Protect Seafloors is the long-term protection of the seafloor from degradation, which helps preserve existing sediment carbon stocks and avoid CO₂ emissions. Advantages of seafloor protection include the conservation of biodiversity and marine ecosystems, potentially low costs, and the ability for immediate implementation. Disadvantages include uncertainties in the effectiveness of legal protection at preventing degradation and in the amount of CO₂ emissions avoided, as well as the risk of displacement of degradation to non-protected areas and/or an increase in other types of degradation. Given these limitations, we conclude that Seafloor Protection is a climate solution to “Keep Watching” until more research can clearly show the carbon benefits of protection.
Based on our analysis, seafloor protection could avoid some CO₂ emissions while preserving critical marine ecosystems from degradation. However, the effectiveness of protection and the magnitude of avoided CO₂ emissions associated with protection are understudied and currently unclear. Therefore, we will “Keep Watching” this potential climate solution.
| Plausible | Could it work? | Yes |
|---|---|---|
| Ready | Is it ready? | No |
| Evidence | Are there data to evaluate it? | Limited |
| Effective | Does it consistently work? | No |
| Impact | Is it big enough to matter? | Yes |
| Risk | Is it risky or harmful? | No |
| Cost | Is it cheap? | Yes |
Protect Seafloors aims to reduce human impacts that can degrade sediment carbon stocks and increase CO₂ emissions. Protection is conferred through legal mechanisms, such as Marine Protected Areas (MPAs), which are managed with the primary goal of conserving nature. The seafloor stores over 2,300 Gt of carbon (roughly 8,400 Gt CO₂‑eq) in the top one meter of sediment. This marine carbon can be stable and remain sequestered for millennia. However, degradation of the seafloor from a range of human activities can disturb bottom sediments, resuspending the carbon and increasing its microbial conversion into CO₂. Currently, degradation of the seafloor primarily results from fishing practices, such as trawling and dredging, which are estimated to occur across 1.3% of the global ocean. Additional sources of degradation include undersea mining, infrastructure development (for offshore wind farms, oil, and gas), and laying telecommunications cables. Estimates of seafloor degradation are highly uncertain due to data limitations and the unpredictable nature of how these activities may expand in the future.
More evidence is needed to confirm whether legal seafloor protection is effective at reducing degradation and the extent to which degradation results in increased CO₂ emissions. While ~8% of the seafloor is currently protected through MPAs, there is mixed evidence that legal protection reduces degradation and CO₂ emissions. For instance, in a review of 49 studies examining the impacts of bottom trawling and dredging on sediment organic carbon stocks, most (61%) showed no change, while nearly a third (29%) showed carbon loss. More recent work suggests that trawling intensity might drive these mixed results, with more heavily trawled areas showing clear reductions in sediment organic carbon. Additionally, the few existing global estimates of CO₂ emissions from trawling and dredging range from 0.03 to 0.58 Gt CO₂/yr, highlighting the need for further research. The effectiveness of MPAs at preventing seafloor degradation is also mixed. In strictly protected areas with enforcement of no-take policies that prevent bottom fishing, MPAs could help minimize degradation and retain seafloor carbon. However, implementation can be challenging, as over half of existing MPAs generally allow high-impact activities. For instance, trawling and dredging occur more frequently in MPAs than in non-protected areas in the territorial waters of Europe.
Advantages of seafloor protection include its potential low cost and its ability to conserve often understudied biodiversity and ecosystems. Human activities, such as trawling and dredging, impact marine organisms on the seafloor, and ecosystem recovery can take years to occur. In the case of undersea mining, ecosystems may never fully recover. Increases in CO₂ emissions along the seafloor from degradation can also enhance local acidification and reduce the ocean's buffering capacity, both of which can affect marine organisms and the carbon sequestration capacity of seawater. Protection can also increase fisheries yields in neighboring waters and reduce other negative impacts of seafloor disturbances. While costs are somewhat uncertain, MPA expenses have been estimated to be an order of magnitude less than the often unseen ecosystem service benefits gained with protection, suggesting MPA expansion could provide cost savings.
