El rastro de auditoría
Cómo se construye la cifra de Teléfono inteligente
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 smartphone of 135 g, the average of 12 disassembled models from 2004 to 2015. 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 — 3,0 × 10⁻⁸ por unidad(1,2–6,3 × 10⁻⁸)BAJAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Vía monetaria — 1,4 × 10⁻⁶ por cada 1.000 € gastados en su industria(0,89–2,1 × 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 |
|---|---|---|---|---|
| Oro | 7,6 × 10⁻⁹ t | 0,0037 | 2,8 × 10⁻⁸ | 93 % |
| Cobre | 5,7 × 10⁻⁶ t | 2,0 × 10⁻⁷ | 1,1 × 10⁻⁹ | 3,7 % |
| Plata | 2,5 × 10⁻⁸ t | 2,0 × 10⁻⁵ | 4,8 × 10⁻¹⁰ | 1,6 % |
| Estaño | 5,9 × 10⁻⁷ t | 5,5 × 10⁻⁷ | 3,2 × 10⁻¹⁰ | 1,1 % |
| Tántalo | 1,9 × 10⁻⁹ t | 1,7 × 10⁻⁵ | 3,2 × 10⁻¹¹ | 0,11 % |
| Mineral de hierro | 1,0 × 10⁻⁵ t | 1,9 × 10⁻⁹ | 1,9 × 10⁻¹¹ | <0,1 % |
| Carbón y lignito | 5,4 × 10⁻⁶ t | 1,7 × 10⁻⁹ | 9,4 × 10⁻¹² | <0,1 % |
| Níquel | 1,9 × 10⁻⁷ t | 3,8 × 10⁻⁸ | 7,4 × 10⁻¹² | <0,1 % |
| Bauxita | 5,6 × 10⁻⁵ t | 1,2 × 10⁻¹⁰ | 6,7 × 10⁻¹² | <0,1 % |
| Cinc | 1,4 × 10⁻⁷ t | 1,7 × 10⁻⁸ | 2,4 × 10⁻¹² | <0,1 % |
| Suma | 3,0 × 10⁻⁸ | = la cifra principal, 3,0 × 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 |
|---|---|---|
| Sudán | 1,3 × 10⁻⁸ | 44 % |
| Burkina Faso | 9,0 × 10⁻⁹ | 30 % |
| Mali | 3,3 × 10⁻⁹ | 11 % |
| México | 2,5 × 10⁻⁹ | 8,2 % |
| República Democrática del Congo | 1,1 × 10⁻⁹ | 3,6 % |
| Colombia | 1,9 × 10⁻¹⁰ | 0,63 % |
| Myanmar (Birmania) | 1,7 × 10⁻¹⁰ | 0,57 % |
| Estados Unidos | 8,8 × 10⁻¹¹ | 0,29 % |
| Canadá | 8,6 × 10⁻¹¹ | 0,29 % |
| Uzbekistán | 7,3 × 10⁻¹¹ | 0,24 % |
| Rusia | 7,3 × 10⁻¹¹ | 0,24 % |
| Brasil | 7,0 × 10⁻¹¹ | 0,23 % |
| Papúa Nueva Guinea | 5,0 × 10⁻¹¹ | 0,17 % |
| Ucrania | 2,5 × 10⁻¹¹ | <0,1 % |
| Australia | 2,5 × 10⁻¹¹ | <0,1 % |
| Argentina | 2,3 × 10⁻¹¹ | <0,1 % |
| Nigeria | 2,2 × 10⁻¹¹ | <0,1 % |
| Ghana | 1,6 × 10⁻¹¹ | <0,1 % |
| Indonesia | 6,5 × 10⁻¹² | <0,1 % |
| Polonia | 6,5 × 10⁻¹² | <0,1 % |
| Perú | 5,0 × 10⁻¹² | <0,1 % |
| Filipinas | 3,7 × 10⁻¹² | <0,1 % |
| Turquía | 2,4 × 10⁻¹² | <0,1 % |
| Etiopía | 1,4 × 10⁻¹² | <0,1 % |
| Sudáfrica | 1,0 × 10⁻¹² | <0,1 % |
| Suecia | 9,3 × 10⁻¹³ | <0,1 % |
| India | 9,2 × 10⁻¹³ | <0,1 % |
| Mozambique | 3,4 × 10⁻¹³ | <0,1 % |
| Grecia | 2,3 × 10⁻¹³ | <0,1 % |
| Bolivia | 1,3 × 10⁻¹³ | <0,1 % |
| Guatemala | 9,0 × 10⁻¹⁴ | <0,1 % |
| Tailandia | 6,3 × 10⁻¹⁴ | <0,1 % |
| Uganda | 6,2 × 10⁻¹⁴ | <0,1 % |
| Portugal | 5,2 × 10⁻¹⁴ | <0,1 % |
| Alemania | 4,2 × 10⁻¹⁴ | <0,1 % |
| Burundi | 3,9 × 10⁻¹⁴ | <0,1 % |
| China | 3,3 × 10⁻¹⁴ | <0,1 % |
| Finlandia | 3,3 × 10⁻¹⁴ | <0,1 % |
| Mongolia | 2,9 × 10⁻¹⁴ | <0,1 % |
| Bulgaria | 2,2 × 10⁻¹⁴ | <0,1 % |
| Chequia | 1,8 × 10⁻¹⁴ | <0,1 % |
| Venezuela | 1,5 × 10⁻¹⁴ | <0,1 % |
| Pakistán | 1,5 × 10⁻¹⁴ | <0,1 % |
| Mauritania | 1,5 × 10⁻¹⁴ | <0,1 % |
| Irlanda | 1,3 × 10⁻¹⁴ | <0,1 % |
