Deploy Seaweed Farming for Food involves cultivating seaweed (often called macroalgae) in the ocean for human consumption as a partial replacement for low-protein foods grown on land (e.g., grains, vegetables). This solution considers the emissions avoided by substituting one kilogram of low-protein food with one kilogram of seaweed. Current evidence suggests that farming seaweed for food could result in lower greenhouse gas emissions compared to some terrestrial crops. Advantages include the potential to reduce land-based agricultural impacts, improve water quality, and achieve globally meaningful climate impacts at a smaller spatial scale than growing seaweed for carbon removal by sinking (see Deploy Ocean Biomass Sinking). Disadvantages include potential adverse effects on marine ecosystems, uncertain climate benefits due to limited data on effectiveness, and opportunity costs if seaweed used for food could have delivered a greater climate impact in other emerging uses. Based on our assessment, we will “Keep Watching” this potential solution.
The overall effectiveness of seaweed cultivation for food as a climate solution remains uncertain. It could deliver climate benefits at modest cultivation scales while providing a useful end product. Expansion could also benefit land and food systems by reducing agricultural pressures, but it may introduce environmental trade-offs in the ocean that are not yet well understood. We will “Keep Watching” this solution.
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | Yes |
| Evidence | Are there data to evaluate it? | Limited |
| Effective | Does it consistently work? | ? |
| Impact | Is it big enough to matter? | ? |
| Risk | Is it risky or harmful? | ? |
| Cost | Is it cheap? | ? |
This solution involves expanding the cultivation of marine seaweed for human consumption as an alternative to higher-emission, lower-protein foods. These can include grains (e.g., wheat, rye, maize, oats, and rice) and, to a lesser extent, vegetables (e.g., potatoes, cassava, broccoli, and cabbage). By switching part of food production from land to ocean systems, seaweed farming helps avoid some sources of terrestrial agricultural emissions, such as those from fertilizer, irrigation, and soil disturbance. Seaweed cultivation, at modest scales and in suitable locations, does not require additional nutrients or irrigation, which can result in lower emissions. Emissions from physical cultivation activities also differ, with tractor use in land-based agriculture being replaced by emissions from boat operations in seaweed farming. Currently, roughly 80% of cultivated seaweed is consumed by humans in food products.
The climate impact of cultivating seaweed is understudied, but existing estimates suggest that growing a ton of seaweed generates less than a quarter of the emissions from growing a ton of vegetables, such as broccoli and cabbage. The actual climate impact will depend on which types of foods are displaced in diets. Replacing higher-emission, low-protein foods, such as some grain-based staples (e.g., bread or rice), with seaweed could provide even greater climate benefits. More data are needed to assess full cradle-to-grave emissions for seaweed that include transport, processing, and storage prior to consumption. Actual benefits may be lower once full life cycle emissions are considered, or higher if seaweed replaces more emissions-intensive foods.
Unlike terrestrial crops, seaweed cultivation does not require fresh water for irrigation or pesticides for pest management. It is the fastest-growing sector of global aquaculture, and can produce higher biomass yields per area than some land-based crops. Because it grows in the ocean, seaweed farming reduces land demand, which can therefore support terrestrial biodiversity and conservation efforts. If deployed in the right place, seaweed cultivation can also help reduce nutrient pollution in coastal areas.
Compared with other seaweed-based climate solutions, farming seaweed for food could achieve a meaningful global climate impact using far less ocean area (1–2 Mha versus 6–7 Mha estimated for solutions like Deploy Ocean Biomass Sinking), though estimates remain highly uncertain. Cultivation might also provide additional carbon removal benefits by selecting for high-productivity cultivars and strategically placing farms in areas where carbon fixation and burial are naturally high.
Finally, global diets currently overrely on starch-rich grain crops, highlighting a potential opportunity for seaweed, which is a nutritious source of protein, essential fatty acids, and minerals, to replace these foods and diversify diets in many regions. Across commonly consumed species, seaweeds are generally low in fat and calories and can be rich in fiber and micronutrients, including iron, iodine, calcium, and magnesium.
There are several environmental and feasibility concerns associated with seaweed cultivation, especially if it is expanded to use large areas of ocean habitat. Global estimates of ocean area suitable for seaweed cultivation range substantially, from 10 to 4,800 Mha, but often lack consideration for real-world nutrient limitations or ecological impacts. A more recent analysis that considers nitrogen, phosphorus, and iron limitations suggests that the viable ocean seaweed farming area is closer to 400 Mha. If regions are prioritized based on where cultivation is not nutrient-limited, where it can achieve high carbon removal efficiency, and where there are lower risks of adverse ecological impacts, potential seaweed farming areas could be limited to the western North Pacific and North Atlantic. The costs of such an expansion are also poorly understood, with some cost estimates per ton of CO₂
fairly high.
Similarly, it’s unclear how viable seaweed is as a large-scale substitute for low-protein foods in real-world diets. Using vegetables as an example, achieving a climate impact of at least 0.1 Gt CO₂‑eq/yr
could require replacing over 25% of global vegetable production. Assuming productivity typical of subtidal seaweed (6.6 t C/ha/yr), this would translate to an additional ~2.6 Mha of ocean cultivation. An area of 2.6 Mha would equate to a 100-meter-wide continuous belt of seaweed cultivation along 22% of the global coastline. For comparison, seaweed cultivation currently covers less than 400,000 ha.
At large scales, seaweed cultivation could alter food webs through competition with phytoplankton for nutrients and/or requiring external nutrient inputs, raising serious concerns similar to Deploy Ocean Biomass Sinking. Cultivation can have a range of other negative impacts on coastal ecosystems, too. Seaweed farms established in or near seagrass beds, for instance, can displace existing habitats and species. More research is needed to assess these trade-offs, including the spatial scale required for a globally meaningful climate impact and how seaweed cultivation relates to potential land-use benefits. Further work is also needed to evaluate whether seaweed cultivation could deliver greater climate benefits through other emerging products, rather than as a direct food replacement.
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Jones, B. L. H., Eklöf, J. S., Unsworth, R. K. F., Coals, L., Christianen, M. J. A., Clifton, J., Cullen-Unsworth, L. C., de la Torre-Castro, M., Esteban, N., Huxham, M., Jiddawi, N. S., McKenzie, L. J., Nakaoka, M., Nordlund, L. M., Ooi, J. L. S., & Prathep, A. (2025). Risks of habitat loss from seaweed cultivation within seagrass. Proceedings of the National Academy of Sciences, 122(8), Article e2426971122. Link to source: https://doi.org/10.1073/pnas.2426971122
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Reduce Overfishing refers to the use of management actions that decrease fishing effort and therefore cut CO₂ emissions from fishing vessel fuel use on overfished stocks. Advantages include the potential to replenish depleted fish stocks, support ecosystem health, and enhance long-term food and job security. Disadvantages include the short-term reductions in fishing effort needed to allow systems to recover, which could impact local livelihoods and economies. While these interventions are not expected to reach globally meaningful levels of emissions reductions (>0.1 Gt CO₂‑eq/yr ), we conclude that Reduce Overfishing is “Worthwhile” with important ecosystem and social benefits.
Our analysis concludes that, despite its limited global impact for reducing emissions, Reduce Overfishing is a “Worthwhile” climate solution that has other important benefits for ecosystem health and long-term food security.
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | Yes |
| Evidence | Are there data to evaluate it? | Yes |
| Effective | Does it consistently work? | Yes |
| Impact | Is it big enough to matter? | No |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | ? |
Reducing overfishing lowers fuel use and CO₂ emissions from wild capture fishing vessels by reducing fishing effort on overfished stocks. This is typically achieved through management actions, such as seasonal closures, gear restrictions, and catch limits. Fishing effort, whether measured as the hours spent fishing or distance traveled, is generally proportional to fuel use. In addition to immediate reductions in emissions, reducing overfishing can allow overfished stocks to recover, which can lead to reduced future emissions since fuel use is lowered when fish are easier to catch and harvested sustainably.
Reducing fishing effort in locations with depleted and overfished wild fish stocks is expected to reduce emissions from fishing vessels. When stocks are overfished, fishers must exert additional effort, traveling further and/or searching longer to make the same catch, which increases fuel use and CO₂ emissions. Reducing overfishing through management actions, such as harvest control rules, gear restrictions, seasonal closures, stronger enforcement of existing regulations, and establishment of marine protected areas, can help fish stocks recover. Other policy tools, such as reducing harmful fuel subsidies that currently enable many otherwise unprofitable fishing fleets, are also likely to result in lower fuel use and CO₂ emissions. Healthy fish stocks can be caught with lower fishing effort, translating to future fuel savings and reduced CO₂ emissions. Global estimates suggest that reductions in overfishing could avoid up to 0.08 Gt CO₂‑eq/yr, representing almost half of the entire capture fisheries sector's annual emissions (0.18 Gt CO₂‑eq/yr ).
Currently, overfishing affects more than 35% of global wild marine fish stocks, increasing by 1%, on average, every year. Reducing overfishing not only lowers fuel use and emissions but also allows overfished stocks to recover. Healthy fish stocks strengthen marine food webs and contribute to ecosystem resilience and biodiversity. Overfishing has widespread consequences for diverse marine ecosystems, such as kelp forests, where declines in fish have led to overgrazing of the kelp by sea urchins. Over time, management interventions will also likely improve the sustainability and long-term reliability of coastal livelihoods and food security by supporting sustainable fisheries.
Policy and management tools for reducing overfishing and, by extension, fishing-related emissions come with some challenges. For instance, management measures or legal protections may not be fully effective if implementation or enforcement is weak. Management and enforcement can be particularly challenging on the high seas, where jurisdiction is limited or shared across many nations, and where illegal, unreported, and unregulated fishing can be widespread. Even when effective, fish stock recovery can take years to decades, and the costs and trade-offs are unlikely to be evenly distributed across fishing fleets. In the short term, efforts to reduce overfishing could create economic challenges for small-scale fishers who may have fewer resources and less capacity to adapt to management restrictions.
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Improved manure management refers to the use of impermeable covers and physical or chemical treatments applied during the storage and processing of wet manure. These techniques can reduce methane emissions under anaerobic storage conditions and nitrous oxide emissions under aerobic conditions. They offer multiple environmental benefits, including reduced air pollution, reduced nutrient leaching and eutrophication of downstream aquatic systems, and reduced demand for energy-intensive synthetic fertilizers. Disadvantages include a relatively small climate impact and, except for covers, high costs. Even at an optimistic level of adoption, the climate impact is unlikely to be globally meaningful (<0.1 Gt CO₂‑eq/yr ). Despite this modest climate impact, we conclude that Improve Manure Management is a “Worthwhile” solution.
Based on our analysis, improved manure management using impermeable covers and physical or chemical treatments will reduce emissions, although not by a globally meaningful amount. However, because these manure management techniques are broadly available, we conclude this climate solution is “Worthwhile.”
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | Yes |
| Evidence | Are there data to evaluate it? | Yes |
| Effective | Does it consistently work? | Yes |
| Impact | Is it big enough to matter? | No |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | ? |
Manure generated from industrial livestock production contains significant quantities of organic carbon and nitrogen. Under low-oxygen conditions, bacteria convert organic material in manure to methane through anaerobic decomposition. Liquid manure, particularly from pigs and cows, produces significant quantities of methane. In oxygen-rich conditions, organic nitrogen in manure undergoes chemical reactions to produce nitrous oxide. Once produced, these GHGs diffuse towards the surface of the manure storage tank, where they are emitted into the atmosphere.
Improved manure management interrupts the production or release of methane and nitrous oxide through a structural barrier, or physical or chemical treatment processes. Manure storage covers made from impermeable synthetic materials effectively prevent the release of GHGs, and can be utilized in conjunction with biogas systems for energy generation. Chemical treatments, such as acidification and the addition of additives, suppress microbial activity, thereby inhibiting methane and nitrous oxide production. Physical processes, such as aeration and temperature reduction, similarly limit optimal conditions for microbial growth. Separating the solids and liquids from manure can also reduce the potential for methane production, enabling more effective solutions such as composting and anaerobic digestion.
Available technologies for manure management are mature and market-ready. However, empirical evidence of their effectiveness for reducing methane emissions is limited. Pilot studies indicate high effectiveness of manure acidification, moderate effectiveness of impermeable synthetic covers, and low effectiveness of manure additives. Except for the use of natural and synthetic impermeable covers, the overall adoption of these techniques is low.
Improved manure management can provide environmental benefits by reducing air pollution, preventing nutrient leaching from organic solids that settle into sludge, mitigating eutrophication in downstream aquatic ecosystems, and preventing soil acidification. In the food system, manure management allows for better alignment between crop needs and natural fertilizer characteristics. Since hauling liquid manure is expensive, manure storage and treatment methods promote efficient nutrient cycling and reduce the need for energy-intensive synthetic fertilizers. Abated methane in manure also limits ground-level ozone production upon application, thereby improving crop yields.
At the farm scale, the wide range of treatment options allows for a high level of customization in the manure management process to achieve joint goals of nutrient management, revenue generation, and emission reductions. Covers also directly mitigate risks to farmworker health and safety from manure handling, and manure treatment can further limit exposure to irritants and noxious gases, improving the health of surrounding communities.
Compared to no treatment and other manure-related solutions, such as composting and anaerobic digesters, evidence for the effectiveness of impermeable covers and manure treatment technologies is limited. At realistic levels of adoption, improving manure management is unlikely to have a globally meaningful climate impact (<0.1 Gt CO₂‑eq/yr ). High costs are also a key barrier to wider adoption, ranging from US$110–145/t CO₂‑eq for synthetic covers to US$500–3,000/t CO₂‑eq for other treatments.
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Rice production is a significant source of methane emissions and a minor source of nitrous oxide emissions. Most rice production occurs in flooded fields called paddies, where anaerobic conditions trigger high levels of methane production. This solution includes two related practices that each reduce emissions from paddy rice production: noncontinuous flooding and nutrient management. Noncontinuous flooding is a water management technique that reduces the amount of time rice paddy soils spend fully saturated, thereby reducing methane. Unfortunately, noncontinuous flooding increases nitrous oxide emissions. Nutrient management helps to address this challenge by controlling the timing, amount, and type of fertilization to maximize plant uptake and minimize nitrous oxide emissions.
Rice is a staple crop of critical importance, occupying 11% of global cropland (FAOstat 2025). Rice production has higher GHG emissions than most crop production, accounting for 9% of all anthropogenic methane and 10% of cropland nitrous oxide (Wang et al., 2020). Nabuurs et al. (2022) found methane emissions from global rice production to be 0.8–1.0 Gt CO₂‑eq/yr and growing 0.4% annually.
Rice paddy systems are fields with berms and plumbing to permit the flooding of rice for the production periods, which helps with weed and pest control (rice thrives in flooded conditions, though it does not require them). Paddy rice is the main source of methane from rice production. Upland rice is grown outside of paddies and does not produce significant methane emissions, so we excluded it from this analysis. Irrigated paddies are provided with irrigation water, while rain-fed paddies are only filled by rainfall and runoff (Raffa, 2021). For this analysis, we considered both irrigated and rain-fed paddies.
Flooded rice paddies encourage the production of methane by microbes. Conventional paddy rice production uses continuous flooding, in which the paddy is flooded for the full rice production period. Several approaches can reduce methane, with the most widespread being noncontinuous flooding. This is a collection of practices (such as alternate wetting and drying) that drain the fields one or more times during the rice production period. As a result, the paddy spends less time in its methane-producing state. This can be done without reducing rice yields in many, but not all, cases, and also significantly reduces irrigation water use (Bo et al., 2022). Impacts on yields depend on soils, climate, and other variables (Cheng et al., 2022).
A major drawback to noncontinuous flooding is that it increases nitrous oxide emissions from fertilizer compared to continuous flooding. High nitrogen levels in flooded paddies encourage the growth of bacteria that produce methane, reduce the natural breakdown of methane, and facilitate emissions of nitrous oxide to the atmosphere (Li et al., 2024). The effect is small compared to the mitigated emissions from methane reduction (Jiang et al., 2019), but remains serious. Use of nutrient management techniques, such as controlling fertilizer amount, type (e.g., controlled-release urea), timing, and application techniques (e.g., deep fertilization), can reduce these emissions. This is in part because nitrogen fertilizers are often overapplied, leaving room to increase efficiency without reducing rice yields (Hergoualc’h et al., 2019; Li et al., 2024).