Disadvantages of seafloor protection include uncertainties surrounding the effectiveness of preventing degradation and avoiding CO₂ emissions, as well as the potential increased risk of disturbance to other ocean areas. The amount and fate of CO₂ generated due to the degradation of seafloor carbon is complex and understudied. It can take months or even centuries for CO₂ produced at depth to reach the sea surface and atmosphere. Current estimates of CO₂ emissions due to dredging and trawling are widely debated and highly variable due to differing methods and assumptions. Large amounts of organic carbon will inevitably re-settle after seafloor disturbances, with no impact on CO₂, but estimates of just how much remain uncertain. The risk of protection-induced leakage, where a reduction in disturbances, such as trawling and dredging in MPAs, leads to increased fishing effort in other ocean areas, is also potentially high.
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Coastal wetland protection is the long-term protection of mangrove, salt marsh, and seagrass ecosystems from degradation by human activities. This solution focuses on legal mechanisms of coastal wetland protection, including the establishment of Protected Areas (PAs) and Marine Protected Areas (MPAs), which are managed with the primary goal of conserving nature. These legal protections reduce a range of human impacts, helping to preserve existing carbon stocks and avoid CO₂ emissions.
Coastal wetlands (defined as mangrove, salt marsh, and seagrass ecosystems, see Figure 1) are highly productive ecosystems that sequester carbon via photosynthesis, storing it primarily below ground in sediments where waterlogged, low-oxygen conditions help preserve it (Adame et al., 2024; Lovelock et al., 2017).
Figure 1. Types of coastal wetlands, from left to right: a salt marsh in Westhampton Beach (United States), a mangrove forest near Staniel Cay (Bahamas), and a seagrass meadow off Notojima Island (Japan).
Adobe Stock | istock; Maria T Hoffman | Adobe Stock; James White and Danita Delimont | AdobeStock
These ecosystems are also efficient at trapping carbon suspended in water, which can comprise up to 50% of the carbon sequestered in the system (McLeod et al., 2011; Temmink et al., 2022). Coastal wetlands operate as large carbon sinks (Figure 2), with long-term carbon accumulation rates averaging 5.1–8.3 t CO₂‑eq /ha/yr (McLeod et al., 2011).
Figure 2. Overview of carbon storage in coastal wetlands. Salt marshes, mangroves, and seagrasses, commonly referred to as blue carbon ecosystems, store carbon in plant biomass and sediment.
Source: Macreadie, P. I., Costa, M. D., Atwood, T. B., Friess, D. A., Kelleway, J. J., Kennedy, H., ... & Duarte, C. M. (2021). Blue carbon as a natural climate solution. Nature Reviews Earth & Environment, 2(12), 826-839. Link to source: https://doi.org/10.1038/s43017-021-00224-1
Protection of coastal wetlands preserves carbon stocks and avoids emissions associated with degradation, which can increase CO₂, methane, and nitrous oxide effluxes. Nearly 50% of the total global area of coastal wetlands has been lost since 1900 and up to 87% since the 18th century (Davidson, 2014). With current loss rates, an additional 30–40% of remaining seagrasses, salt marshes, and nearly all mangroves could be lost by 2100 without protection (Pendleton et al., 2012). Protection of existing coastal wetlands is especially important because restoration is challenging, costly, and not yet fully optimized. For example, seagrass restoration has generally been unsuccessful (Macreadie et al., 2021), and restored seagrass systems can have higher GHG fluxes than natural systems (Mason et al., 2023).
On land, degradation often arises from aquaculture, reclamation and drainage, deforestation, diking, and urbanization (Mcleod et al., 2011). In the ocean, impacts often occur due to dredging, mooring, pollution, and sediment disturbance (Mcleod et al., 2011). For instance, deforestation of mangroves for agriculture removes biomass and oxidizes sediment carbon stocks, leading to high CO₂ effluxes and, potentially, methane and nitrous oxide emissions (Chauhan et al., 2017, Kauffman et al., 2016, Sasmito et al., 2019). Likewise, high CO₂ or methane effluxes from salt marshes commonly result from drainage, which can oxygenate the subsurface and fuel carbon loss, or from infrastructure such as dikes, which can reduce saltwater exchange and increase methane production (Kroeger et al., 2017). In another example, dredging in seagrass meadows drives high rates of ecosystem degradation due to reduced light availability, leading to die-offs that can increase erosion and reduce sediment carbon stocks 21–47% (Trevathan-Tackett et al., 2018).
