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The full breakdown

How the figure for NMC cathode powder 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 NMC532 cathode active material. 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 — 1.4 × 10⁻⁷ per item(0.71–3.2 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r

Money method — 3.2 × 10⁻⁶ per €1,000 spent in its industry(2.1–4.8 × 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
Cobalt1.3 × 10⁻⁴ t8.9 × 10⁻⁷1.1 × 10⁻⁷81%
Lithium7.2 × 10⁻⁵ t1.8 × 10⁻⁷1.3 × 10⁻⁸9.3%
Nickel3.1 × 10⁻⁴ t3.8 × 10⁻⁸1.2 × 10⁻⁸8.5%
Manganese1.7 × 10⁻⁴ t6.6 × 10⁻⁹1.1 × 10⁻⁹0.81%
Total1.4 × 10⁻⁷= the headline figure, 1.4 × 10⁻⁷

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
Congo, Dem. Rep.1.1 × 10⁻⁷81%
Philippines6.1 × 10⁻⁹4.4%
Mali3.7 × 10⁻⁹2.7%
Australia3.5 × 10⁻⁹2.5%
Brazil3.1 × 10⁻⁹2.2%
Colombia1.9 × 10⁻⁹1.4%
Argentina1.7 × 10⁻⁹1.3%
Canada1.6 × 10⁻⁹1.2%
Indonesia1.1 × 10⁻⁹0.82%
Portugal1.0 × 10⁻⁹0.73%
Ukraine9.3 × 10⁻¹⁰0.67%
Russian Federation6.8 × 10⁻¹⁰0.49%
Turkiye4.4 × 10⁻¹⁰0.32%
United States3.0 × 10⁻¹⁰0.22%
Guatemala1.4 × 10⁻¹⁰0.10%
Papua New Guinea9.6 × 10⁻¹¹<0.1%
Mexico6.6 × 10⁻¹¹<0.1%
Myanmar6.6 × 10⁻¹¹<0.1%
Finland5.2 × 10⁻¹¹<0.1%
Georgia3.3 × 10⁻¹¹<0.1%
Morocco1.1 × 10⁻¹¹<0.1%
South Africa8.8 × 10⁻¹²<0.1%
Ghana2.2 × 10⁻¹²<0.1%
India1.6 × 10⁻¹²<0.1%
China1.4 × 10⁻¹²<0.1%
Total1.4 × 10⁻⁷= the headline figure, 1.4 × 10⁻⁷

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 violence1.3 × 10⁻⁷93%
Work1.0 × 10⁻⁸7.4%
Total1.4 × 10⁻⁷= the headline figure, 1.4 × 10⁻⁷

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
IS - Civilians3.1 × 10⁻⁸22%
URDPC - Civilians2.0 × 10⁻⁸14%
Lengola - Mbole1.3 × 10⁻⁸9.4%
Not placed1.0 × 10⁻⁸7.4%
DR Congo (Zaire): Islamic State9.0 × 10⁻⁹6.5%
M23 - VDP5.6 × 10⁻⁹4.0%
Mobondo - Civilians5.4 × 10⁻⁹3.9%
DR Congo (Zaire): Government4.4 × 10⁻⁹3.2%
M23 - Civilians4.3 × 10⁻⁹3.1%
Rwanda: Government3.8 × 10⁻⁹2.8%
Philippines: Government3.7 × 10⁻⁹2.7%
Government of DR Congo (Zaire) - Civilians3.5 × 10⁻⁹2.5%
Government of Rwanda - Civilians2.1 × 10⁻⁹1.5%
Philippines: Islamic State1.8 × 10⁻⁹1.3%
URDPC - Zaire self-defense group1.8 × 10⁻⁹1.3%
Zaire self-defense group - Civilians1.6 × 10⁻⁹1.1%
VDP - Civilians1.5 × 10⁻⁹1.1%
FPIC Chambre noire sanduku - URDPC1.2 × 10⁻⁹0.84%
