The full breakdown

How the figure for Roasted coffee 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.

Is something on this page wrong? Report it →

The headline

One item is one kilogram of roasted coffee beans. Scenario Economic-embedded, 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 — 6.7 × 10⁻⁸ per item(0.27–1.7 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r

Money method — 3.4 × 10⁻⁶ per €1,000 spent in its industry(2.3–5.1 × 10⁻⁶)MEDIUMS-MAX · run 2259 · methodology v1.0 · 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
Material	Per item	Deaths per kg	Part of the figure	Share
Coffee	0.0012 t	5.7 × 10⁻⁸	6.7 × 10⁻⁸	100%
Total			6.7 × 10⁻⁸	= the headline figure, 6.7 × 10⁻⁸

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
Country	Part of the figure	Share
Ethiopia	2.4 × 10⁻⁸	36%
Central African Republic	2.0 × 10⁻⁸	30%
Brazil	5.2 × 10⁻⁹	7.7%
Colombia	4.1 × 10⁻⁹	6.1%
Honduras	4.0 × 10⁻⁹	5.9%
Congo, Dem. Rep.	2.5 × 10⁻⁹	3.7%
Yemen, Rep.	1.3 × 10⁻⁹	2.0%
Uganda	1.1 × 10⁻⁹	1.6%
Haiti	8.9 × 10⁻¹⁰	1.3%
Cameroon	7.5 × 10⁻¹⁰	1.1%
Mexico	6.6 × 10⁻¹⁰	0.98%
Kenya	5.9 × 10⁻¹⁰	0.88%
Togo	4.0 × 10⁻¹⁰	0.59%
Burundi	3.5 × 10⁻¹⁰	0.53%
Myanmar	2.5 × 10⁻¹⁰	0.37%
Guatemala	1.6 × 10⁻¹⁰	0.24%
Costa Rica	1.6 × 10⁻¹⁰	0.23%
Papua New Guinea	1.1 × 10⁻¹⁰	0.16%
Philippines	9.2 × 10⁻¹¹	0.14%
India	6.9 × 10⁻¹¹	0.10%
United States	5.8 × 10⁻¹¹	<0.1%
Thailand	4.2 × 10⁻¹¹	<0.1%
Indonesia	3.8 × 10⁻¹¹	<0.1%
Panama	3.7 × 10⁻¹¹	<0.1%
Nigeria	2.9 × 10⁻¹¹	<0.1%
Peru	2.1 × 10⁻¹¹	<0.1%
Sri Lanka	1.9 × 10⁻¹¹	<0.1%
Ecuador	1.9 × 10⁻¹¹	<0.1%
Mozambique	6.2 × 10⁻¹²	<0.1%
Venezuela, RB	6.2 × 10⁻¹²	<0.1%
Bolivia	4.3 × 10⁻¹³	<0.1%
Benin	3.2 × 10⁻¹³	<0.1%
Ghana	1.8 × 10⁻¹³	<0.1%
China	1.5 × 10⁻¹⁴	<0.1%
Saudi Arabia	5.8 × 10⁻¹⁵	<0.1%
Total	6.7 × 10⁻⁸	= the headline figure, 6.7 × 10⁻⁸

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 harm	Part of the figure	Share
Conflict and political violence	6.5 × 10⁻⁸	96%
Work	2.5 × 10⁻⁹	3.7%
Total	6.7 × 10⁻⁸	= the headline figure, 6.7 × 10⁻⁸

