Farming
Cotton
Where it comes from, what share of an industry’s output it is, and which wars the model links to it.
This page shows production, shares and inputs. It does not show a death toll per tonne. The shares below say what part of an industry’s output this material is, and what part of a war’s harm the model links to it. Multiplying either by a number of people gives a result, and no result is published until it comes from a recorded calculation, with a range and a confidence grade.
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The products it reaches
Each product whose list of materials contains Cotton, with its deaths per item by the materials method and the part of that figure this material accounts for.
Scenario Economic-embedded, using FIGARO 2023.
| Product | Deaths per item |
|---|---|
| Cotton fabric Part from here: 100% | 3.9 × 10⁻⁸ per item(1.5–9.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton T-shirt Part from here: 100% | 6.4 × 10⁻⁹ per item(0.25–1.6 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton yarn Part from here: 100% | 3.8 × 10⁻⁸ per item(1.5–9.3 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Denim fabric Part from here: 100% | 3.8 × 10⁻⁸ per item(1.5–9.8 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Jeans Part from here: 100% | 3.2 × 10⁻⁸ per item(1.2–8.0 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
The figure is the product’s own, with its range. The share beside it is a middle estimate only: the calculation stores a range for each figure, not for each part of one.
Deaths per tonne produced are calculated for this material too, but not shown: that figure has no range yet.
Who produces it
The publisher’s own figures for 2024, across 98 countries. Nothing here has been linked to anything yet.
| Country | Produced | Share | Figure |
|---|---|---|---|
| China CHN |
18,700,000 t | 26.0% | official |
| India IND |
15,000,000 t | 20.8% | official |
| United States USA |
9,573,295 t | 13.3% | official |
| Brazil BRA |
8,523,606 t | 11.8% | official |
| Pakistan PAK |
3,500,618 t | 4.9% | official |
| Uzbekistan UZB |
2,938,089 t | 4.1% | official |
| Australia AUS |
2,400,000 t | 3.3% | official |
| Turkiye TUR |
2,243,000 t | 3.1% | official |
| Argentina ARG |
1,269,399 t | 1.8% | official |
| Burkina Faso BFA |
769,440 t | 1.1% | gap filled |
| Mali MLI |
640,000 t | 0.9% | official |
| Benin BEN |
635,976 t | 0.9% | official |
| Turkmenistan TKM |
600,238 t | 0.8% | official |
| Cameroon CMR |
490,900 t | 0.7% | external |
| Mexico MEX |
479,732 t | 0.7% | official |
Production figures: FAO, FAOSTAT, CC BY 4.0. FAO does not endorse any figure made from them, and none is implied.
What share of an industry’s output it is
Worked out from production, not typed in: an industry’s split between materials is the share of what it actually produced. These are WORLD figures, all years together; the model itself uses a separate mix for every country and year, because a world mix would link deaths in the Congo to copper mined in Chile.
| Industry | Share of output | How |
|---|---|---|
| Crop and animal production, hunting and related service activities 01 |
2.1% | world mix · LOW |
| Agriculture, forestry and fishing A |
1.8% | world mix · LOW |
Weight and value answer different questions and are never added together. A tonne of gold weighs the same as a tonne of iron ore but is worth far more, so the share of an industry’s harm this material gets depends on which one is used.
Which wars the model links to it
The average share of each war’s harm that the model links to this material, taken over the countries and years the war covers. An average of shares is not a share of a total, and the two differ whenever the coverage is uneven.
| War | Average share of its harm | Years |
|---|---|---|
| Burkina Faso: Government | 5.58% | 9 |
| Burkina Faso: Islamic State | 5.58% | 9 |
| Mali: Government | 4.49% | 9 |
| Mali: Islamic State | 4.49% | 9 |
| Afghanistan: Government | 2.04% | 37 |
| Ethiopia: Government | 1.34% | 3 |
| Syria: Government | 1.15% | 15 |
| Sudan: Government | 0.81% | 37 |
| Jalisco Cartel New Generation - Sinaloa Cartel | 0.55% | 11 |
| Nigeria: Government | 0.43% | 17 |
| Iraq: Government | 0.41% | 25 |
| Government of Rwanda - Civilians | 0.36% | 16 |
These are shares of a war, not counts of people. The number of deaths they stand for is calculated but not published: it has no range yet and has not passed the test on past years.
Harm per tonne and per euro
Harm per tonne and harm per euro are both calculated. Neither is shown yet.
Harm per tonne of this material is defined for 55 years, 1970 to 2024: the years for which the model has both the harm and the world production of this material.
Both are numbers of people divided by an amount, from a calculation that has no range and has not passed the test on past years yet, and nothing of that kind is published until it has. What this page can say now is whether each can be worked out, and on what basis.
Which products use it
Semi-finished and finished products whose list of materials reaches this material, through every step in between, and how much of it one of them needs — waste included.
| Product | Needs |
|---|---|
| Cotton fabric
semi-finished product |
3.11 kg for one kilogram of cotton fabric |
| Cotton yarn
semi-finished product |
3.03 kg for one kilogram of spun cotton yarn |
| Denim fabric
semi-finished product |
3.10 kg for one kilogram of cotton denim fabric |
| Cotton T-shirt
finished product |
518 g for one 100% cotton T-shirt of 150 g |
| Jeans
finished product |
2.55 kg for one pair of stretch denim jeans of about 725 g, as Nudie Jeans made one style in 2017 |
Amounts, not harm: how much of the material the product’s supply chain needs. The harm that carries is not shown.
What producing it uses up
What one t of this material uses up, from published technical figures. Where the data allows, a figure for a particular country replaces the world figure shown here.
| Input | Per unit | Source |
|---|---|---|
| Fresh water | 3,644 m3 | Mekonnen, M.M. & Hoekstra, A.Y. (2011), "The green, blue and… · LOW |
Fresh water: Global average, green + blue + grey. The same paper gives country figures varying by a factor of five; using the global average here is the fallback plan/14 S13 warns about, and it is marked global and LOW so that a country result can say so.
Sources
| Version of the data | Downloaded | File fingerprint |
|---|---|---|
| faostat · qcl-20251231 | 2026-09-29 | c5835418c18f9322… |
FAO. Food and Agriculture Organization of the United Nations, FAOSTAT. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — qcl-20251231, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Production_Crops_Livestock_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.