login
quiescence.eu
Skip to content

The full breakdown

How the figure for Cocoa mass 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 cocoa mass (cocoa paste, cocoa liquor). 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 — 4.1 × 10⁻⁸ per item(0.16–1.0 × 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(2.3–5.2 × 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
MaterialPer itemDeaths per kgPart of the figureShare
Cocoa0.0013 t3.3 × 10⁻⁸4.1 × 10⁻⁸100%
Total4.1 × 10⁻⁸= the headline figure, 4.1 × 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
CountryPart of the figureShare
Cameroon1.4 × 10⁻⁸35%
Nigeria1.1 × 10⁻⁸27%
Ecuador6.2 × 10⁻⁹15%
Congo, Dem. Rep.3.3 × 10⁻⁹8.1%
Mexico1.4 × 10⁻⁹3.4%
Brazil1.2 × 10⁻⁹3.0%
Haiti8.8 × 10⁻¹⁰2.1%
Colombia7.7 × 10⁻¹⁰1.9%
Togo7.0 × 10⁻¹⁰1.7%
Ghana3.2 × 10⁻¹⁰0.79%
Uganda1.8 × 10⁻¹⁰0.45%
Papua New Guinea1.5 × 10⁻¹⁰0.38%
Indonesia6.7 × 10⁻¹¹0.16%
Philippines3.8 × 10⁻¹¹<0.1%
Honduras3.5 × 10⁻¹¹<0.1%
Peru1.9 × 10⁻¹¹<0.1%
Guatemala1.8 × 10⁻¹¹<0.1%
Central African Republic1.7 × 10⁻¹¹<0.1%
India1.1 × 10⁻¹¹<0.1%
Venezuela, RB6.1 × 10⁻¹²<0.1%
Sri Lanka6.1 × 10⁻¹²<0.1%
Panama3.7 × 10⁻¹²<0.1%
Costa Rica1.9 × 10⁻¹²<0.1%
Thailand7.8 × 10⁻¹³<0.1%
Bolivia2.1 × 10⁻¹³<0.1%
Total4.1 × 10⁻⁸= the headline figure, 4.1 × 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 harmPart of the figureShare
Conflict and political violence4.0 × 10⁻⁸99%
Work4.6 × 10⁻¹⁰1.1%
Total4.1 × 10⁻⁸= the headline figure, 4.1 × 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
WarPart of the figureShare
Cameroon: Ambazonia4.3 × 10⁻⁹11%
Nigeria: Islamic State4.0 × 10⁻⁹9.8%
JAS - Civilians2.6 × 10⁻⁹6.3%
Cameroon: Government2.5 × 10⁻⁹6.2%
Ambazonia insurgents - Civilians2.3 × 10⁻⁹5.7%
IS - Civilians2.2 × 10⁻⁹5.4%
Los Choneros - Los Lobos2.0 × 10⁻⁹4.9%
Nigeria: Government1.5 × 10⁻⁹3.7%
Cameroon: Islamic State1.2 × 10⁻⁹2.9%
IS - JAS9.7 × 10⁻¹⁰2.4%
Fatales, Los Aguilas - Los Lobos , Los Tiguerones8.3 × 10⁻¹⁰2.0%
Los Chone Killers - Latin Kings6.9 × 10⁻¹⁰1.7%
Los Aguilas - Los Lobos6.1 × 10⁻¹⁰1.5%
Government of Cameroon - Civilians5.6 × 10⁻¹⁰1.4%
Fulani - Mwaghavul5.6 × 10⁻¹⁰1.4%
Los Choneros - Los Lagartos5.5 × 10⁻¹⁰1.4%
Los Lobos - Los Tiguerones5.4 × 10⁻¹⁰1.3%
Los Lagartos - Mafia 185.4 × 10⁻¹⁰1.3%
Jalisco Cartel New Generation - Sinaloa Cartel5.4 × 10⁻¹⁰1.3%
URDPC - Civilians5.3 × 10⁻¹⁰1.3%
Fulani - Mwaghavul , Ron5.1 × 10⁻¹⁰1.3%
Fulani - Tiv4.9 × 10⁻¹⁰1.2%
Not placed4.6 × 10⁻¹⁰1.1%
JNIM - Civilians4.3 × 10⁻¹⁰1.1%
Farmers (Nigeria) - Herders (Nigeria)4.2 × 10⁻¹⁰1.0%