| Rumanía | 8,1 × 10⁻¹⁵ | <0,1 % |
| Níger | 6,8 × 10⁻¹⁵ | <0,1 % |
| Irán | 6,5 × 10⁻¹⁵ | <0,1 % |
| Afganistán | 5,9 × 10⁻¹⁵ | <0,1 % |
| Eslovenia | 2,7 × 10⁻¹⁵ | <0,1 % |
| Arabia Saudí | 2,7 × 10⁻¹⁵ | <0,1 % |
| Corea del Sur | 2,3 × 10⁻¹⁵ | <0,1 % |
| Hungría | 2,1 × 10⁻¹⁵ | <0,1 % |
| Japón | 1,2 × 10⁻¹⁵ | <0,1 % |
| Eslovaquia | 1,0 × 10⁻¹⁵ | <0,1 % |
| Georgia | 7,9 × 10⁻¹⁶ | <0,1 % |
| Esuatini | 1,2 × 10⁻¹⁶ | <0,1 % |
| Bangladés | 1,6 × 10⁻¹⁷ | <0,1 % |
| Noruega | 3,2 × 10⁻¹⁸ | <0,1 % |
| Armenia | 1,1 × 10⁻¹⁹ | <0,1 % |
| Suma | 3,0 × 10⁻⁸ | = la cifra principal, 3,0 × 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 | 3,0 × 10⁻⁸ | 98 % |
| Trabajo | 4,7 × 10⁻¹⁰ | 1,6 % |
| Suma | 3,0 × 10⁻⁸ | = la cifra principal, 3,0 × 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 |
|---|---|---|
| Sudan: Government | 1,1 × 10⁻⁸ | 37 % |
| Burkina Faso: Government | 6,0 × 10⁻⁹ | 20 % |
| RSF - Civilians | 1,6 × 10⁻⁹ | 5,2 % |
| Mali: Government | 1,4 × 10⁻⁹ | 4,8 % |
| Burkina Faso: Islamic State | 1,2 × 10⁻⁹ | 4,1 % |
| Jalisco Cartel New Generation - Sinaloa Cartel | 1,2 × 10⁻⁹ | 4,0 % |
| JNIM - Civilians | 1,2 × 10⁻⁹ | 4,0 % |
| IS - Civilians | 6,6 × 10⁻¹⁰ | 2,2 % |
| IS - JNIM | 5,8 × 10⁻¹⁰ | 1,9 % |
| Sin ubicar | 4,7 × 10⁻¹⁰ | 1,6 % |
| Government of Burkina Faso - Civilians | 4,5 × 10⁻¹⁰ | 1,5 % |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 3,6 × 10⁻¹⁰ | 1,2 % |
| Juarez Cartel - Sinaloa Cartel | 3,2 × 10⁻¹⁰ | 1,1 % |
| Government of Mali - Civilians | 3,0 × 10⁻¹⁰ | 0,99 % |
| Mali: Islamic State | 3,0 × 10⁻¹⁰ | 0,99 % |
| Mali: Government/Azawad | 2,5 × 10⁻¹⁰ | 0,82 % |
| Carteles Unidos - Jalisco Cartel New Generation | 2,4 × 10⁻¹⁰ | 0,81 % |
| URDPC - Civilians | 1,9 × 10⁻¹⁰ | 0,63 % |
| Beni Halba Baggara - Salamat Baggara | 1,7 × 10⁻¹⁰ | 0,57 % |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 1,4 × 10⁻¹⁰ | 0,46 % |
| Lengola - Mbole | 1,2 × 10⁻¹⁰ | 0,41 % |
| Dan na Ambassagou - JNIM | 1,2 × 10⁻¹⁰ | 0,41 % |
| Habaniya - Salamat Baggara | 1,2 × 10⁻¹⁰ | 0,40 % |
| Myanmar (Burma): Government | 9,5 × 10⁻¹¹ | 0,32 % |
| DR Congo (Zaire): Islamic State | 8,6 × 10⁻¹¹ | 0,29 % |
| Arab - Gimir | 8,6 × 10⁻¹¹ | 0,29 % |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 6,1 × 10⁻¹¹ | 0,20 % |
| M23 - VDP | 5,4 × 10⁻¹¹ | 0,18 % |
| Mobondo - Civilians | 5,2 × 10⁻¹¹ | 0,17 % |
| Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin | 4,9 × 10⁻¹¹ | 0,16 % |
| DR Congo (Zaire): Government | 4,2 × 10⁻¹¹ | 0,14 % |
| M23 - Civilians | 4,1 × 10⁻¹¹ | 0,14 % |
| Colombia: Government | 3,8 × 10⁻¹¹ | 0,13 % |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 3,8 × 10⁻¹¹ | 0,13 % |
| Twic Dinka - Ngok Dinka | 3,7 × 10⁻¹¹ | 0,12 % |
| Rwanda: Government | 3,7 × 10⁻¹¹ | 0,12 % |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 3,5 × 10⁻¹¹ | 0,12 % |
| Government of DR Congo (Zaire) - Civilians | 3,4 × 10⁻¹¹ | 0,11 % |
