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Final Report Eco-Profile of Aromatic Polyester Polyols (APP)
Sponsored by PU Europe, Federation of European rigid Polyurethane Foam Associations
Title of the Study: Eco-Profile of Aromatic Polyester Polyols (APP)
Client: PU Europe, Federation of European rigid Polyurethane Foam Associations
March 2010
Authors: Angela Schindler Fabian Haßel Dr. Martin Baitz
PE INTERNATIONAL GmbH
Hauptstraße 111 – 113 70771 Leinfelden – Echterdingen Phone Fax
+49 711 341817 – 470 +49 711 341817 – 25
a.schindler@pe-international.com
Internet
www.pe-international.com
List of Contents
List of Contents List of Contents .................................................................................................................. 3 List of Figures .................................................................................................................... 5 List of Tables ..................................................................................................................... 6 Nomenclature .................................................................................................................... 8 Executive Summary ........................................................................................................... 9 1
Background and Introduction ......................................................................... 10
2
Goal of the study ........................................................................................... 11
3
System description ........................................................................................ 12
3.1
Product description ........................................................................................ 12
3.2 3.3
Functional unit ............................................................................................... 12 System boundary conditions .......................................................................... 12
3.4
Temporal, technological and geographical reference ..................................... 13
3.5
Cut-off rules ................................................................................................... 13
3.6
Allocation ....................................................................................................... 14
4
Data sources and quality ............................................................................... 15
4.1 4.2
Data collection and source of data ................................................................. 15 Data Quality ................................................................................................... 16
4.2.1 4.2.2 4.2.3 4.2.4 4.2.5 4.2.6
Precision........................................................................................................ 16 Accuracy........................................................................................................ 16 Completeness................................................................................................ 16 Representativeness ....................................................................................... 17 Consistency ................................................................................................... 17 Reproducibility ............................................................................................... 17
4.3
Data Validation .............................................................................................. 17
5
Description of the System .............................................................................. 18
6
Life Cycle Inventory for APPs with Flame Retardant ...................................... 20
6.1
Energy Data .................................................................................................. 20
6.2
Raw Materials Input ....................................................................................... 22
6.3
Water Consumption ....................................................................................... 24
6.4 6.5
Air Emission Data .......................................................................................... 25 Wastewater Emission Data ............................................................................ 29
6.6
Solid Waste ................................................................................................... 29
7
Life Cycle Impact Assessment for APPs with Flame Retardant...................... 30
8
Supplement Data for APP without Flame Retardants..................................... 31
8.1
Energy Data .................................................................................................. 31
8.2
Raw Materials Input ....................................................................................... 33
8.3
Water Consumption ....................................................................................... 35
8.4
Air Emission Data .......................................................................................... 36 3
List of Contents
8.5
Wastewater Emission Data ............................................................................ 40
8.6
Solid Waste ................................................................................................... 40
9
Life Cycle Impact Assessment for APPs without Flame Retardant ................ 41
10
Literature ....................................................................................................... 42
Supplement A
Description of result parameters ........................................................... 43
Supplement A 1
Primary energy consumption............................................................. 43
Supplement A 2
Global Warming Potential (GWP) ...................................................... 43
Supplement A 3
Acidification Potential (AP) ................................................................ 44
Supplement A 4
Eutrophication Potential (EP) ............................................................ 45
Supplement A 5
Photochemical Ozone Creation Potential (POCP) ............................. 46
Supplement A 6
Ozone Depletion Potential (ODP)...................................................... 46
Supplement A 7
Abiotic Depletion Potential ................................................................ 47
4
List of Figures
List of Figures Figure 5-1:
Esterification process for the production of Aromatic Polyester Polyols ..................................................................................................18
Figure A 1:
Greenhouse effect (KREISSIG & KÜMMEL 1999) .....................................44
Figure A 2:
Acidification Potential (KREISSIG & KÜMMEL 1999) .................................44
Figure A 3:
Eutrophication Potential (KREISSIG & KÜMMEL 1999) .............................45
Figure A 4:
Photochemical Ozone Creation Potential (KREISSIG & KÜMMEL 1999) ....................................................................................................46
Figure A 5:
Ozone Depletion Potential (KREISSIG & KÜMMEL 1999) .........................47
5
List of Tables
List of Tables Table 3-1:
Typical specific APP products...............................................................12
Table 5-1:
Raw materialsâ€&#x; list for APP-production ..................................................19
Table 6-1:
Primary energy input (gross calorific value) required to produce 1 kg of APP (split into energy types) .....................................................20
Table 6-2:
Primary energy input (gross calorific value) required to produce 1 kg of APP (split into energy content) ..................................................20
Table 6-3:
Primary energy input (gross calorific value) required to produce 1 kg of APP (referring to primary energy resources) .............................21
Table 6-4:
Primary energy input (expressed as mass) ...........................................21
Table 6-5:
Raw material input to produce 1 kg of APP...........................................22
Table 6-6:
Water consumption to produce 1 kg of APP (without circulated cooling water) .......................................................................................24
Table 6-7:
Air emissions associated with the production of 1 kg of APP ................25
Table 6-8:
Wastewater emission associated with the production of 1 kg of APP ......................................................................................................29
Table 6-9:
Waste associated with the production of 1 kg of APP ...........................29
Table 7-1:
Environmental impact associated with the production of 1 kg of APP ......................................................................................................30
Table 8-1:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (split into energy types) .............31
Table 8-2:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (split into energy content)..........31
Table 8-3:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (referring to primary energy resources) ............................................................................................32
Table 8-4:
Primary energy input (expressed as mass) ...........................................32
Table 8-5:
Raw material input to produce 1 kg of APP (without flame retardant) ..............................................................................................33
Table 8-6:
Water consumption to produce 1 kg of APP (without flame retardant), (without circulated cooling water) ........................................35
Table 8-7:
Air emissions associated with the production of 1 kg of APP (without flame retardant) .......................................................................36
Table 8-8:
Wastewater emission associated with the production of 1 kg of APP (without flame retardant) ...............................................................40
6
List of Tables
Table 8-9:
Waste associated with the production of 1 kg of APP (without flame retardant) ....................................................................................40
Table 9-1:
Environmental impact associated with the production of 1 kg of APP (without flame retardant) ...............................................................41
7
Nomenclature
Nomenclature Abbreviation
Explanation
AP
Acidification Potential
APP
Aromatic Polyester Polyol
ADP
Abiotic Depletion Potential
EP
Eutrophication Potential
EPD
Environmental Product Declaration
GWP
Global Warming Potential
ODP
Ozone Depletion Potential
POCP
Photochemical Ozone Creation Potential
8
Executive Summary
Executive Summary This report provides a European average cradle-to-gate Life Cycle Inventory for Aromatic Polyester Polyol (APP). APPs are used in the manufacture of polyisocyanurate (PIR) rigid insulation foam. Data for other components of PIR are available, especially polymeric MDI. There are two sets of results included in the report, one for APPs with flame retardant and one without. The report is created in compliance with the latest PlasticsEurope methodology protocol for uncompounded Polymer Resins and Reactive Polymer Precursors, [PLASTICS EUROPE 2009]. This document defines the methodology and scope of the data. The reference year of the data is 2008. In case of comparative assertions, the respective framework describing the study‟s system boundaries has to be considered. Differences of cut-off criteria and geographical situations with regard to energy carriers and energy grid mixes may influence the results. APP may also be produced by varying technologies and so via different process chains and intermediate products. Depending on the study‟s participants and the number of participants a direct comparison of several studies may lead to wrong conclusions. The LCI is intended for public use as “cradle-to-gate” building blocks of life cycle assessment (LCA) studies of defined applications or products. The report is as detailed and specific as the circumstances in a multi-client project with highly confidential and competitive company data allows. The data of this report show the inventory of the aggregated process chain, i.e. the input and output flows of the Life Cycle as well as the Life Cycle Impact Assessment for the impact categories abiotic depletion potential, global warming potential, acidification potential, eutrophication potential, ozone depletion potential and photochemical ozone creation potential according to the characterization factors of CML 2007.
