El rastro de auditoría
Cómo se construye la cifra de Mantequilla
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 butter from cow's milk. 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 — 3,2 × 10⁻⁷ por unidad(1,3–7,2 × 10⁻⁷)BAJAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Vía monetaria — 3,4 × 10⁻⁶ por cada 1.000 € gastados en su industria(2,3–5,1 × 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 |
|---|---|---|---|---|
| Leche | 0,022 t | 1,5 × 10⁻⁸ | 3,2 × 10⁻⁷ | 100 % |
| Suma | 3,2 × 10⁻⁷ | = la cifra principal, 3,2 × 10⁻⁷ | ||
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 |
|---|---|---|
| Ucrania | 8,5 × 10⁻⁸ | 27 % |
| Israel | 4,5 × 10⁻⁸ | 14 % |
| Sudán | 4,2 × 10⁻⁸ | 13 % |
| Somalia | 4,2 × 10⁻⁸ | 13 % |
| México | 1,2 × 10⁻⁸ | 3,9 % |
| Pakistán | 8,7 × 10⁻⁹ | 2,8 % |
| Turquía | 7,2 × 10⁻⁹ | 2,3 % |
| Siria | 7,0 × 10⁻⁹ | 2,2 % |
| Etiopía | 6,8 × 10⁻⁹ | 2,2 % |
| Francia | 4,6 × 10⁻⁹ | 1,5 % |
| Níger | 4,2 × 10⁻⁹ | 1,3 % |
| Burkina Faso | 4,2 × 10⁻⁹ | 1,3 % |
| Estados Unidos | 4,2 × 10⁻⁹ | 1,3 % |
| Mali | 3,9 × 10⁻⁹ | 1,2 % |
| Yemen | 2,8 × 10⁻⁹ | 0,89 % |
| Italia | 2,8 × 10⁻⁹ | 0,89 % |
| Myanmar (Birmania) | 2,7 × 10⁻⁹ | 0,86 % |
| Japón | 2,3 × 10⁻⁹ | 0,74 % |
| Afganistán | 2,3 × 10⁻⁹ | 0,71 % |
| Alemania | 2,1 × 10⁻⁹ | 0,66 % |
| Brasil | 2,0 × 10⁻⁹ | 0,64 % |
| India | 1,9 × 10⁻⁹ | 0,60 % |
| Kenia | 1,8 × 10⁻⁹ | 0,58 % |
| Colombia | 1,4 × 10⁻⁹ | 0,45 % |
| Sudán del Sur | 1,4 × 10⁻⁹ | 0,44 % |
| España | 1,1 × 10⁻⁹ | 0,36 % |
| Rusia | 9,7 × 10⁻¹⁰ | 0,31 % |
| Corea del Sur | 8,3 × 10⁻¹⁰ | 0,26 % |
| Haití | 7,4 × 10⁻¹⁰ | 0,23 % |
| Portugal | 6,5 × 10⁻¹⁰ | 0,21 % |
| Rumanía | 5,9 × 10⁻¹⁰ | 0,19 % |
| Austria | 5,5 × 10⁻¹⁰ | 0,18 % |
| Ecuador | 5,0 × 10⁻¹⁰ | 0,16 % |
| Bielorrusia | 4,8 × 10⁻¹⁰ | 0,15 % |
| Uzbekistán | 4,8 × 10⁻¹⁰ | 0,15 % |
| Polonia | 4,6 × 10⁻¹⁰ | 0,15 % |
| Argentina | 4,5 × 10⁻¹⁰ | 0,14 % |
| Canadá | 3,9 × 10⁻¹⁰ | 0,12 % |
| Suiza | 3,7 × 10⁻¹⁰ | 0,12 % |
| Uganda | 3,7 × 10⁻¹⁰ | 0,12 % |
| Irlanda | 3,6 × 10⁻¹⁰ | 0,12 % |
| Nigeria | 3,5 × 10⁻¹⁰ | 0,11 % |
| Azerbaiyán | 3,5 × 10⁻¹⁰ | 0,11 % |
| Líbano | 3,3 × 10⁻¹⁰ | 0,11 % |
| Honduras | 2,9 × 10⁻¹⁰ | <0,1 % |
| Camerún | 2,8 × 10⁻¹⁰ | <0,1 % |
| Georgia | 2,6 × 10⁻¹⁰ | <0,1 % |
| Chequia | 2,6 × 10⁻¹⁰ | <0,1 % |
| Grecia | 2,4 × 10⁻¹⁰ | <0,1 % |
| República Centroafricana | 2,2 × 10⁻¹⁰ | <0,1 % |
| Bélgica | 2,2 × 10⁻¹⁰ | <0,1 % |
| Dinamarca | 1,9 × 10⁻¹⁰ | <0,1 % |
| Tailandia | 1,8 × 10⁻¹⁰ | <0,1 % |
| Burundi | 1,7 × 10⁻¹⁰ | <0,1 % |
| Luxemburgo | 1,6 × 10⁻¹⁰ | <0,1 % |
| Países Bajos | 1,6 × 10⁻¹⁰ | <0,1 % |
| Hungría | 1,5 × 10⁻¹⁰ | <0,1 % |
| Chipre | 1,4 × 10⁻¹⁰ | <0,1 % |
| Australia | 1,4 × 10⁻¹⁰ | <0,1 % |
| Lituania | 1,3 × 10⁻¹⁰ | <0,1 % |
| Armenia | 1,1 × 10⁻¹⁰ | <0,1 % |
| Bulgaria | 1,1 × 10⁻¹⁰ | <0,1 % |
| Suecia | 1,0 × 10⁻¹⁰ | <0,1 % |
| Croacia | 9,5 × 10⁻¹¹ | <0,1 % |
| Eslovaquia | 8,4 × 10⁻¹¹ | <0,1 % |
| Eslovenia | 8,4 × 10⁻¹¹ | <0,1 % |
| Letonia | 8,3 × 10⁻¹¹ | <0,1 % |
| Costa Rica | 8,3 × 10⁻¹¹ | <0,1 % |
| Sri Lanka | 8,2 × 10⁻¹¹ | <0,1 % |
| Chad | 7,8 × 10⁻¹¹ | <0,1 % |
| Finlandia | 7,5 × 10⁻¹¹ | <0,1 % |
| Moldavia | 5,8 × 10⁻¹¹ | <0,1 % |
| Estonia | 5,6 × 10⁻¹¹ | <0,1 % |
| Turkmenistán | 5,0 × 10⁻¹¹ | <0,1 % |
| Malta | 4,7 × 10⁻¹¹ | <0,1 % |
| Noruega | 4,1 × 10⁻¹¹ | <0,1 % |
| Benín | 4,1 × 10⁻¹¹ | <0,1 % |
| Bangladés | 3,7 × 10⁻¹¹ | <0,1 % |
| Panamá | 2,9 × 10⁻¹¹ | <0,1 % |
| Irak | 2,8 × 10⁻¹¹ | <0,1 % |
| Mongolia | 2,8 × 10⁻¹¹ | <0,1 % |
