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 — 9,8 × 10⁻⁸ por unidad(0,43–2,1 × 10⁻⁷)BAJAS-MAX · ejecución 2259 · metodología v1.0 · datos dv-20261007-44r
Vía monetaria — 5,8 × 10⁻⁵ por cada 1.000 € gastados en su industria(4,0–8,3 × 10⁻⁵)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 | 1,3 × 10⁻⁷ | 9,8 × 10⁻⁸ | 100 % |
| Suma | 9,8 × 10⁻⁸ | = la cifra principal, 9,8 × 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 |
|---|---|---|
| Italia | 2,3 × 10⁻⁸ | 24 % |
| Países Bajos | 1,6 × 10⁻⁸ | 16 % |
| Turquía | 1,3 × 10⁻⁸ | 14 % |
| Francia | 1,3 × 10⁻⁸ | 13 % |
| Alemania | 9,8 × 10⁻⁹ | 10 % |
| España | 9,0 × 10⁻⁹ | 9,1 % |
| Estados Unidos | 8,2 × 10⁻⁹ | 8,4 % |
| Argentina | 1,2 × 10⁻⁹ | 1,2 % |
| Bélgica | 8,1 × 10⁻¹⁰ | 0,83 % |
| Polonia | 6,3 × 10⁻¹⁰ | 0,64 % |
| Finlandia | 6,2 × 10⁻¹⁰ | 0,63 % |
| Japón | 5,7 × 10⁻¹⁰ | 0,58 % |
| Austria | 5,6 × 10⁻¹⁰ | 0,57 % |
| Canadá | 3,4 × 10⁻¹⁰ | 0,35 % |
| Chequia | 3,0 × 10⁻¹⁰ | 0,31 % |
| Bulgaria | 2,2 × 10⁻¹⁰ | 0,22 % |
| Australia | 1,9 × 10⁻¹⁰ | 0,20 % |
| Moldavia | 1,6 × 10⁻¹⁰ | 0,16 % |
| Letonia | 8,9 × 10⁻¹¹ | <0,1 % |
| México | 4,9 × 10⁻¹¹ | <0,1 % |
| Noruega | 1,2 × 10⁻¹¹ | <0,1 % |
| India | 2,2 × 10⁻¹² | <0,1 % |
| Guatemala | 1,1 × 10⁻¹² | <0,1 % |
| Rusia | 3,9 × 10⁻¹³ | <0,1 % |
| Indonesia | 2,7 × 10⁻¹³ | <0,1 % |
| Irán | 6,6 × 10⁻¹⁴ | <0,1 % |
| Sudáfrica | 3,9 × 10⁻¹⁴ | <0,1 % |
| Egipto | 3,8 × 10⁻¹⁴ | <0,1 % |
| Arabia Saudí | 1,6 × 10⁻¹⁴ | <0,1 % |
| China | 1,2 × 10⁻¹⁴ | <0,1 % |
| Suma | 9,8 × 10⁻⁸ | = la cifra principal, 9,8 × 10⁻⁸ |
3 · Por qué canal de daño
La misma cifra principal, por canal de daño: conflicto, trabajo, privación, exposición.
| Canal | Aportación | Parte |
|---|---|---|
| Trabajo | 9,8 × 10⁻⁸ | 100 % |
| Conflicto y violencia política | 6,3 × 10⁻¹¹ | <0,1 % |
| Suma | 9,8 × 10⁻⁸ | = la cifra principal, 9,8 × 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 |
|---|---|---|
| Sin ubicar | 9,8 × 10⁻⁸ | 100 % |
| Jalisco Cartel New Generation - Sinaloa Cartel | 1,2 × 10⁻¹¹ | <0,1 % |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 1,0 × 10⁻¹¹ | <0,1 % |
| Juarez Cartel - Sinaloa Cartel | 9,4 × 10⁻¹² | <0,1 % |
| Carteles Unidos - Jalisco Cartel New Generation | 7,1 × 10⁻¹² | <0,1 % |
| Turkey: Kurdistan | 5,9 × 10⁻¹² | <0,1 % |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 4,1 × 10⁻¹² | <0,1 % |
| DZ Mafia - Yoda | 3,0 × 10⁻¹² | <0,1 % |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 1,8 × 10⁻¹² | <0,1 % |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 1,1 × 10⁻¹² | <0,1 % |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 1,0 × 10⁻¹² | <0,1 % |
| Los Ardillos - Los Tlacos | 7,5 × 10⁻¹³ | <0,1 % |
| M18 - MS-13 | 6,7 × 10⁻¹³ | <0,1 % |
| India: Kashmir | 6,5 × 10⁻¹³ | <0,1 % |
| Kuki - Meitei | 5,6 × 10⁻¹³ | <0,1 % |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 5,4 × 10⁻¹³ | <0,1 % |
| India: Government | 5,2 × 10⁻¹³ | <0,1 % |
| Russia (Soviet Union): Government | 2,5 × 10⁻¹³ | <0,1 % |