9
Background and Introduction
1 Background and Introduction PU Europe, the Federation of European rigid Polyurethane Foam Associations, supports the collection of detailed environmental data on the processes operated by its member companies with the intention of making this information available for public use. The Ecoprofile initiative [Plastics Europe 2009] provides an industry specific methodology protocol for creating and reporting the Eco-Profiles. The Eco-profile protocol is based on ISO standards for Life Cycle Assessment and Environmental Product Declaration [ISO 14040: 2006; and ISO 14021: 1999 et sqq.]. Eco-profiles1 are widely acknowledged among life cycle practitioners and other stakeholders worldwide as representative, objective and quantitative datasets. The average industry Eco-Profile datasets can be used for internal company benchmarking allowing individual process improvement. Furthermore, these data could be used as building blocks in the LCA of products where APP is used. This allows APP customers to improve their environmental management by: evaluating the plastics contribution relative to the overall product; enabling collaboration with recovery procedures to reduce collective impacts; drawing attention to poor environmental links in user chains, which can lead to subsequent improvement. providing data to investigate alternative solutions for regulatory compliance. Supporting the Eco-Profile initiative, this study aims to develop the Cradle-to-Gate Life Cycle Inventory (Eco-profile) and Life Cycle Impact Assessment for the Aromatic Polyester Polyol (APP). The APP cradle-to-gate lifecycle system is analyzed and the important aspects of the LCI and LCIA are described in this report, following the latest PlasticsEurope methodology protocol for uncompounded Polymer Resins and Reactive Polymer Precursors, [PLASTICS EUROPE 2009]. The content and format of the report is be based on the above mentioned methodology protocol. In accordance with Eco-Profile requirements [PLASTICS EUROPE 2009], the following structure is used for this study: In chapter 1 “Background and Introduction” the motivation for the background to this study is provided. Chapter 2 provides the goal of the study. The specific characteristics and boundaries of the considered production-process are presented in chapter 3; chapter 4 discusses the data sources and quality. The respective process of the APP-production is described in chapter 5. The life cycle inventory results are listed in chapter 6 and 8. Results of the Life Cycle Impact Assessment (LCIA) are reported in chapter 7 and 9.
1
The terms „Eco-profile‟ and „Life cycle inventory‟ have the same meaning under the PlasticsEurope methodology protocol and thus are used interchangeably in this report. 10
Goal of the study
2 Goal of the study Goal of this study is to create an European average cradle–to-gate Life Cycle Inventory (Eco-Profile) of Aromatic Polyester Polyols in compliance with PlasticsEurope Eco-Profile Guidlines [PLASTICS EUROPE 2009]. Thus, the primary data from four APP producers were collected, the lifecycle system was modelled in the GaB 4 software and the important aspects of the LCI and LCIA are reported here, following the latest PlasticsEurope methodology protocol for uncompounded Polymer Resins and Reactive Polymer Precursors, [PLASTICS EUROPE 2009]. The Eco-profiles (LCI) report is intended to be used as “cradle-to-gate” building blocks of life cycle assessment (LCA) studies of defined applications or products.
11
System description
3 System description This chapter describes the different circumstances and boundary conditions of the study, which are vitally important to understand the system and allow the correct interpretation of the results. A description of the LCI dataset and the underlying methodology is described in the chapter in compliance with the Eco-Profile requirements. The section includes the identification of the specific product, the supporting product system, the scope of the study, the boundaries, the data description, the allocation procedures and cut-off criteria.
3.1
Product description
Aromatic Polyester Polyols comprises a group of products which are polymers. Therefore a CAS number, nor an IUPAC name, nor a chemical formula can be stated. The following products are considered: Table 3-1:
Typical specific APP products
Producer
Aromatic Polyester Polyols
COIM
ISOEXTER TM
®
Web-link
3061 – 3557 – 4404
®
INVISTA
TERATE polyols
STEPAN
Stepanpol
SYNTHESIA
Hoopol
http://terate.invista.com/
®
®
www.coimgroup.com
www.stepan.com F-1394/1396/3362/4361/4390
www.synte.es
The data for the production process considered in this study is not split into different steps but comprises the overall procedure. Polyester Polyols are important intermediate products for many production chains. APPs are used to manufacture polyisocyanurate (PIR) and polyurethane rigid insulation foam, which finds extensive use in the automotive, construction, refrigeration and other industrial sectors. Other uses include flexible polyurethane foams, semi-rigid foams, and polyurethane coatings. A major part of the world‟s polyols production is shared by two groups of polyols, namely polyether and polyester polyols. Both production and consumption of aromatic polyester polyols is strongest in Western Europe, where the market is the largest and most established, which gives a high value to the European average LCI dataset.
3.2
Functional unit
The study uses the following functional unit: 1 kg of aromatic polyester polyol on production output, representing the average of the four participants‟ production lines. This implies that the functional unit does not include blending in PU systems.
3.3
System boundary conditions
The APP product was modelled in a cradle-to-gate LCI system. Thus, the cradle-to-gate LCI represents all life cycle processes from extraction of natural resources, up to the point 12
System description
where the product is ready for transportation to a customer. Packaging of the material is not included. The construction of the APP-plant and equipment as well as the maintenance of plants, vehicles and machinery is outside the LCI system boundaries of EcoProfiles. The primary data from four major APP suppliers were collected and vertical averaging was calculated, weighted by the yearly production tonnage of each chain. I.e. every single production line was calculated separately according to data collected from the participants of this study. The result of the Life Cycle Impact Assessment is then weighted according to the total production amount of 2008. Hence the figures reflect the average of four actual existing process chains.
3.4
Temporal, technological and geographical reference
Time related coverage: The LCI data for APP production are collected as 12 month averages representing the year 2008. Background data have reference years from 2002 to 2008 although mostly coming from 2005 to 2008. If all data would be related to 2008, major changes in the result are not expected, as technological breakthrough is not known for refining, re-refining technology or one of the related up-stream technologies. The expected temporal validity of the dataset: the data is considered to be sufficiently valid, till the first significant change in the production chain will take place. Geographical coverage: Primary production data for the APP production comes from four different suppliers in the EU. Fuel and energy inputs in the system reflect the European conditions, site specific to the extent possible. Therefore, the study results are intended to be applicable in EU boundaries and need adjustments in order to be applied in other regions. Technological coverage: The APP production processes are modelled using specific values, representing the specific technology for the four companies. The LCI data represent technology in use in the defined production region employed by participating producers. The considered participants cover 75-85 % of a total market of more than 100,000 t, so the technological coverage is understood as representative. Primary data were used for all foreground processes (under operational control) complimented with secondary data from background processes (under indirect management control).
3.5
Cut-off rules
The cut-off criteria for the study include or exclude materials, energy and emissions data as follows: Mass – If a flow is less than 2 % of the cumulative mass of the model it may be excluded, provided that its environmental relevance is not a concern. Energy – If a flow is less than 2 % of the cumulative energy of the model it may be excluded, provided that its environmental relevance is not a concern. Environmental relevance – If a flow meets the above criteria for exclusion, yet is thought to potentially have a significant environmental impact, it will be included. Material flows which leave the system (emissions) and whose environmental impact is greater than 2 % 13
System description
of the whole impact of an impact category that has been considered in the assessment is covered. The sum of the neglected material flows does not exceed 5 % of mass, energy or environmental relevance. The average of the reported output mass flows of the four participants shows 97 % of the input mass flows. 100 % of the material end energy flows, provided by the participants as primary data, are integrated in the calculations.