Other practices also show potential but were not included in our analysis. These include the application of biochar to rice paddies and the use of rice cultivars that produce fewer emissions (Qian et al., 2023). Other approaches include saturated soil culture, System of Rice Intensification (“SRI”), ground-cover systems, raised beds, and improved irrigation and paddy infrastructure (Surendran et al., 2021).
Note that some practices, such as incorporating rice straw or the use of compost or manure, can increase nitrous oxide emissions (Li et al., 2024).
There is also evidence that, under some circumstances, noncontinuous flooding can sequester soil organic carbon by increasing soil organic matter. However, there are not enough data available to quantify this (Qian et al., 2023). Indeed, one meta-analysis found that noncontinuous flooding can actually lead to a decrease in soil organic carbon (Livsey et al., 2019). One complication is that many production areas plant rice two or even three times per year, and data are typically presented on a per-harvest or even per-flooded day basis. To overcome this challenge, we use data on the percentage of global irrigated rice land in single, double, and triple cropping from Carlson et al. (2016) to create weighted average values as appropriate.
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Eric Toensmeier
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Aiyana Bodi
James Gerber, Ph.D.
Hannah Henkin
Zoltan Nagy, Ph.D.
Ted Otte
Paul C. West, Ph.D.
Methane Reduction
We calculated per-hectare methane emissions using Intergovernmental Panel on Climate Change (IPCC) methodology (Ogle et. al, 2019). To develop regional emissions per rice harvest, we multiplied standard regional daily baseline emissions by standard cultivation period lengths, then multiplied by the mean scaling factor for noncontinuous flooding systems. However, the total number of rice harvests per year ranged from one to three. Carlson et al. (2016) reported a global figure of harvests on rice fields: 42% were harvested once, 50% were harvested twice, and 8% were harvested three times. We used this to develop a weighted average methane emissions figure for each region. National effectiveness ranged from 1.55 to 3.29 t CO₂‑eq /ha/yr (Table 1a).
Nitrous Oxide Reduction
Using data from Adalibieke et al. (2024) and Gerber et al. (2024), we calculated the current country-level rate of nitrogen application per hectare and a target rate reflecting improved efficiency through nutrient management. For a full methodology, see the Appendix.
In noncontinuously flooded systems, nitrous oxide emissions are 1.66 times higher per t of nitrogen applied (Hergoualc’h et al., 2019). Using the different emissions factors, we calculated total nitrous oxide emissions for 1) flooded rice with current nitrogen application rates, and 2) noncontinuously flooded rice with target nitrogen application rates.
The effectiveness of nutrient management for each country with over 100,000 ha of rice production ranged from –0.48 to 0.11 t CO₂‑eq /ha/yr (Table 1).
Combined Reduction
Combined effectiveness of methane and nitrous oxide reduction was 1.49–3.39 t CO₂‑eq /ha/yr (Table 1).
Table 1a. Combined effectiveness at reducing emissions, by country, for noncontinuous flooding with nutrient management.
Unit: t CO₂‑eq /ha/yr
| Afghanistan | 1.63 |
| Argentina | 2.70 |
| Bangladesh | 1.63 |
| Benin | 2.30 |
| Bolivia (Plurinational State of) | 2.70 |
| Brazil | 2.70 |
| Burkina Faso | 2.30 |
| Cambodia | 2.13 |
| Cameroon | 2.30 |
| Chad | 2.30 |
| China | 2.48 |
| Colombia | 2.70 |
| Côte d'Ivoire | 2.30 |
| Democratic People's Republic of Korea | 2.48 |
| Democratic Republic of the Congo | 2.30 |
| Dominican Republic | 2.70 |
| Ecuador | 2.70 |
| Egypt | 2.30 |
| Ghana | 2.30 |
| Guinea | 2.30 |
| Guinea-Bissau | 2.30 |
| Guyana | 2.70 |
| India | 1.63 |
| Indonesia | 2.13 |
| Iran (Islamic Republic of) | 3.29 |
| Italy | 3.29 |
| Japan | 2.48 |
| Lao People's Democratic Republic | 2.13 |
| Liberia | 2.30 |
| Madagascar | 2.30 |
| Malaysia | 2.13 |
| Mali | 2.30 |
| Mozambique | 2.30 |
| Myanmar | 2.13 |
| Nepal | 1.63 |
| Nigeria | 2.30 |
| Pakistan | 1.63 |
| Paraguay | 2.70 |
| Peru | 2.70 |
| Philippines | 2.13 |
| Republic of Korea | 2.48 |
| Russian Federation | 3.29 |
| Senegal | 2.30 |
| Sierra Leone | 2.30 |
| Sri Lanka | 1.63 |
| Thailand | 2.13 |
| Turkey | 3.29 |
| Uganda | 2.70 |
| United Republic of Tanzania | 2.30 |
| United States of America | 1.55 |
| Uruguay | 2.70 |
| Venezuela (Bolivarian Republic of) | 2.70 |
| Vietnam | 2.13 |
Unit: t CO₂‑eq /ha/yr
| Afghanistan | 0.03 |
| Argentina | 0.07 |
| Bangladesh | 0.06 |
| Benin | 0.03 |
| Bolivia (Plurinational State of) | 0.00 |
| Brazil | 0.00 |
| Burkina Faso | –0.02 |
| Cambodia | 0.01 |
| Cameroon | 0.00 |
| Chad | 0.01 |
| China | 0.01 |
| Colombia | –0.07 |
| Côte d'Ivoire | 0.02 |
| Democratic People's Republic of Korea | 0.02 |
| Democratic Republic of the Congo | 0.01 |
| Dominican Republic | –0.16 |
| Ecuador | –0.08 |
| Egypt | –0.15 |
| Ghana | 0.05 |
| Guinea | 0.01 |
| Guinea-Bissau | 0.01 |
| Guyana | –0.06 |
| India | –0.02 |
| Indonesia | 0.11 |
| Iran (Islamic Republic of) | –0.05 |
| Italy | 0.00 |
| Japan | 0.07 |
| Lao People's Democratic Republic | 0.02 |
| Liberia | 0.02 |
| Madagascar | 0.00 |
| Malaysia | –0.01 |
| Mali | –0.03 |
| Mozambique | 0.01 |
| Myanmar | 0.04 |
| Nepal | 0.04 |
| Nigeria | 0.01 |
| Pakistan | –0.04 |
| Paraguay | 0.01 |
| Peru | 0.09 |
| Philippines | 0.00 |
| Republic of Korea | 0.00 |
| Russian Federation | 0.04 |
| Senegal | –0.04 |
| Sierra Leone | 0.02 |
| Sri Lanka | 0.02 |
| Thailand | –0.03 |
| Turkey | 0.10 |
| Uganda | 0.00 |
| United Republic of Tanzania | 0.04 |
| United States of America | –0.05 |
| Uruguay | 0.03 |
| Venezuela (Bolivarian Republic of) | –0.48 |
| Vietnam | 0.00 |
Unit: t CO₂‑eq /ha rice paddies/yr
| Afghanistan | 1.67 |
| Argentina | 2.77 |
| Bangladesh | 1.69 |
| Benin | 2.34 |
| Bolivia (Plurinational State of) | 2.70 |
| Brazil | 2.70 |
| Burkina Faso | 2.28 |
| Cambodia | 2.15 |
| Cameroon | 2.30 |
| Chad | 2.32 |
| China | 2.48 |
| Colombia | 2.63 |
| Côte d'Ivoire | 2.32 |
| Democratic People's Republic of Korea | 2.50 |
| Democratic Republic of the Congo | 2.31 |
| Dominican Republic | 2.54 |
| Ecuador | 2.62 |
| Egypt | 2.16 |
| Ghana | 2.35 |
| Guinea | 2.32 |
| Guinea-Bissau | 2.32 |
| Guyana | 2.63 |
| India | 1.61 |
| Indonesia | 2.24 |
| Iran (Islamic Republic of) | 3.24 |
| Italy | 3.29 |
| Japan | 2.54 |
| Lao People's Democratic Republic | 2.15 |
| Liberia | 2.32 |
| Madagascar | 2.31 |
| Malaysia | 2.13 |
| Mali | 2.28 |
| Mozambique | 2.32 |
| Myanmar | 2.17 |
| Nepal | 1.67 |
| Nigeria | 2.32 |
| Pakistan | 1.59 |
| Paraguay | 2.71 |
| Peru | 2.79 |
| Philippines | 2.14 |
| Republic of Korea | 2.47 |
| Russian Federation | 3.33 |
| Senegal | 2.27 |
| Sierra Leone | 2.32 |
| Sri Lanka | 1.65 |
| Thailand | 2.10 |
| Turkey | 3.39 |
| Uganda | 2.31 |
| United Republic of Tanzania | 2.35 |
| United States of America | 1.49 |
| Uruguay | 2.72 |
| Venezuela (Bolivarian Republic of) | 2.22 |
| Vietnam | 2.13 |
Table 1b. Combined effectiveness at reducing emissions, by country, for noncontinuous flooding with nutrient management.
Unit: t CO₂‑eq /ha rice paddies/yr
| Afghanistan | 4.75 |
| Argentina | 7.85 |
| Bangladesh | 4.75 |
| Benin | 6.71 |
| Bolivia (Plurinational State of) | 7.85 |
| Brazil | 7.85 |
| Burkina Faso | 6.71 |
| Cambodia | 6.21 |
| Cameroon | 6.71 |
| Chad | 6.71 |
| China | 7.20 |
| Colombia | 7.85 |
| Côte d'Ivoire | 6.71 |
| Democratic People's Republic of Korea | 7.20 |
| Democratic Republic of the Congo | 6.71 |
| Dominican Republic | 7.85 |
| Ecuador | 7.85 |
| Egypt | 6.71 |
| Ghana | 6.71 |
| Guinea | 6.71 |
| Guinea-Bissau | 6.71 |
| Guyana | 7.85 |
| India | 4.75 |
| Indonesia | 6.21 |
| Iran (Islamic Republic of) | 9.57 |
| Italy | 9.57 |
| Japan | 7.20 |
| Lao People's Democratic Republic | 6.21 |
| Liberia | 6.71 |
| Madagascar | 6.71 |
| Malaysia | 6.21 |
| Mali | 6.71 |
| Mozambique | 6.71 |
| Myanmar | 6.21 |
| Nepal | 4.75 |
| Nigeria | 6.71 |
| Pakistan | 4.75 |
| Paraguay | 7.85 |
| Peru | 7.85 |
| Philippines | 6.21 |
| Republic of Korea | 7.20 |
| Russian Federation | 9.57 |
| Senegal | 6.71 |
| Sierra Leone | 6.71 |
| Sri Lanka | 4.75 |
| Thailand | 6.21 |
| Turkey | 9.57 |
| Uganda | 6.71 |
| United Republic of Tanzania | 6.71 |
| United States of America | 4.51 |
| Uruguay | 7.85 |
| Venezuela (Bolivarian Republic of) | 7.85 |
| Vietnam | 6.21 |
Unit: t CO₂‑eq /ha rice paddies/yr
| Afghanistan | 0.03 |
| Argentina | 0.07 |
| Bangladesh | 0.06 |
| Benin | 0.03 |
| Bolivia (Plurinational State of) | 0.00 |
| Brazil | 0.00 |
| Burkina Faso | 0.02 |
| Cambodia | 0.01 |
| Cameroon | 0.00 |
| Chad | 0.01 |
| China | 0.01 |
| Colombia | –0.07 |
| Côte d'Ivoire | 0.02 |
| Democratic People's Republic of Korea | 0.02 |
| Democratic Republic of the Congo | 0.01 |
| Dominican Republic | 0.16 |
| Ecuador | –0.08 |
| Egypt | –0.15 |
| Ghana | 0.05 |
| Guinea | 0.01 |
| Guinea-Bissau | 0.01 |
| Guyana | –0.06 |
| India | –0.02 |
| Indonesia | 0.11 |
| Iran (Islamic Republic of) | –0.05 |
| Italy | 0.00 |
| Japan | 0.07 |
| Lao People's Democratic Republic | 0.02 |
| Liberia | 0.02 |
| Madagascar | 0.00 |
| Malaysia | –0.01 |
| Mali | –0.03 |
| Mozambique | 0.01 |
| Myanmar | 0.04 |
| Nepal | 0.04 |
| Nigeria | 0.01 |
| Pakistan | –0.04 |
| Paraguay | 0.01 |
| Peru | 0.09 |
| Philippines | 0.00 |
| Republic of Korea | 0.00 |
| Russian Federation | 0.04 |
| Senegal | –0.04 |
| Sierra Leone | 0.02 |
| Sri Lanka | 0.02 |
| Thailand | –0.03 |
| Turkey | 0.10 |
| Uganda | 0.00 |
| United Republic of Tanzania | 0.04 |
| United States of America | –0.05 |
| Uruguay | 0.03 |
| Venezuela (Bolivarian Republic of) | –0.48 |
| Vietnam | 0.00 |
Unit: t CO₂‑eq /ha rice paddies/yr
| Afghanistan | 4.78 |
| Argentina | 7.93 |
| Bangladesh | 4.81 |
| Benin | 6.74 |
| Bolivia (Plurinational State of) | 7.85 |
| Brazil | 7.85 |
| Burkina Faso | 6.68 |
| Cambodia | 6.22 |
| Cameroon | 6.71 |
| Chad | 6.72 |
| China | 7.21 |
| Colombia | 7.21 |
| Côte d'Ivoire | 6.73 |
| Democratic People's Republic of Korea | 7.23 |
| Democratic Republic of the Congo | 6.71 |
| Dominican Republic | 7.69 |
| Ecuador | 7.77 |
| Egypt | 6.56 |
| Ghana | 6.76 |
| Guinea | 6.72 |
| Guinea-Bissau | 6.72 |
| Guyana | 7.79 |
| India | 4.73 |
| Indonesia | 6.31 |
| Iran (Islamic Republic of) | 9.52 |
| Italy | 9.57 |
| Japan | 7.27 |
| Lao People's Democratic Republic | 6.23 |
| Liberia | 6.72 |
| Madagascar | 6.71 |
| Malaysia | 6.20 |
| Mali | 6.20 |
| Mozambique | 6.72 |
| Myanmar | 6.25 |
| Nepal | 4.79 |
| Nigeria | 6.72 |
| Pakistan | 4.71 |
| Paraguay | 7.86 |
| Peru | 7.95 |
| Philippines | 6.21 |
| Republic of Korea | 7.20 |
| Russian Federation | 9.61 |
| Senegal | 6.67 |
| Sierra Leone | 6.73 |
| Sri Lanka | 4.77 |
| Thailand | 6.18 |
| Turkey | 9.67 |
| Uganda | 6.71 |
| United Republic of Tanzania | 6.75 |
| United States of America | 4.45 |
| Uruguay | 7.88 |
| Venezuela (Bolivarian Republic of) | 7.38 |
| Vietnam | 6.20 |
For conventional paddy rice, we assumed an initial cost of US$0 because many millions of hectares of paddies are already in place (Table 2). We used regional per-hectare average profits from Damania et al. (2024) as the source for net profit per year. Because the initial cost per hectare is US$0, the net cost per hectare is the negative of the per-hectare annual profit.
Table 2. Net cost and profit of conventional paddy rice by region in 2023.
Unit: US$/ha rice paddies
| Africa | 0.00 |
| East Asia | 0.00 |
| Europe | 0.00 |
| North America | 0.00 |
| South America | 0.00 |
| South Asia | 0.00 |
| Southeast Asia | 0.00 |
Unit: US$/ha rice paddies/yr
| Africa | 457.34 |
| East Asia | 543.67 |
| Europe | 585.43 |
| North America | 356.27 |
| South America | 285.69 |
| South Asia | 488.85 |
| Southeast Asia | 322.13 |
Unit: US$/ha rice paddies/yr
| Africa | -457.34 |
| East Asia | -543.67 |
| Europe | -585.43 |
| North America | -356.27 |
| South America | -285.69 |
| South Asia | -488.85 |
| Southeast Asia | -322.13 |
For noncontinuous flooding, we assumed an initial cost of US$0 because no new inputs or changes to paddy infrastructure are required in most cases. Median impact on net profit was an increase of 17% based on nine data points from seven sources. National results are shown in Table 3.