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
War	Part of the figure	Share
Ethiopia: Government/Amhara	1.3 × 10⁻⁸	19%
Central African Republic: Government	1.2 × 10⁻⁸	18%
AAKG - CPC	4.8 × 10⁻⁹	7.1%
Ethiopia: Oromiya	4.7 × 10⁻⁹	7.0%
M18 - MS-13	3.3 × 10⁻⁹	4.9%
Not placed	2.5 × 10⁻⁹	3.7%
Government of Ethiopia - Civilians	1.9 × 10⁻⁹	2.9%
OLA - Civilians	1.5 × 10⁻⁹	2.2%
Comando Vermelho - PCC	1.5 × 10⁻⁹	2.2%
Central African Republic: Logone	1.5 × 10⁻⁹	2.2%
IS - Civilians	1.4 × 10⁻⁹	2.1%
Fano - Civilians	1.3 × 10⁻⁹	2.0%
CPC - Civilians	1.3 × 10⁻⁹	2.0%
Anuak - Nuer	1.3 × 10⁻⁹	1.9%
Yemen (North Yemen): Government	1.1 × 10⁻⁹	1.7%
M18 - Civilians	6.9 × 10⁻¹⁰	1.0%
Bonde do Maluco - Comando Vermelho	5.4 × 10⁻¹⁰	0.80%
Kenya: Northeastern Province and Coast	5.2 × 10⁻¹⁰	0.77%
EGC - Civilians	4.9 × 10⁻¹⁰	0.73%
Cartel do Norte - Comando Vermelho	4.9 × 10⁻¹⁰	0.73%
Government of Central African Republic - Civilians	4.2 × 10⁻¹⁰	0.63%
URDPC - Civilians	4.0 × 10⁻¹⁰	0.59%
Amhara - Oromo	3.5 × 10⁻¹⁰	0.52%
Bonde dos 40 - PCC	3.5 × 10⁻¹⁰	0.51%
Uganda: Islamic State	3.0 × 10⁻¹⁰	0.45%
Colombia: Government	2.8 × 10⁻¹⁰	0.41%
FARC-EMC - Civilians	2.6 × 10⁻¹⁰	0.39%
Comando Vermelho - GDE	2.6 × 10⁻¹⁰	0.39%
Jalisco Cartel New Generation - Sinaloa Cartel	2.6 × 10⁻¹⁰	0.39%
Lengola - Mbole	2.6 × 10⁻¹⁰	0.39%
Nova Okaida - Estados Unidos	2.6 × 10⁻¹⁰	0.39%
GDE, PCC - Sindicato do Crime	2.6 × 10⁻¹⁰	0.38%
Burundi: Government	2.5 × 10⁻¹⁰	0.37%
JNIM - Civilians	2.5 × 10⁻¹⁰	0.37%
PCC - Sindicato do Crime	2.3 × 10⁻¹⁰	0.34%
Cameroon: Ambazonia	2.3 × 10⁻¹⁰	0.33%
Amigos Para Sempre - Família Terror Amapá	2.2 × 10⁻¹⁰	0.33%
Comando Vermelho - Civilians	1.9 × 10⁻¹⁰	0.28%
Government of Rwanda - Civilians	1.8 × 10⁻¹⁰	0.27%
DR Congo (Zaire): Government	1.8 × 10⁻¹⁰	0.27%
DR Congo (Zaire): Islamic State	1.8 × 10⁻¹⁰	0.27%
FARC-EMC - ELN	1.7 × 10⁻¹⁰	0.25%
Government of Haiti - Civilians	1.6 × 10⁻¹⁰	0.24%
Forces of Tony Peña - Los Hondureños	1.6 × 10⁻¹⁰	0.23%
Guraghe - Mareqo	1.5 × 10⁻¹⁰	0.23%
Togo: Government	1.5 × 10⁻¹⁰	0.23%
AQAP - Forces of the Presidential Leadership Council	1.5 × 10⁻¹⁰	0.23%
G9 - G-Pep	1.5 × 10⁻¹⁰	0.22%
Terre Noire - Civilians	1.4 × 10⁻¹⁰	0.21%
Myanmar (Burma): Government	1.4 × 10⁻¹⁰	0.20%
5 Segond, Taliban - Civilians	1.4 × 10⁻¹⁰	0.20%
Bonde dos 13, PCC - Comando Vermelho	1.4 × 10⁻¹⁰	0.20%
Bonde dos 40 - Comando Vermelho	1.4 × 10⁻¹⁰	0.20%
Cameroon: Government	1.3 × 10⁻¹⁰	0.20%
JAS - Civilians	1.3 × 10⁻¹⁰	0.19%
MS-13 - Civilians	1.3 × 10⁻¹⁰	0.19%
Grand Ravine - Civilians	1.3 × 10⁻¹⁰	0.19%
