facts and statistics · Biopolymers, facts and statistics 2016 – 3 1 Introduction and background 4 2 Process routes 6 Glossary7 2.1 Bio-based polyesters 8 2.1.1 Polylactic acid

Biopolymers facts and statistics

2016

Biopolymers, facts and statistics 2016 – 3

1 Introduction and background 4

2 Process routes 6

Glossary 7

2.1 Bio-based polyesters 8

2.1.1 Polylactic acid (PLA) 8

2.1.2 Polyhydroxybutyrat (PHB) 10

2.1.3 Polybutylene succinate (PBS) 12

2.1.4 Polybutylene succinate adipate (PBSA) 15

2.1.5 Polytrimethylene terephthalate (PTT) 18

2.1.6 Polyethylene terephthalate (Bio-PET) 21

2.2 Bio-based polyolefins 24

2.2.1 Polyethylene (Bio-PE) 24

2.3 Bio-based polyamides (Bio-PA) 26

2.3.1 Homopolyamides 26

2.3.1.1 Bio-PA 6 26

2.3.1.2 Bio-PA 11 28

2.3.2 Copolyamides 29

2.3.2.1 Bio-PA 4.10 – Bio-PA 5.10 – Bio-PA 6.10 29

2.3.2.2 Bio-PA 10.10 30

2.4 Polyurethanes 32

2.5 Polysaccharid polymers 34

2.5.1 Cellulose-based polymers 34

2.5.1.1 Regenerated cellulose 34

2.5.1.2 Cellulose diacetate 35

2.5.2 Starch-based polymers 37

2.5.2.1 Thermoplastic starch (TPS) 37

2.5.2.2 Starch blends 38

3 Market data and land use facts 40

3.1 New Economy bioplastics global production capacities 42

3.2 New Economy bioplastics production capacities by material type 43

3.3 New Economy bioplastics production capacities by region 44

3.4 New Economy bioplastics production capacities by market segment 45

3.5 Land use for new Economy bioplastics 2015 and 2020 46

1

2

3

4 – Biopolymers, facts and statistics 2016

The IfBB – Institute for Bioplastics and Biocomposites is a research institute within the Hochschule Hannover, University of Applied Sciences and Arts, which was established in 2011 to respond to the growing need for expert knowledge in the area of bioplastics. With its practice-oriented research and its collaboration with industrial partners, the IfBB is able to shore up the market for bioplastics and, in addition, foster unbiased public awareness and understanding of the topic.

As an independent research-led expert institution for bio-plastics, the IfBB is willing to share its expertise, research findings and data with any interested party via the Internet, online and offline publications or at fairs and conferences. In carrying on these efforts, substantial information regarding market trends, processes and resource needs for bioplastics is being presented here in a concise format, in addition to the more detailed and comprehensive publica tion “Engineering Biopolymers”1.

One of our main concerns is to furnish a more rational basis for discussing bioplastics and use fact-based arguments in the public discourse. Furthermore, “Bio polymers – facts and statistics” aims to provide specific, qualified answers easily and quickly for decision makers in particular from public administration and the industrial sector. Therefore, this publication is made up like a set of rules and standards and largely foregoes textual detail. It offers extensive mar-ket-relevant and technical facts presented in graphs and charts, which means that the information is much easier to grasp. The reader can expect comparative market figures for various materials, regions, applications, process routes, agricultural land use or resource consumption, production capacities, geographic distribution, etc.

In recent years, many new types of bioplastics have emerged and innovative polymer materials are pushing on the plastics market. All the same, bioplastics by no means constitute a completely new class of materials but rather one that has been rediscovered from among the large group of plastic materials.

Introduction and background 1

1 Endres, Hans-Josef; Siebert-Raths, Andrea: Engineering Biopolymers. Markets, Manufacturing, Properties and Applications. München 2011


The first polymer materials fashioned by human hands were all based on modified natural materials (e.g., casein, gelatine, shellac, celluloid, cellophane, linoleum, rubber, etc.). That means they were bio-based since petrochemical materials were not yet available at that time. Ever since the middle of the 20th century, these early bio-based plastics, with a few exceptions (cellulose and rubber-based mate-rials), have almost been fully replaced by petrochemical materials.

By now, due to ecological concerns, limited petrochemical resources and sometimes new property profiles, bioplastics have undergone a remarkable revival and are taken more and more into focus by the general public, politics, the industrial sector and in particular the research community.

Of particular interest today are new types of bioplastics, which were developed in the past 30 years. The publica-tion presented here refers to the socalled “New Economy” bioplastics as opposed to “Old Economy” bioplastics which indicate earlier materials developed before petrochemical bioplastics emerged, yet still exist on the market today (e.g., rubber, cellophane, viscose, celluloid, cellulose aceta-te, linoleum).

“New Economy” bioplastics divide up into two main groups. On the one hand, there are those biopolymers which have a new chemical structure virtually unknown in connection with plastics until a few years ago (e.g. new bio-based polyesters such as PLA), on the other hand socalled “drop-ins”, with the same chemical structure yet bio-based. The most prominent drop-ins at this point are bio-based PET (Bio-PET) and bio-based polyethylene (Bio-PE).

BIOPLASTICS

Old Economy

RubberRegenerated cellulose

Cellulose acetatesLinoleum

etc.

New Economy

Chemical novelPLAPHAPEF

Starch blendsetc.

Drop-insBio-PABio-PE

Bio-PETBio-PP

etc.


Process routes depict the manufacturing steps from the raw material to the finished product, specifying the individual process steps, intermediate products, and input-output streams. So they serve as a guide for all considerations and calculations around the production of bioplastics, in parti-cular also with regard to their resource consumption.

The following methodical approach was chosen to establish the process routes:

The mass flows were first calculated using a molar method based on the chemical process, with the in troduction of known rates and conversion factors. The routes so established were confirmed with polymer manufacturers and the industry. In so far as no loss rates due to the chemical processes or the process stages were included, the calculations were made basically assuming no losses. The mass flows show feedstock and resulting land requirements in ha for the production of one metric ton of bioplastics. Feedstock requirements were calculated for the use of different crops. Yields of the most im-portant crops and renewable raw materials used for feedstock are shown in the chart below.

Please note that the yields in this context refer to the crop itself, which contains the raw material for proces-sing, and not to the harvested whole plant.

For calculating water use data, information on water use for different raw materials originally collected by the ‘Water Foot-print Network’ has been used. It is based on FAOSTAT crop definitions (Food and Agriculture Organization of UN) which are also used for land use calculations. This means, water use is only available from “seed to market place”. Only water, such as rainwater, irrigation and to somewhat extent process water to clean agricultural products, e.g., used/needed to grow the whole plant is included here. On the other side the water use for the processing like polymerization is neglected. This is part of an ongoing research, but this first simplified approach gives a good indication and delivers first data to the issue of water use of bioplastics.

Process routes2


Feedstock Crop Raw material

Global mean yield (Crop)

Average content of raw material

Resulting amount (raw material)

Calculations -> x -> =

Sugar cane Sugar cane

(without cane tops)

fermt. Sugar 70 t/ha 13 % 9.1 t sugar/ha

Sugar beet Beet (without leaves)

fermt. Sugar 52 t/ha 16 % 8.32 t sugar/ha

Corn Maize kernel Starch 6.5 t/ha 70 % 4.55 t starch/ha

Potatoes Potato tuber Starch 21 t/ha 18 % 3.78 t starch/ha

Wheat Wheat grains Starch 3.5 t/ha 46 % 1.60 t starch/ha

Wood Standing timber, residual wood Cellulose 1.64 t atro/ha 40 % 0.66 t cellulose/

ha

Castor oil plant Castor bean Castor oil

1 t seeds/ha (given one harvest

per year)40 %

0.4 t oil/ha (given one

harvest per year)

Glossary

Abbreviations used:atro = bone drybb = bio-basedfermt. = fermentableSCA = Succinic acidBDO = ButanediolPDO = PropanediolPTA = Purified terephthalic acidMEG = Monoethylene glycolPMDA = Pentamethylene diamineTMDA = Tetramethylene diamineHMDA = Hexamethylene diamineDMDA = Decamethylene diaminered coloured ressources have a petro-based origin

A large amount of additional information is also available at: www.ifbb-hannover.de.


Sugar cane

11.31 t

Sugar beet

9.19 t

Sugar

1.47 t

FermentationH2O

Microorg.

Catalyst

CO2

H2ODehydration

Lacticacid*

1.25 t

Lactide

1.00 t

Polymerization

PLA

1.00 t

FermentationH2O

Microorg.