3.6
Allocation
Allocation was applied for the production process of some participants, as minor byproducts result from their specific APP-processing. The by-products have lower values than the main product APP. The process intention is the production of APP only. Therefore an economic allocation was applied according to current market prices, stated by the relevant company. In the refinery operations, co-production was addressed by applying allocation based on mass and net calorific value [GaBi databases, 2006]. The chosen allocation in refinery is based on several sensitivity analyses, which was accompanied by petrochemical experts. The relevance and influence of possible other allocation keys in this context is small. In steam cracking allocation according to net calorific value is applied. Relevance of other allocation rules (mass) is below 2 %.
14
Data sources and quality
4 Data sources and quality 4.1
Data collection and source of data
Gate-to-gate APP production: primary data European producers act as a main source of data for the production of Aromatic Polyester Polyols on the basis of a direct questionnaire. Primary data on gate-to-gate APP production is derived from site specific information for processes under operational control supplied by the participating companies of this study. Four different APP producers are participating in the primary data collection. Upstream supply chain data: The data for the upstream supply chain until the precursors are taken from the database of the software system GaBi 4. All relevant background data such as energy and auxiliary material are also taken from the GaBi 4 database. Most of the background data used is publicly available and public documentation exists [GABI 2006]. Carbon dioxide, which has been sequestrated by biomass is included in the calculation of the balance. The overall considered input-flow of CO2 as sink is 0.134 kg/kg APP. The amount originates from biomass, directly used as raw material as well as from energy which is generated from biomass. Many different small contributors sum up to the 0.134 kg/kg APP. Special attention was paid to the appropriate specifications of related energy supply. Based on the data from producers the following specific processes were modelled: Country specific import mixes of resources and precursors Country specific fuel mix and fuel import mixes Country specific energy supply (depending on location of precursors and APP site) After modelling the site-specific systems, the vertical average was calculated, weighted by the production tonnage of each company. The following companies participated in this study:
COIM GROUP via A. Manzoni 28/32 20019 Settimo Milanese, Italy www.coimgroup.com
INVISTATM Philipp Reis Str. 2 65795 Hattersheim, Germany www.invista.com Production site The Netherlands
15
Data sources and quality
Stepan Company 22 W. Frontage Rd Northfield, Illinois 60093, USA www.stepan.com Production site Germany
SYNTHESIA INTERNACIONAL S.L.U. c/Coure, 6 Àrea Industrial del Llobregat 08755 Castellbisbal (Barcelona), Spain www.synthesia.eu
4.2
Data Quality
Data quality is judged by its precision (measured, calculated or estimated), completeness, consistency (degree of uniformity of the methodology applied on a study serving as a data source) and representativeness (geographical, time period, technology). To cover these requirements and to ensure reliable results, first-hand data in combination with consistent, background LCA information from the GaBi 4 database [GABI 2006] is used. All considered pre-products are integrated into the calculation with their respective environmental burden. The background database of GaBi was initially set-up in 1991 and since then is frequently updated and enlarged. A two-step quality assurance is applied. First, an internal expert check by PE is performed and as a second step, an expert-check by the University of Stuttgart takes place. Additionally, an ongoing check by the users worldwide is done, comparing the GaBi data to other data supply sources. The data sets have been used in LCA-models worldwide for several years in industrial and scientific applications without any actual known negative feedback on shortcomings from users. 4.2.1
Precision
As the relevant foreground data is primary data or modelled based on primary information sources of the owner of the technology, better precision is not reachable within this goal and scope. All background data is consistently GaBi professional data with the documented (high) precision. 4.2.2
Accuracy
Primary data is collected with an accuracy of 0.01 kg. 4.2.3
Completeness
Primary data used for the gate-to-gate production of APP covers all related flows of in accordance with the cut off criteria. Other data in the model that is coming from the GaBi 4 database covers all related flows accordingly to the system boundaries and cut off criteria. There are not any missing data of known concern for the study. 16
Data sources and quality
4.2.4
Representativeness
The considered participants cover 75-85 % of a total market of more than 100,000 t in 2008. The selected background GaBi 4 data can be regarded as representative for the intended purpose, as it is average data and not in the focus of the analysis. 4.2.5
Consistency
To ensure consistency only primary data of the same level of detail and background data from the GaBi 4 databases are used. While building up the model cross-checks concerning the plausibility of mass and energy flows are continuously conducted. The provided primary data was checked by PE several times. Inconsistency could not be found. 4.2.6
Reproducibility
The study has been performed with the LCA software PE GaBi 4. GaBi software and associated database integrate ISO 14040/48 requirements. All data and information used are either documented in this report or they are available from the processes and process plans designed within the PE GaBi 4 software. The reproducibility is given for internal use since the owners of the technology provided the data and the models are stored and available in a database. Sub-systems are modelled by ´state of art´ technology using data from a publicly available and internationally used database. For the external audience it is possible that full reproducibility in any degree of detail will not be available for confidentiality reasons.
4.3
Data Validation
The data on APP production collected from the project partners was validated at PE INTERNATIONAL and the data providing companies in an iterative process several times. The collected data are validated using existing data from published sources [e.g. EYERER 1996, GABI 2006] or experts‟ knowledge from PE INTERNATIONAL and LBP. The background information from the GaBi 4 database is updated regularly and validated in principle daily by the various users worldwide.
17
Description of the System
5 Description of the System The production of APP can be done in different ways. The four participants start from diverse raw materials. The flow chart in Figure 5-1 shows the relevant materials. Primary data refer to the “black box” process of esterification; data of the manufacturers are stated as overall figures for the gate-to-gate process. Background data for the pre-products origins from the GaBi 4 data base and complement the process chain. Waste streams of the APP-process itself cross the system boundaries. Due to lack of further information on the waste streams as e.g. heating value or physical treatment, the waste treatment is not considered in this study.
Figure 5-1:
Esterification process for the production of Aromatic Polyester Polyols
The raw materials used for the production of APP are listed in Table 5-1. As the companies‟ processes require different raw materials according to the respective process version, only parts of the raw materials‟ list are used respectively.
18
Description of the System
Table 5-1:
Raw materials’ list for APP-production
Raw material Dimethyl terephtalate (DMT) Polyethylene terephthalate (PET) Phthalic Anhydride (PA) Polyethylene glycol (PEG) Diethylene glycol (DEG) Catalyst Additives Flame retardants Functionality enhancers
Due to confidentiality reasons details on software modelling and methods used cannot be shown here. The calculation follows the vertical calculation methodology, i.e. that the averaging is done after modelling the specific processes. Restrictions on competition and confidentiality do not allow displaying and describing the systems and analysing details.
19
Life Cycle Inventory for APPs with Flame Retardant
6 Life Cycle Inventory for APPs with Flame Retardant The Life Cycle Inventory shows the results of the cradle-to-gate process for the production of 1 kg APP with flame retardant (see page 31 for APPs without flame retardant).