Ambazonia insurgents - Civilians	1.2 × 10⁻¹⁰	0.18%
FARC - Segunda Marquetalia - Civilians	1.1 × 10⁻¹⁰	0.17%
Jalisco Cartel New Generation - Santa Rosa de Lima Cartel	1.1 × 10⁻¹⁰	0.17%
M23 - VDP	1.1 × 10⁻¹⁰	0.17%
Mobondo - Civilians	1.1 × 10⁻¹⁰	0.16%
Government of Burundi - Civilians	1.1 × 10⁻¹⁰	0.16%
ELN - Civilians	1.1 × 10⁻¹⁰	0.16%
Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin	1.0 × 10⁻¹⁰	0.16%
Murle - Nuer	1.0 × 10⁻¹⁰	0.15%
Juarez Cartel - Sinaloa Cartel	1.0 × 10⁻¹⁰	0.15%
Comando Vermelho - Holanda	9.6 × 10⁻¹¹	0.14%
G-Pep - Civilians	9.6 × 10⁻¹¹	0.14%
Farmers (CAR) - Herders (CAR)	9.4 × 10⁻¹¹	0.14%
AAKG - Civilians	9.4 × 10⁻¹¹	0.14%
Los Costenos - Los Pepes	9.0 × 10⁻¹¹	0.13%
EGC - ELN, FARC-EMC	8.7 × 10⁻¹¹	0.13%
M23 - Civilians	8.7 × 10⁻¹¹	0.13%
EGC - ELN	8.3 × 10⁻¹¹	0.12%
Somalia: Government	7.7 × 10⁻¹¹	0.11%
Rwanda: Government	7.7 × 10⁻¹¹	0.11%
Carteles Unidos - Jalisco Cartel New Generation	7.6 × 10⁻¹¹	0.11%
Comando Vermelho - Massa	7.3 × 10⁻¹¹	0.11%
Government of DR Congo (Zaire) - Civilians	7.1 × 10⁻¹¹	0.11%
Nova Okaida - PCC	7.1 × 10⁻¹¹	0.11%
Bonde do Maluco - Katiara	6.7 × 10⁻¹¹	<0.1%
Bonde do Maluco - Civilians	6.7 × 10⁻¹¹	<0.1%
Cameroon: Islamic State	6.2 × 10⁻¹¹	<0.1%
Al-Shabaab - Civilians	5.8 × 10⁻¹¹	<0.1%
Philippines: Government	5.6 × 10⁻¹¹	<0.1%
Bonde dos 40 - Civilians	5.2 × 10⁻¹¹	<0.1%
Comando Vermelho - Terceiro Comando Puro	5.0 × 10⁻¹¹	<0.1%
Government of Myanmar (Burma) - Civilians	4.8 × 10⁻¹¹	<0.1%
Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos	4.4 × 10⁻¹¹	<0.1%
PCC - Civilians	3.7 × 10⁻¹¹	<0.1%
Gran Grif - Civilians	3.7 × 10⁻¹¹	<0.1%
400 Mawozo - Civilians	3.7 × 10⁻¹¹	<0.1%
EGC - Autodefensas Conquistadoras de la Sierra Nevada	3.7 × 10⁻¹¹	<0.1%
URDPC - Zaire self-defense group	3.6 × 10⁻¹¹	<0.1%
Ajeita - Bonde do Maluco	3.3 × 10⁻¹¹	<0.1%
Zaire self-defense group - Civilians	3.2 × 10⁻¹¹	<0.1%
Amhara - Gumuz	3.1 × 10⁻¹¹	<0.1%
VDP - Civilians	3.0 × 10⁻¹¹	<0.1%
Government of Colombia - Civilians	3.0 × 10⁻¹¹	<0.1%
Government of Cameroon - Civilians	2.9 × 10⁻¹¹	<0.1%
Philippines: Islamic State	2.7 × 10⁻¹¹	<0.1%
Government of Brazil - Civilians	2.5 × 10⁻¹¹	<0.1%
United Kingdom, United States of America - Yemen	2.4 × 10⁻¹¹	<0.1%
Indonesia: West Papua	2.4 × 10⁻¹¹	<0.1%
FPIC Chambre noire sanduku - URDPC	2.3 × 10⁻¹¹	<0.1%
Myanmar (Burma): Kachin	2.3 × 10⁻¹¹	<0.1%
FPIC Chambre noire sanduku - Civilians	2.3 × 10⁻¹¹	<0.1%
Anti-Bala - Bala na Cara	2.3 × 10⁻¹¹	<0.1%
Peru: Government	2.1 × 10⁻¹¹	<0.1%
