El rastro de auditoría
Cómo se construye la cifra de Paquete de baterías de iones de litio
Cada etapa por la que pasa el modelo, con su número. Cada tabla divide la misma cifra principal de una forma distinta, y cada una la suma exactamente — la página lo comprueba y se niega a mostrar una tabla que no la sume.
¿Hay algo mal en esta página? Avísanos →
La cifra principal
Una unidad es one kilogram of assembled lithium-ion battery pack. Escenario Economic-embedded, sobre FIGARO 2023. Cada cifra es la estimación central de 2.000 extracciones, con el intervalo del percentil 5 al 95 al lado y el grado que ese intervalo merece.
Vía de materiales — 6,9 × 10⁻⁸ por unidad(0,36–1,4 × 10⁻⁷)BAJAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Vía monetaria — 2,3 × 10⁻⁶ por cada 1.000 € gastados en su industria(1,5–3,6 × 10⁻⁶)MEDIAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Cada paso de abajo es una estimación central. El modelo calcula un intervalo para la cifra completa, no para cada paso, así que el intervalo que se aplica a un paso es el de la cifra principal.
1 · De qué está hecho, y qué lleva cada material
La cantidad de cada materia prima en una unidad, las muertes que lleva cada kilogramo de ella en esta ejecución, y su producto: su aportación a la cifra principal.
| Material | Por unidad | Muertes por kg | Aportación | Parte |
|---|---|---|---|---|
| Cobalto | 4,8 × 10⁻⁵ t | 8,9 × 10⁻⁷ | 4,3 × 10⁻⁸ | 63 % |
| Cobre | 7,2 × 10⁻⁵ t | 2,0 × 10⁻⁷ | 1,4 × 10⁻⁸ | 20 % |
| Litio | 2,8 × 10⁻⁵ t | 1,8 × 10⁻⁷ | 4,9 × 10⁻⁹ | 7,2 % |
| Níquel | 1,2 × 10⁻⁴ t | 3,8 × 10⁻⁸ | 4,5 × 10⁻⁹ | 6,6 % |
| Grafito natural | 2,0 × 10⁻⁴ t | 6,1 × 10⁻⁹ | 1,2 × 10⁻⁹ | 1,8 % |
| Manganeso | 6,5 × 10⁻⁵ t | 6,6 × 10⁻⁹ | 4,3 × 10⁻¹⁰ | 0,63 % |
| Bauxita | 6,9 × 10⁻⁴ t | 1,2 × 10⁻¹⁰ | 8,3 × 10⁻¹¹ | 0,12 % |
| Mineral de hierro | 6,6 × 10⁻⁶ t | 1,9 × 10⁻⁹ | 1,2 × 10⁻¹¹ | <0,1 % |
| Carbón y lignito | 3,4 × 10⁻⁶ t | 1,7 × 10⁻⁹ | 6,0 × 10⁻¹² | <0,1 % |
| Suma | 6,9 × 10⁻⁸ | = la cifra principal, 6,9 × 10⁻⁸ | ||
2 · Dónde se contó el daño
La misma cifra principal, según el país donde se contó el daño que llevan los materiales.
| País | Aportación | Parte |
|---|---|---|
| República Democrática del Congo | 5,5 × 10⁻⁸ | 80 % |
| Filipinas | 2,3 × 10⁻⁹ | 3,4 % |
| México | 2,2 × 10⁻⁹ | 3,2 % |
| Mali | 1,4 × 10⁻⁹ | 2,1 % |
| Australia | 1,4 × 10⁻⁹ | 2,0 % |
| Brasil | 1,3 × 10⁻⁹ | 1,9 % |
| Colombia | 7,3 × 10⁻¹⁰ | 1,1 % |
| Argentina | 6,7 × 10⁻¹⁰ | 0,97 % |
| Canadá | 6,6 × 10⁻¹⁰ | 0,97 % |
| Ucrania | 6,1 × 10⁻¹⁰ | 0,89 % |
| Mozambique | 4,9 × 10⁻¹⁰ | 0,72 % |
| Indonesia | 4,5 × 10⁻¹⁰ | 0,65 % |
| Portugal | 3,9 × 10⁻¹⁰ | 0,56 % |
| Rusia | 3,1 × 10⁻¹⁰ | 0,45 % |
| Sri Lanka | 2,7 × 10⁻¹⁰ | 0,39 % |
| Estados Unidos | 2,2 × 10⁻¹⁰ | 0,33 % |
| Turquía | 2,1 × 10⁻¹⁰ | 0,31 % |
| Corea del Sur | 5,6 × 10⁻¹¹ | <0,1 % |
