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Thread of Change: Using data to Revolutionise Textile Waste Management and Recycling in Pakistan

Ongoing
Ongoing
Project Link
Reverse Resources, Sustainable Manufacturing and Environmental Pollution (SMEP), Foreign, Commonwealth and Development Office (FCDO), United Nations Conference on Trade and Development (UNCTAD), NTU (National textile university, located in Faisalabad, Punjab, Pakistan), Datini Fibres, Artistic Miliners

Textile Waste Quantities

*All data is in tonnes per annum
Post Consumer
Textile Waste
Rewearable
887,000
Pre Consumer
Textile Waste
Post Industrial
Textile Waste
Recyclable
Imported
Textile Waste
Other
Exported post
consumer textiles
Pre Consumer
Textile Waste
887,000
Total Textile Waste
*More information will be added at a later date. Sign up for updates
Textile Waste compositions
*All data is in tonnes per annum
Post consumer textile waste
POST CONSUMER Textile Waste
Cotton-rich blend (>50% cotton)
100% cotton
95% cotton (up to 5 % elastane)
Poly-cotton blends (>50% polyester)
Poly-rich blend (>50% polyester)
100% Polyester
All other blends
POST Industrial Textile Waste
Pre Consumer Textile Waste
887,000
Cotton-rich blend (>50% cotton)
36%
100% cotton
20%
95% cotton (up to 5 % elastane)
12%
Poly-cotton blends (>50% polyester)
9%
Poly-rich blend (>50% polyester)
11%
100% Polyester
6%
All other blends
6%
pre consumer Textile Waste
Cotton-rich blend (>50% cotton)
100% cotton
95% cotton (up to 5 % elastane)
Poly-cotton blends (>50% polyester)
Poly-rich blend (>50% polyester)
100% Polyester
All other blends
IMPORTED Textile Waste
Cotton-rich blend (>50% cotton)
100% cotton
95% cotton (up to 5 % elastane)
Poly-cotton blends (>50% polyester)
Poly-rich blend (>50% polyester)
100% Polyester
All other blends
Data Methodology

RR uses a comprehensive methodology to gather data on textile waste in Pakistan. This includes utilizing the UN Comtrade database to understand import and export volumes of fiber, yarn, and fabric, supplemented by NTU's data on domestic fiber production.

We use the RR platform to derive waste percentages at each production stage and estimate textile waste volumes based on specific fiber compositions. On-the-ground insights from our work and visits to Pakistan, along with desk research from sources like GIZ and relevant industry associations, further validate our data.

In addition, we are collaborating with ReMatters, who are conducting a cotton Life Cycle Assessment (LCA) in Pakistan, providing valuable data for both Pakistan and Bangladesh. RR is also implementing a custom waste mapping program for brands to enhance visibility into the recycling process.

This methodology helps formalize the structure for the demand and supply of textile waste, establishing a digitally verifiable trace for textile-to-textile (T2T) recycling and facilitating the creation of key performance indicators (KPIs) for scalable circularity.

Upcoming & Notes

We have compiled a public report including a waste mapping and assessing the textile recycling potential of Pakistan. And in the next phase we will start exploring opportunities for post-consumer textile waste in Pakistan.

The report highlights the significant untapped potential in Pakistan's textile recycling industry, suggesting that scaling recycling initiatives can yield economic and environmental benefits. High-quality textile waste often ends up in low-value applications due to brands' lack of visibility into their discarded textiles, even though high-end recyclers seek such feedstock. The informal waste handling sector, crucial for linking textile waste supply to recycling, faces challenges such as leakage, hindering supply chain compliance and transparent textile-to-textile (T2T) recycling.

The collaboration aims to formalise the structure for the demand and supply of textile waste, establishing a digitally verifiable trace for T2T recycling. RR is also implementing a custom waste mapping program to enhance brands' visibility into the recycling process. The report provides essential data to initiate a circular supply chain, helping to identify textile waste volume, location, composition, and recycling potential, and setting KPIs for scalable circularity.