Bonde dos 40 - PCM	2.1 × 10⁻¹¹	<0.1%
India: Kashmir	2.0 × 10⁻¹¹	<0.1%
Cartel Independiente de Acapulco - Los Rusos, UPOEG	1.9 × 10⁻¹¹	<0.1%
Comités locaux de vigilance - JAS	1.8 × 10⁻¹¹	<0.1%
Kuki - Meitei	1.7 × 10⁻¹¹	<0.1%
Government of Yemen (North Yemen) - Civilians	1.7 × 10⁻¹¹	<0.1%
AFC - Civilians	1.7 × 10⁻¹¹	<0.1%
India: Government	1.6 × 10⁻¹¹	<0.1%
AFP-Gutabara - CNPSC, FABB	1.6 × 10⁻¹¹	<0.1%
Myanmar (Burma): Karen	1.5 × 10⁻¹¹	<0.1%
Comandos de la Frontera - Civilians	1.3 × 10⁻¹¹	<0.1%
Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos	1.2 × 10⁻¹¹	<0.1%
Myanmar (Burma): Karenni	1.2 × 10⁻¹¹	<0.1%
OPM - Civilians	1.1 × 10⁻¹¹	<0.1%
Carteles Unidos, Guerreros Unidos - Los Tlacos	1.1 × 10⁻¹¹	<0.1%
Nigeria: Islamic State	1.0 × 10⁻¹¹	<0.1%
Autodefensas Conquistadoras de la Sierra Nevada - Civilians	1.0 × 10⁻¹¹	<0.1%
Los Ardillos - Los Tlacos	8.1 × 10⁻¹²	<0.1%
CPI-Maoist - Civilians	7.3 × 10⁻¹²	<0.1%
Los Costenos - Civilians	6.7 × 10⁻¹²	<0.1%
Myanmar (Burma): Arakan	6.4 × 10⁻¹²	<0.1%
Los Choneros - Los Lobos	6.2 × 10⁻¹²	<0.1%
Jalisco Cartel New Generation - Zetas Vieja Escuela	5.9 × 10⁻¹²	<0.1%
AFP-Gutabara - FABB	5.7 × 10⁻¹²	<0.1%
CPP - Civilians	5.5 × 10⁻¹²	<0.1%
Government of Venezuela - Civilians	5.0 × 10⁻¹²	<0.1%
FRPI - Civilians	4.7 × 10⁻¹²	<0.1%
Mozambique: Islamic State	4.0 × 10⁻¹²	<0.1%
Nigeria: Government	3.9 × 10⁻¹²	<0.1%
Myanmar (Burma): Kokang	3.9 × 10⁻¹²	<0.1%
Kokorat sans ras - Civilians	3.9 × 10⁻¹²	<0.1%
Kashmir insurgents - Civilians	3.2 × 10⁻¹²	<0.1%
Basonge - Bena Nkoma (Bakwa Luntu, Luba)	3.1 × 10⁻¹²	<0.1%
Government of Indonesia - Civilians	2.9 × 10⁻¹²	<0.1%
RED-TABARA - Civilians	2.8 × 10⁻¹²	<0.1%
FDLR-FOCA - Civilians	2.6 × 10⁻¹²	<0.1%
FPIC Chambre noire sanduku - FRPI	2.6 × 10⁻¹²	<0.1%
Fatales, Los Aguilas - Los Lobos , Los Tiguerones	2.6 × 10⁻¹²	<0.1%
IS - JAS	2.5 × 10⁻¹²	<0.1%
Los Chone Killers - Latin Kings	2.2 × 10⁻¹²	<0.1%
Mayi Mayi Chini ya Tuna - Civilians	2.1 × 10⁻¹²	<0.1%
Amigos dos Amigos - Comando Vermelho	2.1 × 10⁻¹²	<0.1%
FDN - PCC	2.1 × 10⁻¹²	<0.1%
Thailand: Patani	1.9 × 10⁻¹²	<0.1%
Los Aguilas - Los Lobos	1.9 × 10⁻¹²	<0.1%
Los Choneros - Los Lagartos	1.7 × 10⁻¹²	<0.1%
Los Rusos, UPOEG - Los Tlacos	1.7 × 10⁻¹²	<0.1%
Los Lobos - Los Tiguerones	1.7 × 10⁻¹²	<0.1%
Los Lagartos - Mafia 18	1.7 × 10⁻¹²	<0.1%
Government of Papua New Guinea - Civilians	1.6 × 10⁻¹²	<0.1%
South Sudan: Government	1.6 × 10⁻¹²	<0.1%
Luba - Batwa	1.6 × 10⁻¹²	<0.1%
Jalisco Cartel New Generation - Civilians	1.5 × 10⁻¹²	<0.1%
