated in figure 4-12 to 4-13 are given in Ap-pendix F.

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62 LCA for food packaging from PLA and alternative materials IFEU-Heidelberg

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Figure 4-10 Combined variant scenarios for PLA 6 clam shells and alternative end-of-life options. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidifica-tion, Terrestrial Eutrophication, Aquatic Eutrophication

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Figure 4-11 Combined variant scenarios for PLA 6 clam shells and alternative end-of-life options. Categories Human Toxicity, Aquatic Eutrophication and additional indicators Farm Land, CED (total), CED (non-renewable) and CED (renewable)

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Figure 4-12 Combined variant scenarios for PLA /NG clam shells and alternative end-of-life options. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication, Aquatic Eutrophication

Aquatic Eutrophication

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Figure 4-13 Combined variant scenarios for PLA /NG clam shells and alternative end-of-life options. Categories Human Toxicity, Aquatic Eutrophication and additional indicators Farm Land, CED (total), CED (non-renewable) and CED (renewable)

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4.2.4 Alternative end-of-life option for treatment of PET packaging waste

The influence of mechanical recycling of PET post-consumer packaging waste via a PET polymer fraction on the environmental performance of the PET clam shell has been investi-gated with this variant scenario (see section 2.3.2)

The environmental effects of mechanical recycling of PET clam shells are visible in the re-sults shown in figures 4-14 to 4-15. A numerical comparison of the net environmental impact indicator results is given in table 4-8. The numerical values of the scenario illustrated in fig-ure 4-14 to 4-15 are given in Appendix F.

Table 4-8 Pair-wise comparison of PET end-of-life variation with mechanical recycling of polymer fraction with PET base scenario. [Green fields mean an improvement, red fields mean a change for the worse.]

Impact Category PET (MechR)

Fossil Resource Consumption 38% Global Warming 43% Summer Smog (POCP) 49% Acidification 45% Terrestrial Eutrophication 44% Carcinogenic Risk 49% Human Toxicity (PM10) 45% Aquatic Eutrophication 20%

Note: Percentage values are calculative differences derived from the net indicator results. They represent the re-duction expressed as a percentage of the PET base case.

Considerable improvements in the overall PET clam shell environmental performance can be achieved by mechanical recycling (instead of a recovery via the mixed plastics fraction) of post-consumer PET packaging waste due to the predominant influence of the primary poly-mer production step on the indicator results.

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Figure 4-14 Variant scenario for the PET clam shell with mechanical recycling of PET polymer frac-tion. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidi-fication, Terrestrial Eutrophication

Fossil Resource Consumption

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Figure 4-15 Variant scenario for the PET clam shell with mechanical recycling of PET polymer frac-tion. Categories Human Toxicity, Aquatic Eutrophication and additional indicators CED (total) and CED (non-renewable)

Aquatic Eutrophication

Human Toxicity: Carcinogenic Risk

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5 Evaluation In this section the results of the base scenarios presented in section 4 shall be further ana-lysed. Emphasis will be put on uncertainties related with data and system assumptions which might affect the overall results. The results of the sensitivity scenarios listed in table 2-6 are presented in section 5.2. Section 5.3 addresses the limitations and section 5.4 the overall data quality.

5.1 Determination and evaluation of significant parameters

5.1.1 Important life cycle aspects

The environmental profiles of the four packaging systems examined are strongly dominated by the life cycle step “polymer production”. This step is accountable for more than 80% of the environmental impact in most environmental impact categories with the exception of Global Warming. In this category the share of the polymer production is between 35% and 50%.

The second most important life cycle step is the end-of-life phase. For the indicator Global Warming, disposal and recycling together account for 80% (PP), 62% (PLA), 72% (PS) and 53% (PET) of the greenhouse gas emissions of the gross system results.

Less relevant are the conversion of polymer pellets into the clam shells and the transport of the polymers to the clam shell production sites. The exception here is the transport of PLA to Germany, which is not a surprise considering the long transport distance. For this step the environmental categories Acidification, Terrestrial Eutrophication and Human Toxicity (PM10) take between 19% to 22% of the gross environmental loads of the system23.

5.1.2 Evaluaton of relevant data and system parameters

The datasets and system parameters which influence the life cycle steps addressed in sec-tion 5.1.1 will be reviewed in the following paragraphs.

Polymer production This life cycle step is completely determined by the underlying polymer datasets described in section 3.1. PP, GPPS and PET inventory data are datasets developed and published by Plastics Europe in an aggregated cradle to polymer factory gate format. In the case of PP and GPPS no other inventory data are made available by the industry. For PET production an additional inventory was calculated within a recent LCA study [IFEU 2004b], but not published separately. For PLA production inventory data were developed by NatureWorks. The data were used in this study but are not published yet. Given this situation the only sensitivity analysis done at this point was for PET data, using the PETCORE data instead of the Plastics Europe data. 23 see footnot No 16

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Overall the inventory datasets mentioned in this section can be regarded as the best possible choice for the purpose of this study.

Conversion into polymer articles (clam shells) The available data from Vitembal are considered appropriate and sufficiently reliable within the framework of a case study approach as implemented in this LCA.

Process data for recovery and recycling The contribution of this area is mainly caused by CO2 emissions from the incineration of clam shells collected via the grey bin and from feedstock recycling as well as thermal treatment. In the related process models, CO2 emissions are calculated directly from the carbon content of the individual materials. The global warming figures related to these processes are hence adequately reliable.

PLA transport to converters The submitted transport distance from the PLA production location in the US to Europe is ac-ceptable. For transportation by truck in Europe the same values are used for all the poly-mers. The inventory dataset for the ocean ship is setup and maintained by IFEU and reflects the current knowledge for modelling environmental loads regarding overseas transport. The data are considered to be reasonable and sufficiently reliable for the purpose of this study.

Clamshell specifications The available packaging specifications correspond to those currently brought to the market by Vitembal. Consequently, they are considered appropriate and sufficiently reliable within the framework of the case study approach implemented in this LCA.

Recovery and recycling rates The applied recovery and recycling rates for clam shells from PET, PP, PS and PLA are based on material mass flow data collected and maintained at DSD AG. They are considered to be sufficiently reliable and applicable for the purpose of this study.

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5.2 Sensitivity Analysis

5.2.1 Treatment of PLA process waste from converting

At the time the underlying study was performed about 16%24 of each unit of PLA polymer in-put ended up as converting process waste that had to be kept on stock. Despite of this, an established production with a fully working internal recycling of PLA waste has been as-sumed in the base scenario for PLA clam shells (see section 2.3.1, figure 2-2). The influence of this assumption on the final results has been examined in two scenarios:

a) all process waste undergoes thermal treatment by using it as a secondary fuel in a cement kiln displacing hard coal; and

b) all process waste is recycled in a chemical recycling process.

The results are shown in figures 5-1 to 5-3. A numerical comparison of the net environmental impact indicator results is given in table 5-1. The numerical values of the scenario as illus-trated in figure 5-1 to 5-3 are given in Appendix F.

Table 5-1 Pair-wise comparison of alternative clam shell systems with PLA clam shells for sensitivity scenarios “treatment of PLA process waste” [Green fields mean an advantage for PLA, red fields mean a disadvantage for PLA.]

Impact Category

PS PP PET

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Sens

(cem.

Kiln)

Sens

(chem.

rec.)

Base

Sens

(cem.

Kiln)

Sens

(chem. rec.)

Base

Sens

(cem.

Kiln)

Sens

(chem. rec.)

Fossil Re-source Consumption

211% 152% 168% 243% 179% 195% 317% 239% 260%

Global Warming 60% 46% 52% 30% 19% 24% 93% 76% 84%

Summer Smog (POCP) 31% 11% 25% 62% 38% 55% 440% 360% 418%

Acidification 85% 116% 92% 147% 188% 157% 15% 1% 11%

Terrestrial Eutrophication 114% 149% 124% 137% 176% 148% 14% 33% 19%

Carcinogenic Risk 2115% 2301% 1971% 129% 148% 114% 6145% 6669% 5737%

Human Toxicity (PM10) 106% 141% 115% 160% 203% 170% 3% 13% 1%

Aquatic Eutrophication 1140% 1357% 1190% 14% 3% 10% 540% 652% 566%

Note: Percentage values are calculative differences derived from the net indicator results. They refer to the sys-tem with the lower environmental impact.

24 Information taken from [Vitembal 2005a]

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Roughly spoken, if chemical recycling is assumed for treatment of process waste currently kept on stock, net indicator results of the PLA system are only slightly worse than in the base case. Consequently, this sensitivity analysis in principal does not change the ranking be-tween the systems within the individual impact categories.

Although disadvantages are clearly visible if the PLA process waste were used as a secon-dary fuel in cement kilns, effects on the ranking between the packaging systems is still lim-ited. Changes are merely for Human Toxicity (PM10) and Aquatic Eutrophication where the advantages of the PLA system versus the PET system found in the base scenario switch into disadvantages.

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Figure 5-1 Sensitivity scenario for the PLA clam shell concerning treatment of PLA waste from con-verting. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication [“cem. kiln” means PLA process waste goes to cement kiln; “chem.rec.” means that process waste is chemically recycled]

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

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Figure 5-2 Sensitivity scenario for the PLA clam shell concerning treatment of PLA waste from con-verting. Categories Human Toxicity, Aquatic Eutrophication and additional indicator Farm Land [“cem. kiln” means PLA process waste goes to cement kiln; “chem.rec.” means that process waste is chemically recycled]

-1

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(base)

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PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

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Figure 5-3 Sensitivity scenario for the PLA clam shell concerning treatment of PLA waste from con-verting. Additional indicators CED renewable, CED non-renewable and CED total [“cem. kiln” means PLA process waste goes to cement kiln; “chem.rec.” means that process waste is chemically recycled]

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CED (non-renewable)

CED: Cumulative primary energy demand

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

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PLA 5(chemrec.)

PLA 5(base)

PS PP PETPLA 5(cem.kiln)

PLA 5(chemrec.)

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5.2.2 Selection of PET inventory data

In the base scenarios, as discussed in section 4-1, the PET data used was based on data published by PlasticsEurope. An alternative dataset has been generated by Petcore [IFEU 2004]. The influence of the selection of the inventory datasets on the outcome of the LCA has been examined by a sensitivity analysis. The PET inventory data sets are documented in section 3.1.3 and 3.1.4. The numerical values of the underlying figures 5-4 to 5-6 are given in Appendix F.

The outcome of the sensitivity analysis is shown in figure 5-4 to 5-6. A numerical comparison of the net environmental impact indicator results for both PET scenarios compared with the PLA 5 base scenario is given in table 5-2.

Table 5-2 Pair-wise comparison of PET clam shell systems with PLA 5 clam shells for sensitivity scenario “selection of PET inventory data” [Green fields mean an advantage for PLA, red fields mean a disadvantage for PLA.]

Impact Category PET (Plastics Europe)

PET (Petcore)

Fossil Resource Consumption 317% 343%

Global Warming 93% 72%

Summer Smog (POCP) 440% 53%

Acidification 15% 101%

Terrestrial Eutrophication 14% 90%

Carcinogenic Risk 6145% 1591%

Human Toxicity (PM10) 3% 119%

Aquatic Eutrophication 540% 1%

Note: Percentage values are calculative differences derived from the net indicator results. They refer to the system with the

lower environmental impact.

The selection of the PET inventory data set has no effect on the ranking within the categories Fossil Resources Consumption, Global Warming, Terrestrial Eutrophication, and Human Toxicity (carcinogenic risk). In the categories Acidification, Human Toxicity (PM10) and Sum-mer Smog (POCP) the relatively close-by scores for PLA 5 and PET (PlasticsEurope) turn into a distinctively better score for the PET (Petcore) scenario. In the category Aquatic Eutro-phication the clearly lower score for PET (PlasticEurope) levels out in the case of PET(Petcore).

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Figure 5-4 Sensitivity scenario concerning PET inventory data. Categories Fossil Resource Con-sumption, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication

Fossil Resource Consumption

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Figure 5-5 Sensitivity scenario concerning PET inventory data. Categories Human Toxicity, Aquatic Eutrophication and additional indicator Farm Land

Aquatic Eutrophication

Human Toxicity: Carcinogenic Risk

Use of Nature: Farm Land

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Figure 5-6 Sensitivity scenario concerning PET inventory data. Additional indicators CED renew-able, CED non-renewable and CED total

CED (renewable)

CED (total)

CED (non-renewable)

CED: Cumulative primary energy demand

PLA 5 PS PP PET(PlEurope)

PET(Petcore)

PLA 5 PS PP PET(PlEurope)

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PET(Petcore)

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5.2.3 Assumptions concerning system allocation

Due to the subjective character of allocation the influence of the 100% allocation method chosen for the base scenarios is examined by applying a 50/50 method. For a better under-standing of the implementation of this 50/50 method in the PLA scenario some additional ex-planations is given below.

For symmetry of application of the allocation rules described in chapter 1.9, the allocation must also take into account the implicit credits in the inventory data underlying the polymer production process (PP-A) in system A.

In the dataset made available by NatureWorks the fixation of CO2 during plant growth are re-flected in the process balance in form of CO2 credits (the CO2 emissions specified in the cra-dle-to-factory gate dataset are calculated as ”CO2 process emissions“ minus ”CO2 fixation during corn production“).

The way this has been dealt with in the allocation procedure shall be explained with the help of figure 5-7. In contrast to the similar figure 1-4, CO2 emissions (“+CO2“) and CO2 fixation (“-CO2“) are additionally indicated. The “-CO2*“ indicated in ”PP-A“ correspond to the renewable C content in the feedstock of the polymer produced. The “+CO2*“ indicated in „MSWI-A*“ and „MSWI-B*“ are directly related to the C content in the feedstock of the product obtained in product system A. The asterisks serve to highlight this relationship.

The upper graph shows the allocation according to the 100%-method. Here, all credits asso-ciated with PP-A’s “-CO2“ in system A are fully balanced out by the release of “+CO2*“ in „MSWI-A*“ which is allocated with 100% to system A. The mass balance rule is fulfilled.

In the 50/50 method the burden of +CO2* from MSWI-A is shared between system A and B. These CO2 emissions would be greenhouse gas neutral if “-CO2“ in PP-A would not have been implicitly credited to system A. Consequently, if greenhouse gas positive CO2 emis-sions occuring at MSWI-A are shared between system A and B, also the credit of “-CO2“ in PP-A must be shared between both systems.

Figures 5-8 to 5-10 show the results of both allocation methods if applied to the clam shells scenarios examined in this study. A numerical comparison between PLA 5 and alternative clam shell systems is given in table 5-4 for both the base and sensitivity scenarios.