FPIC Chambre noire sanduku - Civilians1.1 × 10⁻⁹0.82%
Mali: Government9.8 × 10⁻¹⁰0.71%
Russia - Ukraine9.5 × 10⁻¹⁰0.69%
Comando Vermelho - PCC8.9 × 10⁻¹⁰0.65%
AFC - Civilians8.3 × 10⁻¹⁰0.60%
AFP-Gutabara - CNPSC, FABB7.8 × 10⁻¹⁰0.56%
Indonesia: West Papua7.1 × 10⁻¹⁰0.52%
IS - JNIM6.3 × 10⁻¹⁰0.46%
Government of Mali - Civilians5.0 × 10⁻¹⁰0.36%
Mali: Government/Azawad4.1 × 10⁻¹⁰0.30%
Colombia: Government3.8 × 10⁻¹⁰0.28%
JNIM - Civilians3.7 × 10⁻¹⁰0.27%
CPP - Civilians3.6 × 10⁻¹⁰0.26%
OPM - Civilians3.4 × 10⁻¹⁰0.25%
Bonde do Maluco - Comando Vermelho3.2 × 10⁻¹⁰0.23%
Cartel do Norte - Comando Vermelho2.9 × 10⁻¹⁰0.21%
AFP-Gutabara - FABB2.8 × 10⁻¹⁰0.21%
FRPI - Civilians2.3 × 10⁻¹⁰0.17%
Bonde dos 40 - PCC2.1 × 10⁻¹⁰0.15%
Dan na Ambassagou - JNIM2.1 × 10⁻¹⁰0.15%
Mali: Islamic State2.0 × 10⁻¹⁰0.15%
Burundi: Government1.8 × 10⁻¹⁰0.13%
EGC - Civilians1.8 × 10⁻¹⁰0.13%
Comando Vermelho - GDE1.6 × 10⁻¹⁰0.11%
Nova Okaida - Estados Unidos1.6 × 10⁻¹⁰0.11%
Basonge - Bena Nkoma (Bakwa Luntu, Luba)1.6 × 10⁻¹⁰0.11%
GDE, PCC - Sindicato do Crime1.5 × 10⁻¹⁰0.11%
PCC - Sindicato do Crime1.4 × 10⁻¹⁰<0.1%
Amigos Para Sempre - Família Terror Amapá1.3 × 10⁻¹⁰<0.1%
FDLR-FOCA - Civilians1.3 × 10⁻¹⁰<0.1%
FPIC Chambre noire sanduku - FRPI1.3 × 10⁻¹⁰<0.1%
Comando Vermelho - Civilians1.1 × 10⁻¹⁰<0.1%
Mayi Mayi Chini ya Tuna - Civilians1.0 × 10⁻¹⁰<0.1%
Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin9.5 × 10⁻¹¹<0.1%
FARC-EMC - Civilians9.4 × 10⁻¹¹<0.1%
M18 - MS-138.7 × 10⁻¹¹<0.1%
Government of Indonesia - Civilians8.5 × 10⁻¹¹<0.1%
Bonde dos 13, PCC - Comando Vermelho8.1 × 10⁻¹¹<0.1%
Bonde dos 40 - Comando Vermelho8.1 × 10⁻¹¹<0.1%
South Sudan: Government7.8 × 10⁻¹¹<0.1%
Luba - Batwa7.8 × 10⁻¹¹<0.1%
FARC-EMC - ELN6.0 × 10⁻¹¹<0.1%
Russia (Soviet Union): Government5.8 × 10⁻¹¹<0.1%
Comando Vermelho - Holanda5.7 × 10⁻¹¹<0.1%
Dozos (Mali) - JNIM5.6 × 10⁻¹¹<0.1%
Philippines: Mindanao4.5 × 10⁻¹¹<0.1%
Government of Philippines - Civilians4.5 × 10⁻¹¹<0.1%
Comando Vermelho - Massa4.4 × 10⁻¹¹<0.1%
Nova Okaida - PCC4.2 × 10⁻¹¹<0.1%
FARC - Segunda Marquetalia - Civilians4.0 × 10⁻¹¹<0.1%
Bonde do Maluco - Katiara4.0 × 10⁻¹¹<0.1%
Bonde do Maluco - Civilians4.0 × 10⁻¹¹<0.1%
ELN - Civilians3.8 × 10⁻¹¹<0.1%
Myanmar (Burma): Government3.7 × 10⁻¹¹<0.1%
