Life Cycle Assessment of EU Oilseed Crushing and … FEDIOL LCA report_05062013_CR statement.pdf ·...

Life Cycle Assessment of EU Oilseed Crushing and Vegetable Oil Refining

Commissioned by FEDIOL

May 2013

Authors:

Laura Schneider

Prof. Dr. Matthias Finkbeiner

Technische Universität Berlin

Chair of Sustainable Engineering

Straße des 17. Juni 135

10623 Berlin

Phone +49 30 314 79502 Fax +49 30 314 21720

E-Mail [email protected]

Internet www.see.tu-berlin.de

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Table of Contents

Table of Contents .............................................................................................................. 2

Index of Figures ................................................................................................................. 4

Index of Tables ................................................................................................................... 6

Glossary .......................................................................................................................... 7

1 Introduction ..................................................................................................... 8

1.1 Background ....................................................................................................... 8

1.2 Life cycle assessment ....................................................................................... 8

2 Definition of Goal and Scope ....................................................................... 10

2.1 Goal of the study ............................................................................................. 10

2.2 Scope of the study .......................................................................................... 11

2.2.1 System description .......................................................................................... 11 2.2.2 Functional unit ................................................................................................. 11 2.2.3 System boundary ............................................................................................ 11 2.2.4 Data collection and data sources .................................................................... 12 2.2.5 Data quality and representativeness ............................................................... 13 2.2.6 Allocation ......................................................................................................... 15 2.2.7 Cut-off criteria .................................................................................................. 15 2.2.8 Life cycle impact assessment ......................................................................... 16 2.2.9 Interpretation ................................................................................................... 17 2.2.10 Assumptions and limitations ............................................................................ 17 2.2.11 Reporting ......................................................................................................... 18

3 Results ........................................................................................................... 20

3.1 Life cycle inventory .......................................................................................... 20

3.1.1 Data and modeling .......................................................................................... 20 3.1.2 Life cycle inventory results .............................................................................. 22

3.2 Life cycle impact assessment ......................................................................... 23

3.2.1 Overview results: no-allocation scenario ......................................................... 23 3.2.2 Overview results: energy allocation ................................................................ 29

3.3 Qualitative discussion of other potential impacts ............................................ 31

3.3.1 Toxicity ............................................................................................................ 31 3.3.2 Water consumption ......................................................................................... 31

4 Interpretation ................................................................................................. 32

4.1 Contribution analysis and identification of significant parameters ................... 32

4.2 Completeness, sensitivity and consistency ..................................................... 33

4.2.1 Sensitivity analysis: allocation ......................................................................... 33 4.2.2 Sensitivity analysis: impact assessment according to ReCiPe ....................... 38 4.2.3 Sensitivity analysis: energy mix ...................................................................... 42 4.2.4 Sensitivity analysis: variation of data .............................................................. 43 4.2.5 Sensitivity analysis: acids ................................................................................ 44 4.2.6 Sensitivity analysis: dataset assessment ........................................................ 46

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4.2.7 Sensitivity analysis: wastewater treatment ...................................................... 47

4.3 Conclusions and recommendations ................................................................ 51

5 References ...................................................................................................... 52

Annex A Critical Review Statement ............................................................................... 54

Annex B Supporting Information .................................................................................... 56

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Index of Figures

Figure 2-1: System overview: crushing and refining ........................................................ 12

Figure 2-2: Multifunctional system - crushing .................................................................. 15

Figure 3-1: Relative LCIA results for the selected five environmental impact categories per tonne of refined oil ................................................................ 24

Figure 3-2: Relative LCIA results related to oilseed crushing ......................................... 24

Figure 3-3: Relative LCIA results related to vegetable oil refining ................................... 25

Figure 3-4: Impact assessment results: absolute contributions of each processing step and corresponding inputs to the GWP .................................................. 26

Figure 3-5: Impact assessment results: absolute contributions of each processing step and corresponding inputs to the AP ...................................................... 26

Figure 3-6: Impact assessment results: absolute contributions of each processing step and corresponding inputs to the EP ...................................................... 27

Figure 3-7: Impact assessment results: absolute contributions of each processing step and corresponding inputs to the POCP................................................. 27

Figure 3-8: Impact assessment results: absolute contributions of each processing step and corresponding inputs to the ODP ................................................... 28

Figure 3-9: Normalization to EU 25 ................................................................................. 28

Figure 3-10: Overview energy allocation: environmental burden of one tonne of refined oil ...................................................................................................... 30

Figure 3-11: Overview energy allocation ........................................................................... 30

Figure 4-1: Overview mass allocation ............................................................................. 35

Figure 4-2: Overview economic allocation ....................................................................... 36

Figure 4-3: Overview price development 1997-2011 ........................................................ 36

Figure 4-4: Overview allocation methods: oilseed crushing – percentage share of environmental burdens allocated to crude soybean and rape seed oil for each method ............................................................................................ 37

Figure 4-5: Overview allocation methods: crude oil refining – percentage share of environmental burdens allocated to refined soybean, rape seed and palm oil for each method .............................................................................. 38

Figure 4-6: Potential impacts of GHG emissions according to CML and ReCiPe ............ 39

Figure 4-7: EP: Relative share of environmental impacts according to CML and ReCiPe ......................................................................................................... 40

Figure 4-8: AP according to CML and ReCiPe ................................................................ 41

Figure 4-9: ODP according to CML and ReCiPe ............................................................... 41

Figure 4-10: POCP: Relative share of environmental impacts according to CML and ReCiPe ......................................................................................................... 42

Figure 4-11: Comparison of different energy mixes on the example of soybean crushing. GWP (left) and AP (right) ....................................................... 43

Figure 4-12: Data variations - effects on GWP .................................................................. 44

Figure 4-13: Impact assessment results: comparison of acids and databases ................. 45

Figure 4-14: Sulfuric acid datasets: relative impacts on LCIA results ................................ 46

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Figure 4-15: Relative impacts of the inclusion of talcum on LCIA resultsfor soybean crushing ........................................................................................................ 47

Figure 4-16: Wastewater treatment: LCIA results for soybean crushing and refining (no-allocation) ............................................................................................... 49

Figure 4-17: Wastewater treatment: LCIA results allocated to one tonne of refined soybean oil .................................................................................................... 49

Figure 4-18: Wastewater treatment: LCIA results for rape seed crushing and refining (no-allocation) ............................................................................................... 50

Figure 4-19: Wastewater treatment: LCIA results allocated to one tonne of refined rape seed oil ................................................................................................. 50

Figure B-1: Data variations - effects on POCP ................................................................ 58

Figure B-2: Data variations - effects on AP ..................................................................... 58

Figure B-3: Data variations - effects on EP ..................................................................... 59

Figure B-4: Data variations - effects on ODP .................................................................. 59

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Index of Tables

Table 2-1: Requirements on data quality (ISO 14044) ...................................................... 14

Table 2-2: LCIA categories and indicators ......................................................................... 16

Table 3-1: Inventory rape seed (crushing and refining) ..................................................... 20

Table 3-2: Inventory soybean (crushing and refining) ....................................................... 20

Table 3-3: Inventory palm oil refining ................................................................................. 21

Table 3-4: Average values and standard deviations .......................................................... 22

Table 3-5: LCI results ........................................................................................................ 22

Table 3-6: Overview energy content .................................................................................. 29

Table 3-7: Percentage of environmental burden allocated to oil ....................................... 29

Table 4-1: Contribution analysis: overview of relevant in- and outputs ............................. 32

Table 4-2: Overview mass of products .............................................................................. 34

Table 4-3: Overview of product prices ............................................................................... 35

Table 4-4: EP according to CML and ReCiPe ................................................................... 39

Table 4-5: POCP according to CML and ReCiPe .............................................................. 42

Table 4-6: Overview LCI data for acids ............................................................................. 44

Table B-1: Supplementary information Figure 3-2 ............................................................. 56


Table B-3: Supplementary information Figure 3-11 ........................................................... 57



Table B-6: LCIA results for one tonne of refined soybean oil ............................................ 57

Table B-7: LCIA results for one tonne of refined rape seed oil .......................................... 57

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Glossary

AP Acidification potential

CML Institute of Environmental Sciences of Leiden University (Dutch: Centre for Milieuwetenschappen Leiden)

CC Climate change (global warming potential according to ReCiPe)

CO2 Carbon dioxide

EP Eutrophication potential

EPD Environmental product declaration

Equiv. Equivalent

GaBi 5 GaBi 5 is a database and software for life cycle assessment provided by PE International. GaBi stands for ”holistic balance“ (German: Ganzheitliche Bilanzierung)

GHG Greenhouse gas

GWP Global warming potential

H2S Hydrogen sulfide

ISO International Organization for Standardization

kg Kilogram

kWh Kilowatt hour

LCA Life cycle assessment

LCI Life cycle inventory

LCIA Life cycle impact assessment

LHV Lower heating value

MJ Mega joule

ODP Ozone depletion potential

PCR Product category rules

POCP Photochemical ozone creation potential

ReCiPe Methodology for life cycle impact assessment created by RIVM (National Institute for Public Health and the Environment), PRé Consultants, CML and RUN (Radboud Universiteit Nijmegen)

SD Standard deviation

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1 Introduction

FEDIOL represents the European Vegetable Oil and Proteinmeal Industry. FEDIOL members purchase, store and transport oilseeds and vegetable oils, process oilseeds into meals and crude oils, refine and transform crude vegetable oils and sell oils in bulk and in bottles to the food, feed and energy markets and meals to the feed market.

FEDIOL commissioned TU Berlin to conduct a life cycle assessment (LCA) of oilseed crushing and vegetable oil refining. The objectives of this study are the establishment of a valid database, relating to primary data from the industry, and the assessment of potential environmental impacts of oilseed crushing and vegetable oil refining, focusing on rape seed oil, soybean oil and palm oil.

1.1 Background

Environmental impacts of vegetable oil production are widely discussed. A broad range of literature is available on this topic. However, so far most discussion focuses on the cultivation of plants intended for vegetable oil production. Literature data on oilseed crushing and vegetable oil refining are inconsistent and uncertainties exist due to limited availability of primary data. Hence, there is need for representative, consistent and up-to-date high quality primary data on the environmental performance of the oilseed crushing and vegetable oil refining industry.