| MS-13 - Civilians | 2,4 × 10⁻¹³ | <0,1 % |
| CPI-Maoist - Civilians | 2,3 × 10⁻¹³ | <0,1 % |
| M18 - Civilians | 1,9 × 10⁻¹³ | <0,1 % |
| Indonesia: West Papua | 1,7 × 10⁻¹³ | <0,1 % |
| Los Rusos, UPOEG - Los Tlacos | 1,6 × 10⁻¹³ | <0,1 % |
| Jalisco Cartel New Generation - Civilians | 1,4 × 10⁻¹³ | <0,1 % |
| IS - Civilians | 1,3 × 10⁻¹³ | <0,1 % |
| Jalisco Cartel New Generation - Pájaros Sierra | 1,3 × 10⁻¹³ | <0,1 % |
| Russia - Ukraine | 1,2 × 10⁻¹³ | <0,1 % |
| PKK - Civilians | 1,1 × 10⁻¹³ | <0,1 % |
| Government of Mexico - Civilians | 1,1 × 10⁻¹³ | <0,1 % |
| Kashmir insurgents - Civilians | 1,0 × 10⁻¹³ | <0,1 % |
| Los Ardillos - Los Rojos | 9,4 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 8,9 × 10⁻¹⁴ | <0,1 % |
| OPM - Civilians | 8,0 × 10⁻¹⁴ | <0,1 % |
| Iran: Government | 5,5 × 10⁻¹⁴ | <0,1 % |
| Hindus (India) - Muslims (India) | 4,4 × 10⁻¹⁴ | <0,1 % |
| Government of India - Civilians | 3,8 × 10⁻¹⁴ | <0,1 % |
| Government of Egypt - Civilians | 3,1 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Sinaloa Cartel | 3,1 × 10⁻¹⁴ | <0,1 % |
| Gulf Cartel - Jalisco Cartel New Generation | 3,1 × 10⁻¹⁴ | <0,1 % |
| CATA - Codeta | 2,4 × 10⁻¹⁴ | <0,1 % |
| India: Western South East Asia | 2,2 × 10⁻¹⁴ | <0,1 % |
| Government of Indonesia - Civilians | 2,0 × 10⁻¹⁴ | <0,1 % |
| Yemen (North Yemen): Government | 1,6 × 10⁻¹⁴ | <0,1 % |
| Government of South Africa - Civilians | 1,6 × 10⁻¹⁴ | <0,1 % |
| Russia: Islamic State | 1,3 × 10⁻¹⁴ | <0,1 % |
| Myanmar (Burma): Kachin | 1,2 × 10⁻¹⁴ | <0,1 % |
| Myanmar (Burma): Government | 1,1 × 10⁻¹⁴ | <0,1 % |
| VHP - Civilians | 1,1 × 10⁻¹⁴ | <0,1 % |
| Egypt: Islamic State | 6,3 × 10⁻¹⁵ | <0,1 % |
| Iran: Islamic State | 6,1 × 10⁻¹⁵ | <0,1 % |
| India - Pakistan | 5,4 × 10⁻¹⁵ | <0,1 % |
| India: Nagaland | 5,4 × 10⁻¹⁵ | <0,1 % |
| NSCN-IM - Civilians | 5,4 × 10⁻¹⁵ | <0,1 % |
| PLFI - Civilians | 5,4 × 10⁻¹⁵ | <0,1 % |
| Guerreros Unidos - Los Tlacos | 5,2 × 10⁻¹⁵ | <0,1 % |
| Russia (Soviet Union): Chechnya | 5,2 × 10⁻¹⁵ | <0,1 % |
| Government of Iran - Civilians | 4,6 × 10⁻¹⁵ | <0,1 % |
| Suma | 9,8 × 10⁻⁸ | = la cifra principal, 9,8 × 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 |
|---|---|---|
| Manufacture of other non-metallic mineral products | 2,4 × 10⁻⁵ | 40 % |
| Mining and quarrying | 1,2 × 10⁻⁵ | 20 % |
| Wholesale trade, except of motor vehicles and motorcycles | 2,7 × 10⁻⁶ | 4,6 % |
| Land transport and transport via pipelines | 2,5 × 10⁻⁶ | 4,3 % |
| Warehousing and support activities for transportation | 1,6 × 10⁻⁶ | 2,7 % |
| Security and investigation, service and landscape, office administrative and support activities | 1,4 × 10⁻⁶ | 2,4 % |
| Manufacture of chemicals and chemical products | 1,2 × 10⁻⁶ | 2,0 % |
| Construction | 1,0 × 10⁻⁶ | 1,8 % |
| Manufacture of basic metals | 9,4 × 10⁻⁷ | 1,6 % |
| Rental and leasing activities | 8,5 × 10⁻⁷ | 1,5 % |
| Manufacture of coke and refined petroleum products | 8,5 × 10⁻⁷ | 1,5 % |
| Retail trade, except of motor vehicles and motorcycles | 7,9 × 10⁻⁷ | 1,4 % |
