Restore Salt Marsh Ecosystems involves actively reestablishing salt marshes in areas where they were previously lost to conversion or other disturbance, allowing vegetation to regrow and carbon to accumulate in biomass and sediments. Advantages include salt marshes’ ability to durably store substantial quantities of carbon over long time periods and their numerous co-benefits for the environment and humans. Disadvantages include variable but potentially low effectiveness due to site-to-site differences in carbon removal rates and potential emissions of other GHGs, such as methane and nitrous oxide, as well as costs that might exceed US$500/t CO₂‑eq in some areas. Salt marsh restoration is not expected to have a globally meaningful climate impact (>0.1 Gt CO₂‑eq/yr ), primarily because the adoption ceiling is constrained by the limited area available for restoration, but there are no major environmental risks associated with the solution. Therefore, Restore Salt Marsh Ecosystems is “Worthwhile.”
Based on our analysis, restoring salt marsh ecosystems is a “Worthwhile” carbon removal technique that is ready for large-scale deployment. While the capacity for adoption is limited, limiting climate impact, this solution has no major risks and provides widespread added benefits for people and the environment.
| 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? | Yes |
Restore Salt Marsh Ecosystems removes carbon from the air by reestablishing salt marshes in areas where they were previously drained, filled, or otherwise degraded and lost. As plants take up CO₂ through photosynthesis and vegetation traps sediments, some of this carbon is stored long term in waterlogged soils with slow decomposition rates. Restoration typically reconnects land to tidal exchange and rebuilds marsh elevation and vegetation, which promotes plant growth and sediment accumulation. Active restoration can include breaching levees or removing barriers to restore tidal flow, regrading or adding sediment to raise elevations, planting native marsh vegetation, and controlling invasive species. In many cases, restoration can also reduce GHG emissions by replacing land uses, such as drained agriculture, that emit CO₂.
The fundamental idea of restoring salt marsh ecosystems is scientifically sound, and, on average globally, restored salt marshes have been shown to remove carbon over long timescales through vegetation recovery and sustained carbon burial in waterlogged soils, even after accounting for methane and nitrous oxide emissions. This solution has been in practice worldwide for many decades, and global assessments suggest it could expand to roughly 2 million hectares because ~67% of salt marshes have been destroyed since the early 1900s. Restoration success rates are high relative to those of many other marine habitats. However, its potential adoption ceiling is still low relative to other nature-based solutions (e.g., Restore Forests) because restoration is limited to suitable coastal areas, which are constrained by coastal development and other human stressors. As a result, its climate impact is likely well below 0.1 Gt CO₂‑eq /year.
Restoration of salt marsh ecosystems is a well-established, scalable practice with many benefits for the environment. Restored salt marshes can reduce shoreline erosion and costal flooding, improve water quality by retaining nutrients and sediments, and provide habitat for fish and birds. While global impact is limited, this intervention can be an important multi-benefit tool for building climate resilience and removing carbon in some countries and coastal regions. Restoration is already widely implemented. In some restorations, such as those that reestablish tidal exchange in previously impounded ecosystems, increases in salinity can reduce methane and nitrous oxide production relative to pre-restoration conditions.
The climate impact of salt marsh restoration is constrained by its limited adoption ceiling, variable but potentially high costs, vulnerability to future loss, and potentially low effectiveness. Adoption is limited by where marshes can actually be restored, such as on low-elevation coastal lands that are not heavily developed, and where they can be maintained into the future with climate change stressors, such as sea-level rise. If salt marshes are not restored with consideration of projected sea level rise, loss or conversion to mud flats or open water habitats in the future is possible, which would result in the loss of carbon benefits. Restored salt marshes can also emit potent GHGs such as methane and nitrous oxide as low oxygen conditions and ecosystem function are reestablished, which can offset some of the climate benefits of restoration. As a result, costs vary widely by site, and can exceed US$500/t CO₂‑eq (~US$1,000–7,000/ha), depending on site-specific effectiveness rates. Additionally, few data are available for understanding long-term, multi-decadal changes in carbon accumulation rates in restored sites, and some regions remain underrepresented globally.
Burden, A., Garbutt, A., & Evans, C. D. (2019). Effect of restoration on saltmarsh carbon accumulation in Eastern England. Biology Letters, 15(1). Link to source: https://doi.org/10.1098/rsbl.2018.0773
Convention on Wetlands. (2025). Global Wetland Outlook 2025: Valuing, conserving, restoring and financing wetlands (Scientific and Technical Review Panel report). Secretariat of the Convention on Wetlands. Link to source: https://www.ramsar.org/launch-global-wetland-outlook-2025
Danovaro, R., Aronson, J., Bianchelli, S., Boström, C., Chen, W., Cimino, R., Corinaldesi, C., Cortina-Segarra, J., D’Ambrosio, P., Gambi, C. and Garrabou, J. (2025). Assessing the success of marine ecosystem restoration using meta-analysis. Nature Communications, 16(1), 3062. Link to source: https://doi.org/10.1038/s41467-025-57254-2
Holmquist, J. R., Eagle, M., Molinari, R. L., Nick, S. K., Stachowicz, L. C., & Kroeger, K. D. (2023). Mapping methane reduction potential of tidal wetland restoration in the United States. Communications Earth & Environment, 4(1), 353. Link to source: https://doi.org/10.1038/s43247-023-00988-y
Mason, V. G., Burden, A., Epstein, G., Jupe, L. L., Wood, K. A., & Skov, M. W. (2024). Navigating research challenges to estimate blue carbon benefits from saltmarsh restoration. Global Change Biology, 30(10), 1–3. Link to source: https://doi.org/10.1111/gcb.17526
Pétillon, J., McKinley, E., Alexander, M., Adams, J.B., Angelini, C., Balke, T., Griffin, J.N., Bouma, T., Hacker, S., He, Q. and Hensel, M.J. (2023). Top ten priorities for global saltmarsh restoration, conservation and ecosystem service research. Science of the Total Environment, 898, 165544. Link to source: https://doi.org/10.1016/j.scitotenv.2023.165544
Reilly, A. V., Merrill, N. H., Mulvaney, K. K., Colarusso, P., & Burman, E. (2024). Fantastic wetlands and why to monitor them: Demonstrating the social and financial benefit potential of methane abatement through salt marsh restoration. PLOS Climate, 3(7), e0000317. Link to source: https://doi.org/10.1371/journal.pclm.0000317
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Christina Richardson, Ph.D.
Christina Swanson, Ph.D.
Paul West, Ph.D.
Grassland and savanna restoration removes CO₂ from the atmosphere through photosynthesis as the ecosystem regrows, storing carbon in soils and vegetation. Grassland and savanna restoration faces relatively low barriers to implementation, provides substantial benefits for biodiversity, and may be deployable on large land areas. However, we currently lack sufficient information to assess whether the climate impact of grassland and savanna restoration falls above or below our threshold of globally meaningful carbon removal (>0.1 Gt CO₂‑eq/yr ), given limited data on the magnitude of its effectiveness and adoption potential. Therefore, we conclude that Restoring Grasslands and Savannas is “Worthwhile,” and will reassess the climate impact of this solution as further research is done.