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Figure 5-7 Allocation of CO2-uptake related to C-content in PLA in the 50/50 method

Polymer Production

(PP-A)

Polymer Production

(PP-A)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

MSWI(MSWI-A)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

MSWI(MSWI-B)MSWI

(MSWI-B)

System A:+ CO2PP-A - CO2*PP-A + CO2Pr-A + CO2Rec-A – CO2PP-B + CO2*MSWI-A

System B:CO2PP-B + CO2Pr-B + CO2*MSWI-B – CO2*MSWI-A

Allocation: 100% approach

Recovery(Rec-A)Recovery(Rec-A)

-100%

+100%

-100%

MSWI(MSWI-A)MSWI

(MSWI-A)

+ CO2

- CO2*

+ CO2

+ CO2

Processing &Production

(PP-B)

Processing & Production

(PP-B)

Processing & Production

(PP-B)

+ CO2*

+ CO2

+ CO2

+ CO2

+ CO2

+ CO2*

Polymer Production

(PP-A)

Polymer Production

(PP-A)

Product AProduction &

Use(Pr-A)

Product AProduction &

Use(Pr-A)

MSWI(MSWI-A)

Product BProduction &

Use(Pr-B)

Product BProduction &

Use(Pr-B)

MSWI(MSWI-B)MSWI

(MSWI-B)

System A:+ CO2PP-A – 0.5*CO2*PP-A + CO2Pr-A+ 0.5*CO2Rec-A – 0.5*CO2PP-B + 0.5*CO2*MSWI-A

Allocation: 50% approach

Recovery(Rec-A)Recovery(Rec-A)

-50% +50%

+50% +50%

+50% -50%

MSWI(MSWI-A)MSWI

(MSWI-A)

+ CO2

- CO2*

+ CO2

+ CO2

Processing &Production

(PP-B)

Processing & Production

(PP-B)

Processing & Production

(PP-B)

+ CO2*

+ CO2

+ CO2

+ CO2

+ CO2

+ CO2*

System B:+ 0.5*CO2PP-B – 0.5*CO2*PP-A+ CO2Pr-B + 0.5*CO2Rec-A+ CO2*MSWI-B – 0.5*CO2MSWI-A

+100%

+100%

+0%

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Figure 5-8 Sensitivity scenarios for all examined clam shell systems with 50% system allocation method. Categories Fossil Resource Consumption, Global Warming, Summer Smog, Acidification, Terrestrial Eutrophication

Summer Smog (POCP)

PLA 5 PS PP PETPLA 5 PS PP PET

PLA 5 PS PP PET

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net results(100% system allocation)

net results(50% system allocation)

net results(100% system allocation)

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Figure 5-9 Sensitivity scenarios for all examined clam shell systems with 50% system allocation method. Categories Human Toxicity, Aquatic Eutrophication and additional indicator Farm Land

Aquatic Eutrophication

PLA 5 PS PP PETPLA 5 PS PP PET

PLA 5 PS PP PETPLA 5 PS PP PET

Human Toxicity: Carcinogenic Risk

Use of Nature: Farm Land

PLA 5 PS PP PETPLA 5 PS PP PET

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net results(100% system allocation)

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Figure 5-10 Sensitivity scenarios for all examined clam shell systems with 50% system allocation method. Additional indicators CED renewable, CED non-renewable and CED total.

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CED (renewable)

CED (total)

PLA 5 PS PP PETPLA 5 PS PP PET

CED (non-renewable)

PLA PS PP PETPLA PS PP PET

CED: Cumulative primary energy demand

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Table 5-3 Pair-wise comparison alternative shell systems with PLA 5 clam shells for sensitivity scenarios ”100% versus 50% allocation” [Green fields mean an advantage for PLA, red fields mean a disadvantage for PLA.]

Impact Category PS PP PET Base Sens Base Sens Base Sens

Fossil Resource Consumption 211% 217% 243% 231% 317% 272%

Global Warming 60% 34% 30% 6% 93% 60%

Summer Smog (POCP) 31% 51% 62% 78% 440% 471%

Acidification 85% 56% 147% 117% 15% 24%

Terrestrial Eutrophication 114% 93% 137% 129% 14% 9%

Carcinogenic Risk 2115% 1987% 129% 65% 6145% 5484%

Human Toxicity (PM10) 106% 77% 160% 134% 3% 11%

Aquatic Eutrophication 1140% 1040% 14% 25% 540% 511%

Note: Percentage values are calculative differences derived from the net indicator results. They refer to the sys-tem with the lower environmental impact.

Compared to the base scenario, the ranking of systems does not change when the 50% sys-tem allocation method is applied. Relative differences between the PLA and alternative sys-tems are smaller in some cases, but still show the same trend as in the base scenario.

The fact that the relative differences between some alternative systems compared are smaller when the 50% system allocation method is applied can be attributed to the generally larger influence of credits for secondary products of fossil-based polymer systems on all im-pact category indicator results. Consequently, the effect of the system allocation method in indicator results is higher in case of conventional polymers as compared to PLA.

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5.2.4 Accounting of carbon sequestration in agricultural soils

Roughly 5% of the carbon dioxide credit assigned by NatureWorks to the PLA inventory dataset is due to the adsorption of CO2 from the atmosphere by agricultural soils, the so-called carbon sequestration (Appendix E and section 3.1.5].

On the other hand, agriculture activities can also release CO2 to the atmosphere. Therefore, a carbon sink occurs when carbon sequestration is greater than carbon releases over some time period [US EPA].

Carbon accumulation in soils eventually reaches a saturation point, beyond which additional sequestration is no longer possible. This happens, for example, when the organic matter in soils builds back up to original levels before losses occurred [US EPA]. The degree / velocity of this process depends on the agricultural activities. Increasing carbon storage is a conse-quence of e.g. conversion from conventional to conservation tillage practices on agricultural lands. Even after saturation, the agricultural practices would need to be sustained to maintain the accumulated carbon and prevent subsequent losses of carbon back to the atmosphere.

Carbon sequestration is obviously a temporal effect. In the knowledge of the authors of this study, accounting carbon sequestration as a credit for a crop-based product within LCA is rather uncommon. There are a number of methodological issues related to such accoun-tancy, e.g. is there a clear cause-relationship between the carbon sequestration observed and corn growing for PLA production? What is the alternative use of the land if corn was not grown? E.g. if maintained as green land there would probably be a similar carbon sequestra-tion. How to include the time factor?

Figure 5-11 Sensitivity scenario for the PLA clam shell system concerning soil carbon sequestration. The results shown are valid for the impact category Global Warming.

The uncertainty related to the issue as to whether and if yes, how soil carbon sequestration should be accounted directly to products of agricultural activities has been examined by a sensitivity analysis. For this purpose the CO2 credit was subtracted from the original PLA 5 dataset. The related results are shown in figure 5-14. Indicator results are shown for Global

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Warming only, as no other impact category is affected by assumptions concerning soil car-bon sequestration.

When soil carbon sequestration is not considered in the PLA clam shell system, the net envi-ronmental impact in the Global Warming category shows an increase of 3%. The assumption on soil carbon sequestration is therefore not decisive for the ranking of alternative systems against each other.

5.2.5 Accounting of C-uptake during plant growth

The PLA inventory data shows a net CO2 emission which is the result of the total of process related CO2 emissions (burning fuels, producing CaO and other direct process emissions) minus the carbon dioxide harnessed during corn production in dextrose. A similar approach is among others used by Boustead, Song and Patel [..]. An alternative approach is that the harnessed CO2 is not subtracted and totally left out of the inventory. Examples for the latter are the datasets for corrugated board [FEFCO 2003] and pulp data from Nordic paper indus-tries [Nordpap 1997].

In a cradle-to-grave LCA it should make no difference which approach has been used. In this section the two approaches are compared in a sensitivity analysis.

Approach 1: the base case, in which the CO2 uptake to build the polymer chain is taken into account: CO2 released by thermal treatment or as a result of decomposition of the renewable feedstock is considered in the calculation of greenhouse gases.

Approach 2: the alternative approach, the CO2 uptake is now left out of the inventory: CO2 re-leased by thermal treatment or as a result of decomposition of the renewable feedstock is regarded to be greenhouse neutral25, in other words this CO2 is not included in the global warming potential, because exactly the same amount has been taken from the atmosphere during plant growth.

As an inherent characteristic, approach 2 does not consider carbon dioxide fixation effects that come from soil carbon sequestration, as carbon dioxide uptake is left out of the inventory regardless if it ends up in the product or in soil. Consequently carbon fixed by soil carbon se-questration does not influence the greenhouse gas inventory with this approach.

The results are shown in figure 5-15 as Global Warming only, since no other impact catego-ries are affected by CO2 modelling methodology.

25 this is also the way how greenhouse gas calculations must be performed under the Kyoto protocol

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Figure 5-12 Sensitivity scenarios for the PLA clam shell system concerning an alternative modelling and evaluation of CO2 uptake in biomass. Results shown for category Global Warming.

With the alternative modelling and evaluation of CO2 uptake in biomass, a slightly higher net Global Warming impact can be observed for the PLA clam shell system. The difference can be attributed to soil carbon sequestration which is not be taken into account by the alterna-tive evaluation method. Consequently, the increase of the net indicator result in Global Warming is 3%, the same as what has been observed in the sensitivity analysis concerning soil carbon sequestration.

This means that for the carbon fixed in the product both methods lead to identical net results. The effect of C sequestration in soils as such has already been examined in 5.2.5.

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5.3 Limitations and data quality issues In the opinion of the authors the presented results are reliable within the framework condi-tions described. However, the results obtained should not be used for general comparisons of plastics packaging from different polymer materials. The limitations of the underlying LCA are addressed in this section.

5.3.1 Limitations concerning packaging specifications

The results are valid for the packaging systems as described in chapter 2. Each packaging system is defined by multiple system parameters which all have the potential to alter the en-vironmental profile. For example it is not possible to transfer the results of this study to pack-aging systems with other volumes or weights.

The considered specifications are valid for the specified clam shell products from Vitembal. Therefore this LCA should be considered as a case study. The results neither do represent something like an average market situation nor are they valid for clam shells of other produc-ers. In addition, the LCA results are only valid for clam shells applications used for cold food stuff.

5.3.2 Limitations concerning the PET data

The choice of PET inventory data has an influence on the outcome of the comparison be-tween clam shells from PLA and PET. In the communication of the LCA study results this as-pect should be dealt with in a transparent manner.

5.3.3 Limitations concerning the PLA data

Any conclusions and information regarding PLA as a polymer and raw material for packaging is exclusively valid for NatureWorks PLA. In the communication of the LCA study results this aspect should be dealt with in a transparent manner.

5.3.4 Limitations concerning the converting data

The polymer converting data used are only valid for clam shells produced by Vitembal. Therefore the underlying LCA has to be considered as a case study.

5.3.5 Limitations concerning the geographic boundaries

The LCA study is designed to reflect German conditions. Inventory data and material flow settings which are specific for the German market are:

- Grid electricity data (relevant for electricity requirements for polymer conversion into clam shells and credits for electricity output from MSWI);

- End-of-life settings; and

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- Process data for recovery and recycling operations.

These circumstances should be made transparent in any communication of the study results.

5.3.6 Limitations concerning the representativity of the study

In the PLA base scenario the assumption is made that on-site recycling of PLA process waste at Vitembal is fully implemented. At the time of this LCA study this was not the case.

The PLA base scenario therefore is not completely representative for the status of clam shell production from PLA. However, it should also be mentioned that the sensitivity scenario in chapter 6.2.1 suggests that this aspect only affects the size of the comparative indicator re-sults but not the ranking between the packaging systems.

In addition, this LCA should be considered as a case study as packaging weights and con-version data are only valid for the clam shells of the French packaging producer Vitembal (see also section 5.3.1).

5.3.7 Data gaps concerning transport of PLA in the US

PLA is transported by diesel driven trains in the US. The train model applied in this study is based on a mixture of electricity and diesel driven trains. Therefore, the related emissions in the PLA life cycle model might be slightly underestimated. Given the limited impact of this step regarding the gross PLA lifecycle results this data choice is considered to be not rele-vant for the study outcome.

5.3.8 Data integrity and quality

All relevant information and data required for the evaluation of the packaging systems exam-ined in this LCA were available. Initial data gaps could be covered in the course of the study. Data uncertainties regarding the appropriate clam shell weights data could be solved by fo-cusing on the packaging produced by a single producer.

Concerning the intention to have a reference period as up to date as possible, some un-avoidable differences have to be accepted. Still most of the data, particularly those with high influence on the final indicator results, refer to a period between 2002 and 2005. Hence, the final comparative results are not likely to be biased caused by differences in age of the data used.

For all packaging systems the same methodological choices were applied, concerning allo-cation rules, system boundaries and calculation of environmental impacts.

The cut-off rules applied during the development of the polymer datasets according to the in-formation available differ between the different data generators. However, the highest cut-off level is 1%. The effect of the related differences is therefore regarded to be negligible for the final LCA results of this study.

With respect to the inventory data relevant for the environmental impact assessment (see ta-ble 1-1) data symmetry has been checked. This was done for each life cycle step, with a par-ticular focus on the polymer data, and across the different packaging systems.

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In general, the symmetry can be said to be quite satisfying. When looking at the available numbers, those for the inventory data underlying the category “human toxicity (carcinogenic risk)” called for some attention. In table 5-4 the available numbers are shown for the poly-mers on a kg basis. The different magnitudes across polymers for the same air pollutant, e.g. chromium, do not seem to be plausible.

Table 5-4 Comparison of polymer inventory data for selected air emissions on a kg basis

Air Emission [mg/kg polymer]

PLA 5 PS PP PET

Arsenic 0.0009 0.0095 0.00008 0.00004 Benz(a)pyrene - - - - Benzene - 22.6 3.3E-12 2.3 Cadmium 0.0002 0.0012 0.00009 0.00002 Chromium (unspec.) 0.003 1.58 0.0004 3.6 Dioxins - 8.54E-35 3.7E-26 1.7E-25 Nickel 0.0033 2.87 9E-8 6.6 PCB - - - -

Overall, when looking across the information used in this LCA study, the data quality can be considered to be satisfactory. For the evaluation of identified uncertainties sensitivity analy-ses were performed. However, doubts remain concerning the quality of inventory data under-lying the indicator results for human toxicity (carcinogenic risk).

In the opinion of the authors the data used and the way they were applied provide a solid ba-sis for robust and reliable results, and thus for a conclusive discussion of the study outcome.

Quantitative details concerning data uncertainties were neither for polymer inventory data-sets (PLA, fossil-based polymers) nor for other life cycle steps available. Nevertheless, known uncertainties were evaluated and examined for their influence on the validity of the study results. For this purpose in section 5.1 significant parameters were identified and sub-jected to sensitivity analysis (section 5.2) if required. The selection of relevant uncertainties to be examined by means of sensitivity analysis was agreed upon by the project panel.

Working with probability density functions is in its infancy yet and requires much more infor-mation than usually available within the context of life cycle inventories. Therefore this type of methods has not been applied. Otherwise a lot of subjectivity would have be created, espe-cially given the fact that highly relevant inventory datasets such as PLA and Plastics Europe polymer datasets do not contain the required information.