We assumed nutrient management has an initial cost of US$0 because in many cases, nutrient management begins with reducing the overapplication of fertilizer. Here we used the mean value from Gu et al. (2023), a savings of US$507.8/t nitrogen. We used our national-level data on overapplication of nitrogen to calculate savings per hectare. National results are shown in Table 3.
Combined Net Profit per Hectare
Net profit per hectare varies by country due to regional and some country-specific variables. Country-by-country results are shown in Table 3.
Net Net Cost Compared to Conventional Paddy Rice
Net net cost varies by country. Country-by-country results are shown in Table 3.
Table 3. Net cost and profit of noncontinuous flooding with nutrient management by region.
Unit: US$/ha rice paddies
| Afghanistan | 0.00 |
| Argentina | 0.00 |
| Bangladesh | 0.00 |
| Benin | 0.00 |
| Bolivia (Plurinational State of) | 0.00 |
| Brazil | 0.00 |
| Burkina Faso | 0.00 |
| Cambodia | 0.00 |
| Cameroon | 0.00 |
| Chad | 0.00 |
| China | 0.00 |
| Colombia | 0.00 |
| Cote d'Ivoire | 0.00 |
| Democratic People's Republic of Korea | 0.00 |
| Democratic Republic of the Congo | 0.00 |
| Dominican Republic | 0.00 |
| Ecuador | 0.00 |
| Egypt | 0.00 |
| Ghana | 0.00 |
| Guinea | 0.00 |
| Guinea–Bissau | 0.00 |
| Guyana | 0.00 |
| India | 0.00 |
| Indonesia | 0.00 |
| Iran (Islamic Republic of) | 0.00 |
| Italy | 0.00 |
| Japan | 0.00 |
| Lao People's Democratic Republic | 0.00 |
| Liberia | 0.00 |
| Madagascar | 0.00 |
| Malaysia | 0.00 |
| Mali | 0.00 |
| Mozambique | 0.00 |
| Myanmar | 0.00 |
| Nepal | 0.00 |
| Nigeria | 0.00 |
| Pakistan | 0.00 |
| Paraguay | 0.00 |
| Peru | 0.00 |
| Philippines | 0.00 |
| Republic of Korea | 0.00 |
| Russian Federation | 0.00 |
| Senegal | 0.00 |
| Sierra Leone | 0.00 |
| Sri Lanka | 0.00 |
| Thailand | 0.00 |
| Turkey | 0.00 |
| Uganda | 0.00 |
| United Republic of Tanzania | 0.00 |
| United States of America | 0.00 |
| Uruguay | 0.00 |
| Venezuela (Bolivarian Republic of) | 0.00 |
| Vietnam | 0.00 |
Non-continuous flooding and nutrient management.
Unit: US$/ha rice paddies/yr
| Afghanistan | 573.4 |
| Argentina | 354.8 |
| Bangladesh | 576.7 |
| Benin | 535.1 |
| Bolivia (Plurinational State of) | 354.1 |
| Brazil | 363.4 |
| Burkina Faso | 553.3 |
| Cambodia | 377.8 |
| Cameroon | 543.7 |
| Chad | 535.1 |
| China | 675.1 |
| Colombia | 397.7 |
| Cote d'Ivoire | 535.8 |
| Democratic People's Republic of Korea | 654.6 |
| Democratic Republic of the Congo | 535.6 |
| Dominican Republic | 428.4 |
| Ecuador | 390.3 |
| Egypt | 802.2 |
| Ghana | 535.5 |
| Guinea | 538.5 |
| Guinea–Bissau | 539.2 |
| Guyana | 382.0 |
| India | 607.9 |
| Indonesia | 382.3 |
| Iran (Islamic Republic of) | 726.7 |
| Italy | 567.9 |
| Japan | 636.0 |
| Lao People's Democratic Republic | 377.0 |
| Liberia | 535.3 |
| Madagascar | 535.0 |
| Malaysia | 401.2 |
| Mali | 561.0 |
| Mozambique | 535.5 |
| Myanmar | 380.7 |
| Nepal | 575.2 |
| Nigeria | 537.1 |
| Pakistan | 610.0 |
| Paraguay | 385.9 |
| Peru | 351.7 |
| Philippines | 399.5 |
| Republic of Korea | 678.2 |
| Russian Federation | 475.2 |
| Senegal | 569.9 |
| Sierra Leone | 535.1 |
| Sri Lanka | 591.1 |
| Thailand | 407.7 |
| Turkey | 694.5 |
| Uganda | 543.3 |
| United Republic of Tanzania | 537.4 |
| United States of America | 490.4 |
| Uruguay | 377.6 |
| Venezuela (Bolivarian Republic of) | 546.2 |
| Vietnam | 416.6 |
Non-continuous flooding and nutrient management.
Unit: US$/ha rice paddies/yr
| Afghanistan | -573.4 |
| Argentina | -354.8 |
| Bangladesh | -576.7 |
| Benin | -535.1 |
| Bolivia (Plurinational State of) | -354.1 |
| Brazil | -363.4 |
| Burkina Faso | -553.3 |
| Cambodia | -377.8 |
| Cameroon | -543.7 |
| Chad | -535.1 |
| China | -675.1 |
| Colombia | -397.7 |
| Cote d'Ivoire | -535.8 |
| Democratic People's Republic of Korea | -654.6 |
| Democratic Republic of the Congo | -535.6 |
| Dominican Republic | -428.4 |
| Ecuador | -390.3 |
| Egypt | -802.2 |
| Ghana | -535.5 |
| Guinea | -538.5 |
| Guinea–Bissau | -539.2 |
| Guyana | -382.0 |
| India | -607.9 |
| Indonesia | -382.3 |
| Iran (Islamic Republic of) | -726.7 |
| Italy | -567.9 |
| Japan | -636.0 |
| Lao People's Democratic Republic | -377.0 |
| Liberia | -535.3 |
| Madagascar | -535.0 |
| Malaysia | -401.2 |
| Mali | -561.0 |
| Mozambique | -535.5 |
| Myanmar | -380.7 |
| Nepal | -575.2 |
| Nigeria | -537.1 |
| Pakistan | -610.0 |
| Paraguay | -385.9 |
| Peru | -351.7 |
| Philippines | -399.5 |
| Republic of Korea | -678.2 |
| Russian Federation | -475.2 |
| Senegal | -569.9 |
| Sierra Leone | -535.1 |
| Sri Lanka | -591.1 |
| Thailand | -407.7 |
| Turkey | -694.5 |
| Uganda | -543.3 |
| United Republic of Tanzania | -537.4 |
| United States of America | -490.4 |
| Uruguay | -377.6 |
| Venezuela (Bolivarian Republic of) | -546.2 |
| Vietnam | -416.6 |
Non-continuous flooding and nutrient management.
Unit: US$/ha rice paddies/yr
| Afghanistan | -1,062 |
| Argentina | -640.5 |
| Bangladesh | -1,065 |
| Benin | -992.4 |
| Bolivia (Plurinational State of) | -639.8 |
| Brazil | -649.0 |
| Burkina Faso | -1,010 |
| Cambodia | -699.9 |
| Cameroon | -1,001 |
| Chad | -992.5 |
| China | -1,219 |
| Colombia | -683.4 |
| Cote d'Ivoire | -993.2 |
| Democratic People's Republic of Korea | -1,198 |
| Democratic Republic of the Congo | -992.9 |
| Dominican Republic | -714.1 |
| Ecuador | -676.0 |
| Egypt | -1,387 |
| Ghana | -992.8 |
| Guinea | -995.8 |
| Guinea–Bissau | -996.5 |
| Guyana | -667.7 |
| India | -1,096 |
| Indonesia | -704.5 |
| Iran (Islamic Republic of) | -1,312 |
| Italy | -1,053 |
| Japan | -1,179 |
| Lao People's Democratic Republic | -699.1 |
| Liberia | -992.6 |
| Madagascar | -992.4 |
| Malaysia | -723.3 |
| Mali | -1,018 |
| Mozambique | -992.8 |
| Myanmar | -702.8 |
| Nepal | -1,064 |
| Nigeria | -994.5 |
| Pakistan | -1,098 |
| Paraguay | -671.6 |
| Peru | -637.4 |
| Philippines | -721.6 |
| Republic of Korea | -1,221 |
| Russian Federation | -865.9 |
| Senegal | -1,027 |
| Sierra Leone | -992.4 |
| Sri Lanka | -1,080 |
| Thailand | -729.8 |
| Turkey | -1,279 |
| Uganda | -1,000 |
| United Republic of Tanzania | -994.7 |
| United States of America | -846.7 |
| Uruguay | -663.3 |
| Venezuela (Bolivarian Republic of) | -831.9 |
| Vietnam | -738.8 |
Non-continuous flooding and nutrient management.
Unit: US$/t CO₂‑eq
| Afghanistan | -222.1 |
| Argentina | -80.82 |
| Bangladesh | -221.5 |
| Benin | -147.2 |
| Bolivia (Plurinational State of) | -81.49 |
| Brazil | -82.60 |
| Burkina Faso | -151.2 |
| Cambodia | -112.5 |
| Cameroon | -149.3 |
| Chad | -147.7 |
| China | -168.9 |
| Colombia | -87.77 |
| Cote d'Ivoire | -147.6 |
| Democratic People's Republic of Korea | -165.8 |
| Democratic Republic of the Congo | -147.9 |
| Dominican Republic | -92.82 |
| Ecuador | -86.99 |
| Egypt | -211.5 |
| Ghana | -146.9 |
| Guinea | -148.1 |
| Guinea–Bissau | -148.2 |
| Guyana | -85.72 |
| India | -232.1 |
| Indonesia | -111.5 |
| Iran (Islamic Republic of) | -137.8 |
| Italy | -110.0 |
| Japan | -162.2 |
| Lao People's Democratic Republic | -112.2 |
| Liberia | -147.6 |
| Madagascar | -147.9 |
| Malaysia | -116.6 |
| Mali | -152.2 |
| Mozambique | -147.7 |
| Myanmar | -112.4 |
| Nepal | -222.2 |
| Nigeria | -148.0 |
| Pakistan | -233.3 |
| Paraguay | -85.41 |
| Peru | -80.22 |
| Philippines | -116.1 |
| Republic of Korea | -169.7 |
| Russian Federation | -90.08 |
| Senegal | -154.0 |
| Sierra Leone | -147.5 |
| Sri Lanka | -226.3 |
| Thailand | -118.1 |
| Turkey | -132.3 |
| Uganda | -149.1 |
| United Republic of Tanzania | -147.3 |
| United States of America | -190.1 |
| Uruguay | -84.18 |
| Venezuela (Bolivarian Republic of) | -112.7 |
| Vietnam | -119.1 |
Non-continuous flooding and nutrient management.
Cost per unit climate impact
The cost per t CO₂‑eq varies by country. Country-by-country results are shown in Table 3. The global weighted average is a savings of US$175.0/t CO₂‑eq (Table 4). Note that this is the same for both 100- and 20-yr results.
Table 4. Weighted average cost per unit climate impact.
Unit: US$/t CO₂‑eq
| Weighted average | -175.0 |
Learning curve data are not available for improved rice cultivation.
Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.
At Project Drawdown, we define the speed of action for each climate solution as gradual, emergency brake, or delayed.
The noncontinuous flooding component of Improve Rice Production is an EMERGENCY BRAKE climate solution. It has a disproportionately fast impact after implementation because it reduces the short-lived climate pollutant methane.
The nutrient management component is a GRADUAL climate solution. It has a steady, linear impact on the atmosphere. The cumulative effect over time builds as a straight line.
Caveats like additionality and permanence do not apply to improve rice production as described here. If its carbon sequestration component were included, those caveats would apply.
Noncontinuous Flooding
Rigorous, up-to-date country-level data about the extent of noncontinuous flooding in rice production are in short supply. We found five sources reporting adoption in seven major rice-producing countries. We used these to create regional averages and applied them to all countries that produce more than 100,000 ha of rice (paddy and upland). The total estimated current adoption is 48.65 Mha, or 47% of global rice paddy area (Table 5). This should be considered an extremely rough estimate.
The available sources encompass different forms of noncontinuous flooding, including alternate wetting and drying (Philippines, Vietnam, Bangladesh), mid-season drainage (Japan), or both (China).
Table 5. Current adoption level (2025).
Unit: Mha
| Mean | 48.65 |
Noncontinuous flooding, ha installed.
Nutrient Management
We based nutrient management adoption on our analysis of the overapplication of nitrogen fertilizer on a national basis. Rather than calculate adoption in a parallel way to noncontinuous flooding, this approach provided a national average overapplication rate (the amount of nitrogen fertilizer which is applied that is not needed for crop growth and ends up as nitrous oxide emissions). We assume that every hectare of noncontinuous flooding is also using nutrient management.
We assume the adoption of both noncontinuous flooding and nutrient management for each hectare.
Adoption trend information here takes the form of annual growth rate (%), with a median of 3.76% (Table 6). Adoption rate data are somewhat scarce.
Table 6. Adoption trend.
Unit: %
| 25th percentile | 3.00 |
| Median (50th percentile) | 3.76 |
| 75th percentile | 4.25 |
Percent annual growth rate.
There are barriers to adoption of these techniques and practices. Not all paddy rice is suitable for improved water management, and under certain conditions, undesirable yield reductions are possible (Bo et al., 2022). Other challenges include water access, coordinating water usage between multiple users, and ownership of water pumps (Nabuurs et al., 2022).
There are many challenges in estimating paddy rice land. Food and Agriculture Organization (FAO) statistics can overcount because land that produces more than one crop is double or triple counted. Satellite imagery is often blocked by clouds in the tropical humid areas where rice paddies are concentrated.
A comprehensive effort to calculate total world rice paddy land reported 66.00 Mha of irrigated paddy and 63.00 Mha of rain-fed paddy (Salmon et al., 2015). Our own calculation of the combined paddy rice area of countries producing over 100,000 ha of rice found 104.1 Mha of paddy rice.
We summed high-resolution maps of paddy rice area appropriate for noncontinuous flooding (Bo et al., 2022) over maps of irrigated and rain-fed rice areas (Salmon et al., 2015) to determine a maximum adoption ceiling for each country. Several countries have already exceeded this threshold, and we included their higher adoption in our calculation. The sum of these, and therefore, the median adoption ceiling, is 77.53 Mha (Table 7).
Table 7. Adoption ceiling: upper limit for adoption level.
Unit: Mha
| Median | 77.53 |
Mha of improved rice production installed.
Table 8. Range of achievable adoption levels.
Unit: Mha
| Current adoption | 48.65 |
| Achievable – low | 49.56 |
| Achievable – high | 77.53 |
| Adoption ceiling | 77.53 |
Mha of improved rice production installed.
Given that both China and Japan have already attained adoption rates above our adoption ceiling (Bo et al., 2022; Zhang et al., 2019), we selected for our adoption ceiling our Achievable – High adoption level, which is 77.53 Mha (Table 8).
In contrast, the countries with the lowest adoption rates had rates under 3%. In the absence of a modest adoption example, we chose to use current adoption plus 10% as our Achievable – Low adoption level. This provides an adoption of 49.56 Mha.
As described under Adoption Ceiling above, adoption of nutrient management is already weighted based on regional or national adoption and should not be overcounted in the achievable range calculations.
We calculated the potential impact of improved rice, on a 100-yr basis, at 0.10 Gt CO₂‑eq/yr from current adoption, and 0.10, 0.16, and 0.16 from Achievable – Low, Achievable – High, and Adoption Ceiling, respectively (Table 9). On a 20-yr basis, the totals are 0.29, 0.29, 0.46, and 0.46, respectively.
Table 9. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr
| Current adoption | 0.10 |
| Achievable – low | 0.10 |
| Achievable – high | 0.16 |
| Adoption ceiling | 0.16 |
Unit: Gt CO₂‑eq/yr
| Current adoption | 0.29 |
| Achievable – low | 0.29 |
| Achievable – high | 0.46 |
| Adoption ceiling | 0.46 |
The IPCC estimated a technical potential at 0.3 Gt CO₂‑eq/yr, with 0.2 Gt CO₂‑eq/yr as economically achievable at US$100/t CO₂ (100-yr basis; Nabuurs et al., 2022). Achieving the adoption ceiling of 76% of global flooded rice production could reduce rice paddy methane by 47% (Bo et al., 2022). Applying this percentage to the IPCC reported total paddy methane emissions of 0.49–0.73 Gt CO₂‑eq/yr yields a reduction of 0.23–0.34 Gt CO₂‑eq/yr (Nabuurs et al., 2022). Roe et al. (2021) calculated 0.19 Gt CO₂‑eq/yr. Note that these benchmarks only calculate methane from paddy rice, while we also addressed nitrous oxide from nutrient management.