Based on our analysis, grassland and savanna restoration is a promising climate solution, but there is insufficient evidence to ascertain how much carbon it could remove at the global scale. Restoring Grasslands and Savannas is therefore “Worthwhile.”
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | Yes |
| Evidence | Are there data to evaluate it? | Limited |
| Effective | Does it consistently work? | Yes |
| Impact | Is it big enough to matter? | ? |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | Yes |
Restoring grasslands and savannas removes carbon from the atmosphere via photosynthesis and stores it in soils and vegetation. Grassland and savanna restoration includes a spectrum of practices, such as returning ecologically appropriate grazing and fire regimes, reseeding with native species, and controlling invasive and woody plants.
Because grasslands and savannas are diverse, widespread ecosystems spanning a large climatic range, appropriate restoration and management strategies vary depending on the type of degradation and the natural history of the area. For this solution, we considered only degraded areas that were historically grassland and savanna and are not currently used as croplands or grazing lands. Other Project Drawdown solutions, including Deploy Silvopasture, Reduce Grazing Intensity, and Deploy Alternative Grazing, address increasing carbon removal in grasslands managed for grazing. Protect Grasslands & Savannas addresses protecting existing carbon stocks by reducing ongoing ecosystem degradation.
Grassland and savanna restoration will generally remove carbon when implemented with ecologically appropriate strategies on grasslands and savannas with depleted carbon stocks. Restoration efforts covering millions of hectares have already been initiated in some regions, though data tracking restoration progress are sparse. Although grassland and savanna restoration will remove carbon in principle, very little information is available to quantitatively assess the amount of carbon removed by restoration of degraded, ungrazed grasslands and savannas. One study in the United States found that planting diverse species on degraded grasslands increased total carbon uptake by up to 178% of that associated with natural succession over 22 years; however, the generalizability of this finding is unclear. Other studies that focused on activities outside of the scope of this solution, such as changing grazing practices, restoring croplands to grasslands, planting legumes, and adding fertilizers, found an average increase in carbon uptake rates of ~1.7 t CO₂‑eq /ha/yr with a range of 0.1–3.2 t CO₂‑eq /ha/yr. These estimates may serve as a rough benchmark of the maximum per-hectare carbon removal that grassland restoration could achieve.
Grassland and savanna restoration may be an effective, low-risk strategy for sequestering carbon on hundreds of millions of hectares while also providing substantial benefits for biodiversity and other ecosystem services. Grasslands and savannas are the largest ecosystem on Earth, covering more than 2.8 billion hectares (see Protect Grasslands & Savannas) from the tropics to the tundra. Some studies estimate that roughly half of grasslands are degraded, suggesting that the opportunity for grassland and savanna restoration is in the range of hundreds of millions of hectares even after excluding grazed areas. Grasslands and savannas also play a critical role in the global carbon cycle, containing roughly 30% of the world’s soil carbon stock. Therefore, even small relative increases in grassland and savanna carbon stocks could translate into large absolute climate benefits. Because most grassland and savanna carbon is stored in below-ground biomass and soils, these carbon stocks can be more resilient to disturbance, such as fire, than carbon stored in above-ground biomass.
In addition to the potential climate benefits, healthy grasslands and savannas support diverse biological communities, regulate hydrology, improve water quality, reduce erosion, and provide pollination, cultural, and provisioning services to local communities.
While grassland and savanna restoration can consistently remove carbon, large uncertainties remain in the magnitude of the effectiveness and adoption potential of this solution.
First, most research on the carbon removal potential of grasslands and savannas focuses on improving grazing management or conversion of croplands back to grasslands, which are outside the scope of this solution. Effectiveness at removing carbon also depends on post-restoration management because many grasslands and savannas depend on establishment of ongoing, ecologically appropriate fire and grazing regimes. Additionally, climate change is reducing grassland and savanna productivity in many regions and may prohibit successful restoration in some places.
Second, the area of degraded, ungrazed grasslands and savannas that are restorable remains largely unknown. The definition of land degradation varies across studies, and maps of degraded lands are inconsistent with one another. While maps of grazing extent have improved, they are still uncertain. Thus, it is difficult to assess the adoption potential of this solution. Without sufficient data on effectiveness and adoption potential, we are ultimately unable to assess whether the climate impact of this solution falls above or below our threshold of 0.1 Gt CO₂‑eq/yr. We encourage additional research to alleviate data limitations related to grassland and savanna restoration.
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Avery Driscoll, Ph.D.
Christina Swanson, Ph.D.
Paul C. West, Ph.D.
Forest restoration is the process of returning previously forested land to a forested state. As forests regrow, they remove carbon from the atmosphere and sequester it in biomass.
We define forest restoration as planting new trees or allowing trees to naturally regrow on previously forested land that has been cleared. Through photosynthesis, forests take carbon from the atmosphere and store it in biomass. On net, forests currently take up an estimated 11.4–14.7 Gt CO₂‑eq/yr (Friedlingstein et al., 2023; Gibbs et al., 2025; Pan et al., 2024), equal to approximately 19–25% of total global anthropogenic GHG emissions (Dhakal et al., 2022). Restoring forests increases the size of the forest carbon sink, sequestering additional CO₂.
As commonly defined, restoration ranges from improving management of existing ecosystems, to re-establishing cleared ecosystems, to maintaining the health of functional ecosystems. Forest restoration includes activities such as exclusion of non-native grazing animals from a regenerating site, weed management, assisted seed dispersal, controlled burning, stand thinning, direct seeding, soil amendment, tree planting, and modification of topography or hydrology and other activities (Chazdon et al., 2024; Gann et al., 2022; Kübler & Günter 2024). While acknowledging that all restoration occurs along a spectrum of intervention intensity, we report effectiveness, cost, and adoption data for “low intensity” and “high intensity” restoration separately, with “low intensity” restoration including all interventions up to, but not including, tree planting, and “high intensity” restoration referring to direct seeding or seedling planting. To account for variability in carbon sequestration rates and area available for forest restoration, this analysis also evaluates forest restoration in boreal, temperate, subtropical, and tropical regions separately where possible.
Our definition of forest restoration is more limited than that used by many other sources. First, we only include reforestation of previously forested land with an element of direct human intervention, and therefore exclude entirely passive tree regrowth on abandoned land (i.e., unassisted natural regeneration) and afforestation of native grasslands and savannas. We also exclude areas currently used for crop production. To avoid double counting, we also do not include activities covered in other Project Drawdown solutions, including increasing carbon stocks in existing forests and establishing timber plantations, agroforestry, or silvopasture (see Improve Forest Management, Deploy Biomass Crops on Degraded Land, Deploy Agroforestry, and Deploy Silvopasture, respectively). Restoration of mangroves and forests on peat soils is also excluded, as this is covered in the Restore Coastal Wetlands and Restore Peatlands solutions. Because the scope of this solution is narrower than that of many other studies, the estimated impacts are correspondingly lower as well.