Los Aguilas - Los Lobos , Los Tiguerones4.2 × 10⁻¹⁰1.0%
Comando Vermelho - PCC3.6 × 10⁻¹⁰0.88%
Lengola - Mbole3.5 × 10⁻¹⁰0.85%
Comités locaux de vigilance - JAS3.4 × 10⁻¹⁰0.82%
Kusasi - Mamprusi3.2 × 10⁻¹⁰0.79%
Nigeria: Biafra3.0 × 10⁻¹⁰0.74%
Togo: Government2.7 × 10⁻¹⁰0.65%
Government of Rwanda - Civilians2.4 × 10⁻¹⁰0.60%
DR Congo (Zaire): Government2.4 × 10⁻¹⁰0.59%
DR Congo (Zaire): Islamic State2.4 × 10⁻¹⁰0.59%
Jalisco Cartel New Generation - Santa Rosa de Lima Cartel2.3 × 10⁻¹⁰0.57%
Birom - Fulani2.2 × 10⁻¹⁰0.55%
Juarez Cartel - Sinaloa Cartel2.1 × 10⁻¹⁰0.52%
Atyap - Fulani1.9 × 10⁻¹⁰0.47%
Karimjo - Wurukum1.8 × 10⁻¹⁰0.44%
Black Axe - Eyie1.7 × 10⁻¹⁰0.42%
Government of Haiti - Civilians1.6 × 10⁻¹⁰0.39%
Carteles Unidos - Jalisco Cartel New Generation1.6 × 10⁻¹⁰0.39%
Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin1.5 × 10⁻¹⁰0.37%
Forces of Terwase Akwanza - Civilians1.5 × 10⁻¹⁰0.37%
M23 - VDP1.5 × 10⁻¹⁰0.37%
G9 - G-Pep1.5 × 10⁻¹⁰0.36%
Mobondo - Civilians1.4 × 10⁻¹⁰0.35%
Fulani - Idoma1.4 × 10⁻¹⁰0.34%
Terre Noire - Civilians1.4 × 10⁻¹⁰0.34%
5 Segond, Taliban - Civilians1.3 × 10⁻¹⁰0.33%
Fulani - Kuteb1.3 × 10⁻¹⁰0.32%
Bonde do Maluco - Comando Vermelho1.3 × 10⁻¹⁰0.32%
Grand Ravine - Civilians1.2 × 10⁻¹⁰0.31%
Cartel do Norte - Comando Vermelho1.2 × 10⁻¹⁰0.29%
M23 - Civilians1.2 × 10⁻¹⁰0.28%
Rwanda: Government1.0 × 10⁻¹⁰0.25%
Government of DR Congo (Zaire) - Civilians9.4 × 10⁻¹¹0.23%
G-Pep - Civilians9.4 × 10⁻¹¹0.23%
Government of Nigeria - Civilians9.4 × 10⁻¹¹0.23%
EGC - Civilians9.3 × 10⁻¹¹0.23%
Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos9.1 × 10⁻¹¹0.22%
Bonde dos 40 - PCC8.3 × 10⁻¹¹0.20%
Chain Guys - Full Force7.8 × 10⁻¹¹0.19%
Comando Vermelho - GDE6.3 × 10⁻¹¹0.15%
Nova Okaida - Estados Unidos6.3 × 10⁻¹¹0.15%
GDE, PCC - Sindicato do Crime6.2 × 10⁻¹¹0.15%
PCC - Sindicato do Crime5.5 × 10⁻¹¹0.13%
Amigos Para Sempre - Família Terror Amapá5.4 × 10⁻¹¹0.13%
Colombia: Government5.2 × 10⁻¹¹0.13%
Uganda: Islamic State5.1 × 10⁻¹¹0.13%
FARC-EMC - Civilians4.9 × 10⁻¹¹0.12%
URDPC - Zaire self-defense group4.8 × 10⁻¹¹0.12%
Los Lobos - R74.6 × 10⁻¹¹0.11%
Comando Vermelho - Civilians4.5 × 10⁻¹¹0.11%
Hausa - Fulani4.4 × 10⁻¹¹0.11%
Zaire self-defense group - Civilians4.2 × 10⁻¹¹0.10%
Indonesia: West Papua4.2 × 10⁻¹¹0.10%
VDP - Civilians4.0 × 10⁻¹¹<0.1%
Cartel Independiente de Acapulco - Los Rusos, UPOEG4.0 × 10⁻¹¹<0.1%
M18 - MS-133.9 × 10⁻¹¹<0.1%
Gran Grif - Civilians3.7 × 10⁻¹¹<0.1%
400 Mawozo - Civilians3.7 × 10⁻¹¹<0.1%
Bonde dos 13, PCC - Comando Vermelho3.3 × 10⁻¹¹<0.1%
Bonde dos 40 - Comando Vermelho3.3 × 10⁻¹¹<0.1%
