ENVIRONMENTAL LABELLING LCA ADEME database Technical Committee: « Textile » June 15th 2012

1. ENVIRONMENTAL LABELLING LCA ADEME database Technical Committee: « Textile » June 15th 2012 Olivier Réthoré ADEME Service Eco-conception & Consommation Durable (SECCD) With Intertek RDC (Isabelle Descos, Matthieu Gillis)

2. Agenda • Goal, scope and database context • Data aggregation • Fibers • Textile production • Use phase • End of life

3. Goal and scope • Goal: to establish short term and long term needs in terms of LCI data to give specifications to Cycleco and PE in order to feed ADEME’s DB • Scope: • Apparel (PCR proposals for shirts, jeans and underwear) • Household textile • Shoes (validated PCR)

4. Meeting approach For each type of textile : • 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 shirts, lingerie, jeans and shoes (even if not all yet validated) • Determine the appropriate granularity • Regarding • Technological representativeness • Geographical representativeness • Temporal representativeness • Considering for each differentiation • The relative environmental impact • The information accessibility for the companies that put products on the market (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 Mode 1: Purchasing existing or adapted data From databases suppliers with which the ADEME has a framework contract For lot 3: PE, Cycleco Mode 2: Data co-production In order to fill missing data in specific sectors Projects co-funded by ADEME with research and technical partners Ongoing: AgriBalyse for agriculture products, ACYVIA for food industry, GIE-Solinnen for pulp & paper Mode 3: Third party In order to allow integrating data not yet available in existing databases In order to promote assessment by the industry 6

7. Impact categories • GT where textile is a need • GT4: Beauty, hygiene and health products • GT5: Apparel, household textile, and shoes • GT7: Furniture • GT10S: Sport equipment (e.g. camping material)

8. Impact categories • Categories for PCRs specific to textile • Common categories • Climate change (IPCC 2007) • Eutrophication (Recipe 2008) • Water consumption (direct flow) • Other categories mentioned in current textile PCRs • Resource depletion (EDIP 97 (2004)) (shirt, underwear, shoes) • Non renewable energy resources (in MJ) (shirt) • Photochemical ozone formation (underwear) • Water toxicity (underwear) • Categories for other PCRs: shoes, furniture • Climate change (furniture, shoes) • Resource depletion (furniture, shoes) • Acidification – Recipe 2008 (furniture) • Photochemical ozone formation – Recipe 2008 (furniture) • Eutrophication (shoes)

9. Data aggregation Different typologies exist in PCR Data need will be defined for those two typologies along the presentation

10. Data aggregation • At least two levels of aggregation are required • Fully aggregated for data not specific to textile sector (e.g. an inventory “cotton textile”) • Most of the parameters will be averages or most representative • A very limited number of parameters could be specific (e.g. production country) • Not aggregated at all data specific to textile sector • Decomposition of textile production in elementary processes – e.g. production of fibers, electricity consumption • These elementary processes have to be defined in PCRs as well as the parameters related to them (country, amount of electricity)

11. Data aggregation Electricity consumption Fiber production kWh Spinning m3 Water consumption kg Fabric manufacturing % Textile production Chemicals Finishing DCO, etc. Material wastage Confection Water discharge and treatments …

12. Fibers – Data need • PCR for jean, shirt and underwear • Primary data: type and mass of fibers • Semi-specific data: country of production of fibers

13. Fibers – Technological representativeness • Market data for textile fibers in Europe • Table representative for France? • Available market data to differentiate organic and conventional cultures?

14. Fibers – Technological representativeness • Cultivation/breeding • Must there be some technological differentiation in a same fiber LCI ? Such as: • Organic cultures vs. conventional (cotton, wool…) → see discussion in next slide • Production yield • For viscose, different types of origin (e.g. bamboo) • For synthetic fibers, the representativeness of polymers production will refer to conclusions of technical committee for plastics

15. Fibers – Geographical representativeness • What are the differences from a region to another? • Pesticides and fertilizers types, quantity and origin • Electricity mix • Water consumption • For each fiber, what geographical level to use? → national, continental or global? • If national, what countries produce fibers ultimately sold in France? (e.g. USA and China for cotton) – Are there statistics of fibers origin in textiles sold in France? FAO gives world statistics production for natural fibers, for 2010 http://faostat.fao.org/ • For synthetic fibers, the representativeness of polymers production will refer to conclusions of technical committee for plastics

16. Fibers – organic cultures • Since Usetox and biodiversity are not yet validated indicators, organic culture may have a bigger impact on selected indicators than conventional culture because of lower yields • Comparison not yet feasible • Ongoing & planned projects • Production of USEtox CFs for phytosanitary products: to be launched in 2013 • The Ministry of Ecology is developing its own indicator to assess biodiversity for agriculture productions

17. Fibers – Databases

18. Fibers – Co-products allocation rules • Fibers co-products are • Seed and fiber for cotton, linen… • Sulfuric acid and sodium sulfate for viscose • Meat, milk and wool from sheeps • Fruits, wood, leaves for the production of silk • Are there propositions/recommendations from the technical committee?

19. Accessories – Data need • PCRs requirements • Primary data • Type and mass of each material • Manufacturing site (country) for jean PCR • Semi-specific data • Manufacturing site (country) for underwear and shirt PCRs • Secondary data (→ included in inventory) • Power consumption for jean • Water consumption for jean • Loss rate for jean

20. Accessories – Technological representativeness • Raw material : transversal material (see ad hoc committee) • Are there specific needs for accessories in terms of • Material? • Forming process?

