Database upgrade 2014 upgrades and improvements by Sphera

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Database Upgrade 2014 Upgrades and improvements December 2014

Introduction to the upgrade of databases available with GaBi

Table of Contents 1

Introduction to the upgrade of databases available with GaBi ............................................ 2

GaBi Databases ‘14 .................................................................................................................. 3

2.1

Inventories for electricity, thermal energy and steam .......................................................................... 5

2.2

Inventories for primary energy carriers .............................................................................................. 17

2.3

Organic and inorganic intermediates ................................................................................................. 18

2.4

Inventories for metal processes ......................................................................................................... 19

2.5

Inventories plastic processes ............................................................................................................ 20

2.6

Inventories for end-of-life processes.................................................................................................. 22

2.7

Inventories for electronic processes .................................................................................................. 23

2.8

Inventories for renewable processes ................................................................................................. 25

2.9

Inventories for construction processes .............................................................................................. 27

2.10

Inventories for textile processes ........................................................................................................ 33

2.11

Inventories for transport processes ................................................................................................... 34

2.12

Inventories for US regional processes ............................................................................................... 35

2.13

Inventories for machining processes ................................................................................................. 37

Industry data in GaBi ............................................................................................................. 38

General continuous improvement done in the Upgrade ’14 ............................................... 39

4.1

Naming .............................................................................................................................................. 39

4.2

Sorting ............................................................................................................................................... 40

4.3

Documentation .................................................................................................................................. 41

4.4

LCIA / Method.................................................................................................................................... 45

4.5

New Objects ...................................................................................................................................... 49

4.6

Bugs and improvements .................................................................................................................... 50

References ...................................................................................................................................... 51 Annex: Version 2013 datasets – Explanations and Recommendations ..................................... 53

Introduction to the upgrade of databases available with GaBi

In total over 30 employees of PE were involved in the upgrade of several thousand unit processes and aggregated LCI datasets. The invested time, knowledge and dedication of our employees resulted in the new GaBi Databases 2014 with more than 8000 LCI datasets, 1200 of which are new. The process of continual upgrades to the GaBi Databases is in part at least a result of the team structure within PE which is illustrated in the figure below.

Figure 1-1: Process structure in GaBi databases

In the GaBi Databases, process documentation is directly integrated in the datasets. Additional information about the modelling principles applied to all datasets can be found in the document GaBi Database and Modelling Principles1, which was revised and complements the new impact assessment methods added to the GaBi Databases 2014. Additionally the document GaBi Water Modelling Principles2 was revised, providing an up-to-date GaBi water assessment terminology and details on how water use and water consumption can be assessed using GaBi Software. This document covers all relevant changes in the upgraded LCI datasets of the GaBi Databases. The document will address both methodology changes and changes in technology, if any, and is structured by material or topic, e.g. electricity, metals, plastics, renewables. In general, all PE related datasets have been upgraded.

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GaBi Databases ‘14

“Facts do not cease to exist because they are ignored” Aldous Huxley. PE INTERNATIONAL introduced the annual upgrade of the GaBi databases for three reasons: 

to keep your results as up-to-date and close to the evolving supply chains as possible; including automated upgrades of your valued work to the most current state.



to avoid disruptive changes caused by multiyear intervals that are surprisingly hard to communicate and interpret.

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to keep track on methodological changes and implement them promptly

PE databases are based on technical facts and internationally accepted and broadly applied. Standardized methods are used as a preference, which are established in industry, science and regulatory authorities. New methods are applied, if these have proven to be based on a relevant standard, on broadly and internationally accepted approaches or when enforced by relevant regulations. Changes in datasets are often the result of many effects in the supply chain. But “technical” reasons should be carefully separated from methodological reasons. Necessary methodological adoptions due to evolving standards, knowledge and frameworks may be useful; however GaBi databases do not undertake methodological trials on the back of databases that aim to reflect technological reality. Changes in the environmental profile of the datasets from the GaBi Databases 2013 to the GaBi Databases 2014 may be attributed to one or more of the following factors: 

Upgrade of the foreground and/or background systems. The market situation, applied or newly available technology creates different impacts. The environmental profile for the supply of energy carriers or intermediates is subject to changes over a period of time and affects the environmental profile of virtually all materials and products by varying degrees. For example a change of energy carrier mix or efficiency for electricity supply changes the environmental profile of all materials or products created using that electricity supply.



Improvements and changes in the technology of the production process. Improvements or developments in production processes might achieve for example higher energy efficiency, through the reduction of material losses and process emissions. Sometimes, the technology is subjected to higher quality demands that are placed downstream on the products (e.g. more end-of pipe measures to reduce emissions, higher desulphurization of fuels) and improved use phase performance. In addition, certain production routes might have been phased out, changing the production mix of a certain material, substance or energy. A popular example is the electricity grid mix datasets, as some countries try to reduce or phase-out certain types of energy or fuels in the electricity supply mix, which require the introduction of alternative sources of fuels and energy.



Further standardization and established knowledge in the modelling approach. Modelling of realistic technology chains has always been the core focus of the GaBi database. Some topics have attracted more attention, such as water and waste. Further harmonisation and improvement in the LCA methodology and feedback from clients and employees have enhanced the modelling approach for the GaBi Databases. Detailed information is given in the document GaBi Database and Modelling

GaBi Databases ‘14

Principles3. Methodological adoptions are carried out extremely carefully, passing through multiple levels of reviews by PE experts responsible for standardization, technology knowledge and quality assurance. This internal review process was audited within the continuous improvement process by our external verification partner. GaBi database updates and upgrades focus on reliability through consistency to ensure clients system models and results are not jeopardised due to random methodological changes. The degree of influence of each of these factors is specific to each process and cannot be generalised for all cases nor can a single factor be highlighted. However as technological excellence is a core value of PE data, the focus is to update and apply ALL RELEVANT AND IMPORTANT improvements and changes in technology and the supply chain and THE NECESSARRY AND ESTABLISHED improvements and changes in the methodology. Supply chain modelling of a single material involves hundreds or even thousands of single operations. Therefore even opposing effects (improvements of some processes and higher impacts of other processes along the chain) may occur. GaBi systems e.g. leading to a single aggregated dataset consists of multiple datasets within one supply chain. This means users could find many reasons for changes within a single supply chain. GaBi models must be able to reflect in first instance the necessary complexity of the reality, in order to be able to provide realistic data. Reduction of complexity is only credible if the reality of the supply chains is still mirrored adequately. The change analysis is a time consuming but important process within PE INTERNATIONAL and the results are documented in this report. However, the relevance of changes in the GaBi database related to the users own systems is highly dependent on the goal and scope in the specific user application. This means the same dataset may lead to significant changes for a certain user, whereas in another users system the changes might be irrelevant. To shorten the time for users to reflect on the relevancy of the GaBi databases changes for their own systems, the analyst function of GaBi Software may support in a effective way. To guide users to the relevant changes in their models due to changes in external factors and GaBi background data upgrades, PE INTERNATIONAL provides additionally this document “Database Upgrade, Updates and improvements” in addition to the document “GaBi Database and Modelling Principles” and over 5000 interlinked electronical documentation files supplied with PE databases. The following sections will address the most relevant changes in the GaBi Databases for the different areas.

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2.1

Inventories for electricity, thermal energy and steam Relevant changes in energy carrier mix for electricity generation after the upgrade

The reference year is 2011 for all electricity grid mixes and energy carrier mixes (coal, crude oil and natural gas) in the GaBi databases 20144. Relevant changes in the life cycle inventory (LCI) of the upgraded national grid mix datasets occur for a couple of countries due to changes in the energy carriers that were used for electricity generation, as well as changes in the amount of imported electricity and the country of origin of these imports. The changes in the LCI data sets reveal the following trends: 

An ongoing trend in some countries, to increase the share of renewable energies in their electricity generation, which is for example observable for Denmark, Ireland or Germany.



Annual fluctuation in electricity generation from hydro power (availability of water for electricity generation) due to climate conditions. In 2011, lower water availability for hydro power compared to 2010 resulted in higher shares of fossil fuels for example in Portugal, Spain, Romania, Bulgaria, Slovakia and Greece.



Incremental electricity demand in transition countries is predominantly covered by the use of coal, which is especially the case in China and Turkey.

The following three figures show the development of the energy carrier mix for electricity generation in Germany, the European Union and the United States between 1998 and 2011.

Figure 2-1: Development grid mix in Germany (left) and EU-27 (right) [Eurostat 2013]

The reference year was 2010 in the GaBi Databases 2013 respectively.

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Figure 2-2: Development grid mix United States (EIA 2013)

Compared to 2010, the use of renewable energy sources for electricity generation in Germany in 2011 has increased from 17.8% in 2010 to 21.5%5 in 2011. Main driver for the increase in renewable energies were wind power and photovoltaic. The generation of electricity from photovoltaic has had annual growth rates of 60-70% in the last three years and contributes to 3.2 % of the grid mix (1.9% in 2010). The share of electricity from wind power increased from 6% in 2010 to 8% in 2011. The German grid mix of 2011 also reflects the nuclear phaseout decision made after the Fukushima nuclear disaster in March 2011 and the shutdown of the seven oldest nuclear power stations in Germany. As a consequence the share of nuclear power dropped from 22.5% in 2010 to 17.8% in 2011. Despite some EU Member States with relevant changes in their electricity mix, the overall production share in the European Union remained relatively stable between 2010 and 2011. The use of natural gas for electricity production dropped from 22.8% in 2010 to 21.3% in 2011 and the use of hydro power dropped from 11.9% to 10.3%. This was compensated by a two percent lower demand in electricity and higher production from wind power (4.5% in 2010, 5.5% in 2011), photovoltaic (0.7% in 2010, 1.4% in 2011) and lignite (9.9% in 2010, 10.7% in 2011). Main change in the grid mix of the U.S. electricity generation was a lower electricity output from hard coal power plants (43.5% in 2010, 40.9% in 2011) due to higher production from existing hydro power stations and substitution by natural gas power stations. The share of wind power increased from 2.2 in 2010 to 2.8 in 2011. Gross production and consumption remained stable. The following figures show the absolute primary energy demand (PED), as well as global warming potential (GWP), acidification potential (AP) and eutrophication potential per kWh of supplied electricity in Germany, the European Union and the United States. In Germany, the GWP for the electricity mix increased from 593 g/kWh (2010) to 610 g/kWh (2011). Although the electricity production from renewables has been grown by 21%, it has mainly substituted nuclear power with

50% of electricity from waste is accounted as renewable energy

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a low carbon intensity. Overall, a 2% higher use of combustible, fossil fuels and slightly lower efficiencies for coal power plants led to the 3% higher GWP and fossil primary energy demand per supplied unit of electricity in 2011. The lower share of coal use, for electricity generation in the U.S., resulted in a 5% lower GWP per unit of electricity. The lower AP for electricity in Germany is related to an updated supply of biogas. For the U.S. the decreasing AP (-5.9% compared to 2010) and EP (-3.4% compared to 2010) relates to lower use of hard coal for electricity generation.

Figure 2-3: PED, EP, GWP and AP of electricity grid mixes DE, EU27 and US

In the following tables the energy carrier mix between 2010 and 2011 for selected, noteworthy countries, or those with important changes, are displayed.

GaBi Databases ‘14 Table 2-1: Energy carrier mix for electricity generation – noteworthy EU countries

[%] Nuclear Lignite Hard coal Coal gases Natural gas Heavy fuel oil Biomass (solid) Biogas Waste Hydro Wind Photovoltaic Solar thermal Geothermal Peat

France

Germany

Great Britain

Italy

Poland

Spain

2010 2011 2010 2011 2010 2011 2010 2011 2010 2011 2010 2011 75.3 78.7 0.0 0.0 4.1 2.7 0.5 0.4 4.2 4.8 1.0 0.6 0.3 0.3 0.2 0.2 0.7 0.8 11.8 9.0 1.8 2.2 0.1 0.4 0.0 0.0 0.0 0.0 0.0

0.0

22.5 23.3 18.8 1.6 13.9 1.3 1.7 2.9 1.7 4.4 6.0 1.9 0.0 0.0

17.8 24.8 18.6 1.6 13.8 1.1 1.9 3.5 1.8 3.9 8.1 3.2 0.0 0.0

16.3 0.0 28.3 0.3 45.9 1.3 1.2 1.5 0.8 1.8 2.7 0.0 0.0 0.0

18.8 0.0 29.5 0.3 39.9 1.0 1.5 1.6 0.9 2.3 4.2 0.1 0.0 0.0

0.0 0.3 12.9 1.6 50.7 7.2 0.8 1.7 1.4 18.1 3.0 0.6 0.0 1.8

0.0 0.1 14.7 1.8 47.9 6.6 0.8 2.0 1.5 15.8 3.3 3.6 0.0 1.9

0.0 30.9 55.8 1.1 3.0 1.8 3.7 0.3 0.2 2.2 1.1 0.0 0.0 0.0

0.0 32.1 53.4 1.0 3.6 1.5 4.4 0.3 0.2 1.7 2.0 0.0 0.0 0.0

20.5 0.4 7.9 0.3 31.9 5.5 0.8 0.2 0.5 15.0 14.6 2.1 0.2 0.0

19.8 1.4 13.7 0.4 29.0 5.1 1.0 0.3 0.5 11.3 14.6 2.5 0.4 0.0

0.0

Table 2-2: Energy carrier mix for electricity generation – noteworthy non-EU countries