| Employment activities | 7,2 × 10⁻⁷ | 1,2 % |
| Water transport | 5,9 × 10⁻⁷ | 1,0 % |
| Sewerage, waste management, remediation activities | 5,6 × 10⁻⁷ | 0,96 % |
| Accommodation and food service activities | 4,8 × 10⁻⁷ | 0,82 % |
| Manufacture of fabricated metal products, except machinery and equipment | 4,7 × 10⁻⁷ | 0,81 % |
| Manufacture of rubber and plastic products | 4,4 × 10⁻⁷ | 0,76 % |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 4,1 × 10⁻⁷ | 0,70 % |
| Crop and animal production, hunting and related service activities | 3,9 × 10⁻⁷ | 0,66 % |
| Electricity, gas, steam and air conditioning supply | 3,4 × 10⁻⁷ | 0,58 % |
| Manufacture of paper and paper products | 3,4 × 10⁻⁷ | 0,58 % |
| Legal and accounting activities; activities of head offices; management consultancy activities | 3,4 × 10⁻⁷ | 0,58 % |
| Manufacture of machinery and equipment n.e.c. | 3,3 × 10⁻⁷ | 0,57 % |
| Manufacture of motor vehicles, trailers and semi-trailers | 2,7 × 10⁻⁷ | 0,46 % |
| Manufacture of food products; beverages and tobacco products | 2,6 × 10⁻⁷ | 0,45 % |
| Repair and installation of machinery and equipment | 2,5 × 10⁻⁷ | 0,43 % |
| Air transport | 2,4 × 10⁻⁷ | 0,42 % |
| Postal and courier activities | 2,2 × 10⁻⁷ | 0,38 % |
| Public administration and defence; compulsory social security | 2,1 × 10⁻⁷ | 0,36 % |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 1,9 × 10⁻⁷ | 0,33 % |
| Forestry and logging | 1,9 × 10⁻⁷ | 0,32 % |
| Manufacture of electrical equipment | 1,9 × 10⁻⁷ | 0,32 % |
| Manufacture of textiles, wearing apparel, leather and related products | 1,8 × 10⁻⁷ | 0,31 % |
| Manufacture of computer, electronic and optical products | 1,6 × 10⁻⁷ | 0,28 % |
| Travel agency, tour operator reservation service and related activities | 1,5 × 10⁻⁷ | 0,26 % |
| Architectural and engineering activities; technical testing and analysis | 1,4 × 10⁻⁷ | 0,24 % |
| Human health activities | 1,2 × 10⁻⁷ | 0,21 % |
| Water collection, treatment and supply | 1,0 × 10⁻⁷ | 0,18 % |
| Manufacture of other transport equipment | 8,4 × 10⁻⁸ | 0,14 % |
| Advertising and market research | 7,3 × 10⁻⁸ | 0,13 % |
| Computer programming, consultancy, and information service activities | 6,9 × 10⁻⁸ | 0,12 % |
| Financial service activities, except insurance and pension funding | 6,6 × 10⁻⁸ | 0,11 % |
| Printing and reproduction of recorded media | 6,1 × 10⁻⁸ | 0,11 % |
| Manufacture of basic pharmaceutical products and pharmaceutical preparations | 6,0 × 10⁻⁸ | 0,10 % |
| Manufacture of furniture; other manufacturing | 5,9 × 10⁻⁸ | 0,10 % |
| Activities of membership organisations | 5,5 × 10⁻⁸ | <0,1 % |
| Other professional, scientific and technical activities; veterinary activities | 5,4 × 10⁻⁸ | <0,1 % |
| Real estate activities | 5,3 × 10⁻⁸ | <0,1 % |
| Repair of computers and personal and household goods | 4,3 × 10⁻⁸ | <0,1 % |
| Education | 4,1 × 10⁻⁸ | <0,1 % |
| Sports activities and amusement and recreation activities | 4,1 × 10⁻⁸ | <0,1 % |