| Guatemala | 5,5 × 10⁻¹¹ | <0,1 % |
| Polonia | 4,0 × 10⁻¹¹ | <0,1 % |
| Papúa Nueva Guinea | 3,7 × 10⁻¹¹ | <0,1 % |
| Pakistán | 2,9 × 10⁻¹¹ | <0,1 % |
| Myanmar (Birmania) | 2,5 × 10⁻¹¹ | <0,1 % |
| Finlandia | 2,0 × 10⁻¹¹ | <0,1 % |
| Perú | 1,7 × 10⁻¹¹ | <0,1 % |
| Rumanía | 1,4 × 10⁻¹¹ | <0,1 % |
| Georgia | 1,3 × 10⁻¹¹ | <0,1 % |
| India | 8,0 × 10⁻¹² | <0,1 % |
| Marruecos | 4,2 × 10⁻¹² | <0,1 % |
| Sudáfrica | 3,4 × 10⁻¹² | <0,1 % |
| Grecia | 2,7 × 10⁻¹² | <0,1 % |
| Ghana | 8,5 × 10⁻¹³ | <0,1 % |
| China | 6,8 × 10⁻¹³ | <0,1 % |
| Austria | 5,5 × 10⁻¹³ | <0,1 % |
| Noruega | 3,2 × 10⁻¹³ | <0,1 % |
| Alemania | 1,8 × 10⁻¹³ | <0,1 % |
| Venezuela | 1,3 × 10⁻¹³ | <0,1 % |
| Uzbekistán | 5,0 × 10⁻¹⁴ | <0,1 % |
| Arabia Saudí | 3,4 × 10⁻¹⁴ | <0,1 % |
| Suecia | 2,3 × 10⁻¹⁴ | <0,1 % |
| Mongolia | 1,9 × 10⁻¹⁴ | <0,1 % |
| Bulgaria | 1,4 × 10⁻¹⁴ | <0,1 % |
| Chequia | 1,1 × 10⁻¹⁴ | <0,1 % |
| Mauritania | 9,6 × 10⁻¹⁵ | <0,1 % |
| Tailandia | 8,0 × 10⁻¹⁵ | <0,1 % |
| Níger | 4,3 × 10⁻¹⁵ | <0,1 % |
| Etiopía | 4,2 × 10⁻¹⁵ | <0,1 % |
| Irán | 4,2 × 10⁻¹⁵ | <0,1 % |
| Nigeria | 4,1 × 10⁻¹⁵ | <0,1 % |
| Afganistán | 3,8 × 10⁻¹⁵ | <0,1 % |
| Eslovenia | 1,7 × 10⁻¹⁵ | <0,1 % |
| Hungría | 1,3 × 10⁻¹⁵ | <0,1 % |
| Japón | 7,4 × 10⁻¹⁶ | <0,1 % |
| Eslovaquia | 6,5 × 10⁻¹⁶ | <0,1 % |
| Esuatini | 7,6 × 10⁻¹⁷ | <0,1 % |
| Bangladés | 1,0 × 10⁻¹⁷ | <0,1 % |
| Armenia | 7,1 × 10⁻²⁰ | <0,1 % |
| Suma | 6,9 × 10⁻⁸ | = la cifra principal, 6,9 × 10⁻⁸ |
3 · Por qué canal de daño
La misma cifra principal, por canal de daño: conflicto, trabajo, privación, exposición.
| Canal | Aportación | Parte |
|---|---|---|
| Conflicto y violencia política | 6,4 × 10⁻⁸ | 93 % |
| Trabajo | 4,6 × 10⁻⁹ | 6,7 % |
| Suma | 6,9 × 10⁻⁸ | = la cifra principal, 6,9 × 10⁻⁸ |
4 · Qué conflictos
Las muertes por conflicto de la cifra principal, por conflicto. El daño de cualquier otro canal es la fila que no nombra ningún conflicto.
| Conflicto | Aportación | Parte |
|---|---|---|
| IS - Civilians | 1,5 × 10⁻⁸ | 22 % |
| URDPC - Civilians | 9,6 × 10⁻⁹ | 14 % |
| Lengola - Mbole | 6,3 × 10⁻⁹ | 9,2 % |
| Sin ubicar | 4,6 × 10⁻⁹ | 6,7 % |
| DR Congo (Zaire): Islamic State | 4,4 × 10⁻⁹ | 6,4 % |
| M23 - VDP | 2,7 × 10⁻⁹ | 4,0 % |
| Mobondo - Civilians | 2,6 × 10⁻⁹ | 3,8 % |
| DR Congo (Zaire): Government | 2,2 × 10⁻⁹ | 3,1 % |
| M23 - Civilians | 2,1 × 10⁻⁹ | 3,1 % |
| Rwanda: Government | 1,9 × 10⁻⁹ | 2,7 % |
| Government of DR Congo (Zaire) - Civilians | 1,7 × 10⁻⁹ | 2,5 % |
| Philippines: Government | 1,4 × 10⁻⁹ | 2,1 % |
| Jalisco Cartel New Generation - Sinaloa Cartel | 1,1 × 10⁻⁹ | 1,5 % |
| Government of Rwanda - Civilians | 1,0 × 10⁻⁹ | 1,5 % |
| URDPC - Zaire self-defense group | 8,7 × 10⁻¹⁰ | 1,3 % |
| Zaire self-defense group - Civilians | 7,7 × 10⁻¹⁰ | 1,1 % |
| VDP - Civilians | 7,3 × 10⁻¹⁰ | 1,1 % |