| Venezuela | 1,8 × 10⁻¹¹ | <0,1 % |
| Guatemala | 1,8 × 10⁻¹¹ | <0,1 % |
| República Democrática del Congo | 1,6 × 10⁻¹¹ | <0,1 % |
| Túnez | 1,4 × 10⁻¹¹ | <0,1 % |
| Irán | 1,4 × 10⁻¹¹ | <0,1 % |
| Marruecos | 1,3 × 10⁻¹¹ | <0,1 % |
| Islandia | 1,1 × 10⁻¹¹ | <0,1 % |
| Mauritania | 1,0 × 10⁻¹¹ | <0,1 % |
| Togo | 9,4 × 10⁻¹² | <0,1 % |
| Mozambique | 7,4 × 10⁻¹² | <0,1 % |
| Egipto | 5,6 × 10⁻¹² | <0,1 % |
| Indonesia | 4,4 × 10⁻¹² | <0,1 % |
| Perú | 4,0 × 10⁻¹² | <0,1 % |
| Filipinas | 3,3 × 10⁻¹² | <0,1 % |
| Arabia Saudí | 2,6 × 10⁻¹² | <0,1 % |
| Sudáfrica | 2,4 × 10⁻¹² | <0,1 % |
| Esuatini | 2,4 × 10⁻¹² | <0,1 % |
| Mauricio | 1,4 × 10⁻¹² | <0,1 % |
| Ghana | 5,2 × 10⁻¹³ | <0,1 % |
| Bolivia | 4,8 × 10⁻¹³ | <0,1 % |
| Argelia | 4,7 × 10⁻¹³ | <0,1 % |
| China | 2,7 × 10⁻¹³ | <0,1 % |
| Libia | 1,5 × 10⁻¹³ | <0,1 % |
| Papúa Nueva Guinea | 1,5 × 10⁻¹⁴ | <0,1 % |
| Suma | 3,2 × 10⁻⁷ | = la cifra principal, 3,2 × 10⁻⁷ |
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 | 2,8 × 10⁻⁷ | 89 % |
| Trabajo | 3,4 × 10⁻⁸ | 11 % |
| Suma | 3,2 × 10⁻⁷ | = la cifra principal, 3,2 × 10⁻⁷ |
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 |
|---|---|---|
| Russia - Ukraine | 8,5 × 10⁻⁸ | 27 % |
| Israel: Palestine | 4,3 × 10⁻⁸ | 14 % |
| Somalia: Government | 3,8 × 10⁻⁸ | 12 % |
| Sin ubicar | 3,4 × 10⁻⁸ | 11 % |
| Sudan: Government | 2,7 × 10⁻⁸ | 8,7 % |
| RSF - Civilians | 1,2 × 10⁻⁸ | 3,7 % |
| Pakistan: Government | 6,4 × 10⁻⁹ | 2,0 % |
| Jalisco Cartel New Generation - Sinaloa Cartel | 4,9 × 10⁻⁹ | 1,6 % |
| Ethiopia: Government/Amhara | 3,6 × 10⁻⁹ | 1,1 % |
| SSC-Khatumo Administration - Republic of Somaliland | 2,9 × 10⁻⁹ | 0,91 % |
| Syria: Government | 2,8 × 10⁻⁹ | 0,88 % |
| IS - Civilians | 2,7 × 10⁻⁹ | 0,86 % |
| Burkina Faso: Government | 2,5 × 10⁻⁹ | 0,81 % |
| Yemen (North Yemen): Government | 2,4 × 10⁻⁹ | 0,76 % |
| Niger: Islamic State | 2,2 × 10⁻⁹ | 0,68 % |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 2,1 × 10⁻⁹ | 0,67 % |
| Juarez Cartel - Sinaloa Cartel | 1,9 × 10⁻⁹ | 0,60 % |
| Syria: Islamic State | 1,6 × 10⁻⁹ | 0,52 % |
| Kenya: Northeastern Province and Coast | 1,6 × 10⁻⁹ | 0,50 % |
| Mali: Government | 1,6 × 10⁻⁹ | 0,50 % |
| Myanmar (Burma): Government | 1,5 × 10⁻⁹ | 0,48 % |
| Carteles Unidos - Jalisco Cartel New Generation | 1,4 × 10⁻⁹ | 0,45 % |
| Ethiopia: Oromiya | 1,3 × 10⁻⁹ | 0,42 % |
| Beni Halba Baggara - Salamat Baggara | 1,3 × 10⁻⁹ | 0,40 % |
| Hamas - Civilians | 1,1 × 10⁻⁹ | 0,34 % |
| JNIM - Civilians | 1,1 × 10⁻⁹ | 0,33 % |
| Afghanistan: Islamic State | 9,6 × 10⁻¹⁰ | 0,31 % |
| Luac Jang Dinka - Pakam Dinka | 9,3 × 10⁻¹⁰ | 0,29 % |
| SNA - SDF | 9,1 × 10⁻¹⁰ | 0,29 % |
| Habaniya - Salamat Baggara | 8,8 × 10⁻¹⁰ | 0,28 % |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 8,2 × 10⁻¹⁰ | 0,26 % |
| Pakistan: Balochistan | 8,1 × 10⁻¹⁰ | 0,26 % |
| Pakistan: Islamic State | 6,4 × 10⁻¹⁰ | 0,20 % |
| Arab - Gimir | 6,3 × 10⁻¹⁰ | 0,20 % |
| IS - JNIM | 6,3 × 10⁻¹⁰ | 0,20 % |
| Comando Vermelho - PCC | 5,8 × 10⁻¹⁰ | 0,19 % |
| Iran - Israel | 5,7 × 10⁻¹⁰ | 0,18 % |
| India: Kashmir | 5,6 × 10⁻¹⁰ | 0,18 % |
| Al-Shabaab - Civilians | 5,5 × 10⁻¹⁰ | 0,18 % |
| Government of Ethiopia - Civilians | 5,4 × 10⁻¹⁰ | 0,17 % |
| Government of Myanmar (Burma) - Civilians | 5,2 × 10⁻¹⁰ | 0,17 % |
| Burkina Faso: Islamic State | 5,2 × 10⁻¹⁰ | 0,16 % |
| Kuki - Meitei | 4,8 × 10⁻¹⁰ | 0,15 % |
| Afghanistan: Government | 4,7 × 10⁻¹⁰ | 0,15 % |
| India: Government | 4,5 × 10⁻¹⁰ | 0,14 % |
| Government of Russia (Soviet Union) - Civilians | 4,5 × 10⁻¹⁰ | 0,14 % |