Catalyst

CO2

H2ODehydration

Lacticacid*

1.25 t

Lactide

1.00 t

Polymerization

PLA

1.00 t

0.16 ha

2 370 m³

0.18 ha

1 215 m³

Corn

2.39 t

Potato

9.26 t

Wheat

3.54 t

Starch

1.67 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

1.47 t

0.37 ha

2 921 m³

0.44 ha

2 659 m³

1.04 ha

6 468 m³

Conversion rates:fermt. Sugar – Lactic acid 85 %Starch – Glucose 90 %

*

oror

2.1.1 Polylactic acid (PLA)

2.1 Bio-based polyesters


4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

0

0.2

ha/t

bio

poly

mer

9.26

Potato

0.44

Potato

2 659

Potato

Corn

2.39

Sugar beet

9.19

Sugar cane

11.31

3.54

Wheat

PLA – Feedstock requirements in t (different feedstocks)

Corn

0.37

Sugar beet

0.18

Sugar cane

0.16

1.04

Wheat

PLA – Land use in ha(different feedstocks)

2 000

3 000

0

1 000

m3 /

t bio

poly

mer 4 000

5 000

6 000

Corn

2 921

Sugar beet

1 215

Sugar cane

2 370

Wheat

6 468

PLA – Water use in m3 (different feedstocks)



4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

0

0.2

ha/t

bio

poly

mer

9.26

Potato

0.44

Potato

2 659

Potato

Corn

2.39

Sugar beet

9.19

Sugar cane

11.31

3.54

Wheat


Corn

0.37

Sugar beet

0.18

Sugar cane

0.16

1.04

Wheat


2 000

3 000

0

1 000

m3 /

t bio

poly

mer 4 000

5 000

6 000

Corn

2 921

Sugar beet

1 215

Sugar cane

2 370

Wheat

6 468


4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

0

0.2

ha/t

bio

poly

mer

9.26

Potato

0.44

Potato

2 659

Potato

Corn

2.39

Sugar beet

9.19

Sugar cane

11.31

3.54

Wheat


Corn

0.37

Sugar beet

0.18

Sugar cane

0.16

1.04

Wheat


2 000

3 000

0

1 000

m3 /

t bio

poly

mer 4 000

5 000

6 000

Corn

2 921

Sugar beet

1 215

Sugar cane

2 370

Wheat

6 468


PLA – Land use in ha (different feedstocks)


2.1.2 Polyhydroxybutyrat (PHB)

H2O

Microbialmass

Sugar cane

21.99 t

Sugar beet

17.88 t

Sugar

2.86 t

FermentationH2O

Microorg.

CO2

Compoundingand granulation

PHB*

1.00 t

FermentationH2O

Microorg.

CO2

0.32 ha

4 609 m³

0.34 ha

2 365 m³

Corn

4.63 t

Potato

18.04 t

Wheat

7.12 t

Starch

3.24 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

2.86 t

0.72 ha

5 658 m³

0.86 ha

5 181 m³

2.03 ha

13 009 m³

Conversion rates:Starch – Glucose 90 %fermt. Sugar – PHB 35 %

*

oror

Compoundingand granulation

PHB*

1.00 t

Isolation of biopolymers

Compounding and granulation

Isolation of biopolymers

Compounding and granulation

H2O

Microbialmass


30

10

15

20

25

0

5

t fee

dsto

ck/t

bio

poly

mer

0.8

1.2

1.6

2.0

2.4

0

0.4

ha/t

bio

poly

mer

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

10 000

12 000

Corn

4.63

Sugar beet

17.88

Sugar cane

21.99

7.12

Wheat

18.04

Potato

PHB– Feedstock requirements in t (different feedstocks)

Corn

0.72

Sugar beet

0.34

Sugar cane

0.32

2.03

Wheat

0.86

Potato

PHB – Land use in ha(different feedstocks)

Corn

5 658

Sugar beet

2 365

Sugar cane

4 609

Wheat

13 009

5 181

Potato

PHB– Water use in m3 (different feedstocks)PHB – Water use in m3 (different feedstocks)

PHB – Feedstock requirements in t (different feedstocks)

30

10

15

20

25

0

5

t fee

dsto

ck/t

bio

poly

mer

0.8

1.2

1.6

2.0

2.4

0

0.4

ha/t

bio

poly

mer

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

10 000

12 000

Corn

4.63

Sugar beet

17.88

Sugar cane

21.99

7.12

Wheat

18.04

Potato


Corn

0.72

Sugar beet

0.34

Sugar cane

0.32

2.03

Wheat

0.86

Potato


Corn

5 658

Sugar beet

2 365

Sugar cane

4 609

Wheat

13 009

5 181

Potato

PHB– Water use in m3 (different feedstocks)

30

10

15

20

25

0

5

t fee

dsto

ck/t

bio

poly

mer

0.8

1.2

1.6

2.0

2.4

0

0.4

ha/t

bio

poly

mer

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

10 000

12 000

Corn

4.63

Sugar beet

17.88

Sugar cane

21.99

7.12

Wheat

18.04

Potato


Corn

0.72

Sugar beet

0.34

Sugar cane

0.32

2.03

Wheat

0.86

Potato


Corn

5 658

Sugar beet

2 365

Sugar cane

4 609

Wheat

13 009

5 181

Potato


PHB – Land use in ha (different feedstocks)


2.1.3 Polybutylene succinate (PBS) with bio-based succinic acid (PBS bb SCA)

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Succinicacid*

0.69 t

Esterification1,4-BDO

0.52 t

H2O

0.10 t

H2O

0.10 t

Polycondensation

PBSbb SCA1.00 t

Sugar cane

6.61 t

Sugar beet

5.38 t

Sugar

0.86 t

0.09 ha

1 385 m³

0.10 ha

712 m³

Corn

1.39 t

Potato

5.43 t

Wheat

2.14 t

Starch

0.97 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

0.86 t

0.21 ha

1 699 m³

0.26 ha

1 559 m³

0.61 ha

3 910 m³

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Succinicacid*

0.69 t

Esterification1,4-BDO

0.52 t

H2O

0.10 t

H2O

0.10 t

Polycondensation

PBSbb SCA1.00 t

Conversion Rates:Starch – glucose 90 %fermt. Sugar – Succinic acid 80 %

*

oror


2.1.3 Polybutylene succinate (PBS) 100 % bio-based (PBS 100)

Esterification

H2O

0.10 t

H2O

0.10 t

Polycondensation

PBS100

1.00 t

0.685 t

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Sugar cane

13.15 t

Sugar beet

10.69 t

Sugar

1.71 t

0.19 ha

2 756 m³

0.21 ha

1 414 m³

Corn

2.77 t

Potato

10.79 t

Wheat

4.26 t

Starch

1.95 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

1.71 t

0.43 ha

3 385 m³

0.51 ha

3 099 m³

1.22 ha

7 783 m³

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration1,4-Bu-tanediol

0.52 t

Deoxidation

Succinicacid*

1.37 tLiAlH4

H2O

0.685 t

Esterification

H2O

0.10 t

H2O

0.10 t

Polycondensation

PBS100

1.00 t

0.685 t1,4-Bu-tanediol

0.52 t

Deoxidation

Succinicacid*

1.37 tLiAlH4

H2O

0.685 t

Conversion rates:Starch – Glucose 90 %fermt. Sugar – Succinic acid 80 %

*

oror


10 000

12 000

4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

1.2

0

0.2

ha/t

bio

poly

mer

14

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

Wheat

7 783

Potato

5.43

Potato

0.26

Potato

1 559

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane

PBS variations – Feedstock requirements in t(different feedstocks)

PBS variations – Land use in ha(different feedstocks)

1.39

5.38

6.61

Wheat

2.14

CornSugar beet

Sugar cane

2.77

10.69

13.15

Wheat

4.26

Potato

10.79

0.21

0.100.09

Wheat

0.61

CornSugar beet

Sugar cane

0.43

0.210.19

Wheat

1.22

Potato

0.51

PBS bb SCA

PBS bb SCA

PBS 100

CornSugar beet

Sugar cane

1 699

7121 385

Wheat

3 910

CornSugar beet

Sugar cane

3 385

1 414

2 756

Potato

3 099

PBS bb SCA

PBS 100

PBS 100


PBS variations – Water use in m3 (different feedstocks)

PBS variations – Feedstock requirements in t (different feedstocks)

10 000

12 000

4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

1.2

0

0.2

ha/t

bio

poly

mer

14

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

Wheat

7 783

Potato

5.43

Potato

0.26

Potato

1 559

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.39

5.38

6.61

Wheat

2.14

CornSugar beet

Sugar cane

2.77

10.69

13.15

Wheat

4.26

Potato

10.79

0.21

0.100.09

Wheat

0.61

CornSugar beet

Sugar cane

0.43

0.210.19

Wheat

1.22

Potato

0.51

PBS bb SCA

PBS bb SCA

PBS 100

CornSugar beet

Sugar cane

1 699

7121 385

Wheat

3 910

CornSugar beet

Sugar cane

3 385

1 414

2 756

Potato

3 099

PBS bb SCA

PBS 100

PBS 100


10 000

12 000

4

6

8

10

12

0

2

t fee

dsto

ck/t

bio

poly

mer

0.4

0.6

0.8

1.0

1.2

0

0.2

ha/t

bio

poly

mer

14

4 000

6 000

0

2 000

m3 /

t bio

poly

mer 8 000

Wheat

7 783

Potato

5.43

Potato

0.26

Potato

1 559

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.39

5.38

6.61

Wheat

2.14

CornSugar beet

Sugar cane

2.77

10.69

13.15

Wheat

4.26

Potato

10.79

0.21

0.100.09

Wheat

0.61

CornSugar beet

Sugar cane

0.43

0.210.19

Wheat

1.22

Potato

0.51

PBS bb SCA

PBS bb SCA

PBS 100

CornSugar beet

Sugar cane

1 699

7121 385

Wheat

3 910

CornSugar beet

Sugar cane

3 385

1 414

2 756

Potato

3 099

PBS bb SCA

PBS 100

PBS 100


PBS variations – Land use in ha (different feedstocks)