The study focuses on the environmental assessment of crushing of soybeans and rape seeds as well as refining of soybean oil, rape seed oil and palm oil. Results of the study provide member companies with the “best available” information basis for further environmental management decisions and allow the comparison of potential environmental impact of their activities to average data sets and impacts. Additionally, results of this study can be used for communication on potential environmental impacts of the crushing and refining industry, and for defining the contribution of these impacts compared to upstream and downstream activities in the supply chain of oilseed crushing and oil refining.

1.2 Life cycle assessment (LCA)

LCA addresses the environmental aspects and potential environmental impacts throughout a product’s life cycle, typically from raw material extraction, through production, use, recycling and final disposal (cradle-to-grave). In this study, in correspondence with the core activities of the FEDIOL member companies, a gate-to-gate approach is followed (raw materials entering the gate and products leaving the gate), focusing only on the processing activities and excluding upstream (agricultural step) and downstream (use of oil) processes.

In accordance with the ISO standards of LCA (ISO 14040: 2006 and ISO 14044: 2006), the following structure is used for this report. In Chapter 1 the motivation and background to this study is provided. Chapter 2 describes goal and scope of the study. Here the rationale for the study and the anticipated use of the results are outlined, and information on system boundaries, data requirements and assumptions made to analyze the product system under consideration are provided.

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Chapter 3 presents the life cycle inventory (LCI) and lists the results of the life cycle impact assessment (LCIA). Chapter 4 includes a summary of relevant parameters, a sensitivity analysis, a short conclusion and recommendations.

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2 Definition of Goal and Scope

This chapter describes all aspects of the goal and scope of the study in accordance with the ISO standard (ISO 14040: 2006 and ISO 14044: 2006).

2.1 Goal of the study

Goal of this study is the generation of consistent and up-to-date high quality inventory data on the gate-to-gate LCA of oilseed crushing and vegetable oil refining representative for the European situation and to evaluate potential environmental impacts associated with these activities.

Main targets of this work are

- the environmental impact assessment based on accurate and up-to-date industry LCI data reflecting current technologies and operation of the European Vegetable Oil and Proteinmeal industry

- the identification of potential environmental impacts of oilseed crushing and vegetable oil refining

- the identification of process steps and materials which have a high contribution to the overall potential environmental impacts

- a detailed assessment of potential environmental impacts of soybean oil, rape seed oil and palm oil

- the provision of “up-to date average European data on crushing and refining” (for further assessment of potential environmental impact of oilseed crushing and vegetable oil refining in the entire supply chain).

The potential environmental impacts are evaluated using commonly applied impact categories, such as global warming potential (GWP).

The study complies with the requirements of the ISO standards for LCA (ISO 14040: 2006 and ISO 14044: 2006). A critical review by Hans Blonk has been engaged for quality control with regard to compliance with the ISO standard and to assure the robustness and credibility of the results. The critical review will be included in Annex A of this report.

This study is not intended to be used for carrying out comparative assessment to other processes or materials.

Further intended applications of the results regard the knowledge generated by the LCA. This includes the use as:

- an internal information source for determining and understanding the potential environmental impacts of crushing and refining

- a means to understand the relative share of the potential environmental impacts of crushing and refining in the entire supply chain

- a basis for the future development of a type III environmental product declaration (EPD)

The main audience for the results will be crushing and refining companies and food and feed industry in general.

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2.2 Scope of the study

This section details information, which is necessary to understand the modeled system and to allow for the correct interpretation of results.

2.2.1 System description

The life-cycle under study is the production of vegetable oil by member companies of FEDIOL and can be separated into two different life cycle stages: crushing and refining. A detailed overview of the processes and corresponding system boundaries is given in Figure 2-1.

2.2.1.1 Process description of vegetable oil production

The European production of vegetable oil encompasses crushing of oilseeds and refining of crude vegetable oil produced during the crushing process. Crushing covers solvent based extraction (including directly related preparatory steps) of crude vegetable oil from soybeans or rape seeds. Refining involves further processing of extracted crude oil to produce refined vegetable oil with the desired specifications regarding taste, stability and appearance. In this work, the focus is on the two most commonly used refining methods: chemical refining for soybean and rape seed oil and physical refining for palm oil. The system includes production of electricity and steam used and production and usage of auxiliary materials.

2.2.1.2 Model description of vegetable oil production

Crushing and refining have been modeled using a modular approach, allowing a separate analysis. The assessment is carried out using a model developed in GaBi 5; a publicly available and internationally used LCA software (GaBi 2012). The model is set up based on averaging data provided by the six participating FEDIOL member companies.

2.2.2 Functional unit

The functional unit quantifies the function of a system and is used as a reference unit throughout the assessment. During crushing and refining several products are produced. However, as the principle aim of the process is the production of vegetable oil, the functional unit chosen is one tonne of refined vegetable oil (a commonly used reference unit in the trade of oils). Inputs, outputs and results of the impact assessment are related to the defined functional unit.

A detailed assessment of the function and use of vegetable oil is not necessary, as outputs and not products are considered. Thus, functional unit and reference flow are the same for this study (this is always the case when the focus is on the output of a system and no comparison based on the functional differences is taking place).

2.2.3 System boundary

The system boundary for the assessment comprises following modules:

- oilseed crushing (for soybeans and rape seeds) and

- crude oil refining (for crude soy, rape seed and palm oil).

Figure 2-1 illustrates the production system boundary for soybean and rape seed oil production. The system boundary reflects the core activities of FEDIOL member

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companies. Only processes and materials relevant to the systems “Crushing” and “Refining” are considered. Upstream and downstream activities regarding production (agriculture), transport and storage of rape seeds and soybeans, or use and distribution of oil or by-products are not considered within this LCA.

Figure 2-1: System overview: crushing and refining

Life cycle impacts of production equipment and infrastructure are not included in the system as no evidence could be justified that these affect the results of assessing the potential environmental impacts of one tonne of refined oil.

Site-specific energy production is excluded from the system. Instead, for consistency, an oilseed processing specific energy mix is calculated based on available European statistics for oilseed crushing and vegetable oil refining (FEDIOL 2013). Waste, wastewater, associated emissions and treatment are not considered within this study, as processes are site-specific and no average process could be defined based on the available data. However, a sensitivity analysis is conducted to determine the potential influence of wastewater treatment on overall results.

2.2.4 Data collection and data sources

For this study, primary data from FEDIOL member companies (with best possible accuracy) are collected regarding all relevant processes. The data relate to crushing of oilseeds (soybeans, rape seed) and refining of crude oil (soybean, rape seed, and palm) at production facilities located in Europe. In total, 85% of the oilseed crushing and oil refining capacity in Europe is covered by FEDIOL members. The data obtained from FEDIOL members are aggregated based on information from more than twenty sites and six different countries, covering between 85 and 90% of all FEDIOL activities. Thus, as participating companies constitute a high share of overall European activity, the sample can be seen as representative for Europe.

The provided data are then weighted by the member’s annual production tonnage and an average value across all companies is calculated. The data can be seen as representative for the crushing and refining activities in Europe (see Table 2-1).

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The following companies provided data for this study:

- Archer Daniels Midland (ADM)

- Thywissen

- Cargill

- Bunge

- Wilmar

- IOI Loders Croklaan

Additionally to the primary data following data are needed:

- data regarding the production of auxiliary material and

- data regarding the production of energy and electricity.

All relevant background data related to energy and auxiliary materials are taken from the GaBi 5 professional database provided by PE International and the ecoinvent database (both available within the GaBi 5 software tool). Data quality is as precise as possible and most up-to date data are used. The background database of GaBi 5 was initially set-up in 1991 and has since then been frequently updated and expanded. Thorough quality assurance is provided to ensure that data are up to date. The data sets have been extensively used in LCA-models in industrial and scientific applications worldwide for several years. The ecoinvent datasets are based on industrial data and have been compiled by internationally renowned research institutes and LCA consultants. Comprehensive documentation in form of several reports is available.

Most of the background data used are publicly available and well documented (GaBi 2011, ecoinvent Center 2011).

When needed, process data are approximated with available (and similar) processes within the databases.

2.2.5 Data quality and representativeness

The study is based on primary data provided by FEDIOL member companies and data from the databases available in GaBi 5. The collected data was subject to quality and plausibility checks by means of data comparison and bilateral discussion with the companies providing the data.

Requirements on data quality and representativeness are based on the ISO 14044 guidelines and are listed in Table 2-1.

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Table 2-1: Requirements on data quality (ISO 14044 2006)

Parameter Requirements and implementation

Temporal coverage Data used shall be as new as possible.

Sites are normally operated at maximum capacity and no significant temporal variations exist. Primary data refer mainly to the year 2010. The chosen year is identified as a representative year. In some cases data from other years are also considered if data availability or quality of the base year are insufficient (temporal proximity is provided).

Secondary/background data available in the GaBi 5 professional database are also valid for this time period. LCI data taken from the ecoinvent database might be outdated and are only used when no other data are available.

Geographical coverage

Preferably data representing the average European situation shall be used.

Data for auxiliary materials shall relate to average European datasets. If no European data are available, global or national (only European countries) process data shall be used.

Average European data are used regarding provision of process steam and power grid mix. The average mixes are calculated based on crushing and refining activities in Europe (site-specific energy production is not considered). Based on available statistics (FEDIOL 2013), the energy mix in the countries is weighted pro rata the mass of oilseeds crushed and mass of oil refined in the respective country. Separate energy mixes were calculated for rape seed and soybean crushing and for rape, soy and palm oil refining, representing the actual situation of the European oilseed processing.

LCI-results are specific for the geographical boundaries of the European Union and should be adapted if transferred outside of these boundaries.

Technological coverage

Average technology within Europe is assessed (state of technology at individual production sites might differ from the European average).

Precision Relevant foreground data of the gate-to-gate system are primary data. Background/upstream data included are based on LCI data within GaBi 5 and ecoinvent, with the documented precision.