6.1
Energy Data
Table 6-1 lists data for the primary energy demand (gross calorific value) broken down to the types and areas the energy is used for. Table 6-1:
Primary energy input (gross calorific value) required to produce 1 kg of APP (split into energy types)
Primary energy for
[MJ]
Electricity in APP production
1.6
Thermal energy in APP production
2.8
Pre-products as input in APP production
72.4
Water / sewage treatment in APP production
0.2
Total
77.0
Table 6-2 shows the primary energy demand (gross calorific value) divided into energy content of the energy carrier, including the fuel production and delivery, and the feedstock energy, contained in the raw materials, used for the APP production. Transportation processes are not considered. Transport of pre-products cannot be standardized as industry sites may be manifold. Sensitivity analysis show, that transports contribute mainly only up to 2 %. Assuming a transport of 1000 km in the product chain (truck with 27 t payload, EURO 4) the emissions result in about 0.05 kg CO2-eq. (compared to 2,77 kg CO2-eq. for APP, chapter 7).. The effort for data investigation is not commensurate with the increase of supposed accurateness of the results. Table 6-2:
Primary energy input (gross calorific value) required to produce 1 kg of APP (split into energy content)
Primary energy
[MJ]
Energy content of fuel (incl. fuel production and delivery)
31.5
Feedstock energy
45.6
Total
77.0
20
Life Cycle Inventory for APPs with Flame Retardant
Table 6-3:
Primary energy input (gross calorific value) required to produce 1 kg of APP (referring to primary energy resources)
Energy carrier
Energy content of fuel [MJ]
Lignite
2.5
Natural gas
2.6
12.6
15.2
Crude oil
17.6
33.0
50.6
Hard coal
2. 9
2.9
Uranium
3.7
3.7
Wood
2.3E-04
2.3E-04
Renewable fuels
6.7E-08
6.7E-08
Primary energy from geothermics
1.7E-02
1.7E-02
Primary energy from solar energy
1.5
1.5
Primary energy from hydro power
0.3
0.3
Primary energy from wind power
0.2
0.2
Total
31.5
Table 6-4:
Feedstock energy [MJ]
2.5
45.6
77.0
Primary energy input (expressed as mass)
Energy carrier
[kg]
Lignite
0.2
Natural gas
0.3
Crude oil
1.1
Hard coal
0.1
Uranium
6.7E-06
Wood
1.4E-05
Renewable fuels
4.0E-09
Total
1.8
21
Total [MJ]
Life Cycle Inventory for APPs with Flame Retardant
6.2
Raw Materials Input
Table 6-5:
Raw material input to produce 1 kg of APP
Raw material
[kg]
Barium sulphate
4.09E-14
Basalt
4.73E-05
Bauxite
5.32E-05
Bentonite
1.85E-03
Calcium chloride
4.19E-12
Chromium ore
3.29E-06
Clay
4.68E-04
Colemanite ore
5.99E-07
Copper - Gold - Silver - ore (1.0% Cu; 0.4 g/t Au; 66 g/t Ag)
2.43E-06
Copper - Gold - Silver - ore (1.1% Cu; 0.01 g/t Au; 2.86 g/t Ag)
1.48E-06
Copper - Gold - Silver - ore (1.16% Cu; 0.002 g/t Au; 1.06 g/t Ag)
8.35E-07
Copper - Molybdenum - Gold - Silver - ore (1.13% Cu; 0.02% Mo; 0.01 g/t Au; 2.86 g/t Ag)
2.03E-06
Copper ore (0.14%)
3.52E-04
Copper ore (1.2%)
2.52E-07
Copper ore (4%)
9.40E-16
Copper ore (sulphidic)
1.11E-12
Dolomite
3.54E-08
Ferro manganese
2.00E-16
Fluorspar (calcium fluoride; fluorite)
1.39E-05
Gravel
5.62E-03
Gypsum (natural gypsum)
9.00E-05
Heavy spar (barytes)
4.48E-03
Imenite (titanium ore)
2.45E-06
Inert rock
3.30E+00
Iron
2.56E-07
Iron ore
2.35E-03
Iron ore (65%)
6.66E-07
Kaolin ore
1.08E-06
Lead
3.99E-16
Lead - zinc - ore (4.6%-0.6%)
6.38E-04
22
Life Cycle Inventory for APPs with Flame Retardant
Lead - zinc - silver - ore (5.49% Pb; 12.15% Zn; 57.4 gpt Ag)
8.04E-11
Limestone (calcium carbonate)
8.41E-02
Magnesit (Magnesium carbonate)
5.31E-09
Magnesium chloride leach (40%)
4.03E-03
Manganese ore
6.34E-07
Manganese ore (R.O.M.)
2.18E-03
Molybdenite (Mo 0.24%)
1.26E-06
Nickel ore
1.82E-07
Nickel ore (1.6%)
7.29E-05
Olivine
2.20E-15
Ore (antimony and gold)
8.76E-07
Peat
1.79E-04
Phosphate ore
6.51E-03
Phosphorus minerals
2.18E-09
Phosphorus ore (29% P2O5)
3.92E-02
Potassium chloride
5.01E-04
Potassium salt
2.72E-02
Precious metal ore (R.O.M)
4.14E-08
Quartz sand (silica sand; silicon dioxide)
1.02E-02
Raw pumice
1.04E-07
Rhodium
5.59E-13
Rutil
0.00E+00
Silicon
3.87E-12
Slate
3.69E-15
Sodium chloride (rock salt)
2.72E-02
Sodium sulphate
0.00E+00
Soil
1.19E-02
Sulphur
4.74E-10
Sulphur (bonded)
2.43E-10
Talc
1.87E-08
Tin ore
3.55E-15
Titanium ore
3.38E-07
Zinc - copper ore (4.07%-2.59%)
2.02E-04
Zinc - lead - copper ore (12%-3%-2%)
5.87E-05
23
Life Cycle Inventory for APPs with Flame Retardant
Zinc - lead ore (4.21%-4.96%)
3.21E-16
Zinc ore (sulphide)
3.95E-15
6.3
Water Consumption
Table 6-6:
Water consumption to produce 1 kg of APP (without circulated cooling water)
Water source
[kg]
Water (unspecified)
8.41E-02
Water (river water)
0.00E+00
Water (ground water)
6.36E+00
Water (sea water)
4.62E-02
Water (surface water)
5.92E+00
Water (lake water)
1.16E-18
Water (potable water)
5.34E-07
Water (bank filtrate)
7.08E-12
Total
1.24E+01
24
Life Cycle Inventory for APPs with Flame Retardant
6.4
Air Emission Data
Table 6-7:
Air emissions associated with the production of 1 kg of APP
Emission
[kg]
Inorganic emissions Ammonia
6.88E-05
Ammonium
1.79E-11
Ammonium nitrate
1.43E-12
Argon
2.70E-14
Barium
2.94E-06
Beryllium
7.36E-10
Born coumponds
1.30E-06
Boron
1.59E-18
Bromine
3.37E-07
Carbon dioxide
2.71E+00
Carbon disulphide
1.12E-11
Carbon monoxide
1.05E-03
Chloride (unspecified)
4.78E-06
Chlorine
3.00E-05
Cyanide (unspecified)
5.05E-08
Fluoride (unspecified)
4.13E-07
Fluorides
1.22E-06
Fluorine
4.64E-10
Helium
8.25E-09
Hydrogen
4.90E-05
Hydrogen chloride
1.47E-05
Hydrogen cyanide (prussic acid)
9.49E-10
Hydrogen fluoride
2.05E-06
Hydrogen iodide
3.00E-12
Hydrogen phosphorous
1.72E-13
Hydrogen sulphide
1.24E-05
Hydrogene Bromine
2.76E-09
Lead dioxide
1.46E-13
Nitrogen (atmospheric nitrogen)
5.19E-03
Nitrogen dioxide
1.57E-06 25
Life Cycle Inventory for APPs with Flame Retardant
Nitrogen monoxide
0.00E+00
Nitrogen oxides
3.41E-03
Nitrous oxide (laughing gas)
1.54E-04
Oxygen
7.36E-04
Scandium
7.51E-13
Strontium
3.02E-11
Sulphur dioxide
3.59E-03
Sulphur hexafluoride
1.02E-11
Sulphuric acid
2.16E-09
Tin oxide
1.27E-14
Water vapour
3.46E+00
Zinc oxide
2.54E-14
Zinc sulphate
5.20E-10
Organic emissions Group PAH Anthracene
7.49E-11
Benzo(a)anthracene
3.77E-11
Benzo(a)pyrene
3.66E-10
Benzo(ghi)perylene
3.36E-11
Benzofluorantene
6.72E-11
Chrysene
9.25E-11
Dibenz(a)anthracene
2.09E-11
Indenopyrene
2.50E-11
Naphthalene
7.86E-09
Penanthrene
2.47E-09
Polycylic aromatic hydrocarbons
1.54E-06
Halogenated organic emissions Dichlormethane (methylene chlorid)
1.62E-15
Dioxins (unspec.)