Jalisco Cartel New Generation - Sinaloa Cartel3.2 × 10⁻¹¹<0.1%
Los Costenos - Los Pepes3.2 × 10⁻¹¹<0.1%
Dozos (Mali) - Civilians3.2 × 10⁻¹¹<0.1%
Bonde dos 40 - Civilians3.1 × 10⁻¹¹<0.1%
MS-13 - Civilians3.1 × 10⁻¹¹<0.1%
EGC - ELN, FARC-EMC3.1 × 10⁻¹¹<0.1%
Comando Vermelho - Terceiro Comando Puro3.0 × 10⁻¹¹<0.1%
EGC - ELN3.0 × 10⁻¹¹<0.1%
DR Congo (Zaire): Katanga2.6 × 10⁻¹¹<0.1%
Government of Uganda - Civilians2.6 × 10⁻¹¹<0.1%
Government of Burundi - Civilians2.6 × 10⁻¹¹<0.1%
Twiganeho - Civilians2.6 × 10⁻¹¹<0.1%
AFC - VDP2.6 × 10⁻¹¹<0.1%
M18 - Civilians2.5 × 10⁻¹¹<0.1%
PCC - Civilians2.2 × 10⁻¹¹<0.1%
Turkey: Kurdistan2.1 × 10⁻¹¹<0.1%
Ajeita - Bonde do Maluco2.0 × 10⁻¹¹<0.1%
Dan na Ambassagou - Civilians2.0 × 10⁻¹¹<0.1%
Government of Brazil - Civilians1.5 × 10⁻¹¹<0.1%
GATIA - IS1.5 × 10⁻¹¹<0.1%
Anti-Bala - Bala na Cara1.4 × 10⁻¹¹<0.1%
EGC - Autodefensas Conquistadoras de la Sierra Nevada1.3 × 10⁻¹¹<0.1%
Government of Myanmar (Burma) - Civilians1.3 × 10⁻¹¹<0.1%
Bonde dos 40 - PCM1.2 × 10⁻¹¹<0.1%
Morocco: Sahrawi Arab Democratic Republic (Western Sahara)1.1 × 10⁻¹¹<0.1%
Government of Colombia - Civilians1.1 × 10⁻¹¹<0.1%
Jalisco Cartel New Generation - Santa Rosa de Lima Cartel9.6 × 10⁻¹²<0.1%
Juarez Cartel - Sinaloa Cartel8.7 × 10⁻¹²<0.1%
Government of Russia (Soviet Union) - Civilians8.5 × 10⁻¹²<0.1%
Myanmar (Burma): Kachin7.7 × 10⁻¹²<0.1%
IS - MSA7.3 × 10⁻¹²<0.1%
Carteles Unidos - Jalisco Cartel New Generation6.5 × 10⁻¹²<0.1%
CATA - Codeta5.3 × 10⁻¹²<0.1%
Comandos de la Frontera - Civilians4.7 × 10⁻¹²<0.1%
Myanmar (Burma): Karen4.1 × 10⁻¹²<0.1%
Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos3.7 × 10⁻¹²<0.1%
Autodefensas Conquistadoras de la Sierra Nevada - Civilians3.6 × 10⁻¹²<0.1%
Government of South Africa - Civilians3.5 × 10⁻¹²<0.1%
Myanmar (Burma): Karenni3.2 × 10⁻¹²<0.1%
Russia: Islamic State3.0 × 10⁻¹²<0.1%
Los Costenos - Civilians2.4 × 10⁻¹²<0.1%
Kusasi - Mamprusi2.2 × 10⁻¹²<0.1%
Myanmar (Burma): Arakan1.7 × 10⁻¹²<0.1%
Cartel Independiente de Acapulco - Los Rusos, UPOEG1.6 × 10⁻¹²<0.1%
Government of Papua New Guinea - Civilians1.4 × 10⁻¹²<0.1%
Amigos dos Amigos - Comando Vermelho1.2 × 10⁻¹²<0.1%
FDN - PCC1.2 × 10⁻¹²<0.1%
Russia (Soviet Union): Chechnya1.2 × 10⁻¹²<0.1%
Myanmar (Burma): Kokang1.1 × 10⁻¹²<0.1%
Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos1.0 × 10⁻¹²<0.1%