| Dozos (Mali) - JNIM | 3,4 × 10⁻¹¹ | 0,11 % |
| Government of Myanmar (Burma) - Civilians | 3,3 × 10⁻¹¹ | 0,11 % |
| Russia - Ukraine | 2,8 × 10⁻¹¹ | <0,1 % |
| Arab - Masalit | 2,7 × 10⁻¹¹ | <0,1 % |
| Los Ardillos - Los Tlacos | 2,6 × 10⁻¹¹ | <0,1 % |
| Government of Rwanda - Civilians | 2,0 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - PCC | 2,0 × 10⁻¹¹ | <0,1 % |
| Dozos (Mali) - Civilians | 1,9 × 10⁻¹¹ | <0,1 % |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 1,9 × 10⁻¹¹ | <0,1 % |
| EGC - Civilians | 1,8 × 10⁻¹¹ | <0,1 % |
| URDPC - Zaire self-defense group | 1,7 × 10⁻¹¹ | <0,1 % |
| Hausa - Nuba | 1,7 × 10⁻¹¹ | <0,1 % |
| Myanmar (Burma): Kachin | 1,6 × 10⁻¹¹ | <0,1 % |
| Kusasi - Mamprusi | 1,6 × 10⁻¹¹ | <0,1 % |
| Zaire self-defense group - Civilians | 1,5 × 10⁻¹¹ | <0,1 % |
| VDP - Civilians | 1,4 × 10⁻¹¹ | <0,1 % |
| Dan na Ambassagou - Civilians | 1,2 × 10⁻¹¹ | <0,1 % |
| FPIC Chambre noire sanduku - URDPC | 1,1 × 10⁻¹¹ | <0,1 % |
| FPIC Chambre noire sanduku - Civilians | 1,1 × 10⁻¹¹ | <0,1 % |
| Myanmar (Burma): Karen | 1,1 × 10⁻¹¹ | <0,1 % |
| FARC-EMC - Civilians | 9,4 × 10⁻¹² | <0,1 % |
| Nigeria: Islamic State | 8,8 × 10⁻¹² | <0,1 % |
| GATIA - IS | 8,7 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Karenni | 8,4 × 10⁻¹² | <0,1 % |
| AFC - Civilians | 8,0 × 10⁻¹² | <0,1 % |
| AFP-Gutabara - CNPSC, FABB | 7,5 × 10⁻¹² | <0,1 % |
| Bonde do Maluco - Comando Vermelho | 7,2 × 10⁻¹² | <0,1 % |
| Hawazma - Nuba | 6,8 × 10⁻¹² | <0,1 % |
| Cartel do Norte - Comando Vermelho | 6,6 × 10⁻¹² | <0,1 % |
| Russia (Soviet Union): Government | 6,2 × 10⁻¹² | <0,1 % |
| Hausa - Funj | 6,1 × 10⁻¹² | <0,1 % |
| FARC-EMC - ELN | 6,1 × 10⁻¹² | <0,1 % |
| Government of Sudan - Civilians | 5,4 × 10⁻¹² | <0,1 % |
| Los Rusos, UPOEG - Los Tlacos | 5,4 × 10⁻¹² | <0,1 % |
| Peru: Government | 5,0 × 10⁻¹² | <0,1 % |
| Jalisco Cartel New Generation - Civilians | 4,8 × 10⁻¹² | <0,1 % |
| Bonde dos 40 - PCC | 4,7 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Arakan | 4,5 × 10⁻¹² | <0,1 % |
| Jalisco Cartel New Generation - Pájaros Sierra | 4,5 × 10⁻¹² | <0,1 % |
| IS - MSA | 4,4 × 10⁻¹² | <0,1 % |
| Indonesia: West Papua | 4,1 × 10⁻¹² | <0,1 % |
| FARC - Segunda Marquetalia - Civilians | 4,0 × 10⁻¹² | <0,1 % |
| ELN - Civilians | 3,8 × 10⁻¹² | <0,1 % |
| Government of Mexico - Civilians | 3,7 × 10⁻¹² | <0,1 % |
| Comando Vermelho - GDE | 3,5 × 10⁻¹² | <0,1 % |
| Nova Okaida - Estados Unidos | 3,5 × 10⁻¹² | <0,1 % |
| GDE, PCC - Sindicato do Crime | 3,5 × 10⁻¹² | <0,1 % |
| Los Ardillos - Los Rojos | 3,2 × 10⁻¹² | <0,1 % |
| Los Costenos - Los Pepes | 3,2 × 10⁻¹² | <0,1 % |
| EGC - ELN, FARC-EMC | 3,1 × 10⁻¹² | <0,1 % |
| PCC - Sindicato do Crime | 3,1 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 3,0 × 10⁻¹² | <0,1 % |
| Amigos Para Sempre - Família Terror Amapá | 3,0 × 10⁻¹² | <0,1 % |
