ENVIRONMENTAL LABELLING LCA ADEME database Technical Committee: « Wood and Glass » April 24th 2012

1. ENVIRONMENTAL LABELLING LCA ADEME database Technical Committee: « Wood and Glass » April 24th 2012 Olivier Réthoré ADEME Service Eco-conception & Consommation Durable (SECCD) With Intertek RDC (Isabelle Descos, Matthieu Gillis)

2. Agenda • Goal and scope • For wood and glass • Particular methodological choices • Data need • Existing data

3. Goal and scope • Goal: to establish short term and long term needs in terms of LCI data to give specifications to Ecoinvent and PE in order to feed ADEME’s DB • Scope: • for furniture and beds because the PCR have been validated • for packaging because transverse issue

4. Meeting approach For each type of wood or glass: • Analyze the inventory data need from: • The preliminary study conclusions: « Elaboration d’un plan de développement d’une base publique de données d’ACV comme support à l’affichage » • PCR for furniture and bed • Knowledge about packaging • Determine the appropriate granulometry • Regarding • Technological representativeness • Geographical representativeness • Temporal representativeness • Considering for each differentiation • The relative environmental impact • The information accessibility for the industrial (specific data) • The short term data availability in existing databases (generic data) • Propose a list of inventories to be integrated into ADEME database

5. ADEME database content Processes LCI Flows*, flow property*,Unitgroups Unit Reference flow, Unitgroups Metadata Sources, contacts, external documents X Characterization factors* LCIA Method *Common data for all suppliers (to be given by the JRC) Result for each impact category

6. Data sources: 3 feeding modes • Purchasing existing or adapted data • From databases suppliers with which the ADEME has a framework contract • For both lots (7/wood and 8/glass): PE, ecoinvent • Data co-production • In order to fill missing data in specific sectors • Projects co-funded by ADEME with research and technical partners • Ex.: AgriBalyse for agriculture products, ACYVIA for food industry, etc. • Third party • In order to allow integrating data not yet available in existing databases • In order to promote assessment by the industry

7. PCR for furniture and bed • Impact categories • Climate change – IPCC 2007 • Resource depletion – EDIP 97 (2004) (may change) • Air acidification – Recipe 2008 • Photochemical oxidant formation – Recipe 2008

8. Glass and wood packaging in GT • Wood may be needed in all GT as tertiary packaging (pallets) • Glass is needed in the following GT as primary packaging • GT1: Food • GT4: Beauty, hygiene and health products

9. Wood 9

10. Data need – technological representativeness • PCR • Specific data • Quantity of each wood type (in mass or volume): see the list in next slide • Sustainable management of forests (to be defined by the methodological platform) • Wood machining (usinage): this data is not clear. What must the industrial indicate? (e.g. on what form he buys it: debarked, sawn, planned…)

11. Data need – technological representativeness • Solid wood • What are the differences between wood species from a LCA point of view? (e.g. more energy consumption, time for growing, soil nutrient…) • Is the approach hardwood/softwood enough for short term? • Are there types of wood missing? • Derived wood • Are the suggested categories differentiated enough? (e.g. different densities for fibreboard) • Are there types of wood missing? • Do a furniture manufacturer always know the wood species used in derived wood? NB: list established from preliminary study and PCR

12. Data need – technological representativeness • Forming processes • Debarking • Drying • Sawing • Planning • Preservative treatments Can those processes take place within the furniture manufacturing site? Do we need inventories, or is it always specific data? • Except for preservative treatments, do forming processes only include energy consumption? • For preservative treatments, are specific inventories needed?

13. Data need – technological representativeness • Packaging • Pallets • Wood boxes Do we need more than two average inventories? Are there other needs?

14. Data need – Geographical representativity • PCR does not require any geographical differenciation • What geographical level shall one consider: global ? Regional? National? • What are relevant parameters to differentiate a region from another? • What are available statistical data regarding the origin of wood in products bought in France?

15. Existing data – overview Nom du service

16. Existing data – detail for ecoinvent and GaBi (solid wood) Nom du service

17. Existing data – detail for ecoinvent and GaBi (derived wood)

18. Existing data • Can data from GaBi and ecoinvent be used for furniture? As they where originally produced for construction

19. Data need vs. existing data Data available in GaBi and ecoinvent Data available in one database or unknown information Unavailable data

20. Recycling allocation Furniture • PCR • requires 50/50 allocation for production losses Shall the database have inventories, from recycled losses to be chosen as raw material? Are production losses always considered recycled? • recycling is not considered for furniture end-of-life in short term • Credits • What is (are) the recycling outlet(s)? (energy from wood, process panel…) • Must one inventory be used or an average? • Recycling process • Must the recycling process be differentiated by type of wood, type of outlet? Pallets: energy valorization

21. Glass 24

22. Recycling allocation • BPX requires allocation based on collection rate • Two solutions to model recycling credit • Inventories 100 % primary or 100 % secondary allow choosing recycling content and end of life recycling rate but are not representative of any reality Is it possible/acceptable to have such inventories? Do they represent the reality when combined? • Average inventories represent closed loop systems, and are suitable for collection rate based allocation To databases suppliers: would it be possible to adapt the collection rate to France situation? • Should flat glass, packaging glass and other glasses collection rates be differentiated?

23. Container glass – Refillable glass • Should inventories be distinct between refillable bottles and one-way bottles? Or should it be an average? • Existing data • Ecoinvent and GaBi (?) only has data for one-way glass • FEVE has data for average and for one-way • If refillable glass is distinct, should/may the amount of rotations be a specific parameter in PCR for beverages? (i.e. is it significant on environmental impacts and can it vary from an industrial to another?) Olivier, cette question vapeut-être-t-il un peu trop loin? Nom du service

24. Soda allocation • Solvay process (or ammonia process) produces soda and calcium chloride • Soda allocation factor • ecoinvent: 33% based on economic allocation, world market • FEVE: 100%, because calcium chloride is a by-product not valued • What about GaBi? • Proposition: 100 % allocation to soda

25. Data need – Technological representativeness ListestablishedfromPreliminarystudy and complementaryresearch

26. Data need – Technological representativeness • Must all those categories have an inventory? (e.g. sealing glass is included in electronic processes) • Must those categories be more differentiated? • Are there types of glass missing? • For product directly coming from glass production site (e.g. glassware), do we need inventories for glass raw materials (soda, sand…)? Since quantities and other parameters may be specific. • What is the ideal list of inventories to be integrated into the database?

27. Data need – Geographical representativeness • What parameters differentiate a region from another? • What geography level shall we consider (country, continental, world) • Is it possible to estimate glass production in other continent from European data?

28. Existing data Nom du service

29. Existing data • Can data from GaBi and ecoinvent be used for furniture? As they where originally produced for construction • FEVE • How deep can FEVE inventory be disaggregated? In particular: • is it possible to have an inventory « glass, wool », • Is it possible to have an inventory « glass, refillable », • is it possible to have only the impacts of electricity consumption?

30. Data need vs. existing data Data available in GaBi and ecoinvent Data available in one database Unavailable data