Intact and regenerating forests take up carbon, but human clearing of forests for logging, agriculture, and other activities emits carbon. Humans clear an estimated 15.5 Mha of forests annually, emitting ~7.4 Gt CO₂‑eq/yr (2001–2024; Harris et al., 2021; Gibbs et al., 2025; Sims et al., 2025). Protecting existing forests reduces emissions from deforestation (see Protect Forests) and is an essential complement to forest restoration.
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Zhang, Q., Barnes, M., Benson, M., Burakowski, E., Oishi, A. C., Ouimette, A., Sanders-DeMott, R., Stoy, P. C., Wenzel, M., Xiong, L., Yi, K., & Novick, K. A. (2020). Reforestation and surface cooling in temperate zones: Mechanisms and implications. Global Change Biology, 26(6), 3384–3401. Link to source: https://doi.org/10.1111/gcb.15069
Avery Driscoll, Ph.D.
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Daniel Jasper
Alex Sweeney
James Gerber, Ph.D.
Megan Matthews, Ph.D.
Paul C. West, Ph.D.
We estimated that forest restoration can sequester 5.86–18.19 t CO₂‑eq /ha/yr (Table 1), depending on the climate zone and type of intervention, as growing trees take up carbon through photosynthesis and store it in above- and below-ground biomass. Sequestration rates are highly variable globally; much of this variability is driven by climate, soil properties, forest type, and the type of restoration.
For this solution, we used modeled carbon sequestration rates from natural regeneration to represent low-intensity restoration (Robinson et al., 2025) and modeled carbon sequestration rates from plantation forests to represent high-intensity carbon restoration, which we define as initiatives that include tree planting (Bukoski et al., 2022; Busch et al., 2024). We calculated carbon sequestration rates at the climate zone level (boreal, temperate, subtropical, and tropical) across the potential extent for each reforestation type.
Generally, high-intensity restoration has higher sequestration rates (median values 12.02–18.19 t CO₂‑eq /ha/yr) than low-intensity restoration (median values 5.86–17.06 t CO₂‑eq /ha/yr). Median effectiveness is also higher in tropical areas, where forest growth often continues year-round, than it is in other climate zones. These estimates reflect average sequestration rates over the first 30 years of forest growth. Carbon sequestration rates are also influenced by non-climatic factors. For example, higher tree species diversity is often associated with higher forest carbon storage and uptake (Bialic-Murphy et al., 2024; Poorter et al., 2015; van der Sande et al., 2017).
Table 1. Effectiveness of forest restoration at sequestering carbon.
Unit: t CO₂‑eq /ha/yr, 100-yr basis
| Boreal | 5.86 |
| Temperate | 11.49 |
| Subtropical | 11.53 |
| Tropical | 17.06 |
Unit: t CO₂‑eq /ha/yr, 100-yr basis
| Boreal | 14.57 |
| Temperate | 12.74 |
| Subtropical | 12.02 |
| Tropical | 18.19 |
We estimated the median cost of low-intensity forest restoration at US$23/t CO₂‑eq (2023 US$) and the median cost of high-intensity forest restoration at US$83/t CO₂‑eq (Table 2). The value given in the dashboard above is the average of the low- and high-intensity cost estimates (US$53/t CO₂‑eq).
On a per-hectare basis, the estimated cost of low-intensity restoration ranges from US$213/ha (25th percentile) to US$739/ha (75th percentile), with a median cost of US$304/ha. The estimated cost of high-intensity restoration ranges from US$811/ha (25th percentile) to US$1,914/ha (75th percentile), with a median of US$1,348/ha. We derived these estimates from compilations of global restoration project cost data by Verhoeven et al. (2024) and Busch et al. (2024), supplemented with estimates from five additional publications, representing a total of 50 unique projects.
Estimates of restoration costs remain very uncertain, as data are scarce, costs and revenues are highly variable across geographies and projects, and costs are nonlinear, tending to increase under higher adoption scenarios (Austin et al., 2020; Schimetka et al., 2024). Moreover, the success of a project at establishing new forests drives the cost per metric ton of CO₂‑eq , but such success rates are rarely reported alongside costs. Because of data limitations, we did not separate cost estimates into climate zones.
Our estimates do not account for any new revenues associated with forest restoration, such as carbon credits or provisioning of timber and non-timber forest products (Adams et al. 2016; Ager et al., 2017; Busch et al., 2024). They also do not account for the economic value of ecosystem services, such as increased biodiversity, improved water quality, local cooling, and reduced soil erosion, which have been estimated to outweigh the costs of forest restoration (De Groot et al., 2013).
Table 2. Cost per unit of climate impact.
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| Median | 23 |
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| Median | 83 |
We define a learning curve as falling costs with increased adoption. Reforestation has been practiced for many decades, and there is no evidence of a decrease in costs associated with increasing adoption. Therefore, there is no learning curve 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.
Restore Forests is a DELAYED climate solution. It works more slowly than gradual or emergency brake solutions. Delayed solutions can be robust climate solutions, but it’s important to recognize that they may not realize their full potential for some time.
Barriers to effective forest restoration include challenges around governance, financing, technical capacity (including seed and seedling supply), labor availability, and site-specific knowledge for initial restoration and long-term management (Brumberg et al., 2024; Chazdon et al., 2016; Chazdon et al., 2021; Fargione et al., 2021; Kroeger et al., 2025). Additional research and monitoring are needed to identify locally relevant restoration strategies, reduce barriers, and evaluate the success of restoration projects (Crouzeilles et al., 2019).
Forest restoration also faces challenges around permanence and additionality. Carbon stored in vegetation and soils through forest restoration can be lost to climatic and environmental stressors like wildfire, drought, heat waves, pests, or disease. Young, regenerating forests can be particularly susceptible to these types of stressors. Restored forests are also at risk of clearing (e.g., Piffer et al., 2022), so forest restoration must be coupled with long-term, effective protections against clearing. Additionality refers to the degree to which carbon uptake associated with forest restoration would have occurred in the absence of a project, policy, or incentive. Evaluating additionality is challenging in the context of natural forest regeneration, some of which simply arises from land abandonment without any intervention.
Data on current adoption of forest restoration are very limited. While there are extensive compilations of restoration pledges, estimates of the actual area being restored are noncentralized, typically rely on self-reporting without validation, do not have global coverage, use inconsistent definitions, often include establishment of plantations and agroforestry, and rarely separate estimates by ecosystem. Satellite-based data on tree cover gain are occasionally used as a proxy for restoration, but these do not differentiate among restoration, establishment of timber plantations, regeneration in the absence of human intervention, and plantation regrowth after timber harvest (Reytar et al., 2024). Moreover, they can fail to capture actual restoration areas (Begliomini & Brancalion, 2024).