[%] Nuclear Lignite Hard coal Coal gases Natural gas Heavy fuel oil Biomass (solid) Biogas Waste Hydro Wind Photovoltaic Solar thermal Geothermal Peat

Brazil

China

India

Japan

Russia

USA

2010 2011 2010 2011 2010 2011 2010 2011 2010 2011 2010 2011 2.8 1.2 0.2 0.8 7.1 3.1 6.1 0.0 0.0 78.3 0.4 0.0 0.0 0.0

2.9 1.1 0.2 1.1 4.7 2.8 6.0 0.1 0.0 80.6 0.5 0.0 0.0 0.0

1.8 0.0 77.0 0.6 1.7 0.3 0.1 0.0 0.2 17.3 1.1 0.0 0.0 0.0

1.8 0.0 78.4 0.5 1.8 0.2 0.7 0.0 0.2 14.8 1.5 0.1 0.0 0.0

2.7 2.2 65.7 0.1 12.3 2.8 0.2 0.0 0.0 11.9 2.1 0.0 0.0 0.0

3.2 6.6 61.2 0.1 10.3 1.2 2.7 0.0 0.0 12.4 2.3 0.0 0.0 0.0

25.8 0.0 23.6 3.6 27.2 8.7 1.5 0.0 0.6 8.1 0.4 0.3 0.0 0.2

9.7 0.0 23.5 3.2 35.6 14.6 2.7 0.0 0.8 8.7 0.4 0.5 0.0 0.3

16.4 6.3 9.0 0.7 50.1 0.9 0.0 0.0 0.3 16.2 0.0 0.0 0.0 0.0

16.4 6.2 8.6 0.7 49.2 2.6 0.0 0.0 0.3 15.9 0.0 0.0 0.0 0.0

0.0

0.1

19.2 18.9 2.0 2.2 43.5 40.9 0.1 0.1 23.3 24.0 1.1 0.9 1.0 1.0 0.2 0.2 0.5 0.5 6.5 7.9 2.2 2.8 0.1 0.1 0.0 0.0 0.4 0.4 0.0

0.0

GaBi Databases ‘14 Table 2-3: Energy carrier mix for electricity generation – countries with high changes

[%] Nuclear Lignite Hard coal Coal gases Natural gas Heavy fuel oil Biomass (solid) Biogas Waste Hydro Wind Photovoltaic Solar thermal Geothermal Peat

Denmark

Ireland

Lithuania

Malaysia

Portugal

Romania

2010 2011

2010 2011 2010 2011 2010

2011 2010

2011 2010 2011

0.0 0.0 0.0 0.0 43.8 39.7 0.0 0.0 20.4 16.5 1.9 1.3 8.6 8.7 0.9 1.0 4.3 4.9 0.1 0.0 20.1 27.8 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 14.5 17.0 0.0 0.0 61.9 53.8 2.1 1.5 0.4 0.5 0.7 0.7 0.0 0.0 2.7 2.6 9.8 15.8 0.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 40.7 0.0 44.7 7.7 1.0 0.0 0.0 5.9 0.0 0.0 0.0 0.0

0.0 0.0 13.1 0.0 27.5 5.6 4.1 0.2 1.1 30.6 17.0 0.4 0.0 0.4

0.0 0.0 18.8 0.0 28.4 5.1 4.7 0.3 1.2 23.1 17.5 0.5 0.0 0.4

19.2 32.9 1.2 0.1 12.0 1.1 0.2 0.0 0.0 32.8 0.5 0.0 0.0 0.0

18.9 38.6 1.2 0.0 13.4 1.2 0.3 0.0 0.0 24.0 2.2 0.0 0.0 0.0

0.0

7.9

8.0

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 34.2 0.0 0.0 0.2 57.9 58.4 56.5 11.8 4.6 2.9 2.1 2.7 1.0 0.6 0.8 0.0 0.0 0.0 0.0 23.5 23.1 5.2 4.1 10.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0

The following list summarises countries with significant changes in the energy carrier mix for electricity generation: 

Denmark (DK)  Further decrease of hard coal from 43.8 % in 2010 to 39.7 % in 2011 (48.6 % in 2009), natural gas down from 20.4 % to 16.5 %, wind up from 20.1 % to 27.8 %.



China (CN)  The incremental electricity production in 2011 compared to 2010, mainly realised by new coal power plants, resulted in a substantial drop of hydro power from 17.3% to 14.8% within the grid mix, although the output from hydro power decreased only slightly from 2010 to 2011. Apart from hydro power, the share of renewable energies increased from 1.3% to 2.3%.



France  Nuclear up from 75.3 % to 78.7 %, hard coal down from 4.1 % to 2.7 %, hydro power down from 11.8 % to 8.9 %.



Great Britain (GB)  Natural gas down from 45.9% to 39.9%, nuclear up from 16.3 % to 18.7 %, hard coal up from 28.3 % to 29.5 %, wind power up from 2.7 % to 4.2 %.



India (IN) Main change in India is due to different classification in coal, which resulted in a higher lignite share and a lower hard coal share. Overall, the share of coal remained stable.



Ireland  Natural gas down from 61.9 % to 53.8 %, hard coal up from 14.5 % to 17 %, wind power up from 9.8 % to 15.8 %.



Japan (JP)  The Fukushima nuclear disaster resulted in a successive shut down of all nuclear power station in Japan. As a result, the share of nuclear power decreased from 25.8% in 2010 to 9.7% in 2011. Nuclear power was substituted mainly by electricity from natural gas and fuel oil. The share for

GaBi Databases ‘14

natural gas increased from 27.2% to 35.6% and for fuel oil from 8.7% to 14.6%. In addition, the gross production and consumption of electricity decreased by 6% compared to 2010. 

Lithuania (LT)  After the shutdown of Lithuania’s sole nuclear power station in 2009, Lithuania is further restructuring its electricity supply. Fuel oil down from 11.8 % to 4.6 %, wind up from 4.1 % to 10.4 %.



Malaysia (MY)  In Malaysia, an ongoing trend is observable to substitute natural gas as energy carrier for electricity generation by hard coal and fuel oil, partly also to cover incremental electricity demand. Hard coal up from 34.2 % to 40.7 %, natural gas down from 56.5 % % to 44.7 %, fuel oil up from 2.9% to 7.7%.



Portugal (PT)  Lower production from hydro power plants (down from 30.6% to 23.1%) was substituted mainly by hard coal (up from 13.1% to 18.8%).



Romania (RO)  Lower production from hydro power plants (down from 32.8% to 24.0%) was substituted by lignite (up from 32.9% to 38.6%) and natural gas (up from 12.0% to 13.4%).



Spain (ES) Also in Spain, lower production from hydro power in 2011 compared to 2010 (down from 15.0% to 11.3%), resulted in a higher production share from hard coal (7.9% to 13.7%).

The current legislative situation (e.g. EC 2009, national incentive systems for renewable energies), the decision or discussion about nuclear power phase-out in some countries and the shale gas boom in the USA will result in an ongoing and intensified development of energy carrier mixes for electricity generation in the coming years and decades. Development GWP for electricity grid mix datasets The following figures show the percentile changes of the greenhouse gases for the upgraded electricity grid mixes in the GaBi Professional database and the Extension module Energy compared to the 2010 data, as well as the absolute greenhouse gas emissions per kWh in the 2014 databases (reference year 2011).

Figure 2-4: Changes in GWP of electricity grid mix datasets in GaBi Professional 2014

GaBi Databases ‘14

Figure 2-5: Absolute GWP of electricity grid mix datasets in GaBi Professional 2013 & 2014

For most cases, the changes in the national electricity grid mix datasets are related to the upgraded energy carrier mix or imports: 

Austria (AT)  The GWP increased from 341 g/kWh to 388 g/kWh (+14 %) despite a relatively stable energy carrier mix. The main reason for the change is related to higher imports from countries with higher carbon intensity for their electricity supply, mainly Germany and Czech Republic to cover lower gross production.



Belgium (BE)  The decrease of the GWP in 2010 compared to 2011 is related to an higher share of nuclear power (50.5% in 2010 and 54.5% in 2011) and renewable energies (8.7% in 2010 and 10.9% in 2011) in the electricity mix of Belgium.



Bulgaria (BG)  Similar to other countries, lower water availability resulted in lower electricity generation from hydro power station. In 2010, the share from hydro power was 12.2% compared to 7.3% in 2011. As consequence, more electricity from lignite was produced in 2011.



Denmark (DK)  As described above, Denmark has substituted electricity from hard coal and natural gas by an increase in electricity generation from its wind power installations. The decreasing share of fossil fuel for power generation (down from 66.1% in 2010 to 57.5% in 2011) resulted in a 21% lower GWP per unit of electricity in 2011.



Finland (FI)  Compared to 2010, Finland has reduced the usage of fossil, combustible fuels including peat from 41.5% to 35% in 2011. The electricity was substituted in equal parts by nuclear power and renewable energies.



France (FR)  The GWP for electricity from France has been reduced from 123 g/kWh in 2010 to 95 g/kWh in 2011. Although, the output from hydro power station was 25% lower in 2011 compared to

GaBi Databases ‘14

2010, the GWP was reduced due to a higher share of nuclear power and a 35% reduction in coal use. In addition, net losses have been reduced (from 7.0% to 6.1% of the supply), less electricity from neighbouring countries (with higher GWPs per produced unit of electricity) has been imported and the efficiencies of hard coal and natural gas power plants have been increased. 

Malta (MT)  The 10% decrease in GWP for the electricity supply in Malta is related to a relevant reduction in grid losses from 19.4% of the supply in 2010 to 11.7% in 2011.



Norway (NO), Sweden (SE)  The high relative GWP decrease for, Sweden and Norway is a result of the high sensitivity of changes in the energy carrier mix on electricity grid mixes with low carbon intensities. In both countries, a slightly higher output of electricity from hydro power station resulted in a reduction of combustible, fossil fuel usage for electricity generation. In addition, the import of electricity from neighbouring countries with higher GWPs per produced unit of electricity was reduced.



Portugal (PT), Romania (RO), Slovakia (SK), Spain (ES)  The increased GWP per produced unit of electricity is related to the lower output from hydro power stations, which has been compensated mainly by electricity from power stations using combustible, fossil fuels. In Romania and Slovakia, a higher gross production (approx. 3%) also contributed to a higher share of combustible, fossil fuels.

The following two figures illustrate the relative and absolute changes of the GWP for the electricity grid mix datasets in the extension module Energy.

Figure 2-6: Changes in GWP electricity grid mix datasets in GaBi Extension module Energy2014

GaBi Databases ‘14

Figure 2-7: Absolute GWP of electricity grid mix datasets in GaBi Extension module Energy 2013 & 2014 

Argentina (AR)  The increase in GWP per produced unit of electricity is mainly due to a 3% increase in gross production, which is mainly covered by electricity from power stations using natural gas and fuel oil.



Brazil (BR)  Despite a 3% higher gross production of electricity, the share of hydro power has been increased from 78.3% in 2010 to 80.6% in 2011. As a consequence, the production from power plants using combustible, fossil fuels has been reduced and the share dropped from 12.4% to 9.8%



Canada (CA)  The GWP decrease in Canada is mainly due to a relevant reduction in transmission losses down from 11.7% of the electricity supply to 6.0%. Although the gross production increased by 5% (consumption increase of 10%) the share of hydro power could be increased substituting mainly electricity from coal.



Indonesia (ID)  Main drivers for the increased GWP per unit of electricity is an increase in gross production (+7%), which is mainly covered by electricity from lignite, and a decreased output of electricity from hydro power stations.



Japan (JP)  The changes in the GWP of the Japanese electricity supply are influenced from the Fukushima nuclear disaster in March 2011. The switch from nuclear power stations (see also discussion above) to natural gas and fuel oil power plants is the main driver for the increased GWP (501 g/kWh in 2010, 596 g/kWh in 2011).



South Africa (ZA)  The decreasing GWP for electricity in South Africa is related to higher efficiency of hard coal power plants (up from 34% in 2010 to 36% in 2011).

In addition to the electricity grid mix datasets in the GaBi Prof and the extension module energy, Figure 2-8 and Figure 2-9 illustrate changes of the GWP for the electricity grid mix datasets in the extension module Full US. In this extension module, electricity grid mix datasets are included for the 22 FERC sub regions and 5 US sub grids. The reference year in the GaBi databases 2014 for these datasets is 2010 for all data concerning energy

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carrier share for electricity generation, import of electricity between sub regions/grids and emission factors of the power plants compared to 2009 for the GaBi databases 2013, using eGrid 9th edition V 1.0 released 2014 [EPA 2014] as well as FERC 714 data [FERC 2014]. The reference year for the energy carrier mixes (coal, crude oil and natural gas) in the GaBi databases 2014 is 2011 compared to 2010 in the GaBi databases 2013.