2.1.4 Polybutylene succinate adipate (PBSA) with bio-based succinic acid (PBSA bb SCA)

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Succinicacid*

0.39 t

Esterification1,4-BDO: 0.30 t

Adipic acid: 0.48 t

H2O

0.06 t

H2O

0.12 t

Polycondensation

PBSAbb SCA1.00 t

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Succinicacid*

0.39 t

Esterification1,4-BDO: 0.30 t

Adipic acid: 0.48 t

H2O

0.06 t

H2O

0.12 t

Polycondensation

PBSAbb SCA1.00 t

Sugar cane

3.77 t

Sugar beet

3.06 t

Sugar

0.49 t

0.05 ha

790 m³

0.06 ha

405 m³

Corn

0.79 t

Potato

3.09 t

Wheat

1.22 t

Starch

0.55 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

0.49 t

0.12 ha

965 m³

0.15 ha

887 m³

0.35 ha

2 229 m³


*

oror


2.1.4 Polybutylene succinate adipate (PBSA) with bio-based succinic acid and 1,4-butanediol (PBSA bb SCA/BDO)

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Sugar cane

7.54 t

Sugar beet

6.13 t

Sugar

0.98 t

0.11 ha

1 580 m³

0.12 ha

811 m³

PBSA bb SCA/BDO

1.00 t

Adipic acid: 0.49 t

Esterification

H2O

0.06 t

H2O

0.12 t

Polycondensation

1,4-Bu-tanediol

0.30 t

Deoxidation

Succinicacid*

0.78 tLiAlH4

H2O

0.39 t

0.39 t

FermentationH2O

Microorg.

H2O

Microbialmass

CO2

Filtration

Corn

1.59 t

Potato

6.18 t

Wheat

2.44 t

Starch

1.11 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

0.89 t

0.24 ha

1 943 m³

0.29 ha

1 775 m³

0.70 ha

4 458 m³

PBSA bb SCA/BDO

1.00 t

Adipic acid: 0.49 t

Esterification

H2O

0.06 t

H2O

0.12 t

Polycondensation

1,4-Bu-tanediol

0.30 t

Deoxidation

Succinicacid*

0.78 tLiAlH4

H2O

0.39 t

0.39 t


*

oror


4

6

8

0

2

0.4

0.6

0.8

0

0.2

2 000

3 000

0

1 000

5 000

4 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane

PBSA variations – Feedstock requirements in t(different feedstocks)

PBSA variations – Land use in ha(different feedstocks)

0.79

3.063.77

CornSugar beet

Sugar cane

1.59

6.13

7.54

Wheat

2.44

0.120.060.05

CornSugar beet

Sugar cane

0.24

0.120.11

Wheat

0.70

PBSA bb SCA

PBSA bb SCA

PBSA bb SCA/BDO

CornSugar beet

Sugar cane

965

405790

Potato

3.09

Potato

0.15

Potato

887

Wheat

1.22

Wheat

0.35

Wheat

2 229

CornSugar beet

Sugar cane

1 943

811

1 580

Potato

6.18

Potato

0.29

Potato

1 775

Wheat

4 458

PBSA bb SCA

PBSA bb SCA/BDO

PBSA bb SCA/BDO

PBSA variation – Water use in m3 (different feedstocks)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

PBSA variations – Water use in m3 (different feedstocks)

PBSA variations – Feedstock requirements in t (different feedstocks)

4

6

8

0

2

0.4

0.6

0.8

0

0.2

2 000

3 000

0

1 000

5 000

4 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



0.79

3.063.77

CornSugar beet

Sugar cane

1.59

6.13

7.54

Wheat

2.44

0.120.060.05

CornSugar beet

Sugar cane

0.24

0.120.11

Wheat

0.70

PBSA bb SCA

PBSA bb SCA

PBSA bb SCA/BDO

CornSugar beet

Sugar cane

965

405790

Potato

3.09

Potato

0.15

Potato

887

Wheat

1.22

Wheat

0.35

Wheat

2 229

CornSugar beet

Sugar cane

1 943

811

1 580

Potato

6.18

Potato

0.29

Potato

1 775

Wheat

4 458

PBSA bb SCA

PBSA bb SCA/BDO

PBSA bb SCA/BDO


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

4

6

8

0

2

0.4

0.6

0.8

0

0.2

2 000

3 000

0

1 000

5 000

4 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



0.79

3.063.77

CornSugar beet

Sugar cane

1.59

6.13

7.54

Wheat

2.44

0.120.060.05

CornSugar beet

Sugar cane

0.24

0.120.11

Wheat

0.70

PBSA bb SCA

PBSA bb SCA

PBSA bb SCA/BDO

CornSugar beet

Sugar cane

965

405790

Potato

3.09

Potato

0.15

Potato

887

Wheat

1.22

Wheat

0.35

Wheat

2 229

CornSugar beet

Sugar cane

1 943

811

1 580

Potato

6.18

Potato

0.29

Potato

1 775

Wheat

4 458

PBSA bb SCA

PBSA bb SCA/BDO

PBSA bb SCA/BDO


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

PBSA variations – Land use in ha (different feedstocks)


2.1.5 Polytrimethylene terephthalate (PTT) with bio-based 1,3-propanediol (PTT bb PDO)

FermentationH2O

Microorg.

H2O

Stillage

CO2

Filtration

PTA

0.80 t

1,3-Pro-panediol*

0.37 t

Esterification

H2O

0.09 t

H2O

0.09 t

Polycondensation

PTTbb PDO

1.00 tPTA

0.80 t

1,3-Pro-panediol*

0.37 t

Esterification

H2O

0.09 t

H2O

0.09 t

Polycondensation

PTTbb PDO

1.00 t

FermentationH2O

Microorg.

H2O

Stillage

CO2

Filtration

Sugar cane

7.07 t

Sugar beet

5.75 t

Sugar

0.92 t

0.10 ha

1 482 m³

0.11 ha

761 m³

Corn

1.49 t

Potato

5.81 t

Wheat

2.29 t

Starch

1.04 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

0.92 t

0.23 ha

1 821 m³

0.28 ha

1 669 m³

0.65 ha

4 184 m³

Conversion rates:Starch – Glucose 90 %fermt. Sugar – Propanediol 40 %

*

oror


2.1.5 Polytrimethylene terephthalate (PTT) 100 % bio-based (PTT 100)

H2O

0.92 t 1.94 t

Enzymes

H2O

DextrinsHydrolysis

FermentationH2O

Microorg.

H2O

Stillage

CO2

Filtration

FermentationH2O

Microorg.

H2O

Stillage

CO2

Filtration

1,3-Pro-panediol*

0.37 tEsterification

H2O

0.09 t

H2O

0.09 t

Iso-octene0.54 t

DehydrogenationH2SO4

1.43 t

Polycondensation

DehydrationH2O: 0.18 t

Other: 0.04 t

H2O: 0.26 t

H2SO4: 1.26 t

Sugar cane

21.99 t

Sugar beet

17.88 t

fermt.Sugar/

Glucose*

2.86 t

0.31 ha

4 609 m³

0.34 ha

2 365 m³

Corn

4.63 t

Potato

18.05 t

Wheat

7.12 t

Starch

3.25 t

Iso-butanol*

0.76 t

Dimerization

Para-Xylene1

0.51 t

OxidationKMnO4

3.07 t

KOH: 1.09 t

MnO2: 1.69 t

Bio-PTA

0.81 t

Iso-butene0.54 t

0.71 ha

5 658 m³

0.86 ha

5 184 m³

2.03 ha

13 009 m³

1 GEVO-Process

PTT 100

1.00 t

Conversion rates:Starch – Glucose 90 %fermt. Sugar – Propanediol 40 %Glucose – Isobutanol 39 %

*

or

or or

or


10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane

PTT variations – Feedstock requirements in t(different feedstocks)

PTT variations – Land use in ha(different feedstocks)

1.49

5.757.07

CornSugar beet

Sugar cane

4.63

17.88

21.99

0.230.110.10

CornSugar beet

Sugar cane

0.71

0.340.31

PTT bb PDO

PTT bb PDO

PTT 100

CornSugar beet

Sugar cane

1 821

7611 482

Potato

5.81

Potato

0.28

Potato

1 669

Wheat

2.29

Wheat

0.65

Wheat

4 184

CornSugar beet

Sugar cane

5 658

2 365

4 609

Potato

18.05

Potato

0.86

Potato

5 184

Wheat

7.12

Wheat

2.03

Wheat

13 009

PTT bb PDO

PTT 100

PTT 100

PTT variations – Water use in m3 (different feedstocks)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer


PTT variations – Feedstock requirements in t (different feedstocks)

10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.49

5.757.07

CornSugar beet

Sugar cane

4.63

17.88

21.99

0.230.110.10

CornSugar beet

Sugar cane

0.71

0.340.31

PTT bb PDO

PTT bb PDO

PTT 100

CornSugar beet

Sugar cane

1 821

7611 482

Potato

5.81

Potato

0.28

Potato

1 669

Wheat

2.29

Wheat

0.65

Wheat

4 184

CornSugar beet

Sugar cane

5 658

2 365

4 609

Potato

18.05

Potato

0.86

Potato

5 184

Wheat

7.12

Wheat

2.03

Wheat

13 009

PTT bb PDO

PTT 100

PTT 100


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.49

5.757.07

CornSugar beet

Sugar cane

4.63

17.88

21.99

0.230.110.10

CornSugar beet

Sugar cane

0.71

0.340.31

PTT bb PDO

PTT bb PDO

PTT 100

CornSugar beet

Sugar cane

1 821

7611 482

Potato

5.81

Potato

0.28

Potato

1 669

Wheat

2.29

Wheat

0.65

Wheat

4 184

CornSugar beet

Sugar cane

5 658

2 365

4 609

Potato

18.05

Potato

0.86

Potato

5 184

Wheat

7.12

Wheat

2.03

Wheat

13 009

PTT bb PDO

PTT 100

PTT 100


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

PTT variations – Land use in ha (different feedstocks)


2.1.6 Polyethylene terephthalate (Bio-PET) with bio-based ethanol (Bio-PET bb EtOH)

MEG1

0.32 t

MEG1

0.32 t

Sugar cane

5.69 t

Sugar beet

4.63 t

Sugar

0.74 t

Conversion rates:Starch – Glucose 90 %Glucose – Ethanol 48 %Ethanol – Ethene 48 %Ethene – Etheneoxide 85 %

*

0.08 ha

1 193 m³

0.09 ha

612 m³

Corn

1.21 t

Potato

4.73 t

Wheat

1.85 t

Starch

0.85 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

0.75 t

0.19 ha

1 479 m³

0.23 ha

1 358 m³

0.53 ha

3 380 m³

FermentationH2O

Yeast

CO2

H2O

0.11 tDehydration

Ethene*

0.17 t

Ethanol*

0.36 t

H2O

StillageFiltration

Ethene-carbonate

0.46 t

Catalyticoxidation

Catalyticoxidation

O2

0.10 t

CO2: 0.03 t

H2O: 0.01 t

ReactionH2O

0.09 t

CO2

0.23 t

Ethene-oxide*

0.23 t

ReactionO2

0.23 t

PTA


H2O

0.09 t

H2O

0.095 t

Polycondensation

Bio-PETbb EtOH

1.00 t

FermentationH2O

Yeast

CO2

H2O

0.11 tDehydration

Ethene*

0.17 t

Ethanol*

0.36 t

H2O

StillageFiltration

Ethene-carbonate

0.46 t

O2

0.10 t

CO2: 0.03 t

H2O: 0.01 t

ReactionH2O

0.09 t

CO2

0.23 t

Ethene-oxide*

0.23 t

ReactionO2

0.23 t

PTA


H2O

0.09 t

H2O

0.095 t

Polycondensation

Bio-PETbb EtOH

1.00 t

1 Omega-Process (Shell)

oror


2.1.6 Polyethylene terephthalate (Bio-PET) 100 % bio-based (Bio-PET 100)

H2O

0.74 t 2.08 t

Enzymes

H2O

DextrinsHydrolysis

FermentationH2O

Microorg.

H2O

Stillage

CO2

Filtration

H2O

0.01 t

Iso-octene0.58 t

Polycondensation

Sugar cane

21.69 t

Sugar beet

17.63 t

fermt.Sugar/

Glucose*

2.82 t

0.31 ha

4 546 m³

0.34 ha

2 332 m³

Corn

4.59 t

Potato

17.85 t

Wheat

7.03 t

Starch

3.21 t

DehydrationH2O: 0.19 t

Other: 0.04 t

Iso-butanol*

0.81 t

Para-xylene2

0.55 t

DehydrogenationH2SO4

1.53 t

H2O: 0.28 t

H2SO4: 1.28 t

PTA

0.87 t

OxidationKMnO4

3.29 t

MnO2: 1.81 t

KOH: 1.16 t

Dimerization

Iso-butene0.58 t

0.71 ha

5 609 m³

0.85 ha

5 126 m³

2.01 ha

12 844 m³

Bio-PET100

1.00 t

FermentationH2O

Yeast

CO2

H2O: 0.11 t

EtOH: 0.08 tDehydration

Ethene*

0.17 t

Ethene-carbonate

0.46 t

Ethanol*

0.36 t

H2O

StillageFiltration

Ethene-oxide*

0.23 t

Catalyticoxidation

O2

0.10 t

CO2: 0.03 t

H2O: 0.01 t

ReactionCO2

0.23 t


MEG1

0.32 t

ReactionH2O

0.09 t

CO2

0.23 t


Conversion rates:Starch – Glucose 90 %Glucose – Ethanol 48 %Glucose – Isobutanol 39 %Ethanol – Ethene 48 %Ethene – Etheneoxide 85 %

*

1 Omega-Process (Shell)2 GEVO-Process

oror

or or


10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

Wheat

1.85

Wheat

0.53

Wheat

3 380

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane

Bio-PET variations – Feedstock requirements in t(different feedstocks)

Bio-PET variations – Land use in ha(different feedstocks)

1.21

4.635.69

Potato

4.73

CornSugar beet

Sugar cane

4.59

17.63

21.69

0.190.090.08

Potato

0.23

CornSugar beet

Sugar cane

0.71

0.340.31

Bio-PET bb EtOH

Bio-PET bb EtOH

Bio-PET 100

CornSugar beet

Sugar cane

1 479

6121 193

Potato

1 358

CornSugar beet

Sugar cane

5 609

2 332

4 546

Potato

17.85

Potato

0.85

Potato

5 126

Wheat

7.03

Wheat

2.01

Wheat

12 844

Bio-PET bb EtOH

Bio-PET 100

Bio-PET 100

Bio-PET variations – Water use in m3 (different feedstocks)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer


Bio-PET variations – Feedstock requirements in t (different feedstocks)

10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

Wheat

1.85

Wheat

0.53

Wheat

3 380

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.21

4.635.69

Potato

4.73

CornSugar beet

Sugar cane

4.59

17.63

21.69

0.190.090.08

Potato

0.23

CornSugar beet

Sugar cane

0.71

0.340.31

Bio-PET bb EtOH

Bio-PET bb EtOH

Bio-PET 100

CornSugar beet

Sugar cane

1 479

6121 193

Potato

1 358

CornSugar beet

Sugar cane

5 609

2 332

4 546

Potato

17.85

Potato

0.85

Potato

5 126

Wheat

7.03

Wheat

2.01

Wheat

12 844

Bio-PET bb EtOH

Bio-PET 100

Bio-PET 100


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

10

15

20

25

0

5

0.8

1.2

1.6

2.0

0

0.4

10 000

12 000

4 000

6 000

0

2 000

8 000

Wheat

1.85

Wheat

0.53

Wheat

3 380

CornSugar beet

Sugar cane

CornSugar beet

Sugar cane



1.21

4.635.69

Potato

4.73

CornSugar beet

Sugar cane

4.59

17.63

21.69

0.190.090.08

Potato

0.23

CornSugar beet

Sugar cane

0.71

0.340.31

Bio-PET bb EtOH

Bio-PET bb EtOH

Bio-PET 100

CornSugar beet

Sugar cane

1 479

6121 193

Potato

1 358

CornSugar beet

Sugar cane

5 609

2 332

4 546

Potato

17.85

Potato

0.85

Potato

5 126

Wheat

7.03

Wheat

2.01

Wheat

12 844

Bio-PET bb EtOH

Bio-PET 100

Bio-PET 100


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

Bio-PET variations – Land use in ha (different feedstocks)


Catalyst

Sugar cane

33.53 t

Sugar beet

27.25 t

Sugar

4.36 t

FermentationH2O

Yeast

Catalyst

CO2

RectificationStillage

H2O

H2O: 0.64 t


Bio-Ethanol*

2.08 t

Ethene*

1.00 t

Polymerization

Bio-PE

1.00 t

FermentationH2O

Yeast

CO2

RectificationStillage

H2O

H2O: 0.64 t


Bio-Ethanol*

2.08 t

Ethene*

1.00 t

Polymerization

Bio-PE

1.00 t

0.48 ha

7 028 m³

0.52 ha

3 604 m³

Corn

7.06 t

Potato

27.51 t

Wheat

10.86 t

Starch

4.95 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

4.36 t

1.09 ha

8 627 m³

1.31 ha

7 901 m³

3.10 ha

19 842 m³

Conversion rates:Starch – Glucose 90 %fermt. Sugar – Ethanol 48 %Ethanol – Ethene 48 %(conventional technology)