Assumptions regarding the data will be assessed within a sensitivity analysis.

Completeness All relevant processes shall be considered.

Data shall be checked with the operators of the crushing and refining facilities for completeness.

Representativeness Data shall comply with the temporal, geographical and technological frame.

The study is representative for European oilseed crushing and vegetable oil refining.

Consistency Only primary data of the same level of detail shall be used. Data consistency is checked during site visits and bilateral discussion.

Upstream data are mainly based on the GaBi 5 professional database and only if no other data are available ecoinvent datasets are used.

Reproducibility Available information on data and method enable reproducibility since the models are available in the GaBi 5 software.

Reproduction is permitted for internal use only.

Data sources Data shall be based on reliable sources and databases. In this work primary data are provided directly by FEDIOL member companies, and secondary data is retrieved from established databases.

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2.2.6 Allocation

The ISO standard 14040 (2006) defines allocation as the partitioning of economic and environmental inputs and/or outputs of a process to the product system under study. An allocation problem arises within the analysis due to a multifunctional process (a process that fulfills more than one function). Multifunctionality occurs, for example, if more than one product is produced (Ekvall and Finnveden 2001). According to ISO allocation should be avoided by subdivision of processes or system expansion. If allocation cannot be avoided, physical allocation methods (e.g. based on mass or energy content) are preferred to other, e.g. economic allocation methods (ISO 14040/44 2006).

Figure 2-2: Multifunctional system - crushing

One goal of this work is to identify all potential environmental impacts of oilseed crushing and vegetable oil refining for future communication and positioning within the supply chain. Thus, in a first step focus is on the entire processing activities and no allocation is applied to crushing and refining (section 3.2.1). In a next step, to determine the environmental burden of the functional unit of one tonne of refined oil, the environmental burden of crushing and refining is allocated to the oil and multiple by-products (section 3.2.2). Soybean and rape seed crushing result in the production of crude oil, meal/cake and, in case of soybean crushing, lecithin (see Figure 2-2) (for the case of soybean crushing also soybean hulls are produced which are fed back to the meal and are thus not considered separately). By-products of the oil-refining process are soap stock (chemical refining of rape and soy oil) or fatty acid distillates (physical refining of palm oil). Allocation of environmental burdens cannot be avoided for the processes considered. Following the prioritization of ISO and to align with allocations methods that have already been laid down in EU legislation (EU 2009), FEDIOL has decided, for the time being, to opt for energy allocation. The effects of other allocation methods on the results obtained are analyzed within a sensitivity analysis.

Information on allocation performed in the background system can be found in the database documentation (GaBi 5 2012).

2.2.7 Cut-off criteria

All relevant inputs and outputs of the foreground system (primary data collection) are considered according to best knowledge. Waste management and wastewater treatment are not considered within this assessment. The amount of waste is relatively small (<2% of total output with regard to one tonne of refined oil) and is assumed to be irrelevant for

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the results. Wastewater and associated emissions can have an effect on the results, depending on the particular treatment. A wide variety of treatment processes is utilized by FEDIOL member companies and no representative European average process could be identified. Data availability and quality are too low for modeling the composition and emissions of an average wastewater treatment process. Thus, the potential impact of wastewater treatment is not considered within the main study. The emissions of phosphate with wastewater are not considered as these are not released into the environment but removed within the wastewater treatment process. Only water with an uncritical level of phosphate is released to the environment. As wastewater treatment is outside of the system boundary, no detailed analysis regarding the phosphate load and the removal is conducted. To assess the potential impacts of wastewater treatment on the results, a sensitivity analysis is carried out (see section 4.2.6) using a generic process available in GaBi5.

Furthermore, production equipment and infrastructure are not considered (see section 2.2.3). Also excluded from the assessment is packaging. Consumer packaging is not significant according to the system boundaries (factory gate). Raw materials and products are transported in ships and trucks (in reusable containers) having no relevance for impact assessment. With regard to the background system, cut-off criteria as included within GaBi 5 professional or ecoinvent are applied (documentation within databases).

2.2.8 Life cycle impact assessment

The impact assessment aims at analyzing the environmental loads quantified in the inventory analysis with regard to their potential environmental impacts. The LCIA is carried out by structuring and characterizing the inventory data into selected mid-point impact categories. The impact assessment is based on the internationally accepted methods and data of the Institute of Environmental Sciences in Leiden (CML) (CML 2010). In Table 2-2 an overview over the selected mid-point impact assessment methods is provided. The selection is based on the applicability and expected relevance of the impact categories.

Table 2-2: LCIA categories and indicators Impact category Description Unit Reference

CML Global Warming Potential (GWP)

A measure of greenhouse gas (GHG)emissions such as CO2 and methane

kg CO2-equiv.

IPCC, 2006, 100 year GWP is used

CML Eutrophication Potential (EP)

A measure of emissions that cause eutrophication in the environment

kg Phosphate- equiv.

Guinée et al., 2001 factors updated in 2010

CML Acidification Potential (AP)

A measure of emissions with acidifying effects on the environment

kg SO2-equiv.


CML Photochemical Ozone Creation Potential (POCP)

A measure of emissions that contribute to low level smog (summer smog)

kg Ethene- equiv.


CML Ozone Depletion Potential (ODP)

A measure of emissions that cause thinning of the stratospheric ozone layer

kg R-11-equiv.


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In principle, no impact methodology is excluded and any methodology can be applied on basis of the LCI. The selection of impact categories is a trade-off between relevance and level of detail and can be extended in future studies if necessary. A normalization to EU-25 is performed for the assessed CML-impact categories. In this study no weighting or grouping of the results is conducted due to the subjective nature of these impact categories.

2.2.9 Interpretation

The life cycle interpretation (according to ISO 14040/44) of the study comprises several elements:

- An identification of the significant aspects (processes steps, emissions, methodological choices like allocation procedures etc.) based on the results of the LCI and LCIA phases of LCA;

- an evaluation that considers completeness, sensitivity and consistency checks; and

- conclusions, limitations, and recommendations.

2.2.10 Assumptions and limitations

2.2.10.1 Potential limitations related to system boundary

The system boundary (section 2.2) may have some limitations on the applicability of the

study, its results and interpretation. This study is only valid for the conditions stated in the

sections above.

2.2.10.2 Potential limitations related to impact indicator choice

Potentially relevant environmental issues are not considered by the selected impact categories due to the lack of mature and consistent methodologies or data. Additional categories could be included into the assessment as new and reliable methodologies become available.

2.2.10.3 Assumption and potential limitations related to data

Based on data availability and given the goal of the study (to reflect the average European situation), assumptions and approximations have to be made.

All auxiliary materials and the power generation are modeled based on the available data in the GaBi 5 databases. The model mainly relies on data from the GaBi 5 professional database, provided by PE International. Only if no other data are available process data from the ecoinvent database are used. In the following, further assumptions and limitations are listed:

- Concentration of the acids used in refining is adjusted to the available concentrations in GaBi 5 (professional database and ecoinvent database) Availability of process data within GaBi 5 limits the assessment. Differences in production processes of these different concentrations (if any) are thus not considered.

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- Bleaching earth is approximated with the process “clay powder” from the GaBi 5 database, as not enough data are available to create a specific process. Bleaching earth and clay powder can both be used as adsorbents and have a similar composition (clay minerals consisting mostly of montmorillonite). Best available data within GaBi 5 database are used. Clay has to be treated further for use in vegetable oil production and thus used data provide only an approximation and are addressed again within the sensitivity analysis.

- Talcum can be added to the meal as a free flowing agent. Talcum is, however, not considered in this assessment as it is not used by all FEDIOL member companies. As the aim of this study is to assess the average European situation, use of talcum is neglected in the main impact assessment, but considered within a sensitivity analysis.

- LCI data of phosphoric acid are taken from the ecoinvent database as no data are available in the GaBi 5 professional database. Using data from different sources may lead to inconsistent results and increase uncertainty. Thus, acids are assessed closer within the sensitivity analysis.

- Electricity generation and steam production are calculated based on European statistics and national LCI data available in GaBi 5. Site specific energy production is not considered based on the scope of this study. In reality, at several sites electricity and steam are cogenerated, using natural gas as well as energy feedstock such as biomass, biogas, etc. An individual analysis would be needed to assess site-specific impacts.

- Wastewater treatment and potential wastewater emissions are not assessed specifically in this work. Data regarding wastewater treatment are site-specific and no data regarding an average process could be identified (see section 2.2.8). Thus, wastewater treatment is neglected in the main impact assessment, but considered within a sensitivity analysis using generic process data.

- The use of dedicated emissions control systems at sites has not been taken into account. The effect of these systems on hydrogen sulfide (H2S) emissions is not assessed in this work, as situations differ at sites and an exact quantification is difficult. Values at sites can be well below those used in this study. The hexane emission figures refer to the assumption that all hexane consumed during crushing is emitted on-site. In reality, on-site emissions will be lower as some hexane consumed will be emitted when meal and/or oil with some residual hexane is processed downstream.

2.2.10.4 Potential limitations related to allocation

Different allocation methods are included in this study. Results show that depending on the allocation method the shares of environmental impacts assigned to the oil differ (see section 3.2.1, 3.2.2 and section 4.2.1).

2.2.11 Reporting

The technical report is intended mainly for internal use on an expert level and will be the basis for a critical review.

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Results of this study will be provided to FEDIOL member companies and they may use information of this report for further studies and communication purposes. If applicable, extracts and results of the report will be edited in accordance to target groups’ requirements and published.

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3 Results

3.1 Life cycle inventory

This section describes the results of the LCI. All results refer to one tonne of refined oil produced in Europe.

3.1.1 Data and modeling

The mean values regarding the inputs to the crushing and refining step are based on the primary data provided by the participating companies and are shown in Table 3-1 to Table 3-3. The life cycle phases crushing and refining are modeled separately.