Our analysis focused on the avoided CO₂ emissions and retained carbon sequestration capacity conferred by avoiding degradation of coastal wetlands via legal protection. While degradation can substantially alter emissions of other GHGs, such as methane and nitrous oxide, we focus on CO₂ due to the limited availability of global spatial data on degradation types and extent and associated effluxes of all GHGs across coastal wetlands. Ignoring methane and nitrous oxide benefits with protection is the most conservative approach because limited data exist on emission profiles from both functional and degraded global coastal wetlands, and even PAs/MPAs can be degraded (Holmquist et al., 2023). This solution considered wetlands to be protected if they are formally designated as PAs or MPAs under International Union for Conservation of Nature (IUCN) protection categories I–IV (UNEP-WCMC &IUCN, 2024; see Appendix for more information).
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Christina Richardson, Ph.D.
Ruthie Burrows, Ph.D.
Avery Driscoll
James Gerber, Ph.D.
Daniel Jasper
Christina Swanson, Ph.D.
Alex Sweeney
Paul West, Ph.D.
Aiyana Bodi
Avery Driscoll
James Gerber, Ph.D.
Hannah Henkin
Ted Otte
Christina Swanson, Ph.D.
We estimated that coastal wetland protection avoids emissions of 2.33–5.74 t CO₂‑eq /ha/yr, while also sequestering an additional 1.22–2.14 t CO₂‑eq /ha/yr depending on the ecosystem (Tables 1a–c; see the Appendix for more information). We estimated effectiveness as the avoided CO₂ emissions and the retained carbon sequestration capacity attributable to the reduction in wetland loss conferred by protection, as detailed in Equation 1. First, we calculated the difference between the rate of wetland loss outside PAs and MPAs (Wetland lossbaseline) versus inside PAs and MPAs, since protection does not entirely prevent degradation. Loss rates were primarily driven by anthropogenic habitat conversion. The effectiveness of protection was 53–59% (Reduction in loss). We then multiplied the avoided wetland loss by the sum of the avoided CO₂ emissions associated with the loss of carbon stored in sediment and biomass in one ha of wetland each year over a 30-yr timeframe (Carbonavoided emissions) and the amount of carbon sequestered via long-term storage in sediment carbon by one ha of protected wetland each year over a 30-yr timeframe (Carbonsequestration).
Equation 1. Effectiveness = (Wetland lossbaseline ✕ Reduction in loss)* (Carbonavoided emissions + Carbonsequestration )
We did this calculation separately for mangrove, salt marsh, and seagrass ecosystems, because many of these factors, such as carbon emission and sequestration rates, protection effectiveness, and loss rates, vary across ecosystem types. The rationale for increasing protection varies between coastal wetland ecosystem types, but in all cases, protection is an important tool for retaining and building long-lived carbon stocks. Additionally, climate impacts associated with this solution could be much greater than estimated if protection efficacy improves or is higher than our estimates of 53–59%.
Table 1a. Effectiveness at avoiding emissions and sequestering carbon in mangrove ecosystems.
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 5.64 |
| mean | 6.80 |
| median (50th percentile) | 5.74 |
| 75th percentile | 7.42 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 2.00 |
| mean | 2.14 |
| median (50th percentile) | 2.14 |
| 75th percentile | 2.38 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 7.64 |
| mean | 8.94 |
| median (50th percentile) | 7.88 |
| 75th percentile | 9.81 |
Table 1b. Effectiveness at avoiding emissions and sequestering carbon in salt marsh ecosystems.