| OLA - Civilians | 4,2 × 10⁻¹⁰ | 0,13 % |
| IS - SDF | 4,2 × 10⁻¹⁰ | 0,13 % |
| Niger: Government | 4,2 × 10⁻¹⁰ | 0,13 % |
| Azerbaijan: Artsakh (Nagorno-Karabakh) | 4,2 × 10⁻¹⁰ | 0,13 % |
| Turkey: Kurdistan | 4,0 × 10⁻¹⁰ | 0,13 % |
| Government of Mali - Civilians | 3,9 × 10⁻¹⁰ | 0,12 % |
| Twic Dinka - Ngok Dinka | 3,8 × 10⁻¹⁰ | 0,12 % |
| Fano - Civilians | 3,8 × 10⁻¹⁰ | 0,12 % |
| Anuak - Nuer | 3,6 × 10⁻¹⁰ | 0,12 % |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 3,6 × 10⁻¹⁰ | 0,11 % |
| Israel: Southern Lebanon | 3,5 × 10⁻¹⁰ | 0,11 % |
| Deir ez Zor Military Council - SDF | 3,3 × 10⁻¹⁰ | 0,10 % |
| Mali: Government/Azawad | 3,3 × 10⁻¹⁰ | 0,10 % |
| Mali: Islamic State | 3,2 × 10⁻¹⁰ | 0,10 % |
| AQAP - Forces of the Presidential Leadership Council | 3,2 × 10⁻¹⁰ | 0,10 % |
| Nigeria: Government | 3,0 × 10⁻¹⁰ | <0,1 % |
| Government of Burkina Faso - Civilians | 2,8 × 10⁻¹⁰ | <0,1 % |
| Myanmar (Burma): Kachin | 2,6 × 10⁻¹⁰ | <0,1 % |
| DZ Mafia - Yoda | 2,6 × 10⁻¹⁰ | <0,1 % |
| Government of Afghanistan - Civilians | 2,5 × 10⁻¹⁰ | <0,1 % |
| M18 - MS-13 | 2,5 × 10⁻¹⁰ | <0,1 % |
| Government of South Sudan - Civilians | 2,4 × 10⁻¹⁰ | <0,1 % |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 2,3 × 10⁻¹⁰ | <0,1 % |
| Shia (Pakistan) - Sunni (Pakistan) | 2,1 × 10⁻¹⁰ | <0,1 % |
| Bonde do Maluco - Comando Vermelho | 2,1 × 10⁻¹⁰ | <0,1 % |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 2,1 × 10⁻¹⁰ | <0,1 % |
| CPI-Maoist - Civilians | 2,0 × 10⁻¹⁰ | <0,1 % |
| Sa'ad subclan of Habar Gidir clan (Hawiye) - Leelkase subclan (Darod) | 2,0 × 10⁻¹⁰ | <0,1 % |
| Arab - Masalit | 2,0 × 10⁻¹⁰ | <0,1 % |
| Cartel do Norte - Comando Vermelho | 1,9 × 10⁻¹⁰ | <0,1 % |
| EGC - Civilians | 1,7 × 10⁻¹⁰ | <0,1 % |
| Myanmar (Burma): Karen | 1,7 × 10⁻¹⁰ | <0,1 % |
| Dan na Ambassagou - JNIM | 1,6 × 10⁻¹⁰ | <0,1 % |
| Djerma (Zherma) - Fulani | 1,6 × 10⁻¹⁰ | <0,1 % |
| Los Choneros - Los Lobos | 1,6 × 10⁻¹⁰ | <0,1 % |
| Los Ardillos - Los Tlacos | 1,5 × 10⁻¹⁰ | <0,1 % |
| JAS - Civilians | 1,5 × 10⁻¹⁰ | <0,1 % |
| Somalia: Islamic State | 1,5 × 10⁻¹⁰ | <0,1 % |
| Syria: Government/Rojava Kurdistan | 1,4 × 10⁻¹⁰ | <0,1 % |
| Bonde dos 40 - PCC | 1,4 × 10⁻¹⁰ | <0,1 % |
| Government of Haiti - Civilians | 1,4 × 10⁻¹⁰ | <0,1 % |
| Nigeria: Islamic State | 1,3 × 10⁻¹⁰ | <0,1 % |
| Myanmar (Burma): Karenni | 1,3 × 10⁻¹⁰ | <0,1 % |
| Central African Republic: Government | 1,3 × 10⁻¹⁰ | <0,1 % |
| Hausa - Nuba | 1,3 × 10⁻¹⁰ | <0,1 % |
| G9 - G-Pep | 1,2 × 10⁻¹⁰ | <0,1 % |
| Burundi: Government | 1,2 × 10⁻¹⁰ | <0,1 % |
| Terre Noire - Civilians | 1,2 × 10⁻¹⁰ | <0,1 % |
| 5 Segond, Taliban - Civilians | 1,1 × 10⁻¹⁰ | <0,1 % |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 1,1 × 10⁻¹⁰ | <0,1 % |
| Grand Ravine - Civilians | 1,0 × 10⁻¹⁰ | <0,1 % |
| Uganda: Islamic State | 1,0 × 10⁻¹⁰ | <0,1 % |
| Afghanistan - Pakistan | 1,0 × 10⁻¹⁰ | <0,1 % |
| Comando Vermelho - GDE | 1,0 × 10⁻¹⁰ | <0,1 % |
| Nova Okaida - Estados Unidos | 1,0 × 10⁻¹⁰ | <0,1 % |
| GDE, PCC - Sindicato do Crime | 1,0 × 10⁻¹⁰ | <0,1 % |
| Amhara - Oromo | 9,8 × 10⁻¹¹ | <0,1 % |
| Colombia: Government | 9,5 × 10⁻¹¹ | <0,1 % |
| FARC-EMC - Civilians | 9,0 × 10⁻¹¹ | <0,1 % |
| Kashmir insurgents - Civilians | 8,9 × 10⁻¹¹ | <0,1 % |
| PCC - Sindicato do Crime | 8,9 × 10⁻¹¹ | <0,1 % |
| BRAS - Civilians | 8,9 × 10⁻¹¹ | <0,1 % |
| Amigos Para Sempre - Família Terror Amapá | 8,8 × 10⁻¹¹ | <0,1 % |
| Cameroon: Ambazonia | 8,5 × 10⁻¹¹ | <0,1 % |