The additional benefits of improved rice production arise from both practices (noncontinuous flooding and improved nutrient management) that form this solution.
Noncontinuous flooding can reduce the accumulation of arsenic in rice grains (Ishfaq et al., 2020). Arsenic is a carcinogen that is responsible for thousands of premature deaths in South and Southeast Asia (Jameel et al., 2021). The amount of arsenic reduced can vary by 0–90% depending upon the timing of the wetting and drying periods (Ishfaq et al., 2020).
Better nutrient management improves soil fertility and health, increasing resilience to extreme heat and droughts. Noncontinuous flooding also slows down the rate of soil salinization, protecting soil from degradation (Carrijo et al., 2017).
Rice irrigation is responsible for 40% of all freshwater use in Asia, and rice requires two to three times more water per metric ton of grain than other cereals (Surendran et al., 2021). Field studies across South and Southeast Asia have shown that noncontinuous flooding can typically reduce irrigation requirements 20–30% compared to conventional flooded systems (Suwanmaneepong et al., 2023; Carrijo et al., 2017) without adversely affecting rice yield or grain quality. This reduction in water usage alleviates pressure on water resources in drought-prone areas (Alauddin et al., 2020).
Adoption of noncontinuous flooding up to the adoption ceiling of 76% would reduce rice irrigation needs by 25%.
Both noncontinuous flooding and improved nutrient management reduce water pollution. Nitrogen utilization is generally poor using existing growing techniques, with two-thirds of the nitrogen fertilizer being lost through surface runoff and denitrification (Zhang et al., 2021). While noncontinuous flooding is primarily a water-efficiency and methane reduction technique, it can improve nitrogen use efficiency and reduce nitrogen runoff into water bodies (Liang et al., 2017; Liang et al., 2023). Improved nutrient management also reduces the excess fertilizers that could end up in local water bodies. Both mechanisms can mitigate eutrophication and harmful algal blooms, protect aquatic ecosystems, and ensure safer drinking water supplies (Bijay-Sing and Craswell, 2021).
Not all paddies are suitable, with variables including soil type, irrigation infrastructure and ownership, community partitioning and scheduling of water resources, field size, and more (Nabuurs et al., 2022; Enriquez et al., 2021).
Many rice farmers in Asia do not directly control irrigation access, but instead use a municipal system, which is not always available when needed for noncontinuous flooding production. In addition, they may not actually experience cost savings, as pricing may be based on area rather than amount of water. An additional change is that multiple plots owned or rented by multiple farmers may be irrigated by a single irrigation gate, meaning that all must agree to an irrigation strategy. Generally speaking, pump-based irrigation areas see the best adoption, with poor adoption in gravity-based irrigation system areas. Improved irrigation infrastructure is necessary to increase adoption of noncontinuous flooding (Enriquez et al., 2021).
Continuously flooded paddies have lower weed pressure than noncontinuous paddies, so noncontinuous flooding can raise labor costs or increase herbicide use. Not all rice varieties grow well in noncontinuous flooding (Li et al., 2024). In addition, it is difficult for farmers, especially smallholders, to monitor soil moisture level, which makes determining the timing of the next irrigation difficult (Livsey et al., 2019).
We did not identify any aligned or competing interactions with other solutions.
ha rice paddies
CH₄ , N₂O
In some cases, rice yields are reduced (Nabuurs et al., 2022). However, this has been excluded from our calculations because we worked from the adoption ceiling of Bo et al. (2022), which explicitly addresses the question of maximum adoption without reducing yields.
Long-term impacts on soil health of water-saving irrigation strategies have not been widely studied, but a meta-analysis by Livsey et al. (2019) indicates a risk of decreases in soil carbon and fertility.
Rice is the third most widely grown crop in terms of cultivated area and provides more calories directly to people than any other crop. It also is an important source of methane emissions. Here we show pixels in which at least 1% of the area is devoted to paddy (flooded) rice. Upland (unflooded) rice is included in the Improve Nutrient Management solution.
Cao, P., Bilotto, F., Gonzalez Fischer, C., Mueller, N. D., Carlson, K. M., Gerber, J.S., Smith, P., Tubiello, F. N., West, P. C., You, L., & Herrero, M. (2025). Mapping greenhouse gas emissions from global cropland circa 2020 [Data set, PREPRINT Version 1]. In review at Nature Climate Change. Link to source: https://doi.org/10.21203/rs.3.rs-6622054/v1
Tang, F. H. M., Nguyen, T. H., Conchedda, G., Casse, L., Tubiello, F. N., & Maggi, F. (2024). CROPGRIDS: A global geo-referenced dataset of 173 crops [Data set]. Scientific Data, 11(1), 413. Link to source: https://doi.org/10.1038/s41597-024-03247-7
Rice is the third most widely grown crop in terms of cultivated area and provides more calories directly to people than any other crop. It also is an important source of methane emissions. Here we show pixels in which at least 1% of the area is devoted to paddy (flooded) rice. Upland (unflooded) rice is included in the Improve Nutrient Management solution.
Cao, P., Bilotto, F., Gonzalez Fischer, C., Mueller, N. D., Carlson, K. M., Gerber, J.S., Smith, P., Tubiello, F. N., West, P. C., You, L., & Herrero, M. (2025). Mapping greenhouse gas emissions from global cropland circa 2020 [Data set, PREPRINT Version 1]. In review at Nature Climate Change. Link to source: https://doi.org/10.21203/rs.3.rs-6622054/v1
Tang, F. H. M., Nguyen, T. H., Conchedda, G., Casse, L., Tubiello, F. N., & Maggi, F. (2024). CROPGRIDS: A global geo-referenced dataset of 173 crops [Data set]. Scientific Data, 11(1), 413. Link to source: https://doi.org/10.1038/s41597-024-03247-7
Improved rice production has its greatest potential in regions where there is substantial paddy rice production and adequate water availability to allow farmers to implement drain/flood cycles throughout the growing season (noncontinuous flooding). Rice production is dominated by Asia, so the greatest potential for solution uptake is there. Brazil and the United States rank 9th and 11th for rice production, and each has regions where this solution would have multiple benefits. Because improved rice production solution may not decrease yields, not all paddy rice-growing areas are suitable. There are regions of great potential throughout Southeast Asia, particularly in Vietnam and Thailand.
Other factors besides biophysical factors govern the suitability of noncontinuous flooding. For example, farmers are more likely to release water in their fields if they are confident that water will be available for subsequent irrigation, which often depends on community structures.
There is very scarce information on adoption of noncontinuous flooding, although Bangladesh, China, Japan, and South Korea have relatively high uptake.
There is high consensus on the effectiveness and potential of noncontinuous flooding and nutrient management (Jiang et al., 2019; Zhang et al., 2023; Nabuurs et al., 2022; Qian et al., 2023).
Hergoualc’h et al. (2019) describe methane reduction and associated nitrous oxide increase from noncontinuous flooding in detail. Bo et al. (2022) calculate that 76% of global rice paddy area is suitable to switch to noncontinuous flooding without reducing yields. Carlson et al. (2016) provide emissions intensities for croplands, including rice production. Ludemann et al. (2024) provide country-by-country and crop-by-crop fertilizer use data. Qian et al. (2023) review methane emissions production and reduction potential.
The results presented in this document summarize findings from 12 reviews and meta-analyses and 26 original studies reflecting current evidence from countries across the Asian rice production region. We recognize this limited geographic scope creates bias, and hope this work inspires research and data sharing on this topic in underrepresented regions.
In this analysis, we calculated the potential for reducing crop nitrogen inputs and associated nitrous oxide emissions by integrating spatially explicit, crop-specific data on nitrogen inputs, crop yields, attainable yields, irrigated extent, and climate. Broadly, we calculated a “target” yield-scaled nitrogen input rate based on pixels with low yield gaps and calculated the difference between nitrous oxide emissions under the current rate and under the hypothetical target emissions rate, using nitrous oxide emissions factors disaggregated by fertilizer type and climate.
We used Tier 1 emissions factors from the IPCC 2019 Refinement to the 2006 Guidelines for National Greenhouse Gas Inventories, including direct emissions factors as well as indirect emissions from volatilization and leaching pathways. Direct emissions factors represent the proportion of applied nitrogen emitted as nitrous oxide, while we calculated volatilization and leaching emissions factors by multiplying the proportion of applied nitrogen lost through these pathways by the proportion of volatilized or leached nitrogen ultimately emitted as nitrous oxide. Including both direct and indirect emissions, organic and synthetic fertilizers emit 4.97 kg CO₂‑eq/kg nitrogen and 8.66 kg CO₂‑eq/kg nitrogen, respectively, in wet climates, and 2.59 kg CO₂‑eq/kg nitrogen and 2.38 kg CO₂‑eq/kg nitrogen in dry climates. We included uncertainty bounds (2.5th and 97.5th percentiles) for all emissions factors.
We classified each pixel as “wet” or “dry” using an aridity index (AI) threshold of 0.65, calculated as the ratio of annual precipitation to potential evapotranspiration (PET) from TerraClimate data (1991–2020), based on a threshold of 0.65. For pixels in dry climates that contained irrigation, we took the weighted average of wet and dry emissions factors based on the fraction of cropland that was irrigated (Mehta et al., 2024). We excluded irrigated rice from this analysis due to large differences in nitrous oxide dynamics in flooded rice systems.
Using highly disaggregated data on nitrogen inputs from Adalibieke et al. (2024) for 21 crop groups, we calculated total crop-specific inputs of synthetic and organic nitrogen. We then averaged over 2016–2020 to reduce the influence of interannual variability in factors like fertilizer prices. These values are subsequently referred to as “current” nitrogen inputs. We calculated nitrous oxide emissions under current nitrogen inputs as the sum of the products of nitrogen inputs and the climatically relevant emissions factors for each fertilizer type.
Next, we calculated target nitrogen application rates in terms of kg nitrogen per ton of crop yield using data on actual and attainable yields for 17 crops from Gerber et al., 2024. For each crop, we first identified pixels in which the ratio of actual to attainable yields was above the 80th percentile globally. The target nitrogen application rate was then calculated as the 20th percentile of nitrogen application rates across low-yield-gap pixels. Finally, we calculated total target nitrogen inputs as the product of actual yields and target nitrogen input rates. We calculated hypothetical nitrous oxide emissions from target nitrogen inputs as the product of nitrogen inputs and the climatically relevant emissions factor for each fertilizer type.
The difference between current and target nitrogen inputs represents the amount by which nitrogen inputs could hypothetically be reduced without compromising crop productivity (i.e., “avoidable” nitrogen inputs). We calculated avoidable nitrous oxide emissions as the difference between nitrous oxide emissions with current nitrogen inputs and those with target nitrogen inputs. For crops for which no yield or attainable yield data were available, we applied the average percent reduction in nitrogen inputs under the target scenario from available crops to the nitrogen input data for missing crops to calculate the avoidable nitrogen inputs and emissions.
This simple and empirically driven method aimed to identify realistically low but nutritionally adequate nitrogen application rates by including only pixels with low yield gaps, which are unlikely to be substantially nutrient-constrained. We did not control for other factors affecting nitrogen availability, such as historical nutrient application rates or depletion, rotation with nitrogen fixing crops, or tillage and residue retention practices.
Crop residues are plant materials left after harvest, such as stalks, leaves, and seed husks. Many farmers burn crop residues in the field, which emits CO₂, , methane, and nitrous oxide. Black carbon – a non-GHG climate forcer that generates air pollution, contributing to hundreds of thousands of deaths annually– is also produced. This solution avoids the burning of crop residues through the adoption of lower-emission options including straw balers, no-till seeders that can plant through residues, and developing markets for residue products. Some promising new techniques are also under development that could further increase future adoption and effectiveness of this solution.
When left in the field, crop residues improve soil fertility. But when burned, the residues cause serious health problems and reduce air quality. So why do so many farmers burn crop residues? In fields in which multiple crops are sown in succession in the same year, there is often not enough time for residues to decompose before the next crop is sown, making seeding difficult (Dutta et al., 2022). In many countries – including those with vast agricultural sectors, such as India and Indonesia – crop harvesting has become mechanized, but residue removal equipment has not. Low labor availability poses a further challenge, because manual residue removal is highly labor-intensive (Dutta et al., 2022). Meanwhile, a lack of markets and processing infrastructure for residues remains a barrier in many regions as well (Dutta et al., 2022). For many farmers facing the challenges noted above, burning crop residues is often the lowest-cost option (Krishna & Mkondiwa, 2023).
Crop residue burning produces CO₂, nitrous oxide, and methane (Dong et al., 2019). IT also reduces production of black carbon – a form of particulate matter that contributes to climate change and poses very serious health concerns. In India alone, an estimated 600,000 people die each year from air pollution, which is severely impacted by widespread crop residue burning (Krishna & Mkondiwa, 2023).
There are many alternatives to crop residue burning that produce fewer climate pollutants. One approach leaves residues in the field but circumvents seed planting issues. For example, conservation agriculture and other reduced tillage techniques – described in the Improve Annual Cropping solution – use modern equipment capable of seeding through crop residues without difficulty (Dutta et al., 2022, Kabange et al., 2023). Some promising new techniques can accelerate residue decomposition in the field to facilitate seed planting, though these techniques may generate associated emissions of their own (Krishna & Mkondiwa, 2023).
Another approach uses straw baling equipment to harvest residues for off-farm uses. In countries with developed markets, residues that are baled or otherwise collected from the field can be used or sold for compost production, bioenergy applications, livestock feed and bedding, natural building materials, feedstock for manufacturing of paper and other products, mushroom growing substrate, and more (Dutta et al., 2022). Given that many climate solutions require biomass feedstocks, there is likely to be mounting competition for this limited resource in the near future, so increasing availability of crop residues via reduced burning is strategically advantageous (Toensmeier & Garrity, 2020).
In this analysis, we assume different approaches for the three primary sources of crop residues: maize, rice, and wheat. For maize and wheat, we assume adoption of no-till seeding equipment; for rice, we assume the use of balers.
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Eric Toensmeier
Daniel Jasper
Ruthie Borrows, Ph.D.
James Gerber Ph.D.
Sarah Gleeson Ph.D.
Paul West, Ph.D.
We used the IPCC methodology to determine CO₂, methane, and nitrous oxide emissions per metric ton of burning avoided, for the three main crops whose burning is tracked by the Food and Agriculture Organization of the United Nations (FAO): maize, rice, and wheat. These three crops collectively account for the majority of crop residue burning worldwide (Dong et al., 2019). We then weighted these emissions by the percentage of total burned residues that each crop represents.
We use estimated GWP-100 and GWP-20 values for black carbon from Bond et al. (2013). Black carbon is the most uncertain of climate pollutants for a range of reasons; that is why our analysis includes the high and low confidence intervals for GWP from Bond et al. as well. Because black carbon is particulate matter rather than a GHG, it is not included in global estimates of anthropogenic emissions (Bond et al., 2013). To reflect this, our analysis calculates black carbon climate impacts separately from those of other GHG emissions reduced by this solution.
For black carbon, the GWP-100 reduction is 0.38 t CO₂‑eq /t of avoided burning of crop residues, with an uncertainty of 0.04 to 0.76. The black carbon GWP-20 reduction is 1.34 t CO₂‑eq /t of avoided burning of crop residues, with an uncertainty of 0.13 to 2.69.
Note that we do not account for emissions stemming from alternative activities, such as the use of fuel for straw balers.
Agricultural financial data are generally reported in land units (US$/ha/yr). In this analysis, we convert these units to US$/t of crop residues using standard t residue/ha values from the IPCC Guidelines (Aalde et al., 2006).
For baseline rice, we assume the initial cost to be US$0.00/t because rice production is already established. Profit per hectare is based on regional figures from Damania et al. (2023), with a weighted average of US$82.5/t. Because initial cost is zero, net cost is US$82.5/t. Initial cost of reduced rice straw burning is based on purchase of rice baling equipment, assuming each baler serves 500 ha. The initial cost is US$4.55/t, profit is US$87.3/t, and net cost is –US$87.3/t.