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 2.79 |
| mean | 2.90 |
| median (50th percentile) | 2.90 |
| 75th percentile | 3.01 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 1.59 |
| mean | 1.90 |
| median (50th percentile) | 1.88 |
| 75th percentile | 2.19 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 4.38 |
| mean | 4.80 |
| median (50th percentile) | 4.78 |
| 75th percentile | 5.20 |
Table 1c. Effectiveness at avoiding emissions and sequestering carbon in seagrass ecosystems.
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 2.11 |
| mean | 2.33 |
| median (50th percentile) | 2.33 |
| 75th percentile | 2.56 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 1.04 |
| mean | 1.53 |
| median (50th percentile) | 1.22 |
| 75th percentile | 1.71 |
Unit: t CO₂‑eq /ha protected/yr, 100-yr basis
| 25th percentile | 3.15 |
| mean | 3.86 |
| median (50th percentile) | 3.56 |
| 75th percentile | 4.27 |
We estimate that coastal wetland protection costs approximately US$1–2/t CO₂‑eq for mangrove and salt marsh ecosystems and seagrass ecosystem protection saves US$6/t CO₂‑eq (Tables 2a–c). This is based on protection costs of roughly US$11/ha and revenue of US$23/ha compared with the baseline for mangrove/salt marsh and seagrass ecosystems, respectively. However, data related to the costs of coastal wetland protection are extremely limited, and these estimates are uncertain. These estimates likely underestimate the potentially high costs of coastal land acquisition, for instance.
The costs of coastal wetland protection include up-front costs of land acquisition (for salt marshes and mangroves) and other one-time expenditures as well as ongoing operational costs. Protecting coastal wetlands also generates revenue, primarily through increased tourism. For consistency across solutions, we did not include revenue associated with benefits other than climate change mitigation.
Due to data limitations, we estimated the cost of land acquisition for ecosystem protection for mangroves and salt marshes by extracting coastal forest land purchase costs reported by Dinerstein et al. (2024), who found a median cost of US$1,115/ha (range: US$78–5,910/ha), which we amortized over 30 years. For seagrass ecosystems, which do not generally require land acquisition, we based initial costs were on McCrea-Strub et al.’s (2011) findings that reported a median MPA start-up cost of US$208/ha (range: US$55–434/ha) to cover expenses associated with infrastructure, planning, and site research, which we amortized over 30 years.
Costs of PA maintenance were estimated as US$17/ha/yr (Waldron et al., 2020). While these estimates reflect the costs of effective enforcement and management, many PAs lack sufficient funding for effective management (Bruner et al., 2004). Costs of MPA maintenance were estimated at US$14/ha/yr, though only 16% of the MPAs surveyed in this study reported their current funding as sufficient (Balmford et al., 2004). Tourism revenues directly attributable to protection were estimated to be US$43/ha/yr (Waldron et al., 2020) based on estimates for all PAs and MPAs and excluding downstream revenues. For consistency across solutions, we did not include revenues associated with ecosystem services, which would increase projected revenue.
We also excluded carbon credits as a revenue source due to the challenges inherent in accurate carbon accounting in these ecosystems and their frequently intended use to offset carbon emissions, similar to reported concerns with low-quality carbon credits in forest conservation projects (West et al., 2023). Future actions could explore policies that increase market financing for coastal wetland protection in more holistic ways, such as contributions-based approaches as suggested for forests (Blanchard et al., 2024). Financial support will be critical for backing conservation implementation (Macreadie et al., 2022), particularly in the face of existing political and economic challenges that have historically limited expansion.
Table 2. Cost per unit climate impact.
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| estimate | 1 |
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| estimate | 2 |
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| estimate | -6 |
Negative value indicates cost savings.
We define a learning curve as falling costs with increased adoption. The costs of coastal wetland protection do not fall with increasing adoption, so 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.
Protect Coastal Wetlands 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.
Additionality in this solution refers to whether the ecosystem would have been degraded without protection. In this analysis, we assumed protection confers additional carbon benefits as it reduces degradation and associated emissions. Another aspect of additionality, which is related but not necessarily relevant to our analysis, is whether coastal wetlands would have been protected in the absence of carbon financing, which could be important if protection efforts expand and seek carbon credits as many coastal wetlands are protected for other benefits, such as flood resilience and biodiversity.