| Forces of Tony Peña - Los Hondureños | 8,3 × 10⁻¹¹ | <0,1 % |
| G-Pep - Civilians | 7,9 × 10⁻¹¹ | <0,1 % |
| Government of Israel - Civilians | 7,4 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Civilians | 7,4 × 10⁻¹¹ | <0,1 % |
| Myanmar (Burma): Arakan | 7,0 × 10⁻¹¹ | <0,1 % |
| Fatales, Los Aguilas - Los Lobos , Los Tiguerones | 6,6 × 10⁻¹¹ | <0,1 % |
| Israel - Syria | 6,0 × 10⁻¹¹ | <0,1 % |
| FARC-EMC - ELN | 5,8 × 10⁻¹¹ | <0,1 % |
| Los Chone Killers - Latin Kings | 5,5 × 10⁻¹¹ | <0,1 % |
| Bonde dos 13, PCC - Comando Vermelho | 5,4 × 10⁻¹¹ | <0,1 % |
| Bonde dos 40 - Comando Vermelho | 5,3 × 10⁻¹¹ | <0,1 % |
| Government of Burundi - Civilians | 5,2 × 10⁻¹¹ | <0,1 % |
| TTP - Civilians | 5,2 × 10⁻¹¹ | <0,1 % |
| M18 - Civilians | 5,2 × 10⁻¹¹ | <0,1 % |
| AAKG - CPC | 5,2 × 10⁻¹¹ | <0,1 % |
| United Kingdom, United States of America - Yemen | 5,1 × 10⁻¹¹ | <0,1 % |
| Cameroon: Government | 5,0 × 10⁻¹¹ | <0,1 % |
| Hawazma - Nuba | 5,0 × 10⁻¹¹ | <0,1 % |
| Russia (Soviet Union): Government | 5,0 × 10⁻¹¹ | <0,1 % |
| Toposa - Turkana | 5,0 × 10⁻¹¹ | <0,1 % |
| Dinka - Nuer | 5,0 × 10⁻¹¹ | <0,1 % |
| Los Aguilas - Los Lobos | 4,9 × 10⁻¹¹ | <0,1 % |
| Ambazonia insurgents - Civilians | 4,6 × 10⁻¹¹ | <0,1 % |
| Hausa - Funj | 4,5 × 10⁻¹¹ | <0,1 % |
| Dozos (Mali) - JNIM | 4,4 × 10⁻¹¹ | <0,1 % |
| Los Choneros - Los Lagartos | 4,4 × 10⁻¹¹ | <0,1 % |
| Los Lobos - Los Tiguerones | 4,3 × 10⁻¹¹ | <0,1 % |
| Los Lagartos - Mafia 18 | 4,3 × 10⁻¹¹ | <0,1 % |
| Myanmar (Burma): Kokang | 4,3 × 10⁻¹¹ | <0,1 % |
| Guraghe - Mareqo | 4,3 × 10⁻¹¹ | <0,1 % |
| Government of Pakistan - Civilians | 4,3 × 10⁻¹¹ | <0,1 % |
| Chad: Government | 4,1 × 10⁻¹¹ | <0,1 % |
| Government of Sudan - Civilians | 4,0 × 10⁻¹¹ | <0,1 % |
| Government of Somalia - Civilians | 3,9 × 10⁻¹¹ | <0,1 % |
| FARC - Segunda Marquetalia - Civilians | 3,9 × 10⁻¹¹ | <0,1 % |
| ELN - Civilians | 3,9 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Holanda | 3,8 × 10⁻¹¹ | <0,1 % |
| Hindus (India) - Muslims (India) | 3,8 × 10⁻¹¹ | <0,1 % |
| Government of Yemen (North Yemen) - Civilians | 3,6 × 10⁻¹¹ | <0,1 % |
| Los Aguilas - Los Lobos , Los Tiguerones | 3,3 × 10⁻¹¹ | <0,1 % |
| Government of India - Civilians | 3,3 × 10⁻¹¹ | <0,1 % |
| Syrian insurgents - Civilians | 3,2 × 10⁻¹¹ | <0,1 % |
| Los Rusos, UPOEG - Los Tlacos | 3,2 × 10⁻¹¹ | <0,1 % |
| Los Costenos - Los Pepes | 3,1 × 10⁻¹¹ | <0,1 % |
| Gran Grif - Civilians | 3,1 × 10⁻¹¹ | <0,1 % |
| 400 Mawozo - Civilians | 3,1 × 10⁻¹¹ | <0,1 % |
| IS - JAS | 3,1 × 10⁻¹¹ | <0,1 % |
| Farmers (Chad) - Herders (Chad) | 3,0 × 10⁻¹¹ | <0,1 % |
| EGC - ELN, FARC-EMC | 3,0 × 10⁻¹¹ | <0,1 % |
| Murle - Nuer | 2,9 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Massa | 2,9 × 10⁻¹¹ | <0,1 % |
| EGC - ELN | 2,9 × 10⁻¹¹ | <0,1 % |
| Jalisco Cartel New Generation - Civilians | 2,9 × 10⁻¹¹ | <0,1 % |
| ARSA - Civilians | 2,8 × 10⁻¹¹ | <0,1 % |
| Nova Okaida - PCC | 2,8 × 10⁻¹¹ | <0,1 % |
| Jalisco Cartel New Generation - Pájaros Sierra | 2,6 × 10⁻¹¹ | <0,1 % |
| Bonde do Maluco - Katiara | 2,6 × 10⁻¹¹ | <0,1 % |
| Bonde do Maluco - Civilians | 2,6 × 10⁻¹¹ | <0,1 % |
| Dozos (Mali) - Civilians | 2,5 × 10⁻¹¹ | <0,1 % |
| Benin: Government | 2,5 × 10⁻¹¹ | <0,1 % |
| SDF - Civilians | 2,5 × 10⁻¹¹ | <0,1 % |
| Cameroon: Islamic State | 2,4 × 10⁻¹¹ | <0,1 % |
| Government of Mexico - Civilians | 2,2 × 10⁻¹¹ | <0,1 % |
| Bonde dos 40 - Civilians | 2,0 × 10⁻¹¹ | <0,1 % |
| Al-Shabaab - IS | 2,0 × 10⁻¹¹ | <0,1 % |
| Comando Vermelho - Terceiro Comando Puro | 2,0 × 10⁻¹¹ | <0,1 % |