| Philippines: Islamic State | 6,9 × 10⁻¹⁰ | 1,0 % |
| Russia - Ukraine | 6,2 × 10⁻¹⁰ | 0,90 % |
| FPIC Chambre noire sanduku - URDPC | 5,7 × 10⁻¹⁰ | 0,83 % |
| FPIC Chambre noire sanduku - Civilians | 5,6 × 10⁻¹⁰ | 0,81 % |
| AFC - Civilians | 4,1 × 10⁻¹⁰ | 0,59 % |
| AFP-Gutabara - CNPSC, FABB | 3,8 × 10⁻¹⁰ | 0,55 % |
| Mali: Government | 3,8 × 10⁻¹⁰ | 0,55 % |
| Comando Vermelho - PCC | 3,7 × 10⁻¹⁰ | 0,55 % |
| Mozambique: Islamic State | 3,2 × 10⁻¹⁰ | 0,46 % |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 3,2 × 10⁻¹⁰ | 0,46 % |
| Juarez Cartel - Sinaloa Cartel | 2,8 × 10⁻¹⁰ | 0,41 % |
| Indonesia: West Papua | 2,8 × 10⁻¹⁰ | 0,41 % |
| IS - JNIM | 2,4 × 10⁻¹⁰ | 0,35 % |
| Carteles Unidos - Jalisco Cartel New Generation | 2,1 × 10⁻¹⁰ | 0,31 % |
| Government of Mali - Civilians | 1,9 × 10⁻¹⁰ | 0,28 % |
| Mali: Government/Azawad | 1,6 × 10⁻¹⁰ | 0,23 % |
| Colombia: Government | 1,5 × 10⁻¹⁰ | 0,22 % |
| JNIM - Civilians | 1,4 × 10⁻¹⁰ | 0,21 % |
| CPP - Civilians | 1,4 × 10⁻¹⁰ | 0,20 % |
| AFP-Gutabara - FABB | 1,4 × 10⁻¹⁰ | 0,20 % |
| Bonde do Maluco - Comando Vermelho | 1,4 × 10⁻¹⁰ | 0,20 % |
| OPM - Civilians | 1,3 × 10⁻¹⁰ | 0,19 % |
| Cartel do Norte - Comando Vermelho | 1,2 × 10⁻¹⁰ | 0,18 % |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 1,2 × 10⁻¹⁰ | 0,18 % |
| FRPI - Civilians | 1,1 × 10⁻¹⁰ | 0,17 % |
| Burundi: Government | 8,9 × 10⁻¹¹ | 0,13 % |
| Bonde dos 40 - PCC | 8,7 × 10⁻¹¹ | 0,13 % |
| Dan na Ambassagou - JNIM | 8,0 × 10⁻¹¹ | 0,12 % |
| Mali: Islamic State | 7,8 × 10⁻¹¹ | 0,11 % |
| Basonge - Bena Nkoma (Bakwa Luntu, Luba) | 7,6 × 10⁻¹¹ | 0,11 % |
| EGC - Civilians | 6,8 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - GDE | 6,6 × 10⁻¹¹ | <0,1 % |
| Nova Okaida - Estados Unidos | 6,6 × 10⁻¹¹ | <0,1 % |
| GDE, PCC - Sindicato do Crime | 6,5 × 10⁻¹¹ | <0,1 % |
| FDLR-FOCA - Civilians | 6,3 × 10⁻¹¹ | <0,1 % |
| FPIC Chambre noire sanduku - FRPI | 6,3 × 10⁻¹¹ | <0,1 % |
| PCC - Sindicato do Crime | 5,7 × 10⁻¹¹ | <0,1 % |
| Amigos Para Sempre - Família Terror Amapá | 5,7 × 10⁻¹¹ | <0,1 % |
| IS - Naparama | 5,4 × 10⁻¹¹ | <0,1 % |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 5,4 × 10⁻¹¹ | <0,1 % |
| Mayi Mayi Chini ya Tuna - Civilians | 5,1 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Civilians | 4,7 × 10⁻¹¹ | <0,1 % |
| South Sudan: Government | 3,8 × 10⁻¹¹ | <0,1 % |
| Luba - Batwa | 3,8 × 10⁻¹¹ | <0,1 % |
| Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin | 3,7 × 10⁻¹¹ | <0,1 % |
| FARC-EMC - Civilians | 3,6 × 10⁻¹¹ | <0,1 % |
| Bonde dos 13, PCC - Comando Vermelho | 3,4 × 10⁻¹¹ | <0,1 % |
| Bonde dos 40 - Comando Vermelho | 3,4 × 10⁻¹¹ | <0,1 % |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 3,4 × 10⁻¹¹ | <0,1 % |
| M18 - MS-13 | 3,4 × 10⁻¹¹ | <0,1 % |
| Government of Indonesia - Civilians | 3,3 × 10⁻¹¹ | <0,1 % |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 3,1 × 10⁻¹¹ | <0,1 % |