Carteles Unidos, Guerreros Unidos - Los Tlacos9.4 × 10⁻¹³<0.1%
Los Ardillos - Los Tlacos6.9 × 10⁻¹³<0.1%
Jalisco Cartel New Generation - Zetas Vieja Escuela5.0 × 10⁻¹³<0.1%
India: Kashmir4.5 × 10⁻¹³<0.1%
PKK - Civilians3.9 × 10⁻¹³<0.1%
Kuki - Meitei3.9 × 10⁻¹³<0.1%
India: Government3.7 × 10⁻¹³<0.1%
NUG - Civilians3.2 × 10⁻¹³<0.1%
CPI-Maoist - Civilians1.6 × 10⁻¹³<0.1%
Los Rusos, UPOEG - Los Tlacos1.4 × 10⁻¹³<0.1%
Jalisco Cartel New Generation - Civilians1.3 × 10⁻¹³<0.1%
Jalisco Cartel New Generation - Pájaros Sierra1.2 × 10⁻¹³<0.1%
Government of Mexico - Civilians1.0 × 10⁻¹³<0.1%
Los Ardillos - Los Rojos8.6 × 10⁻¹⁴<0.1%
Gulf Cartel - Los Zetas - Cártel del Noreste faction8.1 × 10⁻¹⁴<0.1%
Kashmir insurgents - Civilians7.3 × 10⁻¹⁴<0.1%
Myanmar (Burma): Shan4.3 × 10⁻¹⁴<0.1%
Hindus (India) - Muslims (India)3.1 × 10⁻¹⁴<0.1%
Gulf Cartel - Sinaloa Cartel2.9 × 10⁻¹⁴<0.1%
Gulf Cartel - Jalisco Cartel New Generation2.9 × 10⁻¹⁴<0.1%
Government of India - Civilians2.7 × 10⁻¹⁴<0.1%
ARSA - Civilians2.1 × 10⁻¹⁴<0.1%
India: Western South East Asia1.5 × 10⁻¹⁴<0.1%
VHP - Civilians7.6 × 10⁻¹⁵<0.1%
Guerreros Unidos - Los Tlacos4.8 × 10⁻¹⁵<0.1%
India - Pakistan3.8 × 10⁻¹⁵<0.1%
India: Nagaland3.8 × 10⁻¹⁵<0.1%
NSCN-IM - Civilians3.8 × 10⁻¹⁵<0.1%
PLFI - Civilians3.8 × 10⁻¹⁵<0.1%
Total1.4 × 10⁻⁷= the headline figure, 1.4 × 10⁻⁷

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 quarrying2.6 × 10⁻⁶83%
Crop and animal production, hunting and related service activities1.6 × 10⁻⁷5.0%
Land transport and transport via pipelines7.0 × 10⁻⁸2.2%
Water transport6.1 × 10⁻⁸1.9%
Manufacture of basic metals5.1 × 10⁻⁸1.6%
Manufacture of chemicals and chemical products5.1 × 10⁻⁸1.6%
Warehousing and support activities for transportation3.1 × 10⁻⁸0.97%
Forestry and logging3.0 × 10⁻⁸0.95%
Air transport1.9 × 10⁻⁸0.61%
Wholesale trade, except of motor vehicles and motorcycles1.3 × 10⁻⁸0.41%
Manufacture of coke and refined petroleum products8.0 × 10⁻⁹0.25%
Postal and courier activities4.9 × 10⁻⁹0.15%
Retail trade, except of motor vehicles and motorcycles4.5 × 10⁻⁹0.14%
Manufacture of fabricated metal products, except machinery and equipment4.3 × 10⁻⁹0.14%
Manufacture of other transport equipment4.0 × 10⁻⁹0.13%
Construction3.5 × 10⁻⁹0.11%
Water collection, treatment and supply3.2 × 10⁻⁹0.10%