| Los Ardillos - Los Rojos | 1,9 × 10⁻¹¹ | <0,1 % |
| India: Western South East Asia | 1,9 × 10⁻¹¹ | <0,1 % |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 1,8 × 10⁻¹¹ | <0,1 % |
| Fulani - Mwaghavul | 1,8 × 10⁻¹¹ | <0,1 % |
| Fulani - Mwaghavul , Ron | 1,6 × 10⁻¹¹ | <0,1 % |
| Central African Republic: Logone | 1,6 × 10⁻¹¹ | <0,1 % |
| Fulani - Tiv | 1,6 × 10⁻¹¹ | <0,1 % |
| Dan na Ambassagou - Civilians | 1,5 × 10⁻¹¹ | <0,1 % |
| Government of Venezuela - Civilians | 1,5 × 10⁻¹¹ | <0,1 % |
| PCC - Civilians | 1,5 × 10⁻¹¹ | <0,1 % |
| CPC - Civilians | 1,4 × 10⁻¹¹ | <0,1 % |
| Tunisia: Government | 1,4 × 10⁻¹¹ | <0,1 % |
| Farmers (Nigeria) - Herders (Nigeria) | 1,3 × 10⁻¹¹ | <0,1 % |
| NUG - Civilians | 1,3 × 10⁻¹¹ | <0,1 % |
| Ajeita - Bonde do Maluco | 1,3 × 10⁻¹¹ | <0,1 % |
| Morocco: Sahrawi Arab Democratic Republic (Western Sahara) | 1,3 × 10⁻¹¹ | <0,1 % |
| EGC - Autodefensas Conquistadoras de la Sierra Nevada | 1,3 × 10⁻¹¹ | <0,1 % |
| South Sudan: Government | 1,2 × 10⁻¹¹ | <0,1 % |
| GATIA - IS | 1,2 × 10⁻¹¹ | <0,1 % |
| Iran: Government | 1,2 × 10⁻¹¹ | <0,1 % |
| Government of Cameroon - Civilians | 1,1 × 10⁻¹¹ | <0,1 % |
| MS-13 - Civilians | 1,1 × 10⁻¹¹ | <0,1 % |
| Mauritania: Government | 1,0 × 10⁻¹¹ | <0,1 % |
| Government of Colombia - Civilians | 1,0 × 10⁻¹¹ | <0,1 % |
| Misseriya - Ngok Dinka | 1,0 × 10⁻¹¹ | <0,1 % |
| Government of Brazil - Civilians | 9,8 × 10⁻¹² | <0,1 % |
| Nigeria: Biafra | 9,5 × 10⁻¹² | <0,1 % |
| VHP - Civilians | 9,4 × 10⁻¹² | <0,1 % |
| Anti-Bala - Bala na Cara | 9,0 × 10⁻¹² | <0,1 % |
| Amhara - Gumuz | 8,6 × 10⁻¹² | <0,1 % |
| Thailand: Patani | 8,4 × 10⁻¹² | <0,1 % |
| Bonde dos 40 - PCM | 8,2 × 10⁻¹² | <0,1 % |
| Iraq: Government | 8,0 × 10⁻¹² | <0,1 % |
| LeJ - Civilians | 7,4 × 10⁻¹² | <0,1 % |
| PKK - Civilians | 7,2 × 10⁻¹² | <0,1 % |
| Birom - Fulani | 7,0 × 10⁻¹² | <0,1 % |
| Comités locaux de vigilance - JAS | 6,7 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Sinaloa Cartel | 6,3 × 10⁻¹² | <0,1 % |
| Gulf Cartel - Jalisco Cartel New Generation | 6,3 × 10⁻¹² | <0,1 % |
| Supporters of Awami League - Supporters of BNP | 6,1 × 10⁻¹² | <0,1 % |
| Atyap - Fulani | 6,1 × 10⁻¹² | <0,1 % |
| IS - MSA | 5,8 × 10⁻¹² | <0,1 % |
| Karimjo - Wurukum | 5,7 × 10⁻¹² | <0,1 % |
| Black Axe - Eyie | 5,4 × 10⁻¹² | <0,1 % |
| Mozambique: Islamic State | 4,8 × 10⁻¹² | <0,1 % |
| Forces of Terwase Akwanza - Civilians | 4,8 × 10⁻¹² | <0,1 % |
| India - Pakistan | 4,7 × 10⁻¹² | <0,1 % |
| India: Nagaland | 4,7 × 10⁻¹² | <0,1 % |
| NSCN-IM - Civilians | 4,7 × 10⁻¹² | <0,1 % |
| PLFI - Civilians | 4,7 × 10⁻¹² | <0,1 % |
| Government of Egypt - Civilians | 4,7 × 10⁻¹² | <0,1 % |
| Government of Central African Republic - Civilians | 4,6 × 10⁻¹² | <0,1 % |
| Comandos de la Frontera - Civilians | 4,6 × 10⁻¹² | <0,1 % |
| Fulani - Idoma | 4,4 × 10⁻¹² | <0,1 % |
| Fulani - Kuteb | 4,2 × 10⁻¹² | <0,1 % |
| Peru: Government | 4,0 × 10⁻¹² | <0,1 % |
| Los Lobos - R7 | 3,7 × 10⁻¹² | <0,1 % |
| Togo: Government | 3,6 × 10⁻¹² | <0,1 % |
| IS - HTS | 3,5 × 10⁻¹² | <0,1 % |
| Autodefensas Conquistadoras de la Sierra Nevada - Civilians | 3,4 × 10⁻¹² | <0,1 % |
| Kokorat sans ras - Civilians | 3,2 × 10⁻¹² | <0,1 % |
| Supporters of Awami League - Supporters of Jamaat-e-Islami | 3,0 × 10⁻¹² | <0,1 % |
| Government of Nigeria - Civilians | 3,0 × 10⁻¹² | <0,1 % |
| Indonesia: West Papua | 2,8 × 10⁻¹² | <0,1 % |
| URDPC - Civilians | 2,6 × 10⁻¹² | <0,1 % |
| Russia: Islamic State | 2,6 × 10⁻¹² | <0,1 % |
