El rastro de auditoría
Cómo se construye la cifra de Vidrio
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.
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La cifra principal
Una unidad es one kilogram of soda-lime glass. 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 — 2,2 × 10⁻¹⁰ por unidad(0,93–4,5 × 10⁻¹⁰)BAJAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Vía monetaria — 2,6 × 10⁻⁶ por cada 1.000 € gastados en su industria(1,7–4,0 × 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 |
|---|---|---|---|---|
| Arena de sílice | 7,3 × 10⁻⁴ t | 3,0 × 10⁻¹⁰ | 2,2 × 10⁻¹⁰ | 100 % |
| Suma | 2,2 × 10⁻¹⁰ | = la cifra principal, 2,2 × 10⁻¹⁰ | ||
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 |
|---|---|---|
| Turquía | 4,2 × 10⁻¹¹ | 19 % |
| Italia | 3,9 × 10⁻¹¹ | 18 % |
| Estados Unidos | 3,6 × 10⁻¹¹ | 17 % |
| Francia | 1,9 × 10⁻¹¹ | 8,6 % |
| México | 1,6 × 10⁻¹¹ | 7,5 % |
| España | 1,3 × 10⁻¹¹ | 6,1 % |
| Corea del Sur | 1,2 × 10⁻¹¹ | 5,6 % |
| Moldavia | 1,0 × 10⁻¹¹ | 4,8 % |
| Bulgaria | 8,1 × 10⁻¹² | 3,7 % |
| Países Bajos | 6,1 × 10⁻¹² | 2,8 % |
| Alemania | 4,4 × 10⁻¹² | 2,0 % |
| Japón | 3,6 × 10⁻¹² | 1,7 % |
| Polonia | 1,7 × 10⁻¹² | 0,79 % |
| Canadá | 1,0 × 10⁻¹² | 0,47 % |
| Argentina | 9,9 × 10⁻¹³ | 0,45 % |
| Rusia | 9,8 × 10⁻¹³ | 0,44 % |
| Letonia | 8,7 × 10⁻¹³ | 0,39 % |
| Austria | 8,6 × 10⁻¹³ | 0,39 % |
| India | 7,4 × 10⁻¹³ | 0,33 % |
| Chequia | 6,9 × 10⁻¹³ | 0,31 % |
| Bélgica | 5,7 × 10⁻¹³ | 0,26 % |
| Guatemala | 3,7 × 10⁻¹³ | 0,17 % |
| Finlandia | 3,1 × 10⁻¹³ | 0,14 % |
| Australia | 2,5 × 10⁻¹³ | 0,11 % |
| Indonesia | 8,9 × 10⁻¹⁴ | <0,1 % |
| Noruega | 2,4 × 10⁻¹⁴ | <0,1 % |
| Irán | 2,2 × 10⁻¹⁴ | <0,1 % |
| Sudáfrica | 1,3 × 10⁻¹⁴ | <0,1 % |
| Egipto | 1,3 × 10⁻¹⁴ | <0,1 % |
| Arabia Saudí | 5,4 × 10⁻¹⁵ | <0,1 % |
| China | 3,9 × 10⁻¹⁵ | <0,1 % |
| Suma | 2,2 × 10⁻¹⁰ | = la cifra principal, 2,2 × 10⁻¹⁰ |
3 · Por qué canal de daño
La misma cifra principal, por canal de daño: conflicto, trabajo, privación, exposición.