Figure 2-8: Changes in GWP electricity grid mix datasets in GaBi Extension module Full US 2014

Figure 2-8 illustrates the relative changes of the electricity grid mix data sets of the Full US extension module in the GaBi databases 2014 compared to the GaBi databases 2013 (GaBi database 2013 = 100%). Figure 2-9 illustrates the absolute GWP of one supplied kWh of electricity within one of the 22 FERC sub regions or 5 US grids for GaBi Databases 2013 and 2014.

Figure 2-9: Absolute GWP of electricity grid mix datasets in GaBi Extension module Full US 2013 & 2014

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The following explanation can be given for changing greenhouse gas emissions related to the supply of electricity in the FERC sub regions / U.S. subgrades (for datasets with relative changes of more than ± 5% in GWP): 

AKGD  Higher usage of natural gas (66% in 2009, 69.4% in 2010) instead of fuel oil, more electricity from hydro power, 3% higher efficiency for fuel oil power plants.



AKMS  Hydro power up from 63.9% in 2009 to 67.5% in 2010, wind power up from 0.5% to 0.9%, lower usage of fuel oil, higher share of electricity output from CHP with same efficiency.



CAMX  Increase of renewable share from 22.8% in 2009 to 25.5% in 2010, increase of net efficiency for natural gas power plants from 46.5% in 2009 to 49.3% in 2010.



MROW  Increase of renewable share from 14.1% in 2009 to 19.1% in 2010 (wind and hydro), coal use decreased from 68.6% to 62.1%.



NYISO  Lower output from hydro power stations (19.8% in 2009 to 17.8% in 2010) and nuclear power stations (31.5% in 2009 to 29.8% in 2010), more imports from NEWE with higher carbon intensity for electricity generation instead of Canada.



RFCW  Installation of wind power resulted in a decreasing share of electricity from coal (99.9% in 2009 to 92.3% in 2010).



Alaska  see AKGD & AKMS above

Additional important changes in the electricity grid mixes for FERC sub regions and U.S. subgrades: 

AKGD/AKMS  Important reduction of SO2 emission factor (156 kg/TJ fuel input to 6 kg/TJ fuel input) for fuel oil power plants in Alaska, due to usage of ultra-low sulphur fuel oil. Overall -15/-20% lower AP for electricity supply



RFCW  Increase of SO2 emission factor for hard coal power plants from 700 kg/TJ input to 1150 kg/TJ. Overall 40% higher AP for electricity supply



SRMV  increase of NOX emission factor for Power Plant PPG Powerhouse C from 118 kg/TJ in 2009 to 937 kg/TJ in 2010. Overall +20% EP for electricity supply.



Various sub regions/sub grids  increasing share of wind power and photovoltaic leads to higher ADP fossil values. Higher share of renewables lead to reduced non-renewable primary energy demand (PED) values and to higher renewable PED values.

GaBi Databases ‘14

Further developments in electricity datasets

Changes in electricity data sets from specific fuels (e.g. electricity from hard coal): The IEA statistics are a valuable and established basic source of energy modelling in LCA. However it is not direcly LCA data and needs to be transformed into LCA consistent data. Power plant efficiencies, calculated based on IEA statistics, can significantly vary between the reference years. The following reasons are considerations of PE experts why the IEA statistic vary over time: 

final or periodic shutdown of specific power plants,



different share between CHP and direct production over time (e.g. different heat demand over time),



technology measures to increase efficiency



unregular usage over time (e.g. used as reserve capacity),



rounding effects (if little fuel is used),



correction of statistical errors



a combination of several of the factors listed above

These aspects must be carefully considered before interpreting and comparing results.

GaBi Databases ‘14

2.2

Inventories for primary energy carriers Primary energy carrier processes after the upgrade



The upgrade of supply mixes (domestic production and origin of imports) for natural gas and crude oil contains relevant changes for certain countries. An increase or decrease of crude oil and natural gas from countries with high environmental impacts (e.g. Nigeria, Russia, Libya and Iraq) and the supply mix can affect impacts. Additionally higher impacts for natural gas can be the result of a higher share of LNG within the overall natural gas supply mix of a country. In addition, the share of production technologies and share of conventional and unconventional crude oil/natural gas within the domestic production or exporting country may have changed. Supply mixes with noteworthy changes are: o

Ireland crude oil mix  decreasing share of crude oil from Norway (75% in 2010, 57% in 2011) and increasing share from Libya results in higher GWP (+27%) and POCP (45%).

Belgium natural gas mix  decreasing share of LNG imports from 26.4% in 2010 to 12.8% in 2011 results in decreasing GWP (-31%).

Great Britain natural gas mix  decreasing domestic production results in higher LNG imports (up from 17.3% in 2010 to 24.5% in 2011) and significant higher relative impacts (+37% GWP, +63% POCP).



Reduced sulphur dioxide emissions (and related acidification potential) for crude oil and natural gas supply due to corrected SO2 emissions from flaring.



Relevant changes (e.g. GWP, AP, EP, POCP) for hard coal mixes, like for Austria, Norway and New Zealand are linked to updated supply mixes (changed share of domestic production or different origin). Changes for lignite mixes are linked to changes in the domestic electricity supply, e.g. Romania.



Changes for diesel and gasoline mixes (at refinery and filling stations) are related to the following updates:



The optional inclusion of direct land use changes, which can lead to changes in the GWP of diesel and gasoline mixes containing biodiesel or bio gasoline based on sugar cane from Brazil or palm oil from Malaysia or Indonesia. For further information on land use change please refer to the GaBi Modelling Principles, which can be found online.

New statistics have been used to update feedstock/biofuel supplies of country specific diesel or gasoline mixes. It should be noted that the EP of biofuels from crops can be significantly higher than from fossil fuels. As a consequence, small changes of the biofuel share in the diesel mix (e.g. 2% instead of 1% from a specific feedstock) can lead to high relative changes for the fuel mix.

Updates in the model used to assess the impacts of crop cultivation, which is especially relevant for eutrophication.

Updates in the crude oil supply.

Changes for other refinery products are mainly related to changes in the background system (e.g. crude oil supply).

GaBi Databases ‘14

2.3

Organic and inorganic intermediates

Possible updates and upgrades of technologies may happen on 3 different levels. In the upgraded datasets most cases multiple effects can be observed. Due to possible breakthrough technologies, due to improvements in the foreground system of the existing technology, due to changed situations in a production or consumption mix of different technologies providing the same product and last but not least due to changes and updates in the background system of resources and energy supply. The needed information to check and update the technologies and supply chains are based on the knowhow of our engineers as well as on input of our customers. The provided documentation of GaBi datasets serves as viable basis to discuss supply chain aspects and demands. Our experts use scientific and engineering knowhow (e.g. thermodynamic laws, the mass- and energy conservation, stoichiometric balances, combustion calculation ans alike) as basis to maintain and update chemical LCA data. All chemical technologies were checked in this sense. In relation to possible breakthrough technologies no major new technologies or significant process improvements on existing technologies were identified by PE experts between 2013 and 2014. For chlorine and sodium hydroxide, used as basis of many downstream organic and inorganic chemicals the situation in the consumption and production mix has considerably changed. The association Eurochlor provides publicly available valuable information concerning different technologies of chlorine and sodium hydroxide production for many Europea countries. Considerations with our review partner DEKRA lead to the update of these datasets (incl. an European dataset based on the production shares of the individual countries) according to the information mentioned. Changes in the background system effects mainly relate to: 

Upgraded distribution on primary, secondary and tertiary fossil resource extraction like oil and gas



Upgraded market share of imported fossil resources



Upgraded distribution of the type of resources used (oil, gas and coal, etc.)



Increased amount of renewable feedstock and energy supply

Changes in the energy sector and supply chain are in most cases the drivers for overall improvement throughout several impact categories. The intermediates are directly influenced by the upgraded performance of the energy supply and the important resource, crude oil and natural gas.

GaBi Databases â&#x20AC;&#x2DC;14 JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-1163

Improvement

Chlorine and Sodium hydroxide mix composition

Changes within chlorine and sodium hydroxide mix of the European countries were identfied in the data and publications of Euro Chlor. It was found that the production technology mix per country has significantly changed. The share of the used technology (amalgam/membrane/diaphrame) is documented in the datasets.

Most affected is Spain, where the impacts increase by about 45% in AP and about 17% for GWP. However, this leads back to the updated energy mix.

Professional database, Extension database Ib: inorganic intermediates, Extension database XV: Textile finishing

In France and Belgium the impacts decrease.

The EU-27 Chlorine mix was modelled according to the actual shares of the different European production countries with their different individual technology shares. After discussions with the reviewer PE experts concluded that this represents the actual situation most adequate. EU-27 Sodium hydroxide was updated according to the actual shares of the different European production technologies (without modelling any country in specific detail).

2.4

Inventories for metal processes

In the 2014 upgrade, aluminium data was revised, based on newer available information from the association EAA (European Aluminium Association). The electricity supply of the Rare earth electrolysis was adapted to the regional geographic boundary conditions in China. The aerospace center DLR (Deutsches Zentrum fĂźr Luftund Raumfahrt e. V.) provided information to PE concerning magnesium production. This data was integrated into GaBi database as three new datasets. Further changes in the metals supply chains primarily relate to the update of the background system (such as energy, intermediates) as PE experts had no indications for other significant foreground process changes or improvements in the metal sector than mentioned above.

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-720

Improvement

Rare Earth Electrolysis electricity mix

The increased demand and focus of Chinese data in the last years lead to a revisiting of the Chinese rare earth metal report of 2009 (see GaBi documentation). After discussion with our metals and Chinese experts it was decided to adapt the electricity mix to a closer regional geographic boundary. A higher share of hydro power is used now.

Impacts decrease. GWP and EP by about 34%, POCP by about 33% AP by about 15%, and Primary Energy by about 19%

Extension database VI: precious metals

GaBi Databases â&#x20AC;&#x2DC;14 GC-979

Improvement

Aluminium datasets

Updated data is available for aluminium production in Europe and Germany, based on "Environmental Profile Report for the European Aluminium Industry", EAA, 2013. Updated aluminium sheet, foil, extrusion profile, ingot (consumption mix) and recycling.

Generally the impacts decrease. For extrusion profile (DE and EU) the impacts increase slightly. For the German and European ingot mix, the impacts decrease significantly, except for ODP, where they increase (60% for EU and 200% for DE). This is related to a higher percentage of French nuclear power in the electrolysis step.

All where aluminium is used directly and as an upstream material (Construction, Electronics, Professional)

GC-992

Improvement

Modelling of silver

The initial goal of updating the water balance lead to a complete reassessment of the dataset by PE metal experts. Specifically the copper-silver ore extraction was newly modelled into a LCA unit process according to the different industry sources mentiond in the dataset documentation.

Impacts change: GWP, AP, EP, POCP decrease by about -50%, Primary energy by about -15%

Extension database VI: precious metals

GC-1194

New objects

Inventory and impacts of "Cast iron part" and "Steel cast part alloyed"

As cast iron can be produced in an electric arc furnace (EAF) as well as in a cupola furnace, there are now 2 GaBi standard processes available. The already existing party aggregated data set "Cast iron part" has been renamed to "Cast iron part (automotive)" and is a worst case assumption based on the cast steel process and uses an electric arc furnace including high electricity consumption. The new aggregated data set "Grey cast iron (GG) part (sand casting)" is based on the usage of a cupola furnace with a lower environmental impact and is now available in the professional database.

New objects, no changes

Professional database

GC-1277

New objects

Unit processes of magnesium production Deutsches Zentrum fĂźr Luft- und Raumfahrt e. V. (DLR) (German aerospace center)

The following unit processes were added to the folder "Industry data\DLR" IL Magnesium production, electrolysis CN Ferrosilicon production CN Magnesium production, pidgeon process

New objects, no changes

Professional database

2.5

Inventories plastic processes

The environmental profile of polymers is largely influenced by the monomer impacts. PE experts checked whether the polymerisation technologies are still representative. To our knowledge no completely new process designs in polymerisation are in industrial use in comparison to last year. This means the polymerisation technologies in the GaBi Databases are still representative. This is supported by our experience within the chemistry and polymer industry.

GaBi Databases ‘14

This year PE experts updated specifically the MMA production process. Higher process efficiency lead to decreased demand of thermal energy for the production of PVAL in recent times. This was adapted accordingly in the related unit process. Three new datasets were added to the Extension database XIX: Bioplastics: EU-27: Recycling of aliphatic/aromatic copolyester, EU-27: Aliphatic/aromatic copolyester, DE: Biopolyamide (PA) 6.10 Further the dataset “EU-27: Plastic granulate secondary (from post-consumer plastic waste, via grinding, metal separation, washing, pelletization)” was added due to growing customer demand concerning information of plastics recycling. More specific aspects are mentioned in the following table JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-668

Improvement

PMMA production data

MMA production process was adapted by PE INTERNATIONAL polymer experts with related industry experience. Carbon monoxide emissions in the MMA process were siginificantly reduced as we have indication for improved processing conditions and further end-of-pipe measures.

Due to the reduction of CO output, POCP decreases by about 40% (see also GC-1159 in construction database)

Professional database, Extension database XVII: Full US

GC-707

Improvement

Thermal energy demand for PVAL from vinyl acetate

Steam input was modelled with an extreme worst-case scenario before. The thermal energy demand for the production of PVAL was adapted by PE experts after extensive internal discussion and validations towards a more realistic assumption. The process conditions now represent rather a realistic, whilst still conservative scenario. The steam input was reduced from 86 MJ to 7,7 MJ based on an updated energy balance due to an internal calculation. Boiler feed water and water vapor was adapted according to the new steam input value to correct the mass balance.