Electricity, gas, steam and air conditioning supply3.2 × 10⁻⁹0.10%
Security and investigation, service and landscape, office administrative and support activities2.4 × 10⁻⁹<0.1%
Rental and leasing activities1.9 × 10⁻⁹<0.1%
Public administration and defence; compulsory social security1.7 × 10⁻⁹<0.1%
Sewerage, waste management, remediation activities1.5 × 10⁻⁹<0.1%
Employment activities1.2 × 10⁻⁹<0.1%
Manufacture of rubber and plastic products1.2 × 10⁻⁹<0.1%
Manufacture of food products; beverages and tobacco products1.1 × 10⁻⁹<0.1%
Legal and accounting activities; activities of head offices; management consultancy activities9.5 × 10⁻¹⁰<0.1%
Wholesale and retail trade and repair of motor vehicles and motorcycles8.3 × 10⁻¹⁰<0.1%
Manufacture of paper and paper products7.5 × 10⁻¹⁰<0.1%
Accommodation and food service activities6.0 × 10⁻¹⁰<0.1%
Manufacture of machinery and equipment n.e.c.5.4 × 10⁻¹⁰<0.1%
Manufacture of computer, electronic and optical products5.1 × 10⁻¹⁰<0.1%
Manufacture of other non-metallic mineral products4.7 × 10⁻¹⁰<0.1%
Manufacture of motor vehicles, trailers and semi-trailers3.6 × 10⁻¹⁰<0.1%
Manufacture of textiles, wearing apparel, leather and related products3.6 × 10⁻¹⁰<0.1%
Repair and installation of machinery and equipment3.4 × 10⁻¹⁰<0.1%
Manufacture of electrical equipment3.0 × 10⁻¹⁰<0.1%
Architectural and engineering activities; technical testing and analysis2.8 × 10⁻¹⁰<0.1%
Human health activities2.7 × 10⁻¹⁰<0.1%
Advertising and market research2.5 × 10⁻¹⁰<0.1%
Travel agency, tour operator reservation service and related activities2.4 × 10⁻¹⁰<0.1%
Manufacture of basic pharmaceutical products and pharmaceutical preparations2.3 × 10⁻¹⁰<0.1%
Real estate activities2.3 × 10⁻¹⁰<0.1%
Computer programming, consultancy, and information service activities2.2 × 10⁻¹⁰<0.1%
Repair of computers and personal and household goods2.2 × 10⁻¹⁰<0.1%
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials1.8 × 10⁻¹⁰<0.1%
Activities of membership organisations1.7 × 10⁻¹⁰<0.1%
Fishing and aquaculture1.6 × 10⁻¹⁰<0.1%
Other personal service activities1.5 × 10⁻¹⁰<0.1%
Printing and reproduction of recorded media1.4 × 10⁻¹⁰<0.1%
Financial service activities, except insurance and pension funding1.4 × 10⁻¹⁰<0.1%