Due to these limitations, we do not provide an estimate of the global area currently under forest restoration. However, we did compile current restoration estimates from three databases: The Mongabay Reforestation Catalog, The Restoration Initiative, and The Restoration Barometer. These databases are subject to the limitations discussed above. Assuming that there is no overlap in projects reported across these databases, including projects with an agroforestry component, and including projects across all ecosystems, we found 40.6 Mha currently being restored. Under more conservative assumptions, including removing projects with an agroforestry component, removing projects from countries that are reported across multiple databases, and discounting estimates to account for restoration in other ecosystems, we estimated that 9.2 Mha are currently being restored. These estimates provide context, but should not be interpreted as representative of the global area under forest restoration.
Despite extensive data on restoration pledges, comprehensive data on the actual implementation of restoration efforts are very limited and not often temporally resolved. The available data are insufficient to calculate an adoption trend for this solution.
We estimated that there are 96.8 Mha available for forest restoration, with 19.4 Mha in boreal regions, 19.0 Mha in temperate regions, 3.5 Mha in the subtropics, and 54.8 Mha in the tropics (Table 3a–e). In this solution, we only included cleared areas that were previously forests in the calculation of the adoption ceiling. To calculate the adoption ceiling, we started with a recent, conservative map of potential forest restoration areas (Fesenmeyer et al., 2025), which we masked to exclude areas classified as other ecosystems in other solutions (peatlands, grasslands and savannahs, and coastal wetlands). We then used a map of the cost-effectiveness of natural regeneration versus plantation establishment (Busch et al., 2024) to remove areas more suitable for plantation establishment from this solution, and assigned them instead to the Deploy Biomass Crops on Degraded Land solution.
Estimates of the area available for forest restoration vary widely due to differing definitions, ranging from 195 Mha (Fesenmeyer et al., 2025) to 900 Mha (Bastin et al., 2019), for example. Using base maps of forest restoration potential from Griscom et al. (2017) and Walker et al. (2022) gave an estimated global adoption ceiling of 426–434 Mha, after applying the same data processing approach to exclude other ecosystems and plantations.
Because of the constrained scope of this solution, we find a smaller adoption ceiling relative to other studies, which often include plantation establishment, agroforestry, densification of existing forests, afforestation on grasslands, restoration of forests on peat soils, reforestation of croplands, and other activities sometimes classified as forest restoration. We leveraged the map from Fesenmeyer et al. (2025) for the estimates reported in Table 3 because its scope aligns most closely with our relatively narrow definition of forest restoration, is one of the most recent studies, includes a review of 89 other forest restoration maps, and incorporates safeguards against conflicts between restoration and biodiversity loss, water scarcity, albedo effects, and land use. However, we note that this estimate is lower than other published estimates of potential forest restoration area and that differences across studies are driven by subjective judgments on land suitability for restoration.
Table 3. Adoption ceiling.
Unit: ha available for restoration
| Estimate | 19,400,000 |
Unit: ha available for restoration
| Estimate | 19,000,000 |
Unit: ha available for restoration
| Estimate | 3,500,000 |
Unit: ha available for restoration
| Estimate | 54,800,000 |
Unit: ha available for restoration
| Estimate | 96,800,000 |
We assigned an arbitrary achievable range of 50–75% of the adoption ceiling, equal to 48.4–72.6 Mha of forest restoration (Table 4a–e). Much of the adoption potential is located in the tropics, which we estimated to contain 27.4 Mha under the Achievable – Low Scenario and 41.1 Mha under the Achievable – High Scenario. We estimated similar achievable ranges of forest restoration area in boreal and temperate regions (9.7–14.6 Mha and 9.5–14.3 Mha, respectively), and an additional 1.7–2.6 Mha in subtropical regions.
Additional research is needed to determine more realistic estimates of the achievable adoption range, particularly differentiated across different restoration activities. National commitments to restoration, as with studies on the potential restoration area, include many activities that are beyond the scope of this solution, such as plantation establishment, agroforestry, and densification. Because of the inconsistency in definitions, we were unable to rely on restoration commitments to quantify the adoption achievable range. For context, the Global Restoration Commitments database (Mariappan & Zumbado, 2024) reports that, under the Rio Conventions, countries have committed to increasing forestland by 122 Mha, with an additional 154 Mha of commitments to restoring or improving forestland. Similarly, 210.1 Mha of land have been pledged for restoration across all ecosystems under the Bonn Challenge (Mariappan & Zumbado, 2024).
Table 4. Range of achievable adoption levels.
Unit: ha
| Current adoption | NA |
| Achievable – low | 9,700,000 |
| Achievable – high | 14,600,000 |
| Adoption ceiling | 19,400,000 |
Unit: ha
| Current adoption | NA |
| Achievable – low | 9,500,000 |
| Achievable – high | 14,300,000 |
| Adoption ceiling | 19,000,000 |
Unit: ha
| Current adoption | NA |
| Achievable – low | 1,700,000 |
| Achievable – high | 2,600,000 |
| Adoption ceiling | 3,500,000 |
Unit: ha
| Current adoption | NA |
| Achievable – low | 27,400,000 |
| Achievable – high | 41,100,000 |
| Adoption ceiling | 54,800,000 |
Unit: ha
| Current adoption | NA |
| Achievable – low | 48,400,000 |
| Achievable – high | 72,600,000 |
| Adoption ceiling | 96,800,000 |
We estimated that forest restoration could sequester 0.718 Gt CO₂‑eq/yr at the low-achievable adoption scenario, 1.077 Gt CO₂‑eq/yr at the high-achievable adoption scenario, and 1.437 Gt CO₂‑eq/yr at the adoption ceiling (Table 5a–e). Nearly 70% of the total climate impacts under these scenarios occur in tropical regions, where much of the current investment in restoration is focused.
Our climate impact estimates are lower than existing literature estimates due to our more constrained definition of this solution. Existing estimates also vary widely. For example, Cook-Patton et al. (2020) estimated that fully implemented national forest restoration commitments as of 2020 would take up 5.9 Gt CO₂‑eq/yr, while the Intergovernmental Panel on Climate Change (IPCC) reported an economically feasible mitigation potential of 1.6 Gt CO₂‑eq/yr (Nabuurs et al., 2022), and Griscom et al. (2017) reported a technical mitigation potential of 10.1 Gt CO₂‑eq/yr. Recently, Wang et al. (2025) estimated an upper-end mitigation potential of 5.85 Gt CO₂‑eq/yr (including afforestation and plantation establishment), with current commitments across all of these activities projected to take up 1.8 Gt CO₂‑eq/yr. Discrepancies between estimates are driven by the area considered suitable for restoration, types of restoration activities considered and their associated carbon uptake rates, and inclusion of cost constraints. Each of these individual estimates is also associated with substantial uncertainty, and further work is needed to standardize definitions of forest restoration and constrain the range of impact estimates.