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6 Discussion The underlying study deals with the ecological comparison of clam shells made from PLA, PP, PS and PET using LCA as a method. In addition it examines the potential environmental effects of improved PLA polymer production and a number of individual end-of-life options for PLA packaging waste respectively.

For the packaging performance of clam shells the material stiffness is a prominent feature. Here, the relatively high elasticity modulus of PLA is particularly favourable (table 2-2). Simi-larly performing PLA clam shells can be produced with a weight smaller than any of the al-ternative polymers.

If the modulus goes along with a lower density – which is the case for PLA compared with PET, particularly large differences in weights can be found. The clam shells produced by the French converter Vitembal show a PET packaging weight 1.63-fold the weight of PLA pack-aging.

However, such an optimized PLA clam shell weight is not necessarily found with clam shells of other producers. As a consequence, the validity of the study results is clearly case-specific and may be applied to clam shells only.

Eight impact category indicators (supplemented by four indicators at the inventory level) have been used to describe the environmental impact profiles of the four packaging systems. Pri-oritizing of individual impact indicators, e.g. by means of normalization, ranking or weighting, was not performed as no agreement for any particular approach could be achieved among the stakeholders involved. As a consequence, all eight environmental impact categories are equally referred to in this section.

The status regarding production, use and waste treatment of clam shells under German framework conditions is reflected in the so-called base scenarios. The comparison of the PLA packaging system against the alternative systems revealed that:

• The PLA system shows advantages compared to all three systems with conventional polymers in the categories Fossil Resource Consumption, Global Warming and Summer Smog (POCP). Similar results regarding Human Toxicity (Carcinogenic Risk) are of limited reliability due to existing data quality issues.

• For the remaining impact categories, comparisons of the PLA system with the alter-native systems do not show a clear trend. The LCA results for Acidification, Terres-trial Eutrophication and Human Toxicity (PM10) show disadvantages of PLA when compared to PS and PP systems.

• On the other hand, with the exception of Terrestrial Eutrophication, advantages in these categories are found when compared to the PET system. However, the latter observation has been found to depend on the choice of PET inventory datasets

• As for Aquatic Eutrophication clam shells from PLA show environmental advantages if compared to PP and disadvantages in comparison with PS and PET.

The use of nature in form of agricultural area is a feature intrinsic to PLA given its origin from corn, an agricultural feedstock. When including this renewable feedstock the total cumulative

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energy demand of the PLA system is in the range of that of the fossil based polymers. How-ever, when looking at the non renewable energy demand only, the PLA systems score best.

It should be emphasized that in all packaging systems examined it is the polymer production step which strongly influences the overall LCA results for most environmental impact indica-tors. In addition, greenhouse gas emissions are also generated in the end-of-life phase to a considerable degree. On the other hand these emissions are partly compensated by the credits achieved through recycling and energy recovery.

Consequently, any scenario assumption related to the polymer as such (polymer demand, datasets, etc.) and – though to a lesser extent – those related to the end-of-life settings po-tentially affect the overall LCA results.

This is particularly true for the choice of PET inventory data. When using the PlasticsEurope PET data in the base scenario the environmental advantages of PLA clam shells over PET are predominant. With the application of “Petcore PET” data, the advantages of PLA over PET in the categories Acidification and Human Toxicity (PM10) turn into disadvantages. In this latter case the ranking of PLA against PET would be rather similar to that already found in the comparison of PLA against PS and PP.

On the other hand, the currently existing limitations regarding on-site recycling of PLA proc-ess wastes faced by Vitembal proved to be of minor relevance for the comparative LCA re-sults of this study. The process waste currently kept on stock could be recycled by chemical recycling which is an economic attractive alternative for waste not suitable for direct me-chanical recycling. In that case the indicator values of the PLA system would only slightly in-crease. If the material was used for energy recovery the extent of differences between the al-ternative packaging systems would be affected while the overall ranking across environ-mental categories remains the same.

Altogether, the comparative results show a pattern of environmental advantages and disad-vantages of PLA according to the individual environmental category considered. The funda-mental message here is that there is a trade-off which does not allow for a clear overall pref-erence of any particular system in the first place.

Readers who emphasize selected impact categories might find one or another system pref-erable on environmental grounds. However, this will have to be considered a subjective choice derived from value-based decision-making and should not be mistaken for a direct conclusion of this study itself.

PLA packages are not yet on the German market which makes it difficult to predict what will happen to the packages after the consumer use phase. If no changes in the infrastructure and organisation of waste collection are assumed, PLA material will be found in the packag-ing waste stream together with other packaging materials. It is likely that PLA is routed into the mixed plastics fraction in the first period after market introduction. Once sufficient vol-umes are available, sorting of PLA into a separate polymer fraction with subsequent chemi-cal recycling can become of interest for the recycling industry.

The question of the appropriate waste management is nonetheless an important issue for both PLA and PET packaging waste. Chemical recycling of source-separated PLA packaging waste would provide a considerable improvement in most impact categories examined. The same is true for PET. Here, the shift from energy recovery to mechanical recycling would im-

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prove the environmental impact profile of the PET packaging system in all impact categories examined in this study.

The situation is somewhat different for used PLA packaging waste undergoing composting or anaerobic digestion. Here all environmental impacts are rather similar or higher than in the PLA base case. The effect of a net increase in environmental impacts, particularly Summer Smog and Global Warming, is related to air emissions released during the composting proc-ess and the quite small credits to be obtained. The advantage of the digestion option when compared to the composting alternative is mainly related to electricity generation with the ob-tained biogas and the related electricity credits for displacement of grid electricity.

Altogether, the LCA-based assessment of packaging systems in this study provides quite ro-bust results, showing similar patterns of comparison regardless of most of the sensitivity analyses performed.

Yet, it is worthwhile to mention, that PLA is a relatively new material. PP, PS and PET are commodities produced in large scale plants which have been optimized during many years of commercialization. PLA certainly still is at a much earlier phase of market development and process optimization.

The PLA/NG scenario here is a good example for such an optimization expected for the fu-ture. The improvements scheduled to be implemented in the lactic acid production have the potential to considerably reduce the Fossil Resource Consumption as well as the Summer Smog.

At the time of this LCA study, short term innovations have already been put into practice by NatureWorks through the purchase of wind power certificates since the start of the year 2006. With the help of these certificates NatureWorks achieves an offset of greenhouse gas emissions as well as emissions causing Acidification and Terrestrial Eutrophication by in-creasing the production of wind power. The benefit associated is reflected in the results cal-culated with the PLA 6 dataset.

RECs are a valuable means to adopt the producer responsibility principle. Still, they are only the second best solution. Increased process efficiency and reduced direct process emissions must be the ultimate goal of environmental optimization. Here, Natureworks should not only consider own process operations but also those maintained by its suppliers. This extents even to farming, e.g. by seeking increased supply of corn from “close to nature” farming practices.

Under an environmental perspective PLA clam shells are clearly competitive with the con-ventional counterparts. However, the discussion presented here provides the target groups of this study, i.e. the trade companies and the political decision makers, with a picture proba-bly more complex than desired.

The main reason for this is the trade-off already mentioned caused by advantages of PLA for some environmental categories and disadvantages for others. Thus, regardless the packag-ing material selected, trade companies should commit to optimized packages using as less material as possible and define respective criteria towards their suppliers.

Used PLA packages are compatible with the treatment routes existing within the German waste management systems. While the mixed plastics route shows some environmental

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benefits, the option of choice seems to be a selective treatment via chemical recycling. The industries involved should consider the implementation of an appropriate infrastructure.

In Germany there is already an extended infrastructure for collection and treatment of source-separated biowastes, mainly in industrial composting facilities. However, composting should not be the standard treatment for PLA packaging waste as this option cannot be ex-pected to provide the environmental benefits achievable by chemical recycling and energy recovery.

Anaerobic digestion seems a more promising option than composting. However, to date little is known about the behaviour of PLA when undergoing anaerobic digestion. An improvement of respective knowledge by future research is desirable.

Political decision-makers should be well aware that the results of this study do not allow for generalized conclusions regarding the comparison of biopolymers in general or PLA in par-ticular against petrochemical polymers. This should be clear in any political statement that makes reference to this LCA study.

On the other hand, this study shows that political decision makers are well advised to en-courage optimized packaging production (e.g. against the current trends on the market which show a tendency to increased packaging weights).

The new approach of NatureWorks to offset the greenhouse gas emissions caused by PLA production by the purchase of renewable energy certificates is a huge step towards producer responsibility for the achievement of environmental improvements on a company level. This attitude should be acknowledged by both stakeholders and decision makers in the trade as well as at the political level.

Breaking-down of the purchase of RECs at the company level down to the product level is not (yet?) common in LCA practice. Here, conventions need to be developed by the LCA community to assure a transparent and agreed upon handling of this type of measures within product LCAs.

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[Plastics Europe 2005b]: Boustead, I.: Eco-profiles of the European Plastics Industry – Poly-propylene (PP), data last calculated March 2005, report prepared for Plastics Europe, Brussels, 2005. (Accessed August 2005 at http://www.lca.plasticseurope.org/index.htm)

[Plastics Europe 2005c]: Boustead, I.: Eco-profiles of the European Plastics Industry – Poly-styrene (General Purpose) (GPPS), data last calculated December 2005, report pre-pared for Plastics Europe, Brussels, 2005. (provided by Ian Boustead to NatureWorks)

[Plastics Europe 2005d]: Boustead, I.: Eco-profiles of the European Plastics Industry – Meth-odology - last revised March 2005, report prepared for Plastics Europe, Brussels, 2005. (Accessed August 2005 at http://www.lca.plasticseurope.org/index.htm)

[UBA 1995] Umweltbundesamt (Hrsg.): Ökobilanz für Getränkeverpackungen. Datengrund-lagen. Berlin, 1995. Unveröffentlicht.

[UBA 1998] Umweltbundesamt: Ökobilanzen für graphische Papiere., Berlin, 1998.

[UBA 1999] Umweltbundesamt: Bewertung in Ökobilanzen. UBA-Texte 92/99, Berlin, 1999.

[UBA 2000] Umweltbundesamt, Berlin (Hrsg.): Ökobilanz für Getränkeverpackungen II, Hauptteil. UBA-Texte 37/00, Berlin, 2000.

[UBA 2001] Umweltbundesamt (Hrsg.): Grundlagen für eine ökologisch und ökonomisch sinnvolle Verwertung von Verkaufsverpackungen; Berlin, Juli 2001.

[UBA 2002] Umweltbundesamt, Berlin (Hrsg.): Ökobilanz für Getränkeverpackungen II/2. UBA-Texte 51/02, Berlin, 2002.

[US EPA] Global Warming Website of US Environment Protection Agency, Subsection: Car-bon Sequestration in Agriculture and Forestry. http://www.epa.gov/sequestration/rates.html; http://www.epa.gov/sequestration/faq.html

[VDEW 2003] VDEW (German Electricity Association): Energy policy and the electricity in-dustry, for the year 2003

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[Vestas 2005] Vestas Wind Systems A/S: Life cycle assessment of offshore and onshore sited wind power plants based on Vestas V90-3.0 MW turbines, March 2005. (Ac-cessed March 2006 at http://www.vestas.com/uk/sustainability/lca_reports.asp)

[Vink et al. 2003]: Vink, E.T.H., Rabago, K.R., Glassner, D.A. and Gruber, P.R. (2003) Appli-cations of life cycle assessment to NatureWorksTM polylactide (PLA) production. Poly-mer Degradation and Stability 2003, 80, 403-419.

[Vink et al. 2004a]: Vink, E.T.H., Rabago, K.R., Glassner, D.A., Springs, B., O’Connor, R.P., Kolstad, J. and Gruber, P.R. (2004) The Sustainability of NatureWorksTM Polylactide Polymers and IngeoTM Polylactide Fibers: an Update of the Future. Macromolecular Bioscience 2004, 4, 551-564.

[Vink et al. 2004b]: Vink, E.T.H., Hettenhaus, J.R., Dale, B.E., Kim, S. and Fairchild, D.: The Life Cycle of NatureWorks® Polylactide 1. Corn Production Inventory Data and Corn Production Eco-profile. (unpublished)

[Vink et al 2004c]: Vink, E.T.H., Hettenhaus, J., O’Connor, R.P., Dale, B.E., Tsobanakis, P. and Stover, D.: The Life Cycle of NatureWorks® Polylactide 2. The Production of Dex-trose via Corn Wet Milling. (unpublished)

[Vink 2005/2006]: personal communication by email with Erwin Vink, NatureWorks, between August 2005 and February 2006.

[Vink 2006a]: personal communication with Erwin Vink, NatureWorks: data on process chemicals were generated by Five Winds International, March 2006.

[Vink 2006b]: Vink, E.T.H, Glassner, D.A., Kolstad, J., Wooley, B., O’Connor, R.P.: Applications of life cycle assessment to NatureWorks® polylactide (PLA) produc-tion: An Update. NatureWorks LLC, Minnetonka Boulevard, Minnetonka, Minnesota 55345, USA (in preparation).

[Vitembal 2005a]: presentation slides by Thierry Grossetête, Vitembal, project panel meeting, October 2005.

[Vitembal 2005b]: personal communication with Thierry Grossetête, Vitembal, November 2005.

[Vitembal 2006]: personal communication with Thierry Grossetête, Vitembal, January 2006.

[Winkler 1997]: Internal memo of the Verein deutscher Zementwerke, 1997

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Appendix A: Description of impact categories

The impact indicators used in this study are introduced below in impact categories and the corresponding characterisation factors are quantified. In each case, references are given for the origin of the methods that were used. The procedure for calculating the indicator is given at the end of each sub-section.

A.1 Global warming

Global warming is the adverse environmental effect caused by anthropogenic heating of the Earth's atmosphere and has already been described in detail in the relative references [IPCC 1995]. The indicator most used in life cycle assessments up until now is the radiative forcing [CML et al. 2002, Klöpffer 1995] and is given as CO2-equivalents. The characterisation method is a generally recognised method.

The Intergovernmental Panel on Climate Change (IPCC) is an international body of ex-perts that computes and extrapolates methods and relevant parameters for all sub-stances that influence climate change. The latest IPCC reports are the scientific basis for quantifying global warming.

Plants remove carbon from the atmosphere, therefore the amount of carbon fixed during plant growth has been subtracted from the CO2-emissions that arise during agricultural pro-duction, for example due to the use of fossil energy resources when using machinery or for the production of fertilisers. Consequently, all carbon dioxide emissions, no matter if they are of regenerative or fossil origin, have been accounted for with a characterisation factor of 1 CO2 equivalent.

When calculating CO2-equivalents, the residence time of the gases in the troposphere is taken into account and the question arises as to what period o f time should be used for the climate model calculations for the purposes of the product life cycle. There are models for 20, 50 and 100 years. The model calculations for 20 years are based on the most reliable prog-nosis. The German environmental agency recommends modelling on a 100 year basis be-cause this best reflects the long-term impact of global warming. This was chosen in this pro-ject.