2.01E-15
Halogenated hydrocarbons (unspecified)
7.99E-16
Organic chlorine compounds (unspecific)
7.16E-13
Polychlorinated biphenyls (PCB unspecified)
4.67E-11
Polychlorinated dibenzo-p-dioxins (2,3,7,8 - TCDD)
7.47E-14
R 11 (trichlorofluoroethane)
4.85E-08
26
Life Cycle Inventory for APPs with Flame Retardant
R 114 (dichlorotetrafuoroethane)
4.96E-08
R116 (hecafluoroethane)
1.86E-14
R 12 (dichlorodifluoromethane)
1.04E-08
R 13 (chlorotrifluoromethane)
6.54E-09
R 22 (chlorodifluoromethane)
1.14E-08
Tetrafluoromethane (chloroform)
2.65E-10
Vinyl chloride (VCM)
9.38E-09
NMVOC Acetaldehyde (Ethanal)
2.30E-06
Acetic acid
2.49E-04
Acetone (dimethylcetone)
5.28E-10
Acrolein
1.62E-08
Aldehyde (unspecified)
1.01E-05
Alkane (unspecified)
1.76E-06
Alkene (unspecified)
8.82E-07
Aromatic hydrocarbons (unspecified)
2.60E-06
Benzene
1.43E-11
Butadiene
8.50E-05
Butane
2.51E-06
Butane (n-butane)
9.06E-18
Cumene
2.56E-10
Cyclohexane (hexahydro benzene)
3.56E-16
Diethyl amine (ethylene ethane amine)
9.13E-06
Ethane
4.44E-06
Ethanol
3.13E-08
Ethene (ethylene)
1.34E-06
Ethyl benzene
2.44E-10
Fluoranthene
7.74E-10
Fluorene
9.17E-06
Formaldehyde (methanal)
2.46E-06
Heptane (isomers)
8.41E-13
Hexamethylene diamine (HMDA)
1.76E-05
Hexane (isomers)
1.24E-07
Mercaptan (unspecified)
1.77E-03
27
Life Cycle Inventory for APPs with Flame Retardant
Methanol
1.72E-03
NMVOC (unspecified)
1.35E-06
Octane
3.47E-05
Pentane (n-pentane)
1.34E-11
Phenol (hydroxy benzene)
3.81E-04
Propane
1.20E-07
Propene (propylene)
1.23E-10
Propionic acid (propane acid)
2.83E-13
Styrene
6.45E-07
Toluene (methyl benzene)
1.24E-13
Trimethylbenzene
5.57E-04
Xylene (dimethyl benzene)
6.02E-03
Others Methane
6.02E-03
VOC (unspecified)
7.45E-07
Particles to air Dust (PM2.5)
5.63E-05
Dust (PM10)
3.40E-05
Dust (unspecified)
1.70E-04
Metals (unspecified)*
1.40E-12
Radioactive emissions to air
5.67E-08
Wood (dust)
4.68E-12
* The value for unspecified metals originates from a multitude number of upstreamprocesses (as energy generation). In the APP production metal dust is not emitted directly. The human toxicity potential (HTP) for this output-flow can be approximated by the value of PM10. The reported flow does not significantly contribute to the HTP (CML 2007).
28
Life Cycle Inventory for APPs with Flame Retardant
6.5
Wastewater Emission Data
Table 6-8:
Wastewater emission associated with the production of 1 kg of APP
Emission
[kg]
Adsorbable organic halogen compounds (AOX)
1.21E-06
Biological oxygen demand (BOD)
5.24E-05
Chemical oxygen demand (COD)
4.35E-03
Total suspended solids (TSS)
9.48E-06
Dissolved organic carbon (DOC)
3.65E-11
Total organic carbon (TOC)
2.00E-05
6.6
Solid Waste
Table 6-9:
Waste associated with the production of 1 kg of APP
Waste
[kg]
Stockpile goods
3.30E+00
Waste for deposition
3.62E-04
Waste for recovery
6.15E-03
Municipal waste
8.44E-03
Hazardous waste for deposition
2.93E-02
Hazardous waste for recovery
1.29E-02
Radioactive waste
1.32E-03
Total
3.36E+00
29
Life Cycle Impact Assessment for APPs with Flame Retardant
7 Life Cycle Impact Assessment for APPs with Flame Retardant The Life Cycle Impact Assessment follows the methodology and characterisation factors of CML updated 2007. (see page 41 for APPs without flame retardant) Table 7-1:
Environmental impact associated with the production of 1 kg of APP
Impact category Abiotic Depletion Potential
0.03 kg Sb-Eq.
Global Warming Potential
2.77 kg CO2-Eq.
Acidification Potential
6.16E-03 kg SO2-Eq.
Eutrophication Potential
1.09E-03 kg PO4 Eq.
Ozone Depletion Potential
9.96E-08 kg R11-Eq.
Photochemical Ozone Creation Potential
1.96E-03 kg C2H2-Eq.
Primary Energy Demand (fossil) (gross cal. value)
74.97 MJ
Primary Energy Demand (renewable) (gross cal. value)
2.06 MJ
Primary Energy Demand (total) (gross cal. value)
77.03 MJ
3-
30
Supplement Data for APP without Flame Retardants
8 Supplement Data for APP without Flame Retardants APP is available on the market with and without flame retardants. This part supplements the above shown data. The results cover the cradle-to-gate process for the production of 1 kg APP without flame retardants (see page 20 for APPs with flame retardant). The process chain of flame retardants also contains some credits. Therefore it may happen that specific values of APP without flame retardant are slightly higher than the respective values for APP with flame retardants.
8.1
Energy Data
Table 8-1 lists data for the primary energy demand (gross calorific value) broken down to the types and areas the energy is used for. Table 8-1:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (split into energy types)
Primary energy for
[MJ]
Electricity in APP production
1.6
Thermal energy in APP production
2.8
Pre-products as input in APP production
69.5
Water / sewage treatment in APP production
0.2
Total
74.1
Table 8-2:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (split into energy content)
Primary energy
[MJ]
Energy content of fuel (incl. fuel production and delivery)
29.3
Feedstock energy
44.8
Total
74.1
31
Supplement Data for APP without Flame Retardants
Table 8-3:
Primary energy input (gross calorific value) required to produce 1 kg of APP (without flame retardant), (referring to primary energy resources)
Energy carrier
Energy content of fuel [MJ]
Lignite
2.2
Natural gas
1.9
12.3
14.3
Crude oil
17.4
32.5
49.9
Hard coal
2.5
2.5
Uranium
3.3
3.3
Wood
2.1E-04
2.1E-04
Renewable fuels
7.8E-08*
7.8E-08*
Primary energy from geothermics
1.7E-02
1.7E-02
Primary energy from solar energy
1.5
1.5
Primary energy from hydro power
0.3
0.3
Primary energy from wind power
0.2
0.2
Total
29.3
Table 8-4:
Feedstock energy [MJ]
2.2
44.8
74.1
Primary energy input (expressed as mass)
Energy carrier
[kg]
Lignite
0.2
Natural gas
0.3
Crude oil
1.1
Hard coal
0.1
Uranium
6.0E-06
Wood
1.3E-05
Renewable fuels
4.7E-09*
Total
1.7
32
Total [MJ]
Supplement Data for APP without Flame Retardants
8.2
Raw Materials Input
Table 8-5:
Raw material input to produce 1 kg of APP (without flame retardant)
Raw material
[kg]
Barium sulphate
4.06E-14
Basalt
4.45E-05
Bauxite
3.00E-05
Bentonite
1.79E-03
Calcium chloride
4.16E-12
Chromium ore
2.97E-06
Clay
4.54E-04
Colemanite ore
5.35E-07
Copper - Gold - Silver - ore (1,0% Cu; 0,4 g/t Au; 66 g/t Ag)
2.19E-06
Copper - Gold - Silver - ore (1,1% Cu; 0,01 g/t Au; 2,86 g/t Ag)
1.33E-06
Copper - Gold - Silver - ore (1,16% Cu; 0,002 g/t Au; 1,06 g/t Ag)
7.53E-07
Copper - Molybdenum - Gold - Silver - ore (1,13% Cu; 0,02% Mo; 0,01 g/t Au; 2,86 g/t Ag)
1.84E-06
Copper ore (0.14%)
2.76E-04
Copper ore (1.2%)
2.27E-07
Copper ore (4%)
8.97E-16
Copper ore (sulphidic)
1.06E-12
Dolomite
3.26E-08
Ferro manganese
1.98E-16
Fluorspar (calcium fluoride; fluorite)
1.39E-05
Gravel
5.26E-03
Gypsum (natural gypsum)
8.63E-05
Heavy spar (barytes)
4.33E-03
Imenite (titanium ore)
1.15E-06
Inert rock
2.82E+00
Iron
1.35E-07
Iron ore
2.09E-03
Iron ore (65%)
9.86E-07
Kaolin ore
9.60E-07
Lead
3.96E-16
Lead - zinc - ore (4,6%-0,6%)
5.50E-04
33
Supplement Data for APP without Flame Retardants
Lead - zinc - silver - ore (5,49% Pb; 12,15% Zn; 57,4 gpt Ag)
8.04E-11
Limestone (calcium carbonate)
5.32E-02
Magnesit (Magnesium carbonate)
5.24E-09
Magnesium chloride leach (40%)
3.09E-03
Manganese ore
5.71E-07
Manganese ore (R.O.M.)