GWP, AP and Primary Energy decrease by about 50%

Extension database VII: plastics, Extension database XVII: Full US

GC-1088

Bug

Sugar cane plans: carbon balance of datasets using sugar cane in bioplastics and plastics DB

The carbon balance in the sugarcane cultivation and its further processing steps was harmonized. This was done by PE experts with agricultural and processing background by closing carbon cycles by considering the carbon content of plant by-products being either allocated into other products or being reused as organic fertilizer in the field. This correction of the carbon balance affects the datasets which are part of the bio-plastics extension database (see also chapter 2.8).

By modifying the model, the results of the impact categories ODP, HTP and OCP increased around 30%, the GWP remains the same and AP and EP were reduced, the main reason of changes is that the new model uses updated values of the most critical parameters in the model: yield, fertilizers, diesel consumption

Extension database XIX: Bioplastics

GaBi Databases â&#x20AC;&#x2DC;14

2.6

Inventories for end-of-life processes

The generic end-of-life processes were checked for their validity. Using the actual report from CEWEP for Europe and ITAD for Germany, the energy efficiency of the waste incineration plants has been reworked. The landfill sites have been reworked concerning biogenic carbon and water, as well as the density of the incorporated waste. The water balance has been harmonized by adding related rain water in and output to the landfills. In the following table more details can be found. GC-916

Improvement

Granulator - minimum and maximum threshold for throughput

Lower and upper limits for free parameter were added for easier and safer use of dataset by customer

Does not change the results

GC-1134

Improvement

EU-27 Municipal waste landfill sites

Due to changed waste composition, the modelled density of the incorporated waste was reduced to 1200 kg/m3, which is the actual maximum in the GaBi landfill model. This was done for the following data sets: DE: Landfill for inert matter (Steel) EU-27: Landfill for inert matter (Steel) DE: Landfill for inert matter (Construction waste) EU-27: Landfill for inert matter (Unspecific construction waste)

Lower density of incorporated waste leads to less waste per volume deposited. This results in higher impacts for reduced waste desities.

In the data set "EU-27: Landfill of ferro metals" the density of the incorporated waste was reduced from the metal elementary density to the actual waste density of 1200 kg/m3.

GC-1272

Improvement

Landfill datasets

GC-1064

Improvement

Efficiency plants

incineration

Due to the change of the density of the incorporated waste, the common impacts like GWP, AP, EP etc. increase by approx. 20%

EU-27: Landfill of ferro metals: Due to the reduction of density of the incorporated waste, impacts increase about the factor 4 â&#x20AC;&#x201C; 6. However the absolute value (and impact on overall result) may still be relatively small for landfill processes in a LCA.

The following improvements have been done in the landfill models by PE end-of-life experts: Correction of parameter formula and setting in landfill model related to carbon storage and release in landfill body and landfill gas treatment. Specification of methane related emissions from landfill operations as bio methane emissions Harmonization of water balance by adding related rain water in and output flows into landfill

Mainly reductions of CO2 impact of about 20 to 50% for household and commercial waste, and acidification and eutrophication impact reductions of about 15 to 30%. No relevant impact on energy demand. However the absolute value (and impact on overall result) may still be relatively small for landfill processes in a LCA

The energy balance/energy efficiency of the European and German waste incineration plants were updated. The energy efficiency of the European and German domestic waste incineration plant were adapted based on the actual CEWEP energy report 2007-2010 for Europe and ITAD (2011) for Germany. Chang-

The variations are modest. In the sum the energy output varies between -11% to +6% depending on the type of incineration good.

GaBi Databases ‘14 ing the relevant parameters in the GaBi domestic waste incineration plant leads to an upgraded energy efficiency and higher energy share of the net electricity and net steam output. Based on the adaption of the parameters in the European and German domestic waste incineration plant, the specific waste incineration plants (e.g. plastic, wood etc.) were also adapted for Europe and Germany. Looking at the datasets of the incineration processes, the output flows “electricity from waste incineration” and “steam from waste incineration” now increased in the energy amount (thus leading to a higher credit).

European incineration processes: - Decrease of the energy efficiency (steam and electricity in total) - higher share of net electricity output - The high gross efficiency for specific waste incinerations was calculated with a worst case approach. The share of the electricity consumed by the incineration plant itself was modelled too conservative. This resulted in a higher net energy output, especially for waste with a high calorific value (e.g. plastics). This was updated by reducing the own consumption of the incineration model which results in a reduction of the net energy output German incineration processes: - Increase of energy efficiency (steam and electricity in total) - The high gross efficiency for specific waste incinerations was calculated with a worst case approach. The share of the electricity consumed by the incineration plant itself was modelled too conservative. This resulted in a higher net energy output, especially for waste with a high calorific value (e.g. plastics). This was updated by reducing the own consumption of the incineration model, which results in a reduction of the net energy output

Remark: the increase of the energy efficiency and the reduction of the net energy output due to the improvement showed a compensatory effect for specific wastes. E.g. for polyethylene, there is hardly any change of the net energy output

2.7

Inventories for electronic processes

All data and models have been checked by PE electronic experts regarding technological upgrades and were identified as still representative for their technology descriptions in 2014. In order to reflect the rapid technology developments a further connector dataset was added to the standard databases. More connector and cable datasets are available on demand.

GaBi Databases ‘14

According to PE electronic experts any possible differences when comparing the results of impact categories with same results for the year 2013, were due to changes in background data in the metals and energy sector (see corresponding chapters in this document). Specific aspects are mentioned in the following list. GC-963

Improvement

Negative results in ADP Elements for some Electronics datasets

Lead frame for electronics active components only considered copper recycling, but used different metals as input materials. The credits for copper recycling, in the category ADPe, are higher than for other metals, what could generate the negative values. This has been changed due to a proposal of PE electronic and related end-of-life experts: now copper, steel and aluminium are recycled to 75%, which represents actual recycling levels in a more realistic way. All the other materials and the remainder goes to landfill. All processes using the lead frame are affected.

Changes in ADPe

GC-1141

Improvement

Electronic components use PU foam as material

PU foam was used in some electronics plans. This dataset was replaced by PU (unfoamed) resin, which represents the application in electronics more adequate. However, this materials correction does not affect major LCA results for now.

No significant changes

GC-1286

Improvement

Electronics Update 2014

1.Electronics Extension DB – Printed Wiring Boards - In the components mixer process of the generic PWB plan model “GLO: Populated printed wiring board (parameterized)”, the parameters and comments for the Capacitor Al-capacitor axial THT were corrected. This increased the precision of the results obtained when using the plan for calculation

No effects on process level, as the plan system is improved.

2.Data on demand – EoL recycling of electronic products The recycling efficiency / loss rate of the metal scrap in the recycling route of electronic products was harmonized and adapted. This was done in the generic model “GLO: Recycling electronic products (mechanical and electronics)” for the steel, copper, aluminium and precious metals recycling route. The following metal scrap loss rates were adapted/defined as efficiency loss rate of the recycling route of electronic scrap between PE electronic and metal experts: loss rate of steel scrap: 5% respectively 1,05 scrap input and 1 kg recycled metal output loss rate of copper scrap: 5% respectively 1,05 scrap input and 1 kg recycled metal output loss rate of aluminium scrap: 5% respectively 1,05 scrap input and 1 kg recycled metal output loss rate of precious metal scrap: 2% respectively 1,02 scrap input and 1 kg recycled metal output

Data on demand The generic model for recycling of electronic parts “GLO: Recycling electronic products (mechanical and electronics)” includes the sub plan “GLO: Recycling of aluminium with credit”. For the aluminium recycling route the updated EAA aluminium recycling process is used in the background model of the process “Aluminium recycling (95% efficiency)”. Due to this change, the common impacts categories like GWP, EP, AP and POCP increases for approx. 20 - 30%. Thus a higher credit is given for recycled aluminium.

GaBi Databases â&#x20AC;&#x2DC;14 GC-908

2.8

New objects

New connector data set

A new connector dataset was modelled, based on updated information on production technology and on the dataset "Mains plug connector CEE 7/16, Type C (15g, 2pins)". This new dataset is called "Connector Schuko CEE 7/16 (15 g, 2 pins)". The previous data set "Mains plug connector CEE 7/16, Type C (15g, 2pins)" {2016f352-f6a9-4ad9-bb557bc1f34fa3a9} is still available, but moved to the folder "Version 2013".

New objects, no changes

Inventories for renewable processes

The renewable processes provided within the GaBi databases are modelled within a comprehensive agricultural model. It considers local and regional aspects of climate, soil and farming practices on the technical side. Further it considers international guidelines, current scientific literature and available databases on the methodological side. The PE agriculture and farming experts maintain and enlarge the model frequently. PE is maintaining one of the most advanced LCA models related to this topic. The datasets related to agriculture and renewable ressources cover all relevant environmental impacts and resource consumptions and provide insight to the environmental impact of agricultural processes. Within the 2014 upgrade, single model aspects, processes, as well as single data, were updated and upgraded when new methods or data were identified by the PE experts. Part of the 2014 annual upgrade process consisted of regular checks in order to improve the available data. This year we especially focussed on the hemp cultivation in Germany and corn cultivation in the USA and Germany. Where applicable, datasets were updated and documention improved. The processing of agricultural products downstream in the value chain was also addressed in this yearâ&#x20AC;&#x2122;s upgrade. Some of the agrarian world commodities prices used in economic allocation were also updated. With this yearâ&#x20AC;&#x2122;s upgrade, PE INTERNATIONAL has included in the GaBi software a flow to account the emissions due to the land use change in all the agrarian models. New impact categories have also been added with this update. Now it is possible to analyze the global warming potential including or excluding the emission from land use change. Additionally, PE INTERNATIONAL has updated the emissions from land use change in all available datasets. The raw data used follows the method described in the PAS2050-1 and is based on the carbon stock calculations according to IPCC rules. The agricultural model used in the background of all crop datasets was also improved. Updated data of fuel consumed by the machinery in different field techniques was included; consequently, the results for Global Warming Potential changed in some datasets. Another major improvement in the background of all agricultural datasets is the harmonization of the carbon balance in all the crop datasets. Further the downstream processing was checked and the carbon balance harmonized, especially if economic allocation is used.

GaBi Databases ‘14

Finally, with the update 2014 new N2O emission factors were entered in the agrarian modell, specifically in the reference system processes.

JIRA Tracking Number

Issue gory

GC-922

Cate-

Item

Description

Change in results

Improvement

Field technique datasets

The field technique processes were updated with the most recent data from the KTBL book (Faustzahlen für die Landwirtschaft. 14. Auflage. 2009); the major changes have been made on the diesel and time consumption.

The results for the common impact categories GWP, AP, EP, POCP, and ODP change accordingly to new values of diesel consumption and time.

GC-924

Improvement

Agrarian world commodities prices for economic allocation

Where an economic allocation is used, the agrarian commodities prices were updated; the new values represent the most recent prices, they were taken from different literature and statistic sources (such as Index mundi, Malaysian Palm Oil board). A new quantity was created in GaBi (Price 2014).

New prices affect the results in processes where economic allocation is used; the changes vary from product to product. It is attempted that the price ratio between the main product and byproducts is consistent with the ratio of previous prices

GC-918

Improvement

Farm cultivation processes

Based on information from literature sources, PE agricultural experts updated the following agrarian datasets: • Corn cultivation in USA • Corn cultivation in Germany • Hemp cultivation in Germany

Hemp: • Changes applied in seed cultivation plans affect the impact categories AP, GWP and ODP in 10% and the impact categories ADP, EP in 30 – 60%. • Changes applied in straw cultivation plans affect the impact categories AP, GWP and ODP in 20% and the impact categories ADP, EP is 45% • The main reason of changes is lower yields and different sources of Nitrogen (fertilizers) Corn: The variation of the most common impact categories in the corn cultivation in Germany is around the 10%

GC-1165

Improvement

Land use change flows for agrarian processes

On all agrarian plans, information on CO2 emissions from land use change were added in a separate flow "carbon dioxide (fland use change)". This allows a reporting according to several standards, e.g. ISO 14067 to display emissions from land use change seperately.

The flow "Carbon change (land use change)" shows up additionally and can be assessed with newly added impact categories which take this flow into account.

GaBi Databases â&#x20AC;&#x2DC;14 GC-1143

New objects

New fibers to the renewables extension DB

Two new fiber datasets were added to the renewable extension database. Those datasets were modelled using literature sources and internal calculation.

New objects, no changes

IN: Jute hessain net CN: Natural bamboo fibres

2.9

Inventories for construction processes

Foreground data and models have been checked by PE construction experts regarding technological upgrades. Identified technology improvements were updated in the database. Transport standards have been upgraded and distances updated. The cement datasets were updated on basis of the latest environmental report from VDZ (German Cement Institution). Main change is a different energy mix. Glass fibres were remodelled based on the newest Best Available Technology (BAT) document for the glass industry. So far PUR foaming process used 100% R134a. Therefore we assumed an actualized mix of foaming agents. The blowing agent mix is now based on alkanes and ethers. Further we added four datasets for street infrastructure, such as road types and sidewalk, which were created by PE construction experts. This supports the modelling of site specific assessments. Three associations (Deutsche Bauchemie, Verband der deutschen Lack- und Druckfarbenindustrie, Industrieverband Klebstoffe) have developed 37 Model EPDs for construction chemical products covering all relevant construction chemical products in buildings based on the following product groups: 1.