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The substances used for calculating the global warming are shown below along with the re-spective CO2-equivalent values – expressed as Global Warming Potential (GWP):

Greenhouse gas CO2 equivalents (GWPi)

Carbon dioxide (CO2) 1

Methane (CH4)26 25.75

Nitrous oxide (N2O) 296

Tetrafluoromethane 5,700

Hexafluoroethane 11,900

Halon 1301 6,900 Source: [IPCC 2001]

Table A-1: Global warming potential for materials taken into account in this study

The contribution to the global warming is obtained by summing the products of the amount of each emitted harmful material (mi) of relevance for global warming and the respective GWP (GWPi) using the following equation:

GWP m GWPi i

i

= ×∑ ( )

A.2 Photo-oxidant formation (photosmog or summer smog)

Due to the complex reactions during the formation of near-ground ozone (photosmog or summer smog), the modelling of the relationships between the emissions of unsaturated hydrocarbons and nitrogen oxides is extremely difficult. The Photochemical Ozone Crea-tion Potential (POCP) [CML 1992], which is expressed in ethene equivalents, and which has been used up until now for assessing environmental impact has created contro-versy amongst experts. This is because it is based on changes to existing ozone concen-trations and because it was developed for calculating the effects over broad regions. It is based on the ozone creation potential of hydrocarbons and completely ignores the contri-bution of nitrogen oxides to the ozone forming reactions.

As part of a UBA research project [UBA 1998] it was attempted to develop an improved model. The aim at the outset was to include the relevant photo-oxidant forming reactions in a model taking into account actual concentrations and mixing ratios and also the nitrogen ox-ides. The atmosphere over a given area - e.g. Germany - was assumed to be a one-box model and new calculations were carried out with the additional ozone-forming substances.

26 According to IPCC (2001), indirect effects such as oxidation of CH4 to CO2 are not considered in the

GWP values given in the IPPC report. Therefore one CO2 equivalent has been added per one CH4 molecule .

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This approach proved however to be too complicated relative to its potential use, due to the poor LCI data on ozone-forming substances.

However, in order to be able to include the nitrogen oxides in the modelling of the photo-oxidant formation, a linear consideration of the nitrogen oxides was proposed [Stern 1997]. Expanding the POCP model, this involved multiplying the ethene equivalents by the calcu-

lated POCP value, for each emitted nitrogen oxide in each System. The result is a new indi-cator - the Nitrogen Corrected Photochemical Ozone Creation Potential - NCPOCP, that allows linear consideration of the nitrogen oxides. Up until now the model has mostly been used in a German context. The scientific reliability of the linear approach for quantifying the interaction between NOx and the gases listed in Table A-2 and the ozone creating poten-tial still has to be discussed.

The table below shows the gases and their ozone creation potential (POCP) as used in this study.

Harmful gas POCP [kg ethene equivalents]

Ethene 1

Methane 0.006

Formaldehyde 0.52

Benzene 0.22

Hydrocarbons: • NMVOC from diesel emissions 0.7 • NMVOC (average) 0.416 • VOC 0.377

NOx For calculating the NCPOCP

Source: [CML 1992, Klöpffer 1995, Jenkin+Hayman 1999]

Table A-2: Ozone creation potential of substances considered in this project

Here, only individual substances having a defined equivalent value (relative to ethene) were considered. For hydrocarbons that are not precisely defined, as is often the case in literature data, an average equivalent value taken from CML [1992] was used.

The POCP was calculated using the following equation:

∑ ∗=i

ii POCPmPOCP )(

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In addition, the POCP value served as the basis for calculating the NCPOCP value. The contribution to the NCPOCP is calculated by summing the products of the amounts of indi-vidual harmful substances emitted and the respective POCP values, and then multiplying this by the emitted amount of nitrogen oxide27:

∑ ∗∗=i

iiii POCPmNOxmNCPOCP )(*

A.3 Eutrophication and oxygen-depletion

Eutrophication means the excessive supply of nutrients, and can apply to both surface wa-ters and soils. As these two different media are affected in very different ways, a distinction is made between water-eutrophication and soil-eutrophication. It is assumed here for simpli-fication that all nutrients emitted via the air cause enrichment of the soil and that all nutri-ents emitted via water cause enrichment of the water. As the nutrient input into surface wa-ters via air emissions is small compared to the nutrient input via wastewater, this assump-tion does not give rise to noteworthy error.

The eutrophication of surface waters also causes oxygen-depletion. If there is an over-abundance of oxygen-consuming reactions taking place, this can lead to oxygen shortage in the water. A measure of the possible perturbation of the oxygen levels is given by the Bio-chemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). As the BOD is only defined by a reaction time and the COD essentially represents all the available poten-tial for oxygen-depletion, COD is used as a conservative estimate28 for the eutrophication in the parameter list.

In order to quantify the magnitude of this undesired supply of nutrients, the eutrophication potential indicator was chosen. This indicator is expressed as phosphate equivalents [CML et al. 2002, Klöpffer 1995]. The table below shows the harmful substances and nutri-ents that were considered in this study, along with their respective characterisation factors:

27 When evaluating life cycle assessments it must be heeded that the procedure for calculating the

NCPOCP does not mathematically allow any sector analysis because it involves a root function (the sum of the NCPOCP of the individual sectors is not the same as the NCPOCP of the sum of the inventory data)

28 The COD is (depending on the degree of degradation) higher than the BOD5, which is why the equivalence factor is deemed relatively unreliable and too high.

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Harmful substance PO43- equivalents (EPi)

Eutrophication potential (terrestrial)

Nitrogen oxides (NOX as NO2) 0,13

Ammonia (NH3) 0,327

Eutrophication potential (aquatic)

Total phosphorus 3,06

Chemical Oxygen Demand (COD) 0,022

Ammonium (NH4+) 0,327

Nitrate (NO3") 0,128

Quelle: [CML 1992, Klöpffer 1995]

Table A-3: Eutrophication potential of substances considered in this study

Regarding the supply of nutrients, the contribution to the eutrophication potential is calcu-lated separately for soil and water. In each case, that contribution is obtained by sum-ming the products of the amounts of harmful substances that are emitted and the respec-tive EP values.

The following equation is used for terrestrial or aquatic eutrophication:

∑ ×=i

ii EPmEP )(

A.4 Acidification

Acidification can occur in both terrestrial and aquatic systems. The emission of acid-forming substances is responsible for this.

The acidification potential impact indicator that was selected and described in [CML 1992, CML et al. 2002, Klöpffer 1995] is deemed adequate for this purpose. No specific charac-teristics of the affected soil or water systems are hence necessary. The acidification poten-tial is usually expressed as SO2 equivalents. The table below shows the harmful sub-stances considered in this study, along with their respective acidification potential (AP) ex-pressed as SO2 equivalents.

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Harmful substance SO2 equivalents (APi)

Sulphur dioxide (SO2) 1

Nitrogen oxides (NOX) 0,7

Hydrochloric acid (HCI) 0,88

Hydrogen sulphide (H2S) 1,88

Hydrogen fluoride (HF) 1,6

Ammonia 1,88

Source: [CML 1992, CML et al. 2002, Klöpffer 1995]

Table A-4: Acidification potential of substances considered in this study

The contribution to the acidification potential is calculated by summing the products of the amounts of the individual harmful substances and the respective AP values using the follow-ing equation:

AP m APi i

i

= ×∑ ( )

A.5 Resource consumption The consumption of resources is deemed adverse for human society. In all considerations regarding sustainable, environmentally-compatible commerce, the conservation of resources plays a key role. The term resources is often limited in use to finite mineral or fossil re-sources but is at other times interpreted very widely to include for example genetic diversity, agricultural land, etc.

When evaluating resource requirements within an LCA study, the scarcity of the resource is usually used as the criterion. The relationship between the factors – consumption, possible regeneration and reserves - is used to determine the scarcity of a resource, relative to a par-ticular geographical unit. The result is a scarcity factor that is then considered in conjunction with the resource data in the life cycle inventory and aggregated into an overall parameter for the resource consumption.

Despite supposedly systematic transparency of the data for the "resource consumption" impact category, some fundamental aspects still remain to be clarified. This in particular concerns sensible classification of types of resources and the definition of scarcity. Only then will understandable and accepted measuring procedures and evaluation principles be possible.

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The difficulties delimiting the resource types arise due to the fact that materials can be also be energy resources and vice-versa, that biotic resources under certain conditions are not renewable, that water can be a renewable material and a renewable energy resource, etc. In addition, there are problems associated with the life cycle inventory: If the growth of a biotic resource is part of the system, it is not the biological material that is an input to the system but rather the area of ground where it is grown. As such, ground area is the re-source that must be considered in estimating and evaluating the environmental impact and not the biotic resource itself.

Against this background, there are assumed to be three resource categories:

• Energy resources

• Material resources

• Use of nature

Based on the selection of primary impact categories for this study, only the two resource categories energy resources and use of nature are discussed below.

A.5.1 Energy resources

Various energy resources, for example crude oil and wood, can be used as both material resources (so-called feedstock) and energy resources. Due to the many conversion proc-esses within a life cycle, it is tricky to set system boundaries.

These characteristics of energy resources have resulted up until now in some cases in pro-posals to represent the energy resources as materials. This has made it difficult to include non-material energy resources such as wind power, hydroelectric power, tidal energy and photovoltaic energy, etc. in a single concept. In other studies, materials that can be consid-ered as both a material resource and an energy resource are represented by their energy content. This necessarily brings the problem that these materials cannot be included with non-energetic materials. For example, when replacing glass with plastic, the used mass can-not be compared with the amount of energy. Instead of relating this to the energy content of the plastic, conversion to a weight-related scenario is necessary.

Energy reserves on Earth are finite - as long as people continue using them. This applies in particular for the exhaustible energy resources such as fossil fuels and also uranium, the raw material for nuclear energy generation. For that reason, it is important to consider fossil resources and uranium when evaluating environmental impact. In addition, informa-tion about the total amount of energy29 in a system is important, because it describes the

29 The total energy requirements of the systems under study here are represented by the LCI parame-

ter CED (the sum of the energy contents of the primary energy resources) and CED (total)

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fundamental energetic efficiency of this system, including other forms of energy such as so-lar energy and geothermal energy.

The aggregation of the energy resources is carried out in two ways in this study: Firstly, the concept of fossil primary energetic resources is introduced. Secondly, evaluation of the finite nature of the primary energy resources is undertaken.

The term CED (cumulative primary energy demand) is used as a category description for the primary energy evaluation. It is a life cycle inventory parameter and expresses the sum of the energy contents of all primary energy resources up to the system boundaries. The term CED fossil refers to the sum of the fossil primary energy resources considered in this way. The term CED nuclear refers to the consumption of uranium. The calculation of CED nuclear is carried out by taking the atom flow consumed in the systems under study and assuming a degree of efficiency of 33%. Both CED fossil and CED nuclear are summarized to CED non-renewable. In addition, the CED hydroelectric power, CED regenerative and CED Other as well as the CED total obtained by summing all the CED values are recorded in the life cy-cle inventory results. Furthermore, CED hydroelectric power and CED regenerative are summarized as CED renewable. The CED hydroelectric power is determined assuming a degree of efficiency of 85%. CED regenerative is calculated from biomass input, in case of corn based on an energy content of 16.3MJ/ kg corn input.

In accordance with the method of the UBA, the static range of the energy resources serves as indicator for the scarcity of fossil fuels30. The static range here is derived from data on available global reserves and the current consumption of the respective resource. The scarcity values are converted to Crude Oil Equivalents (COE) [UBA 1995]. The table be-low shows the conversion factors for calculating the crude oil equivalents.

INPUT Static range Energy content, fossil Crude oil equivalent (COEi)

Raw material

reserves

[a] [kJ/kg] [kg crude oil eq.]

Brown coal 200 8.303 0,0409

Natural gas 60 40.400 0,5212

Crude oil 42 42.622 1

Mineral coal 160 29.809 0,1836

Source: UBA [1995]

Table A-5: Crude oil equivalents of raw material reserves considered in this study

30 The reliability of the static range as a scarcity factor is adversely affected by the uncertainties in the

status of known, commercially viable reserves of the resources.

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The following equation was used to calculate the crude oil equivalent values:

∑ ×=i

ii COEmCOE )(

A.5.2 Use of nature

Land can be considered a finite resource when evaluating environmental impact. It is how-ever not helpful to consider land as merely an available area. Land has to be defined by the environmental state of this land.

When the environmental status of an area of land is being considered, this takes into account all land-related environmental impact such as the reduction in biodiversity, soil erosion, ad-verse effects on the landscape, etc. It seems appropriate to include all such natural interrela-tionships in the term "use of nature" - in contrast to the term "land".

For this purpose, the UBA life cycle assessment of graphical papers [UBA 1998] devel-oped a method for assessing environmental impact based on describing the "degree of natu-ralness" (hemerobic levels) of natural areas [Klöpffer1995]. This was first of all used for for-est ecosystems. They key feature of the method is the classification of the quality of the land into seven quality classes, with decreasing degree of naturalness (see table A-6). All areas of land must be able to be ranked. Forest areas can be classified in the first five classes. Class I corresponds to "unperturbed nature", which may not be used for any purpose for the foreseeable future. The next four classes are for forest practices ranging from "close to na-ture" to "distant to nature". Classes III, IV, V and VI cover agricultural use. Three classes (III, IV and V) hence over-lap with forestry use. Class VII corresponds to land sealed by paving or land which has degraded over a long period of time such as waste disposal sites.

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Proximity Class

Level of Proximity Land use type

I Natural Ecosystem without anthropogenic management, natural forests

II Close to natural Close to natural forest management and use

III Semi-close to natural Semi-close to natural forest and agricultural manage-ment and use

IV Semi-natural Semi-natural forest and agricultural management and use

V Semi-distant to natural Semi-distant to natural forest and agricultural manage-ment and use

Vl Distant to natural Distant to natural agricultural management and use

VII Artificial / non natural Long-term sealed areas

Table A-6: Land use classes based on level of proximity to nature [UBA 1999]

The method is described in detail in [UBA 1999]. It is pointed out there that the develop-ment of the method is not yet complete. In particular, apart from forestry use, there is no general classification of all the uses of land relevant to LCA studies into degree of natu-ralness classes. This is due, amongst other things, to the fact that the available data sets do not as a rule provide the required information and for use of nature outside Germany the in-dicators for forming classes still have to be defined. Within the context of this study, agricul-tural land use (class VI) and sealed area (class VII) are most relevant and have been se-lected to serve as environmental indicators representing the impact category “Use of Na-ture”.

A.6 Human Toxicity

Concerning the impact category “human toxicity”, a generally accepted approach covering the whole range of toxicological concerns is not available. In this assessment, two indicators have been chosen to represent human toxic effects: carcinogenic pollutants and fine particu-lates (primary particulates as well as precursors).

A.6.1 Carcinogenic Risk

Generally toxicological evaluations are conducted on a site specific local scale within a risk analysis or an environmental impact assessment (EIA). Within a clearly defined spatial unit an exposition analysis can be applied which allows an evaluation of potential toxicological impacts on human. In contrast, LCA is a system specific method without local reference of emission inventory data, thus the generally accepted tools for toxicological evaluations can not be applied.