For wheat, we assume adoption of no-till seeders, an important strategy to reduce burning given that it permits planting into crop residues (Dutta et al., 2022, Kabange et al., 2023, Kaur et al., 2022). The cost is based on purchase of a no-till seeder. Baseline initial cost is US$0.00/t. Profit per hectare is based on regional figures from Damania et al. (2023). Baseline profit is US$7.69/t and net cost is –US$7.69/t. No-till wheat’s initial cost is US$2.32/t, profit is US$40.7/t, and net cost is –US$43.0/t.
For maize, we assume no-till seeders, as for wheat. The prices per metric ton are different because of different values for t/ha of residue from IPCC (Dong et al., 2019). The cost is based on purchase of a no-till seeder. Baseline initial cost per metric ton is US$0.00. Profit per hectare is based on regional figures from Damania et al. (2023); profit is US$7.69/t, and net cost is –US$7.69/t. No-till maize’s initial cost is US$0.93/t. Profit is US$16.2/t, and net cost is –US$17.2/t.
We used a weighted average based on total t burned globally. Baseline initial values are US$0.00/t, profits are US$25.1/t, and net cost is –US$25.1/t. For reduced burning, the weighted initial cost is US$2.0/t, profit is US$3.4/t, and net cost is –US$38.8/t.
Finally, cost per metric ton CO₂ is –US$10.2/t CO₂‑eq. Note that these are costs to the farmer; including the negative costs of health improvements and environmental benefits associated with reduced burning would make the practice even more economically desirable. See table 2.
Table 2. Cost per unit of climate impact.
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| Median | -$10.20 |
Learning curve data are not available for reduced crop residue burning. However, it is likely that learning curves do exist for the baling and no-till seeding equipment modeled.
Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.
At Project Drawdown, we define the speed of action for each climate solution as emergency brake, gradual, or delayed.
Reduce Crop Residue Burning is an EMERGENCY BRAKE climate solution. It has the potential to deliver a more rapid impact than gradual and delayed solutions. Because emergency brake solutions can deliver their climate benefits quickly, they can help accelerate our efforts to address dangerous levels of climate change. For this reason, they are a high priority.
Caveats such as additionality and permanence do not apply to reduced crop residue burning.
Because the amount of crop residues burned each year globally is on the rise, we have not quantified current adoption (FAO, n.d.). From 2002–2022, residues burned increased 22% (67 Mt). See Table 3.
Table 3. Current adoption level.
Unit: t of crop residue burning avoided
| Median (50th percentile) | not determined |
We used FAO data showing metric tons burned for each year by country, for the three crops – maize, rice, and wheat – that account for the majority of burning (FAO, n.d.). We compared this to metric tons of those crops produced each year, and calculated the ratio of metric tons burned to metric tons produced, to make sure that reduced production of those crops did not appear as reduced burning. We express this as the “burn ratio,” which is metric tons of residues burned over total metric tons of residues produced.
During the past 20 years, the total metric tons of crop residues burned per year has increased, even as the percent of residues burned has decreased. This is because the total amount of crop residues has grown as the total cropping area – and crop yields per hectare – have increased.
French Polynesia, Haiti, and Cameroon share the lowest burn ratios (ratio of metric tons of residue burned to metric tons of crops produced). Each country burns only 1% of crop residues. We have chosen this rate of 99% of residues unburned as our adoption ceiling. Applying this 99% reduction to our total metric tons burned per year provides an adoption ceiling of 364 Mt of burning avoided per year. See Table 4.
Table 4. Adoption ceiling.
Unit: Mt of crop residue burning avoided/yr
| Median (50th percentile) | 364 |
The FAO (n.d.) found that Turkmenistan has the highest percent reduction of total crop residue burning of any country, with 77.8% over a 20-year period – a reduction of 18,900 t. We use Turkmenistan’s rate of reduction as our Achievable – High level of adoption. Note that other countries had higher total metric tonnage of burning avoided – with South Africa at the highest, at 894,000 t of burning avoided, but this was a smaller percent reduction than that of Turkmenistan. Applying Turkmenistan’s rate to the total global amount burned would provide a reduction of 287 Mt/yr.
While total global metric tons of crop residues burned is increasing, the burn rate decreased 23% between 1998–2002 and 2018–2022. We used this global average reduction rate of 23% for our Achievable – Low level of adoption. Applying this rate to the total global amount burned would provide a reduction of 85 Mt/yr. See Table 5.
Table 5. Range of achievable adoption levels.
Unit: Mt of avoided crop residue burning/yr
| Current adoption | 0 |
| Achievable – low | 85 |
| Achievable - high | 287 |
| Adoption ceiling | 364 |
The GHG climate impact of current adoption is 0.00 Gt CO₂‑eq/yr for all cases because current adoption is not determined (Table 6a–d).
The GHG climate impact for Achievable – Low adoption is 0.11 Gt CO₂‑eq/yr (100-yr basis). The climate impact for Achievable – High adoption is 0.39 Gt CO₂‑eq/yr (100-yr basis). The climate impact for the Adoption Ceiling is 0.49 Gt CO₂‑eq/yr (100-yr basis). See Table 6a.
For black carbon, impacts in GWP-100 are, for Achievable – Low adoption, 0.03 Gt CO₂‑eq/yr, with uncertainty range of 0.00–0.07; for Achievable – High adoption, 0.11 Gt CO₂‑eq/yr, with uncertainty range of 0.01–0.22; and, for the Adoption Ceiling, 0.14 Gt CO₂‑eq/yr, with an uncertainty range of 0.00–0.28. See Table 6b.
Meanwhile, climate impacts for GWP-20 at Achievable – Low adoption levels in GWP-20 are 0.12 Gt CO₂‑eq/yr, while climate impacts for GWP-20 at Achievable – High adoption levels in GWP-20 are 0.42 Gt CO₂‑eq/yr. Climate impacts for GWP-20 for the Adoption Ceiling in GWP-20 are 0.53 Gt CO₂‑eq/yr. See Table 6c.
For black carbon, impacts in GWP-20 are, for Achievable – Low adoption, 0.11 Gt CO₂‑eq/yr, with uncertainty range of 0.00–0.23; for Achievable – High adoption, 0.39 Gt CO₂‑eq/yr, with uncertainty range of 0.04–0.77; and, for the Adoption Ceiling, 0.49 Gt CO₂‑eq/yr with an uncertainty range of 0.05–0.98. See Table 6d.
Table 6. Climate impact at different levels of adoption.
Unit: GtCO₂‑eq/yr
| Current adoption | 0.00 |
| Achievable – low | 0.11 |
| Achievable – high | 0.39 |
| Adoption ceiling | 0.49 |
Unit: GtCO₂‑eq/yr
| Current adoption | 0.00 |
| Achievable – low | 0.03 |
| Achievable – high | 0.11 |
| Adoption ceiling | 0.14 |
Unit: GtCO₂‑eq/yr
| Current adoption | 0.00 |
| Achievable – low | 0.12 |
| Achievable – high | 0.42 |
| Adoption ceiling | 0.53 |
Unit: GtCO₂‑eq/yr
| Current adoption | 0.00 |
| Achievable – low | 0.11 |
| Achievable – high | 0.39 |
| Adoption ceiling | 0.49 |
Income and Work
Sustainable crop residue management can not only reduce morbidity and mortality, but also significantly reduce health costs associated with crop residue burning (Raza et al., 2022). Farmers can increase revenues by adopting alternative practices that use crop residues instead of burning them, such as selling residues or producing biochar or bio-oils (Na Talang et al., 2024).
Health
Poor air quality stemming from crop residue burning is harmful to health, and has demonstrably contributed to premature mortality in Southeast Asia (Lan et al., 2022). More generally, air pollution from burning crop residue has been linked to eye irritation, headaches, nausea, skin irritation, allergies, respiratory infections, increased risk of lung cancer, and reduced lung function (Gupta, 2019; Huang et al., 2022; Raza et al., 2022). During burning season, farmers have reported increasing severity of chronic illnesses as well as poorer productivity at work due to illness (Raza et al., 2022). Exposure to air pollution is particularly harmful for children because it can harm their development; Gupta et al. (2019) found that children living near agricultural fields had poorer lung function during periods of crop burning. Sustainable crop residue management can not only reduce morbidity and mortality, but also significantly reduce health costs associated with crop residue burning (Raza et al., 2022).
Land Resources
Crop residue burning can significantly degrade soils because burning leads to a loss of nutrients – especially nitrogen – that might otherwise be retained in the soil (Bhuvaneshwari et al., 2019). For example, in areas in northern India where crop residue burning is common, soils have very low nitrogen content compared with those in other regions of the country where crop burning is less common (Kumar et al., 2015). Burning also raises soil temperatures, which can kill beneficial microorganisms (Bhuvaneshwari et al., 2019).
Studies have found that retaining crop residue on agricultural fields can benefit soil quality, soil organic carbon, soil moisture, nutrient cycling, and soil retention (Fu et al., 2021; Turmel et al., 2015). In experimental field sites in India and Bhutan, crop residue was used as mulch rather than burned, and agricultural production subsequently increased 36–64% (Dey et al., 2020).
Air Quality
Crop residue burning is a major source of air pollution because it generates fine particulate matter, CO₂, and carbon monoxide across regions such as South and Southeast Asia, and especially in countries including India, Pakistan, Nepal, and Bangladesh (Jain et al., 2014; Kaskaoutis et al., 2014; Lan et al., 2022; Na Talang et al., 2024; Sharma et al., 2010, Singh et al., 2021). The burning of rice straw is often the largest contributor to air pollution, followed by wheat straw, sugarcane, and corn (Jain et al., 2014; Na Talang et al., 2024). In India, crop residue burning is most common in northern states such as Punjab, Haryana, and Uttar Pradesh (Sakar et al., 2018). Because fine particulate matter and black carbon constitute a large percentage of the pollution, crop residue burning can trigger poor air quality hundreds of kilometers away from agricultural fields (Kaskaoutis et al., 2014). In fact, several studies have found that crop residue burning in northern India threatens the air quality throughout the country – especially in Delhi, the densely populated capital region (Bikkina et al., 2019; Lan et al., 2022; Sarkar et al., 2018).
For rice – mechanically harvesting of residues for off-farm use risks losses of soil fertility. There is also a risk that harvested residues will be burned off-farm, producing the same emissions and health concerns as on-field residue burning. (Dutta et al.,2022; Krishna and Mkondiwa, 2023; Raza et al., (2022); Singh et al., 2022.
We assume wheat and maize production shifts to retaining residue in fields and subsequently uses no-till seeding equipment to plant through the residues. Risks associated with this practice include increased herbicide use (Clapp, 2021).
This solution increases the supply of crop residues. In turn, this makes more raw material available for the following solutions:
t of crop residue burning avoided
CO₂, CH₄ , N₂O , BC
To maintain soil organic carbon levels, it is necessary to retain half of crop residues on the field. This practice applies to maize, rice, and wheat (Lorenz & Lal, 2018).
Consensus of effectiveness in reducing GHG emissions: High
There is high consensus on the effectiveness and potential of reducing crop residue burning. The 2019 Refinement to the 2006 U.N. Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories provides clear formulas to calculate the impact of crop residue burning as well as the impact of limiting the practice (Dong et al., 2019). With the latest IPCC chapter on agricultural mitigation identifying crop residue burning as an important driver of global warming, advancing viable alternatives to the practice is vital (Nabuurs et al., 2022). Overviews of the alternatives to crop residue burning are provided by Dutta e. al. (2022), Krishna and Mkondiwa (2023), Singh et al. (2022), and Raza et al. (2022).
The results presented in this analysis summarize findings from five reviews and meta-analyses reflecting current evidence at the global scale. Nonetheless, not all countries are represented. We recognize this limited geographic scope creates bias, and hope this work inspires research and data sharing on this topic in underrepresented regions.
Irrigation water use efficiency involves reducing water use without compromising crop productivity by improving irrigation scheduling and/or equipment. Irrigation produces GHG emissions by altering biogeochemical cycling of carbon and nitrogen cycles in water and soils, and through energy use for pumping. Reducing the duration of soil saturation, the amount of groundwater extracted, and the total volume of water pumped can help reduce associated emissions. However, data on the effectiveness of improved water use efficiency in reducing emissions remain very limited. We will "Keep Watching" this solution as additional data become available.
Improving irrigation water use efficiency is a promising strategy for reducing emissions. However, additional data are needed to evaluate the magnitude of its impact and its effectiveness, especially under different environmental and management conditions. Therefore, this solution is classified as "Keep Watching."
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | Yes |
| Evidence | Are there data to evaluate it? | Limited |
| Effective | Does it consistently work? | ? |
| Impact | Is it big enough to matter? | ? |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | Yes |
Improving irrigation water use efficiency involves optimizing the timing, volume, and method of irrigation to reduce water use while still meeting crop water demand, thereby reducing emissions from soils, extracted groundwater, and pumping. Irrigation is the practice of adding water to croplands or pastures to reduce crop water stress and increase productivity. However, irrigation also creates wet soil conditions that promote nitrous oxide emissions, releases greenhouse gases that had been dissolved in groundwater, and, in some cases, uses energy to pump water. Increasing water use efficiency will reduce the duration of near-saturated soil conditions, potentially reducing nitrous oxide emissions from soils. For the ~40% of global irrigated croplands that rely on groundwater, increasing water use efficiency will reduce emissions from groundwater. For irrigation systems that use pumps powered by fossil fuels or non-renewable electricity, improving water use efficiency can also reduce pumping-related emissions. Of note, energy use for pumping is also addressed by Deploy Electric Irrigation Pumps.
Although the mechanisms by which improved irrigation water use efficiency can reduce emissions from soils, groundwater, and pumping are scientifically sound, the effectiveness of this solution is context-dependent, and data on effectiveness and potential impact are very limited.
Irrigation contributes to nitrous oxide emissions by stimulating denitrification, a microbial process that produces nitrous oxide emissions and tends to occur when soils are nearly saturated with water. Reducing the frequency and duration of near-saturated conditions through improved irrigation water use efficiency will likely reduce associated pulses of nitrous oxide emissions. One recent study reported that irrigation increased nitrous oxide emissions from U.S. croplands by 2.9 Mt CO₂‑eq/yr. However, data on nitrous oxide emissions under different types of irrigation management, including improved water use efficiency, are not yet available.
For croplands irrigated with groundwater, reducing water use will directly reduce emissions from groundwater degassing. Groundwater is often supersaturated in CO₂, meaning that it contains more dissolved CO₂ gas than the atmosphere. The excess CO₂ in groundwater accumulates from two sources: 1) the air space in soils tends to have high CO₂ concentrations from microbial respiration, and groundwater absorbs some of the CO₂ as it percolates through the soil profile; and 2) groundwater reacts with carbonate-containing minerals in aquifers. Similarly, dissolved nitrous oxide can also accumulate in groundwater, particularly in regions with heavy fertilizer use. However, the concentration of these GHGs in groundwater remains uncertain as it varies substantially between aquifers. Recent studies have estimated that degassing of CO₂ from groundwater produces 1.7–3.6 Mt CO₂‑eq/yr in the U.S., and one global study reported 6 Mt CO₂‑eq/yr ; however, many uncertainties remain in these studies.
For croplands that already rely on pumps for irrigation, improving irrigation scheduling to reduce water use will reduce emissions from energy use. However, other croplands rely on surface water and gravity irrigation methods and do not require pumps. For these croplands, switching to sprinklers or drip irrigation will increase water use efficiency but will also require the addition of pumps and associated energy use emissions.
Irrigation has a tremendous impact on the planet, accounting for nearly 90% of human-caused consumptive water use. Globally, around 23% of croplands are irrigated. Therefore, opportunities to increase water use efficiency abound, and improvements in irrigation water management can have widespread impacts. Many places are facing surface water shortages and groundwater depletion, and improving irrigation practices is a critical part of sustainable water management as resource availability changes. Increases in irrigation water use efficiency have the potential to help alleviate water scarcity when coupled with appropriate policy reforms. Moreover, reducing water use can also reduce energy and water costs for producers, and reductions in runoff can improve water quality and slow erosion, benefitting biodiversity and soil health.
Due to limited data, the effects of irrigation on emissions from groundwater and soils remain poorly understood. Additional data, including direct field measurements, are needed before we can confidently assess the effectiveness of improved irrigation water use efficiency in reducing emissions. The effectiveness of this solution depends on environmental and management conditions, the extent to which water use is reduced, and the method used to improve irrigation water use efficiency.