FARC-EMC - ELN3.2 × 10⁻¹¹<0.1%
FPIC Chambre noire sanduku - URDPC3.1 × 10⁻¹¹<0.1%
Fulani - Irigwe3.1 × 10⁻¹¹<0.1%
FPIC Chambre noire sanduku - Civilians3.1 × 10⁻¹¹<0.1%
Fulani - Igala2.6 × 10⁻¹¹<0.1%
Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos2.5 × 10⁻¹¹<0.1%
Greenlanders - NDV2.3 × 10⁻¹¹<0.1%
Black Axe - Maphite2.3 × 10⁻¹¹<0.1%
Philippines: Government2.3 × 10⁻¹¹<0.1%
Comando Vermelho - Holanda2.3 × 10⁻¹¹<0.1%
Carteles Unidos, Guerreros Unidos - Los Tlacos2.3 × 10⁻¹¹<0.1%
Choa Arab - Kotoko2.2 × 10⁻¹¹<0.1%
Choa Arab - Musgum2.2 × 10⁻¹¹<0.1%
AFC - Civilians2.2 × 10⁻¹¹<0.1%
FARC - Segunda Marquetalia - Civilians2.1 × 10⁻¹¹<0.1%
AFP-Gutabara - CNPSC, FABB2.1 × 10⁻¹¹<0.1%
ELN - Civilians2.1 × 10⁻¹¹<0.1%
OPM - Civilians2.0 × 10⁻¹¹<0.1%
Peru: Government1.9 × 10⁻¹¹<0.1%
Comando Vermelho - Massa1.8 × 10⁻¹¹<0.1%
Nova Okaida - PCC1.7 × 10⁻¹¹<0.1%
Los Costenos - Los Pepes1.7 × 10⁻¹¹<0.1%
Los Ardillos - Los Tlacos1.7 × 10⁻¹¹<0.1%
EGC - ELN, FARC-EMC1.6 × 10⁻¹¹<0.1%
Bonde do Maluco - Katiara1.6 × 10⁻¹¹<0.1%
Bonde do Maluco - Civilians1.6 × 10⁻¹¹<0.1%
Supporters of APC - Supporters of PDP1.6 × 10⁻¹¹<0.1%
EGC - ELN1.6 × 10⁻¹¹<0.1%
Black Axe - SVC1.3 × 10⁻¹¹<0.1%
IPOB - Civilians1.3 × 10⁻¹¹<0.1%
Bonde dos 40 - Civilians1.3 × 10⁻¹¹<0.1%
Jalisco Cartel New Generation - Zetas Vieja Escuela1.2 × 10⁻¹¹<0.1%
Comando Vermelho - Terceiro Comando Puro1.2 × 10⁻¹¹<0.1%
Philippines: Islamic State1.1 × 10⁻¹¹<0.1%
Agatu - Fulani1.0 × 10⁻¹¹<0.1%
IS - Yan Gora1.0 × 10⁻¹¹<0.1%
Deebam - NDV1.0 × 10⁻¹¹<0.1%
Central African Republic: Government1.0 × 10⁻¹¹<0.1%
PCC - Civilians9.0 × 10⁻¹²<0.1%
M18 - Civilians8.8 × 10⁻¹²<0.1%
Ajeita - Bonde do Maluco8.0 × 10⁻¹²<0.1%
AFP-Gutabara - FABB7.6 × 10⁻¹²<0.1%
EGC - Autodefensas Conquistadoras de la Sierra Nevada6.8 × 10⁻¹²<0.1%
FRPI - Civilians6.2 × 10⁻¹²<0.1%
Government of Brazil - Civilians6.0 × 10⁻¹²<0.1%
Government of Colombia - Civilians5.6 × 10⁻¹²<0.1%
Anti-Bala - Bala na Cara5.5 × 10⁻¹²<0.1%
Jukun - Tiv5.2 × 10⁻¹²<0.1%
Bonde dos 40 - PCM5.0 × 10⁻¹²<0.1%
Government of Indonesia - Civilians5.0 × 10⁻¹²<0.1%
Government of Venezuela - Civilians5.0 × 10⁻¹²<0.1%
Burundi: Government4.9 × 10⁻¹²<0.1%
MS-13 - Civilians4.6 × 10⁻¹²<0.1%
Basonge - Bena Nkoma (Bakwa Luntu, Luba)4.2 × 10⁻¹²<0.1%
AAKG - CPC4.1 × 10⁻¹²<0.1%
Kokorat sans ras - Civilians3.8 × 10⁻¹²<0.1%
Los Rusos, UPOEG - Los Tlacos3.5 × 10⁻¹²<0.1%
FDLR-FOCA - Civilians3.5 × 10⁻¹²<0.1%
FPIC Chambre noire sanduku - FRPI3.5 × 10⁻¹²<0.1%
India: Kashmir3.3 × 10⁻¹²<0.1%
Jalisco Cartel New Generation - Civilians3.2 × 10⁻¹²<0.1%