Table 5. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-year basis
| Current adoption | NA |
| Achievable – low | 0.099 |
| Achievable – high | 0.149 |
| Adoption ceiling | 0.198 |
Unit: Gt CO₂‑eq/yr, 100-year basis
| Current adoption | NA |
| Achievable – low | 0.115 |
| Achievable – high | 0.173 |
| Adoption ceiling | 0.230 |
Unit: Gt CO₂‑eq/yr, 100-year basis
| Current adoption | NA |
| Achievable – low | 0.020 |
| Achievable – high | 0.031 |
| Adoption ceiling | 0.041 |
Unit: Gt CO₂‑eq/yr, 100-year basis
| Current adoption | NA |
| Achievable – low | 0.483 |
| Achievable – high | 0.725 |
| Adoption ceiling | 0.966 |
Unit: Gt CO₂‑eq/yr, 100-year basis
| Current adoption | NA |
| Achievable – low | 0.718 |
| Achievable – high | 1.077 |
| Adoption ceiling | 1.437 |
Forests help regulate local climate by reducing temperature extremes (Lawrence et al., 2022; Walton et al., 2016). Zhang et al. (2020) found the land surfaces of restored forests were 1–2 °C cooler than grasslands.
Forest restoration can improve biodiversity and health of the ecosystem, leading to more ecological resilience (DeGroot et al., 2013; Hua et al., 2022). Restored forests can intercept rainfall and attenuate flood risk during extreme rainfall events (Kabeja et al., 2020; Gardon et al., 2020). In some climates, certain reforestation methods could increase ecosystem resilience to wildfires (North et al., 2019).
For a description of the flood benefits, please refer to the “Extreme Weather Events” subsection.
Forest restoration may increase or decrease the ecosystem’s resilience to drought, depending on changes in factors such as evapotranspiration, precipitation, and water storage in vegetation (Andres et al., 2022; Sankey et al., 2020; Teo et al., 2022). For example, Teo et al. (2022) found that reforestation of degraded lands reduced the probability of experiencing extremely dry conditions in water-insecure regions of East Asia.
Forest restoration creates both temporary and permanent job opportunities, especially in rural areas (DeGroot et al., 2013). A study in Brazil found that restoration can generate about 0.42 jobs per hectare of forest undergoing restoration (Brancalion et al., 2022). Restoration of forests may also improve livelihoods and income opportunities based on the ecosystem services the forest provides. While these benefits vary substantially with household and community characteristics, in general, they include income diversification and the availability of food and fiber from forests (Adams et al., 2016). For example, in Burkina Faso, smallholders who restored lands through assisted regeneration diversified their income by harvesting resources such as fodder for livestock and small wildlife (Kumar et al., 2015).
Forests provide income and livelihoods for subsistence households and individuals (de Souza et al., 2016; Herrera et al., 2017; Naidoo et al., 2019). Forest restoration may improve food security for some households by improving incomes and livelihoods.
Reforestation may promote the health of nearby communities. Herrera et al. (2017) found that in rural areas of low- and middle-income countries, household members living downstream of higher tree cover had a lower probability of diarrheal disease. Biodiverse forests are linked to a reduced risk of animal-to-human infections because zoonotic hosts tend to be less abundant in less disturbed ecosystems (Keesing & Ostfeld, 2021; Reddington et al., 2015).
Indigenous peoples have a long history of caring for and shaping landscapes that are rich with biodiversity (Fletcher et al., 2021), and restoring the health and function of forests is essential for protecting indigenous cultural values and practices. Indigenous communities provide vital ecological functions for preserving landscape health, such as seed dispersal and predation (Bliege Bird & Nimmo, 2018). Indigenous peoples also have spiritual and cultural ties to their lands (Garnett et al., 2018). Restoration must be implemented using an equity-centered approach that reduces power imbalances between stakeholders, ensures people are not displaced, and involves local actors (Löfqvist et al., 2023).
Forests are home to a wide range of species and habitats and are essential for safeguarding biodiversity. Reforestation of native forests increases the biodiversity of an ecosystem relative to its previous cleared state (Brancalion et al., 2025; Hua et al., 2022). While many factors, such as the restoration method, time since restoration, and biophysical conditions, can impact restoration, studies of reforestation report increases in biodiversity and more species abundance after restoration, though the biodiversity typically remains below that of intact forests (Crouzeilles et al., 2016; Hua et al., 2022).
The impacts of reforestation on water quality vary based on factors such as geography and time since undergoing restoration (Dib et al., 2023). In general, forests act as natural water filters, maintaining and improving water quality (Dib et al., 2023; Melo et al., 2021). Restoration of forests is associated with improved water quality in streams compared with their previously degraded state (dos Reis Oliveira et al., 2025).
Forest restoration initiatives that are not responsive to local socioeconomic conditions risk displacing community land access and compromising local livelihoods. Effective forest restoration activities can be highly diverse, but must be targeted towards local environmental, sociopolitical, and economic conditions (Stanturf et al., 2019).
If forest restoration encroaches on agricultural lands, it can trigger clearing of forests elsewhere to replace lost agricultural production.
Planting trees in areas where they do not naturally occur, such as in grasslands and savannas, can alter hydrologic cycles and harm biodiversity (Veldman et al., 2015a; Veldman et al., 2015b). The estimates of potential forest restoration area that we use in this analysis are constrained to minimize these risks by including only land that was once forested and not allowing for forest restoration on croplands or in urban areas.
Forest restoration can improve the health and function of adjacent ecosystems that are being protected or restored.
These solutions are all suitable to implement on degraded land, and thus are in competition for the available degraded land.
ha under restoration
CO₂
ha under restoration
CO₂
ha under restoration
CO₂
ha under restoration
CO₂
Forest restoration can divert resources from other climate solutions, including protecting intact forests. Humans clear approximately 0.4% of forests annually (Curtis et al., 2018; Hansen et al., 2013; Sims et al., 2025), and halting further deforestation is an urgent priority with huge benefits for the climate, biodiversity, and other ecosystem services (see Protect Forests). While restoration provides carbon sequestration over a period of decades, preventing deforestation reduces emissions immediately and is typically more cost-effective. Restoration should therefore complement, rather than compete with, efforts to reduce deforestation.
Forest restoration can also decrease the albedo, or reflectivity, of Earth’s surface. This can increase temperatures as more of the sun’s energy is absorbed and reradiated as thermal energy. Albedo effects are most pronounced in boreal and dryland regions, where they reduce the net climate benefits of forest restoration (Hasler et al., 2024).
Consensus of effectiveness in enhancing carbon removal: High
Many scientific studies have evaluated the potential for forest restoration, consistently reporting that forest restoration has potential to provide substantial carbon removal. The effectiveness of forest restoration in terms of carbon uptake per hectare is highly spatially variable, with over 100-fold variability in uptake rates globally (Cook-Patton et al., 2020). These uptake rates have been extensively modeled, though estimates vary with respect to restoration activity (e.g., natural regeneration or plantation establishment) and carbon pools included (e.g., above-ground biomass only, above- and below-ground biomass, or total biomass and soil carbon). For forests undergoing natural regeneration, estimates of effectiveness ranged from 1.0 t CO₂‑eq /ha/yr for biomass in boreal forests (Cook-Patton et al., 2020) to 18.8 t CO₂‑eq /ha/yr for biomass and soils in humid tropical forests in South America (Bernal et al., 2018).
