Sustainability Metrics
ESG scores across textile supply chains | 20 producing countries
Metric Comparison
Normalized scores — green is better, red is worse
Composite Score Ranking
Weighted average of all four metrics (equal weights, 0–100)
All Countries — Click headers to sort
| # | Country | Carbon | Water | Score ↓ |
|---|---|---|---|---|
| 1 | Germany | 2,100 | 55 | 80 |
| 2 | Italy | 2,300 | 70 | 73 |
| 3 | South Korea | 2,800 | 60 | 64 |
| 4 | USA | 2,500 | 75 | 64 |
| 5 | Brazil | 1,200 | 110 | 62 |
| 6 | Sri Lanka | 2,400 | 105 | 50 |
| 7 | Vietnam | 3,200 | 85 | 45 |
| 8 | Thailand | 3,400 | 90 | 45 |
| 9 | Mexico | 2,900 | 100 | 45 |
| 10 | Ethiopia | 800 | 140 | 41 |
| 11 | Turkey | 2,900 | 130 | 40 |
| 12 | Indonesia | 4,100 | 95 | 36 |
| 13 | Cambodia | 3,500 | 100 | 36 |
| 14 | Myanmar | 2,700 | 95 | 35 |
| 15 | Morocco | 3,800 | 115 | 35 |
| 16 | China | 3,850 | 120 | 34 |
| 17 | Pakistan | 3,100 | 185 | 21 |
| 18 | India | 4,500 | 165 | 20 |
| 19 | Bangladesh | 4,200 | 150 | 20 |
| 20 | Egypt | 3,300 | 195 | 20 |
Methodology
Carbon Footprint — Estimated from national grid carbon intensity (Low Carbon Power, 2024–25) combined with textile-specific energy consumption (~5 MWh/ton from DOE textile energy reviews). Countries with coal-heavy grids score higher emissions.
Water Usage — Based on Water Footprint Network cotton water footprint assessments and ICAC country-level data. Cotton-intensive producers (Pakistan, Egypt, India) show higher usage; synthetic-focused countries are lower.
Labor Index — Composite of minimum wage adequacy, working hours, and safety standards from ILO ILOSTAT garment worker data and ITUC Global Rights Index 2024 ratings. Scale: 0 (worst) to 100 (best).
Transparency Index — Derived from Fashion Transparency Index 2024 (Fashion Revolution) brand scores aggregated by country, supplemented by national supply chain legislation (e.g., German LkSG). Scale: 0 (opaque) to 100 (transparent).
Composite Score — All four metrics normalized to 0–100 (carbon and water inverted, since lower raw values are better), then averaged with equal weights (25% each).