| Canal | Aportación | Parte |
|---|---|---|
| Trabajo | 2,0 × 10⁻¹⁰ | 91 % |
| Conflicto y violencia política | 2,1 × 10⁻¹¹ | 9,5 % |
| Suma | 2,2 × 10⁻¹⁰ | = la cifra principal, 2,2 × 10⁻¹⁰ |
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 |
|---|---|---|
| Sin ubicar | 2,0 × 10⁻¹⁰ | 91 % |
| Jalisco Cartel New Generation - Sinaloa Cartel | 4,1 × 10⁻¹² | 1,9 % |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 3,5 × 10⁻¹² | 1,6 % |
| Juarez Cartel - Sinaloa Cartel | 3,1 × 10⁻¹² | 1,4 % |
| Carteles Unidos - Jalisco Cartel New Generation | 2,4 × 10⁻¹² | 1,1 % |
| Turkey: Kurdistan | 2,0 × 10⁻¹² | 0,89 % |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 1,4 × 10⁻¹² | 0,61 % |
| DZ Mafia - Yoda | 1,0 × 10⁻¹² | 0,45 % |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 5,9 × 10⁻¹³ | 0,27 % |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 3,7 × 10⁻¹³ | 0,17 % |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 3,4 × 10⁻¹³ | 0,16 % |
| Los Ardillos - Los Tlacos | 2,5 × 10⁻¹³ | 0,11 % |
| M18 - MS-13 | 2,2 × 10⁻¹³ | 0,10 % |
| India: Kashmir | 2,2 × 10⁻¹³ | <0,1 % |
| Kuki - Meitei | 1,9 × 10⁻¹³ | <0,1 % |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 1,8 × 10⁻¹³ | <0,1 % |
| India: Government | 1,7 × 10⁻¹³ | <0,1 % |
| Russia (Soviet Union): Government | 8,3 × 10⁻¹⁴ | <0,1 % |
| MS-13 - Civilians | 8,0 × 10⁻¹⁴ | <0,1 % |
| CPI-Maoist - Civilians | 7,8 × 10⁻¹⁴ | <0,1 % |
| M18 - Civilians | 6,4 × 10⁻¹⁴ | <0,1 % |
| Indonesia: West Papua | 5,6 × 10⁻¹⁴ | <0,1 % |
| Los Rusos, UPOEG - Los Tlacos | 5,2 × 10⁻¹⁴ | <0,1 % |
| Jalisco Cartel New Generation - Civilians | 4,7 × 10⁻¹⁴ | <0,1 % |
| IS - Civilians | 4,4 × 10⁻¹⁴ | <0,1 % |
| Jalisco Cartel New Generation - Pájaros Sierra | 4,3 × 10⁻¹⁴ | <0,1 % |
| Russia - Ukraine | 4,1 × 10⁻¹⁴ | <0,1 % |
| PKK - Civilians | 3,7 × 10⁻¹⁴ | <0,1 % |
| Government of Mexico - Civilians | 3,6 × 10⁻¹⁴ | <0,1 % |
| Kashmir insurgents - Civilians | 3,4 × 10⁻¹⁴ | <0,1 % |
| Los Ardillos - Los Rojos | 3,1 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 3,0 × 10⁻¹⁴ | <0,1 % |
| OPM - Civilians | 2,7 × 10⁻¹⁴ | <0,1 % |
| Iran: Government | 1,8 × 10⁻¹⁴ | <0,1 % |
| Hindus (India) - Muslims (India) | 1,5 × 10⁻¹⁴ | <0,1 % |
| Government of India - Civilians | 1,3 × 10⁻¹⁴ | <0,1 % |
| Government of Egypt - Civilians | 1,0 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Sinaloa Cartel | 1,0 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Jalisco Cartel New Generation | 1,0 × 10⁻¹⁴ | <0,1 % |
| CATA - Codeta | 7,9 × 10⁻¹⁵ | <0,1 % |
| India: Western South East Asia | 7,3 × 10⁻¹⁵ | <0,1 % |
| Government of Indonesia - Civilians | 6,6 × 10⁻¹⁵ | <0,1 % |
| Yemen (North Yemen): Government | 5,4 × 10⁻¹⁵ | <0,1 % |
| Government of South Africa - Civilians | 5,2 × 10⁻¹⁵ | <0,1 % |
| Russia: Islamic State | 4,3 × 10⁻¹⁵ | <0,1 % |
| Myanmar (Burma): Kachin | 3,9 × 10⁻¹⁵ | <0,1 % |
| Myanmar (Burma): Government | 3,6 × 10⁻¹⁵ | <0,1 % |
| VHP - Civilians | 3,6 × 10⁻¹⁵ | <0,1 % |
| Egypt: Islamic State | 2,1 × 10⁻¹⁵ | <0,1 % |
| Iran: Islamic State | 2,0 × 10⁻¹⁵ | <0,1 % |
| India - Pakistan | 1,8 × 10⁻¹⁵ | <0,1 % |
| India: Nagaland | 1,8 × 10⁻¹⁵ | <0,1 % |
| NSCN-IM - Civilians | 1,8 × 10⁻¹⁵ | <0,1 % |
| PLFI - Civilians | 1,8 × 10⁻¹⁵ | <0,1 % |
| Guerreros Unidos - Los Tlacos | 1,7 × 10⁻¹⁵ | <0,1 % |
| Russia (Soviet Union): Chechnya | 1,7 × 10⁻¹⁵ | <0,1 % |
| Government of Iran - Civilians | 1,5 × 10⁻¹⁵ | <0,1 % |