The permanence of stored carbon in coastal wetlands is another critical issue as climate change impacts unfold. For instance, with sea-level rise, the ability of salt marshes to expand both vertically and laterally can determine resiliency, suggesting that protection of wetlands might also need to include adjacent areas for expansion (Schuerch et al., 2018). On a global scale, recent research suggests that global carbon accumulation might actually increase by 2100 from climate change impacts on tidal wetlands (Wang et al., 2021), though more work is needed as other work suggests the opposite (Noyce et al., 2023). There is also substantial risk of reversal of carbon benefits if protections are reversed or unenforced, which can require long-term financial investments, community engagement, and management/enforcement commitments (Giakoumi et al., 2018), particularly if the land is leased.
Finally, there are significant uncertainties associated with the available data on coastal wetland areas and distributions, loss rates, drivers of loss, extent and boundaries of PAs/MPAs, and efficacy of PAs/MPAs at reducing coastal wetland disturbance. For example, the geospatial datasets we used to identify the adoption ceiling for this solution could include partially degraded systems, such as drained wetlands, where protection alone would not stop emissions or restore function without restoration – yet we lack enough data to distinguish these current differences at a global scale. Similarly, legal protection of coastal wetlands does not always prevent degradation (Heck et al., 2024). The emissions dynamics of both intact and degraded coastal wetlands are also uncertain. Even less is known about the impacts of different types of degradation on coastal wetland carbon dynamics and how they vary spatially and temporally around the world.
We estimated that approximately 8.04 million ha of coastal wetlands are currently protected, with 5.13 million ha recognized as PAs and MPAs in strict (I–II) protection categories and 2.90 million ha in non-strict protection categories (III–IV) (Tables 3a–c; Garnett et al., 2018; UNEP-WCMC & IUCN, 2024, see Appendix). Indigenous People’s Lands (IPLs) cover an additional 3.44 million ha; we did not include these in our analysis due to limited data, but we recognize that these sites might currently deliver conservation benefits. In total, we estimate that roughly 15% of all coastal wetlands have some protection (as MPAs or PAs in IUCN categories I–IV), though only about 9% are under strict protection (IUCN categories I or II). Across individual ecosystem types, strict protection categories (IUCN I–II) are highest for mangroves (~15%) and lowest for seagrasses (~7%).
Our estimates of PA and MPA protection (12–19%) were lower than previously reported estimates for mangroves (40–43%, Dabalà et al., 2023; Leal and Spalding, 2024), tidal marshes (45%, Worthington et al., 2024), and seagrasses (26%, United Nations Environment Programme [UNEP], 2020). This is likely because our calculations excluded IUCN categories (“not assigned,” “not applicable,” and “not reported”) that contain large areal estimates for each ecosystem type – 4.3 million ha (mangrove), 1.9 million ha (salt marsh), and 5.4 million ha (seagrasses) – because their protection category was unclear as well as IUCN protection categories V–VI, which permit sustainable use and where extractive activities that could degrade these ecosystems are less formally restricted. Our spatial analysis also differed (see Appendix).
Table 3a. Current extent of mangrove ecosystems under legal protection by ecosystem type (circa 2023). “Strict Protection” includes land within IUCN Categories I–II PAs or MPAs. “Nonstrict Protection” includes land within IUCN Categories III–IV PAs or MPAs. “Other” includes land within all remaining IUCN PA or MPA categories (Million ha protected).
Table 3. Current extent of ecosystems under legal protection by ecosystem type (circa 2023). “Strict Protection” includes land within IUCN Categories I–II PAs or MPAs. “Nonstrict Protection” includes land within IUCN Categories III–IV PAs or MPAs. “Other” includes land within all remaining IUCN PA or MPA categories.