1.36E-05
Molybdenite (Mo 0,24%)
1.14E-06
Nickel ore
1.82E-07
Nickel ore (1.6%)
6.51E-05
Olivine
2.18E-15
Ore (antimony and gold)
8.76E-07
Peat
1.70E-04
Phosphate ore
6.51E-03
Phosphorus minerals
2.08E-09
Phosphorus ore (29% P2O5)
7.35E-04
Potassium chloride
5.01E-04
Potassium salt
2.32E-02
Precious metal ore (R.O.M)
2.26E-07
Quartz sand (silica sand; silicon dioxide)
1.35E-03
Raw pumice
9.32E-08
Rhodium
5.59E-13
Rutil
0.00E+00
Silicon
3.87E-12
Slate
3.67E-15
Sodium chloride (rock salt)
1.46E-02
Sodium sulphate
0.00E+00
Soil
5.47E-03
Sulphur
4.67E-10
Sulphur (bonded)
2.40E-10
Talc
1.67E-08
Tin ore
3.52E-15
Titanium ore
0.00E+00
Zinc - copper ore (4.07%-2.59%)
1.63E-04
Zinc - lead - copper ore (12%-3%-2%)
4.94E-05
34
Supplement Data for APP without Flame Retardants
Zinc - lead ore (4.21%-4.96%)
3.06E-16
Zinc ore (sulphide)
1.05E-14
8.3
Water Consumption
Table 8-6:
Water consumption to produce 1 kg of APP (without flame retardant), (without circulated cooling water)
Water source
[kg]
Water (unspecified)
6.92E-02
Water (river water)
0.00E+00
Water (ground water)
5.51E+00
Water (sea water)
4.56E-02
Water (surface water)
5.82E+00
Water (lake water)
1.16E-18
Water (potable water)
2.54E-07
Water (bank filtrate)
5.22E-12
Total
1.09E+01
35
Supplement Data for APP without Flame Retardants
8.4
Air Emission Data
Table 8-7:
Air emissions associated with the production of 1 kg of APP (without flame retardant)
Emission
[kg]
Inorganic emissions Ammonia
6.82E-05
Ammonium
1.65E-11
Ammonium nitrate
1.41E-12
Argon
2.70E-14
Barium
2.84E-06
Beryllium
6.53E-10
Born coumponds
1.15E-06
Boron
1.59E-18
Bromine
2.98E-07
Carbon dioxide
2.53E+00
Carbon disulphide
7.78E-12
Carbon monoxide
8.29E-04
Chloride (unspecified)
3.55E-06
Chlorine
1.42E-05
Cyanide (unspecified)
4.98E-08
Fluoride (unspecified)
3.95E-07
Fluorides
1.20E-06
Fluorine
3.42E-10
Helium
9.20E-09
Hydrogen
4.46E-05
Hydrogen chloride
1.33E-05
Hydrogen cyanide (prussic acid)
5.27E-10
Hydrogen fluoride
1.82E-06
Hydrogen iodide
2.73E-12
Hydrogen phosphorous
1.58E-13
Hydrogen sulphide
1.23E-05
Hydrogene Bromine
2.51E-09
Lead dioxide
1.35E-13
Nitrogen (atmospheric nitrogen)
4.99E-03
36
Supplement Data for APP without Flame Retardants
Nitrogen dioxide
1.57E-06
Nitrogen monoxide
0.00E+00
Nitrogen oxides
3.17E-03
Nitrous oxide (laughing gas)
1.49E-04
Oxygen
7.02E-04
Scandium
8.14E-13
Strontium
3.24E-11
Sulphur dioxide
3.40E-03
Sulphur hexafluoride
9.40E-12
Sulphuric acid
1.91E-09
Tin oxide
1.17E-14
Water vapour
3.69E+00
Zinc oxide
2.34E-14
Zinc sulphate
5.03E-10
Organic emissions Group PAH Anthracene
7.25E-11
Benzo(a)anthracene
3.65E-11
Benzo(a)pyrene
3.61E-10
Benzo(ghi)perylene
3.25E-11
Benzofluorantene
6.51E-11
Chrysene
8.96E-11
Dibenz(a)anthracene
2.03E-11
Indenopyrene
2.42E-11
Naphthalene
7.61E-09
Penanthrene
2.39E-09
Polycylic aromatic hydrocarbons
1.53E-06
Halogenated organic emissions Dichlormethane (methylene chlorid)
1.61E-15
Dioxins (unspec.)
1.95E-15
Halogenated hydrocarbons (unspecified)
7.94E-16
Organic chlorine compounds (unspecific)
7.05E-13
Polychlorinated biphenyls (PCB unspecified)
4.45E-11
Polychlorinated dibenzo-p-dioxins (2,3,7,8 - TCDD)
6.31E-14
37
Supplement Data for APP without Flame Retardants
R 11 (trichlorofluoroethane)
4.33E-08
R 114 (dichlorotetrafuoroethane)
4.44E-08
R116 (hecafluoroethane)
1.86E-14
R 12 (dichlorodifluoromethane)
9.32E-09
R 13 (chlorotrifluoromethane)
5.85E-09
R 22 (chlorodifluoromethane)
1.02E-08
Tetrafluoromethane (chloroform)
2.40E-10
Vinyl chloride (VCM)
9.15E-09
NMVOC Acetaldehyde (Ethanal)
2.29E-06
Acetic acid
2.27E-06
Acetone (dimethylcetone)
5.11E-10
Acrolein
1.51E-08
Aldehyde (unspecified)
9.89E-06
Alkane (unspecified)
1.61E-06
Alkene (unspecified)
8.72E-07
Aromatic hydrocarbons (unspecified)
2.49E-06
Benzene
1.28E-11
Butadiene
8.26E-05
Butane
2.29E-06
Butane (n-butane)
9.06E-18
Cumene
1.78E-10
Cyclohexane (hexahydro benzene)
3.22E-16
Diethyl amine (ethylene ethane amine)
9.00E-06
Ethane
2.41E-04
Ethanol
4.39E-06
Ethene (ethylene)
3.07E-08
Ethyl benzene
1.19E-06
Fluoranthene
2.36E-10
Fluorene
7.49E-10
Formaldehyde (methanal)
8.86E-06
Heptane (isomers)
2.42E-06
Hexamethylene diamine (HMDA)
7.51E-13
Hexane (isomers)
1.76E-05
38
Supplement Data for APP without Flame Retardants
Mercaptan (unspecified)
1.21E-07
Methanol
1.77E-03
NMVOC (unspecified)
1.69E-03
Octane
1.33E-06
Pentane (n-pentane)
3.33E-05
Phenol (hydroxy benzene)
1.33E-11
Propane
3.73E-04
Propene (propylene)
1.07E-07
Propionic acid (propane acid)
1.20E-10
Styrene
1.97E-13
Toluene (methyl benzene)
5.78E-07
Trimethylbenzene
1.14E-13
Xylene (dimethyl benzene)
5.56E-04
Others Methane
5.75E-03
VOC (unspecified)
7.17E-07
Particles to air Dust (PM2.5)
5.07E-05
Dust (PM10)
3.28E-05
Dust (unspecified)
8.70E-05
Metals (unspecified)*
1.38E-12
Radioactive emissions to air
5.08E-08
Wood (dust)
4.32E-12
* The value for unspecified metals originates from a multitude number of upstreamprocesses (as energy generation). In the APP production metal dust is not emitted directly. The human toxicity potential (HTP) for this output-flow can be approximated by the value of PM10. The reported flow does not significantly contribute to the HTP (CML 2007).