Reactive resins based on polyurethane (PU)

Reactive resins based on epoxy resins (EP)

Reactive resins based on methacrylates

Dispersion-based products (incl. colors)

Sealants based on silicone and polysulfide

Modified mineral mortars

Concrete admixtures

In total, for these model EPDs around 70 datasets have been included in the database containing information for the modules A1-A3 (production, according to EN15804), and if relevant A5 (installation in the building, according to EN15804). Further changes leading back to the background system (energy, intermediates) are responsible for the remaining differences between GaBi Databases 2013 and 2014 for construction. Specific aspects for this years upgrade are mentioned in the following table.

GaBi Databases â&#x20AC;&#x2DC;14

JIRA

Issue Cat-

Tracking

egory

Item

Description

Change in results

Affects Extension

Number GC-1076

module Improve-

Glass fibre model

ment

Glass fibre data sets have been remod-

The results of the data set

Professional

elled based on the availability of the new

show an improved environ-

database,

Best Available Technology (BAT) docu-

mental performance. Due to

Plastics, Ex-

ment for the glass industry.

NO (Nitrogen Monoxide)

tension data-

emission handling in CML,

base

POCP

Construction

impact

becomes

more negative

XIV:

materials, Extension database IX: recycling economy

GC-750

Bug

Scaling of DE: District

Ratio of input amount of natural gas and

GWP and EP increase by

Extension

heating 120-400 kW

lignite was corrected

17%, AP by 10%

database

(EN15804 B6)

XIV:

Con-

struction materials GC-849

Bug

Building

Equipment

There is a mass difference between the

No significant changes

Extension

heat pumps: Manufac-

manufacturing of heat pumps and the cor-

database

turing weight differs

responding End of Life process, which is

XIV:

from

correct. In the manufacturing process of

struction ma-

heat pumps, a substantial amount of plas-

terials

corresponding

End of life weight

Con-

tic pipes is used. Those pipes are not recovered at the end of life of the pump, but remain in the soil. The mass balance was checked and compared with the End of Life process, and changed in three cases: DE: Electric heat pump (Brine-Water, geothermal collector) 10 kW DE: Electric heat pump (Brine-Water, geothermal collector) 20 kW DE: Electric heat pump (Brine-Water, geothermal probe) 10 kW GC-850

Bug

Manufacturing

and

EN15804 uses cut-off approach. In this

Impact of manufacturing

Extension

EoL plan of Stainless

case here, the manufacturing used pri-

process will decrease, while

database

steel chimney

mary input of material, while the End of

now due to higher recycling

XIV:

Life was modelled using cut-off approach.

rate, End of Life will improve

struction ma-

Manufacturing and End of Life were har-

slightly.

terials

Con-

GaBi Databases â&#x20AC;&#x2DC;14

monized, so that it now matches. Additionally the End of life recycling quote was increased from 90% to 95%. GC-1226

Bug

Building

Equipment:

Manufacturing

and

Mass balance between manufacturing

No significant changes

Extension

and end of life differed. The weight for the

database

corresponding End of

following manufacturing processes was

XIV:

life weight

corrected:

struction ma-

DE: Compact fluorescent lamp 18W (ex-

terials

Con-

cluding control gear) DE: Fluorescent lamp T5 14W (EN15804 A1-A3) DE: Fluorescent lamp T5 28W (EN15804 A1-A3) DE: Fluorescent lamp T8 18W (EN15804 A1-A3) DE: Fluorescent lamp T8 36W (EN15804 A1-A3) GC-1585

Bug

CO2 incorporation in

For the following processes, the CO2 bal-

Slight changes to GWP incl.

Extension

timber products

ance was checked and harmonized. The

Biogenic carbon only

database

incorporated carbon, according to the car-

XIV:

Con-

bon content of the product is included in

struction ma-

the LCI.

terials

UA Timber larch (10.7% water content; estimate) BR Timber pine UA Timber pine (10.7% water content) CN Timber pine (10.7% water content) UA Timber spruce (10.7% water content) BR Timber teak CN Timber teak GC-767

Improve-

Simultaneous

lead

After discussion with PE metals and con-

Since only 0,00024 kg of

Extension

ment

and brass scrap input

struction experts, the lead scrap in put was

lead scrap were saturated

database

for "Red brass part

saturated

and this is only 0,02% in

XIV:

weight of the product, it does

struction ma-

not change the results.

terials

(EN15804 A1-A3)"

GC-833

Con-

Improve-

"Polyurethane

foam

The PUR foam was originally modelled us-

Polyurethane foam (PUR):

Extension

ment

(PUR)" foaming pro-

ing 100% R134a as blowing agent. Ac-

Process: DE Polyurethane

database

cess

cording to PE plastics experts, this does

foam (PUR) {9D971202-

XIV:

not reflect the current market situation an-

B93B-441B-B5F7-

struction ma-

ymore. The blowing agent mix has been

2A139C0B3DC4}

terials

Con-

GaBi Databases â&#x20AC;&#x2DC;14

adapted. Now the blowing agent mix is

Due to new Blowing agent

based on alkanes and ethers.

mixture the GWP reduces by 10% and the ODP by factor 30 as no R134a is used as blowing agent anymore. Elastomer Joint tape: Process: DE Elastomer joint tape, polyurethane (EN15804 A1-A3) {7EBA0B29-D81E-4EB98F99-B4ACFE806B46} Due to the change PUR precursor type and the decreased amount of R134a, the Ozone Layer Depletion Potential (ODP) impact will decrease significantly. All other impact categories also show a high decrease, especially the GWP (-80%) and the AP (-50%), excluding the impact of the Abiotic Depletion (ADP elements) which increases.

GC-854

Improve-

Transport processes

The construction extension database in-

Due to improved technology,

Extension

ment

in construction data-

cludes transport processes with the refer-

the environmental impacts

database

base

ence unit of 1 tkm. After discussion and

will decrease.

XIV:

Con-

input from PE transportation experts,

struction ma-

those transport processes were updated.

terials

For Germany, the truck transport processes have been updated to the Euro 5 standard. Additionally, the fuel used has been changed from "Diesel mix at refinery" to "Diesel mix at filling station", which represents the diesel used on the market. For Ukraine, Brazil and China, the truck transports were updated from Euro 2 to Euro 3. GC-884

Improve-

Transport

distances

ment

for gravel and sand

For other mineral materials, such as lava

Impacts decrease

Professional

granulate, the transport distance in GaBi

database,

is 40km. Based on expert input from the

Extension

GaBi Databases â&#x20AC;&#x2DC;14

construction team, the transport distance

database

from the gravel mining to processsing site

XIV:

was changed from 100km to 40km.

struction ma-

Con-

terials Affected in Professional database: CN: Crushed rock 16-32 mm, CN: Crushed sand 0/2, CN: Crushed stone grain 2-15 mm, CN: Gravel (grain size 232mm), CN: Sand 0/2, EU-27: Crushed stone 16/32

Affected in Extension database Construction materials: BR: Crushed rock 16-32 mm, BR: Crushed sand 0/2, BR: Crushed stone grain 2-15 mm, BR: Gravel (grain size 232mm), BR: Sand 0/2, DE: Crushed rock 16-32 mm (EN15804 A1-A3), DE: Crushed sand grain 0-2 mm (EN15804 A1-A3), DE: Crushed stone grain 2-15 mm (EN15804 A1-A3), DE: Gravel (Grain size 2/32) (EN15804 A1-A3), DE: Gravel grain 2-32 mm, DE: Limestone, crushed gravel, grain size 2/16) (EN15804 A1-A3), DE: Limestone, crushed stone fines (Grain size 0/4) (EN15804 A1-A3), DE: Limestone, gravel (grain size 32/63) (ENN15804 A1-A3), DE: Sand (grain size 0/2) (EN15804 A1-A3), DE: Sand grain 02 mm (dried) (EN15804 A1-A3), UA: Crushed rock 16-32 mm, UA: Crushed sand 0/2, UA: Crushed stone grain 2-15 mm, UA: Gravel (grain size 2-32mm), UA: Sand 0/2, UA: Normal mortar GC-1049

Improve-

New information for

Every year VDZ (Verein Deutscher Ze-

GWP, EP, ADPf increases

Professional

ment

cement datasets from

mentwerke) releases an environmental re-

slightly due to a different en-

database,

VDZ

port. Using this latest VDZ report and ad-

ergy mix. AP and POCP de-

Extension

ditional calculations by PE experts, the en-

crease.

database

ergy and raw material usage for the pro-

XIV:

Con-

duction of cement clinker has been up-

struction ma-

dated. This affects all cement datasets and

terials

datasets using cement as input (screed,

GaBi Databases ‘14

mortar, tile adhesive, concrete pipe, concrete block, ...) GC-1050

Improve-

Energy input of lime

Changed energy input mix for lime produc-

No change in GWP. ADP

Professional

ment

dataset

tion using the newest available data from

fossil, AP, EP and Primary

database,

the report "Die Klimavorsorgeverpflichtung

energy impact decreases.

Extension

der deutschen Wirtschaft – Monitoringbe-

ADP Elements increases by

database

richt 2011 und 2012".

56%.

XIV:

ODP and primary energy

struction ma-

from renewables increases

terials

Con-

by over 300%. However those absolute numbers are very small. Increase here is linked to the German electricity mix. GC-1052

GC-1159

Improve-

Generic

ment

tasets

wood

da-

Using the literature reference “Ökobilanz

Does

Basisdaten für Bauprodukte aus Holz,

change the results

not

significantly

Extension database

Thünen Institut, 2012”, diverse NMVOC

XIV:

Con-

emissions have been added in the drying

struction ma-

process.

terials

Improve-

MMA and PMMA da-

DE Transparent boards PMMA, cast

Changes in impact linked to

Extension

ment

tasets

(EN15804 A1-A3)

entry

database

DE Transparent boards PMMA, extruded

PMMA data)

GC-668

(Revise

(EN15804 A1-A3)

XIV:

Con-

struction materials

GC-1344

Improve-

Aluminium

datasets

ment

used in database

Since new aluminium manufacturing pro-

Impacts decrease (see also

Extension

cesses were introduced into the database,

GC-979 in inventories for

database

it was checked by PE metal experts where

metal processes)

XIV:

Con-

the information in the construction data-

struction ma-

base can be updated. This concerns alu-

terials

minium hydroxide mix and alumina. Additionally Aluminium extrusion profiles were updated in plans for windows manufacturing, and aluminium foil for PEx pipes were also updated. GC-1035

New jects

ob-

Country specific data

In total 954 datasets for the usage of build-

New objects, no changes

Extension

for building equipment

ing equipment are published. Usage data

database

usage

for Circulating pump, Electric instantane-

XIV:

ous water heater (use), Electrical heat

struction ma-

pump Brine-water, Electrical heat pump

terials

Con-

water-water, Flat collector, Gas condensing boiler, Gas heat pump air, Gas low

GaBi Databases ‘14

temperature boiler, Oil condensing boiler, Oil low temperature boiler, Tube collector, Use Multisplit air conditioner, Use room air conditioner, Use Split air conditioner across European countries is now available GC-1051

New

ob-

Street infrastructure

Four new datasets are available for infra-

jects

GC-1091

New jects

New objects, no changes

structure calculations:

ob-

EN15804

EPDs

construction database



Industrial road, asphaltic



Parking area, asphaltic



Parking area, paved



Sidewalk

About 150 EPD datasets published in Construction Database Extension

Professional database

New objects, no changes

Extension database XIV:

Con-

struction materials

2.10 Inventories for textile processes No major technology changes took place in the foreground system and therefore the data is still representative. Visible changes come from the background system, such as electricity grid mixes. Five new datasets were added to the Extension database XV: Textile finishing. Textile processes after the upgrade 

Due to changes in the chlorine and sodium hydroxide mix composition (see GC-1163) the dataset “water repelling agent” has a decreased impact in GWP. Due to remodelled upstream borax datasets, “Sodium sulphate” has an increased impact in all categories.



Textile intermediate chemicals in general: Many different chemicals are used in textile finishing industry processes; most in relatively small amounts. The datasets represent the production of those textile chemicals focusing on the textile industry. The datasets are an estimation and suitable within the scope of textile production, but may not be used outside this scope. The datasets do not cover all relevant process steps / technologies over the supply chain of the represented cradle-to-gate inventory and have a medium to low overall data quality. The inventories are primarily based on secondary data.

GaBi Databases â&#x20AC;&#x2DC;14

ď&#x201A;ˇ

New datasets: o

CN: Polyethylene terephthalate (PET) granulate secondary ; no metal fraction

EU-27: Polyethylene terephthalate (PET) granulate secondary ; no metal fraction

EU-27: Polyethylene terephthalate (PET) granulate secondary ; no metal fraction ; w/o washing

IN: Jute hessain net

CN: Natural bamboo fibres

2.11 Inventories for transport processes The transport processes were all checked against validity and passed. 12 new truck datasets with the latest standard EURO6 were added, additionally now also 7 new light duty vehicles datasets are available. Due to growing customer demand, the manufacturing for selected transport vehicles is now available. For a detailed list, please see the following table.