Unit: million ha protected
| Strict Protection | 2.35 |
| Nonstrict Protection | 0.59 |
| Total (Strict + Nonstrict) | 2.94 |
| IPL | 1.86 |
| Other | 7.52 |
Unit: million ha protected
| Strict Protection | 0.62 |
| Nonstrict Protection | 0.62 |
| Total (Strict + Nonstrict) | 1.24 |
| IPL | 1.09 |
| Other | 3.14 |
Unit: million ha protected
| Strict Protection | 2.17 |
| Nonstrict Protection | 1.69 |
| Total (Strict + Nonstrict) | 3.86 |
| IPL | 0.49 |
| Other | 9.00 |
We calculated the rate of PA and MPA expansion based on their recorded year of establishment. Protection expanded by an average of 59,600, 19,700, and 98,500 ha/yr in mangrove, salt marsh, and seagrass ecosystems, respectively (Tables 4a–c; Figure 3a). Salt marsh ecosystems have the lowest absolute rate of coastal wetland protection expansion (Figure 3b), while seagrasses have the lowest expansion of PAs relative to their adoption ceiling (Figure 3, right). The median total annual adoption trend across the three ecosystems is roughly 123,100 ha/yr (roughly 0.12 million ha/yr).
Table 4. 2000–2020 adoption trend for legal protection of ecosystems.
Unit: ha/yr protected
| 25th percentile | 23,000 |
| mean | 59,600 |
| median (50th percentile) | 40,700 |
| 75th percentile | 76,600 |
Unit: ha/yr protected
| 25th percentile | 8,400 |
| mean | 19,700 |
| median (50th percentile) | 18,500 |
| 75th percentile | 23,300 |
Unit: ha/yr protected
| 25th percentile | 12,800 |
| mean | 98,500 |
| median (50th percentile) | 37,800 |
| 75th percentile | 142,900 |
Figure 3. (a) Areal trend in coastal wetland protection by ecosystem type (2000–2020). These values reflect only the area located within IUCN Class I–IV PAs or MPAs; (ha/yr protected). (b) Trend in coastal wetland protection by ecosystem type as a percent of the adoption ceiling. These values reflect only the area located within IUCN Class I–IV PAs or MPAs; (Percent). Source: Project Drawdown original analysis.
Credit: Project Drawdown
We estimate an adoption ceiling of 54.6 million ha of coastal wetlands globally, which includes 15.7 million ha of mangroves, 7.50 million ha of salt marshes, and 31.4 million ha of seagrasses (Tables 5a–c). This estimate is in line with recent existing global estimates of coastal wetlands (36–185 million ha), which have large ranges due to uncertainties surrounding seagrass and salt marsh distributions (Macreadie et al., 2021, Krause et al., 2025). The adoption ceiling of our solution is therefore a conservative estimate of potential climate impact if global areas are indeed larger than calculated. While the protection of all existing coastal wetlands is highly unlikely, these values are used to represent the technical limits of adoption of this solution.
Table 5. Adoption ceiling: upper limit for adoption of legal protection of ecosystems.
Unit: million ha protected
| estimate | 15.7 |
Unit: million ha protected
| estimate | 7.50 |
Unit: million ha protected
| estimate | 31.4 |
We defined the lower end of the achievable range for coastal wetland protection (under IUCN categories I–IV) as 50% of the adoption ceiling and the higher end of the achievable range as 70% of the adoption ceiling for each ecosystem (Tables 6a–c). These numbers are ambitious but precedent exists to support them. For instance, roughly 11 countries already protect over 70% of their mangroves (Dabalà et al., 2023), and the global “30 by 30” target aims to protect 30% of ecosystems on land and in the ocean by 2030 (Roberts et al., 2020). Further, a significant extent of existing global coastal wetland areas already fall under non-strict protection categories not included in our analysis (V–VI and “Other”). These are prime candidates for conversion to stricter protection categories, so long as the designation confers real conservation benefits; recent work suggests that stricter protection can coincide with increased degradation in some mangroves (Heck et al., 2024).