Manufacture of furniture; other manufacturing1.1 × 10⁻¹⁰<0.1%
Other professional, scientific and technical activities; veterinary activities1.1 × 10⁻¹⁰<0.1%
Telecommunications1.0 × 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 activities7.8 × 10⁻¹¹<0.1%
Education6.1 × 10⁻¹¹<0.1%
Motion picture, video, television programme production; programming and broadcasting activities5.2 × 10⁻¹¹<0.1%
Activities auxiliary to financial services and insurance activities4.5 × 10⁻¹¹<0.1%
Publishing activities4.5 × 10⁻¹¹<0.1%
Insurance, reinsurance and pension funding, except compulsory social security4.1 × 10⁻¹¹<0.1%
Scientific research and development2.5 × 10⁻¹¹<0.1%
Residential care activities and social work activities without accommodation1.7 × 10⁻¹¹<0.1%
Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use2.8 × 10⁻¹²<0.1%
Total3.2 × 10⁻⁶= the headline figure, 3.2 × 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 placed2.8 × 10⁻⁶87%
Mexico2.1 × 10⁻⁷6.7%
Brazil6.5 × 10⁻⁸2.0%
United States2.9 × 10⁻⁸0.92%
Russian Federation2.7 × 10⁻⁸0.85%
Turkiye1.5 × 10⁻⁸0.46%
Canada1.2 × 10⁻⁸0.37%
Korea, Rep.1.1 × 10⁻⁸0.35%
Japan7.9 × 10⁻⁹0.25%
France7.5 × 10⁻⁹0.24%
India5.0 × 10⁻⁹0.16%
Argentina4.1 × 10⁻⁹0.13%
Germany4.0 × 10⁻⁹0.13%
Spain3.1 × 10⁻⁹<0.1%
Indonesia3.0 × 10⁻⁹<0.1%
Italy3.0 × 10⁻⁹<0.1%
Poland1.8 × 10⁻⁹<0.1%
Australia1.2 × 10⁻⁹<0.1%
Portugal9.5 × 10⁻¹⁰<0.1%
Austria9.4 × 10⁻¹⁰<0.1%
Czechia7.1 × 10⁻¹⁰<0.1%
Belgium6.8 × 10⁻¹⁰<0.1%
Bulgaria6.5 × 10⁻¹⁰<0.1%
Netherlands6.5 × 10⁻¹⁰<0.1%
Romania5.4 × 10⁻¹⁰<0.1%
Hungary4.9 × 10⁻¹⁰<0.1%
Switzerland4.7 × 10⁻¹⁰<0.1%
Lithuania4.5 × 10⁻¹⁰<0.1%
Denmark4.0 × 10⁻¹⁰<0.1%
Greece3.9 × 10⁻¹⁰<0.1%
Sweden3.6 × 10⁻¹⁰<0.1%
Saudi Arabia3.6 × 10⁻¹⁰<0.1%
Norway3.1 × 10⁻¹⁰<0.1%
Finland3.0 × 10⁻¹⁰<0.1%
Ireland2.5 × 10⁻¹⁰<0.1%
Latvia2.5 × 10⁻¹⁰<0.1%
Slovak Republic1.7 × 10⁻¹⁰<0.1%
Slovenia1.5 × 10⁻¹⁰<0.1%
Croatia1.3 × 10⁻¹⁰<0.1%
South Africa9.5 × 10⁻¹¹<0.1%
Luxembourg6.5 × 10⁻¹¹<0.1%
Estonia6.1 × 10⁻¹¹<0.1%
United Kingdom4.2 × 10⁻¹¹<0.1%
Cyprus4.0 × 10⁻¹¹<0.1%
China2.9 × 10⁻¹¹<0.1%
Malta9.0 × 10⁻¹²<0.1%
Serbia1.6 × 10⁻¹⁴<0.1%
Total3.2 × 10⁻⁶= the headline figure, 3.2 × 10⁻⁶

What this trail does not show

Sources behind this figure

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

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