| Chain Guys - Full Force | 2,5 × 10⁻¹² | <0,1 % |
| Government of eSwatini (Swaziland) - Civilians | 2,4 × 10⁻¹² | <0,1 % |
| Los Costenos - Civilians | 2,3 × 10⁻¹² | <0,1 % |
| Philippines: Government | 2,0 × 10⁻¹² | <0,1 % |
| Myanmar (Burma): Shan | 1,8 × 10⁻¹² | <0,1 % |
| Lengola - Mbole | 1,7 × 10⁻¹² | <0,1 % |
| CATA - Codeta | 1,5 × 10⁻¹² | <0,1 % |
| Hausa - Fulani | 1,4 × 10⁻¹² | <0,1 % |
| RED-TABARA - Civilians | 1,4 × 10⁻¹² | <0,1 % |
| OPM - Civilians | 1,3 × 10⁻¹² | <0,1 % |
| Iran: Islamic State | 1,3 × 10⁻¹² | <0,1 % |
| Government of Rwanda - Civilians | 1,2 × 10⁻¹² | <0,1 % |
| DR Congo (Zaire): Government | 1,2 × 10⁻¹² | <0,1 % |
| DR Congo (Zaire): Islamic State | 1,2 × 10⁻¹² | <0,1 % |
| Guerreros Unidos - Los Tlacos | 1,1 × 10⁻¹² | <0,1 % |
| Russia (Soviet Union): Chechnya | 1,0 × 10⁻¹² | <0,1 % |
| Farmers (CAR) - Herders (CAR) | 1,0 × 10⁻¹² | <0,1 % |
| AAKG - Civilians | 1,0 × 10⁻¹² | <0,1 % |
| Fulani - Irigwe | 9,8 × 10⁻¹³ | <0,1 % |
| Government of South Africa - Civilians | 9,7 × 10⁻¹³ | <0,1 % |
| Philippines: Islamic State | 9,6 × 10⁻¹³ | <0,1 % |
| Government of Iran - Civilians | 9,6 × 10⁻¹³ | <0,1 % |
| Egypt: Islamic State | 9,4 × 10⁻¹³ | <0,1 % |
| Fulani - Igala | 8,2 × 10⁻¹³ | <0,1 % |
| Amigos dos Amigos - Comando Vermelho | 8,2 × 10⁻¹³ | <0,1 % |
| FDN - PCC | 8,2 × 10⁻¹³ | <0,1 % |
| IS - Naparama | 8,2 × 10⁻¹³ | <0,1 % |
| Greenlanders - NDV | 7,4 × 10⁻¹³ | <0,1 % |
| Black Axe - Maphite | 7,4 × 10⁻¹³ | <0,1 % |
| M23 - VDP | 7,4 × 10⁻¹³ | <0,1 % |
| Mobondo - Civilians | 7,1 × 10⁻¹³ | <0,1 % |
| M23 - Civilians | 5,7 × 10⁻¹³ | <0,1 % |
| Kusasi - Mamprusi | 5,2 × 10⁻¹³ | <0,1 % |
| Rwanda: Government | 5,0 × 10⁻¹³ | <0,1 % |
| Supporters of APC - Supporters of PDP | 4,9 × 10⁻¹³ | <0,1 % |
| Algeria: Government | 4,7 × 10⁻¹³ | <0,1 % |
| Government of DR Congo (Zaire) - Civilians | 4,6 × 10⁻¹³ | <0,1 % |
| Choa Arab - Kotoko | 4,4 × 10⁻¹³ | <0,1 % |
| Choa Arab - Musgum | 4,4 × 10⁻¹³ | <0,1 % |
| Black Axe - SVC | 4,1 × 10⁻¹³ | <0,1 % |
| IPOB - Civilians | 4,1 × 10⁻¹³ | <0,1 % |
| Government of Mozambique - Civilians | 3,5 × 10⁻¹³ | <0,1 % |
| Government of Indonesia - Civilians | 3,3 × 10⁻¹³ | <0,1 % |
| Agatu - Fulani | 3,3 × 10⁻¹³ | <0,1 % |
| IS - Yan Gora | 3,3 × 10⁻¹³ | <0,1 % |
| Deebam - NDV | 3,3 × 10⁻¹³ | <0,1 % |
| Patani insurgents - Civilians | 2,8 × 10⁻¹³ | <0,1 % |
| URDPC - Zaire self-defense group | 2,3 × 10⁻¹³ | <0,1 % |
| Zaire self-defense group - Civilians | 2,1 × 10⁻¹³ | <0,1 % |
| VDP - Civilians | 2,0 × 10⁻¹³ | <0,1 % |
| CPP - Civilians | 2,0 × 10⁻¹³ | <0,1 % |
| Jukun - Tiv | 1,6 × 10⁻¹³ | <0,1 % |
| FPIC Chambre noire sanduku - URDPC | 1,5 × 10⁻¹³ | <0,1 % |
| FPIC Chambre noire sanduku - Civilians | 1,5 × 10⁻¹³ | <0,1 % |
| Libya: Government | 1,5 × 10⁻¹³ | <0,1 % |
| AFC - Civilians | 1,1 × 10⁻¹³ | <0,1 % |
| AFP-Gutabara - CNPSC, FABB | 1,0 × 10⁻¹³ | <0,1 % |
| AFP-Gutabara - FABB | 3,7 × 10⁻¹⁴ | <0,1 % |
| FRPI - Civilians | 3,1 × 10⁻¹⁴ | <0,1 % |
| Philippines: Mindanao | 2,4 × 10⁻¹⁴ | <0,1 % |
| Government of Philippines - Civilians | 2,4 × 10⁻¹⁴ | <0,1 % |
| Basonge - Bena Nkoma (Bakwa Luntu, Luba) | 2,0 × 10⁻¹⁴ | <0,1 % |
| FDLR-FOCA - Civilians | 1,7 × 10⁻¹⁴ | <0,1 % |
| FPIC Chambre noire sanduku - FRPI | 1,7 × 10⁻¹⁴ | <0,1 % |
| Ambulin, Lungupin, Nenei, Sau, Sau Walep, Yandamau, Yopo - Kaekin, Lanzerakin, Lyona, Mupapalu, Murap, Palinau, Sakaikin, Sikin, Wapukin | 1,5 × 10⁻¹⁴ | <0,1 % |
| Mayi Mayi Chini ya Tuna - Civilians | 1,4 × 10⁻¹⁴ | <0,1 % |