| Suma | 2,2 × 10⁻¹⁰ | = la cifra principal, 2,2 × 10⁻¹⁰ |
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 | 2,2 × 10⁻⁶ | 85 % |
| Manufacture of basic metals | 7,5 × 10⁻⁸ | 2,9 % |
| Land transport and transport via pipelines | 6,5 × 10⁻⁸ | 2,5 % |
| Water transport | 4,4 × 10⁻⁸ | 1,7 % |
| Manufacture of other non-metallic mineral products | 4,4 × 10⁻⁸ | 1,7 % |
| Crop and animal production, hunting and related service activities | 3,6 × 10⁻⁸ | 1,4 % |
| Forestry and logging | 2,8 × 10⁻⁸ | 1,1 % |
| Warehousing and support activities for transportation | 2,7 × 10⁻⁸ | 1,0 % |
| Air transport | 1,6 × 10⁻⁸ | 0,61 % |
| Wholesale trade, except of motor vehicles and motorcycles | 9,2 × 10⁻⁹ | 0,35 % |
| Manufacture of fabricated metal products, except machinery and equipment | 5,3 × 10⁻⁹ | 0,20 % |
| Construction | 4,1 × 10⁻⁹ | 0,16 % |
| Manufacture of coke and refined petroleum products | 3,9 × 10⁻⁹ | 0,15 % |
| Manufacture of other transport equipment | 3,6 × 10⁻⁹ | 0,14 % |
| Electricity, gas, steam and air conditioning supply | 3,6 × 10⁻⁹ | 0,14 % |
| Postal and courier activities | 3,4 × 10⁻⁹ | 0,13 % |
| Retail trade, except of motor vehicles and motorcycles | 3,1 × 10⁻⁹ | 0,12 % |
| Manufacture of chemicals and chemical products | 2,5 × 10⁻⁹ | <0,1 % |
| Water collection, treatment and supply | 2,4 × 10⁻⁹ | <0,1 % |
| Security and investigation, service and landscape, office administrative and support activities | 2,0 × 10⁻⁹ | <0,1 % |
| Rental and leasing activities | 1,5 × 10⁻⁹ | <0,1 % |
| Sewerage, waste management, remediation activities | 1,5 × 10⁻⁹ | <0,1 % |
| Public administration and defence; compulsory social security | 1,4 × 10⁻⁹ | <0,1 % |
| Employment activities | 1,3 × 10⁻⁹ | <0,1 % |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 1,0 × 10⁻⁹ | <0,1 % |
| Manufacture of rubber and plastic products | 8,0 × 10⁻¹⁰ | <0,1 % |
| Legal and accounting activities; activities of head offices; management consultancy activities | 7,0 × 10⁻¹⁰ | <0,1 % |
| Manufacture of paper and paper products | 6,8 × 10⁻¹⁰ | <0,1 % |
| Manufacture of machinery and equipment n.e.c. | 5,7 × 10⁻¹⁰ | <0,1 % |
| Accommodation and food service activities | 5,2 × 10⁻¹⁰ | <0,1 % |
| Manufacture of computer, electronic and optical products | 4,5 × 10⁻¹⁰ | <0,1 % |
| Repair and installation of machinery and equipment | 4,2 × 10⁻¹⁰ | <0,1 % |
| Manufacture of food products; beverages and tobacco products | 4,0 × 10⁻¹⁰ | <0,1 % |
| Manufacture of motor vehicles, trailers and semi-trailers | 3,9 × 10⁻¹⁰ | <0,1 % |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 3,4 × 10⁻¹⁰ | <0,1 % |
| Manufacture of textiles, wearing apparel, leather and related products | 3,4 × 10⁻¹⁰ | <0,1 % |
| Manufacture of electrical equipment | 3,3 × 10⁻¹⁰ | <0,1 % |
| Architectural and engineering activities; technical testing and analysis | 2,4 × 10⁻¹⁰ | <0,1 % |
| Travel agency, tour operator reservation service and related activities | 2,3 × 10⁻¹⁰ | <0,1 % |
| Human health activities | 2,1 × 10⁻¹⁰ | <0,1 % |
| Real estate activities | 2,0 × 10⁻¹⁰ | <0,1 % |
| Advertising and market research | 1,6 × 10⁻¹⁰ | <0,1 % |
| Activities of membership organisations | 1,5 × 10⁻¹⁰ | <0,1 % |
| Repair of computers and personal and household goods | 1,5 × 10⁻¹⁰ | <0,1 % |
| Computer programming, consultancy, and information service activities | 1,5 × 10⁻¹⁰ | <0,1 % |