Fulani - Mwaghavul	1.5 × 10⁻¹²	<0.1%
Jalisco Cartel New Generation - Pájaros Sierra	1.4 × 10⁻¹²	<0.1%
Hindus (India) - Muslims (India)	1.4 × 10⁻¹²	<0.1%
Fulani - Mwaghavul , Ron	1.3 × 10⁻¹²	<0.1%
Los Aguilas - Los Lobos , Los Tiguerones	1.3 × 10⁻¹²	<0.1%
Fulani - Tiv	1.3 × 10⁻¹²	<0.1%
NUG - Civilians	1.2 × 10⁻¹²	<0.1%
Government of India - Civilians	1.2 × 10⁻¹²	<0.1%
Government of Mexico - Civilians	1.2 × 10⁻¹²	<0.1%
Choa Arab - Kotoko	1.2 × 10⁻¹²	<0.1%
Choa Arab - Musgum	1.2 × 10⁻¹²	<0.1%
Farmers (Nigeria) - Herders (Nigeria)	1.1 × 10⁻¹²	<0.1%
Los Ardillos - Los Rojos	1.0 × 10⁻¹²	<0.1%
Gulf Cartel - Los Zetas - Cártel del Noreste faction	9.6 × 10⁻¹³	<0.1%
Nigeria: Biafra	7.8 × 10⁻¹³	<0.1%
Philippines: Mindanao	6.9 × 10⁻¹³	<0.1%
Government of Philippines - Civilians	6.9 × 10⁻¹³	<0.1%
IS - Naparama	6.9 × 10⁻¹³	<0.1%
India: Western South East Asia	6.8 × 10⁻¹³	<0.1%
Birom - Fulani	5.8 × 10⁻¹³	<0.1%
DR Congo (Zaire): Katanga	5.2 × 10⁻¹³	<0.1%
Government of Uganda - Civilians	5.2 × 10⁻¹³	<0.1%
Twiganeho - Civilians	5.2 × 10⁻¹³	<0.1%
AFC - VDP	5.2 × 10⁻¹³	<0.1%
Atyap - Fulani	5.0 × 10⁻¹³	<0.1%
Karimjo - Wurukum	4.7 × 10⁻¹³	<0.1%
Black Axe - Eyie	4.5 × 10⁻¹³	<0.1%
Forces of Terwase Akwanza - Civilians	3.9 × 10⁻¹³	<0.1%
Fulani - Idoma	3.6 × 10⁻¹³	<0.1%
Fulani - Kuteb	3.4 × 10⁻¹³	<0.1%
VHP - Civilians	3.4 × 10⁻¹³	<0.1%
Gulf Cartel - Sinaloa Cartel	3.4 × 10⁻¹³	<0.1%
Gulf Cartel - Jalisco Cartel New Generation	3.4 × 10⁻¹³	<0.1%
Government of Mozambique - Civilians	3.0 × 10⁻¹³	<0.1%
Government of Nigeria - Civilians	2.4 × 10⁻¹³	<0.1%
Chain Guys - Full Force	2.0 × 10⁻¹³	<0.1%
Benin: Government	1.9 × 10⁻¹³	<0.1%
Kusasi - Mamprusi	1.8 × 10⁻¹³	<0.1%
India - Pakistan	1.7 × 10⁻¹³	<0.1%
India: Nagaland	1.7 × 10⁻¹³	<0.1%
NSCN-IM - Civilians	1.7 × 10⁻¹³	<0.1%
PLFI - Civilians	1.7 × 10⁻¹³	<0.1%
Myanmar (Burma): Shan	1.6 × 10⁻¹³	<0.1%
Los Lobos - R7	1.4 × 10⁻¹³	<0.1%
Hausa - Fulani	1.1 × 10⁻¹³	<0.1%
Fulani - Irigwe	8.1 × 10⁻¹⁴	<0.1%
ARSA - Civilians	8.0 × 10⁻¹⁴	<0.1%
Fulani - Igala	6.8 × 10⁻¹⁴	<0.1%
Patani insurgents - Civilians	6.4 × 10⁻¹⁴	<0.1%
Greenlanders - NDV	6.1 × 10⁻¹⁴	<0.1%
Black Axe - Maphite	6.1 × 10⁻¹⁴	<0.1%
Guerreros Unidos - Los Tlacos	5.6 × 10⁻¹⁴	<0.1%
Supporters of APC - Supporters of PDP	4.1 × 10⁻¹⁴	<0.1%
Black Axe - SVC	3.4 × 10⁻¹⁴	<0.1%
IPOB - Civilians	3.4 × 10⁻¹⁴	<0.1%
Agatu - Fulani	2.7 × 10⁻¹⁴	<0.1%
IS - Yan Gora	2.7 × 10⁻¹⁴	<0.1%
Deebam - NDV	2.7 × 10⁻¹⁴	<0.1%
Jukun - Tiv	1.4 × 10⁻¹⁴	<0.1%
Total	6.7 × 10⁻⁸	= the headline figure, 6.7 × 10⁻⁸