| Russia (Soviet Union): Government | 2,6 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Holanda | 2,4 × 10⁻¹¹ | <0,1 % |
| Government of Mozambique - Civilians | 2,3 × 10⁻¹¹ | <0,1 % |
| FARC-EMC - ELN | 2,3 × 10⁻¹¹ | <0,1 % |
| Los Ardillos - Los Tlacos | 2,3 × 10⁻¹¹ | <0,1 % |
| Dozos (Mali) - JNIM | 2,2 × 10⁻¹¹ | <0,1 % |
| Pakistan: Government | 2,1 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Massa | 1,8 × 10⁻¹¹ | <0,1 % |
| Nova Okaida - PCC | 1,8 × 10⁻¹¹ | <0,1 % |
| Philippines: Mindanao | 1,7 × 10⁻¹¹ | <0,1 % |
| Government of Philippines - Civilians | 1,7 × 10⁻¹¹ | <0,1 % |
| Peru: Government | 1,7 × 10⁻¹¹ | <0,1 % |
| Bonde do Maluco - Katiara | 1,7 × 10⁻¹¹ | <0,1 % |
| Bonde do Maluco - Civilians | 1,7 × 10⁻¹¹ | <0,1 % |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 1,6 × 10⁻¹¹ | <0,1 % |
| FARC - Segunda Marquetalia - Civilians | 1,6 × 10⁻¹¹ | <0,1 % |
| ELN - Civilians | 1,5 × 10⁻¹¹ | <0,1 % |
| Myanmar (Burma): Government | 1,4 × 10⁻¹¹ | <0,1 % |
| Bonde dos 40 - Civilians | 1,3 × 10⁻¹¹ | <0,1 % |
| DR Congo (Zaire): Katanga | 1,3 × 10⁻¹¹ | <0,1 % |
| Government of Uganda - Civilians | 1,3 × 10⁻¹¹ | <0,1 % |
| Government of Burundi - Civilians | 1,3 × 10⁻¹¹ | <0,1 % |
| Twiganeho - Civilians | 1,3 × 10⁻¹¹ | <0,1 % |
| AFC - VDP | 1,3 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Terceiro Comando Puro | 1,3 × 10⁻¹¹ | <0,1 % |
| Los Costenos - Los Pepes | 1,2 × 10⁻¹¹ | <0,1 % |
| Dozos (Mali) - Civilians | 1,2 × 10⁻¹¹ | <0,1 % |
| MS-13 - Civilians | 1,2 × 10⁻¹¹ | <0,1 % |
| EGC - ELN, FARC-EMC | 1,2 × 10⁻¹¹ | <0,1 % |
| EGC - ELN | 1,1 × 10⁻¹¹ | <0,1 % |
| Turkey: Kurdistan | 9,9 × 10⁻¹² | <0,1 % |
| M18 - Civilians | 9,6 × 10⁻¹² | <0,1 % |
| PCC - Civilians | 9,4 × 10⁻¹² | <0,1 % |
| Ajeita - Bonde do Maluco | 8,4 × 10⁻¹² | <0,1 % |
| Dan na Ambassagou - Civilians | 7,5 × 10⁻¹² | <0,1 % |
| Government of Brazil - Civilians | 6,3 × 10⁻¹² | <0,1 % |
| Anti-Bala - Bala na Cara | 5,8 × 10⁻¹² | <0,1 % |
| GATIA - IS | 5,6 × 10⁻¹² | <0,1 % |
| Government of Russia (Soviet Union) - Civilians | 5,4 × 10⁻¹² | <0,1 % |
| Bonde dos 40 - PCM | 5,2 × 10⁻¹² | <0,1 % |
| EGC - Autodefensas Conquistadoras de la Sierra Nevada | 5,0 × 10⁻¹² | <0,1 % |
| Government of Myanmar (Burma) - Civilians | 4,9 × 10⁻¹² | <0,1 % |
| Los Rusos, UPOEG - Los Tlacos | 4,7 × 10⁻¹² | <0,1 % |
| Jalisco Cartel New Generation - Civilians | 4,3 × 10⁻¹² | <0,1 % |
| Morocco: Sahrawi Arab Democratic Republic (Western Sahara) | 4,2 × 10⁻¹² | <0,1 % |
| Government of Colombia - Civilians | 4,1 × 10⁻¹² | <0,1 % |
| Jalisco Cartel New Generation - Pájaros Sierra | 3,9 × 10⁻¹² | <0,1 % |
| Government of Mexico - Civilians | 3,3 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Kachin | 3,1 × 10⁻¹² | <0,1 % |