Estimates of the potential climate impacts of forest restoration vary widely, with differences driven largely by variability in the estimates of land area available for forest restoration. The IPCC reported a global technical mitigation potential of 3.9 Gt CO₂‑eq/yr with an uncertainty range of 0.5–10.1 Gt CO₂‑eq/yr, and an economically feasible mitigation potential of 1.6 Gt CO₂‑eq/yr with an uncertainty range of 0.5–3.0 Gt CO₂‑eq/yr (Nabuurs et al., 2022). Cook-Patton et al. (2020) estimated a maximum mitigation potential of 8.91 Gt CO₂‑eq/yr and a mitigation potential of 5.87 Gt CO₂‑eq/yr under existing national commitments. Roe et al. (2021) estimated a technical mitigation potential of 8.47 Gt CO₂‑eq/yr and a cost-effective mitigation potential of 1.53 Gt CO₂‑eq/yr. Griscom et al. (2017) reported a technical mitigation potential of 10.1 Gt CO₂‑eq/yr, though the uncertainty estimates spanned 2.7–17.9 Gt CO₂‑eq/yr. Using a more conservative estimate of the area available for forest restoration than previous studies, Fesenmeyer et al. (2025) estimated that sequestration of 2.2 Gt CO₂‑eq/yr is feasible.
The quantitative results presented in this assessment synthesize findings from 16 global datasets supplemented by four national-scale studies. We recognize that geographic bias in the information underlying global data products creates bias and hope this work inspires research and data sharing on this topic in underrepresented regions.
Farmers on much of the world’s 1.4 billion ha of cropland grow and harvest annual crops – crops like wheat, rice, and soybeans that live for one year or less. After harvest, croplands are often left bare for the rest of the year and sometimes tilled, exposing the soil to wind and rain. This keeps soil carbon levels low and can lead to soil erosion. There are many ways to improve annual cropping to protect or enhance the health of the soil and increase soil organic matter. Project Drawdown’s Improve Annual Cropping solution is a set of practices that protects soils by minimizing plowing (no-till/reduced tillage) and maintaining continuous soil cover (by retaining crop residues or growing cover crops). This increases soil carbon sequestration and reduces nitrous oxide emissions. These techniques are commonly used in conservation agriculture, regenerative, and agro-ecological cropping systems. Other annual cropping practices with desirable climate impacts – including compost application and crop rotations – are omitted here due to lack of data and much smaller scale of adoption. New adoption is estimated from the 2025 level as a baseline which is therefore set to zero.
The Improve Annual Cropping solution incorporates several practices that minimize soil disturbance and introduce a physical barrier meant to prevent erosion to fragile topsoils. Our definition includes two of the three pillars of conservation agriculture: minimal soil disturbance and permanent soil cover (Kassam et al., 2022).
Soil organic carbon (SOC) – which originates from decomposed plants – helps soils hold moisture and provides the kinds of chemical bonding that allow nutrients to be stored and exchanged easily with plants. Soil health and productivity depend on microbial decomposition of plant biomass residues, which mobilizes critical nutrients in soil organic matter (SOM) and builds SOC. Conventional tillage inverts soil, buries residues, and breaks down compacted soil aggregates. This process facilitates microbial activity, weed removal, and water infiltration for planting. However, tillage can accelerate CO₂ fluxes as SOC is lost to oxidation and runoff. Mechanical disturbance further exposes deeper soils to the atmosphere, leading to radiative absorption, higher soil temperatures, and catalyzed biological processes – all of which increase oxidation of SOC (Francaviglia et al., 2023).
Reduced tillage limits soil disturbance to support increased microbial activity, moisture retention, and stable temperature at the soil surface. This practice can increase carbon sequestration, at least when combined with cover cropping. These effects are highly contextual, depending on tillage intensity and soil depth as well as the practice type, duration, and timing. Reduced tillage further reduces fossil fuel emissions from on-farm machinery. However, this practice often leads to increased reliance on herbicides for weed control (Francaviglia et al., 2023).
Residue retention and cover cropping practices aim to provide permanent plant cover to protect and improve soils. This can improve aggregate stability, water retention, and nutrient cycling. Farmers practicing residue retention leave crop biomass residues on the soil surface to suppress weed growth, improve water infiltration, and reduce evapotranspiration from soils (Francaviglia et al., 2023).
Cover cropping includes growth of spontaneous or seeded plant cover, either during or between established cropping cycles. In addition to SOC, cover cropping can help decrease nitrous oxide emissions and bind nitrogen typically lost via oxidation and leaching. Leguminous cover crops can also fix atmospheric nitrogen, reducing the need for fertilizer. Cover cropping can further be combined with reduced tillage for additive SOC and SOM gains (Blanco-Canqui et al., 2015; Francaviglia et al., 2023).
Improved annual cropping practices can simultaneously reduce GHG emissions and improve SOC stocks. However, there are biological limits to SOC stocks – particularly in mineral soils. Environmental benefits are impermanent and only remain if practices continue long term (Francaviglia et al., 2023).
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Avery Driscoll
Erika Luna
Megan Matthews, Ph.D.
Eric Toensmeier
Aishwarya Venkat, Ph.D.
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Aiyana Bodi
Emily Cassidy, Ph.D.
James Gerber, Ph.D.
Hannah Henkin
Zoltan Nagy, Ph.D.
Ted Otte
Paul C. West, Ph.D.
Based on seven reviews and meta-analyses, which collectively analyzed over 500 studies, we estimate that this solution’s SOC sequestration potential is 1.28 t CO₂‑eq/ha/yr. This is limited to the topsoil (>30 cm), with minimal effects at deeper levels (Sun et al., 2020; Tiefenbacher et al., 2021). Moreover, carbon sequestration potential is not constant over time. The first two decades show the highest increase, followed by an equilibrium or SOC saturation (Cai, 2022; Sun et al., 2020).
The effectiveness of the Improve Annual Cropping solution heavily depends on local geographic conditions (e.g., soil properties, climate), crop management practices, cover crop biomass, cover crop types, and the duration of annual cropping production – with effects typically better assessed in the long term (Abdalla et al., 2019; Francaviglia et al., 2023; Moukanni et al., 2022; Paustian et al., 2019).
Based on reviewed literature (three papers, 18 studies), we estimated that improved annual cropping can potentially reduce nitrous oxide emissions by 0.51 t CO₂‑eq/ha/yr (Table 1). Cover crops can increase direct nitrous oxide emissions by stimulating microbial activity, but – compared with conventional cropping – lower indirect emissions allow for reduced net nitrous oxide emissions from cropland (Abdalla et al., 2019).
Nitrogen fertilizers drive direct nitrous oxide emissions, so genetic optimization of cover crops to increase nitrogen-use efficiencies and decrease nitrogen leaching could further improve mitigation of direct nitrous oxide emissions (Abdalla et al., 2019).