39
Supplement Data for APP without Flame Retardants
8.5
Wastewater Emission Data
Table 8-8:
Wastewater emission associated with the production of 1 kg of APP (without flame retardant)
Emission
[kg]
Adsorbable organic halogen compounds (AOX)
1.18E-06
Biological oxygen demand (BOD)
5.08E-05
Chemical oxygen demand (COD)
3.23E-03
Total suspended solids (TSS)
8.60E-06
Dissolved organic carbon (DOC)
3.24E-11
Total organic carbon (TOC)
1.96E-05
8.6
Solid Waste
Table 8-9:
Waste associated with the production of 1 kg of APP (without flame retardant)
Waste
[kg]
Stockpile goods
2.80E+00
Waste for deposition
2.89E-04
Waste for recovery
4.89E-03
Municipal waste
8.22E-03
Hazardous waste for deposition
4.57E-03
Hazardous waste for recovery
1.11E-02
Radioactive waste
1.18E-03
Total
2.83E+00
40
Life Cycle Impact Assessment for APPs without Flame Retardant
9 Life Cycle Impact Assessment for APPs without Flame Retardant The Life Cycle Impact Assessment follows the methodology and characterisation factors of CML updated 2007. (see page 30 for APPs with flame retardant) Table 9-1:
Environmental impact associated with the production of 1 kg of APP (without flame retardant)
Impact category Abiotic Depletion Potential
0.03 kg Sb-Eq.
Global Warming Potential
2.58 kg CO2-Eq.
Acidification Potential
5.79E-03 kg SO2-Eq.
Eutrophication Potential
1.02E-03 kg PO4 Eq.
Ozone Depletion Potential
8.91E-08 kg R11-Eq.
Photochemical Ozone Creation Potential
1.93E-03 kg C2H2-Eq.
Primary Energy Demand (fossil) (gross cal. value)
72.14 MJ
Primary Energy Demand (renewable) (gross cal. value)
2.01 MJ
Primary Energy Demand (total) (gross cal. value)
74.15 MJ
3-
41
Literature
10 Literature EYERER 1996
Ganzheitliche Bilanzierung – Werkzeug zum Planen und Wirtschaften in Kreisläufen, 1996
GABI 2006
GaBi 4: Software und Datenbank zur Ganzheitlichen Bilanzierung. IKP, Universität Stuttgart und PE Europe GmbH, LeinfeldenEchterdingen, 2006.“
GUINÉE ET AL. 1996
LCA impact assessment of toxic releases; Generic modelling of fate, exposure and effect for ecosystems and human beings. (no. 1996/21) Centre of Environmental Science (CML) Leiden and National Institute of Public Health and Environmental Protection (RIVM), Bilthoven, May 1996.
GUINÈE ET AL. 2001
Guinée, J. et. al. Handbook on Life Cycle Assessment - Operational Guide to the ISO Standards. Centre of Environmental Science, Leiden University (CML); The Netherlands, 2001.
GUINÉE ET AL. 2002
Handbook on Life Cycle Assessment: An operational Guide to the ISO Standards; Dordrecht: Kluvver Academic Publsihers, 2002.
IKP 2003
Institut für Kunststoffprüfung und Kunststoffkunde der Universität Stuttgart, Abteilung Ganzheitliche Bilanzierung, 2003
ISO 14021: 1999
ISO 14021 Environmental labels and declarations -- Self-declared environmental claims (Type II environmental labelling). Geneva,1999
ISO 14024: 1999
ISO 14024 Environmental labels and declarations -- Type I environmental labelling -- Principles and procedures. Geneva, 1999
ISO 14025: 2006
ISO 14025 Environmental labels and declarations -- Type III environmental declarations -- Principles and procedures. Geneva, 2006
ISO 14040: 2006
ISO 14040 Environmental Management – Life Cycle Assessment – Principles and Framework. Geneva, 2006
ISO 14044: 2006
ISO 14044 Environmental management -- Life cycle assessment -Requirements and guidelines. Geneva, 2006
ISO 14048: 2002
ISO 14048 Environmental management -- Life cycle assessment -Data documentation format. Geneva, 2002
ISO 14049: 2000
ISO 14049 Environmental management -- Life cycle assessment -Examples of application of ISO 14041 to goal and scope definition and inventory analysis. Geneva, 2000
KREISSIG & KÜMMEL 1999
Kreißig, J. und J. Kümmel (1999): Baustoff-Ökobilanzen. Wirkungsabschätzung und Auswertung in der Steine-Erden-Industrie. Hrsg. Bundesverband Baustoffe Steine + Erden e.V.
PLASTICS EUROPE 2009
Plastic Europe Eco-Profiles and environmental Declarations. Life Cycle Inventory Methodology and Product Category Rules (PCR) for Uncoumpounded Polymer Precursors. March 2009.
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Supplement A
Supplement A Description of result parameters Supplement A 1 Primary energy consumption Primary energy demand is often difficult to determine due to the various types of energy source. Primary energy demand is the quantity of energy directly withdrawn from the hydrosphere, atmosphere or geosphere or energy source without any anthropogenic change. For fossil fuels and uranium, this would be the amount of resource withdrawn expressed in its energy equivalent (i.e. the energy content of the raw material). For renewable resources, the energy-characterised amount of biomass consumed would be described. For hydropower, it would be based on the amount of energy that is gained from the change in the potential energy of the water (i.e. from the height difference). As aggregated values, the following primary energies are designated: The total “Primary energy consumption non-renewable”, given in MJ, essentially characterises the gain from the energy sources natural gas, crude oil, lignite, coal and uranium. Natural gas and crude oil will be used both for energy production and as material constituents e.g. in plastics. Coal will primarily be used for energy production. Uranium will only be used for electricity production in nuclear power stations. The total “Primary energy consumption renewable”, given in MJ, is generally accounted separately and comprises hydropower, wind power, solar energy and biomass. It is important that the end energy (e.g. 1 kWh of electricity) and the primary energy used are not miscalculated with each other; otherwise the efficiency for production or supply of the end energy will not be accounted for. The energy content of the manufactured products will be considered as feedstock energy content. It will be characterised by the net calorific value of the product. It represents the still usable energy content. Supplement A 2 Global Warming Potential (GWP) The mechanism of the greenhouse effect can be observed on a small scale, as the name suggests, in a greenhouse. These effects are also occurring on a global scale. The occuring short-wave radiation from the sun comes into contact with the earth‟s surface and is partly absorbed (leading to direct warming) and partly reflected as infrared radiation. The reflected part is absorbed by so-called greenhouse gases in the troposphere and is reradiated in all directions, including back to earth. This results in a warming effect at the earth‟s surface. In addition to the natural mechanism, the greenhouse effect is enhanced by human activites. Greenhouse gases that are considered to be caused, or increased, anthropogenically are, for example, carbon dioxide, methane and CFCs. Figure A 1 shows the main processes of the anthropogenic greenhouse effect. An analysis of the greenhouse effect should consider the possible long term global effects.
