Misapplied lifecycle assessment data could distort textile sector decision-making and reduce the credibility of environmental claims, industry nonprofit Textile Exchange has warned. In a new guidance, it has warned against unverified fibre comparisons and dependence on averaged figures, urging stronger primary data collection and broader measurement to include biodiversity, soil health, animal welfare, and livelihoods alongside established environmental impact categories.
- The guidance warns against comparing separate LCA studies unless they are explicitly designed and validated as comparative under the relevant ISO standards.
- It has advised brands to favour supplier-specific primary data for Scope 3 footprinting rather than generic averages to improve accuracy.
- Current LCAs often omit context-specific nature-related impacts such as biodiversity, soil health, and animal welfare, prompting the organisation to propose an LCA+ framework.
- The guidance 'Ensuring Integrity in the Use of Lifecycle Assessment Data' was issued by Textile Exchange on Thursday.
THE GUIDANCE: Textile Exchange’s guidance explains how lifecycle assessment follows environmental impacts from raw material sourcing to pre-spin processing for seven major fibres. It calls for clear articulation of underlying choices, thorough dataset records, and wider database sharing. The document also presents its ‘LCA+’ concept, adding biodiversity, soil health, animal welfare, and livelihoods to conventional metrics for evaluating textile and apparel supply chains.
WHAT’S AT STAKE: Misuse of lifecycle assessment data could distort corporate reporting, could undermine targets, and mislead policy. Textile Exchange warns that flawed comparisons and reliance on averages risk hiding real impacts. The guidance calls for stronger primary data, context-specific analysis, and complementary qualitative tools to ensure interventions reduce environmental harm and protect livelihoods.
- Inaccurate comparisons can misallocate investment and weaken efforts to reduce greenhouse gas emissions at the systems level and affect operational planning.
- Overreliance on averaged background data may obscure regional risks such as water stress or biodiversity loss in specific sourcing areas.
- Poorly documented assumptions and allocation methods can produce inconsistent results that undermine stakeholder trust, regulatory compliance, and confuse benchmarking exercises.
- Improving primary data collection, transparency, and critical review is necessary to make LCA outputs reliable for corporate reporting and targets.