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The full breakdown

How the figure for Cotton yarn is built

Every stage the model passes through, with its number. Each table below divides the same headline figure a different way, and each one adds up to it exactly — the page checks, and refuses to show a table that does not.

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The headline

One item is one kilogram of spun cotton yarn. Scenario Arms and resources, using FIGARO 2023. Each figure is the middle result of 2,000 runs of the calculation, with the range that holds nine in ten of them beside it, and the grade that range earns.

Materials method — 8.0 × 10⁻⁹ per item(0.32–2.0 × 10⁻⁸)LOWS-ARMS · run 2179 · methodology v0.1 · data dv-20261007-44r

Money method — 5.2 × 10⁻⁷ per €1,000 spent in its industry(3.4–7.7 × 10⁻⁷)MEDIUMS-ARMS · run 2179 · methodology v0.1 · data dv-20261007-44r

Each step below is a middle estimate. The model works out a range for the whole figure, not for each step, so the range that applies to a step is the headline’s.

1 · What it is made of, and what each material carries

How much of each raw material is in one item, the deaths linked to each kilogram of it in this calculation, and the two multiplied together: its part of the headline figure.

1 · What it is made of, and what each material carries
MaterialPer itemDeaths per kgPart of the figureShare
Cotton0.0030 t2.6 × 10⁻⁹8.0 × 10⁻⁹100%
Total8.0 × 10⁻⁹= the headline figure, 8.0 × 10⁻⁹

2 · Where the harm was counted

The same headline, by the country where the harm the materials carry was counted.

2 · Where the harm was counted
CountryPart of the figureShare
Burkina Faso5.5 × 10⁻⁹69%
Mali8.6 × 10⁻¹⁰11%
Sudan6.6 × 10⁻¹⁰8.3%
Mexico3.6 × 10⁻¹⁰4.5%
United States2.3 × 10⁻¹⁰2.9%
Syrian Arab Republic9.2 × 10⁻¹¹1.2%
Australia6.8 × 10⁻¹¹0.85%
Turkiye4.3 × 10⁻¹¹0.53%
Nigeria3.2 × 10⁻¹¹0.40%
Afghanistan1.7 × 10⁻¹¹0.21%
Argentina1.7 × 10⁻¹¹0.21%
Uzbekistan1.5 × 10⁻¹¹0.19%
Turkmenistan1.5 × 10⁻¹¹0.18%
Congo, Dem. Rep.1.4 × 10⁻¹¹0.17%
Niger7.8 × 10⁻¹²<0.1%
Spain4.9 × 10⁻¹²<0.1%
Greece4.2 × 10⁻¹²<0.1%
Colombia3.9 × 10⁻¹²<0.1%
Azerbaijan2.4 × 10⁻¹²<0.1%
Israel8.9 × 10⁻¹³<0.1%
Thailand1.3 × 10⁻¹³<0.1%
Total8.0 × 10⁻⁹= the headline figure, 8.0 × 10⁻⁹

3 · Through which kind of harm

The same headline, by kind of harm: war, work, poverty, pollution.

3 · Through which kind of harm
Kind of harmPart of the figureShare
Conflict and political violence7.6 × 10⁻⁹95%
Work4.0 × 10⁻¹⁰5.0%
Total8.0 × 10⁻⁹= the headline figure, 8.0 × 10⁻⁹

4 · Which wars

The war deaths in the headline, by war. Harm of any other kind is the row that names no war.

4 · Which wars
WarPart of the figureShare
Burkina Faso: Government4.6 × 10⁻⁹58%
Burkina Faso: Islamic State9.4 × 10⁻¹⁰12%
Mali: Government7.1 × 10⁻¹⁰8.9%
Sudan: Government6.6 × 10⁻¹⁰8.3%
Not placed4.0 × 10⁻¹⁰5.0%
Jalisco Cartel New Generation - Sinaloa Cartel3.6 × 10⁻¹⁰4.5%
Mali: Islamic State1.5 × 10⁻¹⁰1.8%
Syria: Government9.2 × 10⁻¹¹1.2%
Nigeria: Government3.3 × 10⁻¹¹0.41%
Afghanistan: Government1.7 × 10⁻¹¹0.21%
Government of Rwanda - Civilians7.2 × 10⁻¹²<0.1%
DR Congo (Zaire): Government6.4 × 10⁻¹²<0.1%
Niger: Islamic State5.8 × 10⁻¹²<0.1%
Colombia: Government1.9 × 10⁻¹²<0.1%
Niger: Government1.1 × 10⁻¹²<0.1%
Total8.0 × 10⁻⁹= the headline figure, 8.0 × 10⁻⁹

5 · The money method: which industries

The figure per €1,000, by the industry where the harm happened, anywhere in the supply chain.