It is important that improvements in irrigation water use efficiency do not compromise crop yields. Efforts to improve irrigation water use efficiency that impose water stress and reduce yields can lead to the expansion of agricultural land, resulting in the loss of carbon-rich ecosystems.
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Avery Driscoll, Ph.D.
Christina Swanson, Ph.D.
Heather McDiarmid, Ph.D.
James Gerber, Ph.D.
We define the Improve Nutrient Management solution as reducing excessive nitrogen use on croplands. Nitrogen is critical for crop production and is added to croplands as synthetic or organic fertilizers and through microbial activity. However, farmers often add more nitrogen to croplands than crops can use. Some of that excess nitrogen is emitted to the atmosphere as nitrous oxide, a potent GHG.
Agriculture is the dominant source of human-caused emissions of nitrous oxide (Tian et al., 2020). Nitrogen is critical for plant growth and is added to croplands in synthetic forms, such as urea, ammonium nitrate, or anhydrous ammonia; in organic forms, such as manure or compost; and by growing legume crops, which host microbes that capture nitrogen from the air and add it to the soil (Adalibieke et al., 2023; Ludemann et al., 2024). If more nitrogen is added than crops can use, the excess can be converted to other forms, including nitrous oxide, through microbial processes called denitrification and nitrification (Figure 1; Reay et al., 2012).
Figure 1. The agricultural nitrogen cycle represents the key pathways by which nitrogen is added to croplands and lost to the environment, including as nitrous oxide. The “4R” nutrient management principles – right source, right rate, right time, right place – increase the proportion of nitrogen taken up by the plant, therefore reducing nitrogen losses to the environment.
Illustrations: BioRender CC-BY 4.0
Farmers can reduce nitrous oxide emissions from croplands by using the right amount and the right type of fertilizer at the right time and in the right place (Fixen, 2020; Gao & Cabrera Serrenho, 2023). Together, these four “rights” increase nitrogen use efficiency – the proportion of applied nitrogen that the crop uses (Congreves et al., 2021). Improved nutrient management is often a win-win for the farmer and the environment, reducing fertilizer costs while also lowering nitrous oxide emissions (Gu et al., 2023).
Improving nutrient management involves reducing the amount of nitrogen applied to match the crop’s requirements in areas where nitrogen is currently overapplied. A farmer can implement the other three principles – type, time, and place – in a number of ways. For example, fertilizing just before planting instead of after the previous season’s harvest better matches the timing of nitrogen addition to that of plant uptake, reducing nitrous oxide emissions before the crop is planted. Certain types of fertilizers are better suited for maximizing plant uptake, such as extended-release fertilizers, which allow the crop to steadily absorb nutrients over time. Techniques such as banding, in which farmers apply fertilizers in concentrated bands close to the plant roots instead of spreading them evenly across the soil surface, also reduce nitrous oxide emissions. Each of these practices can increase nitrogen use efficiency and decrease the amount of excess nitrogen lost as nitrous oxide (Gao & Cabrera Serrenho, 2023; Gu et al., 2023; Wang et al., 2024; You et al., 2023).
For this solution, we estimated a target rate of nitrogen application for major crops as the 20th percentile of the current rate of nitrogen application (in t N/t crop) in areas where yields are near a realistic ceiling. Excess nitrogen was defined as the amount of nitrogen applied beyond the target rate (see Adoption and Appendix for more details). Our emissions estimates include nitrous oxide from croplands, fertilizer runoff, and fertilizer volatilization. They do not include emissions from fertilizer manufacturing, which are addressed in the Deploy Low-Emission Industrial Feedstocks and Boost Industrial Efficiency solutions. We excluded nutrient management on pastures from this solution due to data limitations and address nutrient management in paddy rice systems in the Improve Rice Production solution instead.
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Avery Driscoll
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Eric Toensmeier
Aiyana Bodi
Hannah Henkin
Ted Otte
We relied on the 2019 Intergovernmental Panel on Climate Change (IPCC) emissions factors to calculate the emissions impacts of improved nutrient management. These are disaggregated by climate zone (“wet” vs. “dry”) and by fertilizer type (“organic” vs. “synthetic”). Nitrogen use reductions in wet climates, which include ~65% of the cropland area represented in this analysis (see Appendix for details), have the largest impact. In these areas, a 1 t reduction in nitrogen use reduces emissions by 8.7 t CO₂‑eq on average for synthetic fertilizers and by 5.0 t CO₂‑eq for organic fertilizers. Emissions savings are lower in dry climates, where a 1 t reduction in nitrogen use reduces emissions by 2.4 t CO₂‑eq for synthetic fertilizers and by 2.6 t CO₂‑eq for organic fertilizers. While these values reflect the median emissions reduction for each climate zone and fertilizer type, they are associated with large uncertainties because emissions are highly variable depending on climate, soil, and management conditions.
Based on our analysis of the adoption ceiling for each climate zone and fertilizer type (see Appendix), we estimated that a 1 t reduction in nitrogen use reduces emissions by 6.0 t CO₂‑eq at the global median (Table 1). This suggests that ~1.4% of the applied nitrogen is emitted as nitrous oxide at the global average, which is consistent with existing estimates (IPCC, 2019).
Table 1. Effectiveness at reducing emissions.
Unit: t CO₂‑eq /t nitrogen, 100-yr basis
| 25th percentile | 4.2 |
| Median (50th percentile) | 6.0 |
| 75th percentile | 7.7 |
Improving nutrient management typically reduces fertilizer costs while maintaining or increasing yields, resulting in a net financial benefit to the producer. Gu et al. (2023) found that a 21% reduction in global nitrogen use would be economically beneficial, notably after accounting for increased fertilizer use in places that do not currently have adequate access. Using data from their study, we evaluated the average cost of reduced nitrogen application considering the following nutrient management practices: increased use of high-efficiency fertilizers, organic fertilizers, and/or legumes; optimizing fertilizer rates; altering the timing and/or placement of fertilizer applications; and use of buffer zones. Implementation costs depend on the strategy used to improve nutrient management. For example, optimizing fertilizer rates requires soil testing and the ability to apply different fertilizer rates to different parts of a field. Improving timing can involve applying fertilizers at two different times during the season, increasing labor and equipment operation costs. Furthermore, planting legumes incurs seed purchase and planting costs.
Gu et al. (2023) estimated that annual reductions of 42 Mt of nitrogen were achievable globally using these practices, providing total fertilizer savings of US$37.2 billion and requiring implementation costs of US$15.9 billion, adjusted for inflation to 2023. A 1 t reduction in excess nitrogen application, therefore, was estimated to provide an average of US$507.80 of net cost savings, corresponding to a savings of US$85.21 per t CO₂‑eq of emissions reductions (Table 2).
Table 2. Cost per unit of climate impact, 100-yr basis.
Unit: 2023 US$/t CO₂‑eq
| Mean | -85.21 |
The improved nutrient management strategies considered for this solution are already well established and widely deployed (Fixen, 2020). Large nitrogen excesses are relatively easy to mitigate through simple management changes with low implementation costs. As nitrogen use efficiency increases, further reductions may require increasingly complex mitigation practices and increasing marginal costs. Therefore, a learning curve was not quantified for this solution.
Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.
At Project Drawdown, we define the speed of action for each climate solution as emergency brake, gradual, or delayed.
Improve Nutrient Management is a GRADUAL climate solution. It has a steady, linear impact on the atmosphere. The cumulative effect over time builds as a straight line.
Emissions reductions from improved nutrient management are permanent, though they may not be additional in all cases.
As this solution reduces emissions rather than enhancing sequestration, permanence is not applicable.
Additionality requires that the emissions benefits of the practice are attributable to climate-related incentives and would not have occurred in the absence of incentives (Michaelowa et al., 2019). If they are not contingent on external incentives, fertilizer use reductions implemented solely to maximize profits do not meet the threshold for additionality. However, fertilizer reductions may be additional if incentives are required to provide access to the technical knowledge and soil testing required to identify optimal rates. Other forms of nutrient management (e.g., applying nitrification inhibitors, using extended-release or organic fertilizers, or splitting applications between two time points) may involve additional costs, substantial practice change, and technical expertise. Thus, these practices are likely to be additional.
Given that improved nutrient management takes a variety of forms and data on the adoption of individual practices are very limited, we leveraged several global datasets related to nitrogen use and yields to directly assess improvements in nitrogen use efficiency (see Appendix for details).
First, we calculated nitrogen use per metric ton of crop produced using global maps of nitrogen fertilizer use (Adalibieke et al., 2023) and global maps of crop yields (Gerber et al., 2024) for 17 major crops (see Appendix). Next, we determined a target nitrogen use rate (t nitrogen/t crop) for each crop, corresponding to the 20th percentile of nitrogen use rates observed in croplands with yield gaps at or below the 20th percentile, meaning that actual yields were close to an attainable yield ceiling (Gerber et al., 2024). Areas with large yield gaps were excluded from the calculation of target nutrient use efficiency because insufficient nitrogen supply may be compromising yields (Mueller et al., 2012). Yield data were not available for a small number of crops; for these, we assumed reductions in nitrogen use to be proportional to those of other crops.
We considered croplands that had achieved the target rate and had yield gaps lower than the global median to have adopted the solution. We calculated the amount of excess nitrogen use avoided from these croplands as the difference in total nitrogen use under current fertilization rates relative to median fertilizer application rates. As of 2020, croplands that had achieved the adoption threshold for improved nutrient management avoided 10.45 Mt of nitrogen annually relative to the median nitrogen use rate (Table 3), equivalent to 11% of the adoption ceiling.
Table 3. Current (2020) adoption level.
Unit: t nitrogen/yr
| Estimate | 10,450,000 |
Global average nitrogen use efficiency increased from 47.7% to 54.6% between 2000 and 2020, a rate of approximately 0.43%/yr (Ludemann et al., 2024). This increase accelerated somewhat in the latter decade, from an average rate of 0.38%/yr to 0.53%/yr. Underlying this increase were increases in both the amount of nitrogen used and the amount of excess nitrogen. Total nitrogen additions increased by approximately 2.64 Mt/yr, with the amount of nitrogen used increasing more rapidly (1.99 Mt/yr) than the amount of excess nitrogen (0.65 Mt/yr) between 2000 and 2020 (Ludemann et al., 2024). Although nitrogen use increased between 2000 and 2020 as yields increased, the increase in nitrogen use efficiency suggests uptake of this solution.
We estimated the adoption ceiling of improved nutrient management to be 95.13 Mt avoided excess nitrogen use/year, not including current adoption (Table 4). This value reflects our estimate of the maximum potential reduction in nitrogen application while avoiding large yield losses and consists of the potential to avoid 62.25 Mt of synthetic nitrogen use and 32.88 Mt of manure and other organic nitrogen use, in addition to current adoption. In total, this is equivalent to an additional 68% reduction in global nitrogen use. The adoption ceiling was calculated as the difference between total nitrogen use at the current rate and total nitrogen use at the target rate (as described in Current Adoption), assuming no change in crop yields. For nitrogen applied to crops for which yield data were not available, the potential reduction in nitrogen use was assumed to be proportional to that of crops for which full data were available.
Table 4. Adoption ceiling.
Unit: t nitrogen/yr
| Estimate | 105,580,000 |
We estimated that fertilizer use reductions of 69.85–91.06 Mt of nitrogen are achievable, reflecting current adoption plus nitrogen savings due to the achievement of nitrogen application rates equal to the median and 30th percentile of nitrogen application rates occurring in locations where yield gaps are small (Table 5).
This range is more ambitious than a comparable recent estimate by Gu et al. (2023), who found that reductions of approximately 42 Mt of nitrogen are avoidable via cost-effective implementation of similar practices. Differences in target nitrogen use efficiencies underlie differences between our estimates and those of Gu et al., whose findings correspond to an increase in global average cropland nitrogen use efficiency from 42% to 52%. Our estimates reflect higher target nitrogen use efficiencies. Nitrogen use efficiencies greater than 52% have been widely achieved through basic practice modification without compromising yields or requiring prohibitively expensive additional inputs. For instance, You et al. (2023) estimated that the global average nitrogen use efficiency could be increased to 78%. Similarly, cropland nitrogen use efficiency in the United States in 2020 was estimated to be 71%, and substantial opportunities for improved nitrogen use efficiency are still available within the United States (Ludemann et al., 2024), though Lu et al. (2019) and Swaney et al. (2018) report slightly lower estimates. These findings support our slightly more ambitious range of achievable nitrogen use reductions for this solution.
Table 5. Range of achievable adoption levels.
Unit: t nitrogen/yr
| Current adoption | 10,450,000 |
| Achievable – low | 69,850,000 |
| Achievable – high | 91,060,000 |
| Adoption ceiling | 105,580,000 |
We estimated that improved nutrient management has the potential to reduce emissions by 0.63 Gt CO₂‑eq/yr, with achievable emissions reductions of 0.42–0.54 Gt CO₂‑eq/yr (Table 6). This is equivalent to an additional 56–76% reduction in total nitrous oxide emissions from fertilizer use, based on the croplands represented in our analysis.
We estimated avoidable emissions by multiplying our estimates of adoption ceiling and achievable adoption by the relevant IPCC 2019 emissions factors, disaggregated by climate zone and fertilizer type. Under the adoption ceiling scenario, approximately 70% of emissions reductions occurred in wet climates, where emissions per t of applied fertilizer are higher. Reductions in synthetic fertilizer use, which are larger than reductions in organic fertilizer use, contributed about 76% of the potential avoidable emissions. We estimated that the current implementation of improved nutrient management was associated with 0.06 Gt CO₂‑eq/yr of avoided emissions.
Our estimates are slightly more optimistic but well within the range of the IPCC 2021 estimates, which found that improved nutrient management could reduce nitrous oxide emissions by 0.06–0.7 Gt CO₂‑eq/yr.
Table 6. Climate impact at different levels of adoption.
Unit: Gt CO₂-eq/yr, 100-yr basis
| Current adoption | 0.06 |
| Achievable – low | 0.42 |
| Achievable – high | 0.54 |
| Adoption ceiling | 0.63 |
Balanced nutrient concentration contributes to long-term soil fertility and improved soil health by enhancing organic matter content, microbial diversity, and nutrient cycling (Antil & Raj, 2020; Selim, 2020). Healthy soil experiences reduced erosion and has higher water content, which increases its resilience to droughts and extreme heat (Rockström et al., 2017).
Better nutrient management reduces farmers' input costs and increases profitability (Rurinda et al., 2020; Wang et al., 2020). It is especially beneficial to smallholder farmers in sub-Saharan Africa, where site-specific nutrient management programs have demonstrated a significant increase in yield (Chivenge et al., 2021). A review of 61 studies across 11 countries showed that site-specific nutrient management resulted in an average increase in yield by 12% and increased farmer’s’ income by 15% while improving nitrogen use efficiency (Chivenge et al., 2021).
While excessive nutrients cause environmental problems in some parts of the world, insufficient nutrients are a significant problem in others, resulting in lower agricultural yields (Foley et al., 2011). Targeted, site-specific, efficient use of fertilizers can improve crop productivity (Mueller et al., 2012; Vanlauwe et al., 2015), improving food security globally.
Domingo et al. (2021) estimated about 16,000 premature deaths annually in the United States are due to air pollution from the food sector and found that more than 3,500 premature deaths per year could be avoided through reduced use of ammonia fertilizer, a secondary particulate matter precursor. Better agriculture practices overall can reduce particulate matter-related premature deaths from the agriculture sector by 50% (Domingo et al., 2021). Nitrogen oxides from fertilized croplands are another source of agriculture-based air pollution, and improved management can lead to decreased respiratory and cardiovascular disease (Almarez et al., 2018; Sobota et al., 2015).
Nitrate contamination of drinking water due to excessive runoff from agriculture fields has been linked to several health issues, including blood disorders and cancer (Patel et al., 2022; Ward et al., 2018). Reducing nutrient runoff through better management is critical to minimize these risks (Ward et al., 2018).
Nutrient runoff from agricultural systems is a major driver of water pollution globally, leading to eutrophication and hypoxic zones in aquatic ecosystems (Bijay-Singh & Craswell, 2021). Nitrogen pollution also harms terrestrial biodiversity through soil acidification and increases productivity of fast-growing species, including invasives, which can outcompete native species (Porter et al., 2013). Improved nutrient management is necessary to reduce nitrogen and phosphorus loads to water bodies (Withers et al., 2014; van Grinsven et al., 2019) and terrestrial ecosystems (Porter et al., 2013). These practices have been effective in reducing harmful algal blooms and preserving biodiversity in sensitive water systems (Scavia et al., 2014).