Jalisco Cartel New Generation - Pájaros Sierra2.9 × 10⁻¹²<0.1%
Kuki - Meitei2.9 × 10⁻¹²<0.1%
Mayi Mayi Chini ya Tuna - Civilians2.8 × 10⁻¹²<0.1%
India: Government2.7 × 10⁻¹²<0.1%
Comandos de la Frontera - Civilians2.5 × 10⁻¹²<0.1%
Government of Mexico - Civilians2.5 × 10⁻¹²<0.1%
Government of Papua New Guinea - Civilians2.3 × 10⁻¹²<0.1%
CPP - Civilians2.3 × 10⁻¹²<0.1%
Los Ardillos - Los Rojos2.1 × 10⁻¹²<0.1%
South Sudan: Government2.1 × 10⁻¹²<0.1%
Luba - Batwa2.1 × 10⁻¹²<0.1%
Gulf Cartel - Los Zetas - Cártel del Noreste faction2.0 × 10⁻¹²<0.1%
Forces of Tony Peña - Los Hondureños1.9 × 10⁻¹²<0.1%
Autodefensas Conquistadoras de la Sierra Nevada - Civilians1.9 × 10⁻¹²<0.1%
Central African Republic: Logone1.2 × 10⁻¹²<0.1%
Los Costenos - Civilians1.2 × 10⁻¹²<0.1%
CPI-Maoist - Civilians1.2 × 10⁻¹²<0.1%
CPC - Civilians1.1 × 10⁻¹²<0.1%
Gulf Cartel - Sinaloa Cartel7.0 × 10⁻¹³<0.1%
Gulf Cartel - Jalisco Cartel New Generation7.0 × 10⁻¹³<0.1%
DR Congo (Zaire): Katanga6.9 × 10⁻¹³<0.1%
Government of Uganda - Civilians6.9 × 10⁻¹³<0.1%
Government of Burundi - Civilians6.9 × 10⁻¹³<0.1%
Twiganeho - Civilians6.9 × 10⁻¹³<0.1%
AFC - VDP6.9 × 10⁻¹³<0.1%
Kashmir insurgents - Civilians5.3 × 10⁻¹³<0.1%
Amigos dos Amigos - Comando Vermelho5.0 × 10⁻¹³<0.1%
FDN - PCC5.0 × 10⁻¹³<0.1%
Government of Central African Republic - Civilians3.6 × 10⁻¹³<0.1%
Philippines: Mindanao2.8 × 10⁻¹³<0.1%
Government of Philippines - Civilians2.8 × 10⁻¹³<0.1%
Hindus (India) - Muslims (India)2.2 × 10⁻¹³<0.1%
Government of India - Civilians2.0 × 10⁻¹³<0.1%
Guerreros Unidos - Los Tlacos1.2 × 10⁻¹³<0.1%
India: Western South East Asia1.1 × 10⁻¹³<0.1%
Farmers (CAR) - Herders (CAR)8.1 × 10⁻¹⁴<0.1%
AAKG - Civilians8.1 × 10⁻¹⁴<0.1%
Myanmar (Burma): Government5.6 × 10⁻¹⁴<0.1%
VHP - Civilians5.6 × 10⁻¹⁴<0.1%
Thailand: Patani3.7 × 10⁻¹⁴<0.1%
India - Pakistan2.8 × 10⁻¹⁴<0.1%
India: Nagaland2.8 × 10⁻¹⁴<0.1%
NSCN-IM - Civilians2.8 × 10⁻¹⁴<0.1%
PLFI - Civilians2.8 × 10⁻¹⁴<0.1%
Patani insurgents - Civilians1.2 × 10⁻¹⁵<0.1%
Total4.1 × 10⁻⁸= the headline figure, 4.1 × 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
IndustryPart of the figureShare
Crop and animal production, hunting and related service activities2.3 × 10⁻⁶69%
Mining and quarrying7.0 × 10⁻⁷21%
Land transport and transport via pipelines7.0 × 10⁻⁸2.0%
Manufacture of food products; beverages and tobacco products6.0 × 10⁻⁸1.8%
Water transport3.3 × 10⁻⁸0.98%
Forestry and logging3.3 × 10⁻⁸0.98%
Manufacture of basic metals3.3 × 10⁻⁸0.96%
Warehousing and support activities for transportation2.8 × 10⁻⁸0.82%