| Los Ardillos - Los Rojos | 2,8 × 10⁻¹² | <0,1 % |
| IS - MSA | 2,8 × 10⁻¹² | <0,1 % |
| Pakistan: Balochistan | 2,7 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 2,7 × 10⁻¹² | <0,1 % |
| India: Kashmir | 2,3 × 10⁻¹² | <0,1 % |
| Pakistan: Islamic State | 2,1 × 10⁻¹² | <0,1 % |
| CATA - Codeta | 2,0 × 10⁻¹² | <0,1 % |
| Kuki - Meitei | 2,0 × 10⁻¹² | <0,1 % |
| India: Government | 1,9 × 10⁻¹² | <0,1 % |
| Comandos de la Frontera - Civilians | 1,8 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Karen | 1,6 × 10⁻¹² | <0,1 % |
| Autodefensas Conquistadoras de la Sierra Nevada - Civilians | 1,4 × 10⁻¹² | <0,1 % |
| Government of South Africa - Civilians | 1,4 × 10⁻¹² | <0,1 % |
| Russia: Islamic State | 1,4 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Karenni | 1,2 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Sinaloa Cartel | 9,4 × 10⁻¹³ | <0,1 % |
| Gulf Cartel - Jalisco Cartel New Generation | 9,4 × 10⁻¹³ | <0,1 % |
| Los Costenos - Civilians | 9,1 × 10⁻¹³ | <0,1 % |
| Kusasi - Mamprusi | 8,5 × 10⁻¹³ | <0,1 % |
| CPI-Maoist - Civilians | 8,4 × 10⁻¹³ | <0,1 % |
| Shia (Pakistan) - Sunni (Pakistan) | 7,1 × 10⁻¹³ | <0,1 % |
| Myanmar (Burma): Arakan | 6,6 × 10⁻¹³ | <0,1 % |
| Government of Papua New Guinea - Civilians | 5,5 × 10⁻¹³ | <0,1 % |
| Russia (Soviet Union): Chechnya | 5,4 × 10⁻¹³ | <0,1 % |
| Amigos dos Amigos - Comando Vermelho | 5,2 × 10⁻¹³ | <0,1 % |
| FDN - PCC | 5,2 × 10⁻¹³ | <0,1 % |
| Myanmar (Burma): Kokang | 4,1 × 10⁻¹³ | <0,1 % |
| Kashmir insurgents - Civilians | 3,7 × 10⁻¹³ | <0,1 % |
| BRAS - Civilians | 2,9 × 10⁻¹³ | <0,1 % |
| PKK - Civilians | 1,9 × 10⁻¹³ | <0,1 % |
| TTP - Civilians | 1,7 × 10⁻¹³ | <0,1 % |
| Guerreros Unidos - Los Tlacos | 1,6 × 10⁻¹³ | <0,1 % |
| Hindus (India) - Muslims (India) | 1,6 × 10⁻¹³ | <0,1 % |
| Government of India - Civilians | 1,4 × 10⁻¹³ | <0,1 % |
| NUG - Civilians | 1,2 × 10⁻¹³ | <0,1 % |
| Government of Pakistan - Civilians | 1,2 × 10⁻¹³ | <0,1 % |
| Government of Venezuela - Civilians | 1,1 × 10⁻¹³ | <0,1 % |
| India: Western South East Asia | 7,9 × 10⁻¹⁴ | <0,1 % |
| Afghanistan - Pakistan | 4,9 × 10⁻¹⁴ | <0,1 % |
| VHP - Civilians | 3,9 × 10⁻¹⁴ | <0,1 % |
| Yemen (North Yemen): Government | 3,4 × 10⁻¹⁴ | <0,1 % |
| LeJ - Civilians | 2,4 × 10⁻¹⁴ | <0,1 % |
| India - Pakistan | 2,0 × 10⁻¹⁴ | <0,1 % |
| India: Nagaland | 2,0 × 10⁻¹⁴ | <0,1 % |
| NSCN-IM - Civilians | 2,0 × 10⁻¹⁴ | <0,1 % |
| PLFI - Civilians | 2,0 × 10⁻¹⁴ | <0,1 % |
| Myanmar (Burma): Shan | 1,7 × 10⁻¹⁴ | <0,1 % |
| Mauritania: Government | 9,6 × 10⁻¹⁵ | <0,1 % |
| ARSA - Civilians | 8,3 × 10⁻¹⁵ | <0,1 % |
| Iran: Government | 3,5 × 10⁻¹⁵ | <0,1 % |
| Ethiopia: Government/Amhara | 2,2 × 10⁻¹⁵ | <0,1 % |
| Niger: Islamic State | 1,9 × 10⁻¹⁵ | <0,1 % |
| Afghanistan: Islamic State | 1,7 × 10⁻¹⁵ | <0,1 % |
| Nigeria: Islamic State | 1,6 × 10⁻¹⁵ | <0,1 % |