| EGC - ELN | 3,0 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Kokang | 2,7 × 10⁻¹² | <0,1 % |
| AFP-Gutabara - FABB | 2,7 × 10⁻¹² | <0,1 % |
| Comando Vermelho - Civilians | 2,5 × 10⁻¹² | <0,1 % |
| Philippines: Government | 2,3 × 10⁻¹² | <0,1 % |
| FRPI - Civilians | 2,2 × 10⁻¹² | <0,1 % |
| IS - JAS | 2,1 × 10⁻¹² | <0,1 % |
| Bonde dos 13, PCC - Comando Vermelho | 2,0 × 10⁻¹² | <0,1 % |
| OPM - Civilians | 1,9 × 10⁻¹² | <0,1 % |
| Bonde dos 40 - Comando Vermelho | 1,8 × 10⁻¹² | <0,1 % |
| Burundi: Government | 1,8 × 10⁻¹² | <0,1 % |
| Basonge - Bena Nkoma (Bakwa Luntu, Luba) | 1,5 × 10⁻¹² | <0,1 % |
| Misseriya - Ngok Dinka | 1,4 × 10⁻¹² | <0,1 % |
| EGC - Autodefensas Conquistadoras de la Sierra Nevada | 1,3 × 10⁻¹² | <0,1 % |
| Comando Vermelho - Holanda | 1,3 × 10⁻¹² | <0,1 % |
| FDLR-FOCA - Civilians | 1,2 × 10⁻¹² | <0,1 % |
| FPIC Chambre noire sanduku - FRPI | 1,2 × 10⁻¹² | <0,1 % |
| Fulani - Mwaghavul | 1,2 × 10⁻¹² | <0,1 % |
| Fulani - Mwaghavul , Ron | 1,1 × 10⁻¹² | <0,1 % |
| Philippines: Islamic State | 1,1 × 10⁻¹² | <0,1 % |
| Nigeria: Government | 1,1 × 10⁻¹² | <0,1 % |
| Fulani - Tiv | 1,1 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Sinaloa Cartel | 1,1 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Jalisco Cartel New Generation | 1,1 × 10⁻¹² | <0,1 % |
| Government of Colombia - Civilians | 1,1 × 10⁻¹² | <0,1 % |
| Mayi Mayi Chini ya Tuna - Civilians | 9,9 × 10⁻¹³ | <0,1 % |
| Comando Vermelho - Massa | 9,8 × 10⁻¹³ | <0,1 % |
| Nova Okaida - PCC | 9,5 × 10⁻¹³ | <0,1 % |
| Farmers (Nigeria) - Herders (Nigeria) | 9,2 × 10⁻¹³ | <0,1 % |
| Bonde do Maluco - Katiara | 9,0 × 10⁻¹³ | <0,1 % |
| Bonde do Maluco - Civilians | 9,0 × 10⁻¹³ | <0,1 % |
| NUG - Civilians | 8,4 × 10⁻¹³ | <0,1 % |
| South Sudan: Government | 7,5 × 10⁻¹³ | <0,1 % |
| Luba - Batwa | 7,5 × 10⁻¹³ | <0,1 % |
| Government of Papua New Guinea - Civilians | 7,4 × 10⁻¹³ | <0,1 % |
| Ethiopia: Government/Amhara | 7,2 × 10⁻¹³ | <0,1 % |
| Bonde dos 40 - Civilians | 7,0 × 10⁻¹³ | <0,1 % |
| Comando Vermelho - Terceiro Comando Puro | 6,7 × 10⁻¹³ | <0,1 % |
| Nigeria: Biafra | 6,6 × 10⁻¹³ | <0,1 % |
| CATA - Codeta | 6,3 × 10⁻¹³ | <0,1 % |
| PCC - Civilians | 5,1 × 10⁻¹³ | <0,1 % |
| Birom - Fulani | 4,9 × 10⁻¹³ | <0,1 % |
| Government of Indonesia - Civilians | 4,8 × 10⁻¹³ | <0,1 % |
| Comandos de la Frontera - Civilians | 4,8 × 10⁻¹³ | <0,1 % |
| Ajeita - Bonde do Maluco | 4,5 × 10⁻¹³ | <0,1 % |
| Atyap - Fulani | 4,2 × 10⁻¹³ | <0,1 % |
| Government of South Africa - Civilians | 4,2 × 10⁻¹³ | <0,1 % |
| Karimjo - Wurukum | 4,0 × 10⁻¹³ | <0,1 % |
| Black Axe - Eyie | 3,7 × 10⁻¹³ | <0,1 % |
| Autodefensas Conquistadoras de la Sierra Nevada - Civilians | 3,6 × 10⁻¹³ | <0,1 % |
| Government of Brazil - Civilians | 3,4 × 10⁻¹³ | <0,1 % |
| Forces of Terwase Akwanza - Civilians | 3,3 × 10⁻¹³ | <0,1 % |
| Russia: Islamic State | 3,2 × 10⁻¹³ | <0,1 % |