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
Industry	Part of the figure	Share
Crop and animal production, hunting and related service activities	2.3 × 10⁻⁶	69%
Mining and quarrying	7.0 × 10⁻⁷	21%
Land transport and transport via pipelines	7.0 × 10⁻⁸	2.0%
Manufacture of food products; beverages and tobacco products	6.0 × 10⁻⁸	1.8%
Water transport	3.3 × 10⁻⁸	0.98%
Forestry and logging	3.3 × 10⁻⁸	0.98%
Manufacture of basic metals	3.3 × 10⁻⁸	0.96%
Warehousing and support activities for transportation	2.8 × 10⁻⁸	0.82%
Wholesale trade, except of motor vehicles and motorcycles	1.8 × 10⁻⁸	0.53%
Air transport	1.3 × 10⁻⁸	0.39%
Retail trade, except of motor vehicles and motorcycles	7.8 × 10⁻⁹	0.23%
Postal and courier activities	5.1 × 10⁻⁹	0.15%
Manufacture of fabricated metal products, except machinery and equipment	4.8 × 10⁻⁹	0.14%
Water collection, treatment and supply	4.3 × 10⁻⁹	0.13%
Construction	3.6 × 10⁻⁹	0.11%
Fishing and aquaculture	3.1 × 10⁻⁹	<0.1%
Manufacture of other transport equipment	3.0 × 10⁻⁹	<0.1%
Manufacture of coke and refined petroleum products	2.5 × 10⁻⁹	<0.1%
Security and investigation, service and landscape, office administrative and support activities	2.5 × 10⁻⁹	<0.1%
Manufacture of chemicals and chemical products	2.2 × 10⁻⁹	<0.1%
Electricity, gas, steam and air conditioning supply	2.0 × 10⁻⁹	<0.1%
Rental and leasing activities	1.7 × 10⁻⁹	<0.1%
Employment activities	1.5 × 10⁻⁹	<0.1%
Public administration and defence; compulsory social security	1.5 × 10⁻⁹	<0.1%
Manufacture of rubber and plastic products	1.4 × 10⁻⁹	<0.1%
Manufacture of paper and paper products	1.3 × 10⁻⁹	<0.1%
Wholesale and retail trade and repair of motor vehicles and motorcycles	1.2 × 10⁻⁹	<0.1%
Sewerage, waste management, remediation activities	1.2 × 10⁻⁹	<0.1%
Legal and accounting activities; activities of head offices; management consultancy activities	8.5 × 10⁻¹⁰	<0.1%
Accommodation and food service activities	5.5 × 10⁻¹⁰	<0.1%
Manufacture of other non-metallic mineral products	5.4 × 10⁻¹⁰	<0.1%
Manufacture of machinery and equipment n.e.c.	5.1 × 10⁻¹⁰	<0.1%
Repair and installation of machinery and equipment	3.9 × 10⁻¹⁰	<0.1%
Manufacture of motor vehicles, trailers and semi-trailers	3.6 × 10⁻¹⁰	<0.1%
Human health activities	3.4 × 10⁻¹⁰	<0.1%
Advertising and market research	3.3 × 10⁻¹⁰	<0.1%
Manufacture of textiles, wearing apparel, leather and related products	3.1 × 10⁻¹⁰	<0.1%
Manufacture of computer, electronic and optical products	3.1 × 10⁻¹⁰	<0.1%
Real estate activities	2.9 × 10⁻¹⁰	<0.1%
Manufacture of electrical equipment	2.9 × 10⁻¹⁰	<0.1%
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials	2.5 × 10⁻¹⁰	<0.1%
Travel agency, tour operator reservation service and related activities	2.3 × 10⁻¹⁰	<0.1%
Architectural and engineering activities; technical testing and analysis	2.3 × 10⁻¹⁰	<0.1%
Computer programming, consultancy, and information service activities	2.1 × 10⁻¹⁰	<0.1%
Repair of computers and personal and household goods	2.0 × 10⁻¹⁰	<0.1%
Manufacture of basic pharmaceutical products and pharmaceutical preparations	1.8 × 10⁻¹⁰	<0.1%
Other professional, scientific and technical activities; veterinary activities	1.7 × 10⁻¹⁰	<0.1%
Printing and reproduction of recorded media	1.7 × 10⁻¹⁰	<0.1%
Activities of membership organisations	1.6 × 10⁻¹⁰	<0.1%
Financial service activities, except insurance and pension funding	1.4 × 10⁻¹⁰	<0.1%
Other personal service activities	1.3 × 10⁻¹⁰	<0.1%
Telecommunications	1.0 × 10⁻¹⁰	<0.1%
Manufacture of furniture; other manufacturing	1.0 × 10⁻¹⁰	<0.1%
Sports activities and amusement and recreation activities	1.0 × 10⁻¹⁰	<0.1%
Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities	8.3 × 10⁻¹¹	<0.1%
Education	6.2 × 10⁻¹¹	<0.1%
Motion picture, video, television programme production; programming and broadcasting activities	6.2 × 10⁻¹¹	<0.1%
Insurance, reinsurance and pension funding, except compulsory social security	4.7 × 10⁻¹¹	<0.1%
Publishing activities	4.6 × 10⁻¹¹	<0.1%
Activities auxiliary to financial services and insurance activities	4.5 × 10⁻¹¹	<0.1%
Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use	2.5 × 10⁻¹¹	<0.1%
Residential care activities and social work activities without accommodation	2.4 × 10⁻¹¹	<0.1%
Scientific research and development	1.8 × 10⁻¹¹	<0.1%
Total	3.4 × 10⁻⁶	= the headline figure, 3.4 × 10⁻⁶