Although substantial reductions in nitrogen use can be achieved in many places with no or minimal impacts on yields, reducing nitrogen application by too much can lead to yield declines, which in turn can boost demand for cropland, causing GHG-producing land use change. Reductions in only excess nitrogen application will prevent substantial yield losses.
Some nutrient management practices are associated with additional emissions. For example, nitrification inhibitors reduce direct nitrous oxide emissions (Qiao et al., 2014) but can increase ammonia volatilization and subsequent indirect nitrous oxide emissions (Lam et al., 2016). Additionally, in wet climates, nitrous oxide emissions may be reduced through the use of manure instead of synthetic fertilizers (Hergoualc’h et al., 2019), though impacts vary across sites and studies (Zhang et al., 2020). Increased demand for manure could increase livestock production, which has high associated GHG emissions. Emissions also arise from transporting manure to the site of use (Qin et al., 2021).
Although nitrous oxide has a strong direct climate-warming effect, fertilizer use can cool the climate through emissions of other reactive nitrogen-containing compounds (Gong et al., 2024). First, aerosols from fertilizers scatter heat from the sun and cool the climate (Shindell et al., 2009; Gong et al., 2024). Moreover, other reactive nitrogen compounds from fertilizers shorten the lifespan of methane in the atmosphere, reducing its warming effects (Pinder et al., 2012). Finally, nitrogen fertilizers that leave farm fields through volatilization or runoff are ultimately deposited elsewhere, enhancing photosynthesis and storing more carbon in plants and soils (Zaehle et al., 2011; Gong et al., 2024). Improved nutrient management would reduce these cooling effects.
Improved nutrient management will reduce emissions from the production phase of biomass crops, increasing their benefit.
(mixed) Improving nutrient management can reduce nutrient pollution in nearby and downstream ecosystems, aiding in their protection or restoration. However, this interaction can be mixed as fertilizer can also enhance terrestrial primary productivity and carbon sequestration in some landscapes.
Improved nutrient management will reduce the GHG production associated with each calorie and, therefore, the impacts of the Improve Diets and Reduce Food Loss and Waste solutions will be reduced.
Each of these solutions could decrease emissions associated with fertilizer production, but improved nutrient management will reduce total demand for fertilizers.
t avoided excess nitrogen application
N₂O
The world’s agricultural lands can emit high levels of nitrous oxide, the third most powerful greenhouse gas. These emissions stem from overusing nitrogen-based fertilizers, especially in regions in China, India, Western Europe, and central North America (in red). While crops absorb some of the nitrogen fertilizer we apply, much of what remains is lost to the atmosphere as nitrous oxide pollution or to local waterways as nitrate pollution. Using fertilizers more wisely can dramatically reduce greenhouse gas emissions and water pollution while maintaining high levels of crop production.
Project Drawdown
The world’s agricultural lands can emit high levels of nitrous oxide, the third most powerful greenhouse gas. These emissions stem from overusing nitrogen-based fertilizers, especially in regions in China, India, Western Europe, and central North America (in red). While crops absorb some of the nitrogen fertilizer we apply, much of what remains is lost to the atmosphere as nitrous oxide pollution or to local waterways as nitrate pollution. Using fertilizers more wisely can dramatically reduce greenhouse gas emissions and water pollution while maintaining high levels of crop production.
Project Drawdown
Improved nutrient management will have the greatest emissions reduction if it is targeted at areas with the largest excesses of nitrogen fertilizer use. In 2020, China, India, and the United States alone accounted for 52% of global excess nitrogen application (Ludemann et al., 2024). Improved nutrient management could be particularly beneficial in China and India, where nutrient use efficiency is currently lower than average (Ludemann et al., 2024). You et al. (2023) also found potential for large increases in nitrogen use efficiency in parts of China, India, Australia, Northern Europe, the United States Midwest, Mexico, and Brazil under standard best management practices. Gu et al. (2024) found that nitrogen input reductions are economically feasible in most of Southern Asia, Northern and Western Europe, parts of the Middle East, North America, and Oceania.
In addition to regional patterns in the adoption ceiling, greater nitrous oxide emissions reductions are possible in wet climates or on irrigated croplands compared to dry climates. Nitrous oxide emissions tend to peak when nitrogen availability is high and soil moisture is in the ~70–90% range (Betterbach-Bahl et al., 2013; Elberling et al., 2023; Hao et al., 2025; Lawrence et al., 2021), though untangling the drivers of nitrous oxide emissions is complex (Lawrence et al., 2021). Water management to avoid prolonged periods of soil moisture in this range is an important complement to nutrient management in wet climates and on irrigated croplands (Deng et al., 2018).
Importantly, improved nutrient management, as defined here, is not appropriate for implementation in areas with nitrogen deficits or negligible nitrogen surpluses, including much of Africa. In these areas, crop yields are constrained by nitrogen availability, and an increase in nutrient inputs may be needed to achieve target yields. Additionally, nutrient management in paddy (flooded) rice systems is not included in this solution but rather in the Improve Rice Production solution.
There is high scientific consensus that reducing nitrogen surpluses through improved nutrient management reduces nitrous oxide emissions from croplands.
Nutrient additions to croplands produce an estimated 0.9 Gt CO₂‑eq/yr (range 0.7–1.1 Gt CO₂‑eq/yr ) of direct nitrous oxide emissions from fields, plus approximately 0.3 Gt CO₂‑eq/yr of emissions from fertilizers that runoff into waterways or erode (Tian et al., 2020). Nitrous oxide emissions from croplands are directly linked to the amount of nitrogen applied. Furthermore, the amount of nitrous oxide emitted per unit of applied nitrogen is well quantified for a range of different nitrogen sources and field conditions (Reay et al., 2012; Shcherbak et al., 2014; Gerber et al., 2016; Intergovernmental Panel on Climate Change [IPCC], 2019; Hergoualc’h et al., 2021). Tools to improve nutrient management have been extensively studied, and practices that improve nitrogen use efficiency through right rate, time, place, and type principles have been implemented in some places for several decades (Fixen, 2020; Ludemann et al., 2024).
Recently, Gao & Cabrera Serrenho (2023) estimated that fertilizer-related emissions could be reduced up to 80% by 2050 relative to current levels using a combination of nutrient management and new fertilizer production methods. You et al. (2023) found that adopting improved nutrient management practices would increase nitrogen use efficiency from a global average of 48% to 78%, substantially reducing excess nitrogen. Wang et al. (2024) estimated that the use of enhanced-efficiency fertilizers could reduce nitrogen losses to the environment 70–75% for maize and wheat systems. Chivenge et al. (2021) found comparable results in smallholder systems in Africa and Asia.
The results presented in this document were produced through analysis of global datasets. We recognize that geographic biases can influence the development of global datasets and hope this work inspires research and data sharing on this topic in underrepresented regions.
In this analysis, we calculated the potential for reducing crop nitrogen inputs and associated nitrous oxide emissions by integrating spatially explicit, crop-specific data on nitrogen inputs, crop yields, attainable yields, irrigated extent, and climate. Broadly, we calculated a “target” yield-scaled nitrogen input rate based on pixels with low yield gaps and calculated the difference between nitrous oxide emissions under the current rate and under the hypothetical target emissions rate, using nitrous oxide emissions factors disaggregated by fertilizer type and climate.
We used Tier 1 emissions factors from the IPCC 2019 Refinement to the 2006 Guidelines for National Greenhouse Gas Inventories, including direct emissions factors as well as indirect emissions from volatilization and leaching pathways. Direct emissions factors represent the proportion of applied nitrogen emitted as nitrous oxide, while we calculated volatilization and leaching emissions factors by multiplying the proportion of applied nitrogen lost through these pathways by the proportion of volatilized or leached nitrogen ultimately emitted as nitrous oxide. Including both direct and indirect emissions, organic and synthetic fertilizers emit 4.97 kg CO₂‑eq/kg nitrogen and 8.66 kg CO₂‑eq/kg nitrogen, respectively, in wet climates, and 2.59 kg CO₂‑eq/kg nitrogen and 2.38 kg CO₂‑eq/kg nitrogen in dry climates. We included uncertainty bounds (2.5th and 97.5th percentiles) for all emissions factors.
We classified each pixel as “wet” or “dry” using an aridity index (AI) threshold of 0.65, calculated as the ratio of annual precipitation to potential evapotranspiration (PET) from TerraClimate data (1991–2020), based on a threshold of 0.65. For pixels in dry climates that contained irrigation, we took the weighted average of wet and dry emissions factors based on the fraction of cropland that was irrigated (Mehta et al., 2024). We excluded irrigated rice from this analysis due to large differences in nitrous oxide dynamics in flooded rice systems.
Using highly disaggregated data on nitrogen inputs from Adalibieke et al. (2024) for 21 crop groups (Table S1), we calculated total crop-specific inputs of synthetic and organic nitrogen. We then averaged over 2016–2020 to reduce the influence of interannual variability in factors like fertilizer prices. These values are subsequently referred to as “current” nitrogen inputs. We calculated nitrous oxide emissions under current nitrogen inputs as the sum of the products of nitrogen inputs and the climatically relevant emissions factors for each fertilizer type.
Next, we calculated target nitrogen application rates in terms of kg nitrogen per ton of crop yield using data on actual and attainable yields for 17 crops from Gerber et al., 2024 (Table S1). For each crop, we first identified pixels in which the ratio of actual to attainable yields was above the 80th percentile globally. The target nitrogen application rate was then calculated as the 20th percentile of nitrogen application rates across low-yield-gap pixels. Finally, we calculated total target nitrogen inputs as the product of actual yields and target nitrogen input rates. We calculated hypothetical nitrous oxide emissions from target nitrogen inputs as the product of nitrogen inputs and the climatically relevant emissions factor for each fertilizer type.
The difference between current and target nitrogen inputs represents the amount by which nitrogen inputs could hypothetically be reduced without compromising crop productivity (i.e., “avoidable” nitrogen inputs). We calculated avoidable nitrous oxide emissions as the difference between nitrous oxide emissions with current nitrogen inputs and those with target nitrogen inputs. For crops for which no yield or attainable yield data were available, we applied the average percent reduction in nitrogen inputs under the target scenario from available crops to the nitrogen input data for missing crops to calculate the avoidable nitrogen inputs and emissions.
This simple and empirically driven method aimed to identify realistically low but nutritionally adequate nitrogen application rates by including only pixels with low yield gaps, which are unlikely to be substantially nutrient-constrained. We did not control for other factors affecting nitrogen availability, such as historical nutrient application rates or depletion, rotation with nitrogen fixing crops, or tillage and residue retention practices.
Table S1. Crops represented by the source data on nitrogen inputs (Adalibieke et al., 2024) and estimated and attainable yields (Gerber et al., 2024). Crop groups included consistently in both datasets are marked as “both,” and crop groups represented in the nitrogen input data but not in the yield datasets are marked as “nitrogen only.”
| Crop | Dataset(s) |
|---|---|
| Barley | Both |
| Cassava | Both |
| Cotton | Both |
| Maize | Both |
| Millet | Both |
| Oil palm | Both |
| Potato | Both |
| Rice | Both |
| Rye | Both |
| Rapeseed | Both |
| Sorghum | Both |
| Soybean | Both |
| Sugarbeet | Both |
| Sugarcane | Both |
| Sunflower | Both |
| Sweet potato | Both |
| Wheat | Both |
| Groundnut | Nitrogen only |
| Fruits | Nitrogen only |
| Vegetables | Nitrogen only |
| Other | Nitrogen only |
Protect Seafloors is the long-term protection of the seafloor from degradation, which helps preserve existing sediment carbon stocks and avoid CO₂ emissions. Advantages of seafloor protection include the conservation of biodiversity and marine ecosystems, potentially low costs, and the ability for immediate implementation. Disadvantages include uncertainties in the effectiveness of legal protection at preventing degradation and in the amount of CO₂ emissions avoided, as well as the risk of displacement of degradation to non-protected areas and/or an increase in other types of degradation. Given these considerations, we conclude that Seafloor Protection is a “Worthwhile” climate solution.
Based on our analysis, seafloor protection could avoid some CO₂ emissions while preserving critical marine ecosystems from degradation. However, the effectiveness of protection and the magnitude of avoided CO₂ emissions associated with protection are understudied and currently unclear. All told, we consider this a “Worthwhile” climate solution.
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | No |
| Evidence | Are there data to evaluate it? | Limited |
| Effective | Does it consistently work? | No |
| Impact | Is it big enough to matter? | Yes |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | Yes |
Protect Seafloors aims to reduce human impacts that can degrade sediment carbon stocks and increase CO₂ emissions. Protection is conferred through legal mechanisms, such as Marine Protected Areas (MPAs), which are managed with the primary goal of conserving nature. The seafloor stores over 2,300 Gt of carbon (roughly 8,400 Gt CO₂‑eq) in the top one meter of sediment. This marine carbon can be stable and remain sequestered for millennia. However, degradation of the seafloor from a range of human activities can disturb bottom sediments, resuspending the carbon and increasing its microbial conversion into CO₂. Currently, degradation of the seafloor primarily results from fishing practices, such as trawling and dredging, which are estimated to occur across 1.3% of the global ocean. Additional sources of degradation include undersea mining, infrastructure development (for offshore wind farms, oil, and gas), and laying telecommunications cables. Estimates of seafloor degradation are highly uncertain due to data limitations and the unpredictable nature of how these activities may expand in the future.
More evidence is needed to confirm whether legal seafloor protection is effective at reducing degradation and the extent to which degradation results in increased CO₂ emissions. While ~8% of the seafloor is currently protected through MPAs, there is mixed evidence that legal protection reduces degradation and CO₂ emissions. For instance, in a review of 49 studies examining the impacts of bottom trawling and dredging on sediment organic carbon stocks, most (61%) showed no change, while nearly a third (29%) showed carbon loss. More recent work suggests that trawling intensity might drive these mixed results, with more heavily trawled areas showing clear reductions in sediment organic carbon. Additionally, the few existing global estimates of CO₂ emissions from trawling and dredging range from 0.03 to 0.58 Gt CO₂/yr, highlighting the need for further research. The effectiveness of MPAs at preventing seafloor degradation is also mixed. In strictly protected areas with enforcement of no-take policies that prevent bottom fishing, MPAs could help minimize degradation and retain seafloor carbon. However, implementation can be challenging, as over half of existing MPAs generally allow high-impact activities. For instance, trawling and dredging occur more frequently in MPAs than in non-protected areas in the territorial waters of Europe.
Advantages of seafloor protection include its potential low cost and its ability to conserve often understudied biodiversity and ecosystems. Human activities, such as trawling and dredging, impact marine organisms on the seafloor, and ecosystem recovery can take years to occur. In the case of undersea mining, ecosystems may never fully recover. Increases in CO₂ emissions along the seafloor from degradation can also enhance local acidification and reduce the ocean's buffering capacity, both of which can affect marine organisms and the carbon sequestration capacity of seawater. Protection can also increase fisheries yields in neighboring waters and reduce other negative impacts of seafloor disturbances. While costs are somewhat uncertain, MPA expenses have been estimated to be an order of magnitude less than the often unseen ecosystem service benefits gained with protection, suggesting MPA expansion could provide cost savings.
Disadvantages of seafloor protection include uncertainties surrounding the effectiveness of preventing degradation and avoiding CO₂ emissions, as well as the potential increased risk of disturbance to other ocean areas. The amount and fate of CO₂ generated due to the degradation of seafloor carbon is complex and understudied. It can take months or even centuries for CO₂ produced at depth to reach the sea surface and atmosphere. Current estimates of CO₂ emissions due to dredging and trawling are widely debated and highly variable due to differing methods and assumptions. Large amounts of organic carbon will inevitably re-settle after seafloor disturbances, with no impact on CO₂, but estimates of just how much remain uncertain. The risk of protection-induced leakage, where a reduction in disturbances, such as trawling and dredging in MPAs, leads to increased fishing effort in other ocean areas, is also potentially high.
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More than one-third of all food produced for human consumption is lost or wasted before it can be eaten. This means that the GHGs emitted during the production and distribution of that particular food – including emissions from agriculture-related deforestation and soil management, methane emissions from livestock and rice production, and nitrous oxide emissions from fertilizer management – are also wasted. This solution reduces emissions by lowering the amount of food and its associated emissions that are lost or wasted across the supply chain, from production through consumption.