| Ethiopia: Oromiya | 8,2 × 10⁻¹⁶ | <0,1 % |
| Afghanistan: Government | 6,0 × 10⁻¹⁶ | <0,1 % |
| Government of Afghanistan - Civilians | 4,5 × 10⁻¹⁶ | <0,1 % |
| Thailand: Patani | 4,0 × 10⁻¹⁶ | <0,1 % |
| IS - JAS | 3,9 × 10⁻¹⁶ | <0,1 % |
| Nigeria: Government | 3,9 × 10⁻¹⁶ | <0,1 % |
| Iran: Islamic State | 3,9 × 10⁻¹⁶ | <0,1 % |
| Niger: Government | 3,8 × 10⁻¹⁶ | <0,1 % |
| Government of Ethiopia - Civilians | 3,4 × 10⁻¹⁶ | <0,1 % |
| Government of Iran - Civilians | 2,9 × 10⁻¹⁶ | <0,1 % |
| OLA - Civilians | 2,6 × 10⁻¹⁶ | <0,1 % |
| Fano - Civilians | 2,3 × 10⁻¹⁶ | <0,1 % |
| Fulani - Mwaghavul | 2,3 × 10⁻¹⁶ | <0,1 % |
| Anuak - Nuer | 2,3 × 10⁻¹⁶ | <0,1 % |
| Djerma (Zherma) - Fulani | 2,1 × 10⁻¹⁶ | <0,1 % |
| Fulani - Mwaghavul , Ron | 2,1 × 10⁻¹⁶ | <0,1 % |
| Fulani - Tiv | 2,0 × 10⁻¹⁶ | <0,1 % |
| Farmers (Nigeria) - Herders (Nigeria) | 1,7 × 10⁻¹⁶ | <0,1 % |
| JAS - Civilians | 1,6 × 10⁻¹⁶ | <0,1 % |
| Nigeria: Biafra | 1,2 × 10⁻¹⁶ | <0,1 % |
| Birom - Fulani | 9,1 × 10⁻¹⁷ | <0,1 % |
| Atyap - Fulani | 7,8 × 10⁻¹⁷ | <0,1 % |
| Government of eSwatini (Swaziland) - Civilians | 7,6 × 10⁻¹⁷ | <0,1 % |
| Karimjo - Wurukum | 7,4 × 10⁻¹⁷ | <0,1 % |
| Black Axe - Eyie | 7,0 × 10⁻¹⁷ | <0,1 % |
| Forces of Terwase Akwanza - Civilians | 6,1 × 10⁻¹⁷ | <0,1 % |
| Amhara - Oromo | 6,0 × 10⁻¹⁷ | <0,1 % |
| Fulani - Idoma | 5,7 × 10⁻¹⁷ | <0,1 % |
| Fulani - Kuteb | 5,4 × 10⁻¹⁷ | <0,1 % |
| Government of Nigeria - Civilians | 3,8 × 10⁻¹⁷ | <0,1 % |
| Chain Guys - Full Force | 3,2 × 10⁻¹⁷ | <0,1 % |
| Guraghe - Mareqo | 2,7 × 10⁻¹⁷ | <0,1 % |
| Hausa - Fulani | 1,8 × 10⁻¹⁷ | <0,1 % |
| Murle - Nuer | 1,8 × 10⁻¹⁷ | <0,1 % |
| Patani insurgents - Civilians | 1,3 × 10⁻¹⁷ | <0,1 % |
| Fulani - Irigwe | 1,3 × 10⁻¹⁷ | <0,1 % |
| Somalia: Government | 1,1 × 10⁻¹⁷ | <0,1 % |
| Fulani - Igala | 1,1 × 10⁻¹⁷ | <0,1 % |
| Greenlanders - NDV | 9,5 × 10⁻¹⁸ | <0,1 % |
| Black Axe - Maphite | 9,5 × 10⁻¹⁸ | <0,1 % |
| Supporters of APC - Supporters of PDP | 6,3 × 10⁻¹⁸ | <0,1 % |
| Amhara - Gumuz | 5,3 × 10⁻¹⁸ | <0,1 % |
| Black Axe - SVC | 5,3 × 10⁻¹⁸ | <0,1 % |
| IPOB - Civilians | 5,3 × 10⁻¹⁸ | <0,1 % |
| Agatu - Fulani | 4,2 × 10⁻¹⁸ | <0,1 % |
| IS - Yan Gora | 4,2 × 10⁻¹⁸ | <0,1 % |
| Deebam - NDV | 4,2 × 10⁻¹⁸ | <0,1 % |
| Jukun - Tiv | 2,1 × 10⁻¹⁸ | <0,1 % |
| Supporters of Awami League - Supporters of BNP | 1,7 × 10⁻¹⁸ | <0,1 % |
| Cameroon: Ambazonia | 1,1 × 10⁻¹⁸ | <0,1 % |
| Ambazonia insurgents - Civilians | 1,1 × 10⁻¹⁸ | <0,1 % |
| Supporters of Awami League - Supporters of Jamaat-e-Islami | 8,5 × 10⁻¹⁹ | <0,1 % |
| Azerbaijan: Artsakh (Nagorno-Karabakh) | 7,1 × 10⁻²⁰ | <0,1 % |
| Suma | 6,9 × 10⁻⁸ | = la cifra principal, 6,9 × 10⁻⁸ |
5 · La vía monetaria: qué industrias
La cifra por cada 1.000 €, según la industria donde se produjo el daño en cualquier punto de la cadena de suministro.