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A commonly accepted assessment method for the variety of potential toxicological impacts does not exist. Nevertheless, in order not to exclude such environmental impacts of a LCA study, a simplified approach based on toxic pollutants without effect threshold can be ap-plied. Pollutants with effect threshold are recorded on inventory level but not further aggre-gated within an impact category, as only pollutants without effect threshold are suitable to use for the characterisation step of LCAs. Especially carcinogenic pollutants with effects be-ing already caused at very low concentration levels can be used in this impact category, be-cause these effects are independent of local dilution processes, specific pathways or expo-sure. This approach has been developed and applied in several Life cycle assessments [IFEU 1997; UBA 1998].

The carcinogenic substances are aggregated by characterisation factors based on inhalation unit risk values of the Integrated Risk Information System (IRIS) of the U.S. EPA which is regularly revised and published. With these unit risk values all carcinogenic pollutants can be expressed as “Arsenic equivalents”. The characterization factors applied are shown in the table below. In case of chromium, the carcinogenic risk depends on the degree of oxidation. As often only Chromium, unspecified is given in inventory data, it is assumed that 10% of Chromium, unspecified actually is carcinogenic chromium VI.

Carcinogenic Risk Potential (CRPi) [kg Arsenic equivalents/kg]

Arsenic (As) 1 Benzo(a)pyren (BaP) 20.9 Benzene 0.0019 Cadmium (Cd) 0.42 Chromium as Cr-VI 2.79 Dioxins als TE 10,500 Nickel (Ni) 0.056

Source: [IRIS 1996]

Table A-7: Carcinogenic risk potential of selected substances relevant in this study

The contribution to the carcinogenic risk potential (CRP) is calculated by summing the prod-ucts of the amounts of the individual harmful substances and the respective As equivalent values using the following equation:

∑ ×=i

ii CRPmCRP )(

A.6.2 Fine particulate matter (PM10)

Fine particulates (PM10) are subsuming primary particulates and precursors of secondary particulates. They are characterized according to an approach by the European Environ-ment Agency (EEA).

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Epidemiological studies have shown a correlation between the exposure to particulate matter and the mortality from respiratory diseases as well as a weakening of the im-mune system. Relevant are small particles with a diameter of less than 10 and especially less than 2.5 µm (in short referred to as PM10 and PM2.5).These particles can not be ab-sorbed by protection mechanisms and thus deeply penetrate into the lung and cause dam-age.

Fine particulate matter can be formed from emissions by different mechanisms: On the one hand carbon-particulate matter is emitted directly during the combustion process (primary particles), on the other hand particles are formed by chemical processes from ni-trogen oxide and sulphur-dioxide (secondary particles).

As an indicator for the category “Human Toxicity: Particulate matter”, the absolute quantity of dust particles and secondary particles smaller than 10 micrometers (PM10) measured in kg of PM10 equivalent has been chosen. Characterisation factors (shown in table below) sup-plied by the European Environmental Agency [Leeuw 2002] are used to quantify compounds such as SO2, NOx, NMVOC and NH3 as secondary particles. They are regarded to be repre-sentative for Europe.

PM10 equivalents (PM10i) [kg PM10 equivalents/kg]

PM10 1

SO2 0.54

NOx as NO2 0.88

NMVOC 0.012

NH3 0.64

Source: [Leeuw 2002]

Table A-8: PM10 equivalents of secondary particles considered in this study

The contribution to the fine particulate matter potential is calculated by summing the products of the amounts of the individual harmful substances and the respective PM10 equivalent val-ues using the following equation:

A.7 References

[CML 1992]: Environmental life cycle assessment of products, Guide and backgrounds, Cen-ter of Environmental Science (CML), Netherlands Organisation for Applied Scientific Re-search (TNO), Fuels and Raw Materials Bureau (B&G), Leiden, 1992

[CML et al. 2002]: Guinée, J.B. (Ed.) - Centre of Environmental Science - Leiden University (CML), de Bruijn, H., van Duin, R., Huijbregts, M., Lindeijer, E., Roorda, A., van der Ven, B.,

∑ ×=i

ii PMmPM )10(10

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Weidema. B.: Handbook on Life Cycle Assessment. Operational Guide to the ISO Standards. Eco-Efficiency in Industry and Science Vol. 7. Kluwer Academic Publishers, Netherlands 2002.

[IPCC 1995]: IPCC (Publisher): Intergovernmental panel on the climatic change. Climatic Change, Report to the United Nations 1996, New York (USA) 1995

[IPCC 2001]: IPCC Third Assessment Report – Climate Change 2001: Synthesis Report, 29.09.2001; http://www.ipcc.ch/pub/SYR-text.pdf

[IRIS 1996] Environmental Protection Agency (US-EPA): Environmental and Risk Assess-ment Software, Washington D.C., 1996

[Jenkin + Hayman 1999]: Jenkin, M.E. & G.D. Hayman, 1999: Photochemical ozone creation potentials for oxygenated volatile organic compounds: sensitivity to variations in kinetic and mechanistic parameters. Atmospheric Environment 33: 1775-1293.

[Klöpffer 1995]: Methodik der Wirkungsbilanz im Rahmen von Produkt-Ökobilanzen unter Be-rücksichtigung nicht oder nur schwer quantifizierbarer Umwelt-Kategorien, UBA-Texte 23/95, Berlin, 1995

[Leeuw 2002]: Leeuw, F.D.: A set of emission indicators for long-range transboundary air pollu-tion, Bilthoven 2002

[UBA 1995]: Umweltbundesamt (Publisher): Ökobilanz für Getränkeverpackungen. Daten-grundlagen. Berlin, 1995. Not published.

[UBA 1998]: Umweltbundesamt Berlin (Publisher): Ökobilanz Graphischer Papiere. Berlin, 1998

[UBA 1999] Umweltbundesamt: Bewertung in Ökobilanzen. UBA-Texte 92/99, Berlin, 1999.

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Appendix B: Examples for normalisation and ranking

B.1 Normalisation The aim of the normalization is to better understand the relative magnitude for each indicator result of the product system under study. In this study indicator results of each impact cate-gory were normalized into so-called “resident-equivalents (REQs)”. In the underlying study the REQs are calculated and presented for Germany and Western Europe.

The normalisation factors are obtained by dividing the overall German / Western Europe loads per impact category with the number of inhabitants in Germany / Western Europe. The results are statistical environmental impacts per inhabitant and listed in table B-1.

In the next step the net indicator results of the base scenario given in Table 4-1 to 4-3 are divided by the respective REQ and mulitiplied by a factor 1000, giving the contribution ex-pressed as REQ per 1 000 000 clam shells. These REQs hence simply provide a reference quantity that allows the different indicator results to be converted to the same units and so allows the relevance of the contribution of the environmental impact of a study option to be highlighted.

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Table B-1: Basic data for Germany and Western Europe used to calculate REQs.

Impact per resident

Germany Western Europe Germany

Western Europe

Residents Residents 82 532 000 a) 397 404 900 b) Resources Lignite 1 547 000 c) 2 239 394 j) TJ 18 744 5 635 MJ Natural gas 3 025 000 c) 15 552 120 j) TJ 36 652 39 134 MJ Crude oil 5 478 000 c) 26 042 733 j) TJ 66 374 65 532 MJ Hard coal 1 920 000 c) 6 823 563 j) TJ 23 264 17 170 MJ Total area 35 703 000 v) 400 000 000 ha 4 326 10 065 m2 Emissions (Air) Ammonia 601 000 i) 3 540 000 k) 7,28 8,91 kg Arsenic 33 d) 193 k) t 0,0004 0,0005 kg Benzene 42 900 f) 306 000 k) t 0,52 0,77 kg Benzo(a)pyrene 13,76 e) 209 k) t 0,0002 0,0005 kg Cadmium 11 d) 133 k) t 0,00013 0,00033 kg Hydrogen chloride 730 000 k) 1,84 kg Chromium 115 d) 646 k) t 0,0014 0,0032 kg Dioxins (unspecified) 1,25 g) 3,55 l) kg 15,15 8,93 µg Dinitrous oxide 205 000 i) 1 300 000 k) t 2,48 3,27 kg Hydrogen fluoride 124 000 h) t 1,50 kg Carbon dioxide, fossil 865 000 000 i) 3 390 000 000 k) t 10 481 8 530 kg Carbon monoxide 4 155 000 i) 42 800 000 k) t 50,34 107,70 kg Methan 3 582 000 i) 20 265 000 k) t 43,40 50,99 kg Nickel 159 d) 1580 k) t 0,0019 0,0040 kg NMVOC 1 460 000 i) t 17,69 kg NOx (as NO2) 1 428 000 i) 14 000 000 k) t 17,30 35,23 kg PCB 43,6 g) 106 k) t 0,00053 0,00027 kg Sulfur dioxide 616 000 i) 12 220 000 k) t 7,46 30,75 kg Dust (PM10) 224 930 i) 1 350 000 k) t 2,73 3,40 kg Emissions (Water) Phosphorus (freshwa-ter) 33 000 i) 224 000 k) t 0,39984 0,56366 kg Nitrogen (freshwater) 688 000 i) 1 370 000 k) t 8,33616 3,44737 kg Aggregated values for impact categories Crude oil equivalents 189 702 096 878 621 435 t COE-Eq 2 298,53 2 210,90 kg Global warming 1 017 916 500 4 296 623 750 t CO2-Eq 12 334 10 812 kg Acidification 2 943 880 29 317 600 t SO2-Eq 35,67 73,77 kg Eutrophication (ter-restrial) 395 990 3 059 000 t PO4-Eq 4,80 7,70 kg Eutrophication (aquatic) 389 940 1 260 840 t PO4-Eq 4,72 3,17 kg Eutrophication (total) 785 930 4 319 840 t PO4-Eq 9,52 10,87 kg Summer smog (POCP) 638 290 8 200 000 t Eth-Eq 7,73 20,63 kg Cancerogenic risk (air) 473 5714 t As-Eq 0,0057 0,0144 kg PM10 equivalents 2 216 370 22 534 400 t PM10-Eq 26,85 56,70 kg

a) Stat. Bundesamt 2004 (31.12.2003) b) Eurostat (1.1.2005) c) Daten zur Umwelt 2005, data valid for 2000 d) Daten zur Umwelt 1996, data valid for 1995 e) IFEU-study „POP in Deutschland“, reference year 1994 f) Enquete Stoff- und Materialströme 1993, p. 146 g) Communicated by UBA h) Daten zur Umwelt 92/92, data valid for 1991 i) Daten zur Umwelt 2005, data valid for 2003 j) Eurostat, taken from „Energiebilanzen – Daten 2002-2003. Detailed tables, 2005 Edition“ k) Reference Emissions Western Europe, 1995, data taken from CML (April 2004) l) European Dioxin Inventory – Stage II – data valid for 2000

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Note

One limitation is that in the case of the aquatic eutrophication the REQ values in Figure B-1 and B-2 are too high, because the REQ value in Table B-1 does not contain COD. For ex-ample, the known eutrophication potential for the PLA clam shell system is 4 g PO4 equiva-lents per 1000 clam shells of which 1.6 g (40%) is caused by the COD. Hence, neglecting the COD value for this system would result in about a 40% lower aquatic eutrophication po-tential in the REQ representation. This data omission for the parameter is taken into ac-count in the subsequent evaluation of the REQ results.

Normalised results for PLA, PS, PP and PET base scenarios

Normalised indicator results show those impact categories which have a high specific contri-bution to the overall German / Western European environmental impacts. Categories with high specific contributions point to environmental impacts, where the influence of the packag-ing systems under study could be considerable within a German/European context. In other words, in those categories a reduction of environmental impacts of packaging systems could potentially result in considerable environmental impact abatement at German /European level.

Figure B-1 and B-2 show specific contributions for the studied clam shell systems both normalised for Germany and Western Europe. All resident equivalents refer to 1 million clam shells.

Normalised indicator results for Germany (figure B-1) can be classified as 3 groups of magnitude based on average specific contributions of all alternative clam shell systems to impact categories: The highest specific contributions are found in the categories Human Toxicity (PM 10), Fossil Resource Consumption, Global Warming, and Acidification. Me-dium contributions can be found for Terrestrial Eutrophication and Summer Smog (POCP). Categories with overall low scores are Aquatic Eutrophication and Human Toxic-ity (Carcinogenic risk).

A different pattern can be observed in the normalized results for Western Europe (figure B-2): The highest specific contributions are found for the categories Fossil Resource Con-sumption and Global Warming. Medium contributions are found for Acidification, Terrestrial Eutrophication, Summer Smog (POCP) and Human Toxicity (PM 10) and low contributions are shown for Human Toxicity (Carcinogenic Risk) and Aquatic Eutrophication.

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Figure B-1 Net indicator results of 1 million clam shells made of PS, PP, PLA 5 and PET, normalised for Germany.

Figure B-2 Net indicator results of 1 million clam shells made of PS, PP, PLA 5 and PET, normalised for Western Europe.

0

2

4

6

8

10

12

Fossil ResourceConsumption

Global Warming Summer Smog(POCP)

Acidification TerrestrialEutrophication

Human Toxicity:Carcinogenic

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Use of Nature:Farm Land

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Use of Nature:Farm Land

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PLA 5 PS PP PETPLA 5 PS PP PETPLA 5 PS PP PET

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B.2 Ranking The German Environment Agency (UBA) has developed an approach for the valuation of LCA indicator results [UBA 1999]. One of the components of this approach is that impact categories are ranked according to their ecological priority on an ordinal scale.The elements of the UBA approach will be shortly described in chapter B.2.1 and B.2.2.

The UBA approach is worthwhile to refer to for two reasons:

• it is the only ranking system which has an “official” status at a national level and

• German authorities are among the main target groups of this study.

B.2.1. Environmental vulnerability

The term "environmental vulnerability" allows the different environmental impact and envi-ronmental quality targets to be related to each other. This is achieved by ranking the impact categories in accordance with the extent of their impact on the environment.

It must be pointed out that such prioritisation is necessarily subjective in nature due to people having different values and interests and must always be considered in the relevant social context. For ranking impact categories, the UBA (Berlin) uses the following criteria to create an understandable, schematic classification [UBA 1999]:

• impact mechanisms (profound effects and effects on higher hierarchy levels31 are deemed to be more serious);

• reversibility versus irreversibility and duration (an irreversible impact is deemed more serious);

• geographical expansion (ubiquitous effects are deemed more serious than geo-graphically restricted effects); and

• uncertainties in the prediction of effects (a greater uncertainty is deemed more seri-ous).

B.2.2 Distance to Target

The "distance to target" expresses how far we are removed from the political targets. The bigger the distance, the higher the weight of the effect of an increased environmental bur-den.