The global food system, including land use, production, storage, and distribution, generates more than 25% of global GHG emissions (Poore and Nemecek, 2018). More than one-third of this food is lost or wasted before it can be eaten, with estimated associated emissions being recorded at 4.9 Gt CO₂‑eq/yr (our own calculation). FLW emissions arise from supply chain embodied emissions (i.e., the emissions generated from producing food and delivering to consumers). Reducing food loss and waste avoids the embodied emissions while simultaneously increasing food supply and reducing pressure to expand agricultural land use and intensity.
FLW occurs at each stage of the food supply chain (Figure 1). Food loss refers to the stages of production, handling, storage, and processing within the supply chain. Food waste occurs at the distribution, retail, and consumer stages of the supply chain.
Figure 1. GHG emissions occur at each stage of the food supply chain. Food loss occurs at the pre-consumer stages of the supply chain, whereas food waste occurs at the distribution, market, and consumption stages. Credit: Project Drawdown
Food loss can be reduced through improved post-harvest management practices, such as increasing the number and storage capacity of warehouses, optimizing processes and equipment, and improving packaging to increase shelf life. Retailers can reduce food waste by improving inventory management, forecasting demand, donating unsold food to food banks, and standardizing date labeling. Consumers can reduce food waste by educating themselves, making informed purchasing decisions, and effectively planning meals. The type of interventions to reduce FLW will depend on the type(s) of food product, the supply chain stage(s), and the location(s).
When FLW cannot be prevented, organic waste can be managed in ways that limit its GHG emissions. Waste management is not included in this solution but is addressed in other Drawdown Explorer solutions (see Deploy Methane Digesters, Improve Landfill Management, and Increase Centralized Composting).
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Erika Luna
Aishwarya Venkat, Ph.D.
Ruthie Burrows, Ph.D.
Emily Cassidy, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Eric Toensmeier
Paul C. West, Ph.D.
Aiyana Bodi
Hannah Henkin
Megan Matthews, Ph.D.
Heather McDiarmid, Ph.D.
Ted Otte
Christina Swanson, Ph.D.
Paul C. West, Ph.D.
Our analysis estimates that reducing FLW reduces emissions 2.82 t CO₂‑eq (100-yr basis) for every metric ton of food saved (Table 1). This estimate is based on selected country and global assessments from nongovernmental organizations (NGOs), public agencies, and development banks (ReFED, 2024; World Bank, 2020; WRAP, 2024). All studies included in this estimate reported a reduction in both volumes of FLW and GHG emissions. However, it is important to recognize that the range of embodied emissions varies widely across foods (Poore & Nemecek, 2018). For example, reducing meat waste can be more effective than reducing fruit waste because the embodied emissions are much higher.
Effectiveness is only reported on a 100-yr time frame here because our data sources did not include enough information to separate out the contribution of different GHGs and calculate the effectiveness on a 20-yr time frame.
Table 1. Effectiveness at reducing emissions.
Unit: t CO₂‑eq /t reduced FLW, 100-yr basis
| 25th percentile | 2.75 |
| Mean | 3.11 |
| Median (50th percentile) | 2.82 |
| 75th percentile | 3.30 |
The net cost of baseline FLW is US$932.56/t waste, based on values from the Food and Agriculture Organization of the United Nations (FAO, 2014) and Hegensholt et al. (2018). The median net cost of implementing strategies and practices that reduce FLW is US$385.5/t waste reduced, based on values from ReFED (2024) and Hanson and Mitchell (2017). These costs include, but are not limited to, improvements to inventory tracking, storage, and diversion to food banks. Therefore, the net cost of the solution compared to baseline is a total savings of US$547.0/t waste reduced.
Therefore, reducing emissions for FLW is cost-effective, saving US$194.0/t avoided CO₂‑eq on a 100-yr basis (Table 2).
Table 2. Net cost per unit climate impact.
Unit: US$/t CO₂‑eq , 2023
| Median (100-yr basis) | -194.0 |
Learning curve data were not yet available for this solution.
Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.
At Project Drawdown, we define the speed of action for each climate solution as emergency brake, gradual, or delayed.
Reduce Food Loss and Waste is an EMERGENCY BRAKE climate solution. It has the potential to deliver a more rapid impact than nominal and delayed solutions. Because emergency brake solutions can deliver their climate benefits quickly, they can help accelerate our efforts to address dangerous levels of climate change. For this reason, they are a high priority.
Reducing FLW through consumer behavior, supply chain efficiencies, or other means can lead to lower food prices, creating a rebound effect that leads to increased consumption and GHG emissions (Hegwood et al., 2023). This rebound effect could offset around 53–71% of the mitigation benefits (Hegwood et al., 2023). Population and economic growth also increase FLW. The question remains however, who should bear the cost of implementing FLW solutions. A combination of value chain investments by governments and waste taxes for consumers may be required for optimal FLW reduction (Gatto, 2023; Hegwood, 2023; The World Bank, 2020).
Strategies for managing post-consumer waste through composting and landfills are captured in other Project Drawdown solutions (see Improve Landfill Management, Increase Centralized Composting, and Deploy Methane Digesters).
Due to a lack of data we were not able to quantify current adoption for this solution.
Data on adoption trends were not available.
We assumed an adoption ceiling of 1.75 Gt of FLW reduction in 2023, which reflects a 100% reduction in FLW (Table 3). While reducing FLW by 100% is unrealistic because some losses and waste are inevitable (e.g., trimmings, fruit pits and peels) and some surplus food is needed to ensure a stable food supply (HLPE, 2014), we kept that simple assumption because there wasn’t sufficient information on the amount of inevitable waste, and it is consistent with other research used in this assessment.
Table 3. Adoption ceiling.
Unit: t reduced FLW/yr
| Median | 1,750,000,000 |
Studies consider that halving the reduction in FLW by 2050 is extremely ambitious and would require “breakthrough technologies,” whereas a 25% reduction is classified as highly ambitious, and a 10% reduction is more realistic based on coordinated efforts (Searchinger, 2019; Springmann et al., 2018). With our estimate of 1.75 Gt of FLW per year, a 25% reduction equals 0.48 Gt, while a 50% reduction would represent 0.95 Gt of reduced FLW.
It is important to acknowledge that, 10 years after the 50% reduction target was set in the Sustainable Development Goals (SDGs, Goal 12.3), the world has not made sufficient progress. The challenge has therefore become larger as the amounts of FLW keep increasing at a rate of 2.2%/yr (Gatto & Chepeliev, 2023; Hegnsholt, et al. 2018; Porter et al., 2016).
As a result of these outcomes, we have selected a 25% reduction in FLW as our Achievable – Low and 50% as our Achievable – High. Reductions in FLW are 437.5, 875.0, and 1,750 Mt FLW/year for Achievable – Low, Achievable – High, and Adoption Ceiling, respectively (Table 4).
Table 4. Adoption levels.
Unit: t reduced FLW/yr
| Current adoption (baseline) | Not determined |
| Achievable – low (25% of total FLW) | 437,500,000 |
| Achievable – high (50% of total FLW) | 875,000,000 |
| Adoption ceiling (100% of total FLW) | 1,750,000,000 |
An Achievable – Low (25% FLW reduction) could represent 1.23 Gt CO₂‑eq/yr (100-yr basis) of reduced emissions, whereas an Achievable – High (50% FLW reduction) could represent up to 2.47 Gt CO₂‑eq/yr. The adoption potential (100% FLW reduction) would result in 4.94 Gt CO₂‑eq/yr (Table 5). We only report emissions outcomes on a 100-yr basis here because most data sources did not separate the percentage of type of food wasted or disaggregate their associated emissions factors by GHG type. Estimated impacts would be higher on a 20-yr basis due to the higher GWP of methane associated with meat and rice production.
Table 5. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current adoption (1.5% of total FLW) | Not determined |
| Achievable – low (25% of total FLW) | 1.23 |
| Achievable – high (50% of total FLW) | 2.47 |
| Adoption ceiling (100% of total FLW) | 4.94 |
We also compiled studies that have modeled the climate impacts of different FLW reduction scenarios, from 10% to 75%. For an achievable 25% reduction, Scheringer (2019) estimated a climate impact of 1.6 Gt CO₂‑eq/yr. Studies that modeled the climate impact of a 50% reduction by 2050 estimated between 0.5 Gt CO₂‑eq/yr (excluding emissions from agricultural production and land use change; Roe at al., 2021) to 3.1–4.5 Gt CO₂‑eq/yr (including emissions from agricultural production and land use change; Roe at al., 2021; Searchinger et al., 2019).
Multiple studies stated that climate impacts from FLW reduction would be greater when combined with the implementation of dietary changes (see the Improve Diets solution; Almaraz et al., 2023; Babiker et al.; 2022; Roe et al., 2021; Springmann et al., 2018; Zhu et al., 2023).
Households and communities can strengthen adaptation to climate change by improving food storage, which helps reduce food loss (Ziervogel & Ericksen, 2010). Better food storage infrastructure improves food security from extreme weather events such as drought or floods which make it more difficult to grow food and can disrupt food distribution (Mbow et al., 2019).
FLW accounts for a loss of about US$1 trillion annually (World Bank, 2020). In the United States, a four-person household spends about US$2,913 on food that is wasted (Kenny, 2025). These household-level savings are particularly important for low-income families because they commonly spend a higher proportion of their income on food (Davidenko & Sweitzer, 2024). Reducing FLW can improve economic efficiency (Jaglo et al., 2021). In fact, a report by Champions 12.3 found efforts to reduce food waste produced positive returns on investments in cities, businesses, and households in the United Kingdom (Hanson & Mitchell, 2017). FLW in low- and middle-income countries mostly occurs during the pre-consumer stages, such as storage, processing, and transport (Kaza et al., 2018). Preventive measures to reduce these losses have been linked to improved incomes and profits (Rolker et al., 2022).
Reducing FLW increases the amount of available food, thereby improving food security without requiring increased production (Neff et al., 2015). The World Resources Institute estimated that halving the rate of FLW could reduce the projected global need for food approximately 20% by 2050 (Searchinger et al., 2019). In the United States, about 30–40% of food is wasted (U.S. Food and Drug Administration [U.S. FDA], 2019) with this uneaten food accounting for enough calories to feed more than 150 million people annually (Jaglo et al., 2021). These studies demonstrate that reducing FLW can simultaneously decrease the demand for food production while improving food security.
Policies that reduce food waste at the consumer level, such as those that improve food packaging and require clearer information on shelf life and date labels, can reduce the number of foodborne illnesses (Neff et al., 2015; U.S. FDA, 2019). Additionally, efforts to improve food storage and food handling can further reduce illnesses and improve working conditions for food-supply-chain workers (Neff et al., 2015). Reducing FLW can lower air pollution from food production, processing, and transportation and from disposal of wasted food (Nutrition Connect, 2023). Gatto and Chepeliev (2024) found that reducing FLW can improve air quality (primarily through reductions in carbon monoxide, ammonia, nitrogen oxides, and particulate matter), which lowers premature mortality from respiratory infections. These benefits were primarily observed in China, India, and Indonesia, where high FLW-embedded air pollution is prevalent across all stages of the food supply chain (Gatto & Chepeliev, 2024).
For a description of the land resources benefits, please refer to the “water resources” subsection below.
Reducing FLW can conserve resources and improve biodiversity (Cattaneo, Federighi, & Vaz, 2021). A reduction in FLW reflects improvements in resource efficiency of freshwater, synthetic fertilizers, and cropland used for agriculture (Kummu et al., 2012). Reducing the strain on freshwater resources is particularly relevant in water-scarce areas such as North Africa and West-Central Asia (Kummu et al., 2012). In the United States, halving the amount of FLW could reduce approximately 290,000 metric tons of nitrogen from fertilizers, thereby reducing runoff, improving water quality, and decreasing algal blooms (Jaglo et al., 2021).
Interventions to address FLW risk ignoring economic factors such as price transmission mechanisms and cascading effects, both upstream and downstream in the supply chain. The results of a FLW reduction policy or program depend greatly on the commodity, initial FLW rates, and market integration (Cattaneo, 2021; de Gorter, 2021).
On the consumer side, there is a risk of a rebound effect: Avoiding FLW can lower food prices, leading to increased consumption and net increase in GHG emissions (Hegwood et al., 2023). Available evidence is highly contextual and often difficult to scale, so relevant dynamics must be studied with care (Goossens, 2019).
The production site is a critical loss point, and farm incomes, scale of operations, and expected returns to investment affect loss reduction interventions (Anriquez, 2021; Fabi, 2021; Sheahan and Barrett, 2017).
Reducing FLW can lower new demand for high-emissions foods, like ruminant meat.
Reducing FLW can lower demand for new production of livestock and crops, reducing the use of fertilizers or manure and therefore associated emissions.
Reducing FLW can reduce the demand to expand agriculture, support land conservation and restoration, and benefit water quality.
Reducing food loss and waste can reduce the demand for wild-harvested macroalgae.
(mixed) Reducing FLW can increase demand for cold storage, more efficient appliances, and optimized transport, which could reinforce the adoption of solutions targeting these improvements. However, reducing FLW could compete with other solutions if loss reductions are achieved mainly from producing less food, which could lead to lower refrigeration demand.
Food waste is used as raw material for methane digestors and composting. Reducing FLW may reduce the impact of those solutions as a result of decreased feedstock availability.
t reduced FLW
CO₂ , CH₄ , N₂O
Some FLW reduction strategies have trade-offs for emission reductions (Cattaneo, 2021; de Gorter et al., 2021). For example, improved cold storage and packaging are important interventions for reducing food loss, yet they require additional electricity and refrigerants, which can increase GHG emissions (Babiker et al., 2022; FAO, 2019).
A large volume of scientific research exists regarding reducing emissions of FLW effectively. The IPCC Sixth Assessment Report (AR6) estimates the mitigation potential of FLW reduction (through multiple reduction strategies) to be 2.1 Gt CO₂‑eq/yr (with a range of 0.1–5.8 Gt CO₂‑eq/yr ) (Nabuurs et al., 2022). This accounts for savings along the whole value chain.
Following the 2011 FAO report – which estimated that around one-third (1.3 Gt) of food is lost and wasted worldwide per year – global coordination has prioritized the measurement of the FLW problem. This statistic has served as a baseline for multiple FLW reduction strategies. However, more recent studies suggest that the percentage of FLW may be closer to 40% (WWF, 2021). The median of the studies included in our analysis is 1.75 Gt/yr of FLW (FAO, 2024; Gatto & Chepeliev, 2024; Guo et al., 2020; Porter et al., 2016; UNEP, 2024; WWF, 2021; Zhu et al., 2023), with an annual increasing trend of 2.2%.
Only one study included in our analysis calculated food embodied emissions from all stages of the supply chain, while the rest focused on the primary production stages. Zhu et al. (2023) estimated 6.5 Gt CO₂‑eq/yr arising from the supply chain side, representing 35% of total food system emissions.
When referring to food types, meat and animal products were estimated to emit 3.5 Gt CO₂‑eq/yr compared to 0.12 Gt CO₂‑eq/yr from fruits and vegetables (Zhu et al., 2023). Although meat is emissions-intensive, fruits and vegetables are the most wasted types of food by volume, making up 37% of total FLW by mass (Chen et al., 2020). The consumer stage is associated with the highest share of global emissions at 36% of total supply-embodied emissions from FLW, compared to 10.9% and 11.5% at the retail and wholesale levels, respectively (Zhu et al., 2023).
While efforts to measure the FLW problem are invaluable, critical gaps exist regarding evidence of the effectiveness of different reduction strategies across supply chain stages ( Cattaneo, 2021; Goossens, 2019; Karl et al., 2025). To facilitate impact assessments and cost-effectiveness, standardized metrics are required to report actual quantities of FLW reduced as well as resulting GHG emissions savings (Food Loss and Waste Protocol, 2024).
The results presented in this document summarize findings across 22 studies. These studies are made up of eight academic reviews and original studies, eight reports from NGOs, and six reports from public and multilateral organizations. This reflects current evidence from five countries, primarily the United States and the United Kingdom. We recognize this limited geographic scope creates bias, and hope this work inspires research for meta-analyses and data sharing on this topic in underrepresented regions and stages of the supply chain.
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