*

oror

2.2.1 Polyethylene (Bio-PE)

2.2 Bio-based polyolefi ns


1.0

1.5

2.0

2.5

3.0

0

0.5

8 000

10 000

4 000

6 000

0

2 000

30

35

10

15

20

25

0

5

27.51

Potato

7 901

Potato

1.31

Potato

10.86

Wheat

3.10

Wheat

Wheat

19 842

Corn

7.06

Sugar beet

27.25

Sugar cane

33.53

Bio-PE– Feedstock requirements in t (different feedstocks)

Corn

8 627

Sugar beet

3 604

Sugar cane

7 028

Corn

1.09

Sugar beet

0.52

Sugar cane

0.48

Bio-PE – Land use in ha(different feedstocks)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

Bio-PE – Water use in m3

(different feedstocks)

Bio-PE – Feedstock requirements in t (different feedstocks)

1.0

1.5

2.0

2.5

3.0

0

0.5

8 000

10 000

4 000

6 000

0

2 000

30

35

10

15

20

25

0

5

27.51

Potato

7 901

Potato

1.31

Potato

10.86

Wheat

3.10

Wheat

Wheat

19 842

Corn

7.06

Sugar beet

27.25

Sugar cane

33.53


Corn

8 627

Sugar beet

3 604

Sugar cane

7 028

Corn

1.09

Sugar beet

0.52

Sugar cane

0.48


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

1.0

1.5

2.0

2.5

3.0

0

0.5

8 000

10 000

4 000

6 000

0

2 000

30

35

10

15

20

25

0

5

27.51

Potato

7 901

Potato

1.31

Potato

10.86

Wheat

3.10

Wheat

Wheat

19 842

Corn

7.06

Sugar beet

27.25

Sugar cane

33.53


Corn

8 627

Sugar beet

3 604

Sugar cane

7 028

Corn

1.09

Sugar beet

0.52

Sugar cane

0.48


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

Bio-PE – Land use in ha (different feedstocks)


Ring-openingpolymerization

Sugar cane

23.61 t

Sugar beet

19.19 t

Sugar

3.07 t

FermentationH2O

Microorg.

Catalyst

Catalyst

Microbialmass

CO2, H2O

CO2, H2O

Microbialmass

Fermentation

Lysine*

2.15 t

Ring-openingpolymerization

Bio-PA 6

1.00 t

Capro-lactam*

1.00 t

FermentationH2O

Microorg.

H2O

Microorg.

H2O

Microorg. Microbialmass

CO2, H2O

CO2, H2O

Microbialmass

Fermentation

Lysine*

2.15 t

Bio-PA 6

1.00 t

Capro-lactam*

1.00 t

0.34 ha

4 948 m³

0.37 ha

2 538 m³

Corn

4.99 t

Potato

19.37 t

Wheat

7.64 t

Starch

3.49 t

H2O

Enzymes

H2O

DextrinsHydrolysis

Glucose*

3.07 t

0.77 ha

6 098 m³

0.92 ha

5 563 m³

2.18 ha

13 959 m³

Conversion rates:Starch – Glucose 90 %fermt. Sugar – Lysine 70 %Lysine – Caprolactam 47 %

*

oror

2.3.1 Homopolyamides 2.3.1.1 Bio-PA 6

2.3 Bio-based polyamides (Bio-PA)


10

15

20

25

0

5

0.8

1.2

1.6

2.0

2.4

0

0.4

8 000

10 000

12 000

4 000

6 000

0

2 000

Corn

4.99

Sugar beet

19.19

Sugar cane

23.61

Bio-PA 6 – Feedstock requirements in t (different feedstocks)

Corn

0.77

Sugar beet

0.37

Sugar cane

0.34

Bio-PA 6 – Land use in ha(different feedstocks)

Corn

6 098

Sugar beet

2 538

Sugar cane

4 948

7.64

Wheat

2.18

Wheat

Wheat

13 959

19.37

Potato

0.92

Potato

5 563

Potato

Bio-PA 6 – Water use in m3


t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

Bio-PA 6 – Water use in m3 (different feedstocks)


10

15

20

25

0

5

0.8

1.2

1.6

2.0

2.4

0

0.4

8 000

10 000

12 000

4 000

6 000

0

2 000

Corn

4.99

Sugar beet

19.19

Sugar cane

23.61


Corn

0.77

Sugar beet

0.37

Sugar cane

0.34


Corn

6 098

Sugar beet

2 538

Sugar cane

4 948

7.64

Wheat

2.18

Wheat

Wheat

13 959

19.37

Potato

0.92

Potato

5 563

Potato



t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

10

15

20

25

0

5

0.8

1.2

1.6

2.0

2.4

0

0.4

8 000

10 000

12 000

4 000

6 000

0

2 000

Corn

4.99

Sugar beet

19.19

Sugar cane

23.61


Corn

0.77

Sugar beet

0.37

Sugar cane

0.34


Corn

6 098

Sugar beet

2 538

Sugar cane

4 948

7.64

Wheat

2.18

Wheat

Wheat

13 959

19.37

Potato

0.92

Potato

5 563

Potato



t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

m3 /

t bio

poly

mer

Bio-PA 6 – Land use in ha (different feedstocks)