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
Country	Part of the figure	Share
Not placed	2.6 × 10⁻⁶	77%
Mexico	3.9 × 10⁻⁷	12%
Brazil	1.5 × 10⁻⁷	4.3%
United States	6.8 × 10⁻⁸	2.0%
Russian Federation	2.9 × 10⁻⁸	0.85%
Turkiye	2.6 × 10⁻⁸	0.77%
France	1.6 × 10⁻⁸	0.47%
India	1.2 × 10⁻⁸	0.35%
Canada	1.2 × 10⁻⁸	0.34%
Korea, Rep.	1.1 × 10⁻⁸	0.31%
Germany	9.7 × 10⁻⁹	0.28%
Spain	9.3 × 10⁻⁹	0.27%
Italy	9.0 × 10⁻⁹	0.26%
Japan	8.9 × 10⁻⁹	0.26%
Argentina	8.6 × 10⁻⁹	0.25%
Austria	5.5 × 10⁻⁹	0.16%
Australia	3.4 × 10⁻⁹	<0.1%
Poland	3.3 × 10⁻⁹	<0.1%
Romania	2.9 × 10⁻⁹	<0.1%
Indonesia	2.4 × 10⁻⁹	<0.1%
Portugal	2.4 × 10⁻⁹	<0.1%
Ireland	2.1 × 10⁻⁹	<0.1%
Denmark	1.4 × 10⁻⁹	<0.1%
Bulgaria	1.4 × 10⁻⁹	<0.1%
Norway	1.2 × 10⁻⁹	<0.1%
Hungary	1.2 × 10⁻⁹	<0.1%
Belgium	9.1 × 10⁻¹⁰	<0.1%
Switzerland	9.1 × 10⁻¹⁰	<0.1%
Lithuania	8.9 × 10⁻¹⁰	<0.1%
Czechia	8.9 × 10⁻¹⁰	<0.1%
Finland	7.7 × 10⁻¹⁰	<0.1%
Greece	7.6 × 10⁻¹⁰	<0.1%
Netherlands	6.1 × 10⁻¹⁰	<0.1%
Sweden	6.0 × 10⁻¹⁰	<0.1%
Croatia	5.8 × 10⁻¹⁰	<0.1%
Latvia	3.8 × 10⁻¹⁰	<0.1%
Cyprus	3.5 × 10⁻¹⁰	<0.1%
Slovak Republic	3.5 × 10⁻¹⁰	<0.1%
Luxembourg	2.3 × 10⁻¹⁰	<0.1%
Slovenia	1.9 × 10⁻¹⁰	<0.1%
South Africa	1.2 × 10⁻¹⁰	<0.1%
Estonia	8.3 × 10⁻¹¹	<0.1%
Saudi Arabia	6.8 × 10⁻¹¹	<0.1%
United Kingdom	4.7 × 10⁻¹¹	<0.1%
Malta	4.3 × 10⁻¹¹	<0.1%
China	3.8 × 10⁻¹¹	<0.1%
Serbia	2.5 × 10⁻¹⁴	<0.1%
Total	3.4 × 10⁻⁶	= the headline figure, 3.4 × 10⁻⁶