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Supplement A
The global warming potential is calcuAbsorption lated in carbon dioxide equivalents Reflection UV - radiation (CO2-Eq.). This means that the greenhouse potential of an emission is given Infrared radiation in relation to CO2 Since the residence CFCs CO CH time of the gases in the atmosphere is incorporated into the calculation, a time range for the assessment must also be specified. A period of 100 Figure A 1: Greenhouse effect years is customary. T
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ce
s ga
i es
sph tmo
4
a he nt
2
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(KREISSIG & KĂœMMEL 1999)
Supplement A 3 Acidification Potential (AP) The acidification of soils and waters occurs predominantly through the transformation of air pollutants into acids. This leads to a decrease in the pH-value of rainwater and fog from 5.6 to 4 and below. Sulphur dioxide and nitrogen oxide and their respective acids (H2SO4 und HNO3) produce relevant contributions. This damages ecosystems, whereby forest dieback is the most well-known impact. Acidification has direct and indirect damaging effects (such as nutrients being washed out of soils or an increased solubility of metals into soils). But even buildings and building materials can be damaged. Examples include metals and natural stones which are corroded or disintegrated at an increased rate. When analysing acidification, it should be considered that although it is a global problem, the regional effects of acidification can vary. Figure A 2 displays the primary impact pathways of acidification. The acidification potential is given in sulphur dioxide equivalents (SO2-Eq.). The acidification potential is described as the ability of certain substances to build and release H+ - ions. Certain emissions can also be considered to have an acidification potential, if the given S-, N- and halogen atoms are set in proportion to the molecular mass of the emission. The reference substance is sulpher dioxide.
NOX SO2 H2SO44 HNO3
Figure A 2: Acidification Potential (KREISSIG & KĂœMMEL 1999)
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Supplement A 4 Eutrophication Potential (EP) Eutrophication is the enrichment of nutrients in a certain place. Eutrophication can be aquatic or terrestrial. Air pollutants, waste water and fertilization in agriculture all contribute to eutrophication. The result in water is an accelerated algae growth, which in turn, prevents sunlight from reaching the lower depths. This leads to a decrease in photosynthesis and less oxygen production. In addition, oxygen is needed for the decomposition of dead algae. Both effects cause a decreased oxygen concentration in the water, which can eventually lead to fish dying and to anaerobic decomposition (decomposition without the presence of oxygen). Hydrogen sulphide and methane are thereby produced. This can lead, among others, to the destruction of the eco-system. On eutrophicated soils, an increased susceptibility of plants to diseases and pests is often observed, as is a degradation of plant stability. If the nutrification level exceeds the amounts of nitrogen necessary for a maximum harvest, it can lead to an enrichment of nitrate. This can cause, by means of leaching, increased nitrate content in groundwater. Nitrate also ends up in drinking water. Nitrate at low levels is harmless from a toxicological point of view. However, nitrite, a reaction product of nitrate, is toxic to humans. The causes of eutrophication are displayed in Figure A 3. The eutrophication potential is calculated in phosphate equivalents (PO4-Eq). As with acidification potential, itâ€&#x;s important to remember that the effects of eutrophication potential differ regionally.
Air pollution NOX
N2O
NH3
Fertilisation
NO3 -
Waste water
PO4-3
Figure A 3: Eutrophication Potential (KREISSIG & KĂœMMEL 1999)
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NH4+
Supplement A
Supplement A 5 Photochemical Ozone Creation Potential (POCP) Despite playing a protective role in the stratosphere, at ground-level ozone is classified as a damaging trace gas. Photochemical ozone production in the troposphere, also known as summer smog, is suspected to damage vegetation and material. High concentrations of ozone are toxic to humans. Radiation from the sun and the presence of nitrogen oxides and hydrocarbons incur complex chemical reactions, producing aggressive reaction products, one of which is ozone. Nitrogen oxides alone do not cause high ozone concentration levels. Hydrocarbon emissions occur from incomplete combustion, in conjunction with petrol (storage, turnover, refuelling etc.) or from solvents. High concentrations of ozone arise when the temperature is high, humidity is low, when air is relatively static and when there are high concentrations of hydrocarbons. Today it is assumed that the existance of NO and CO reduces the accumulated ozone to NO2, CO2 and O2. This means, that high concentrations of ozone do not often occur near hydrocarbon emission sources. Higher ozone concentrations more commonly arise in areas of clean air, such as forests, where there is less NO and CO (Figure A 4). In Life Cycle Assessments, photochemical ozone creation potential (POCP) is referred to in ethyleneequivalents (C2H4-Äq.). When analyzing, it‟s important to remember that the actual ozone concentration is strongly influenced by the weather and by the characterristics of the local conditions.
Hydrocarbons Nitrogen oxides
Ozone
Dry and warm climate Hydrocarbons
Nitrogen oxides
Figure A 4: Photochemical Ozone Creation Potential (KREISSIG & KÜMMEL 1999)
Supplement A 6 Ozone Depletion Potential (ODP) Ozone is created in the stratosphere by the disassociation of oxygen atoms that are exposed to short-wave UV-light. This leads to the formation of the so-called ozone layer in the stratosphere (15 - 50 km high). About 10 % of this ozone reaches the troposphere through mixing processes. In spite of its minimal concentration, the ozone layer is essential for life on earth. Ozone absorbs the short-wave UV-radiation and releases it in longer wavelengths. As a result, only a small part of the UV-radiation reaches the earth. Anthropogenic emissions deplete ozone. This is well-known from reports on the hole in the ozone layer. The hole is currently confined to the region above Antarctica, however another ozone depletion can be identified, albeit not to the same extent, over the midlatitudes (e.g. Europe). The substances which have a depleting effect on the ozone can essentially be divided into two groups; the fluorine-chlorine-hydrocarbons (CFCs) and the nitrogen oxides (NOX). Figure A 5 depicts the procedure of ozone depletion. One effect of ozone depletion is the warming of the earth's surface. The sensitivity of humans, animals and plants to UV-B and UV-A radiation is of particular importance. Possible 46
Supplement A
effects are changes in growth or a decrease in harvest crops (disruption of photosynthesis), indications of tumors (skin cancer and eye diseases) and decrease of sea plankton, which would strongly affect the food chain. In calculating the ozone depletion potential, the anthropogenically released halogenated hydrocarbons, which can destroy many ozone molecules, are recorded first. The so-called Ozone Depletion Potential (ODP) results from the calculation of the potential of different ozone relevant substances. This is done by calculating, first of all, a scenario for a fixed quantity of emissions of a CFC reference (CFC 11). This results in an equilibrium state of total ozone reduction. The same scenario is considered for each substance under study whereby CFC 11 is replaced by the quantity of the substance. This leads to the ozone depletion potential for each respective substance, which is given in CFC 11 equivalents. An evaluation of the ozone depletion potential should take into consideration the long term, global and partly irreversible effects.
UV - radiation
Stratosphere 15 - 50 km
Absorption
Absorption
CFCs Nitrogen oxide
Figure A 5: Ozone Depletion Potential (KREISSIG & KĂœMMEL 1999)
Supplement A 7 Abiotic Depletion Potential The abiotic depletion potential covers all natural resources (incl. fossil energy carriers) as metal containing ores, crude oil and mineral raw materials. Abiotic resources include all raw materials from non-living resources that are non-renewable. This impact category describes the reduction of the global amount of non-renewable raw materials. Nonrenewable means a time frame of at least 500 years. This impact category covers an evaluation of the availability of natural elements in general, as well as the availability of fossil energy carriers. The reference substance for the characterisation factors is antimony.
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