| Anti-Bala - Bala na Cara | 3,1 × 10⁻¹³ | <0,1 % |
| Fulani - Idoma | 3,1 × 10⁻¹³ | <0,1 % |
| Fulani - Kuteb | 2,9 × 10⁻¹³ | <0,1 % |
| Bonde dos 40 - PCM | 2,8 × 10⁻¹³ | <0,1 % |
| India: Kashmir | 2,7 × 10⁻¹³ | <0,1 % |
| Ethiopia: Oromiya | 2,6 × 10⁻¹³ | <0,1 % |
| Government of Burundi - Civilians | 2,6 × 10⁻¹³ | <0,1 % |
| DR Congo (Zaire): Katanga | 2,5 × 10⁻¹³ | <0,1 % |
| Government of Uganda - Civilians | 2,5 × 10⁻¹³ | <0,1 % |
| Twiganeho - Civilians | 2,5 × 10⁻¹³ | <0,1 % |
| AFC - VDP | 2,5 × 10⁻¹³ | <0,1 % |
| Los Costenos - Civilians | 2,4 × 10⁻¹³ | <0,1 % |
| Kuki - Meitei | 2,3 × 10⁻¹³ | <0,1 % |
| CPP - Civilians | 2,2 × 10⁻¹³ | <0,1 % |
| India: Government | 2,2 × 10⁻¹³ | <0,1 % |
| Mozambique: Islamic State | 2,2 × 10⁻¹³ | <0,1 % |
| Government of Nigeria - Civilians | 2,0 × 10⁻¹³ | <0,1 % |
| JAS - Civilians | 1,9 × 10⁻¹³ | <0,1 % |
| Guerreros Unidos - Los Tlacos | 1,8 × 10⁻¹³ | <0,1 % |
| Chain Guys - Full Force | 1,7 × 10⁻¹³ | <0,1 % |
| Government of Russia (Soviet Union) - Civilians | 1,6 × 10⁻¹³ | <0,1 % |
| Russia (Soviet Union): Chechnya | 1,3 × 10⁻¹³ | <0,1 % |
| Myanmar (Burma): Shan | 1,1 × 10⁻¹³ | <0,1 % |
| Turkey: Kurdistan | 1,1 × 10⁻¹³ | <0,1 % |
| Government of Ethiopia - Civilians | 1,1 × 10⁻¹³ | <0,1 % |
| CPI-Maoist - Civilians | 9,7 × 10⁻¹⁴ | <0,1 % |
| Hausa - Fulani | 9,6 × 10⁻¹⁴ | <0,1 % |
| OLA - Civilians | 8,4 × 10⁻¹⁴ | <0,1 % |
| Fano - Civilians | 7,5 × 10⁻¹⁴ | <0,1 % |
| Anuak - Nuer | 7,3 × 10⁻¹⁴ | <0,1 % |
| Fulani - Irigwe | 6,8 × 10⁻¹⁴ | <0,1 % |
| Fulani - Igala | 5,7 × 10⁻¹⁴ | <0,1 % |
| ARSA - Civilians | 5,6 × 10⁻¹⁴ | <0,1 % |
| M18 - MS-13 | 5,4 × 10⁻¹⁴ | <0,1 % |
| Greenlanders - NDV | 5,1 × 10⁻¹⁴ | <0,1 % |
| Black Axe - Maphite | 5,1 × 10⁻¹⁴ | <0,1 % |
| Kashmir insurgents - Civilians | 4,3 × 10⁻¹⁴ | <0,1 % |
| IS - Naparama | 3,7 × 10⁻¹⁴ | <0,1 % |
| Supporters of APC - Supporters of PDP | 3,4 × 10⁻¹⁴ | <0,1 % |
| Black Axe - SVC | 2,8 × 10⁻¹⁴ | <0,1 % |
| IPOB - Civilians | 2,8 × 10⁻¹⁴ | <0,1 % |
| Amigos dos Amigos - Comando Vermelho | 2,8 × 10⁻¹⁴ | <0,1 % |
| FDN - PCC | 2,8 × 10⁻¹⁴ | <0,1 % |
| Philippines: Mindanao | 2,8 × 10⁻¹⁴ | <0,1 % |
| Government of Philippines - Civilians | 2,8 × 10⁻¹⁴ | <0,1 % |
| Agatu - Fulani | 2,3 × 10⁻¹⁴ | <0,1 % |
| IS - Yan Gora | 2,3 × 10⁻¹⁴ | <0,1 % |
| Deebam - NDV | 2,3 × 10⁻¹⁴ | <0,1 % |
| MS-13 - Civilians | 1,9 × 10⁻¹⁴ | <0,1 % |
| Amhara - Oromo | 1,9 × 10⁻¹⁴ | <0,1 % |
| Hindus (India) - Muslims (India) | 1,8 × 10⁻¹⁴ | <0,1 % |
| Uganda: Islamic State | 1,7 × 10⁻¹⁴ | <0,1 % |
| Government of Mozambique - Civilians | 1,6 × 10⁻¹⁴ | <0,1 % |
| Government of India - Civilians | 1,6 × 10⁻¹⁴ | <0,1 % |
| M18 - Civilians | 1,6 × 10⁻¹⁴ | <0,1 % |
| Mauritania: Government | 1,5 × 10⁻¹⁴ | <0,1 % |
| Government of Venezuela - Civilians | 1,2 × 10⁻¹⁴ | <0,1 % |
| Jukun - Tiv | 1,1 × 10⁻¹⁴ | <0,1 % |