| Luba - Batwa | 1,0 × 10⁻¹⁴ | <0,1 % |
| DR Congo (Zaire): Katanga | 3,4 × 10⁻¹⁵ | <0,1 % |
| Government of Uganda - Civilians | 3,4 × 10⁻¹⁵ | <0,1 % |
| Twiganeho - Civilians | 3,4 × 10⁻¹⁵ | <0,1 % |
| AFC - VDP | 3,4 × 10⁻¹⁵ | <0,1 % |
| Government of Papua New Guinea - Civilians | 2,2 × 10⁻¹⁶ | <0,1 % |
| Suma | 3,2 × 10⁻⁷ | = la cifra principal, 3,2 × 10⁻⁷ |
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 |
|---|---|---|
| Crop and animal production, hunting and related service activities | 2,3 × 10⁻⁶ | 69 % |
| Mining and quarrying | 7,0 × 10⁻⁷ | 21 % |
| Land transport and transport via pipelines | 7,0 × 10⁻⁸ | 2,0 % |
| Manufacture of food products; beverages and tobacco products | 6,0 × 10⁻⁸ | 1,8 % |
| Water transport | 3,3 × 10⁻⁸ | 0,98 % |
| Forestry and logging | 3,3 × 10⁻⁸ | 0,98 % |
| Manufacture of basic metals | 3,3 × 10⁻⁸ | 0,96 % |
| Warehousing and support activities for transportation | 2,8 × 10⁻⁸ | 0,82 % |
| Wholesale trade, except of motor vehicles and motorcycles | 1,8 × 10⁻⁸ | 0,53 % |
| Air transport | 1,3 × 10⁻⁸ | 0,39 % |
| Retail trade, except of motor vehicles and motorcycles | 7,8 × 10⁻⁹ | 0,23 % |
| Postal and courier activities | 5,1 × 10⁻⁹ | 0,15 % |
| Manufacture of fabricated metal products, except machinery and equipment | 4,8 × 10⁻⁹ | 0,14 % |
| Water collection, treatment and supply | 4,3 × 10⁻⁹ | 0,13 % |
| Construction | 3,6 × 10⁻⁹ | 0,11 % |
| Fishing and aquaculture | 3,1 × 10⁻⁹ | <0,1 % |
| Manufacture of other transport equipment | 3,0 × 10⁻⁹ | <0,1 % |
| Manufacture of coke and refined petroleum products | 2,5 × 10⁻⁹ | <0,1 % |
| Security and investigation, service and landscape, office administrative and support activities | 2,5 × 10⁻⁹ | <0,1 % |
| Manufacture of chemicals and chemical products | 2,2 × 10⁻⁹ | <0,1 % |
| Electricity, gas, steam and air conditioning supply | 2,0 × 10⁻⁹ | <0,1 % |
| Rental and leasing activities | 1,7 × 10⁻⁹ | <0,1 % |
| Employment activities | 1,5 × 10⁻⁹ | <0,1 % |
| Public administration and defence; compulsory social security | 1,5 × 10⁻⁹ | <0,1 % |
| Manufacture of rubber and plastic products | 1,4 × 10⁻⁹ | <0,1 % |
| Manufacture of paper and paper products | 1,3 × 10⁻⁹ | <0,1 % |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 1,2 × 10⁻⁹ | <0,1 % |
| Sewerage, waste management, remediation activities | 1,2 × 10⁻⁹ | <0,1 % |
| Legal and accounting activities; activities of head offices; management consultancy activities | 8,5 × 10⁻¹⁰ | <0,1 % |
| Accommodation and food service activities | 5,5 × 10⁻¹⁰ | <0,1 % |
| Manufacture of other non-metallic mineral products | 5,4 × 10⁻¹⁰ | <0,1 % |
| Manufacture of machinery and equipment n.e.c. | 5,1 × 10⁻¹⁰ | <0,1 % |
| Repair and installation of machinery and equipment | 3,9 × 10⁻¹⁰ | <0,1 % |
| Manufacture of motor vehicles, trailers and semi-trailers | 3,6 × 10⁻¹⁰ | <0,1 % |
| Human health activities | 3,4 × 10⁻¹⁰ | <0,1 % |
| Advertising and market research | 3,3 × 10⁻¹⁰ | <0,1 % |
| Manufacture of textiles, wearing apparel, leather and related products | 3,1 × 10⁻¹⁰ | <0,1 % |
| Manufacture of computer, electronic and optical products | 3,1 × 10⁻¹⁰ | <0,1 % |
| Real estate activities | 2,9 × 10⁻¹⁰ | <0,1 % |
| Manufacture of electrical equipment | 2,9 × 10⁻¹⁰ | <0,1 % |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 2,5 × 10⁻¹⁰ | <0,1 % |
| Travel agency, tour operator reservation service and related activities | 2,3 × 10⁻¹⁰ | <0,1 % |
| Architectural and engineering activities; technical testing and analysis | 2,3 × 10⁻¹⁰ | <0,1 % |