Wholesale trade, except of motor vehicles and motorcycles1.8 × 10⁻⁸0.53%
Air transport1.3 × 10⁻⁸0.39%
Retail trade, except of motor vehicles and motorcycles7.8 × 10⁻⁹0.23%
Postal and courier activities5.1 × 10⁻⁹0.15%
Manufacture of fabricated metal products, except machinery and equipment4.8 × 10⁻⁹0.14%
Water collection, treatment and supply4.3 × 10⁻⁹0.13%
Construction3.6 × 10⁻⁹0.11%
Fishing and aquaculture3.1 × 10⁻⁹<0.1%
Manufacture of other transport equipment3.0 × 10⁻⁹<0.1%
Manufacture of coke and refined petroleum products2.5 × 10⁻⁹<0.1%
Security and investigation, service and landscape, office administrative and support activities2.5 × 10⁻⁹<0.1%
Manufacture of chemicals and chemical products2.2 × 10⁻⁹<0.1%
Electricity, gas, steam and air conditioning supply2.0 × 10⁻⁹<0.1%
Rental and leasing activities1.7 × 10⁻⁹<0.1%
Employment activities1.5 × 10⁻⁹<0.1%
Public administration and defence; compulsory social security1.5 × 10⁻⁹<0.1%
Manufacture of rubber and plastic products1.4 × 10⁻⁹<0.1%
Manufacture of paper and paper products1.3 × 10⁻⁹<0.1%
Wholesale and retail trade and repair of motor vehicles and motorcycles1.2 × 10⁻⁹<0.1%
Sewerage, waste management, remediation activities1.2 × 10⁻⁹<0.1%
Legal and accounting activities; activities of head offices; management consultancy activities8.5 × 10⁻¹⁰<0.1%
Accommodation and food service activities5.5 × 10⁻¹⁰<0.1%
Manufacture of other non-metallic mineral products5.4 × 10⁻¹⁰<0.1%
Manufacture of machinery and equipment n.e.c.5.1 × 10⁻¹⁰<0.1%
Repair and installation of machinery and equipment3.9 × 10⁻¹⁰<0.1%
Manufacture of motor vehicles, trailers and semi-trailers3.6 × 10⁻¹⁰<0.1%
Human health activities3.4 × 10⁻¹⁰<0.1%
Advertising and market research3.3 × 10⁻¹⁰<0.1%
Manufacture of textiles, wearing apparel, leather and related products3.1 × 10⁻¹⁰<0.1%
Manufacture of computer, electronic and optical products3.1 × 10⁻¹⁰<0.1%
Real estate activities2.9 × 10⁻¹⁰<0.1%
Manufacture of electrical equipment2.9 × 10⁻¹⁰<0.1%
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials2.5 × 10⁻¹⁰<0.1%
Travel agency, tour operator reservation service and related activities2.3 × 10⁻¹⁰<0.1%
Architectural and engineering activities; technical testing and analysis2.3 × 10⁻¹⁰<0.1%
Computer programming, consultancy, and information service activities2.1 × 10⁻¹⁰<0.1%
Repair of computers and personal and household goods2.0 × 10⁻¹⁰<0.1%
Manufacture of basic pharmaceutical products and pharmaceutical preparations1.8 × 10⁻¹⁰<0.1%