2.3.1 Homopolyamides 2.3.1.2 Bio-PA 11

Bio-PA 11

1.00 t

Castor oil1

2.38 t

5.99 ha

23 553 m³

Conversion rates:Ricinoleic acid – Undecane acid 50 %

*

Pyrolysis0.62 t

Heptanal

Hydrolysis

Amino-undecane

acid1.09 t

Ricinoleicacid

2.02 t

Undecaneacid*

1.01 t

Catalyticconversion

Ammonia

0.09 t

H2

0.01 t

CondensationH2O

0.09 t

1 one harvest per year


2.3.2 Copolyamides 2.3.2.1 Bio-PA 4.10 – Bio-PA 5.10 – Bio-PA 6.10

Conversion rates:Ricinoleic acid – Sebacic acid 60 %

*


Castor oil1

1.56 t

3.86 ha

15 438 m³

Hydrolysis

Ricinoleicacid

1.33 t

Sebacicacid*

0.80 t

Alkalinecracking

Alkalinecracking

Alkalinecracking

NaOH

0.32 t

2-Octanol:0.51 t

Sodium:0.18 t

TMDA

0.35 tCondensation

H2O

0.15 t

Bio-PA4.101.00 t

Castor oil1

1.47 t

3.70 ha

14 547 m³

Hydrolysis

Ricinoleicacid

1.25 t

Sebacicacid*

0.75 t

NaOH

0.30 t

2-Octanol:0.48 t

Sodium:0.17 t

PMDA

0.38 tCondensation

H2O

0.13 t

Bio-PA5.101.00 t

Castor oil1

1.41t

3.57 ha

13 953 m³

Hydrolysis

Ricinoleicacid

1.20 t

Sebacicacid*

0.72 t

NaOH

0.28 t

2-Octanol:0.46 t

Sodium:0.16 t

TMDA

0.41 tCondensation

H2O

0.13 t

Bio-PA6.101.00 t


*


Castor oil1

1.56 t

3.86 ha

15 438 m³

Hydrolysis

Ricinoleicacid

1.33 t

Sebacicacid*

0.80 t

Alkalinecracking

Alkalinecracking

Alkalinecracking

NaOH

0.32 t

2-Octanol:0.51 t

Sodium:0.18 t

TMDA

0.35 tCondensation

H2O

0.15 t

Bio-PA4.101.00 t

Castor oil1

1.47 t

3.70 ha

14 547 m³

Hydrolysis

Ricinoleicacid

1.25 t

Sebacicacid*

0.75 t

NaOH

0.30 t

2-Octanol:0.48 t

Sodium:0.17 t

PMDA

0.38 tCondensation

H2O

0.13 t

Bio-PA5.101.00 t

Castor oil1

1.41t

3.57 ha

13 953 m³

Hydrolysis

Ricinoleicacid

1.20 t

Sebacicacid*

0.72 t

NaOH

0.28 t

2-Octanol:0.46 t

Sodium:0.16 t

TMDA

0.41 tCondensation

H2O

0.13 t

Bio-PA6.101.00 t


*


Castor oil1

1.56 t

3.86 ha

15 438 m³

Hydrolysis

Ricinoleicacid

1.33 t

Sebacicacid*

0.80 t

Alkalinecracking

Alkalinecracking

Alkalinecracking

NaOH

0.32 t

2-Octanol:0.51 t

Sodium:0.18 t

TMDA

0.35 tCondensation

H2O

0.15 t

Bio-PA4.101.00 t

Castor oil1

1.47 t

3.70 ha

14 547 m³

Hydrolysis

Ricinoleicacid

1.25 t

Sebacicacid*

0.75 t

NaOH

0.30 t

2-Octanol:0.48 t

Sodium:0.17 t

PMDA

0.38 tCondensation

H2O

0.13 t

Bio-PA5.101.00 t

Castor oil1

1.41t

3.57 ha

13 953 m³

Hydrolysis

Ricinoleicacid

1.20 t

Sebacicacid*

0.72 t

NaOH

0.28 t

2-Octanol:0.46 t

Sodium:0.16 t

TMDA

0.41 tCondensation

H2O

0.13 t

Bio-PA6.101.00 t


2.3.2 Copolyamids 2.3.2.2 Bio-PA 10.10

Castor oil1

2.35 t

5.85 ha

23 256 m³


*

Hydrolysis

Ricinoleicacid

2.00 t

Sebacicacid*

1.20 t

Alkalinecracking

NaOH

0.48 t

2-Octanol: 0.77 t

Sodium: 0.27 t


Deca-dinitrile

Nitrilesynthesis

Deoxidation

Bio-PA10.101.00 t

CondensationH2O

0.11 t

NH3

0.10 t

H2O

0.21 t

H+/Ni

0.02 t

0.60 t

0.60 t

DMDA

0.51 t


1.0

1.5

2.0

2.5

0

0.5

2.0

3.0

4.0

5.0

6.0

0

1.0

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

16 000

20 000

24 000

8 000

12 000

0

4 000

m3 /

t bio

poly

mer

Bio-PA – Water use in m3


Bio-PA 6.10

1.41

Bio-PA 5.10

1.47

Bio-PA 4.10

1.56

2.35

Bio-PA 10.10

2.38

Bio-PA 11

Bio-PA 6.10

Bio-PA 5.10

Bio-PA 4.10

Bio-PA 10.10

Bio-PA 11

Bio-PA – Feedstock requirements in t (feedstock castor oil)

3.573.703.86

5.85 5.99

Bio-PA – Land use in ha(feedstock castor oil)

Bio-PA 6.10

13 953

Bio-PA 5.10

14 547

Bio-PA 4.10

15 438

23 256

Bio-PA 10.10

23 256

Bio-PA 11

Bio-PA – Water use in m3 (feedstock castor oil)


1.0

1.5

2.0

2.5

0

0.5

2.0

3.0

4.0

5.0

6.0

0

1.0

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

16 000

20 000

24 000

8 000

12 000

0

4 000

m3 /

t bio

poly

mer



Bio-PA 6.10

1.41

Bio-PA 5.10

1.47

Bio-PA 4.10

1.56

2.35

Bio-PA 10.10

2.38

Bio-PA 11

Bio-PA 6.10

Bio-PA 5.10

Bio-PA 4.10

Bio-PA 10.10

Bio-PA 11


3.573.703.86

5.85 5.99


Bio-PA 6.10

13 953

Bio-PA 5.10

14 547

Bio-PA 4.10

15 438

23 256

Bio-PA 10.10

23 256

Bio-PA 11

1.0

1.5

2.0

2.5

0

0.5

2.0

3.0

4.0

5.0

6.0

0

1.0

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

16 000

20 000

24 000

8 000

12 000

0

4 000

m3 /

t bio

poly

mer



Bio-PA 6.10

1.41

Bio-PA 5.10

1.47

Bio-PA 4.10

1.56

2.35

Bio-PA 10.10

2.38

Bio-PA 11

Bio-PA 6.10

Bio-PA 5.10

Bio-PA 4.10

Bio-PA 10.10

Bio-PA 11


3.573.703.86

5.85 5.99


Bio-PA 6.10

13 953

Bio-PA 5.10

14 547

Bio-PA 4.10

15 438

23 256

Bio-PA 10.10

23 256

Bio-PA 11

Bio-PA – Land use in ha (feedstock castor oil)


Castor oil1

0.19 t

0.46 ha

1 831 m³

Transesterification,epoxidation


MeOH, CO

H2, Catalyst

Isocyanates

0.50 t

MeOH

Glycerine

Polyaddition


Bio-PURRigid foam

1.00 t

Natural oil polyols

0.50 t

Castor oil1

0.22 t

0.56 ha

2 177 m³

MeOH, CO

H2, Catalyst

Isocyanates

0.40 t

MeOH

Glycerine

Polyaddition

Bio-PURFlexible foam

1.00 t

Natural oil polyols

0.60 t

Castor oil1

0.19 t

0.46 ha

1 831 m³



MeOH, CO

H2, Catalyst

Isocyanates

0.50 t

MeOH

Glycerine

Polyaddition


Bio-PURRigid foam

1.00 t

Natural oil polyols

0.50 t

Castor oil1

0.22 t

0.56 ha

2 177 m³

MeOH, CO

H2, Catalyst

Isocyanates

0.40 t

MeOH

Glycerine

Polyaddition

Bio-PURFlexible foam

1.00 t

Natural oil polyols

0.60 t

2.4 Polyurethanes


Bio-PUR – Feedstock requirements in t (feedstock castor oil)

0.10

0.15

0.20

0.25

0

0.05

0.2

0.3

0.4

0.5

0.6

0

0.1

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

2 000

1 000

1 500

0

500m3 /

t bio

poly

mer

Bio-PUR flexible foam

0.22

Bio-PUR rigid foam

0.19


Bio-PUR rigid foam


0.56

0.46

Bio-PUR – Land use in ha(feedstock castor oil)


2 177

Bio-PUR rigid foam

1 831

Bio-PUR – Water use in m3 (feedstock castor oil)

0.10

0.15

0.20

0.25

0

0.05

0.2

0.3

0.4

0.5

0.6

0

0.1

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

2 000

1 000

1 500

0

500m3 /

t bio

poly

mer


0.22

Bio-PUR rigid foam

0.19


Bio-PUR rigid foam


0.56

0.46



2 177

Bio-PUR rigid foam

1 831

Bio-PUR – Water use in m3 (feedstock castor oil)Bio-PUR – Water use in m3 (feedstock castor oil)

0.10

0.15

0.20

0.25

0

0.05

0.2

0.3

0.4

0.5

0.6

0

0.1

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

2 000

1 000

1 500

0

500m3 /

t bio

poly

mer


0.22

Bio-PUR rigid foam

0.19


Bio-PUR rigid foam


0.56

0.46



2 177

Bio-PUR rigid foam

1 831

Bio-PUR – Water use in m3 (feedstock castor oil)

Bio-PUR – Land use in ha (feedstock castor oil)


Wood

2.50 t

Regene-rated

cellulose1.00 t

1.52 ha

Pulping process

Alkali-cellulose

3.38 t

Solving,bulging

NaOH

2.38 t

CS2

0.14 t

H2SO4

1.15 t

Cellulose-xanthate

3.52 t

Sulfidation

Polymerization CS2, NaSO2

H2O

Cellulose

1.00 t

2.5.1 Cellulose-based polymers (Cellulosics)2.5.1.1 Regenerated cellulose

2.5 Polysaccharid polymers


Wood

1.33 t

0.82 ha

Pulping process

Acetic acid

0.37 t

Plasticizer

0.20 t

EsterificationH2O

0.11 t

Cellulose

0.53 t

Cellulosediacetate

1.00 t

Wood

1.33 t

0.82 ha

Pulping process

Acetic anhydride

0.64 t

Plasticizer

0.20 t

EsterificationAcetic acid

0.37 t

Cellulose

0.53 t

Cellulosediacetate

1.00 t

Wood

1.33 t

0.82 ha

Pulping process

Acetic acid

0.37 t

Plasticizer

0.20 t

EsterificationH2O

0.11 t

Cellulose

0.53 t

Cellulosediacetate

1.00 t

Wood

1.33 t

0.82 ha

Pulping process

Acetic anhydride

0.64 t

Plasticizer

0.20 t

EsterificationAcetic acid

0.37 t

Cellulose

0.53 t

Cellulosediacetate

1.00 t

2.5.1 Cellulose-based polymers (Cellulosics)2.5.1.2 Cellulose diacetate


Cellulosics – Feedstock requirements in t (feedstock wood)

1.0

1.5

2.0

2.5

0

0.5

0.8

1.2

1.6

2.0

0

0.4

Regeneratedcellulose

2.50

Cellulosediacetat

1.33


Cellulosediacetat


1.52

0.82

Cellulosics – Land use in ha(feedstock wood)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

1.0

1.5

2.0

2.5

0

0.5

0.8

1.2

1.6

2.0

0

0.4


2.50

Cellulosediacetat

1.33


Cellulosediacetat


1.52

0.82

Cellulosics – Land use in ha(feedstock wood)

t fee

dsto

ck/t

bio

poly

mer

ha/t

bio

poly

mer

Cellulosics – Land use in ha (feedstock wood)


Corn

1.07 t

Potato

4.17 t

Wheat

1.64 t

Starch

0.75 t

0.17 ha

1 308 m³

0.20 ha

1 198 m³

0.47 ha

2 996 m³

Starch content 75 %*

TPS*

1.00 t

Destruction(Extrusion)