GC-956

New objects

New datasets for EURO 6 emission norm trucks and for 3,5 t trucks

Added: 12 new EURO 6 Trucks 7 new light duty vehicles (from oldest norm to EURO 6) by LBP University of Stuttgart transport experts, using information from HBEFA 3.1, status January 2010.

New objects, changes

Professional database

GaBi Databases ‘14 GC-957

New objects

Transport vehicles production

Using literature sources which are linked in the documentation as basis and combined with consistent background data from the GaBi databases, production of transport vehicles was added:

New objects, changes

Professional database

Truck production (20t - 26t gross weight) Truck-trailer production (28t - 34t gross weight) Truck-trailer production (34t - 40t gross weight) Truck production (<=7.5t gross weight) Truck-trailer production (14t - 20t gross weight) Truck production (28t - 32t gross weight) Truck production (26t - 28t gross weight) Truck production (7.5t - 12t gross weight) Truck-trailer production incl. EoL (40t 50t gross weight) Truck production (14t - 20t gross weight) Truck-trailer production (50t - 60t gross weight) Truck-trailer production incl. EoL (20t 28t gross weight) Truck production (>32t gross weight) Truck production (12t - 14t gross weight) Ocean ferry production (1,200t - 10,000t DWT) Ocean container ship production (27,500t DWT) Ocean bulk ship production (100t 200,000t DWT) Towboat production Motorboat production Airbus 330-200F production Airbus 310-200F production Train production (diesel locomotive) Train production (electric locomotive)

2.12 Inventories for US regional processes Changes to the end-of-life processes which are specific to the US and contained in the US Extension Database (Extension DB XVII) are described in the topically defined sections above (section 2.6, GC-1272). The changes in the specific grid mixes for different regions in the US can be seen in Section 2.1, figure 2.8 (page 14). The absolute values can be seen in figure 2.9 (page 14). The process “Grocery transport by car” was upgraded to GREET 2013 emissions factors, and the amounts of trips changed. EPD datasets specific for the US market are now available. 14 new datasets from associations from the US were added to the professional database, these include Worldsteel, Aluminium Association and AF&PA. The full list can be found in Section 3: Industry data in GaBi.

GaBi Databases ‘14

JIRA

Issue Cat-

Tracking

egory

Item

Description

Change in results

Affects Extension

Number GC-1097

module Improve-

US retail datasets

ment

Updated the following processes:

Extension da-

US: Warehousing, unrefrigerated [p-agg]

tabase XVII:

US: Warehousing, refrigerated [p-agg]

Full US

US: Grocery transport by car [p-agg]

Datasets “US: Warehousing, unrefrigerated [pagg]” and “US: Warehousing, refrigerated [pagg]”: The link of the source “Economics of Warehouse Density” did not work anymore. This was fixed. Dataset “US: Grocery transport by car [p-agg]”:

Parameter “costs”: Changed value to $102.87 USD; changed reference in comment to www.fmi.org/research-resources/supermarketfacts/ Parameter “trips”: Changed value to 1.6 Parameters “mpg” and all other emissions: Changed to GREET.net 2013 values Changed comment of parameter “mpg” to “[mpg] 23.4 taken from GREET.net 2013 default (MY2005). Avg age of US cars was 11.4 yrs in 2013.” Exchanged data source “Supermarket Facts 2011” in documentation tab with “Supermarket Facts 2013” Exchanged data source “Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends” with “GREET.net 2013” Added additional data source “IHS 2014” GC-1110

New jects

ob-

US EPD's

EPDs from the US market added to the database

New

objects,

changes

Extension database XVII: Full US

GaBi Databases ‘14

2.13 Inventories for machining processes The machining processes where all checked against validity and passed. Selected datasets have been updated. In the following table, the changes are listed.

JIRA

Issue Cate-

Tracking

gory

Item

Description

Change in results

Machining processes

The process name of the data set "Steel sheet"

No significant changes

Number GC-1073

Improvement

{8c484370-a298-4eaf-b1e0-c12c9a68e12c} was renamed to "Steel sheet (1mm) MAG welding". CO2 as component for the active gas mix was added in a typical ratio. For the partly aggregated processes "cast iron part" and the "steel cast part alloyed“, the application was specified by adding automotive in the name. After discussions with PE metal experts, the output amount of slag was reduced whereas the output amount of scrap was increased. But due to the closed loop recycling approach, the overall scrap amount is reduced (comparing the scrap input and the product output). The upgraded amounts of slag and scrap in the output are included in the unit process "Steel cast part alloyed (automotive)". The data set "Unit load galvanization (1 m² steel sheet part; electrolytic)" was renamed to "Electrolytic galvanisation (1 m² steel sheet part; electrolytic)". The input flow Auxiliary material [Operating materials] was deleted. The data set "Welding seam 1m" was renamed to "Welding seam 1m (including welding wire)" The data set "Aluminium laser welding (1 to 3.5mm depth)" was renamed to "Aluminium laser welding (1 to 3.5mm depth; including aluminium welding wire)". The process name of the data set "Steel sheet" {9DDCFE23-D82C-4E25-BA98-BC9AF7AB97DD} was changed to "Steel sheet (1mm) spot welding"

Industry data in GaBi

Despite the fact, that several associations have updated their data, some associations did not update this year. Since they have an own cycle for upgrading their data, these processes have not been altered during this upgrade. PE INTERNATIONAL must keep these processes identical to those in the GaBi Databases 2013 until the associations decide to update these and make these available on our platform. However, several new association datasets use the GaBi database to reach global customers. New sources of industry data added in GaBi Databases 2014: From ILA (http://www.ila-lead.org/): EU-27: Lead primary and secondary mix, production mix, at producer, primary 46% / secondary 54% From worldsteel (http://www.worldsteel.org) NA: Steel pickled hot rolled coil, production mix, at plant NA: Steel sections (interim data), production mix, at plant NA: Steel hot rolled coil, production mix, at plant NA: Steel finished cold rolled coil, production mix, at plant NA: Steel cold rolled coil, production mix, at plant NA: Steel plate, production mix, at plant NA: Steel hot dip galvanized, production mix, at plant From AF & PA (http://www.afandpa.org/) US: Corrugated product, production mix, at plant US: Containerboard, production mix, at plant From Aluminum Association (http://www.aluminum.org/) NA: Secondary Aluminum Ingot, production mix, at producer NA: Primary Aluminum Ingot, production mix, at producer NA: Extruded Aluminum, production mix, at producer NA: Hot Rolled Aluminum, production mix, at producer NA: Cold Rolled Aluminum, production mix, at producer From DLR (http://www.dlr.de) CN: Ferrosilicon production IL: Magnesium production, electrolysis CN: Magnesium production, pidgeon process

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.1

Naming

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-357

Naming

Naming of 'Aluminium'

"Aluminum" changed to "Aluminium": spelling changed to British English

Does not change the results

All

GC-739

Naming

Spelling Construction database (German)

Spelling corrected in German Construction database: "Undbehandelt" was corrected to "unbehandelt"

Does not change the results

Extension database XIV: Construction materials (German)

GC-775

Naming

Carbon fiber datasets: fiber type in name

The process Carbon Fiber (CF; from PAN) was renamed to Carbon Fiber (CF; from PAN; short fibers) The process Carbon fiber yarn (CF) (high strengths from PAN)was renamed to Carbon fiber yarn (CF; from PAN; long fiber; high strengths)

Does not change the results

Extension database VII: plastics

GC-812

Naming

Spelling German process data "Kerosin" in German

Name of Kerosin was written wrong in German (Kerosoin)

Does not change the results

Professional database

GC-1702

Naming

Naming of "US Polyethylene terephthalate resin (via terephthalic acid *und* ethylene glycol)

Process name contained German word "und", which was corrected to "and"

Does not change the results

Extension database XVII: Full US

GC-960, GC-886, GC-773, GC-772, GC-771, GC-768, GC-763

Naming

Processes: p-agg instead of agg

Processes having more than one input should be set to p-agg to be ILCD conform. Process type has been changed from agg to p-agg

Does not change the results

All

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.2

Sorting

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-714

Sorting

"Oil condensing boiler <20 kW" sorting

Process "DE: Oil condensing boiler <20 kW" moved to folder Construction Industry\use building services engineering\Heating

Does not change the results

Extension database XIV: Construction materials

GC-966

Sorting

EPDM / caoutchuc foam

Folder: Construction Industry\Insulation materials: The process "EPDM foam (pipe insulation) (EN15804 A1-A3)" was stored in the folder for natural rubber. A new folder for synthetic rubber was generated and the process was relocated.

Does not change the results

Extension database XIV: Construction materials

The product flow of the caoutchuk foam process has been EPDM. This has been corrected to "Natural Rubber (NR)". GC-1233

Sorting

Association datasets with expired validity

Association and EPD data with validity data older than 5 years (2009) were moved to the outdated folder. Validity of the ENEA data sets for textiles has been extended by one year after consultation with textile experts of PE.

Does not change the results

Professional database, Extension database XIV: Construction materials; Extension database XV: Textile finishing

GC-1339

Sorting

Strontium flows sorting

The following strontium flows have been moved from heavy metals to inorganic emissions of the related compartment. Strontium is not a heavy metal, it is an alkaline earth metal

Does not change the results

All

Strontium Heavy metals to fresh water {ddf137d3-63bc-4fb6-88f21e05e909774e} Strontium Heavy metals to industrial soil {aa85cfca-fb99-4188-bccd4e6eb6a27dbb} Strontium Heavy metals to sea water {d492c0c9-628c-4879-857a6f9dedb615e6} Strontium Heavy metals to agricultural soil {76b6447e-4ed9-4051-8fa1e1b05d639aa8}

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.3

Documentation

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-696

Documentation

Density information in "Film for green roof"

Density information "Density: 1126 kg/m3" added to the documentation field further quantitative specifications

Does not change the results

Extension database XIV: Construction materials

GC-751

Documentation

Documentation: district heating process

Documentation of the district heating process still refered to the old GaBi4 data documentation with links to 2002 and GaBi 4 software in it. Documentation was updated

Does not change the results

Extension database XIV: Construction materials

GC-844

Documentation

Dataset documentation of items in the Construction Extension Database

Documentations for the following processes were updated. Standard energy processes and construction energy processes now have the same documentation: DE Electricity grid mix (EN15804 B6) DE Electricity from hydro power (EN15804 B6) BR Electricity from hydro power BR Electricity from wind power BR Electricity grid mix UA Electricity from hydro power UA Electricity grid mix CN Electricity from hydro power CN Electricity from wind power CN Electricity grid mix DE Light fuel oil at refinery (EN15804 B6) DE Heavy fuel oil (EN15804 B6) DE Thermal energy from light fuel oil (EN15804 B6) DE Liquefied Petroleum Gas (LPG) (EN15804 B6)

Does not change the results

Extension database XIV: Construction materials

GC-846

Documentation

Documentation and parameter comments in the process "Drying grain"

The documentation of the dataset "Drying grain" {895CC239-D11F-409C-9CCE4D68D770943B} as well as the parameter comments were updated.

Does not change the results

Extension database XII: Renewable materials 2013

GC-848

Documentation

Valuable flow for "Triethylene glycol"

The process "EU-27: Triethylene glycol" {1F281DA2-D1DF-0EE9-CF1300006A95D416} had an emission flow instead of a product flow as valuable substance. Changed reference flow from emission to valuable substance flow "Triethylene glycol".

Does not change the results

Professional database

GC-863

Documentation

Documentation of process "GLO: Fertilising; liquid manure"

A clarification comment was added in the documentation of the process:

Does not change the results

Extension database XII: Renewable materials

"This process includes the efforts to bring out the fertilizer, but does not include the fertilizer production itself or the impact of the fertilizer on the environment"

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14 GC-888

Documentation

Flow diagram in process "Hydrogen from steam reforming"

Diagram updated (synthesis gas was deleted in the flow diagram)

Does not change the results

Professional database, Extension database Ib: inorganic intermediates, Extension database XVII: Full US

GC-983

Documentation

Documentation: recycling potential dataset

Changed documentation: Entered comment: fixed collection rate entered General comment: Text corrected Flowchart: graphic changed

Does not change the results

Metals, Extension database XIV: Construction materials

Recycling potential aluminium sheet Recycling potential stainless steel sheet Recycling potential steel sheet galvanised Recycling potential steel sheet galvanized (EN15804 C3) Recycling potential stainless steel sheet (EN15804 D) Recycling potential steel profile (EN15804 C3) Recycling potential steel profile (EN15804 D) Recycling potential steel thin sheet (EN15804 C3) Recycling potential steel thin sheet (EN15804 D) Recycling potential steel thick plate hot rolled (EN15804 C3) Recycling potential steel thick plate hot rolled (EN15804 D) Recycling potential stainless steel sheet (EN15804 C3) Recycling potential steel sheet galvanised (EN15804 D) Recycling potential steel thin sheet (galvanized) Recycling potential aluminium (sheet and profiles) Recycling potential steel sections Recycling potential steel sections Recycling potential - steel thin sheet Recycling potential stainless steel Recycling potential aluminium (sheet and profiles) Recycling potential steel sections Recycling potential steel thin sheet (galvanized) Recycling potential aluminium (sheet and profiles) GC-1001

Documentation

Documentation: Mix and location type

The documentation field "mix and location type" was reworked throughout the database

Does not change the results

All

GC-1002

Documentation

Documentation: Origin of u-so data

The origin for all flows in unit processes are now given

Does not change the results

All

General continuous improvement done in the Upgrade ’14 GC-1013

Documentation

Documentation: technology description

Filled gaps in the field “technical description” throughout the database.