| Telecommunications | 3,4 × 10⁻⁸ | <0,1 % |
| Other personal service activities | 3,2 × 10⁻⁸ | <0,1 % |
| Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities | 3,0 × 10⁻⁸ | <0,1 % |
| Residential care activities and social work activities without accommodation | 2,4 × 10⁻⁸ | <0,1 % |
| Insurance, reinsurance and pension funding, except compulsory social security | 2,0 × 10⁻⁸ | <0,1 % |
| Activities auxiliary to financial services and insurance activities | 1,9 × 10⁻⁸ | <0,1 % |
| Scientific research and development | 1,4 × 10⁻⁸ | <0,1 % |
| Motion picture, video, television programme production; programming and broadcasting activities | 1,1 × 10⁻⁸ | <0,1 % |
| Publishing activities | 1,1 × 10⁻⁸ | <0,1 % |
| Fishing and aquaculture | 5,1 × 10⁻⁹ | <0,1 % |
| Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use | 2,6 × 10⁻¹¹ | <0,1 % |
| Suma | 5,8 × 10⁻⁵ | = la cifra principal, 5,8 × 10⁻⁵ |
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 |
|---|---|---|
| Turquía | 1,4 × 10⁻⁵ | 24 % |
| Sin ubicar | 1,3 × 10⁻⁵ | 22 % |
| Alemania | 6,0 × 10⁻⁶ | 10 % |
| España | 3,9 × 10⁻⁶ | 6,7 % |
| Estados Unidos | 3,6 × 10⁻⁶ | 6,2 % |
| Francia | 3,1 × 10⁻⁶ | 5,3 % |
| Italia | 2,4 × 10⁻⁶ | 4,2 % |
| Argentina | 2,1 × 10⁻⁶ | 3,6 % |
| Canadá | 1,8 × 10⁻⁶ | 3,1 % |
| Portugal | 1,4 × 10⁻⁶ | 2,5 % |
| Polonia | 9,3 × 10⁻⁷ | 1,6 % |
| Australia | 8,4 × 10⁻⁷ | 1,4 % |
| Japón | 7,1 × 10⁻⁷ | 1,2 % |
| México | 6,2 × 10⁻⁷ | 1,1 % |
| Chequia | 4,9 × 10⁻⁷ | 0,84 % |
| Suiza | 4,2 × 10⁻⁷ | 0,72 % |
| Austria | 4,2 × 10⁻⁷ | 0,72 % |
| Países Bajos | 4,1 × 10⁻⁷ | 0,70 % |
| Bélgica | 4,0 × 10⁻⁷ | 0,70 % |
| Suecia | 2,3 × 10⁻⁷ | 0,40 % |
| Hungría | 2,0 × 10⁻⁷ | 0,34 % |
| Dinamarca | 2,0 × 10⁻⁷ | 0,34 % |
| Finlandia | 2,0 × 10⁻⁷ | 0,34 % |
| Eslovenia | 1,4 × 10⁻⁷ | 0,24 % |
| Croacia | 1,1 × 10⁻⁷ | 0,19 % |
| Brasil | 9,2 × 10⁻⁸ | 0,16 % |
| Eslovaquia | 9,0 × 10⁻⁸ | 0,16 % |
| Irlanda | 8,4 × 10⁻⁸ | 0,14 % |
| Noruega | 7,9 × 10⁻⁸ | 0,14 % |
| Estonia | 6,1 × 10⁻⁸ | 0,11 % |
| Lituania | 4,9 × 10⁻⁸ | <0,1 % |
| Rumanía | 4,0 × 10⁻⁸ | <0,1 % |
| Grecia | 3,8 × 10⁻⁸ | <0,1 % |
| Bulgaria | 3,2 × 10⁻⁸ | <0,1 % |
| Letonia | 3,2 × 10⁻⁸ | <0,1 % |
| Luxemburgo | 3,1 × 10⁻⁸ | <0,1 % |
| Rusia | 2,8 × 10⁻⁸ | <0,1 % |
| Chipre | 1,9 × 10⁻⁸ | <0,1 % |
| Malta | 1,5 × 10⁻⁸ | <0,1 % |
| India | 1,2 × 10⁻⁸ | <0,1 % |
| Indonesia | 8,7 × 10⁻⁹ | <0,1 % |
| Arabia Saudí | 5,7 × 10⁻¹⁰ | <0,1 % |
| Sudáfrica | 2,8 × 10⁻¹⁰ | <0,1 % |
| China | 1,3 × 10⁻¹⁰ | <0,1 % |
| Reino Unido | 1,2 × 10⁻¹⁰ | <0,1 % |
| Corea del Sur | 3,0 × 10⁻¹¹ | <0,1 % |
| Serbia | 4,9 × 10⁻¹⁴ | <0,1 % |
| Suma | 5,8 × 10⁻⁵ | = la cifra principal, 5,8 × 10⁻⁵ |
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.
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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.
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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 — 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/