31 This is understood to mean the following hierarchy: Individuals - Populations - Ecosystems. The

highest level is the global ecosystem

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In addition to the ratio between the “current”-state and the environmental target (the larger this ratio, the more serious the situation), the UBA uses the following criteria for ranking the impact categories:

1. Situations where there is a need for larger reductions are deemed to be more serious (no quantitative environmental quality targets available)

2. An increasing impact is deemed to be more serious than a static or decreasing im-pact

3. Situations where there is smaller throughput and poorer technical feasibility are deemed more serious.

B.2.3 Ranking in accordance with the proposal of the UBA (Berlin)

For each impact category, the UBA has estimated the environmental vulnerability and dis-tance to target. A five-level ordinal scale is used, denoted by the letters A to E. This is the result of the work of an interdisciplinary internal UBA work group. The above-mentioned classification criteria were used. A stands for "very high", B for "high", C for "medium", D for "low" and E for "very low". The classification levels are shown in Table B-3 [UBA 1999].

Table B-3: Classification system proposed by the UBA Impact Category Environmental

vulnerability Distance to target

Human toxicity Individual inventory data Eco-toxicity Individual inventory data Aquatic eutrophication potential B C Terrestrial eutrophication potential B B Summer smog D B Resource consumption (scarcity of fossil energy resources)

C B

Stratospheric ozone depletion A D Global warming A A Acidification (aquatic and terrestrial) B B Use of nature A B

The UBA procedure for evaluating LCA results continues as follows: An "ecological signifi-cance" is attributed to an impact category from the classification of the environmental vulner-ability and the distance to target. This is combined with the specific contribution (normalisa-tion) to give a final result. Both the environmental significance and the specific contribution are again given values on a five level scale in this procedure.

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Note

The ranking shown in table B-3, was developed in 1999 and still is the current status ap-plied by UBA. Other stakeholders might favor a different ranking, e.g. when focusing on the increasing concerns around the availability of fossil resources and climate change.

For Germany, the "Use of Nature" has a score "A". However, the corn is produced in Nebraska, US, where the availability of land per resident is totally different: in Germany the available land is about 4,000 m2/resident, the available land in Nebraska is about 122,000 m2/resident. For this reason it is not possible to apply the German ranking factor directly in this case.

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Appendix C: Reprint of the review report for PLA datasets (2005 and 2008)

written by I. Boustead on behalf of Natureworks LLC

PEER REVIEW

of

Data and reports on the production of polylactic acid by NatureWorks LLC

1. NatureWorks LLC is a company specialising in the production of polylactic acid (PLA).

2. The company has instigated a programme of work to evaluate the environmental charac-teristics of the production process.

3. Within the limits of commercial confidentiality, the company wishes to make available to a wider audience, the environmental data so far evaluated.

4. In June 2005, I was asked to review the results that had been obtained so far.

5. I was supplied with four data sets for:

(i) Corn production – report plus supporting data

(ii) Dextrose production – report plus supporting data

(iii) Raw data and analysis for current PLA production system

(iv) Raw data and analysis for the projected 2008 PLA production system.

6. Having reviewed all of the available data, I can confirm that the analysis is consistent with the requirements of ISO 14040 and 14041.

7. The calculations were carried out in the same manner and using the same ancillary data as those for other synthetic polymers as reported by APME/PlasticsEurope. The results for PLA should therefore be consistent and comparable with the APME data.

8. In the spreadsheets converting raw data into the format used in the calculations, it is pref-erable to use five decimal places. Experience has shown that this eliminates any possible rounding errors in the results.

There are a number of presentational points that might be considered to improve the reports.

9. In agricultural systems, the use of fertiliser can be a significant contributor to gross energy and emissions. The report on corn production gives an excellent review of available data. However, it is difficult to put the different data sets into context because of the different units

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involved. For example, input nitrogen might be expressed as N, NH3, NH4NO3 and nitrogen outputs might be expresses as N2O, NOx, NO3

-. Furthermore, data may be expressed per acre, per ha or per tonne of corn produced. It would have been helpful to have a summary table with all data presented in the same units so that direct comparisons could be made more easily.

10. The presence of water in agricultural products frequently poses problems. Here a water content of 15% is used. However, although the calculations reported here take this into ac-count, it is common for the water content to be overlooked by subsequent workers using these data as a source for their own calculations. It might be preferable to express the data on a bone-dry basis.

11. It is important that feedstock energy is always included in the presentation of energy re-sults. Failure to do this can lead to spurious comparisons.

12. Note that 'data' is a plural noun (singular = datum). Thus, 'data are' is correct whereas 'data is' is incorrect. The reports use both!

13. Overall this work is of a high standard and its publication would be a welcome addition to the available industry based data sets.

I Boustead

18 June 2005

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Appendix D: Statement of NatureWorks

To: Mr. Andreas Detzel

IFEU

Wilckenstrasse 3

D-69120 Heidelberg

Germany

Minnetonka, November 23, 2005

Subject: The use of alternative data for PET in the NatureWorks LLC Packaging LCA.

Dear Mr. Detzel,

As discussed during our LCA team meeting of October 25 2005 in Berlin,

The tables on page 24 of section 4.1 of the Draft IFEU Report 2, received on October 17 2005 have two sets of data for PET polymer: one set from PlasticsEurope; the other from Petcore. During the October 25 meeting Erwin Vink explained that this approach has several shortcomings. The major issue is that using two sets of data for PET in the base scenario is confusing for the target audience of this LCA.

NatureWorks doesn’t support utilization of data conflicting with the PlasticsEurope data be-cause:

1. PlasticsEurope is the official organization representing the European PET producers;

2. The PlasticsEurope data is used in many other studies inside and outside NatureWorks;

3. NatureWorks does not want to create any doubt about PlasticsEurope data and

4. Two sets of data for the same polymer will lead to discussion/confusion and can under-mine the credibility of the study.

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Therefore, NatureWorks believes that using the unmodified PlasticsEurope data in the base scenario is appropriate.

NatureWorks doesn’t want its LCA report to create doubt about the PlasticsEurope data.

If anyone doubts the PlasticsEurope data then a separate study should address those is-sues.

However, in order to meet the reservations of some of the Advisory Panel members about the PlasticsEurope data we understand and agree that it is common practice in a LCA to use the alternative data in a sensitivity analysis.

I hope I have you informed sufficiently about this topic.

Sincerely,

Dr. David Glassner

Director New Process Technology

NatureWorks LLC

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Appendix E: Soil carbon sequestration during corn production

E. Vink, NatureWorks LLC, February 05 2006

Globally, agriculture in the U.S. contributes about 2 percent of the gases that lead to the greenhouse effect. In the US, agriculture contributes about 10% of the total human-caused greenhouse gases (DOE 1999 and Snyder and Bruulsema 2002). “Agricultural intensification through adoption of scientifically proven best management practices (BMP) can solve, rather than cause, numerous environmental problems, including CO2 emission. BMPs can improve soil organic carbon (SOC) content, enhance soil quality, restore degraded ecosystems, in-crease biomass production, improve crop yield, and encourage investment in soil resources for soil restoration.” (Lal 1998)

Robertson (Robertson 2000) studied the influence of tillage practices on the emissions of greenhouse gases. During the period of 1991-1999 N2O production, CH4 oxidation and soil carbon sequestration were studied in a replicated series of cropped and unmanaged ecosys-tems in the Midwest United States. Among others, four corn-wheat-soybean rotations were studied under the assumption that these plantings were managed with: (I) conventional chemical inputs and tillage, (II) conventional inputs and no tillage, (III) reduced chemical in-puts, and (IV) organically with no chemical inputs. The latter one did not include manure ap-plications, as is often the case in organic systems. Manure amendments can greatly increase the emissions of greenhouse gases (Snyder and Bruulsema 2002). The latter two treatments included a winter legume cover crop following the corn and wheat portions of the rotations to provide nitrogen and mechanical cultivation to control weeds. In both cases the cover corps were plowed back into the soil. The results are summarized in Table 1.

Table 1 Relative Global Warming Potentials for different annual crop (corn-soybean-wheat) management systems based on soil carbon sequestration, agronomic inputs and trace gas fluxes. Units are CO2 equivalents (g/m2/year), using IPCC conversion factors. Negative val-ues indicate global warming mitigation potential through in situ soil sequestration.

Corn-soybean-wheat rotations CO2

Soil C

CO2

N fert.

CO2

Lime

CO2

Fuel

N2O CH4 Net

GWP

I. Conventional inputs + tillage 0 27 23 16 52 -4 114

II. Conventional inputs + No-till -110 27 34 12 56 -5 14

III. Reduced inputs + legume cover + tillage

-40 9 19 20 60 -5 63

IV. Organic inputs + legume cover + tillage

-29 0 0 19 56 -5 41

The study supports a conclusion that all the studied non-conventional tillage systems in-creased soil carbon over the decade-long period of the study. This soil carbon accumulation even characterized the low-input and organic regimes despite the use of plowing/tilling tech-niques. In those two cases, the sequestered carbon is likely the result of the winter cover

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crop adding unharvested plant biomass to the soil. None of the cropping systems provided a net reduction in greenhouse gas emissions. However, no-till conservation tillage performed best in reducing contributions to global climate change. The no-till system accumulated 30 g C or 110 g CO2/m2/year, which is an average value for no-till rotations in the Mid-west United States.

The average accumulation of carbon in the soil in the twenty-six counties surrounding the Cargill/NatureWorks production facilities can be estimated at 16 g C/m2/year. This is equiva-lent to a carbon dioxide fixation of 59 g CO2/m2/year.

In light of this data, the following assumptions were made:

- conservation no-till practices are applied on 35.8% of the corn acreage’s. Soil carbon ac-cumulation is assumed to be 30 g C/m2/year (Case II of Table 1).

- conventional till practices are applied on 15.4% of the corn acreage’s. The soil carbon accumulation for these areas is assumed to be 0 g C/m2/year (Case I of Table 1).

- For the remaining acreage (48.7%), it is assumed that mulching and reducing tilling are practiced, with a soil carbon accumulation of 10.9 g C/m2/year (Case III of Table 1).

Data from the analysis of corn yield and land use reveals the relative significance of this car-bon fixation in the soil through conservation tillage practices. The average corn yield in the twenty-six counties serving the corn wet mill was 0.86 kg/m2. The carbon dioxide fixed by the corn grain is 1,420 g/kg corn or 1,420 x 0.86 = 1,221 g/m2. This means that the carbon diox-ide ‘fixed’ by carbon sequestration in the soil is about 5% (59/1,221 x 100) of the carbon di-oxide fixed by the corn grain itself.

Kim (Kim 2004a) calculated soil organic carbon sequestration for continuously grown corn under no-tillage conditions for a period of 40 years in 14 counties situated in seven major corn production states. Results from the DAYCENT model showed that carbon sequestration rate range from 138 to 250 g CO2/m2/year. Sheehan (Sheehan 2003) calculated with the CENTURY model carbon sequestration over a period of 95 years in a continuous corn, no till, no residue collection production system. Results showed a carbon sequestration rates of about 131 g CO2/m2/year. Both values (Kim and Sheehan) are higher than the no-till scenario (Case II) of Table 1. However, this value is determined for a corn-wheat-soybean rotation system.

According to Dobermann (Dobermann 2004) one should be cautious about the potential for soil C sequestration in agricultural no-till systems. Most estimates come from long term ex-periments in which some form of conservation tillage is compared with no-till. In other words, they assume that carbon accumulates once land is changed to no-till. In most cases, the published carbon sequestration rates range from about 20 to 60 CO2-C/m2/y (or 73-220 g CO2/m2/y). He had not seen much convincing evidence that such rates have been achieved in absolute terms over larger land areas, under normal production conditions. The prelimi-nary results of new studies on this, started in 2001, suggest that little C sequestration may occur in irrigated no-till systems, mainly because residue on the surface is decomposed quickly rather than transformed into stable soil humus. Not much evidence was seen for sig-nificant carbon accumulation under no-till over a period of 3 years after the fields had been

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disked. He recommended to be cautious about the potential for soil C sequestration in agri-cultural no-till systems. The greatest uncertainty remains for irrigated systems, i.e. most of the literature data published come from dryland/rainfed experiments or, in other papers, are simply simulated changes in soil C with no field verification.

West (West 2002) reports that preliminary analysis suggests that, on average, conversion from conventional tillage to no-tillage in the US will result in a sequestration of 337 ± 108 kg C/ha/yr (124 ± 11 g CO2/m2/yr) in agricultural soils, to a depth of 30 cm. This data is based on 76 long-term soil carbon experiments assembled by the Center for Research on Enhanc-ing Carbon Sequestration in Terrestrial Ecosystems, US Department of Energy.

Six et al. (Six 2004) compiled all available data of soil-derived GHG emission comparisons between conventional tilled and no-tillage systems for humid and dry temperate climates. In humid climates, net soil organic C storage within the 0-30 cm soil layer averaged 222 kg C/ha/yr (81 g CO2/m2/yr) over the first 20 years following adoption of no-tillage practices. In contrast, no-tillage adoption in dry climates was estimated to result in C emissions at years 5 and 10, whereas the trend changed to net C sequestration during the second decade and averaged 97 kg C/ha/yr (35 g CO2/m2/yr) by year 20. Six concluded that the results indicated a strong time dependency in the GHG mitigation potential of no-tillage agriculture, demon-strating that GHG mitigation by adoption of no-tillage is much more variable and complex than previously considered.

Considering the differences in crop growing and rotation practices, locations and the meth-odologies used – Robertson measured the sequestration while Kim and Sheehan calculated the sequestration – the published values for no till corn production all fall in the same range (73-250 g CO2/m2/y).

Taking into account the comments of Dobermann and the fact that the corn in the 26 coun-ties is produced with a mix of all kind of agricultural practices (i.e. only 35.8% is no-till) the above calculated value of 59 g CO2/m2/y is considered to be conservative and will be used in the LCI of corn.

References:

DOE. 1999. Emission reduction of greenhouse gases from agriculture and food manufacturing. A summary white paper. December 1999. U.S. Department of Energy publication, DOE/GO-10099-646. http://www.oit.doe.gov/agriclture.pdfs/greenhousegaspap.pdf

Dobermann A., Department of Agronomy and Horticulture, University of Nebraska, personal communication by e-mail, May 07 and July 14 2004.

Kim S. and B. Dale. (2004a). Nonrenewable energy consumption and Greenhouse Gas Profile of Polyhydroxyalkanoates (PHA) derived from No-Tilled Corn Grains, De-partment of Chemical Engineering & Materials Science, Michigan State University, In-ternational Journal of Life Cycle Assessment (not published yet).

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Lal, R., J.M. Kumble, R.F. Follett, and C.V. Cole. (1998). The potential of U.S. crop-land to sequester carbon and mitigate the greenhouse effect. Ann Arbor Press. Chel-sea, MI.

Robertson G.P., et al. (2000). Greenhouse gases in intensive agriculture: Contribu-tions of individual gases to the radiative forcing of the atmosphere, Science, 15 Sep-tember 2000, Volume 289, page 1922-1925.