Table 1. Effectiveness at reducing emissions and removing carbon.
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| 25th percentile | 0.29 |
| Median (50th percentile) | 0.51 |
| 75th percentile | 0.80 |
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| 25th percentile | 0.58 |
| Median (50th percentile) | 1.28 |
| 75th percentile | 1.72 |
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| 25th percentile | 0.87 |
| Median (50th percentile) | 1.79 |
| 75th percentile | 2.52 |
Because baseline (conventional) annual cropping systems are already extensive and well established, we assume there is no cost to establish new baseline cropland. In the absence of global datasets on costs and revenues of cropping systems, we used data on the global average profit per ha of cropland from Damania et al. (2023) to create a weighted average profit of US$76.86/ha/yr.
Based on 13 data points (of which seven were from the United States), the median establishment cost of the Improve Annual Cropping solution is $329.78/ha. Nine data points (three from the United States) provided a median increase in profitability of US$86.01/ha/yr.
The net net cost of the Improve Annual Cropping solution is US$86.01. The cost per t CO₂‑eq is US$47.80 (Table 2).
Table 2. Cost per unit climate impact.
Unit: 2023 US$/t CO₂‑eq, 100-yr basis
| Median | 47.80 |
We found limited information on this solution’s learning curve. A survey of farmers in Zambia found a reluctance to avoid tilling soils because of the increased need for weeding or herbicides and because crop residues may need to be used for livestock feed (Arslan et al., 2015; Searchinger et al., 2019).
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 Annual Cropping is a DELAYED climate solution. It works more slowly than gradual or emergency brake solutions. Delayed solutions can be robust climate solutions, but it’s important to recognize that they may not realize their full potential for some time.
As with other biosequestration solutions, carbon stored in soils via improved annual cropping is not permanent. It can be lost quickly through a return to conventional agriculture practices like plowing, and/or through a regional shift to a drier climate or other human- or climate change–driven disturbances. Carbon sequestration also only continues for a limited time, estimated at 20–50 years (Lal et al., 2018)).
Kassam et al. (2022) provided regional adoption from 2008–2019. We used a linear forecast to project 2025 adoption. This provided a figure of 267.4 Mha in 2025 (Table 3). Note that in Solution Basics in the dashboard we set current adoption at zero. This is a conservative assumption to avoid counting carbon sequestration from land that has already ceased to sequester net carbon due to saturation, which takes place after 20–50 years (Lal et al., 2018).
Table 3. Current (2025) adoption level.
Unit: Mha of improved annual cropping
| Estimate | 267.4 |
Between 2008–2009 and 2018–2019 (the most recent data available), the cropland area under improved annual cropping practices nearly doubled globally, increasing from 10.6 Mha to 20.5 Mha at an average rate of 1.0 Mha/yr (Kassam et al., 2022), equivalent to a 9.2% annual increase in area relative to 2008–2009 levels. Adoption slowed slightly in the latter half of the decade, with an average increase of 0.8 Mha/yr between 2015–2016 and 2018–2019, equivalent to 4.6% annual increase in area relative to 2015–2016 levels, as shown in Table 4.
Table 4. 2008–2009 to 2018–2019 adoption trend.
Unit: Mha adopted/yr
| Mean | 9.99 |
Griscom et al. (2017) estimate that 800 Mha of global cropland are suitable – but not yet used for – cover cropping, in addition to 168 Mha already in cover crops (Popelau and Don, 2015). We update the 168 Mha in cover crops to 267 Mha based on Kassam (2022). Griscom et al.’s estimate is based on their analysis that much cropland is unsuitable because it already is used to produce crops during seasons in which cover crops would be grown. Their estimate thus provides a maximum technical potential of 1,067 Mha by adding 800 Mha of remaining potential to the 267.4 Mha of current adoption (Table 5).
Table 5. Adoption ceiling.
Unit: Mha
| Adoption ceiling | 1,067 |
The 8th World Congress on Conservation Agriculture (8WCCA) set a goal to achieve adoption of improved annual cropping on 50% of available cropland by 2050 (WCCA 2021). That provides an Achievable – High of 700 Mha – though this is not a biophysical limit.
We used the 2008–2019 data from Kassam (2022) to calculate average annual regional growth rates. From these we selected the 25th percentile as our low achievable level (Table 6).
Table 6. Range of achievable adoption levels.
Unit: Mha
| Current adoption | 267.4 |
| Achievable – low | 331.7 |
| Achievable – high | 700.0 |
| Adoption ceiling | 1,067 |
Unit: Mha installed
| Current adoption | 0.00 |
| Achievable – low | 64.2 |
| Achievable – high | 432.6 |
| Adoption ceiling | 868.6 |
Carbon sequestration continues only for a period of decades; because adoption of improved annual cropping was already underway in the 1970s (Kassam et al., 2022), we could not assume that previously adopted hectares continue to sequester carbon indefinitely. Much of the current adoption of improved annual cropping has been in place for decades and sequestration in some of this land has presumably already slowed down to almost zero. We apply an adoption adjustment factor of 0.5 to current adoption (see methodology) to reflect that an estimated half of current adoption is no longer sequestering significant carbon, yet there is substantial new adoption within the last 20-50 years.
For new adoption, the calculation is effectiveness * new adoption = climate impact.
For calculating impact of current adoption, the calculation is the sum of a and b where:
a: for carbon sequestration, the calculation is effectiveness * 0.5 * current adoption = climate impact, and
b: for nitrous oxide reduction, the calculation is effectiveness * current adoption = climate impact.
Climate impacts shown in Table 6 are the sum of current and new adoption impacts. Combined effect is 0.31 Gt CO2-eq/yr for current adoption, 0.43 for Achievable – Low, 1.09 for Achievable – High, and 1.87 for our Adoption Ceiling.
Table 8. Climate impact at different levels of adoption.
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current adoption | 0.14 |
| Achievable – low | 0.17 |
| Achievable – high | 0.36 |
| Adoption ceiling | 0.58 |
(from nitrous oxide)
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current adoption | 0.17 |
| Achievable – low | 0.25 |
| Achievable – high | 0.73 |
| Adoption ceiling | 1.29 |
(from SOC)
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current adoption | 0.31 |
| Achievable – low | 0.43 |
| Achievable – high | 1.09 |
| Adoption ceiling | 1.87 |
The soil and water benefits of this solution can lead to agricultural systems that are more resilient to extreme weather events (Mrabet et al., 2023). These agricultural systems have improved uptake, conservation, and use of water, so they are more likely to successfully cope and adapt to drought, dry conditions, and other adverse weather events (Su et al., 2021). Additionally, more sustained year-round plant cover can increase the capacity of cropping systems to adapt to high temperatures and extreme rainfall (Blanco-Canqui & Francis, 2016; Martínez-Mena et al., 2020).
Increased organic matter due to improved annual cropping increases soil water holding capacity. This increases drought resilience (Su et al., 2021).