| Industria | Aportación | Parte |
|---|---|---|
| Mining and quarrying | 1,5 × 10⁻⁶ | 64 % |
| Manufacture of basic metals | 4,9 × 10⁻⁷ | 21 % |
| Land transport and transport via pipelines | 5,6 × 10⁻⁸ | 2,4 % |
| Water transport | 5,2 × 10⁻⁸ | 2,3 % |
| Manufacture of electrical equipment | 4,2 × 10⁻⁸ | 1,8 % |
| Crop and animal production, hunting and related service activities | 3,9 × 10⁻⁸ | 1,7 % |
| Warehousing and support activities for transportation | 2,5 × 10⁻⁸ | 1,1 % |
| Air transport | 2,4 × 10⁻⁸ | 1,0 % |
| Forestry and logging | 2,1 × 10⁻⁸ | 0,91 % |
| Wholesale trade, except of motor vehicles and motorcycles | 1,4 × 10⁻⁸ | 0,59 % |
| Manufacture of fabricated metal products, except machinery and equipment | 9,4 × 10⁻⁹ | 0,41 % |
| Postal and courier activities | 4,4 × 10⁻⁹ | 0,19 % |
| Retail trade, except of motor vehicles and motorcycles | 4,0 × 10⁻⁹ | 0,17 % |
| Construction | 3,6 × 10⁻⁹ | 0,16 % |
| Sewerage, waste management, remediation activities | 3,6 × 10⁻⁹ | 0,16 % |
| Manufacture of other transport equipment | 3,5 × 10⁻⁹ | 0,15 % |
| Manufacture of computer, electronic and optical products | 3,1 × 10⁻⁹ | 0,13 % |
| Manufacture of chemicals and chemical products | 2,6 × 10⁻⁹ | 0,11 % |
| Manufacture of coke and refined petroleum products | 2,5 × 10⁻⁹ | 0,11 % |
| Security and investigation, service and landscape, office administrative and support activities | 2,2 × 10⁻⁹ | <0,1 % |
| Water collection, treatment and supply | 1,9 × 10⁻⁹ | <0,1 % |
| Electricity, gas, steam and air conditioning supply | 1,8 × 10⁻⁹ | <0,1 % |
| Manufacture of rubber and plastic products | 1,8 × 10⁻⁹ | <0,1 % |
| Rental and leasing activities | 1,5 × 10⁻⁹ | <0,1 % |
| Employment activities | 1,3 × 10⁻⁹ | <0,1 % |
| Public administration and defence; compulsory social security | 1,3 × 10⁻⁹ | <0,1 % |
| Manufacture of machinery and equipment n.e.c. | 1,3 × 10⁻⁹ | <0,1 % |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 9,0 × 10⁻¹⁰ | <0,1 % |
| Manufacture of motor vehicles, trailers and semi-trailers | 8,7 × 10⁻¹⁰ | <0,1 % |
| Legal and accounting activities; activities of head offices; management consultancy activities | 8,4 × 10⁻¹⁰ | <0,1 % |
| Manufacture of other non-metallic mineral products | 7,1 × 10⁻¹⁰ | <0,1 % |
| Accommodation and food service activities | 6,6 × 10⁻¹⁰ | <0,1 % |
| Manufacture of paper and paper products | 5,9 × 10⁻¹⁰ | <0,1 % |
| Manufacture of food products; beverages and tobacco products | 4,1 × 10⁻¹⁰ | <0,1 % |
| Repair and installation of machinery and equipment | 3,8 × 10⁻¹⁰ | <0,1 % |
| Manufacture of textiles, wearing apparel, leather and related products | 3,6 × 10⁻¹⁰ | <0,1 % |
| Repair of computers and personal and household goods | 3,1 × 10⁻¹⁰ | <0,1 % |
| Architectural and engineering activities; technical testing and analysis | 2,9 × 10⁻¹⁰ | <0,1 % |
| Human health activities | 2,9 × 10⁻¹⁰ | <0,1 % |
| Advertising and market research | 2,7 × 10⁻¹⁰ | <0,1 % |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 2,6 × 10⁻¹⁰ | <0,1 % |
| Real estate activities | 2,5 × 10⁻¹⁰ | <0,1 % |
| Travel agency, tour operator reservation service and related activities | 2,2 × 10⁻¹⁰ | <0,1 % |
| Computer programming, consultancy, and information service activities | 1,9 × 10⁻¹⁰ | <0,1 % |
| Activities of membership organisations | 1,8 × 10⁻¹⁰ | <0,1 % |
| Other personal service activities | 1,6 × 10⁻¹⁰ | <0,1 % |
| Manufacture of furniture; other manufacturing | 1,6 × 10⁻¹⁰ | <0,1 % |
| Financial service activities, except insurance and pension funding | 1,4 × 10⁻¹⁰ | <0,1 % |
| Printing and reproduction of recorded media | 1,4 × 10⁻¹⁰ | <0,1 % |
| Other professional, scientific and technical activities; veterinary activities | 1,2 × 10⁻¹⁰ | <0,1 % |
| Fishing and aquaculture | 9,9 × 10⁻¹¹ | <0,1 % |
| Telecommunications | 9,0 × 10⁻¹¹ | <0,1 % |
| Sports activities and amusement and recreation activities | 8,4 × 10⁻¹¹ | <0,1 % |
| Manufacture of basic pharmaceutical products and pharmaceutical preparations | 8,3 × 10⁻¹¹ | <0,1 % |
| Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities | 6,7 × 10⁻¹¹ | <0,1 % |
| Education | 6,7 × 10⁻¹¹ | <0,1 % |
| Motion picture, video, television programme production; programming and broadcasting activities | 4,7 × 10⁻¹¹ | <0,1 % |
| Activities auxiliary to financial services and insurance activities | 4,0 × 10⁻¹¹ | <0,1 % |
| Insurance, reinsurance and pension funding, except compulsory social security | 3,8 × 10⁻¹¹ | <0,1 % |
| Scientific research and development | 3,5 × 10⁻¹¹ | <0,1 % |
| Publishing activities | 3,2 × 10⁻¹¹ | <0,1 % |
| Residential care activities and social work activities without accommodation | 2,4 × 10⁻¹¹ | <0,1 % |
| Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use | 2,9 × 10⁻¹² | <0,1 % |
| Suma | 2,3 × 10⁻⁶ | = la cifra principal, 2,3 × 10⁻⁶ |
6 · La vía monetaria: qué países
La cifra por cada 1.000 €, según el país de la industria donde se produjo el daño.