21. Spinning – Data need • Last GT5 discussion for PCRs specific to textile • For other PCRs: all data are a priori secondary

22. Spinning – data need • The PCRs and last GT discussions consider this step as a sum of elementary processes • Are there missing processes? • Spinning may include in addition (source: preliminary study) • Gluing, Lubricant (mineral or vegetal), Surfactant non ionic, Ethylene glycoln Acid polyacrylic, PVA, Starch • Are those elements neglected on purpose? Or should they be included? • Should there be an average composition or a most representative input depending on the fiber/the type of spinning?

23. Spinning – Technological representativeness What is the geographic representativeness ?

24. Fabric manufacturing and confection – Data need • Last GT5 discussion for PCRs specific to textile • For other PCRs: all data are a priori secondary

25. Fabric manufacturing and confection – Data need • The PCRs and last GT discussions consider those steps as a sum of elementary processes • Are there missing processes? • Weaving may include lubricant • Non weaving may include polymers • Are those elements neglected on purpose? Or should they be included? • Should there be an average composition or a most representative input depending on the fiber/the type of spinning?

26. Fabric manufacturing and confection – Technological representativeness What is the geographic representativeness ?

27. Finishing – Data need • Last GT5 discussion for PCRs specific to textile • For other PCRs: all data are a priori secondary

28. Finishing – Data definition • Finishing processes may take place after every step of textile production (fiber, yarn, and fabric) • The way to address finishing is not fixed yet in PCRs • Finishing can be considered in different ways • Sum of elementary processes (e.g. electricity consumption, chemicals…) • Average inventories per type of finishing (e.g. one inventory “printing”) • And intermediate situations

29. Finishing – Data definition Electricity consumption Printing kWh Dyeing m3 Water consumption kg Bleaching % Finishing Chemicals Drying DCO, etc. Material wastage Coating Water discharge and treatments …

30. Textile production – Finishing Dyeing 1 Electricity consumption Finishing Printing Sum of average inventories Sum of elementary processes X kWh … Water consumption X liters Finishing X kg Chemicals Dyeing without electricity, water, chemicals … Printing without electricity, water, chemicals 1 1 … 1 X kWh Electricity consumption Finishing Intermediate situation X liters Water consumption X kg Chemicals

31. Textile production – Technological representativeness

32. Textile production – Technological representativeness

33. Textile production – Geographic representativeness What is the geographic representativeness ?

34. Textile production – Finishing – Chemicals • What granularity for chemicals regarding the production phase and the discharge in water? • Global (one inventory “chemicals for textile finishing”) • By family (e.g. inventory for “dyeing agents”) • By chemical (e.g. “chromium complex azoic dyestuff”) • Geographical representativeness: global (proposal)

35. Textile production – Finishing – Wastewater treatment → To be discussed by a specific Technical Committee on WWTP (end of year 2012) In short term • The database does not allow to have a dynamic model for WWTP depending on wastewater composition • → A finite quantity of inventories is required • Proposal • Functional unit: 1 m³ of water treated and related to the data “water consumption” • Several level of water treatment depending on • The typology of input water (e.g. water from finishing, water from dyeing…) • The quality of the treatment plant (e.g. no WWTP, average quality, BAT quality…) • How many levels to choose and how to characterize them?

36. Textile production – Databases

37. Aggregated data for non specific sectors Proposal • Two types of inventories • Cradle-to-gate for fabric production (without finishing processes) • Example: “cotton, weaved, Italy” • If there is a mix of fibers in a fabric (e.g. 80% cotton, 20% acrylic), is it a good approach to sum the two basic processes (0.8 * “cotton, weaved, Italy” + 0.2 * “acrylic, weaved, Italy”) • Gate-to-gate for finishing because it can take place or not at any step • Example: “dyeing”

38. Aggregated data for non specific sectors Proposal

39. Use phase – Data need • PCR for jean • Primary data • Label of utilization advices • Semi-specific data • Heat of temperature • Drying in machine • Ironing • Secondary data • Energy consumption and water consumption for above steps • Type and quantity washing products

40. Use phase – Data need • Must the production and end-of-life of the machine be included in the scope? • Database will include one generic inventory for washing products • Market share (AFISE, 2010) • Powder: 20 % • Liquid: 52 % • Concentrated liquid: 4 % • Other: 24 % • Product composition: on Cleanright website (http://uk.cleanright.eu/)

41. Textile end of life – scenario • PCR for lingerie and shoes: household waste (i.e. incineration and landfill – cf. ad hoc committee) • PCR for jean: most recent data from EcoTLC • Taux de collecte sélective : 18% • Taux de réemploi après collecte : 58% • Taux de recyclage après collecte : 22% • Taux d’élimination après collecte : 20% • Taux d’élimination : 82% • Taux d’incinération avec valorisation énergétique : 43,6% • Taux d’incinération sans valorisation énergétique : 2.3% • Taux d’enfouissement : 54,2% • Lingerie and jean not coherent

42. Textile end of life – scenario • Incineration and landfill – see ad hoc committee • Reuse • Extension of lifetime Is reuse taken into account in the proposals made for life time? • Recycling approach (credits for avoiding virgin material) • Recycling (see next slide)

43. Textile end of life – recycling allocation What allocation rule for textile recycling? • It should be determined in an economic study • PCR for jean is not specific • 0-100 by default • 100-0 if the industrial has a traceability system to justify he uses recycled textiles • This rule leads to double counting • What differentiations for textile recycling processes? • Type of fiber • Outlet • Country • … • What are the avoided material application? (e.g. fiber, yarn, textile, rag…)