Table 3-1: Inventory rape seed (crushing and refining)

Input crushing Input refining

Seeds 2420 kg Crude oil 1032 kg

Water 600 kg Water 500 kg

Steam 590 kg Bleaching earth 4.0 kg

Electricity 100 kWh Phosphoric acid (85%) 0.7 kg

Hexane 1.5 kg Sulfuric acid (96%) 2.0 kg

Output crushing Nitrogen gas 0.5 kg

Crude oil 1000 kg Activated carbon 0.2 kg

Meal 1390 kg Sodium hydroxide (100%) 3.0 kg

Hexane emissions (losses) 1.5 kg Steam 170 kg

H2S emissions 0.15 kg Electricity 27 kWh

Output refining

Refined oil 1000 kg

Soap stock 20 kg

Table 3-2: Inventory soybean (crushing and refining)

Input crushing Input refining

Beans 5200 kg Crude oil 1038 kg

Water 1300 kg Water 540 kg

Steam 1300 kg Bleaching earth 5.4 kg

Electricity 150 kWh Phosphoric acid (85%) 1.0 kg

Hexane 3.0 kg Sulfuric acid (96%) 2.0 kg

Mineral oil 0.1 kg Activated carbon 0.2 kg

Output crushing Sodium hydroxide (100%) 2.8 kg

Crude oil 1000 kg Steam 225 kg

Meal 4080 kg Electricity 40 kWh

Lecithin 20 kg Output refining

Hexane emissions (losses) 3.0 kg Refined oil 1000 kg

H2S emissions 0.02 kg Soap stock 23 kg

The difference between amount of input (seeds/beans) and amount of outputs in the crushing process is partly caused by impurities (e.g. sticks and stones) in the seed/beans as delivered ‘at the gate’. These impurities are removed during a pre-cleaning step and

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are considered as waste. Furthermore, part of the deviation can also be explained by a difference in the moisture content of inputs and outputs.

Table 3-3: Inventory palm oil refining

Input

Crude oil 1080 kg

Water 130 kg

Bleaching earth 12 kg

Phosphoric acid (85%) 0.85 kg

Nitrogen 1.5 kg

Steam 115 kg

Electricity 29 kWh

Output

Refined oil 1000 kg

Fatty acid distillates 70 kg

With regard to hexane, it is assumed that all hexane consumed during crushing is emitted on-site. This assumption constitutes an overestimation as, in reality, some emissions will occur off-site e.g. during further processing of meal or crude oil at facilities downstream in the supply chain. The consumption values (kg hexane per tonne of rape seed/soybean) are below the values set by the Solvents Emission Directive 1999/13/EC (1999) for extraction and vegetable oil refining. The H2S emissions are based on average H2S loads (kg/tonne oil) but do not consider any emission treatment (to avoid an underestimation of environmental burdens). They will be lower at processing plants with air treatment units in place in order to comply with legal specifications and /or odor reduction programs.

Naturally, data obtained from participating companies show a spread. Data verification and validation at site indicated that the observed spread is mostly due to site specific processes, the age of components, etc., which is not considered in detail within this study. As the focus of this work is to assess the environmental performance of the European Vegetable Oil and Proteinmeal Industry, mean-values are considered in this assessment. In Table 3-4 the standard deviation of different parameters () is presented to show how much variation exists from the average. Each standard deviation is calculated based on the average data provided by three member companies. The average data of each company represent several sites.

Crushing comprises similar processes for all FEDIOL member companies, whereas refining is characterized by more specific process steps (e.g. differences in deodorization caused by specific quality and state of the crude oil). Thus, the standard deviation is comparably higher regarding data provided for refining. The impact of this data variation (see Table 3-4) is assessed further in the sensitivity analysis.

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Table 3-4: Average values and standard deviations

Rape seed Soybean Palm oil

Average (3)1 Average (3) Average (3)

Crushing

Seeds/Beans (kg) 2420 103,0 5200 96,3

Steam (kg) 590 48.0 1300 115.7

Electricity (kWh) 100 23.4 150 31.5

Hexane (kg) 1.5 0.2 3.0 0.5

Meal (kg) 1390 90.6 4080 111.1

Refining

Bleaching earths (kg) 4,0 0.2 5.4 2.9 12 2.2

Acids2 (kg) 2.7 1.1 3.0 2.5 0.85 0.5

Sodium hydroxide (caustic soda) (kg)

3.0 1.5 2.8 0.1

Steam (kg) 170 55.1 225 40.1 115 59.0

Electricity (kWh) 27 11.5 40 10.1 29 11.9 1number of values used to build standard deviation 2sum of all acids

The background data for energy supply and auxiliary materials are taken from the databases available in the GaBi 5 software. Hereby, preferably European data are used. If none are available, global or national data are chosen. Always the most up-to-date datasets are used.

Based on the primary and secondary data sources describe above the LCI is calculated as quantification of all relevant energy and material flows from and to the environment (material withdrawal from the environment and emissions into air, soil, water). The LCI results are briefly summarized in the following section and are then used for further analysis in the LCIA.

3.1.2 Life cycle inventory results

In this section, exemplary results of the LCI are presented for comparison of soybean and rape seed crushing and crude soy, rape seed and palm oil refining (Table 3-5). Results refer to one tonne of refined oil in each case.

Table 3-5: LCI results

Rape seed crushing

Soybean crushing

Rape seed oil refining

Soybean oil refining

Palm oil refining

CO2 (kg) 175 346 56 73 44 CH4 (kg) 0.41 1,00 0.13 0.20 0.08

SO2 (kg) 0.22 0.25 0.10 0.10 0.06

NOx (kg) 0.20 0.33 0.07 0.08 0.05

In the LCI results, the soybean crushing process shows the highest values for all elementary flows. The difference is significant regarding all emissions. Furthermore, inventory results for the crushing phase are considerably higher than for the refining phase.

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3.2 Life cycle impact assessment

In this section, an overview of potential environmental impacts of oilseed crushing and vegetable oil refining is given, based on the five impact categories described in section 2.2.8. Results are neither grouped nor weighted. As one objective of this work is to provide the basis for an assessment of the relative share of the potential environmental impacts of crushing and refining in the entire supply chain, a result including all potential environmental burdens is desirable. Thus, in the first part, the total environmental burdens of crushing and refining are shown. Methodologically this can be achieved by either allocating all environmental burdens to the oil or by expanding the functional unit to all by-products (and avoiding allocation). In this LCIA, the former scenario is applied and is referred to as a “no-allocation scenario”, assessing all potential environmental impacts of crushing and refining during production of one tonne of refined oil (section 3.2.1). In the second part, potential environmental impacts are allocated to the functional unit of one tonne of refined oil performing energy allocation (section 3.2.2).

3.2.1 Overview results: no-allocation scenario

All potential environmental impacts of crushing and refining are considered regarding the production of one tonne of refined oil. No allocation of environmental burdens to by-products is performed. In Figure 3-1, relative LCIA results of the average FEDIOL processing steps in Europe (per tonne of refined vegetable oil) are presented. The relative shares of the potential environmental impacts for each impact category are broken down per processing step and per type of oil.

Across all impact categories considered, the potential environmental impacts of crushing dominate the results.

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Figure 3-1: Relative LCIA results for the selected five environmental impact categories

The relative contribution of the individual inputs and emissions for crushing and refining are displayed in Figure 3-2 and Figure 3-3 (more detailed information with regard to the share of individual inputs can be found in the Annex B).

Figure 3-2: Relative LCIA results related to oilseed crushing

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Figure 3-3: Relative LCIA results related to vegetable oil refining

The potential environmental impacts associated with process steam and electricity production have a high share of the overall burden for both, crushing and refining. In the crushing process, emissions of hexane contribute significantly to the photochemical ozone creation potential and emissions of H2S contribute to the AP. Furthermore, production of acids has a relatively high contribution to several impact categories. Crude palm oil has a more intensive coloring than crude rape seed or soybean oil, thus more bleaching earth is needed in the refining process, leading to higher impacts (see Figure 3-3).

The absolute contributions of individual inputs and emissions to the different impact category results are presented in the following sections (per processing step and type of oil).

3.2.1.1 Global warming potential (GWP)

The GWP is of high relevance for all assessed process steps and is mainly caused by the emission of carbon dioxide CO2 (>90%) and methane CH4 (6%-7%). The main sources for these emissions are the production of process steam from natural gas and the production of electricity (power grid mix). Crushing is more energy intensive and thus has a higher global warming potential than refining (see Figure 3-4). Soybean crushing has a higher GWP than rape seed crushing. This is related to the lower oil content of soybeans, requiring more raw materials (beans) to be processed to produce one tonne of oil.

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Figure 3-4: Impact assessment results: absolute contributions of each processing step and

corresponding inputs to the GWP

3.2.1.2 Acidification potential (AP)

The AP is dominated by emissions of sulfur dioxide (SO2) (42%-75%). The processes with the highest contribution to the AP are electricity and process steam production (relative significance varies for different oilseeds). Electricity production is associated with high emission of SO2 from the burning of fossil fuels (especially coal). Emissions of H2S also contribute to the AP impact category. The H2S emitted during rape seed crushing contributes with 40% to the AP (see Figure 3-5).


corresponding inputs to the AP

3.2.1.3 Eutrophication potential (EP)

The principal contributors to the EP of the crushing process are electricity and process steam production. Regarding refining, production of acids (mainly phosphoric acid) is a significant contributor to this impact category. (Figure 3-6). The relevant emissions contributing to eutrophication are nitrogen oxides (NOx) for crushing (~90%), and NOx (26%-37%) and phosphate (41 -50%) for refining.

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corresponding inputs to the EP

3.2.1.4 Photochemical ozone creation potential (POCP)

The emissions of hexane during crushing dominate the impact category result (>95%) (Figure 3-7). In this study, a conservative approach is adopted by assuming that all hexane consumed during crushing is emitted on-site.


corresponding inputs to the POCP

3.2.1.5 Ozone layer depletion potential (ODP)

Emissions of chlorofluorocarbons (CFCs) such as e.g. R11 or R114 (e.g. used as flame retardants on off-shore oil platforms) in the background systems of the electricity production have a significant contribution to the ODP (Figure 3-8). The applied power grid mixes for rape, soy and palm determine the potential impacts. The emissions of CFCs contribute over 90% to the ODP of the refining process and over 95% to the ODP of the crushing process.