Current adoption of PAs and MPAs in many countries with the highest land areas of coastal wetlands is low. For example, protection levels (IUCN I–IV) in countries with the top 10 greatest mangrove areas ranges between less than 1% (India, Myanmar, Nigeria, and Papua New Guinea) to 8.8–21.2% (Australia, Bangladesh, Brazil, Indonesia, Malaysia, and Mexico;Dabalà et al., 2023). Expansion of PAs, particularly under IUCN I–IV categories, is a significant challenge with real implementation barriers due to competing land uses and local reliance on these areas for livelihoods. Further, protection does not guarantee conservation benefits, and significant funding is required to maintain/enforce these areas or they run the risk of becoming “paper parks” (Di Minin & Toivonen, 2015). Strong policy and financial incentives for conservation will be necessary to achieve these ambitious goals. Pathways for operationalizing protection could include finance, governance, and stakeholder alignment and will likely require a combination of these tactics around the world.
Table 6. Range of achievable adoption levels for ecosystems.
Unit: million ha protected
| Current Adoption | 2.94 |
| Achievable – Low | 7.85 |
| Achievable – High | 11.0 |
| Adoption Ceiling | 15.7 |
Unit: million ha protected
| Current Adoption | 1.24 |
| Achievable – Low | 3.75 |
| Achievable – High | 5.25 |
| Adoption Ceiling | 7.50 |
Unit: million ha protected
| Current Adoption | 3.86 |
| Achievable – Low | 15.7 |
| Achievable – High | 22.0 |
| Adoption Ceiling | 31.4 |
We estimated that coastal wetland protection currently avoids approximately 0.04 Gt CO₂‑eq/yr, with potential impacts of 0.27 Gt CO₂‑eq/yr at the adoption ceiling (Table 7a–c, see Appendix for more information on the calculations). The lower-end achievable scenario (50% protection) would avoid 0.14 Gt CO₂‑eq/yr and the upper-end achievable scenario (70% protection) would avoid 0.20 Gt CO₂‑eq/yr (Tables 7a–c). These values are in line with Macreadie et al. (2021), who estimated a maximum mitigation potential from avoided emissions due to degradation (land conversion) of 0.30 (range: 0.14–0.47) Gt CO₂‑eq/yr for mangrove, salt marsh, and seagrass ecosystems. Our estimate was slightly lower, but within their range, and differed in a few key ways. We accounted for the effectiveness of protection at reducing degradation (53–59%, instead of assuming 100%), included retained carbon sequestration with each hectare protected, and used slightly different loss rates and ecosystem areas.
Table 7. Climate impact at different levels of adoption for ecosystems.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.02 |
| Achievable – Low | 0.06 |
| Achievable – High | 0.09 |
| Adoption Ceiling | 0.12 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.01 |
| Achievable – Low | 0.02 |
| Achievable – High | 0.03 |
| Adoption Ceiling | 0.04 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.01 |
| Achievable – Low | 0.06 |
| Achievable – High | 0.08 |
| Adoption Ceiling | 0.11 |
Wetlands buffer coastal communities from waves and storm surge due to extreme weather and have important roles in disaster risk mitigation (Sheng et al., 2022; Guannel et al., 2016). Mangroves slow the flow of water and reduce surface waves to protect more than 60 million people in low-lying coastal areas, mainly in low- and middle-income countries (McIvor et al., 2012; Hochard et al., 2021). Wetlands also protect structures against damage during storms and lead to savings in insurance claims (Barbier et al., 2013; Sheng et al., 2022). Mangroves provide an estimated US$65 billion in flood protection globally (Menéndez et al., 2020). A study of the damages of Hurricane Sandy found that wetlands in the northeastern United States avoided US$625 million in direct flood damages (Narayan et al., 2017).
Wetlands reduce coastal erosion which can benefit local communities during strong storms (Jensen, 2022). Wetlands mitigate erosion impacts by absorbing wave energy that would degrade sand and other marine sediments (U.S. EPA, 2025b). Specifically, mangroves reduce erosion through their aerial root structure that retain sediments that would otherwise degrade the shoreline (Thampanya et al., 2006).