5 · The money method: which industries
IndustryPart of the figureShare
Mining and quarrying3.7 × 10⁻⁷73%
Crop and animal production, hunting and related service activities9.9 × 10⁻⁸19%
Manufacture of basic metals3.0 × 10⁻⁸5.8%
Water collection, treatment and supply3.3 × 10⁻⁹0.63%
Public administration and defence; compulsory social security1.9 × 10⁻⁹0.36%
Manufacture of fabricated metal products, except machinery and equipment1.8 × 10⁻⁹0.35%
Electricity, gas, steam and air conditioning supply1.7 × 10⁻⁹0.33%
Manufacture of other transport equipment1.7 × 10⁻⁹0.32%
Manufacture of coke and refined petroleum products9.6 × 10⁻¹⁰0.19%
Forestry and logging4.4 × 10⁻¹⁰<0.1%
Real estate activities2.6 × 10⁻¹⁰<0.1%
Fishing and aquaculture1.2 × 10⁻¹⁰<0.1%
Total5.2 × 10⁻⁷= the headline figure, 5.2 × 10⁻⁷

6 · The money method: which countries

The figure per €1,000, by the country of the industry where the harm happened.

6 · The money method: which countries
CountryPart of the figureShare
Not placed5.0 × 10⁻⁷96%
Mexico6.5 × 10⁻⁹1.3%
Russian Federation4.0 × 10⁻⁹0.78%
United States3.1 × 10⁻⁹0.60%
Turkiye2.1 × 10⁻⁹0.42%
Italy9.7 × 10⁻¹⁰0.19%
Argentina4.3 × 10⁻¹⁰<0.1%
Korea, Rep.4.1 × 10⁻¹⁰<0.1%
Spain3.1 × 10⁻¹⁰<0.1%
Germany2.5 × 10⁻¹⁰<0.1%
Australia2.3 × 10⁻¹⁰<0.1%
Canada2.1 × 10⁻¹⁰<0.1%
Japan2.0 × 10⁻¹⁰<0.1%
Austria1.7 × 10⁻¹⁰<0.1%
Poland1.4 × 10⁻¹⁰<0.1%
France1.4 × 10⁻¹⁰<0.1%
Romania1.2 × 10⁻¹⁰<0.1%
Bulgaria1.1 × 10⁻¹⁰<0.1%
Czechia6.8 × 10⁻¹¹<0.1%
Ireland4.3 × 10⁻¹¹<0.1%
Finland4.1 × 10⁻¹¹<0.1%
Lithuania4.0 × 10⁻¹¹<0.1%
Hungary3.8 × 10⁻¹¹<0.1%
Portugal3.4 × 10⁻¹¹<0.1%
Slovak Republic2.6 × 10⁻¹¹<0.1%
Croatia2.3 × 10⁻¹¹<0.1%
Norway2.1 × 10⁻¹¹<0.1%
Switzerland2.1 × 10⁻¹¹<0.1%
Sweden2.0 × 10⁻¹¹<0.1%
Greece1.8 × 10⁻¹¹<0.1%
Denmark1.7 × 10⁻¹¹<0.1%
United Kingdom1.5 × 10⁻¹¹<0.1%
Netherlands8.9 × 10⁻¹²<0.1%
Slovenia6.8 × 10⁻¹²<0.1%
China6.6 × 10⁻¹²<0.1%
Brazil6.0 × 10⁻¹²<0.1%
South Africa5.0 × 10⁻¹²<0.1%
Latvia2.5 × 10⁻¹²<0.1%
Luxembourg2.4 × 10⁻¹²<0.1%
Belgium2.3 × 10⁻¹²<0.1%
Malta1.6 × 10⁻¹²<0.1%
Serbia1.2 × 10⁻¹⁴<0.1%
Total5.2 × 10⁻⁷= the headline figure, 5.2 × 10⁻⁷

What this trail does not show

Sources behind this figure

HumanToll 2026, run 2179, methodology v0.1. https://quiescence.eu/humantoll/explain/cotton-yarn/

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