| Pakistan: Government | 1,1 × 10⁻¹⁴ | <0,1 % |
| India: Western South East Asia | 9,0 × 10⁻¹⁵ | <0,1 % |
| Guraghe - Mareqo | 8,6 × 10⁻¹⁵ | <0,1 % |
| Murle - Nuer | 5,7 × 10⁻¹⁵ | <0,1 % |
| Cameroon: Ambazonia | 5,7 × 10⁻¹⁵ | <0,1 % |
| Ambazonia insurgents - Civilians | 5,7 × 10⁻¹⁵ | <0,1 % |
| Iran: Government | 5,4 × 10⁻¹⁵ | <0,1 % |
| VHP - Civilians | 4,5 × 10⁻¹⁵ | <0,1 % |
| Somalia: Government | 3,4 × 10⁻¹⁵ | <0,1 % |
| Thailand: Patani | 3,1 × 10⁻¹⁵ | <0,1 % |
| Niger: Islamic State | 3,1 × 10⁻¹⁵ | <0,1 % |
| Yemen (North Yemen): Government | 2,7 × 10⁻¹⁵ | <0,1 % |
| Afghanistan: Islamic State | 2,7 × 10⁻¹⁵ | <0,1 % |
| India - Pakistan | 2,3 × 10⁻¹⁵ | <0,1 % |
| India: Nagaland | 2,3 × 10⁻¹⁵ | <0,1 % |
| NSCN-IM - Civilians | 2,3 × 10⁻¹⁵ | <0,1 % |
| PLFI - Civilians | 2,3 × 10⁻¹⁵ | <0,1 % |
| PKK - Civilians | 2,1 × 10⁻¹⁵ | <0,1 % |
| Amhara - Gumuz | 1,7 × 10⁻¹⁵ | <0,1 % |
| Pakistan: Balochistan | 1,4 × 10⁻¹⁵ | <0,1 % |
| Pakistan: Islamic State | 1,1 × 10⁻¹⁵ | <0,1 % |
| Afghanistan: Government | 9,4 × 10⁻¹⁶ | <0,1 % |
| Government of Afghanistan - Civilians | 7,1 × 10⁻¹⁶ | <0,1 % |
| Iran: Islamic State | 6,1 × 10⁻¹⁶ | <0,1 % |
| Niger: Government | 5,9 × 10⁻¹⁶ | <0,1 % |
| Government of Iran - Civilians | 4,5 × 10⁻¹⁶ | <0,1 % |
| Shia (Pakistan) - Sunni (Pakistan) | 3,7 × 10⁻¹⁶ | <0,1 % |
| Djerma (Zherma) - Fulani | 3,4 × 10⁻¹⁶ | <0,1 % |
| RED-TABARA - Civilians | 3,1 × 10⁻¹⁶ | <0,1 % |
| Afghanistan - Pakistan | 2,7 × 10⁻¹⁶ | <0,1 % |
| BRAS - Civilians | 1,5 × 10⁻¹⁶ | <0,1 % |
| Government of eSwatini (Swaziland) - Civilians | 1,2 × 10⁻¹⁶ | <0,1 % |
| Patani insurgents - Civilians | 1,0 × 10⁻¹⁶ | <0,1 % |
| TTP - Civilians | 8,9 × 10⁻¹⁷ | <0,1 % |
| Government of Pakistan - Civilians | 8,0 × 10⁻¹⁷ | <0,1 % |
| LeJ - Civilians | 1,3 × 10⁻¹⁷ | <0,1 % |
| Supporters of Awami League - Supporters of BNP | 2,7 × 10⁻¹⁸ | <0,1 % |
| Supporters of Awami League - Supporters of Jamaat-e-Islami | 1,3 × 10⁻¹⁸ | <0,1 % |
| Azerbaijan: Artsakh (Nagorno-Karabakh) | 1,1 × 10⁻¹⁹ | <0,1 % |
| Suma | 3,0 × 10⁻⁸ | = la cifra principal, 3,0 × 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 | 8,4 × 10⁻⁷ | 59 % |
| Manufacture of basic metals | 2,0 × 10⁻⁷ | 14 % |
| Water transport | 7,3 × 10⁻⁸ | 5,2 % |
| Land transport and transport via pipelines | 5,6 × 10⁻⁸ | 4,0 % |
| Air transport | 4,5 × 10⁻⁸ | 3,2 % |
| Manufacture of computer, electronic and optical products | 4,4 × 10⁻⁸ | 3,2 % |
| Crop and animal production, hunting and related service activities | 4,2 × 10⁻⁸ | 3,0 % |
| Warehousing and support activities for transportation | 3,1 × 10⁻⁸ | 2,2 % |
| Forestry and logging | 1,8 × 10⁻⁸ | 1,3 % |
| Wholesale trade, except of motor vehicles and motorcycles | 1,7 × 10⁻⁸ | 1,2 % |
| Postal and courier activities | 6,1 × 10⁻⁹ | 0,43 % |
| Manufacture of fabricated metal products, except machinery and equipment | 5,6 × 10⁻⁹ | 0,40 % |