Does not change the results

All

GC-1014

Documentation

Documentation: Technical purpose (intended application)

Documentation field "technical purpose" checked and reworked throughout the database.

Does not change the results

All

GC-1015

Documentation

Documentation: Sources for key technologies

Four new documents are now made available to the public on the homepage and are linked into each dataset: - Refinery modelling principles - Energy modelling principles - Agrarian model - Land use change

Does not change the results

All

GC-1016

Documentation

Documentation: external reviews, QA routines

Reviews added to the "validation" section of the documentation throughout the database.

Does not change the results

All

GC-1157

Documentation

PET production route process

Literature research has shown that the production route of PET via DMT has become less important for the European production. The process is still performed but the path via terephthalic acid has become the most important in Europe. A comment was added in the documentation of EU PET via DMT processes.

Does not change the results

Professional database

GC-1329

Documentation

Documentation for DE: aluminium datasets

Aluminium datasets for Germany have been updated, now also stating that the aluminium is primary and does not contain secondary amounts. Updated used data sources. Updated graphics in some processes.

Does not change the results

Professional database, Extension database IV: Aluminium

GC-1338

Documentation

CAS numbers of "Sodium (+I)" flows

The CAS number of the flows has been adapted to the correct material specification (ion). CAS number should be "82115-62-6" according to: http://www.chemindustry.com/chemicals/026532.html

Does not change the results

All

Sodium (+I) Inorganic emissions to fresh water {13c1688b-8778-4661-a0e3-582175814cb6} Sodium (+I) ecoinvent long-term to fresh water {2e4cd86f-71e1-4f59-8b6d-a0b5d777adaa} Sodium (+I) Inorganic emissions to industrial soil {d8f193c7-1878-4651-b977-4d8ab6a0b616} Sodium (+I) Inorganic emissions to sea water {6f360feb-e6e6-46f7-af6c-e553d6828c25} GC-1382

Documentation

Link to "GaBi Water Modelling Principles"

In the reference "GaBi Water Modelling Principles" the link to the corresponding PDF document was broken. The link was added.

Does not change the results

All

GC-1383

Documentation

Link to "GaBi Modelling Principles 2007"

In the reference "GaBi Modelling Principles 2007" the link to the corresponding PDF document was broken. The link was added.

Does not change the results

All

General continuous improvement done in the Upgrade ’14 GC-1384

Documentation

Link to "GaBi homepage (Land use documentation)"

In the reference "GaBi homepage (Land use documentation)” the link to the corresponding PDF document was broken. The link was added.

Does not change the results

All

GC-1386

Documentation

Link to "GaBi conformity system"

In the reference "GaBi conformity system" the link to the corresponding PDF document was broken. The link was added.

Does not change the results

All

GC-1387

Documentation

Link to "GaBi homepage (LCWE documentation)"

In the reference "GaBi homepage (LCWE documentation)" the link to the corresponding PDF document was broken. The link was added.

Does not change the results

All

GC-1514

Documentation

CAS code for water

Water flows contained CAS number 7789-200, which is the CAS for heavy water. CAS number was changed to 007732-18-5.

Does not change the results

All

GC-1681

Documentation

Documentation: secondary fuels in cement datasets

In the technology description of cement datasets a sentence was added, which explicitly states the treatment of secondary fuels: "Secondary fuels for cement production are modelled with a "cut-off approach", i.e. the materials have no environmental burden", following “Environmental Data of the German Cement Industry 2013 by VDZ, which served as the source for the data.

Does not change the results

Extension database XIV: Construction materials

GC-1746

Documentation

Literature source to US truck datasets

For the US trucks, additional literature sources have been added as reference

Does not change the results

Extension database XVII: Full US 2013

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.4

LCIA / Method

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-546

LCIA / Method

Conversion factor for Ecoinvent quantity/unit tkm

The conversion factor to kgkm was added in the Ecoinvent unit "Ecoinvent unit ton kilometer". Users can now enter values in either tkm or kgkm.

Does not change the results

Ecoinvent

GC-622

LCIA / Method

Pesticide flows following implementation of UBP 2013

When implementing the pesicised according to UBP 2013 the LCIA experts of PE noticed an inconsistency regarding the implementation of other methods. So Alachlor to agricultural soil was updated with characterization factors from ReCiPe and USEtox. Other pesticides were in accordance with methodology spreadsheets/reports

Minor changes only to agricultural products using specific pesticide

All

GC-697

LCIA / Method

Biogenic methane in the most important processes

Specification (from fossil methane to date) to biogenic methane emissions was done (as a first step in 2014) in the most important unit processes like animal husbandry (cows, sheep, pig, manure), landfill and landfill gas treatment processes, clearance and slash and burn processes as well as some selected renewable resources (palm oil, coconut ) by PE renewables experts. This does not change the results in terms of GWP significantly, but addresses the call for more differentiation on LCI level.

Does not change the results significantly

All

GC-950

LCIA / Method

CO2 aircraft transportation emissions

In the standard airplane unit processes, the existing flow Carbon dioxide [Inorganic emissions to air] was replaced by the new flow "Carbon dioxide (aviation) [Inorganic emissions to air] ". Emission values are kept the same. The biogenic CO2 flow was not influenced by this change, but is set to zero in the standard settings of the airplane processes. The new flow implemented (Carbon dioxide (aviation)) now allows to evaluate the CO2 emissions arising from aviation separately.

Changes results when evaluating processes using air plane transport

All

GC-1009

LCIA / Method

Lanca implementation

LANCA information added by LBP University of Stuttgart land use experts to now consistently cover all farm, forest and mining datasets. This will affect only land use results made with LANCA method

Changes results when evaluating with land use method LANCA

All

General continuous improvement done in the Upgrade ’14 GC-1027

LCIA / Method

Flows for rain water (on output side)

Corresponding to a customer wish, three new water flows to environment were created, originating from rain water: Water (lake water from technosphere, rain water) {53e2d34b-45b5-4a5d-9c50158ac7138d84} Water (sea water from technosphere, rain water) {09fe6531-8a47-4acf-8979131e81493f94} Water (river water from technosphere, rain water) {b1f08696-54fa-458d-9a6baf614db865e6} The new flows better allow to close the water balance for “total water consumption (including rain water)” Additional clarification was added in the documentation.

The blue water consumption of landfills was negative before for nearly all landfills. This is because rain water which was not counted in blue water consumption ended as river water that was credited in blue water consumption. Now the flow of the water to environment has been changed to water (river water from technosphere, rain water) which is not credited in blue water consumption. Therefore the value is no longer negative.

All

GC-1230

LCIA / Method

Impacts in ILCD default dashboard

Within the dashboard some Traci quantities were accidentally used to represent the ILCD recommended quantities. All ILCD recommendations have been checked, incorrect quantities have been replaced. All used quantities can be found in the folder Quantities/Environmental quantities/Impacts ILCD/PEF recommendation

Does not change the results

All

GC-1284

LCIA / Method

PEF normalisation factors

PEF recommended normalization factors were added, according to document "Guidance for the implementation of the EU PEF pilot phase 4.0", Table A2

New objects, no changes to existing results

All

GC-1285

LCIA / Method

Characterization of the flow "Water (fossil ground water)"

Fossil ground water was characterized in the four water quantities with same impact factors as ground water. Total freshwater consumption (including rainwater) {e588a3c8-68fd-4686-9811f8a7b2c3442a} Blue water consumption {ff22d4db-a81e-4695-84c5-95790ab7dcfc} Blue water use {4dab804f-d372-4bbf-9adc-cc0373f59715} Total freshwater use {a4052461-e0d3-48fe-89fbb8d441a65ade}

Does not change the results

All

GC-1340

LCIA / Method

Characterisation factor in "UBP 2013, Global Warming" impact category for Carbon dioxide (peat oxidation)

The following two flows below are given the GWP value of 460 UBP/kg identical to emission of fossil carbon dioxide: Carbon dioxide (land use change) and Carbon dioxide (peat oxidation)

No significant changes

All

GC-1343

LCIA / Method

Characterization of several copper flows

Characterization for several copper emissions to fresh water and sea water were corrected according to ReCiPe 1.07 and 1.08

No significant changes

All

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14 GC-1411

LCIA / Method

UBP 2013 - water consumption conversion m3 to kg

The characterization factor for water is given as UBP/m3 in the source material and was not converted when switching to UBP/kg in GaBi. Water factors were therefore divided with a factor 1000 to correct.

High impact if water intensive LCAs were evaluated with UBP2013. Otherwise no effect

All

GC-1470

LCIA / Method

ReCiPe 1.08 toxicity categories update from December 2012 to February 2013

Toxicity factors according to ReCiPe 1.08 were previously implemented from an Excel sheet released from authors on December 2012. A newer release of ReCiPe 1.08 from February 2013 had differences in toxicity and a complete re-implementation of all toxicity categories was performed (Human toxicity, Fresh water toxicity, Sea water toxicity and ecotoxitity).

Minor effects on agricultural products including pesticides.

All

GC-1543

LCIA / Method

Characterization for flow "Flumioxazin" GUID: {59F008A3-886B41E0-A7104F3EEFF414D7}

Flow is updated with USEtox Ecotox, PEF/ILCD, and Traci2.1. Updates to emission to air, freshwater and agricultural soil. Human toxicity cancer and non-cancer are not available

No significant changes

All

GC-1577

LCIA / Method

Characterization factors for PAH in CML

Inconsistencies in the characterization of PAHs were corrected. Notably, that CML contains different characterization factors for PAH (unspecified) and PAH (carcinogenic) when emitted to air.

No significant changes

All

GC-1602

LCIA / Method

IPCC AR5 flows and other LCIA methods

Approx 100 new flows were created to implement the 5th Assessment Report (AR5, WG1, Table 8.A.1) from IPCC. The new flows were aligned with the existing methodologies of Traci, CML, ReCiPe, and USEtox.

No significant changes

All

GC-1694

LCIA / Method

Metals toxicity in Traci 2.1

Metals toxicity were not implemented into Traci 2.1 when implemented into USEtox

Some effect if LCA with major metal emissions were evaluated for toxicity using Traci 2.1. Otherwise no effect.

All

GC-1818

LCIA / Method

Metal emissions and assignment of Ecotox factors (Sb III, Sb V, Sb) in ILCD

Finding of the PEF pilot projects: Characterisation factor for "antimony [heavy metals to air]" (as a metal) {E2A6A7F2-09EB4EC7-B3BD-8367A0259B5C} is changed from 491 CTUe/kg to 76487,7 CTUe/kg in the ILCD/PEF quantity "Ecotoxicity for aquatic fresh water, USEtox (recommended)". 491 is the value for antimony (III) ion, 76487,7 is the value for antimony (V) ion. The official ILCD excel specifies that for the metal the char. factor for antimony (V) ion shall be used. The UseTox quantity "USEtox, Ecotoxicity (recommended)" is not subject to this change.

Because of the factor 156 between the charaterisation factors, the changes for all processes that contain the flow antimony [heavy metals to air] (metal) {E2A6A7F209EB-4EC7-B3BD8367A0259B5C} are big for some processes, even if they are close to zero for the most processes. An average change of plus 2% for the ILCD Ecotoxicity is observed throughout the database.

All

GC-1899

LCIA / Method

Implementation of ILCD marine EP

Finding of the PEF pilot projects: The LCIA for marine EP recommended in ILCD/PEF was not implemented as in the official Excel file from JRC. GaBi implemented ReCiPe

The ILCD recommended method ReCiPe 1.05 does not (yet) use trans-

All

General continuous improvement done in the Upgrade ’14 1.07 whereas ILCD recommends ReCiPe 1.05. This is now harmonized in upgrade 2014. The aim is to be fully compliant to ILCD/PEF.

GC-1900

GC-974

LCIA / Method

formation factors for modelling the fate of emissions to fresh water, all emissions are characterized as if they would end up in sea water completely (using the same characterization factors for emissions to fresh water and emissions to sea water). Therefore the now implemented LCIA quantity ReCiPe 1.05 leads to considerably higher results for marine EP for all datasets.

Implementation of ILCD particulate matter

Finding of the PEF pilot projects: In the official Excel file for the ILCD recommended impact method for particulate matter/respiratory inorganics some flows were not characterized even if they plausibly should be. For example the flows particles PM 10 and particles PM 2.5 are characterized but the flow particles (2.5 to 10 µm) is not. PE INTERNATIONAL had introduced characterization factors for these flows but was therefore not 100% compliant to ILCD/PEF. Therefore the characterization factors are now removed. The aim is to be fully compliant to ILCD/PEF.