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corresponding inputs to the ODP

3.2.1.6 Normalization

To get an impression of the share of the single impact category results associated with the production of one tonne of refined oil (considering oilseed crushing and vegetable oil refin-ing) in relation to the total amount of potential impact generated in the EU, a normalized reference (EU-25) for each of the environmental impact categories is calculated (Figure 3-9).

Figure 3-9: Normalization to EU 25

Normalization can serve as a rough estimate of the quantitative relevance of impacts and different impact categories. However, as impacts, which do not occur in the EU-25 reference area (e.g. in certain background processes) are included within the assessment, normalization has only limited informative value.

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3.2.2 Overview results: energy allocation

Results of the impact assessment from section 3.2.1 need to be allocated in order to distribute environmental burdens to the individual products of crushing and refining and to assess environmental burdens of one tonne of refined oil. The potential burdens have to be split between crude oil, meal/cake and lecithin for crushing and refined oil and soap stock (or fatty acid distillates) for refining. As indicated in section 2.2.6, allocation based on the energy content (lower heating value, LHV) of products is used.

Table 3-6 provides further information concerning the energy content of the different products assessed within this study.

Table 3-6: Overview energy content

Crushing Energy content (LHV) (MJ/kg)

Refining Energy content (LHV) (MJ/kg)

Soybean

Soybean crude oil 37 Soybean refined oil 37

Soybean meal 20 Soap stock 20

Soy lecithin 30

Rape seed

Rape seed crude oil 37 Rape seed refined oil 37

Rape seed cake 16 Soap stock 20

Palm

Palm refined oil 37

Palm fatty acids 30

In Figure 3-10, environmental burdens associated with the functional unit of one tonne of refined oil are presented for all process steps. In comparison to Figure 3-1, results vary significantly. The crushing step is no longer dominant across all impact categories, and also the spread between the environmental burden of rape seed crushing and soybean crushing changed. This is caused by the comparatively high share of meal during the production of soybean oil and consequently the higher environmental burden allocated to soybean meal. The percentage share of environmental burden allocated to oil (energy allocation) is presented in Table 3-7.

Table 3-7: Percentage of environmental burden allocated to oil

Soybean crushing

Soybean refining

Rape seed crushing

Rape seed refining

Palm refining

32.1% 98.8% 63.0% 98.9% 95.6%

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Figure 3-10: Relative LCIA results for the selected five environmental impact categories performing energy allocation

Figure 3-11 shows, exemplarily, the detailed allocation of the GWP to oil, meal/cake and other by-products based on energy content (LHV). The relative share of environmental burdens allocated to individual products is the same for all impact categories (see Table 3-7).

Figure 3-11: Overview energy allocation (using the example of GWP)

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3.3 Qualitative discussion of other potential impacts

3.3.1 Toxicity

Toxicity plays potentially an important role in the environmental and sustainability assessment of products and processes. However, an assessment of toxicity impacts (by means of the USEtox model (Rosenbaum et al. 2008)) is not included in this study, due to methodological shortcomings, missing inventory data and difficulty of interpretation. The uncertainty of the available methods for evaluation potential toxicity is significantly higher than for other assessed impact categories.

3.3.2 Water consumption

The cultivation of oilseeds requires significant amounts of water. However, this occurs outside the system boundary of this gate-to-gate study. Water consumption of the assessed processes is relatively small compared to other stages of the supply chain.

Potential impacts of water consumption are not considered further in this work as there is currently no agreed standard on how to assess water use within LCA (Berger et al. 2010). The assessment of water resource depletion is outside the scope of this project, but is recommended for future study.

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4 Interpretation

Key findings for the “gate-to-gate” assessment of oilseed crushing and vegetable oil refining are presented in this chapter. Processes that are main contributors to the five impact categories, considered in this LCA (section 4.1) are analyzed and a sensitivity analysis regarding different parameters is conducted to verify results (section 4.2).

4.1 Contribution analysis and identification of significant parameters

The extent to which individual processes contribute to the results is assessed as part of a significance analysis. Significant parameters are methodological choices and data with significant influence on the results of the study. Inputs and outputs with high significance for the impact assessment results are displayed in Table 4-1. Methodological choices that can have an influence on the results are e.g. the choice of impact assessment method or choice of allocation method (assessed within a sensitivity analysis in the next sections).

Table 4-1: Contribution analysis: overview of relevant in- and outputs

GWP AP EP POCP ODP

Crushing Process steam Electricity Electricity Emissions of hexane (on-site)

Electricity

Electricity Process steam Process steam

Emissions of H2S (untreated off gases)

Refining Process steam Process steam Production of acids

Electricity

Electricity Electricity

Production of electricity and process steam (from natural gas) dominate results across most impact categories. Underlying LC data are up-to-date and represent best available data from a reliable database (GaBi 5 professional). As these data are relatively robust and assessment of company specific processes data are out of the scope of this study, no further sensitivity analysis is conducted.

In the crushing phase, emissions of H2S are relevant for the AP and emissions of hexane dominate the POCP. H2S-emissions are based on average H2S loads (kg/tonne oil) but do not consider any emission treatment. In reality, emissions and associated impacts are expected to be lower at processing plants with air treatment units in place (complying with legal specifications). Thus, effects of H2S emissions are not considered further. An increase of hexane used and emitted is included within the sensitivity analysis (assessing data variation, see section 4.2.3). The production of acids is significant for the EP in the refining phase and datasets used are assessed further in section 4.2.4.

Referring to the normalization (section 3.2.1.6), the POCP is the impact category with the relatively highest relevance based on the contribution of oilseed crushing and crude oil refining to the total impacts generated in the EU. This is mainly related to the emissions of hexane. However, as this study does not consider any post-treatment of off gases and assumes all hexane used is emitted on site (see assumptions, section 3.2.1.4); the relevance of results has to be seen in context of these assumptions. Results of the normalization are only intended to exemplify dimensions and caution should therefore be exercised in interpreting them.

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4.2 Completeness, sensitivity and consistency

Completeness was checked at gate-to-gate level for all process steps and inputs and was verified with FEDIOL member companies that provided data. Furthermore, data consistency was checked regarding the scope of the LCA. No relevant data gaps exist according to this evaluation and all material flows relevant for representing the average European crushing and refining situation are included in this study.

A sensitivity analysis serves as a measure to assess the robustness of an LCA and provides an insight on the sensitivity of results in relation to various parameters. In this study a sensitivity analysis is carried out regarding

- different allocations methods (applying mass and economic allocation)

- different impact assessment methods (using the ReCiPe method)

- the range of provided data

- inclusion of specific flows (talcum) and specific processes (wastewater treatment) on the LCIA results

- validity of used LCI data.

The sensitivity analysis is performed in relation to the functional unit (one tonne of refined oil).

4.2.1 Sensitivity analysis: allocation

Allocation based on the energy content of the oil and the different by-products is used in this report (see 3.2.2). In this section allocation of potential environmental impacts (always using the example of GWP – percentage share of the allocated burden is the same for all impact categories) is tested for sensitivity by comparing results obtained by energy allocation with other common allocation methods: allocation according to mass and allocation according to economic value (price).

4.2.1.1 Mass allocation

Basis for this allocation method is the mass of the individual products (see Table 4-2). Figure 4-1 depicts the potential environmental impacts allocated to soybean, rape seed and palm oil and the associated by-products according to mass allocation. Several by-products are included: Meal/cake and soy lecithin (crushing) and soap stock and fatty acids (refining).

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Table 4-2: Overview mass of products

Crushing Amount (kg) Refining Amount (kg)

Soybean

Soybean crude oil 1000 Soybean refined oil 1000

Soybean meal 4080 Soap stock 23

Soy lecithin 20

Rape seed

Rape seed crude oil 1000 Rape seed refined oil 1000

Rape seed cake 1390 Soap stock 20

Palm

Palm refined oil 1000

Palm fatty acids 68

Results of the mass allocation scenario in Figure 4-1 suggest that mass allocation would lower impact results for one tonne of refined oil (by around 10% for soybean, 15% for rape seed and 0.3% for palm oil) compared to the results obtained by performing energy allocation. The reason for this is the high amount/mass of by-products occurring during crushing: 79% of the impacts of the soybean crushing process are allocated to the meal (57% for rape seed). Other by-products like lecithin and soap stock have almost no impact on the results. Mass allocation is very easy to apply as data are available and easy to calculate. However, when using mass allocation all outputs get the same burden per mass. This results in the allocation of most of the environmental impacts of crushing to the meal, considered as a by-product in this study. As energy-allocation is a recognized method in the vegetable oil sector and has already been laid down in EU legislation, mass allocation is not considered further.

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Figure 4-1: Overview mass allocation (using the example of GWP)

4.2.1.2 Economic allocation

For performing economic allocation, the average market prices for oil and meal/cake for the period 2009 to 2011 are used as a basis (see Table 4-4) (Oil World 2012). Price data for soap stock, lecithin and fatty acid distillates are provided on a company basis referring to the years 2010 and 2011.

Table 4-3: Overview of product prices

Crushing Price (€/t) Refining Price (€/t)

Soybean

Soybean crude oil 759 Soybean refined oil 809 Soybean meal 297 Soap stock 350

Soy lecithin 600 Rape seed Rape seed crude oil 778 Rape seed refined oil 843 Rape seed cake 174 Soap stock 200 Palm Palm refined oil 803 Palm fatty acids 632

Results of the economic allocation scenario, as shown in Figure 4-2, suggest that environmental burden of one tonne of refined oil would increase (by around 6% for soybean, 10% for rape seed and 1% for palm oil) compared to results obtained by performing energy allocation. Compared to the other allocation methods, oil has a higher share of the environmental burden due to its relatively high price.

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Figure 4-2: Overview economic allocation (using the example of GWP)

However, price variations regarding the products cannot be considered properly creating inconsistency and uncertainty:

- Prices of oil are volatile (see Figure 4-3),

- the price-ratio between oil and meal/cake changes,

- prices for by-products differ substantially across different applications (e.g. deodistillates sold for feed or as raw material for vitamin E production), as quality, specifications and composition vary, and

- price data are often inconsistent (e.g. internal vs. market price, taxes, etc.).