Other professional, scientific and technical activities; veterinary activities1.7 × 10⁻¹⁰<0.1%
Printing and reproduction of recorded media1.7 × 10⁻¹⁰<0.1%
Activities of membership organisations1.6 × 10⁻¹⁰<0.1%
Financial service activities, except insurance and pension funding1.4 × 10⁻¹⁰<0.1%
Other personal service activities1.3 × 10⁻¹⁰<0.1%
Telecommunications1.0 × 10⁻¹⁰<0.1%
Manufacture of furniture; other manufacturing1.0 × 10⁻¹⁰<0.1%
Sports activities and amusement and recreation activities1.0 × 10⁻¹⁰<0.1%
Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities8.3 × 10⁻¹¹<0.1%
Education6.2 × 10⁻¹¹<0.1%
Motion picture, video, television programme production; programming and broadcasting activities6.2 × 10⁻¹¹<0.1%
Insurance, reinsurance and pension funding, except compulsory social security4.7 × 10⁻¹¹<0.1%
Publishing activities4.6 × 10⁻¹¹<0.1%
Activities auxiliary to financial services and insurance activities4.5 × 10⁻¹¹<0.1%
Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use2.5 × 10⁻¹¹<0.1%
Residential care activities and social work activities without accommodation2.4 × 10⁻¹¹<0.1%
Scientific research and development1.8 × 10⁻¹¹<0.1%
Total3.4 × 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
CountryPart of the figureShare
Not placed2.6 × 10⁻⁶77%
Mexico3.9 × 10⁻⁷12%
Brazil1.5 × 10⁻⁷4.3%
United States6.8 × 10⁻⁸2.0%
Russian Federation2.9 × 10⁻⁸0.85%
Turkiye2.6 × 10⁻⁸0.77%
France1.6 × 10⁻⁸0.47%
India1.2 × 10⁻⁸0.35%
Canada1.2 × 10⁻⁸0.34%
Korea, Rep.1.1 × 10⁻⁸0.31%
Germany9.7 × 10⁻⁹0.28%
Spain9.3 × 10⁻⁹0.27%
Italy9.0 × 10⁻⁹0.26%
Japan8.9 × 10⁻⁹0.26%
Argentina8.6 × 10⁻⁹0.25%
Austria5.5 × 10⁻⁹0.16%
Australia3.4 × 10⁻⁹<0.1%
Poland3.3 × 10⁻⁹<0.1%
Romania2.9 × 10⁻⁹<0.1%
Indonesia2.4 × 10⁻⁹<0.1%
Portugal2.4 × 10⁻⁹<0.1%
Ireland2.1 × 10⁻⁹<0.1%
Denmark1.4 × 10⁻⁹<0.1%
Bulgaria1.4 × 10⁻⁹<0.1%
Norway1.2 × 10⁻⁹<0.1%
Hungary1.2 × 10⁻⁹<0.1%
Belgium9.1 × 10⁻¹⁰<0.1%
Switzerland9.1 × 10⁻¹⁰<0.1%
Lithuania8.9 × 10⁻¹⁰<0.1%
Czechia8.9 × 10⁻¹⁰<0.1%
Finland7.7 × 10⁻¹⁰<0.1%
Greece7.6 × 10⁻¹⁰<0.1%
Netherlands6.1 × 10⁻¹⁰<0.1%
Sweden6.0 × 10⁻¹⁰<0.1%
Croatia5.8 × 10⁻¹⁰<0.1%
Latvia3.8 × 10⁻¹⁰<0.1%
Cyprus3.5 × 10⁻¹⁰<0.1%
Slovak Republic3.5 × 10⁻¹⁰<0.1%
Luxembourg2.3 × 10⁻¹⁰<0.1%
Slovenia1.9 × 10⁻¹⁰<0.1%
South Africa1.2 × 10⁻¹⁰<0.1%
Estonia8.3 × 10⁻¹¹<0.1%
Saudi Arabia6.8 × 10⁻¹¹<0.1%
United Kingdom4.7 × 10⁻¹¹<0.1%
Malta4.3 × 10⁻¹¹<0.1%
China3.8 × 10⁻¹¹<0.1%
Serbia2.5 × 10⁻¹⁴<0.1%
Total3.4 × 10⁻⁶= the headline figure, 3.4 × 10⁻⁶

What this trail does not show

Sources behind this figure

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

Back to Cocoa mass →