| Computer programming, consultancy, and information service activities | 2,1 × 10⁻¹⁰ | <0,1 % |
| Repair of computers and personal and household goods | 2,0 × 10⁻¹⁰ | <0,1 % |
| Manufacture of basic pharmaceutical products and pharmaceutical preparations | 1,8 × 10⁻¹⁰ | <0,1 % |
| Other professional, scientific and technical activities; veterinary activities | 1,7 × 10⁻¹⁰ | <0,1 % |
| Printing and reproduction of recorded media | 1,7 × 10⁻¹⁰ | <0,1 % |
| Activities of membership organisations | 1,6 × 10⁻¹⁰ | <0,1 % |
| Financial service activities, except insurance and pension funding | 1,4 × 10⁻¹⁰ | <0,1 % |
| Other personal service activities | 1,3 × 10⁻¹⁰ | <0,1 % |
| Telecommunications | 1,0 × 10⁻¹⁰ | <0,1 % |
| Manufacture of furniture; other manufacturing | 1,0 × 10⁻¹⁰ | <0,1 % |
| Sports activities and amusement and recreation activities | 1,0 × 10⁻¹⁰ | <0,1 % |
| Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities | 8,3 × 10⁻¹¹ | <0,1 % |
| Education | 6,2 × 10⁻¹¹ | <0,1 % |
| Motion picture, video, television programme production; programming and broadcasting activities | 6,2 × 10⁻¹¹ | <0,1 % |
| Insurance, reinsurance and pension funding, except compulsory social security | 4,7 × 10⁻¹¹ | <0,1 % |
| Publishing activities | 4,6 × 10⁻¹¹ | <0,1 % |
| Activities auxiliary to financial services and insurance activities | 4,5 × 10⁻¹¹ | <0,1 % |
| Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use | 2,5 × 10⁻¹¹ | <0,1 % |
| Residential care activities and social work activities without accommodation | 2,4 × 10⁻¹¹ | <0,1 % |
| Scientific research and development | 1,8 × 10⁻¹¹ | <0,1 % |
| Suma | 3,4 × 10⁻⁶ | = la cifra principal, 3,4 × 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 | 2,6 × 10⁻⁶ | 77 % |
| México | 3,9 × 10⁻⁷ | 12 % |
| Brasil | 1,5 × 10⁻⁷ | 4,3 % |
| Estados Unidos | 6,8 × 10⁻⁸ | 2,0 % |
| Rusia | 2,9 × 10⁻⁸ | 0,85 % |
| Turquía | 2,6 × 10⁻⁸ | 0,77 % |
| Francia | 1,6 × 10⁻⁸ | 0,47 % |
| India | 1,2 × 10⁻⁸ | 0,35 % |
| Canadá | 1,2 × 10⁻⁸ | 0,34 % |
| Corea del Sur | 1,1 × 10⁻⁸ | 0,31 % |
| Alemania | 9,7 × 10⁻⁹ | 0,28 % |
| España | 9,3 × 10⁻⁹ | 0,27 % |
| Italia | 9,0 × 10⁻⁹ | 0,26 % |
| Japón | 8,9 × 10⁻⁹ | 0,26 % |
| Argentina | 8,6 × 10⁻⁹ | 0,25 % |
| Austria | 5,5 × 10⁻⁹ | 0,16 % |
| Australia | 3,4 × 10⁻⁹ | <0,1 % |
| Polonia | 3,3 × 10⁻⁹ | <0,1 % |
| Rumanía | 2,9 × 10⁻⁹ | <0,1 % |
| Indonesia | 2,4 × 10⁻⁹ | <0,1 % |
| Portugal | 2,4 × 10⁻⁹ | <0,1 % |
| Irlanda | 2,1 × 10⁻⁹ | <0,1 % |
| Dinamarca | 1,4 × 10⁻⁹ | <0,1 % |
| Bulgaria | 1,4 × 10⁻⁹ | <0,1 % |
| Noruega | 1,2 × 10⁻⁹ | <0,1 % |
| Hungría | 1,2 × 10⁻⁹ | <0,1 % |
| Bélgica | 9,1 × 10⁻¹⁰ | <0,1 % |
| Suiza | 9,1 × 10⁻¹⁰ | <0,1 % |
| Lituania | 8,9 × 10⁻¹⁰ | <0,1 % |
| Chequia | 8,9 × 10⁻¹⁰ | <0,1 % |
| Finlandia | 7,7 × 10⁻¹⁰ | <0,1 % |
| Grecia | 7,6 × 10⁻¹⁰ | <0,1 % |
| Países Bajos | 6,1 × 10⁻¹⁰ | <0,1 % |
| Suecia | 6,0 × 10⁻¹⁰ | <0,1 % |
| Croacia | 5,8 × 10⁻¹⁰ | <0,1 % |
| Letonia | 3,8 × 10⁻¹⁰ | <0,1 % |
| Chipre | 3,5 × 10⁻¹⁰ | <0,1 % |
| Eslovaquia | 3,5 × 10⁻¹⁰ | <0,1 % |
| Luxemburgo | 2,3 × 10⁻¹⁰ | <0,1 % |
| Eslovenia | 1,9 × 10⁻¹⁰ | <0,1 % |
| Sudáfrica | 1,2 × 10⁻¹⁰ | <0,1 % |
| Estonia | 8,3 × 10⁻¹¹ | <0,1 % |
| Arabia Saudí | 6,8 × 10⁻¹¹ | <0,1 % |
| Reino Unido | 4,7 × 10⁻¹¹ | <0,1 % |
| Malta | 4,3 × 10⁻¹¹ | <0,1 % |
| China | 3,8 × 10⁻¹¹ | <0,1 % |
| Serbia | 2,5 × 10⁻¹⁴ | <0,1 % |
| Suma | 3,4 × 10⁻⁶ | = la cifra principal, 3,4 × 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/butter/