| País | Aportación | Parte |
|---|---|---|
| Sin ubicar | 2,1 × 10⁻⁶ | 90 % |
| México | 9,2 × 10⁻⁸ | 4,0 % |
| Turquía | 2,6 × 10⁻⁸ | 1,1 % |
| Brasil | 2,0 × 10⁻⁸ | 0,84 % |
| Rusia | 1,9 × 10⁻⁸ | 0,84 % |
| Corea del Sur | 1,4 × 10⁻⁸ | 0,63 % |
| Estados Unidos | 1,4 × 10⁻⁸ | 0,60 % |
| Japón | 9,5 × 10⁻⁹ | 0,41 % |
| Alemania | 5,6 × 10⁻⁹ | 0,24 % |
| Francia | 5,5 × 10⁻⁹ | 0,24 % |
| Canadá | 5,4 × 10⁻⁹ | 0,23 % |
| India | 4,9 × 10⁻⁹ | 0,21 % |
| Italia | 3,7 × 10⁻⁹ | 0,16 % |
| Polonia | 3,3 × 10⁻⁹ | 0,14 % |
| España | 3,1 × 10⁻⁹ | 0,13 % |
| Rumanía | 1,5 × 10⁻⁹ | <0,1 % |
| Chequia | 1,3 × 10⁻⁹ | <0,1 % |
| Bulgaria | 1,2 × 10⁻⁹ | <0,1 % |
| Indonesia | 1,1 × 10⁻⁹ | <0,1 % |
| Australia | 9,8 × 10⁻¹⁰ | <0,1 % |
| Portugal | 9,7 × 10⁻¹⁰ | <0,1 % |
| Argentina | 9,5 × 10⁻¹⁰ | <0,1 % |
| Austria | 9,2 × 10⁻¹⁰ | <0,1 % |
| Hungría | 8,6 × 10⁻¹⁰ | <0,1 % |
| Eslovenia | 4,6 × 10⁻¹⁰ | <0,1 % |
| Suecia | 4,4 × 10⁻¹⁰ | <0,1 % |
| Suiza | 4,3 × 10⁻¹⁰ | <0,1 % |
| Grecia | 4,1 × 10⁻¹⁰ | <0,1 % |
| Eslovaquia | 3,6 × 10⁻¹⁰ | <0,1 % |
| Finlandia | 3,1 × 10⁻¹⁰ | <0,1 % |
| Croacia | 3,1 × 10⁻¹⁰ | <0,1 % |
| Países Bajos | 2,8 × 10⁻¹⁰ | <0,1 % |
| Bélgica | 2,8 × 10⁻¹⁰ | <0,1 % |
| Dinamarca | 2,6 × 10⁻¹⁰ | <0,1 % |
| Lituania | 2,4 × 10⁻¹⁰ | <0,1 % |
| Letonia | 2,3 × 10⁻¹⁰ | <0,1 % |
| Noruega | 2,3 × 10⁻¹⁰ | <0,1 % |
| Sudáfrica | 1,8 × 10⁻¹⁰ | <0,1 % |
| Arabia Saudí | 1,7 × 10⁻¹⁰ | <0,1 % |
| Irlanda | 1,1 × 10⁻¹⁰ | <0,1 % |
| Estonia | 9,9 × 10⁻¹¹ | <0,1 % |
| Reino Unido | 9,3 × 10⁻¹¹ | <0,1 % |
| Luxemburgo | 6,3 × 10⁻¹¹ | <0,1 % |
| Chipre | 4,8 × 10⁻¹¹ | <0,1 % |
| China | 3,7 × 10⁻¹¹ | <0,1 % |
| Malta | 1,1 × 10⁻¹¹ | <0,1 % |
| Serbia | 4,6 × 10⁻¹⁴ | <0,1 % |
| Suma | 2,3 × 10⁻⁶ | = la cifra principal, 2,3 × 10⁻⁶ |
Lo que este rastro no muestra
- Las tablas son marginales. «El cobalto lleva el 40 %» y «un país lleva el 60 %» son dos lecturas de una cifra, no un camino a través de ella: la ejecución guarda la cifra por cada dimensión, no por cada combinación de ellas.
- Un intervalo pertenece a la cifra completa. El número de un paso es su estimación central.
- Solo fase de producción. El daño derivado de usar el producto — conducir el coche, cargar el teléfono — no está en esta cifra.
Fuentes de esta cifra
- 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, ejecución 2259, metodología v1.0. https://quiescence.eu/humantoll/explain/battery-pack/