Six j., S.M. Ogle, F.J. Bredit, R.T. Conant, A.R. Mosier and K. Paustian, (2004), The potential to mitigate global warming with no-tillage management is only realized when practiced in the long term, Global Change Biology (2004) 10, 155-160.

Sheenan J. et al. (2002). Is ethanol from corn stover sustainable? Adventures in cy-ber-farming, National Renewable Energy Laboratory, Golden, CO, Draft report for Peer review, December 2002.

Snyder, C.S. and T.W. Bruulsema. 2002. Nutrients and environmental quality. Pp. 45-68. In, Plant Nutrient Use in North American Agriculture. PPI/PPIC/FAR Technical Bulletin 2002-1. Potash and Phosphate Institute, Norcross, GA.

West T.O. and G. Marland. (2002). A synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: comparing tillage practices in the United States, Agriculture, Ecosystems and Environment 91 (200) 217-232.

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Appendix F: Numerical presentation of the result graphs of the scenarios inves-tigated

All values given in the following tables refer to the functional unit of 1000 clam shells.

Sectoral indicator results “base scenario PLA 5” (Figure 4-1 to 4-3):

Impact Category Plastics production

Trans-port

plastics

Clam shell pro-duction

Recy-cling

Disposal Credit (feed-

stock re-cycling)

Credit (mech. re-

cycling

Fossil Resource Con-sumption [kg crude oil equ.] 6,56 0,58 0,64 0,48 0,02 4,15 0 Global Warming [kg CO2 equ] 23,4 2,4 8,5 20,6 9,1 15,6 0 Summer Smog (POCP) [g ethene equ.] 12,64 0,61 0,24 0,42 0,08 1,11 0 Acidification [g SO2 equ.] 184 59 12 12 4 21 0 Terrestrial Eutrophication [g PO4 equ.] 17,5 4,8 0,9 1,3 0,6 1,29 0 Carcinogenic Risk [mg As equ.] 0,02 0,22 0,29 0,26 0,11 0,49 0 Human Toxicity (PM10) [g PM10-equ.] 197 53 10 11 4 17 0 Aquatic Eutrophication [g PO4 equ.] 3,99 0,00 0,01 0,05 0,00 0,02 0 Farm Land [m2/year.] 21,4 0 0 0 0 0 0 CED (renewable) [kJ] 310336 154 4637 1208 0 2604 0 CED (non-renewable) [kJ] 613073 32475 129043 58105 897 250875 0 CED (total) [kJ] 923409 32629 133680 59313 898 253480 0

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Sectoral indicator results “base scenario PS” (Figure 4-1 to 4-3)

Impact Category Plastics production

Trans-port

plastics

Clam shell pro-duction

Recycling Disposal Credit (feed-

stock re-cycling)

Credit (mech.

recycling)

Fossil Resource Con-sumption [kg crude oil equ.] 23,46 0,14 0,80 0,62 0,04 5,17 7,16 Global Warming [kg CO2 equ] 54,8 0,4 10,6 30,7 25,2 12,3 32,1 Summer Smog (POCP) [g ethene equ.] 22,87 0,12 0,30 0,42 0,29 5,04 2,15 Acidification [g SO2 equ.] 174 3 15 18 12 39 47 Terrestrial Eutrophication [g PO4 equ.] 10,8 0,5 1,1 2,3 2,1 2,5 3,2 Carcinogenic Risk [mg As equ.] 10,79 0,04 0,36 0,68 0,30 2,26 0,97 Human Toxicity (PM10) [g PM10-equ.] 149 4 12 19 14 34 39 Aquatic Eutrophication [g PO4 equ.] 0,39 0,00 0,01 0,03 0,00 0,09 0,02 Farm Land [m2/year.] 0 0 0 0 0 0 0 CED (renewable) [kJ] 3854 0 5777 2690 0 2271 7855 CED (non-renewable) [kJ] 1279837 5911 160775 91625 1496 282753 490537 CED (total) [kJ] 1283691 5911 166553 94314 1497 285025 498392

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Sectoral indicator results “base scenario PP” (Figure 4-1 to 4-3)

Impact Category Plastics production

Trans-port

plastics

Clam shell pro-duction

Recy-cling

Disposal Credit (feed-

stock re-cycling)

Credit (mech. re-

cycling

Fossil Resource Con-sumption [kg crude oil equ.] 23,01 0,15 1,06 0,70 0,04 3,84 7,11 Global Warming [kg CO2 equ] 34,4 0,5 14,0 27,8 22,4 6,3 29,9 Summer Smog (POCP) [g ethene equ.] 25,64 0,11 0,39 0,52 0,37 4,27 1,94 Acidification [g SO2 equ.] 107 4 20 18 13 19 41 Terrestrial Eutrophication [g PO4 equ.] 7,4 0,6 1,4 2,3 2,4 1,4 2,7 Carcinogenic Risk [mg As equ.] 0,00 0,05 0,48 0,90 0,43 0,01 0,94 Human Toxicity (PM10) [g PM10-equ.] 96 4 16 19 16 19 34 Aquatic Eutrophication [g PO4 equ.] 5,46 0,00 0,01 0,05 0,00 0,90 0,02 Farm Land [m2/year.] 0 0 0 0 0 0 0 CED (renewable) [kJ] 6762 0 7629 2842 0 5271 6531 CED (non-renewable) [kJ] 1202425 6572 212293 101106 1586 202394 467767 CED (total) [kJ] 1209187 6572 219922 103948 1586 207665 474299

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Sectoral indicator results “base scenario PET” (Figure 4-1 to 4-3)

Impact Category Plastics production

Trans-port

plastics

Clam shell pro-duction

Recy-cling

Disposal Credit (feed-

stock re-cycling)

Credit (mech. re-

cycling

Fossil Resource Con-sumption [kg crude oil equ.] 24,60 0,18 0,88 0,85 0,05 3,23 6,29 Global Warming [kg CO2 equ] 67,4 0,6 11,7 28,9 20,0 9,5 26,2 Summer Smog (POCP) [g ethene equ.] 80,38 0,16 0,33 0,52 0,34 10,43 1,79 Acidification [g SO2 equ.] 315 4 16 20 11 42,8 36,5 Terrestrial Eutrophication [g PO4 equ.] 19,7 0,7 1,2 2,4 2,0 2,8 2,4 Carcinogenic Risk [mg As equ.] 28,30 0,05 0,40 0,48 0,13 3,67 0,80 Human Toxicity (PM10) [g PM10-equ.] 284 5 14 20 13 40,5 30,4 Aquatic Eutrophication [g PO4 equ.] 0,67 0,00 0,01 0,06 0,00 0,09 0,02 Farm Land [m2/year.] 0 0 0 0 0 0 0 CED (renewable) [kJ] 9158 0 6352 3444 0 6915 3479 CED (non-renewable) [kJ] 1522484 7739 176778 123026 1959 201972 407531 CED (total) [kJ] 1531642 7739 183130 126469 1959 209718 413270

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Net indicator results for base scenarios (Figure 4-1 to 4-3) Impact Category Unit PLA 5 PS PP PET Fossil Resource Consumption

kg crude oil equ. 4,08 12,68 14,00 17,04

Global Warming kg CO2 equ. 48,2 77,2 62,8 92,9 Summer Smog (POCP) g ethene equ. 12,87 16,81 20,82 69,50 Acidification g SO2 equ. 250 135 101 287 Terrestrial Eutrophi-cation g PO4 equ. 23,8 11,1 10,0 20,8 Carcinogenic Risk mg As equ. 0,40 8,83 0,91 24,90 Human Toxicity (PM10) g PM10-equ. 257 124 99 266 Aquatic Eutrophica-tion g PO4 equ. 4,03 0,33 4,60 0,63 CED renewable kJ. 313648 2116 5399 5904 CED (non-renewable) kJ 579030 762916 852471 1222106 CED (total) kJ 892679 765032 857870 1228010

Net indicator results for variant scenarios “PLA production” (Figure 4-4 tot 4-6) Impact Category Unit PLA 5 PLA 6 PLA/NG Fossil Resource Consumption

kg crude oil equ. 4,08 2,26 0,40

Global Warming kg CO2 equ. 48,2 25,6 15,0 Summer Smog (POCP) g ethene equ. 12,87 11,72 5,40 Acidification g SO2 equ. 250 144 142 Terrestrial Eutrophi-cation g PO4 equ. 23,8 18,1 15,7 Carcinogenic Risk mg As equ. 0,40 1,03 0,74 Human Toxicity (PM10) g PM10-equ. 257 157 146 Aquatic Eutrophica-tion g PO4 equ. 4,03 4,03 4,48 Farm land m2/year 21,4 21,4 20,8 CED renewable kJ. 313648 415871 373102 CED (non-renewable) kJ 579030 243005 169695 CED (total) kJ 892679 658877 542797

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Net indicator results for variant scenarios “PLA end-of-life options” (Figure 4-7 to 4-9) Impact Category Unit PLA 5

(base) PLA 5 (com-

posting) PLA 5 (anaero-bic digestion)

PLA 5 (chemi-cal recycling)

Fossil Resource Consumption

kg crude oil equ. 4,08 7,24 6,84 5,34

Global Warming kg CO2 equ. 48,2 57,3 48,1 34,1 Summer Smog (POCP) g ethene equ. 12,87 62,56 19,34 7,69 Acidification g SO2 equ. 250 256 253 144 Terrestrial Eutrophi-cation g PO4 equ. 23,8 23,5 23,7 13,9 Carcinogenic Risk mg As equ. 0,40 0,55 0,41 0,61 Human Toxicity (PM10) g PM10-equ. 257 261 259 147 Aquatic Eutrophica-tion g PO4 equ. 4,03 4,58 4,71 2,48 Farm land m2/year 21,4 21,4 21,4 10,5 CED renewable kJ. 313648 312865 310170 157636 CED (non-renewable) kJ 579030 743188 666959 547517 CED (total) kJ 892679 1056052 977129 705153

Net indicator results for combined variant scenarios “PLA 6 end-of-life options” (Figure 4-10 to 4-11) Impact Category Unit PLA 6 PLA 6 (com-

posting) PLA 6 (anaero-bic digestion)

PLA 6 (chemi-cal recycling)

Fossil Resource Consumption

kg crude oil equ. 2,26 5,42 5,01 4,27

Global Warming kg CO2 equ. 25,6 34,6 25,4 20,5 Summer Smog (POCP) g ethene equ. 11,72 61,64 18,42 7,08 Acidification g SO2 equ. 144 150 147 88 Terrestrial Eutrophi-cation g PO4 equ. 18,1 17,8 18,0 10,8 Carcinogenic Risk mg As equ. 1,03 1,18 1,04 0,92 Human Toxicity (PM10) g PM10-equ. 157 161 159 95 Aquatic Eutrophica-tion g PO4 equ. 4,03 4,58 4,71 2,45 Farm land m2/year 21,4 21,4 21,4 10,50 CED renewable kJ. 415871 415087 412392 219667 CED (non-renewable) kJ 243005 407151 330923 348557 CED (total) kJ 658877 822239 743315 568224

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Net indicator results for combined variant scenarios “PLA/NG end-of-life options” (Figure 4-12 to 4-13) Impact Category Unit PLA/NG PLA/NG

(composting)

PLA/NG (anaerobic digestion)

PLA /NG (chemical recycling)

Fossil Resource Consumption

kg crude oil equ. 0,40 3,47 3,06 3,30

Global Warming kg CO2 equ. 15,0 24,1 14,8 15,4 Summer Smog (POCP) g ethene equ. 5,40

55,16 11,94 3,88

Acidification g SO2 equ. 142 148 145 87 Terrestrial Eutrophi-cation g PO4 equ. 15,7 15,5 15,7 9,7 Carcinogenic Risk mg As equ. 0,74 0,92 0,79 0,80 Human Toxicity (PM10) g PM10-equ. 146 150 148 90 Aquatic Eutrophica-tion g PO4 equ. 4,48 4,84 4,97 2,60 Farm land m2/year 20,8 20,8 20,8 10,2 CED renewable kJ. 373102 372163 369468 198350 CED (non-renewable) kJ 169695 326543 250314 307752 CED (total) kJ 542797 698706 619783 506102

Net indicator results for variant scenarios “PET end-of-life options” (Figure 4-14 to 4-15) Impact Category Unit PET (ba-

se) PET (mecha-nical recyc-

ling) Fossil Resource Consumption

kg crude oil equ. 17,04 10,56

Global Warming kg CO2 equ. 92,9 52,6 Summer Smog (POCP) g ethene equ. 69,50 35,38 Acidification g SO2 equ. 287 158 Terrestrial Eutrophi-cation g PO4 equ. 20,8 11,7 Carcinogenic Risk mg As equ. 24,90 12,75 Human Toxicity (PM10) g PM10-equ. 266 147 Aquatic Eutrophica-tion g PO4 equ. 0,63 0,50 CED renewable kJ. 5904 9397 CED (non-renewable) kJ 1222106 769178 CED (total) kJ 1228010 778575

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Net indicator results for sensitivity scenarios “PLA process waste”- (Figure 5-1 to 5-3): Impact Category Unit PLA 5

(base) PLA 5 (proc-ess waste to cement kiln)

PLA 5 (process waste chemi-cally recycled)

Fossil Resource Consumption

kg crude oil equ. 4,08 5,03 4,74

Global Warming kg CO2 equ. 48,2 52,8 50,6 Summer Smog (POCP) g ethene equ. 12,87 15,09 13,41 Acidification g SO2 equ. 250 291 260 Terrestrial Eutrophi-cation g PO4 equ. 23,8 27,7 24,9 Carcinogenic Risk mg As equ. 0,40 0,37 0,43 Human Toxicity (PM10) g PM10-equ. 257 300 268 Aquatic Eutrophica-tion g PO4 equ. 4,03 4,74 4,20 Farm Land m2/year 21,4 25,2 22,0 CED renewable kJ. 313648 368094 323081 CED (non-renewable) kJ 579030 643000 624104 CED (total) kJ 892679 1011093 947185

Net indicator results for sensitivity scenarios “PET inventory dataset”- (Figure 5-4 to 5-6): Impact Category Unit PLA 5

(base) PET (Plastics

Europe) PET(Petcore) Fossil Resource Consumption

kg crude oil equ. 4,08 17,04 18,10

Global Warming kg CO2 equ. 48,2 92,9 82,9 Summer Smog (POCP) g ethene equ. 12,87 69,50 8,41 Acidification g SO2 equ. 250 287 125 Terrestrial Eutrophi-cation g PO4 equ. 23,8 20,8 12,5 Carcinogenic Risk mg As equ. 0,40 24,90 6,74 Human Toxicity (PM10) g PM10-equ. 257 266 117 Aquatic Eutrophica-tion g PO4 equ. 4,03 0,63 3,99 CED renewable kJ. 313648 5904 4101 CED (non-renewable) kJ 579030 1222106 1137503 CED (total) kJ 892679 1228010 1141604

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Net indicator results for sensitivity scenarios “50% Allocation” (Figure 5-8 to 5.10) Impact Category Unit PLA 5

(50% Al-location)

PS (50% Allo-cation)

PP (50% Alloca-tion)

PET (50% Allo-cation)

Fossil Resource Consumption

kg crude oil equ. 5,62 17,84 18,60 20,91

Global Warming kg CO2 equ. 56,5 75,6 59,9 90,3 Summer Smog (POCP)

g ethene e-qu. 13,20 19,91 23,47 75,39

Acidification g SO2 equ. 252 162 116 312 Terrestrial Eutrophi-cation g PO4 equ. 23,7 12,2 10,3 21,7 Carcinogenic Risk mg As equ. 0,48 10,05 0,79 26,89 Human Toxicity (PM10) g PM10-equ. 259 146 111 286 Aquatic Eutrophica-tion g PO4 equ. 4,02 0,36 5,03 0,66 CED renewable kJ. 313829 4596 8895 9854 CED (non-renewable) kJ 651855 1047812 1092741 1428928 CED (total) kJ 965684 1052408 1101636 1438782

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Appendix G: Critical Review Report

Life Cycle Assessment of POLYLACTIDE (PLA)

A comparison of food packaging made from NatureWorks® PLA and alternative materials Commissioned by NatureWorks LLC

Critical Review Report by

Stefan Schmitz (chair)

and

Dr. Andreas Ciroth

July 2006

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1 Introduction

The life cycle assessment study to be reviewed here

Life Cycle Assessment of PolyLactide (PLA) - A comparison of food packaging made from NatureWorks® PLA and alternative materials

was commissioned by NatureWorks LLC (in the following: “Commissioner”) and car-ried out by ifeu-Institut GmbH (Institute for Energy and Environmental Research), Heidelberg (in the following: “Practitioner”).