Conservation agriculture practices can reduce costs on fuel, fertilizer, and pesticides (Stavi et al., 2016). The highest revenues from improved annual cropping are often found in drier climates. Tambo et al. (2018) found when smallholder farmers in sub-Saharan Africa jointly employed the three aspects of conservation agriculture – reduced tillage, cover crops, and crop rotation – households and individuals saw the largest income gains. Nyagumbo et al. (2020) found that smallholder farms in sub-Saharan Africa using conservation agriculture had the highest returns on crop yields when rainfall was low.
Improved annual cropping can improve food security by increasing the amount and the stability of crop yields. A meta-analysis of studies of South Asian cropping systems found that those following conservation agriculture methods had 5.8% higher mean yield than cropping systems with more conventional agriculture practices (Jat et al., 2020). Evidence supports that conservation agriculture practices especially improve yields in water scarce areas (Su et al., 2021). Nyagumbo et al. (2020) found that smallholder farmers in sub-Saharan Africa experienced reduced yield variability when using conservation agriculture practices.
Improved annual cropping can increase biodiversity below and above soils (Mrabet et al., 2023). Increased vegetation cover improves habitats for arthropods, which help with pest and pathogen management (Stavi et al., 2016).
Improved annual cropping methods can lead to improved soil health through increased stability of soil structure, increased soil nutrients, and improved soil water storage (Francaviglia et al., 2023). This can reduce soil degradation and erosion (Mrabet et al., 2023). Additionally, more soil organic matter can lead to additional microbial growth and nutrient availability for crops (Blanco-Canqui & Francis, 2016).
Runoff of soil and other agrochemicals can be minimized through conservation agricultural practices, reducing the amount of nitrate and phosphorus that leach into waterways and contribute to algal blooms and eutrophication (Jayaraman et al., 2021). Abdalla et al. (2019) found that cover crops reduced nitrogen leaching.
Herbicides – in place of tillage – are used in many but not all no-till cropping systems to kill (terminate) the cover crop. The large-scale use of herbicides in improved annual cropping systems can produce a range of environmental and human health consequences. Agricultural impacts can include development of herbicide-resistant weeds (Clapp, 2021).
If cover crops are not fully terminated before establishing the main crop, there is a risk that cover crops can compete with the main crop (Quintarelli et al., 2022).
Improved annual cropping has competing interactions with several other solutions related to shifting annual practices. For each of these other solutions, the Improve Annual Cropping solution can reduce the area on which the solution can be applied or the nutrient excess available for improved management.
In no-till systems, cover crops are typically terminated with herbicides, often preventing incorporation of trees depending on the type of herbicide used.
Land managed under the Improve Annual Cropping solution is not available for perennial crops.
Improved annual cropping typically reduces fertilizer demand, reducing the scale of climate impact under improved nutrient management.
Our definition of improved annual cropping requires residue retention, limiting the additional area available for deployment of reduced burning.
ha cropland
CO₂ , N₂O
Some studies have found that conservation tillage without cover crops can reduce soil carbon stocks in deeper soil layers. They caution against overreliance on no-till as a sequestration solution in the absence of cover cropping. Reduced tillage should be combined with cover crops to ensure carbon sequestration (Luo et al., 2010; Ogle et al., 2019; Powlson et al., 2014).
Agriculture has altered the soil carbon balance around the world, resulting in changes (mostly losses) of soil carbon. Much of the nearly 500 Gt CO2-eq lost in the last 12,000 years is now in the atmosphere in the form of CO2.
Sanderman, J. et al. (2017). The soil carbon debt of 12,000 years of human land use [Data set]. PNAS 114(36): 9575–9580. Link to source: https://doi.org/10.1073/pnas.1706103114
Agriculture has altered the soil carbon balance around the world, resulting in changes (mostly losses) of soil carbon. Much of the nearly 500 Gt CO2-eq lost in the last 12,000 years is now in the atmosphere in the form of CO2.
Sanderman, J. et al. (2017). The soil carbon debt of 12,000 years of human land use [Data set]. PNAS 114(36): 9575–9580. Link to source: https://doi.org/10.1073/pnas.1706103114
Adoption of this solution varies substantially across the globe. Currently, improved annual cropping practices are widely implemented in Australia and New Zealand (74% of annual cropland) and Central and South America (69%), with intermediate adoption in North America (34%) and low adoption in Asia, Europe, and Africa (1–5%) (Kassam et al., 2022), though estimates vary (see also Prestele et al., 2018). Future expansion of this solution is most promising in Asia, Africa, and Europe, where adoption has increased in recent years. Large areas of croplands are still available for implementation in these regions, whereas Australia, New Zealand, and Central and South America may be reaching a saturation point, and these practices may be less suitable for the relatively small area of remaining croplands.
The carbon sequestration effectiveness of this solution also varies across space. Drivers of soil carbon sequestration rates are complex and interactive, with climate, initial soil carbon content, soil texture, soil chemical properties (such as pH), and other land management practices all influencing the effectiveness of adopting this solution. Very broadly, the carbon sequestration potential of improved annual cropping tends to be two to three times higher in warm areas than cool areas (Bai et al., 2019; Cui et al., 2024; Lessmann et al., 2022). Warm and humid conditions enable vigorous cover crop growth, providing additional carbon inputs into soils. Complicating patterns of effectiveness, however, arid regions often experience increased crop yields following adoption of this solution whereas humid regions are more likely to experience yield losses (Pittelkow et al., 2015). Yield losses may reduce adoption in humid areas and can lead to cropland expansion to compensate for lower production.
Uptake of this solution may be constrained by spatial variation in places where cover cropping is suitable. In areas with double or triple cropping, there may not be an adequate interval for growth of a cover crop between harvests. In areas with an extended dry season, there may be inadequate moisture to grow a cover crop.
The impacts of improved annual cropping practices on soil carbon sequestration have been extensively studied, and there is high consensus that adoption of cover crops can increase carbon sequestration in soils. However, estimates of how much carbon can be sequestered vary substantially, and sequestration rates are strongly influenced by factors such as climate, soil properties, time since adoption, and how the practices are implemented.
The carbon sequestration benefits of cover cropping are well established. They have been documented in reviews and meta-analyses including Hu et al. (2023) and Vendig et al. (2023).
Relative to conventional tillage, estimates of soil carbon gains in shallow soils under no-till management include average increases of 5–20% (Bai et al., 2019; Cui et al., 2024; Kan et al., 2022). Lessmann et al. (2022) estimated that use of no-till is associated with an average annual increase in carbon sequestration of 0.88 t CO₂‑eq /ha/yr relative to high-intensity tillage.
Consensus on nitrous oxide reductions from improved annual cropping is mixed. Several reviews have demonstrated a modest reduction in nitrous oxide from cover cropping (Abdalla et al., 2019; Xing & Wang, 2024). Reduced tillage can result in either increased or decreased nitrous oxide emissions (Hassan et al., 2022).
The results presented in this document summarize findings from 10 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.
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(2019). 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.
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