Plasticizer

0.25 t

or

2.5.2 Starch-based polymers2.5.2.1 Thermoplastic starch (TPS)



TPS*

0.30 t

TPS*

0.30 t

Starch content 75 %* Ratio TPS/Polymer**

Corn

0.33 t

Potato

1.28 t

Wheat

0.50 t

Starch

0.23 t

0.05 ha

403 m³

0.06 ha

368 m³

0.14 ha

914 m³



Plasticizer

0.07 t

TPS*

0.30 t

Polymers

0.70 tExtrusion

Starch blend

30/70**30/7030/701.00 t

Corn

0.54 t

Potato

2.11 t

Wheat

0.83 t

Starch

0.38 t

0.08 ha

660 m³

0.10 ha

606 m³

0.24 ha

1 516 m³

Plasticizer

0.12 t

Polymers

0.50 tExtrusion

Starch blend

50/50**

1.00 t

Corn

0.76 t

Potato

2.95 t

Wheat

1.16 t

Starch

0.53 t

0.12 ha

929 m³

0.14 ha

847 m³

0.33 ha

2 119 m³

Plasticizer

0.17 t

Polymers

0.30 tExtrusion

Starch blend

70/30**

1.00 t

ororor


TPS*

0.30 t

TPS*

0.30 t


Corn

0.33 t

Potato

1.28 t

Wheat

0.50 t

Starch

0.23 t

0.05 ha

403 m³

0.06 ha

368 m³

0.14 ha

914 m³



Plasticizer

0.07 t

TPS*

0.30 t

Polymers

0.70 tExtrusion

Starch blend

30/70**

1.00 t

Corn

0.54 t

Potato

2.11 t

Wheat

0.83 t

Starch

0.38 t

0.08 ha

660 m³

0.10 ha

606 m³

0.24 ha

1 516 m³

Plasticizer

0.12 t

Polymers

0.50 tExtrusion

Starch blend

50/50**50/5050/501.00 t

Corn

0.76 t

Potato

2.95 t

Wheat

1.16 t

Starch

0.53 t

0.12 ha

929 m³

0.14 ha

847 m³

0.33 ha

2 119 m³

Plasticizer

0.17 t

Polymers

0.30 tExtrusion

Starch blend

70/30**

1.00 t

ororor


TPS*

0.30 t

TPS*

0.30 t


Corn

0.33 t

Potato

1.28 t

Wheat

0.50 t

Starch

0.23 t

0.05 ha

403 m³

0.06 ha

368 m³

0.14 ha

914 m³



Plasticizer

0.07 t

TPS*

0.30 t

Polymers

0.70 tExtrusion

Starch blend

30/70**

1.00 t

Corn

0.54 t

Potato

2.11 t

Wheat

0.83 t

Starch

0.38 t

0.08 ha

660 m³

0.10 ha

606 m³

0.24 ha

1 516 m³

Plasticizer

0.12 t

Polymers

0.50 tExtrusion

Starch blend

50/50**

1.00 t

Corn

0.76 t

Potato

2.95 t

Wheat

1.16 t

Starch

0.53 t

0.12 ha

929 m³

0.14 ha

847 m³

0.33 ha

2 119 m³

Plasticizer

0.17 t

Polymers

0.30 tExtrusion

Starch blend

70/30**70/3070/301.00 t

ororor

2.5.2 Starch-based polymers2.5.2.2 Starch blends


2

3

4

5

0

1t fee

dsto

ck/t

bio

poly

mer

0.2

0.3

0.4

0.5

0

0.1

ha/t

bio

poly

mer

1 000

1 500

2 000

2 500

0

500

m3 /

t bio

poly

mer

3 000

1.16

Wheat

0.33

Wheat

Wheat

2 119

Starch-based polymers – Feedstock requirements in t(different feedstocks)

Starch-based polymers – Land use in ha(different feedstocks)

1.07

Corn

0.33

Corn

Starch blend 30/70

0.54

Corn

Starch blend 50/50

0.76

Corn

Starch blend 70/30

0.17

Corn

0.05

Corn

Starch blend 30/70

0.08

Corn

Starch blend 50/50

0.12

Corn

Starch blend 70/30

Starch-based polymers – Water use in m3


1 308

Corn

1.64

Wheat

0.47

Wheat

Wheat

2 996TPS

403

Corn

Potato

1.28

Potato

0.06

368

Potato

0.50

Wheat

0.14

Wheat

Wheat

914

Starch blend 30/70

660

Corn

Potato

2.11

Potato

0.10

606

Potato

0.83

Wheat

0.24

Wheat

Wheat

1 516

Starch blend 50/50

929

Corn

Potato

2.95

Potato

0.14

847

Potato

Starch blend 70/30

TPS

TPS

Potato

4.17

Potato

0.20

1 198

Potato

Starch-based polymers – Water use in m3 (diff erent feedstocks)

Starch-based polymers – Feedstock requirements in t (diff erent feedstocks)

2

3

4

5

0

1t fee

dsto

ck/t

bio

poly

mer

0.2

0.3

0.4

0.5

0

0.1

ha/t

bio

poly

mer

1 000

1 500

2 000

2 500

0

500

m3 /

t bio

poly

mer

3 000

1.16

Wheat

0.33

Wheat

Wheat

2 119



1.07

Corn

0.33

Corn

Starch blend 30/70

0.54

Corn

Starch blend 50/50

0.76

Corn

Starch blend 70/30

0.17

Corn

0.05

Corn

Starch blend 30/70

0.08

Corn

Starch blend 50/50

0.12

Corn

Starch blend 70/30



1 308

Corn

1.64

Wheat

0.47

Wheat

Wheat

2 996TPS

403

Corn

Potato

1.28

Potato

0.06

368

Potato

0.50

Wheat

0.14

Wheat

Wheat

914

Starch blend 30/70

660

Corn

Potato

2.11

Potato

0.10

606

Potato

0.83

Wheat

0.24

Wheat

Wheat

1 516

Starch blend 50/50

929

Corn

Potato

2.95

Potato

0.14

847

Potato

Starch blend 70/30

TPS

TPS

Potato

4.17

Potato

0.20

1 198

Potato

2

3

4

5

0

1t fee

dsto

ck/t

bio

poly

mer

0.2

0.3

0.4

0.5

0

0.1

ha/t

bio

poly

mer

1 000

1 500

2 000

2 500

0

500

m3 /

t bio

poly

mer

3 000

1.16

Wheat

0.33

Wheat

Wheat

2 119



1.07

Corn

0.33

Corn

Starch blend 30/70

0.54

Corn

Starch blend 50/50

0.76

Corn

Starch blend 70/30

0.17

Corn

0.05

Corn

Starch blend 30/70

0.08

Corn

Starch blend 50/50

0.12

Corn

Starch blend 70/30



1 308

Corn

1.64

Wheat

0.47

Wheat

Wheat

2 996TPS

403

Corn

Potato

1.28

Potato

0.06

368

Potato

0.50

Wheat

0.14

Wheat

Wheat

914

Starch blend 30/70

660

Corn

Potato

2.11

Potato

0.10

606

Potato

0.83

Wheat

0.24

Wheat

Wheat

1 516

Starch blend 50/50

929

Corn

Potato

2.95

Potato

0.14

847

Potato

Starch blend 70/30

TPS

TPS

Potato

4.17

Potato

0.20

1 198

Potato

Starch-based polymers – Land use in ha (diff erent feedstocks)


As already mentioned in the introduction, the focus of attention is on “New Economy” bioplastics, including their position at the market. To give the reader an impression of the market share of these innovative and novel bioplastics:

When considering the most important Old Economy bio-plastics with their global production capacity of 17 million tonnes annually, it turns out that the share of New Economy bioplastics is almost 10 times lower, i.e. 12 % of the market volume of all bio-based plastics (including the Old Economy bioplastics), with rising tendency.

By and large, Old and New Economy bioplastics (about 18.9 million tonnes) have a combined share of presently about 6 % of the global plastics market. Given the anticipated market growth, especially of New Economy bioplastics, over a 5-year period, the market share of Old and New Economy bioplastics is expected to reach a maximum of 10 % of the global market for plastics within the next 5 years. The corresponding land use of Old and New Economy bioplastics is currently at approximately 15.7 million hectares, which is equivalent to only 0.3 % of the global agricultural area or approximately 1 % of the arable land. Comparing these figu-res reveals that New Economy bioplastics, which tend to be the only focus of interest in land use discussions, use up only 5 % of the area required for all bio-based plastics combined.

Even though global forecasts predict a rapidly growing market for these novel bioplastics in the next few years, the need for agricultural areas will be kept at a very low level. While the market for new bioplastics has been growing by around 15 % annually during the last three years and a sustained growth is anticipated in the future, it can be assumed that land use for New Economy bioplastics by 2020 (9.4 million tonnes), for example, will be as low as 0.04 % of the global agricultural area or about 0.1 % of the arable land. Regardless of the significant growth rates, it should be mentioned that the market share of these New Economy bioplastics is still hovering at less than 1 % of the global plastics market and is likely not to exceed 2-3 % in the near future. To make things even more compelling, it is a fact that bio-based plastics, even after multiple material

Market data and land use facts

3


usage, can still serve as an energy carrier. This means that additional crop lands, which are currently used for direct energy production, could be set aside for the production of bioplastics. Prior material usage of biomass, as in the case of bioplastics, still permits subsequent trouble-free energy recovery, whereas direct incineration of biomass (and also crude oil-based products!) precludes an immediate subsequent material usage. In this case, more arable land for plant cultivation is needed and consequently another photosynthesis process, in order to gain new resources once again as feedstock for material usage.