| Retail trade, except of motor vehicles and motorcycles | 4,8 × 10⁻⁹ | 0,34 % |
| Water collection, treatment and supply | 3,0 × 10⁻⁹ | 0,21 % |
| Manufacture of other transport equipment | 2,9 × 10⁻⁹ | 0,21 % |
| Construction | 2,2 × 10⁻⁹ | 0,16 % |
| Manufacture of coke and refined petroleum products | 2,0 × 10⁻⁹ | 0,14 % |
| Manufacture of chemicals and chemical products | 2,0 × 10⁻⁹ | 0,14 % |
| Rental and leasing activities | 2,0 × 10⁻⁹ | 0,14 % |
| Public administration and defence; compulsory social security | 1,8 × 10⁻⁹ | 0,13 % |
| Security and investigation, service and landscape, office administrative and support activities | 1,7 × 10⁻⁹ | 0,12 % |
| Manufacture of electrical equipment | 1,5 × 10⁻⁹ | 0,10 % |
| Employment activities | 1,4 × 10⁻⁹ | <0,1 % |
| Electricity, gas, steam and air conditioning supply | 1,2 × 10⁻⁹ | <0,1 % |
| Sewerage, waste management, remediation activities | 1,1 × 10⁻⁹ | <0,1 % |
| Manufacture of rubber and plastic products | 1,0 × 10⁻⁹ | <0,1 % |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 8,7 × 10⁻¹⁰ | <0,1 % |
| Legal and accounting activities; activities of head offices; management consultancy activities | 7,7 × 10⁻¹⁰ | <0,1 % |
| Manufacture of machinery and equipment n.e.c. | 7,2 × 10⁻¹⁰ | <0,1 % |
| Manufacture of other non-metallic mineral products | 5,7 × 10⁻¹⁰ | <0,1 % |
| Accommodation and food service activities | 5,5 × 10⁻¹⁰ | <0,1 % |
| Manufacture of motor vehicles, trailers and semi-trailers | 4,6 × 10⁻¹⁰ | <0,1 % |
| Human health activities | 3,8 × 10⁻¹⁰ | <0,1 % |
| Manufacture of paper and paper products | 3,7 × 10⁻¹⁰ | <0,1 % |
| Repair of computers and personal and household goods | 3,3 × 10⁻¹⁰ | <0,1 % |
| Manufacture of food products; beverages and tobacco products | 3,1 × 10⁻¹⁰ | <0,1 % |
| Manufacture of textiles, wearing apparel, leather and related products | 3,0 × 10⁻¹⁰ | <0,1 % |
| Architectural and engineering activities; technical testing and analysis | 2,6 × 10⁻¹⁰ | <0,1 % |
| Repair and installation of machinery and equipment | 2,5 × 10⁻¹⁰ | <0,1 % |
| Real estate activities | 2,3 × 10⁻¹⁰ | <0,1 % |
| Computer programming, consultancy, and information service activities | 2,0 × 10⁻¹⁰ | <0,1 % |
| Travel agency, tour operator reservation service and related activities | 2,0 × 10⁻¹⁰ | <0,1 % |
| Activities of membership organisations | 1,7 × 10⁻¹⁰ | <0,1 % |
| Other personal service activities | 1,7 × 10⁻¹⁰ | <0,1 % |
| Advertising and market research | 1,6 × 10⁻¹⁰ | <0,1 % |
| Financial service activities, except insurance and pension funding | 1,5 × 10⁻¹⁰ | <0,1 % |
| Manufacture of furniture; other manufacturing | 1,5 × 10⁻¹⁰ | <0,1 % |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 1,1 × 10⁻¹⁰ | <0,1 % |
| Printing and reproduction of recorded media | 1,0 × 10⁻¹⁰ | <0,1 % |
| Telecommunications | 9,6 × 10⁻¹¹ | <0,1 % |
