Farming
Rice
Where it comes from, what share of an industry’s output it is, and which wars the model links to it.
This page shows production, shares and inputs. It does not show a death toll per tonne. The shares below say what part of an industry’s output this material is, and what part of a war’s harm the model links to it. Multiplying either by a number of people gives a result, and no result is published until it comes from a recorded calculation, with a range and a confidence grade.
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The products it reaches
Each product whose list of materials contains Rice, with its deaths per item by the materials method and the part of that figure this material accounts for.
Scenario Economic-embedded, using FIGARO 2023.
In this calculation, no product’s figure reaches it.
Deaths per tonne produced are calculated for this material too, but not shown: that figure has no range yet.
Who produces it
The publisher’s own figures for 2024, across 139 countries. Nothing here has been linked to anything yet.
| Country | Produced | Share | Figure |
|---|---|---|---|
| India IND |
217,867,864 t | 26.6% | official |
| China CHN |
207,530,000 t | 25.4% | official |
| Bangladesh BGD |
60,570,453 t | 7.4% | official |
| Indonesia IDN |
53,142,727 t | 6.5% | official |
| Viet Nam VNM |
43,450,449 t | 5.3% | official |
| Thailand THA |
33,551,337 t | 4.1% | official |
| Myanmar MMR |
27,650,000 t | 3.4% | gap filled |
| Philippines PHL |
19,087,135 t | 2.3% | official |
| Pakistan PAK |
14,585,231 t | 1.8% | official |
| Cambodia KHM |
14,200,000 t | 1.7% | gap filled |
| Brazil BRA |
10,671,490 t | 1.3% | official |
| Japan JPN |
10,142,000 t | 1.2% | estimated |
| United States USA |
10,075,780 t | 1.2% | official |
| Nigeria NGA |
9,129,900 t | 1.1% | official |
| Egypt, Arab Rep. EGY |
6,430,000 t | 0.8% | gap filled |
Production figures: FAO, FAOSTAT, CC BY 4.0. FAO does not endorse any figure made from them, and none is implied.
What share of an industry’s output it is
Worked out from production, not typed in: an industry’s split between materials is the share of what it actually produced. These are WORLD figures, all years together; the model itself uses a separate mix for every country and year, because a world mix would link deaths in the Congo to copper mined in Chile.
| Industry | Share of output | How |
|---|---|---|
| Crop and animal production, hunting and related service activities 01 |
13.2% | world mix · LOW |
| Agriculture, forestry and fishing A |
13.1% | world mix · LOW |
Weight and value answer different questions and are never added together. A tonne of gold weighs the same as a tonne of iron ore but is worth far more, so the share of an industry’s harm this material gets depends on which one is used.
Which wars the model links to it
The average share of each war’s harm that the model links to this material, taken over the countries and years the war covers. An average of shares is not a share of a total, and the two differ whenever the coverage is uneven.
| War | Average share of its harm | Years |
|---|---|---|
| Sri Lanka (Ceylon): Eelam | 58.21% | 21 |
| Mali: Government | 15.04% | 9 |
| Mali: Islamic State | 14.72% | 9 |
| Nigeria: Government | 6.59% | 17 |
| Afghanistan: Government | 6.39% | 37 |
| Burkina Faso: Government | 4.43% | 9 |
| Burkina Faso: Islamic State | 4.43% | 9 |
| Government of Rwanda - Civilians | 3.89% | 22 |
| Niger: Government | 3.77% | 9 |
| Niger: Islamic State | 3.77% | 9 |
| DR Congo (Zaire): Government | 2.51% | 26 |
| Colombia: Government | 1.92% | 37 |
These are shares of a war, not counts of people. The number of deaths they stand for is calculated but not published: it has no range yet and has not passed the test on past years.
Harm per tonne and per euro
Harm per tonne and harm per euro are both calculated. Neither is shown yet.
Harm per tonne of this material is defined for 55 years, 1970 to 2024: the years for which the model has both the harm and the world production of this material.
Both are numbers of people divided by an amount, from a calculation that has no range and has not passed the test on past years yet, and nothing of that kind is published until it has. What this page can say now is whether each can be worked out, and on what basis.
What producing it uses up
What one t of this material uses up, from published technical figures. Where the data allows, a figure for a particular country replaces the world figure shown here.
| Input | Per unit | Source |
|---|---|---|
| Fresh water | 2,497 m3 | Mekonnen, M.M. & Hoekstra, A.Y. (2011), "The green, blue and… · LOW |
Fresh water: Global average, green + blue + grey. The same paper gives country figures varying by a factor of five; using the global average here is the fallback plan/14 S13 warns about, and it is marked global and LOW so that a country result can say so.
Sources
| Version of the data | Downloaded | File fingerprint |
|---|---|---|
| faostat · qcl-20251231 | 2026-09-29 | c5835418c18f9322… |
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.