Figure 4-3: Overview price development 1997-2011

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Price is not seen as a good basis for allocation in the oilseed processing industry as it leads to high uncertainties in results. Even though included within this sensitivity analysis, economic allocation is not recommended for use.

4.2.1.3 Comparison of allocation method results

In this section, results of all three allocation methods are compared. In Figure 4-4 the results of the different allocation methods for soybean and rape seed crushing are presented. During soybean crushing a higher amount of meal is produced for obtaining one tonne of crude oil. Thus, compared with the processing of rape seeds, the share of environmental burden allocated to oil is considerably lower than the share allocated to meal. This difference is most significant when applying mass allocation. The share of the environmental burden allocated to soy lecithin is below 1% for all three methods.

Figure 4-4: Overview allocation methods: oilseed crushing – percentage share of

environmental burdens allocated to crude soybean and rape seed oil for each method

(using the example of GWP)

Regarding refining, the environmental burden allocated to by-products is relatively small, independent from the allocation method (see Figure 4-5). Less than 2% of the environmental burdens of refining are allocated to the soap stock and between 4% and 6% of the environmental burdens are allocated to the palm fatty acid distillates.

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Figure 4-5: Overview allocation methods: crude oil refining – percentage share of

environmental burdens allocated to refined soybean, rape seed and palm oil for each

method (using the example of GWP)

4.2.1.4 Choice of allocation method

The selection of the allocation procedures is a value choice. However, consistent allocations methods should be applied within each study. Otherwise, inconsistencies occur (e.g. unintended ignorance or unintended double-counting of environmental burden). This is challenging in practice for the product systems crushing and refining. As an example, energy allocation based on lower heating values might be appropriate for energy products like biofuels, but for feed products, energy that can be effectively utilized in animal metabolism is much more relevant.

Allocation according to mass is an established approach and data are readily available. However, the product with the largest mass might not be the output in focus in the assessment and mass allocation is appropriate only if by-products have a similar economic value. The price differences between typical FEDIOL products (oil and meal) are significant. Thus, mass allocation will most likely not be seen as appropriate as a high value product gets the same burden (per unit of mass) as a low value one. Economic allocation should only be applied if physical relationships cannot be established (ISO 14040). Economic allocation considers the added value of a product and is used in studies on the agri-food chain. In the present study, economic allocation has its limitations due to non-disclosure of contracts (including price data) and, as mentioned before, the fact that market prices are subject to instability and volatility (see section 4.2.1.2).

Prioritization of allocation methods according to the ISO standard should be the basis for allocation decisions.

4.2.2 Sensitivity analysis: impact assessment according to ReCiPe

The CML-method is the most commonly applied impact assessment method. One of the newer impact assessment methods available is the ReCiPe-method (Goedkoop et al. 2008), which can be seen as an advancement of the CML-method. In this section, results of both assessment methods are compared for the five environmental impact categories

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considered in this study. The comparison is based on environmental burdens allocated to the production of one tonne of refined oil.

Regarding potential impacts of GHG emissions, CML categorizes impacts as “Global Warming Potential” and ReCiPe as “Climate Change”. Both methods provide similar results, due to the similarity of evaluation methods used (Figure 4-6). The minor differences in results obtained are caused by ReCiPe not accounting for biogenic sequestration of CO2-emissions by renewable resources (Goedkoop et al. 2008, CML 2010).

Figure 4-6: Potential impacts of GHG emissions according to CML and ReCiPe

Application of the two methods for assessing eutrophication leads to incomparable results. The CML-method summarizes all flows within one value, measured in phosphate equivalents (see Table 4-4), whereas ReCiPe splits the impacts into two different categories with different reference units: In EP-freshwater all phosphorus-based flows are assessed and in EP-marine all flows associated with nitrogen are considered. Nitrous oxide, organic components and xylene are included only in the CML-method. However, the assessment according to ReCiPe results in higher impacts, due to different characterization factors and different probability of occurrence. Overall, results are not comparable in an absolute way due to the different reference units and interpretation of results would lead to different conclusions.

Table 4-4: EP according to CML and ReCiPe

CML ReCiPe freshwater ReCiPe marine

kg PO4-equiv. kg P-equiv. kg N-equiv.

Rape seed crushing 0,018 0,000 0,051

Soybean crushing 0,015 0,000 0,042

Rape seed oil refining 0,024 0,001 0,027

Soybean oil refining 0,031 0,002 0,031

Palm oil refining 0,023 0,015 0,018

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In Figure 4-7, relative shares of the potential environmental impacts allocated to oil for each impact category (CML and ReCiPe) are broken down per processing step and per type of oil. On the left side, relative LCIA results of the production of one tonne of refined oil are presented. Significant differences occur between CML and ReCiPe. Within the ReCiPe-method, marine and freshwater eutrophication potentials vary significantly for the processes considered. However, when combining and scaling the results of the ReCiPe categories (which is only done for representation reasons and not based on scientific justification), the relative relevance of the individual processes is the same as based on the CML method (right side of Figure). Even though results of the different methods cannot be compared directly and in an absolute way, interpretation would lead to similar conclusions. The ReCiPe method delivers additional information regarding the contribution of substances either to marine or freshwater eutrophication

Figure 4-7: EP: Relative share of environmental impacts according to CML and ReCiPe

Regarding acidification, both methods use the same reference unit (kg SO2-equiv.). However, CML calculates results based on 141 different flows, while results according to ReCiPe are based only on four different flows. Nevertheless, both methods provide similar results for the refining phase. Regarding rape seed crushing, more significant differences occur, as not all emissions assessed within the CML evaluation are covered by the ReCiPe-method. Within the CML-method, most relevant emissions for acidification are sulfur dioxide, nitrogen dioxide and H2S. The ReCiPe method, does not consider emissions of H2S. As the amount of H2S emitted during rape seed crushing is relatively high, the difference in results is most significant here (see Figure 4-8).

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Figure 4-8: AP according to CML and ReCiPe

The ODP is based on almost the same basis and weighting for both methods. Within ReCiPe carbon hydrides are considered in addition to substances assessed within CML. However, only minor differences occur in the results of the two methods (see Figure 4-9).

Figure 4-9: ODP according to CML and ReCiPe

The methods use different reference units for assessing the POCP, but basically the same substance flows are analyzed. Due to the different reference units weighting of individual flows as well as results differs (see Table 4-5).

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Table 4-5: POCP according to CML and ReCiPe

CML (kg Ethene-equiv.) ReCiPe (kg NMVOC-equiv.)

Rape seed crushing 0,476 0,926

Soybean crushing 0,486 0,928

Rape seed refining 0,012 0,087

Soybean refining 0,016 0,107

Palm refining 0,007 0,057

Hence, results of CML and ReCiPe are not comparable in an absolute way for this impact category. However, the same relative ranking of results occurs for the different process steps and oils (see Figure 4-10). Despite the fact that different reference units are used, interpretation of results would lead to similar conclusions

Figure 4-10: POCP: Relative share of environmental impacts according to CML and ReCiPe

In summary, both methods lead to similar results when impact categories are based on the same reference units and existing differences are caused by consideration of different substance flows. For EP and POCP different reference units are used, thus comparison of these impact categories is not possible and conclusions can differ.

4.2.3 Sensitivity analysis: energy mix

In this study, a European oilseed crushing and vegetable oil refining specific energy mix is used, based on available statistics (FEDIOL 2013). Country specific processing volumes influence the energy mix as potential environmental impacts associated with e.g. the elec-tricity grid mix vary among countries. Within a sensitivity analysis, the applied energy mix is compared with the average European grid and process steam mix (EU-27) provided within the GaBi 5 database. Exemplarily, GWP and AP with regard to crushing of soy-beans for production of one tonne of refined oil are compared (see Figure 4-11). Overall,

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no significant change in results can be observed. Depending on the system under study, the energy mix and the potential environmental impacts associated with the energy mix change. Data used in this study is more precise than a generic European energy mix based on GaBi 5 data and provides a more realistic representation of the energy mix of oilseed crushing and vegetable oil refining in Europe. Thus, no further research is con-ducted.

Figure 4-11: Comparison of different energy mixes (electricity grid and process steam) on

the example of soybean crushing: GWP (left) and AP (right)

4.2.4 Sensitivity analysis: variation of data

To assess potential effects of data variations on results, a sensitivity analysis with regard to the average data used is conducted. For this purpose, standard deviations (+1 SD) are utilized (see Table 3-4).

In Figure 4-11, the GWP based on average European data as used in this study (base scenario), and the GWP based on average values increased with the respective standard deviations (see Table 3-4) are compared. Thereby, potential effects of data variations on results can be analyzed. For crushing, the spread in data results in a difference of about 11 to 13%. For refining, the results vary more and for palm refining resulting impacts are up to 44% higher (for underlying data see section 3.1.1).

Similar differences occur for other impact categories. The most significant difference is found regarding the EP of soybean refining, which is 60% higher when based on the average values + 1SD compared to the base scenario results. This is due to the relatively high standard deviation regarding acid use (see Table 3-4) (detailed information can be found in Annex B). Sensitivity of data used regarding different acids and associated potential environmental impacts is assessed in more detail in the following section. Increase of use and emissions of hexane results in absolute changes of the POCP and EP categories, however, within the range of the results in Figure 4-12.

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Figure 4-12: Data variations - effects on GWP

The assessment of data ranges gives an impression of the potential divergence of impact assessment results and approximates a “worst case” scenario with regard to individual companies/sites considered for the assessment of the average European situation.

Furthermore, relevant issues on the inventory level (e.g. the use of acids) that should be considered in detail in future studies are identified. For this study, the use of average data is, however, appropriate as the scope of this study is a representation of the European industry standards for oilseed crushing and vegetable oil refining.

