The numbers are becoming harder to ignore. Let’s look at a few examples.

🇳🇱 The Netherlands: in 2026, textile collection and pre-sorting are operating at a net shortfall of €0.07–0.12 per kg, while sorting faces a shortfall of €0.07–0.14 per kg. That means up to €140 of deficit for every tonne sorted.

🇬🇧 The UK: textile collectors and sorters are already paying around £88 million every year to deal with worn-out clothes. If the existing system collapses, local authorities could face another £64 million a year in disposal costs.

🇫🇷 France: the government has provided exceptional support of €49 million for 2025 and €57 million for 2026 for textile collection and sorting operators.

🇪🇺 At European level: scaling textile-to-textile recycling to around 15% by 2035 could require €8–11 billion in capital investment, alongside €5–6.5 billion in annual operating costs.

📉 At the same time, Europe generates around 15.2 million tonnes of textile waste every year, yet less than 1% is recycled back into new textiles, according to the latest BCG x ReHubs report published in March 2026. The report says Europe needs to reach around 2.7 million tonnes of textile-to-textile recycling annually by 2035 to create a viable circular textile system.

⚙️ And technology is moving fast.

TOMRA Recycling is developing automated textile sorting around its AUTOSORT™ platform, combining NIR, VIS and electromagnetic sensing to identify fibre composition, colour and contaminants.

ANDRITZ is developing mechanical recycling lines for post-consumer textiles, including opening, tearing and fibre preparation.

STADLER Group is applying automated sorting technology to textile waste, focusing on the separation of different textile streams before further processing.

Valvan has developed Fibersort, using NIR technology to automatically identify textile fibres by composition.

Pellenc ST is applying optical sorting technology to textile streams using NIR-based identification.

NewRetex A/S combines NIR, RGB cameras, machine learning and traceability to automate the sorting of post-consumer textiles into multiple material fractions.

🇪🇸 PICVISA combines NIR, VIS and deep learning in its ECOSORT TEXTIL platform to classify textiles by fibre, colour and garment type.

🔄 The direction is clear: the industry is moving from basic textile waste handling towards automated identification, higher-purity sorting and feedstock preparation for textile-to-textile recycling.

But technology alone will not close the loop. The real question is becoming much bigger: can Europe build a textile recycling system that is not only technically possible, but economically viable?

Sources: Stichting UPV Textiel / KPMG, WRAP, French Ministry for Ecological Transition

Image credit: NewRetex, unsplash