Since the characterization factors for some often used flows like particles (2.5 to 10 µm) are removed, the results for many datasets are lower now. PE INTERNATIONAL however anticipates that the missing flows will be re-characterized later by the European Commission JRC.

All

Land Occupation Indicator as reference quantity in two flows from USLCI database

Two flows from the USLCI database had a unit of "Land Occupation Indicator". This is changed to 'Number of Pieces' as listed on the USLCI website (http://www.nrel.gov/lci/). The two flows are: 1. RNA: Dummy, softwood seed, at greenhouse, INW [Dummy Flows] 2. RNA: Greenhouse seedling, softwood, INW [Products and Intermediates]

Does not change the results

Extension database XVII: Full US

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.5

New Objects

JIRA Tracking Number

GC-745

Issue Category

New objects

Item

Description

Change in results

New dataset for gasoline E5 mix at refinery and filling station

Added DE: Gasoline mix (E5) at filling station DE: Gasoline mix (E5) at refinery, using consistent information from other gasoline datasets.

New objects, changes

Affects Extension module no

Professional database

General continuous improvement done in the Upgrade â&#x20AC;&#x2122;14

4.6

Bugs and improvements

JIRA Tracking Number

Issue Category

Item

Description

Change in results

Affects Extension module

GC-671

Improvement

Oil & Gas production: H2S emission factors of venting and flaring

The specific emissions of the gas flare process in the GaBi databases (background data sets) were analysed, compared to the literature data currently available and updated, if needed.

This change has an effect on the Crude oil mix (AP decreases), as well as the subsequent products, but here the effect is not as pronounced.

All

GC-722

Improvement

Refinery model - amout of freshwater input

The water balance of the refinery models in the GaBi databases (background data sets) was analysed, compared to the literature data currently available and adapted/updated, if needed

Due to the adaptation of the amount of freshwater to the amount of waste water of the refinery, there are significant changes in the water categories (total freshwater use and consumption, blue water use and consumption).

All

GC-902

Improvement

FEFCO upstream data

New information of FEFCO was available on how to interpret the LCI of the unit processes on paper production. This information was used to update the FEFCO datasets.

Considerable changes lowering the overall results. For Kraftliner and Semichemical fluting GWP goes down by approx. 20%

Professional database

GC-1083

Improvement

Float / container glass update

Based on the 2013 BAT document for Glass, the data set for container and float flat glass was updated.

The results of the data set show an improved environmental performance of between 1-8% for the major impact categories.

Professional database

GC-1710

Bug

CO2 balance in plans with extended allocation

Working on the food&feed extension database, PE experts identified incorrect carbon balances in datasets where economic allocation is applied, specifically in cases where renewable materials are used in any step of the supply chain. All datasets with economic allocation and extended allocation using economic ratios were checked and if necessary corrected regarding the carbon balance.

The new carbon balance affects the LCI of the dataset and the GWP

Several

References

References Baitz, M. 2002

Baitz, M. (2002): Die Bedeutung der funktionsbasierten Charakterisierung von FlächenInanspruchnahmen in industriellen Prozesskettenanalysen. Ein Beitrag zur ganzheitlichen Bilanzierung. Dissertation. Aachen: Shaker (Berichte aus der Umwelttechnik).

Beck 2010

Beck, T.; Bos, U.; Wittstock, B. (2010): LANCA – Calculation of Land Use Indicator Values in Life Cycle Assessment; to be published. Online: www.lbp-gabi.de.

Brentrup 2000

Brentrup, F.; Küsters, J.; Lammel, J.; Kuhlmann, H.; (2000): Methods to estimate on-field nitrogen emissions from crop production as an input to LCA studies in the Agricultural Sector. The International Journal of Life Cycle Assessment. 5(6), 349-357.

EC 2001

European Commission: Directive 2001/80/EC on the limitation of emissions of certain pollutants into the air from large combustion plants, 2001

EC 2001

European Commission: Directive 2001/80/EC on the limitation of emissions of certain pollutants into the air from large combustion plants, 2001

EC 2009

European Commission: Directive 2009/28/EC on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC (Renewable Directive), April 2009

EIA 2013

U.S. Energy Information Administration: Electric Power Annual 2011, Washington, 2013

EPA 2014

U.S. Environmental Protection Agency (EPA): The Emissions and Generation Resource integrated database (eGrid), 9th edition of eGrid with Year 2010 data, Washington, 2014

Eurochlor 2012

Eurochlor, Chlorine Industry Review 2011-2012, 2012

Eurostat 2013

Eurostat: Energy Database - Supply, transformation, consumption - electricity - annual data [nrg_105a], Luxembourg, 2013

FERC 2014

Federal Energy Regulatory Commission (FERC): Form No. 2014 – Annual Electric Balancing Authority Area and Planning Area Report, 2014

IEA 2012

International Energy Agency: Electricity Information 2012, Paris, 2012

IPCC 2006

Intergovernmental Panel on Climate Change (IPCC). (2006). Guidelines for National Greenhouse Gas Inventories, Volume 4 Agriculture, Forestry and Other Land Use, Retrieved December 22, 2009 from: http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.html

ISO 14046

ISO/CD Life Cycle Assessment – Water Footprint – Requirements and guidelines

ISO 2006

International Organization for Standardization (ISO). (2006): Environmental Management – Life Cycle Assessment – Principles and Framework. Series 14040 and 14044.

Pfister 2011

Pfister, S.; Bayer, P.; Koehler, A.; Hellweg. S. (2011): Environmental Science & Technology 2011 45 (13), 5761-5768 Environmental Impacts of Water Use in Global Crop Production: Hotspots and Trade-Offs with Land Use

SICAS 2008

Semiconductor Industry Association (SIA): Semiconductor Internantional Capacity Statistics (SICAS) 2008

References

UBA 2010

Handbuch Emissionsfaktoren des StraĂ&#x;enverkehrs, Version 3.1, Umweltbundesamt Berlin; BUWAL / OFEFP Bern; Umweltbundesamt Wien, http://www.hbefa.net, Berlin, Bern, Vienna / Germany, Switzerland, Austria

WaterGAP 2012

Water - a Global Assessment and Prognosis. Version 2.0. Center for environmental systems research, University of Kassel, Germany. 2012 World Semiconductor Trade Statistics: Semiconductor Market Forecast 2008

WSTS 2008

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations For various reasons, there are a few processes in the Databases 2014 which are no longer appropriate. These have been moved into a folder called Version 2013 and have been given the suffix '(Version 2013)'. They are still available for clients who need to work with them but will not be upgraded anymore, and are not part of the delivery scope for new GaBi clients. The are two reasons behind this approach; i) PE INTERNATIONAL are commited not to provide information which is not up-to-date and ii) on the other hand PE INTERNATIONAL want to enable users who have used the dataset to decide if it is still appropriate in their specific goal and scope. The table below shows an overview of how many plans and processes are affected and to which database they belong. The additional sheets in this Excel file list all affected processes along with the explanations and recommended alternatives.

Version 2013 processes Professional database Extension database XI: Electronics

20 19 1

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations

EU-27

Beverage carton converting

u-so

Liquid PackagEU-27 ing Board agg (LPB)

Process name

Country

Alternative process to be used instead

{90a3b10d-83cc4bc7-a715991e2ea786ad}

If relevant, please contact data on demand from PE for alternative processes

ELCD/ACE

technology mix|production mix, at {68e3f3d7-4b59plant|mineral coated 4ae8-87b7LPB (n=4), basis e561ccc2bf73} weight: 266 g/m2

If relevant, please contact data on demand from PE for alternative processes

Object group

converting technology|production mix, at plant

Source

ELCD/ACE

Type

Details

Process GUID Can be entered in Reason for being clasthe search tool sified as outdated

Source

Type

Process name

Country

Version 2013 processes Professional database

Details

RER

Stainless Steel agg Hot Rolled Coil

ELCD/Eurofer

annealed and pickled, grade 304, austenitic, electric arc {1ad9a56d-a2d0furnace route|pro4808-b2cfduction mix, at b348c109cb4a} plant|18% chromium, 10% nickel

RER

Steel hot rolled agg coil

ELCD/Eurofer

blast furnace route|production mix, {119e8cc1-0859at plant|thickness 2 45ca-8f63to 7 mm, width 600 93a8a518ffd2} to 2100 mm

If relevant, please contact data on demand from PE for alternative processes

GLO

Steel hot rolled agg section

ELCD/Eurofer

blast furnace and {f9d4581e-14deelectric arc furnace 417e-8f9froute|production mix, 6c74e6f14051} at plant

If relevant, please contact data on demand from PE for alternative processes

Steel rebar

ELCD/Eurofer

blast furnace and {268a11fb-baf2electric arc furnace 4b9e-8867route|production mix, 38bea0e76ef6} at plant

If relevant, please contact data on demand from PE for alternative processes

GLO

agg

Process GUID Can be entered in the search tool

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations

Object group

Source

Type

Process GUID Can be entered in the search tool Reason for being classified as outdated

Process name

Details

Country

Source

Alternative process to be used instead

Type

Process name

Country

Version 2013 processes Professional database

Details

RER

Acrylonitrile{76d6aaa4-37e2butadiene-styELCD/Plas technology mix|prop-agg 40b2-994crene granulate ticsEurope duction mix, at plant 03292b600074} (ABS)

If relevant, please contact data on demand from PE for alternative processes

RER

Chlorine

technology mix|pro- {945256f7-e041ELCD/Plas duction mix for PVC 46c8-b3bbticsEurope production, at plant 0d447d4b398b}

If relevant, please contact data on demand from PE for alternative processes

RER

Nylon 6 granuELCD/Plas technology mix|pro- {fad4c07f-40db-48fap-agg late (PA 6) ticsEurope duction mix, at plant 8d62-de5ae8d9fcbf}

If relevant, please contact data on demand from PE for alternative processes

RER

Nylon 6.6 {e7920ba8-e048GF30 comELCD/Plas technology mix|prop-agg 49b5-b16bpound (PA 6.6 ticsEurope duction mix, at plant 387a937b901b} GF30)

If relevant, please contact data on demand from PE for alternative processes

RER

{744e255f-3b81Nylon 6.6 granELCD/Plas technology mix|prop-agg 4eed-b2d3ulate (PA 6.6) ticsEurope duction mix, at plant 7794353e0efb}

If relevant, please contact data on demand from PE for alternative processes

RER

Polymethylmethacrylateball (PMMA)

If relevant, please contact data on demand from PE for alternative processes

p-agg

{67116372-6605ELCD/Plas technology mix|pro4c48-a973ticsEurope duction mix, at plant e0445b81dd29}

Process GUID Can be entered in the search tool

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations

Object group

Source

Type

Process name

Details

Process GUID Can be entered in the Reason for being classearch tool sified as outdated

Country

Alternative process to be used instead Source

Type

Process name

Country

Version 2013 processes Professional database

Details

RER

Polyvinylchloride granulate (Emulsion, EPVC)

p-agg

emulsion polymeriELCD/Plas sation|production ticsEurope mix, at plant

{ccbdee3b-27db4852-a14cec73ad8421ea}

If relevant, please contact data on demand from PE for alternative processes

RER

Polyvinylchloride granulate (Suspension, S-PVC)

p-agg

suspension polymer- {129b8f8d-7667ELCD/Plas isation|production 41bc-91f4ticsEurope mix, at plant 421bfcdfc8c3}

If relevant, please contact data on demand from PE for alternative processes

RER

Sodium chlotechnology mix|pro- {84d5e0e5-cc4bELCD/Plas ride (NaCl, dis- p-agg duction mix for PVC 49ff-a9c4ticsEurope solved) production, at plant dc5c2b06351d}

If relevant, please contact data on demand from PE for alternative processes

RER

technology mix|proSodium hy{f7ba74a4-e81cELCD/Plas duction mix for PVC droxide (100%; p-agg 4084-97c9ticsEurope production, at caustic soda) b9dd5456446c} plant|100% NaOH

If relevant, please contact data on demand from PE for alternative processes

RER

Vinyl chloride technology mix|pro- {d1240334-eb6aELCD/Plas (VCM; chloroe- p-agg duction mix for PVC 47f4-93a1ticsEurope thene) production, at plant 4b5f0feba440}

If relevant, please contact data on demand from PE for alternative processes

RER

Electricity

agg

technology mix|proPlasduction mix, at proticsEurope ducer

{9511861c-41c14e6b-901dc5322f174c64}

Process GUID Can be entered in the search tool

If relevant, please contact data on demand from PE for alternative processes

Annex: Version 2013 datasets â&#x20AC;&#x201C; Explanations and Recommendations

GLO

Mains plug connector CEE agg 7/16, Type C (15g, 2pins)

{2016f352-f6a9technology mix|pro4ad9-bb55duction mix, at plant 7bc1f34fa3a9}

GLO

Connector Schuko CEE 7/16 (15 g, 2 pins)

agg

Object group

Source

Type

Details

Process GUID Can be entered in the Reason for being classearch tool sified as outdated

Process name

Alternative process to be used instead Country

Source

Type

Process name

Country

Version 2013 processes Extension database XI: Electronics

Connectors

Details technology mix, production mix, at producer

Process GUID Can be entered in the search tool {8DA988C5A15D-410F90866C92B08A74D6 }