4.2.5 Sensitivity analysis: acids

For rape and soy refining phosphoric and sulfuric acid are used. Phosphoric acid is used in chemical refineries for degumming in a purification process; sulfuric acid is used for soap stock splitting. Within the GaBi 5 professional database and the ecoinvent database only few life cycle inventories are available for production of phosphoric and sulfuric acid (Table 4-6).

Table 4-6: Overview LCI data for acids

LCI – data acids Reference year

‘Phosphoric acid, industrial grade, 85% in H2O, at plant’, ecoinvent

database

1994

‘Sulphuric acid, liquid, at plant’, ecoinvent database 2001

´Sulphuric acid (96%), PE database 2010

LCI data for ‘phosphoric acid’ are taken from the ecoinvent database as this is the only data set available within GaBi 5 software. LCI data for sulfuric acid are based on data by PE International – two different inventories are available, but data from PE International are most up-to-date (and valid as of 2010/2011). Following, the potential environmental

45

impacts associated with production of acids are assessed in more detail and compared using the example of soybean refining (see Table 3-2).

In Figure 4-13 the relative relevance of sulfuric and phosphoric acid is compared (including data from PE International and ecoinvent) with regard to the individual contribution of the acids to the different impact categories.

Figure 4-13: Impact assessment results: comparison of acids and databases

The difference between the impacts associated with sulfuric acid from different databases can have many causes. For instance, in the ecoinvent dataset, sulfuric acid is considered as a byproduct from the processing of sulfide ores and it is thus determined that the sulfuric acid produced by smelter gas burning is obtained "for free”. Consequently, the contribution of this process is subtracted from the overall average (Althaus et al. 2003). As mentioned before, due to temporal requirements and consistency the dataset of PE International is used in this study.

For phosphoric acid, no data by PE International are available within GaBi 5. The LCI data for phosphoric acid provided by ecoinvent are outdated. However, as no other or newer data are available the study makes use of this dataset. In future studies, a closer assessment should be conducted, due to the relevance of phosphoric acids for the impact results.

In Figure 4-14 a comparison of the overall results of the environmental impact assessment based on the two different datasets for sulfuric acid is presented to verify that choices made do not meaningfully affect the results. The variation of potential environmental impacts across the different impact categories when using LCI data provided by ecoinvent is put in relation to the application of data by PE (base scenario). The use of these different background datasets has no significant impact on the results of this study.

46

Figure 4-14: Sulfuric acid datasets: relative impacts on LCIA results

As describe in section 2.2.7 the release of emissions associated with the use of acids are not considered in this study.

4.2.6 Sensitivity analysis: dataset assessment

4.2.6.1 Talcum

Talcum can be used within soybean crushing. As use of talcum is site-specific, it is not considered to be representative for the average European situation and not taken into account within this study. The potential relevance of talcum for the overall results is analyzed within this sensitivity analysis. In Figure 4-15 the relative effects of talcum on the LCIA results are displayed using the example of soybean crushing.

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Figure 4-15: Relative impacts of the inclusion of talcum on LCIA results for soybean crushing

The inclusion of talcum into the assessment leads to comparably small changes in the overall results. As the use of talcum does not represent the average European situation, its exclusion is in line with the scope of the study.

4.2.6.2 Bleaching earth

Only one LCI of production of bleaching earth has been identified, i.e. “Bentonite”, included in the ecoinvent database available in GaBi 5 software. The data are representative for Germany (no European average is available) and are based on production data from a German company (Kellenberger et al. 2003). However, base year for this dataset is 1997 and data is valid only until 2000. Thus, in this study, the new process “clay powder” (data valid until 2013) based on data by PE International is used. The use of this dataset is based on the best available data and thus in line with the scope of the study. However, creation of a new dataset could improve results.

4.2.7 Sensitivity analysis: wastewater treatment

Wastewater treatment is not explicitly considered within this study as treatment procedures of FEDIOL member companies are heterogeneous. Site-specific properties of wastewater, i.e. quantity and contaminants, affect energy need, material usage and sludge generation. Different treatment processes are in place at the assessed production sites and no process displaying the average European situation could be identified. In this section an approximation of wastewater treatment is conducted within a sensitivity analysis. For this approximation, the process “wastewater treatment (contains organic load)” (GaBi 5 2011) from the GaBi 5 professional database is used. On average two tonnes of wastewater are generated during production of one tonne of refined soybean oil, equally distributed among crushing and refining. For one tonne of refined rape seed oil on

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average one tonne of wastewater accumulate, also equally distributed among crushing and refining. The wastewater that occurs during palm oil refining is not considered further, as the amount of wastewater in physical refineries is comparably small. In Figures 4-16 to 4-19 the potential impact of wastewater treatment based on the standard processes “wastewater treatment (contains organic load)” is displayed

- with regard to the entire impacts of the processing activities (no allocation) (Figure 4-15 and 4-17) and

- with regard to the allocated impact assessment results of one tonne of refined soybean and rape seed oil (performing energy allocation) (Figure 4-16 and 4-18).

Results show that wastewater treatment is insignificant for most impact categories. Relatively high relevance occurs regarding eutrophication. However, as wastewater treatment is not considered in detail in this study, the exact composition of wastewater e.g. the specific phosphate load or the amount of sodium sulfate discharged with the wastewater is not determined.

Including wastewater treatment leads to higher results regarding the potential environ-mental impacts (especially eutrophication potential). This is counter-intuitive at first sight, as wastewater treatment reduces emissions in reality. However, emissions to waste water (like e.g. phosphate) have not been considered in this LCA so far, because of the chosen cut-off criteria (see section 2.2.7). In the sensitivity analysis, the effort of removing these is now implicitly included in this approximated wastewater treatment process. The impacts are caused by the additional energy input, auxiliary materials and the remaining emissions from the treatment process. If the untreated, raw emissions to wastewater were chosen to be included in the assessment, the treatment of wastewater would have resulted in lower overall impacts.

In this study, a European state-of-the art wastewater treatment process, as available in the GaBi 5 database is used. A detailed assessment of wastewater treatment options and a site-specific analysis of potential environmental impacts of wastewater treatment should be conducted in future studies.

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Figure 4-16: Wastewater treatment: LCIA results for soybean crushing and refining (no-

allocation)

Figure 4-17: Wastewater treatment: LCIA results allocated to one tonne of refined soybean

oil

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Figure 4-18: Wastewater treatment: LCIA results for rape seed crushing and refining (no

allocation)

Figure 4-19: Wastewater treatment: LCIA results allocated to one tonne of refined rape seed

oil

0,1% 11,6% 0,2%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

AcidificationPotential (AP) [kg

SO2‐Equiv.]

EutrophicationPotential (EP) [kgPhosphate‐Equiv.]

Global WarmingPotential (GWP100 years) [kgCO2‐Equiv.]

Ozone LayerDepletion

Potential (ODP,steady state) [kg

R11‐Equiv.]

Photochem. OzoneCreation Potential(POCP) [kg Ethene‐

Equiv.]

Rape seed Crushing Rape seed Refining Wastewater Treatment

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4.3 Conclusions and recommendations

The gate-to-gate LCA study evaluates the environmental performance of crushing soybeans and rape seeds and refining crude soybean, rape seed and palm oil in Europe. A valid database is established and results are specific and representative for the average European situation. This study enables the comparison of site-specific inventories of FEDIOL member companies with the average European industry standard and improvement potentials can be identified.

Potential environmental impacts related to crushing and refining in Europe are analyzed. Results of the LCIA differ for the assessed oils due to different underlying energy mixes and varying amounts of inputs and emissions. The study revealed that air emissions and energy consumption associated with the crushing step (production of crude oil) are main contributors to the results of the LCIA. Furthermore, the production of several auxiliary materials has an effect on the level of environmental impacts.

Some general gaps regarding background data from available databases are identified. Data quality should be improved, and own datasets could be developed (e.g. regarding specific acids used) in the future.

The results of this study can be used as a solid basis for follow-up studies. Such follow-up studies could assess the sensitivity of results with regard to data variations more closely, include a detailed assessment of wastewater and wastewater treatment and perform a comprehensive analysis of acid usage and water consumption (e.g. by means of a water footprint). Additionally, the scope of the LCA could be expanded to include sunflower seed crushing and sunflower oil refining.

Based on the study findings it is recommended that FEDIOL member companies, when aiming to reduce potential environmental aspects, focus on energy efficiency measures for crushing and refining (reducing energy consumption), off-gas treatment, and reduction of hexane and acid consumption. Furthermore, results of this study can serve as a benchmark for a site (or company)-specific LCA. Profiles can differ significantly due to different situations on-site, especially regarding the presence and effectiveness of exhaust gas treatment and the nature and efficiency of energy production.

This LCA may serve as a basis for the development of an EPD including product category rules (PCRs) for oilseed crushing and vegetable oil refining. The availability of such PCRs would help to avoid inconsistencies between companies when communicating information on the potential environmental impact of similar products. Based on this LCA study, different methodological options can be assessed and the LCA can serve as a decision support for the approaches to be defined in the PCRs.

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5 References Althaus H. J., Chudacoff, M., Hellweg, S., Hischier, R., Jungbluth, N., Osses, M. and Primas, A.. 2003, Life cycle inventories of chemicals. ecoinvent report No. 8. Swiss Centre for Life Cycle Inventories, Dübendorf

Berger, M., Finkbeiner, M. 2010. Water Footprinting: how to Address Water Use in Life Cycle Assessment?. Sustainability 2, no.4: 919-944

Brankatschk, G. and M. Finkbeiner. 2012. The Cereal Unit allocation as a new allocation procedure for agricultural life cycle assessments. In 6th SETAC World Congress 2012. Berlin.

CML 2010. CML- IA Characterization Factors. Leiden University, [http://cml.leiden.edu/ software/data-cmlia.html], accessed on 21.04.2012

ecoinvent (2010). ecoinvent data v2.0. Final reports ecoinvent 2010. Swiss Centre for Life Cycle Inventories, Dübendorf

Ekvall, T. and G. Finnveden. 2001. Allocation in ISO 14041 - a critical review. Journal of Cleaner Production 9: 197-208.