Production capacities and land use Old and New Economy bioplastics

10 978 000Natural rubber

140 000Linoleum3

2 028 000New Economy bioplastics1

5 800 000Cellulose2


56 000Linoleum3

750 000New Economy bioplastics1

2 900 000Cellulose2


140 000Linoleum3

2 028 000New Economy bioplastics1

5 800 000Cellulose2


56 000Linoleum3

750 000New Economy bioplastics1

2 900 000Cellulose2

1 PLA, PHA, PTT, PBAT, Starch blends, Drop-Ins (Bio-PE, Bio-PET, Bio-PA) and other2 Material use excl. paperindustry 3 Calculations include linseed oil only


3.1 New Economy bioplastics global production capacities

1 034

663

1 697

1 291

737

2 028

9 405

916

528

1 448 1 581

990

591

2015 202020142013

in 1

000

t

Fore

cast

8 000

9 000

10 000

7 000

6 000

5 000

4 000

3 000

2 000

1 000

0

7 691

1 714

Bio-based/non-biodegrable

Biodegrable

Total capacity


3.2 New Economy bioplastics production capacities by material type 2015

202074.41.83.21,01,37,25,43,12,10,30,1

total

2.03 milliontonnes

total

9.41 milliontonnes

10.9 %PLA

10.8 %Biodegradable

polyesters4

9.4 %Biodegradablestarch blends

3.6 %PHA

1.4 %Regenerated

cellulose2

0.2 %Cellulose

derivatives2

41.9 %Bio-PET 303

5.9 %PTT

9.9 %Bio-PE

4.8 %Bio-PA

1.2 %Others

(bio-based/non-biodegradable)

7.2 %PLA

5.4 %Biodegradable

polyesters4 3.1 %Biodegradablestarch blends

2.1 %PHA

0.3 %Regenerated

cellulose2

0.1 %Cellulose

derivatives2

74.4 %Bio-PET 303

1.8 %PTT

3.2 %Bio-PE

1.0 %Bio-PA

1.3 %Others


63.7 %

36.3 %

bio-based/non-biodegradable

biodegradable

81.8 %

18.2 %


biodegradable

74.41.83.21,01,37,25,43,12,10,30,1

total

2.03 milliontonnes

total

9.41 milliontonnes

10.9 %PLA

10.8 %Biodegradable

polyesters4

9.4 %Biodegradablestarch blends

3.6 %PHA

1.4 %Regenerated

cellulose2

0.2 %Cellulose

derivatives2

41.9 %Bio-PET 303

5.9 %PTT

9.9 %Bio-PE

4.8 %Bio-PA

1.2 %Others


7.2 %PLA

5.4 %Biodegradable

polyesters4 3.1 %Biodegradablestarch blends

2.1 %PHA

0.3 %Regenerated

cellulose2

0.1 %Cellulose

derivatives2

74.4 %Bio-PET 303

1.8 %PTT

3.2 %Bio-PE

1.0 %Bio-PA

1.3 %Others


63.7 %

36.3 %


biodegradable

81.8 %

18.2 %


biodegradable

1 Biodegradable cellulose esters2 Compostable hydrated cellulose foils 3 Bio-based content amounts 30%4 Contains PBAT, PBS, PCL

1 Biodegradable cellulose esters2 Compostable hydrated cellulose foils 3 Bio-based content amounts 30%4 Contains PBAT, PBS, PCL


3.3 New Economy bioplastics production capacities by region 2015

2020

in % total

2.03 milliontonnes

in % total

9.41 milliontonnes

10.0 %

13.0 %

0.4 %

63.1 %13.5 %

10.5 %

6.9

0.1

79.13.4 %

10.0 %South America

13.0 %Europe

13.5 %North America

63.1 %Asia

0.4 %Australia/Oceania

10.5 %South America

6.9 %Europe

3.4 %North America

79.1 %Asia


in % total

2.03 milliontonnes

in % total

9.41 milliontonnes

10.0 %

13.0 %

0.4 %

63.1 %13.5 %

10.5 %

6.9

0.1

79.13.4 %

10.0 %South America

13.0 %Europe

13.5 %North America

63.1 %Asia


10.5 %South America

6.9 %Europe

3.4 %North America

79.1 %Asia



3.4 New Economy bioplastics production capacities by market segment 2015

2020

6 000

1 000

500

0

600

400

200

0

in 1

000

t in

1 0

00 t

800

1 000

7 000

PLA & PLA blends

Starch blends

Others1biod

egra

dabl

e Bio-PET 302

Bio-PE

Others3

non-

biod

egra

dabl

ebi

o-ba

sed/

PLA & PLA blends

Starch blends

Others1biod

egra

dabl

e Bio-PET 302

Bio-PE

Others3

non-

biod

egra

dabl

ebi

o-ba

sed/

Others

8

Electricaland

electronic

18

Agriculture and

horticulture

131

Consumergoods

124

Textiles

191

Flexible packaging

399

Others

21

Textiles

635

Flexible packaging

814

Rigidpackaging

6 897

Rigidpackaging

1 013

Buildingand

construction

21

Electricaland

electronic

33

Consumergoods

258

Agriculture and

horticulture

272

Automotive and

transports

455

Automotive and

transports

124Building

and construction

21

6 000

1 000

500

0

600

400

200

0

in 1

000

t in

1 0

00 t

800

1 000

7 000

PLA & PLA blends

Starch blends

Others1biod

egra

dabl

e Bio-PET 302

Bio-PE

Others3

non-

biod

egra

dabl

ebi

o-ba

sed/

PLA & PLA blends

Starch blends

Others1biod

egra

dabl

e Bio-PET 302

Bio-PE

Others3no

n-bi

odeg

rada

ble

bio-

base

d/

Others

8

Electricaland

electronic

18

Agriculture and

horticulture

131

Consumergoods

124

Textiles

191

Flexible packaging

399

Others

21

Textiles

635

Flexible packaging

814

Rigidpackaging

6 897

Rigidpackaging

1 013

Buildingand

construction

21

Electricaland

electronic

33

Consumergoods

258

Agriculture and

horticulture

272

Automotive and

transports

455

Automotive and

transports

124Building

and construction

211 Contains regenerated cellulose and biodegradable cellulose ester2 Bio-based content amounts to 30%3 Contains durable starch blends, Bio-PC, Bio-TPE, Bio-PUR (except thermosets), Bio-PA, PTT

1 Contains regenerated cellulose and biodegradable cellulose ester2 Bio-based content amounts to 30%3 Contains durable starch blends, Bio-PC, Bio-TPE, Bio-PUR (except thermosets), Bio-PA, PTT


3.5 Land use for New Economy bioplastics 2015 and 2020

For final land use calculation only the most commonly used crop was taken into consideration. Yield data from FAO statis-tics served as a basis for calculation (global, non-weighted average over the past 10 years). To calculate land use in this bottom-up approach, the producer-specific production capa-cities of a type of bioplastics were multiplied by the output data of the corresponding process routes.

In all of the calculations no allocation was made, which means land use was fully, by 100 %, allocated to the raw materials for bioplastics and not split up between various parallel side products such as proteins or straw in wheat. So this approach leads to a rather conservative estimate.

Arable land*1.4 billion ha

= 10.4 %

Pasture 3.5 billion ha

= 26.1 %Food & Feed1.24 billion ha

= 9.25 %

Biofuels53 million ha = 0.39 %

Material use106 million ha = 0.79 %

Global land area 13.4 billion ha = 100 %

Glob

al ag

ricultural area 5 billion ha = 36.5 % Bioplastics2015: 750 000 ha = 0.0056 %2020: 1 784 000 ha = 0.0133 %

* Also includes area growing permanent crops as well as approx. 1 % fallow land. Abandoned land resulting from shifting cultivation is not included.

A large amount of additional information is also available at www.ifbb-hannover.de

© IfBB – Institute for Bioplastics and BiocompositesThis document is licensed under a Creative Commons Attribution 4.0 (CC BY ND 4.0): https://creativecommons.org/licenses/by-nd/4.0/

Hochschule Hannover | Heisterbergallee 12D-30453 Hannover | Germany

Phone: +49 511 9296-2268Fax: +49 511 9296-99 2268E-mail: [email protected]

ISSN (Print) 2363-8559ISSN (Online) 2510-3431

EDITION 3 2016

Published by IfBB – Institute for Bioplastics and Biocomposites

facts and statistics · Biopolymers, facts and statistics 2016 – 3 1 Introduction and background 4 2 Process routes 6 Glossary7 2.1 Bio-based polyesters 8 2.1.1 Polylactic acid

Documents