| Other personal service activities | 1,2 × 10⁻¹⁰ | <0,1 % |
| Financial service activities, except insurance and pension funding | 1,1 × 10⁻¹⁰ | <0,1 % |
| Printing and reproduction of recorded media | 1,0 × 10⁻¹⁰ | <0,1 % |
| Other professional, scientific and technical activities; veterinary activities | 9,9 × 10⁻¹¹ | <0,1 % |
| Manufacture of furniture; other manufacturing | 9,3 × 10⁻¹¹ | <0,1 % |
| Telecommunications | 7,9 × 10⁻¹¹ | <0,1 % |
| Sports activities and amusement and recreation activities | 7,1 × 10⁻¹¹ | <0,1 % |
| Fishing and aquaculture | 6,9 × 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 | 5,7 × 10⁻¹¹ | <0,1 % |
| Education | 4,7 × 10⁻¹¹ | <0,1 % |
| Activities auxiliary to financial services and insurance activities | 3,4 × 10⁻¹¹ | <0,1 % |
| Insurance, reinsurance and pension funding, except compulsory social security | 3,1 × 10⁻¹¹ | <0,1 % |
| Motion picture, video, television programme production; programming and broadcasting activities | 3,0 × 10⁻¹¹ | <0,1 % |
| Publishing activities | 2,3 × 10⁻¹¹ | <0,1 % |
| Scientific research and development | 2,0 × 10⁻¹¹ | <0,1 % |
| Residential care activities and social work activities without accommodation | 1,4 × 10⁻¹¹ | <0,1 % |
| Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use | 1,6 × 10⁻¹² | <0,1 % |
| Suma | 2,6 × 10⁻⁶ | = la cifra principal, 2,6 × 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 | 2,3 × 10⁻⁶ | 86 % |
| México | 2,1 × 10⁻⁷ | 7,8 % |
| Turquía | 3,6 × 10⁻⁸ | 1,4 % |
| Brasil | 3,1 × 10⁻⁸ | 1,2 % |
| Rusia | 2,5 × 10⁻⁸ | 0,95 % |
| Estados Unidos | 1,9 × 10⁻⁸ | 0,71 % |
| Corea del Sur | 8,5 × 10⁻⁹ | 0,32 % |
| Canadá | 8,1 × 10⁻⁹ | 0,31 % |
| Francia | 5,5 × 10⁻⁹ | 0,21 % |
| India | 4,0 × 10⁻⁹ | 0,15 % |
| Japón | 3,7 × 10⁻⁹ | 0,14 % |
| Italia | 3,6 × 10⁻⁹ | 0,14 % |
| Alemania | 3,3 × 10⁻⁹ | 0,13 % |
| España | 3,2 × 10⁻⁹ | 0,12 % |
| Indonesia | 2,9 × 10⁻⁹ | 0,11 % |
| Polonia | 2,6 × 10⁻⁹ | <0,1 % |
| Argentina | 1,8 × 10⁻⁹ | <0,1 % |
| Portugal | 1,5 × 10⁻⁹ | <0,1 % |
| Australia | 1,4 × 10⁻⁹ | <0,1 % |
| Rumanía | 9,9 × 10⁻¹⁰ | <0,1 % |
| Chequia | 9,0 × 10⁻¹⁰ | <0,1 % |
| Bulgaria | 8,9 × 10⁻¹⁰ | <0,1 % |
| Austria | 6,7 × 10⁻¹⁰ | <0,1 % |
| Grecia | 5,6 × 10⁻¹⁰ | <0,1 % |
| Chipre | 3,9 × 10⁻¹⁰ | <0,1 % |
| Bélgica | 3,8 × 10⁻¹⁰ | <0,1 % |
| Suecia | 3,6 × 10⁻¹⁰ | <0,1 % |
| Croacia | 3,4 × 10⁻¹⁰ | <0,1 % |
| Letonia | 3,3 × 10⁻¹⁰ | <0,1 % |
| Hungría | 3,3 × 10⁻¹⁰ | <0,1 % |
| Lituania | 2,8 × 10⁻¹⁰ | <0,1 % |
| Eslovaquia | 2,6 × 10⁻¹⁰ | <0,1 % |
| Dinamarca | 2,4 × 10⁻¹⁰ | <0,1 % |
| Noruega | 2,4 × 10⁻¹⁰ | <0,1 % |
| Países Bajos | 2,3 × 10⁻¹⁰ | <0,1 % |
| Suiza | 2,1 × 10⁻¹⁰ | <0,1 % |
| Finlandia | 2,0 × 10⁻¹⁰ | <0,1 % |
| Arabia Saudí | 1,9 × 10⁻¹⁰ | <0,1 % |
| Eslovenia | 1,7 × 10⁻¹⁰ | <0,1 % |
| Sudáfrica | 9,3 × 10⁻¹¹ | <0,1 % |
| Irlanda | 9,1 × 10⁻¹¹ | <0,1 % |
| Estonia | 7,8 × 10⁻¹¹ | <0,1 % |
| China | 4,4 × 10⁻¹¹ | <0,1 % |
| Luxemburgo | 4,3 × 10⁻¹¹ | <0,1 % |
| Reino Unido | 3,9 × 10⁻¹¹ | <0,1 % |
| Malta | 3,0 × 10⁻¹¹ | <0,1 % |
| Serbia | 1,6 × 10⁻¹⁴ | <0,1 % |
| Suma | 2,6 × 10⁻⁶ | = la cifra principal, 2,6 × 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.
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- 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.
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HumanToll 2026, ejecución 2259, metodología v1.0. https://quiescence.eu/humantoll/explain/glass/