European Union. 2009. DIRECTIVE 2009/28/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC

FEDIOL. 2013. http://www.fediol.eu/web/statistics%202011/1011306087/list1187970179/ f1.html

GaBi 5. 2012. PE International. GaBi 5 software-System and Database for Life Cycle Engineering. Copyright, TM. Stuttgart, Echterdingen 1992-2011. Retrieved from www.gabi-software.com

Goedkoop, M. et al. 2009, ReCiPe 2008 – A life cycle impact assessment method which comprises harmonised category indica-tors at the midpoint and the endpoint level, first edition, Januar 2009, Netherlands

Guinée, J.B.; Gorrée, M.; Heijungs, R.; Huppes, G.; Kleijn, R.; Koning, A. de; Oers, L. van; Wegener Sleeswijk, A.; Suh, S.; Udo de Haes, H.A.; Bruijn, H. de; Duin, R. van; Huijbregts, M.A.J. 2001. Handbook on life cycle assessment. Operational guide to the ISO standards. I: LCA in perspective. IIa: Guide. IIb: Operational annex. III: Scientific background. Kluwer Academic Publishers, ISBN 1-4020-0228-9, 692 pp., Dordrecht

IPCC. 2006. Intergovernmental Panel on Climate Change (2006) Guidelines for National Greenhouse Gas Inventories. Retrieved from http://www.ipcc-nggip.iges.or.jp/ISO 14040. 2006. Life cycle assessment - Principles and framework. In Environmental management.

ISO 14040, 2006. Environmental management - Life cycle assessment - Principles and framework, International Organisation for Standardisation (ISO), Geneva

ISO 14044. 2006. Environmental management - Life cycle assessment - Requirements and guidelines, International Organisation for Standardisation (ISO), Geneva.

Kellenberger D., Althaus, H.-J., Künniger, T. and Jungbluth, N. 2003. Life Cycle Inventories of Building Products, Data v1.01 (2003). ecoin-vent report No. 7, EMPA Dübendorf , Swiss Centre for Life Cycle Inventories, Dübendorf

Oil World Monthly, Weekly, issues 2003-2011, ISTA Mielke GmbH

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Rosenbaum, R. K. 2008, USEtox – the UNEP SETAC toxicity mod-el: recommended characterization factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment, Internation-al Journal of Life Cycle Assessment, Vol. 13, No. 7, S. 532-546

Solvents Emission Directive 1999/13/EC. 1999. Council directive on the limitation of emissions of volatile organic compound due to the use of organic solvents in certain activities and installations. Official Journal of the European Communities.

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Annex A Critical Review Statement

A.1 Commissioned by

Fediol, Brussels, Belgium

A.2 Reviewers

Drs. Hans Blonk, Gouda, the Netherlands

Dr. Willem-Jan van Zeist, Gouda, the Netherlands

A.3 Reference

• ISO 14040 (2006): Environmental Management - Life Cycle Assessment - Principles and Framework

• ISO 14044 (2006): Environmental Management - Life Cycle Assessment – Require-ments and Guidelines

A.4 Scope of the critical review

The reviewers had the task to assess whether

• the methods used to carry out the LCA are consistent with the international stand-ards ISO 14040 and ISO 14044

• 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, and

• the study report is transparent and consistent.

The review was performed according to paragraph 6.2 of ISO 14044, because the study as such is not intended to be used for comparative assertions intended to be disclosed to the public. This does not preclude, that the data may be used in studies where compara-tive assertions are made, provided a separate review of that study is carried out.

This review statement is only valid for this specific report in its final version received on 16.05.2013. The analysis of the LCI model and the verification of individual datasets are outside the scope of this review.

A.5 Review process

The review process was coordinated between the authors of the report form Technische Universität Berlin (Matthias Finkbeiner & Laura Schneider) and Hans Blonk & Willem-Jan van Zeist. The first draft final report was submitted to the reviewers on 25.01.2013. The

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reviewers provided comments of general, technical and editorial nature to the authors of the report in February 2013. Answers and actions to be taken based on the comments were provided in March and were discussed in a review meeting (telephone conference) on 12.04.2011. The meeting addressed the actions taken on the review comments and allowed common understanding to be reached on unresolved issues. Some minor issues were still to be resolved and the agreed upon revisions were implemented in a new ver-sion of the report received on 26.04.2013. This version still required some minor adjust-ments, which were agreed upon via email communication with the Technische Universität Berlin. The reviewers checked the implementation of the final comments and agreed to the final report which was submitted on 16.05.2013.

A.6 Conclusion

The study has been carried out in compliance with ISO 14040 and ISO 14044. The re-viewers were satisfied with the methodology and its execution and are positive about the insights provided by the study. The study is reported in a comprehensive manner includ-ing a transparent documentation of its scope and methodological choices.

Hans Blonk Willem-Jan van Zeist

May 2013

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Annex B Supporting Information

Table B-1 and B-2 show the relative contribution of the individual inputs and emissions for crushing and refining (supplementary information section 3.2.1).

Table B-1: Supplementary information Figure 3-2

Water Process steam

Power grid mix

Emissions (Hexane, H2S)

Hexane (production)

Mineral oil

Acidification Potential [kg SO2-Equiv.]

Rape 0,05% 16,88% 42,60% 39,42% 1,05% 0,00%

Soy 0,13% 49,29% 41,85% 6,21% 2,48% 0,03%

Eutrophication Potential [kg Phosphate-Equiv.]

Rape 0,44% 55,35% 42,56% 0,00% 1,65% 0,00%

Soy 0,58% 64,13% 33,26% 0,00% 2,02% 0,02%

Global Warming Potential [kg CO2-Equiv.]

Rape 0,15% 69,60% 29,35% 0,00% 0,90% 0,00%

Soy 0,16% 78,50% 20,43% 0,00% 0,90% 0,01%

Ozone Layer Depletion Potential [kg R11-Equiv.]

Rape 0,00% 2,24% 97,75% 0,00% 0,00% 0,00%

Soy 0,01% 3,55% 96,43% 0,00% 0,00% 0,00%

Photochemical Ozone Creation Potential [kg Ethene-Equiv.]

Rape 0,01% 2,23% 1,93% 95,70% 0,13% 0,00%

Soy 0,01% 3,36% 1,05% 95,45% 0,13% 0,00%


Activated carbon

Bleaching earth

Caustic soda

Water Process steam

Power grid mix

Acid(s) Nitrogen

Acidification Potential [kg SO2-Equiv.]

Rape 0,98% 0,80% 5,22% 0,17% 19,26% 46,86% 26,70%

Soy 0,92% 1,02% 4,58% 0,18% 26,86% 34,17% 32,27%

Palm 3,90% 0,07% 17,40% 43,00% 35,12% 0,50%

Eutrophication Potential [kg Phosphate-Equiv.]

Rape 0,59% 0,54% 4,70% 0,43% 18,88% 14,00% 60,87%

Soy 0,45% 0,55% 3,34% 0,35% 16,41% 12,75% 66,14%

Palm 1,62% 0,11% 11,08% 13,24% 73,84% 0,11%

Global Warming Potential [kg CO2-Equiv.]

Rape 0,90% 1,81% 6,63% 0,38% 62,41% 25,38% 2,50%

Soy 0,69% 1,87% 4,73% 0,31% 64,72% 25,23% 2,45%

Palm 7,12% 0,13% 53,44% 36,45% 2,62% 0,24%

Ozone Layer Depletion Potential [kg R11-Equiv.]

Rape 0,95% 0,04% 1,42% 0,01% 2,06% 86,65% 8,87%

Soy 1,23% 0,07% 1,73% 0,02% 1,94% 78,95% 16,07%

Palm 0,30% 0,01% 0,74% 71,08% 26,17% 1,70%

Photochemical Ozone Creation Potential [kg Ethene-Equiv.]

Rape 1,24% 0,72% 6,20% 0,45% 40,20% 33,56% 17,62%

Soy 0,90% 0,70% 4,20% 0,35% 52,90% 24,74% 16,21%

Palm 3,54% 0,19% 35,25% 38,53% 22,10% 0,39%

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Supplementary information to sections 3.2.2 and 4.2.1: Table B-3: Supplementary information Figure 3-11

Energy allocation Soybean Rape seed Palm

Crude oil 119.8 117.5

Refined oil 77.4 59.3 42.9

Meal/cake 251.8 69.1

Lecithin, soap stock, fatty acid 2.8 0.6 2.8


Mass allocation Soybean Rape seed Palm

Crude oil 76.1 79.1

Refined oil 76.6 58.8 43.3

Meal/cake 295.8 107.5



Economic allocation Soybean Rape seed Palm

Crude oil 147.2 143.3

Refined oil 77.6 59.7 43.3

Meal/cake 224.0 43.4


Table B-6: LCIA results for one tonne of refined soybean oil, gate-to-gate assessment

Impact GWP (kg CO2-equiv.)

AP (kg SO2-equiv.)

EP (kg Phosphate-equiv.)

POCP (kg Ethene-equiv.)

ODP (kg R11-equiv.)

No allocation 451.8 0.7 0.08 1.5 3.6E-06

Energy allocation 197.3 0.3 0.05 0.5 1.7E-06

Mass allocation 152.7 0.3 0.04 0.3 1.4E-06

Economic allocation 224.8 0.4 0.05 0.6 1.9E-06

Table B-7: LCIA results for one tonne of refined rape seed oil, gate-to-gate assessment

Impact GWP (kg CO2-quiv.)

AP (kg SO2-equiv.)

EP (kg Phospahe-equiv.)

POCP (kg Ethene-equiv.)

ODP (kg R11-equiv.)

No allocation 246.6 0.8 0.05 0.8 4.7E-06

Energy allocation 176.3 0.5 0.04 0.5 3.4E-06

Mass allocation 137.9 0.4 0.04 0.3 2.6E-06

Economic allocation 202.9 0.6 0.05 0.6 3.9E-06

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Assessment of potential effects of data variations on results within a sensitivity analysis (supplementary information to section 4.2.3):

Figure B-1: Data variations - effects on POCP

Figure B-2: Data variations - effects on AP

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Figure B-3: Data variations - effects on EP

Figure B-4: Data variations - effects on ODP

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