| Fishing and aquaculture | 9,5 × 10⁻¹¹ | <0,1 % |
| Other professional, scientific and technical activities; veterinary activities | 9,4 × 10⁻¹¹ | <0,1 % |
| Sports activities and amusement and recreation activities | 7,7 × 10⁻¹¹ | <0,1 % |
| Manufacture of basic pharmaceutical products and pharmaceutical preparations | 6,8 × 10⁻¹¹ | <0,1 % |
| Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities | 6,2 × 10⁻¹¹ | <0,1 % |
| Education | 5,8 × 10⁻¹¹ | <0,1 % |
| Scientific research and development | 5,6 × 10⁻¹¹ | <0,1 % |
| Motion picture, video, television programme production; programming and broadcasting activities | 4,3 × 10⁻¹¹ | <0,1 % |
| Insurance, reinsurance and pension funding, except compulsory social security | 3,9 × 10⁻¹¹ | <0,1 % |
| Publishing activities | 3,7 × 10⁻¹¹ | <0,1 % |
| Activities auxiliary to financial services and insurance activities | 3,3 × 10⁻¹¹ | <0,1 % |
| Residential care activities and social work activities without accommodation | 2,2 × 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 | 1,4 × 10⁻⁶ | = la cifra principal, 1,4 × 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 | 1,3 × 10⁻⁶ | 91 % |
| México | 4,1 × 10⁻⁸ | 2,9 % |
| Corea del Sur | 1,9 × 10⁻⁸ | 1,3 % |
| Estados Unidos | 1,3 × 10⁻⁸ | 0,91 % |
| Rusia | 1,2 × 10⁻⁸ | 0,83 % |
| Brasil | 9,0 × 10⁻⁹ | 0,63 % |
| Japón | 7,0 × 10⁻⁹ | 0,50 % |
| Turquía | 6,8 × 10⁻⁹ | 0,48 % |
| Francia | 4,0 × 10⁻⁹ | 0,28 % |
| Alemania | 3,0 × 10⁻⁹ | 0,21 % |
| Canadá | 2,7 × 10⁻⁹ | 0,19 % |
| Italia | 1,6 × 10⁻⁹ | 0,11 % |
| India | 1,1 × 10⁻⁹ | <0,1 % |
| Polonia | 1,1 × 10⁻⁹ | <0,1 % |
| España | 8,4 × 10⁻¹⁰ | <0,1 % |
| Suiza | 7,1 × 10⁻¹⁰ | <0,1 % |
| Indonesia | 6,1 × 10⁻¹⁰ | <0,1 % |
| Argentina | 6,0 × 10⁻¹⁰ | <0,1 % |
| Australia | 5,9 × 10⁻¹⁰ | <0,1 % |
| Chequia | 5,7 × 10⁻¹⁰ | <0,1 % |
| Portugal | 5,5 × 10⁻¹⁰ | <0,1 % |
| Rumanía | 4,6 × 10⁻¹⁰ | <0,1 % |
| Austria | 4,4 × 10⁻¹⁰ | <0,1 % |
| Hungría | 4,2 × 10⁻¹⁰ | <0,1 % |
| Bulgaria | 3,9 × 10⁻¹⁰ | <0,1 % |
| Suecia | 2,4 × 10⁻¹⁰ | <0,1 % |
| Irlanda | 2,3 × 10⁻¹⁰ | <0,1 % |
| Dinamarca | 2,3 × 10⁻¹⁰ | <0,1 % |
| Finlandia | 2,1 × 10⁻¹⁰ | <0,1 % |
| Países Bajos | 2,1 × 10⁻¹⁰ | <0,1 % |
| Grecia | 2,0 × 10⁻¹⁰ | <0,1 % |
| Letonia | 2,0 × 10⁻¹⁰ | <0,1 % |
| Lituania | 1,9 × 10⁻¹⁰ | <0,1 % |
| Bélgica | 1,9 × 10⁻¹⁰ | <0,1 % |
| Noruega | 1,6 × 10⁻¹⁰ | <0,1 % |
| Eslovaquia | 1,3 × 10⁻¹⁰ | <0,1 % |
| Eslovenia | 1,0 × 10⁻¹⁰ | <0,1 % |
| Arabia Saudí | 9,9 × 10⁻¹¹ | <0,1 % |
| Croacia | 9,0 × 10⁻¹¹ | <0,1 % |
| Estonia | 6,9 × 10⁻¹¹ | <0,1 % |
| Sudáfrica | 6,5 × 10⁻¹¹ | <0,1 % |
| Luxemburgo | 5,3 × 10⁻¹¹ | <0,1 % |
| Reino Unido | 5,1 × 10⁻¹¹ | <0,1 % |
| Chipre | 2,8 × 10⁻¹¹ | <0,1 % |
| China | 2,4 × 10⁻¹¹ | <0,1 % |
| Malta | 1,9 × 10⁻¹¹ | <0,1 % |
| Serbia | 1,7 × 10⁻¹⁴ | <0,1 % |
| Suma | 1,4 × 10⁻⁶ | = la cifra principal, 1,4 × 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/smartphone/