What this trail does not show

Each table is a separate way of dividing the figure. “Cobalt accounts for 40%” and “one country accounts for 60%” are two views of one figure, not a path through it: the calculation stores the figure divided each way on its own, not every combination of them.
A range belongs to the whole figure. A step’s number is only its middle estimate.
Production phase only. Harm from using the product — driving the car, charging the phone — is not in this figure.

Sources behind this figure

CEPII, BACI — Gaulier, G. and Zignago, S. (2010), BACI: International Trade Database at the Product-Level, CEPII Working Paper 2010-23. CEPII did not endorse these derived figures — HS92_V202601-20260130, retrieved 2026-09-29 from https://www.cepii.fr/DATA_DOWNLOAD/baci/data/BACI_HS92_V202601.zip. Licensed under Open Licence 2.0 (Licence Ouverte, Etalab) (https://www.etalab.gouv.fr/wp-content/uploads/2018/11/open-licence.pdf).
Eurostat, Euro/ECU exchange rates - annual data (ert_bil_eur_a) — ert_bil_eur_a-USD-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/ert_bil_eur_a/A.AVG.NAC.USD?format=SDMX-CSV&startPeriod=1995. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, European Commission — esaw-fatal-20260910, retrieved 2026-09-10 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_02?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, European Commission — esaw-fatal-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_02?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, European Commission — esaw-non_fatal-20260910, retrieved 2026-09-10 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_01?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, European Commission — esaw-non_fatal-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_01?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, FIGARO inter-country input-output tables — ii1-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii1?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, FIGARO inter-country input-output tables — ii2-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii2?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, FIGARO inter-country input-output tables — ii3-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii3?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Eurostat, FIGARO inter-country input-output tables — ii4-20260720, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii4?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
FAO. AQUASTAT, FAO's Global Information System on Water and Agriculture: municipal water withdrawal. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — ds-20260713, retrieved 2026-10-06 from https://api.data.apps.fao.org/api/v2/bigquery. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
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 — fo-20260109, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Forestry_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
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.
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 — rfb-20260730, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Inputs_FertilizersProduct_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
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 — rl-20261002, retrieved 2026-10-06 from https://bulks-faostat.fao.org/production/Inputs_LandUse_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
Information from the Stockholm International Peace Research Institute (SIPRI) — arms-register-1950-2025, retrieved 2026-09-29 from https://atbackend.sipri.org/api/p/trades/trade-register-csv/. Used under SIPRI terms and conditions — fair-use policy; see https://www.sipri.org/about/terms-and-conditions.
Information from the Stockholm International Peace Research Institute (SIPRI) — milex-1949-2025-v1.2, retrieved 2026-09-29 from https://www.sipri.org/sites/default/files/SIPRI-Milex-data-1949-2025_v1.2.xlsx. Used under SIPRI terms and conditions — fair-use policy; see https://www.sipri.org/about/terms-and-conditions.
International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — emp-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_EMP_TEMP_SEX_ECO_NB,1.0/.A..SEX_T.. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — emp-20261007, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_EMP_TEMP_SEX_ECO_NB,1.0/.A..SEX_T.. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — fatal-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_INJ_FATL_ECO_NB,1.0/all. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — non_fatal-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_INJ_NFTL_ECO_NB,1.0/all. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 1995-2000_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/1995-2000_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 2001-2005_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/2001-2005_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 2006-2010_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/2006-2010_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 2011-2015_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/2011-2015_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 2016-2022_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/2016-2022_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
Source: U.S. Energy Information Administration, International Energy Statistics — intl-20261003, retrieved 2026-10-06 from https://www.eia.gov/opendata/bulk/INTL.zip. Used under U.S. Government work — public domain (EIA Copyrights and Reuse); see https://www.eia.gov/about/copyrights_reuse.php.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2012-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2012.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2013-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2013.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2014-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2014.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2015-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2015.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2016-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2016.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2017-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2017.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2018-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/mineral-pubs/mcs/mcs2018.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2019-PDF, retrieved 2026-10-06 from https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/atoms/files/mcs2019_all.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2020-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2020/mcs2020.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2021-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2021/mcs2021.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2022-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2022/mcs2022.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2023-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2023/mcs2023.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2024-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2024/mcs2024.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2025-PDF, retrieved 2026-10-06 from https://pubs.usgs.gov/periodicals/mcs2025/mcs2025.pdf. Used under U.S. Government work — public domain (USGS Copyrights and Credits); see https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits.
U.S. Geological Survey, National Minerals Information Center, Mineral Commodity Summaries — MCS2026-20260206, retrieved 2026-09-29 from https://www.sciencebase.gov/catalog/file/get/69837e43b66b01367d7ec7c7?f=__disk__d3%2Fac%2F84%2Fd3ac8466552946c5e8caa2c2c6338d9e1aff655d. Licensed under Creative Commons Zero v1.0 Universal (public domain dedication) (https://creativecommons.org/publicdomain/zero/1.0/).
Uppsala Conflict Data Program (UCDP), Uppsala University — Davies, Pettersson and Oberg, "Organized violence 1989-2025, and violent political protests", Journal of Peace Research (2026), doi:10.1093/jopres/xjag046 — ged-v26.1, retrieved 2026-09-10 from https://ucdp.uu.se/downloads/ged/ged261-csv.zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
World Health Organization, Global Health Estimates. WHO did not prepare, review or endorse these derived figures — wsh_10-20261006, retrieved 2026-10-06 from https://ghoapi.azureedge.net/api/WSH_10. Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/). Data modified by HumanToll.

HumanToll 2026, run 2259, methodology v1.0. https://quiescence.eu/humantoll/explain/roasted-coffee/

Back to Roasted coffee →