The study aims to comply with the international standards ISO 14040 series. Since it contains comparative assertions that are intended to be disclosed to the public, a critical review according to ISO 14040, §7.3.3 (“review by interested parties”) has to be performed. Within this special and most stringent type of a critical review proce-dure, a panel of external LCA-experts must be commissioned to carry out the review. Moreover, these experts may include interested parties, such as competitors, in the review process.

The critical review started in Nov. 2004, virtually at the same time as the LCA-project itself, shortly after the kick-off project meeting. The reviewers participated in three out of four project panel meetings, in which all issues concerning goal and scope of the LCA study were discussed and decided among the involved stakeholders, as well as further methodological and data related issues. An additional meeting took place be-tween commissioner, practitioner, and review panel, with the aim to clarify the goal and scope definition and, in particular, to specify the packaging systems to be stud-ied. Moreover, the reviewers received all drafts of the LCA report and used the op-portunity to make comments on them. Hence, this critical review can be regarded as “accompanying review”. It was designed as an interactive, integrated quality assur-ance procedure.

The critical review process took place in an open and constructive atmosphere. The statements made in this critical review report represent the consensus between the reviewers.

2 Review criteria

The critical review was performed according to the ISO standard 14040, taking into account the ISO standards 14041 to 14043. The review criteria, laid down in ISO 14040, section 7, are as follows:

The critical review process shall ensure that • the methods used to carry out the LCA are consistent with this International

Standard;

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• the methods used to carry out the LCA are scientifically and technically valid; • the data used are appropriate and reasonable in relation to the goal of the

study; • the interpretations reflect the limitations identified and the goal of the study; • the study report is transparent and consistent.

As for the method used it was checked whether all regulations and constraints, espe-cially those from ISO 14041 and 14042, were met and whether the method was con-sistent and state of the art.

As for the soundness of the data used datasets were checked and those with a par-ticularly high influence on the result were scrutinized to the highest possible degree. This holds especially for important parameters in the product system, such as spe-cific packaging weights, or recycling rates. In addition, CO2 balance calculations were used as a quality measure, both on the level of the whole inventory and on the level of important unit processes or aggregated processes. For data that seemed to be both relevant and uncertain, sensitivity analyses were proposed.

3 Results of the Critical Review

3.1 General Comments The LCA study deals in many respects with novel technologies and markets. In the course of the study, several practical, methodological, and data-related issues emerged. Due to a conjoint effort of a constructive stakeholder panel, active support by the commissioner of the study, and of the practitioner conducting the study, the review panel thinks that these issues were solved in a satisfying manner. Consequently, the general impression of the LCA study is excellent. It contains not only all formal elements required by ISO 1404032, but provides, further, all informa-tion concerning assumptions, constraints, calculations, and results in a transparent and comprehensible way. The study is titled “Life Cycle Assessment of PolyLactide (PLA)”. This may possibly suggest that the study compares different packaging materials and that it comes to the conclusion that one material is environmentally advantageous compared to the others. Therefore, it shall be stressed that only one specific application of this mate-rial, namely a 500 ml clam shell made by one defined packaging producer, has been investigated in this LCA. Thus, this study is a case study (which is also mentioned in the 2nd line of the title, and several times in the report), and the results gained cannot be transferred to other applications, nor can they be generalised. 32 Even if they are, in part, named differently (e.g., discussion instead of interpretation)

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It should be pointed out that, for the time being, the packaging material under obser-vation, PLA, has only a very little share of the German market. Thus, all assumptions regarding material demand, manufacturing, recycling etc. are of prospective nature and cannot be validated at present. The resulting uncertainty has been taken into ac-count by several sensitivity analyses.

3.2 Method The ISO standard 14040 requires a four-step procedure for LCA studies: goal and scope, inventory, impact assessment, interpretation. According to the review report, all four steps were carried out in this study, partly in an iterative procedure. Where necessary, methodological explanations are given (e.g., impact categories, allocation procedure). The methods used in this study are, to a large extent, identical to those applied in several other packaging LCA carried out by the ifeu-institute in the past, many of them having been critically reviewed according to ISO 14040. Nonetheless all meth-odological steps were scrutinized again within this critical review. In the first step “goal and scope definition” the definition of the systems and the sys-tem boundaries were carried out as well as assumptions and methodological deter-minations. This was done in an iterative process within the project panel meetings and is comprehensively documented in the report. For further details see next section “assumptions”. The second step “life cycle inventory” (LCI) basically comprises the data gathering, setting up of the network model and the calculation of the inventory. In the course of the critical review the appropriateness of the data used was discussed and proce-dures in case of data uncertainties were decided upon (see below section 3.4). The network model was checked and no mistakes were found. A thorough review of the inventory calculations was not feasible. However, the used software UMBERTO® has proved itself as a suitable tool in previous LCAs. Finally, the results of the LCI were plausibility-checked and no inconsistencies were found. The method of the third step “life cycle impact assessment” (LCIA) and the impact categories chosen are described in chapter 1.8 of the study. The method described and applied here is constrained to the mandatory elements according to ISO 14042, i.e., neither normalisation nor grouping has been performed. The characterisation factors used are documented in annex A. Both method and values are in line with the state of the art. The aspects of the last step of an LCA, “life cycle interpretation”, are handled com-pletely in chapters 5 and 6, “evaluation” and “discussion”. It is not clear why these terms are used instead of the original ISO terms. But this is only a formal aspect. The content of the two chapters meet the requirements of ISO 14043 with regard to inter-pretation.

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One visible difference to most LCA studies on packaging systems is that the study at hand does not conclude with a comparative assertion as to the overall environmental advantage of one of the compared packaging systems. However, this is no omission since the ISO standard merely demands for conclusions, limitations, and recommen-dations which are stated in chapters 5 and 6 of the study. In conclusion, it can be stated that the methods used are consistent with the interna-tional standards and represent the state of the art.

3.3 Assumptions Specifications of the packaging systems: Since the physical properties of the four packaging materials under study differ con-siderably in density and elasticity (see report, section 2.1) a mass related 1:1 com-parison of the materials would have been inappropriate. Hence, specific packaging systems had to be defined, with material specific weights per packaging unit. After an analysis of several packaging systems of the different materials, 500 ml clam shells were chosen as described in table 2-4. The differing weights of the clam shells both reflect physical properties and packaging unit production conditions and approxi-mately match the existing packaging systems. In conclusion, even if this LCA study is, strictly spoken, only a comparison between four defined, specific packaging systems, without general meaning for the material, the mass relation between the packaging systems can be regarded as “typical” for the materials involved. Material flows at the manufacturing site: According to the information given by Vitembal, about 16% of the material input in the thermoforming process occurs as waste that cannot be recycled within the process and is transferred to stock, for the time being (see report, section 2.3.1). Since LCAs usually assume steady state situations it is difficult to model mass flows with growing stock terms adequately in LCA. Therefore, it had to be decided how the share of the waste going to stock should be modelled. Considering the fact that PLA is a relatively new material and that, for the time being, the converting process for PLA is not technically mature yet, it was assumed that, in future, internal recycling will be feasible to a greater extent than in the reference process today. In consequence, it was assumed that a smaller part of the plastic waste generated in the PLA converting process will need to be disposed of by waste incineration, and a larger part will be recycled internally (see report, figure 2-2, part B). Moreover, it was assumed that all waste was either internally recycled or inciner-ated, and not stored on stock. This assumption was critically discussed in the panel, and backed by various expertises from industry. It is, however, quite optimistic and, as for the current situation, favours the PLA scenario. In order to estimate the influ-ence of this assumption on the results sensitivity analyses were carried out. The re-

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sults of these analyses are documented in section 5.2.1. They show that the assump-tion has only a minor influence on the results. However, this point has to be taken into consideration when interpreting the results. This is adequately reflected in the summary of the report.

3.4 Data As the results show that the most significant contributions stem from polymer produc-tion processes, special attention has to be paid to production related data. Unfortu-nately, the datasets for all polymers, PLA as well as the competing materials, PP, GPPS, and PET, are fully aggregated. They cannot be scrutinised in detail, since they contain no detailed information regarding their genesis, energy mix, allocation rules etc. The data set describing the production of PLA has been provided by the commis-sioner of the study and was reviewed by Dr. Ian Boustead. The datasets of the com-peting materials come, likewise, from the respective producers, compiled also by Dr. Boustead. Thus, it can be assumed that the methodological backgrounds of the datasets do not differ substantially. The PLA dataset was plausibility checked concerning carbon balance. It was found that the carbon uptake in the corn plant is about equivalent to the carbon outputs within the system boundaries and, consequently, the carbon cycle is closed over the whole life cycle of the observed system. Even though it is regrettable that the most important data sets of all four systems un-der study do not allow a detailed review, the conclusion drawn in the report “Overall the inventory datasets…can be regarded as the best possible choice for the purpose of the study” (section 5.1.2) can be supported by the reviewers.

3.5 Interpretation Chapter 5 of the report deals with the uncertainties of data and assumptions and ex-plains the limitations of results and conclusions. The reviewers believe that all rele-vant uncertainties are addressed in this chapter. It can be stated that the choice of the sensitivity scenarios as well as the conclusions drawn are appropriate and suffi-cient. It is the task of the interpretation phase of an LCA to combine the manifold single re-sults of the different scenarios reflecting the uncertainties and limitations identified and to derive conclusions and recommendations from these facts. Chapter 6 meets these requirements in a quite satisfying way. All relevant aspects are sufficiently considered. It can be stated that the authors of the report succeeded in the difficult task to merge the different findings of the study to only few impartial

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and unbiased conclusions and to derive recommendations to political decision mak-ers as well as to the commissioner and the scientific community.

3.6 Report The requirements of the standard for LCA reporting are stipulated in ISO 14040, chapter 6, and ISO 14041, chapter 8. The report at hand was examined with respect to these requirements. All mandatory elements are well documented in a transparent and comprehensible way. The reader of the report is enabled to trace the way from the assumptions and basic data via the results of the calculations to the point of con-clusions and recommendations. The report is well-balanced and illuminates both ad-vantages and disadvantages of the observed systems.

4 Summary and recommendations The observed LCA study can be said to be complete, in compliance with the stan-dards, and methodologically up to date. The conclusions described in the last chapter, discussion, are not of a better/worse-type as for the overall environmentally advantage of one of the packaging systems under study. Any further aggregation of the results would lead to inconsistencies as well as any quotation of only parts of the results. This is well reflected in the summary and in the discussion provided in chapter 6 of the study. The LCA study deals in many respects with novel technologies and markets. In the course of the study, several practical, methodological, and data-related issues emerged. Due to a conjoint effort of a constructive stakeholder panel, active support by the commissioner of the study, and of the practitioner conducting the study, the review panel thinks that these issues were solved in a satisfying manner. Consequently, the general impression of the LCA study is excellent. It contains all formal elements claimed in ISO 1404033 and provides all information concerning as-sumptions, constraints, calculations, and results in a transparent and comprehensible way.

In future reports on the same or similar topic, the reviewers see the following points for a further development:

- A validation of the assumptions of the current study on production conditions, market share, and the disposal situation for PLA

33 Even if they are, in part, named differenty (e.g., discussion instead of interpretation)

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- A provision of disaggregated datasets for plastics, which would foster trans-parency of the study

- Land use is for agricultural products a highly relevant impact category, espe-cially when these are compared to non-agricultural products. The land use im-pact modelling is currently still under development, with several competing scientific concepts. In a future study this development should be critically as-sessed as to whether a recommended land use modelling approach can be applied in a practical study.

- Agriculture is liable to quantitative uncertainties that seem of a higher degree than uncertainties for industrial processes. This calls for considering quantita-tive uncertainty in LCI datasets. It relies, however, on the availability of accord-ing uncertainty information, preferably on the level of disaggregated datasets.

We recommend publishing the report as a full LCA study according to ISO 14040.

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Appendix H: Short information about the critical reviewers

Stefan Schmitz (Chairman)

Stefan Schmitz studied at the Technical University of Berlin and has a professional back-ground of environmental engineering. He is working with the German Federal Environment Agency (UBA) where, during almost 15 years, he was a project leader in the area of packag-ing LCA and LCA-based product assessment. In this time he also made important contribu-tions to the development of the “German LCA methodology”.

Since 1993 he is representing UBA at the national and international standardization activities of ISO and DIN in the matter of Life Cycle Asssessment.

He was a leading UBA representative in the well-acknowledged LCA on beverage packaging II, one of the most comprehensive packaging LCAs ever performed in Germany.

He is also a member of the Editorial Board of the International Journal of Life Cycle Assess-ment.

Dr. Andreas Ciroth (Co-Reviewer)

Andreas Ciroth directs GreenDeltaTC GmbH, a company dedicated to tools and consulting for sound life cycle analyses. He earned his PhD 1998-2001 at the Technical University of Berlin, Germany, with a thesis on error calculation in Life Cycle Assessment. Since 2001, Andreas worked as consultant in systems analysis, Life Cycle Assessment, Life Cycle Cost-ing, environmental statistics, and software development, in various national and international projects.

Dr. Ciroth is author of several publications on Life Cycle Assessment and data quality, Life Cycle Costing, and software development. Since 2004 he is subject editor for "Uncertainty in LCA" for the International, and member of the Editorial Board of the Journal.