Wetlands are a contributor to local livelihoods, providing employment for coastal populations via the fisheries and tourism that they support. Coastal ecosystems, such as mangroves, are crucial for subsistence fisheries as they sustain approximately 4.1 million small-scale fishers (Leal and Spalding, 2022). Wetlands provide sources of income for low-income coastal communities as they make small-scale fishing accessible, requiring limited gear and materials to fish (Cullen-Unsworth & Unsworth, 2018). The economic value of mangrove ecosystem services is estimated at US$33,000–57,000/ha/yr and is a major contributor to the national economies of low- and middle-income countries with mangroves (UNEP, 2014).
Mangroves support the development of numerous commercially important species and strengthen overall fishery productivity. For example, research conducted across 6,000 villages in Indonesia found that rural coastal households near high and medium-density mangroves consumed more fish and aquatic animals than households without mangroves nearby (Ickowitz et al., 2023). Seagrasses also support fisheries as 20% of the world’s largest fisheries rely on seagrasses for habitats (Jensen, 2022). The amount and diversity of species within seagrasses also provide important nutrition for fishery species (Cullen-Unsworth & Unsworth, 2018).
Coastal wetlands are significant in cultural heritages and identities for nearby people. They can be associated with historical, religious, and spiritual values for communities and especially for Indigenous communities (UNEP, 2014). For example, a combination of sea-level rise and oil and gas drilling have contributed to the decline of coastal wetlands in Louisiana, which threatens livelihoods and deep spiritual ties of local Indigenous tribes (Baniewicz, 2020; Hutchinson, 2022). Indigenous people have a long history of managing and protecting coastal wetlands (Commonwealth of Australia, 2016; Matthews & Turner, 2017). Efforts to protect these areas must include legal recognition of Indigenous ownership to support a just and sustainable conservation process (Fletcher et al., 2021).
Coastal wetlands are integral in supporting the biodiversity of surrounding watersheds. High species diversity of mangroves and seagrasses provide a unique habitat for marine life, birds, insects, and mammals, and contain numerous threatened or endangered species (Green and Short, 2003; U.S. EPA, 2025a). A variety of species rely on wetlands for food and shelter, and they can provide temporary habitats for species during critical times in their life cycles, such as migration and breeding (Unsworth et al., 2022). Wetlands can improve water quality, making the surrounding ecosystem more favorable to supporting marine life (Cullen-Unsworth & Unsworth, 2018). Seagrasses can improve coral health by filtering water and reducing pathogens that could cause disease (Cullen-Unsworth & Unsworth, 2018).
Coastal wetlands improve the water quality of watersheds by filtering chemicals, particles (including microplastics), sediment, and cycling nutrients (Unsworth et al. 2022). There is even evidence that wetlands can remove viruses and bacteria from water, leading to better sanitation and health for marine wildlife and humans (Lamb et al., 2017).
There are several risks associated with coastal wetland protection. Leakage, wherein protection in one region could prompt degradation of another, could reduce climate benefits (Renwick et al., 2015). Strict conservation of coastal wetlands could impact local economies, creating “poverty traps” if protection threatens livelihoods (McNally et al., 2011). Conservation projects also risk unequal distribution of benefits (Lang et al., 2023). In places where habitats are fragmented or existing infrastructure limits landward migration, even protected coastal wetlands are at risk of being lost with climate change (commonly known as “the coastal squeeze”; Borchert et al., 2018). Funding gaps risk reversal of climate benefits despite initial conservation efforts; most MPAs and PAs report a lack of funding (Balmford et al., 2004; Bruner et al., 2004). If coastal wetlands are subjected to human impacts that protection cannot prevent, such as upgradient nutrient pollution, there could also be a risk of increased GHG emissions (Feng et al., 2025) and ecosystem degradation.
Other ecosystems often occur adjacent to areas of coastal wetlands, and the health of nearby ecosystems can be improved by the services provided by intact coastal wetlands (and vice versa).
Reducing food loss and waste and improving diets reduce demand for agricultural land. These solutions reduce pressure to convert coastal wetlands to agricultural use, easing expansion of PAs.
Mangrove deforestation can occur for fuel wood needs. Fuel wood sourced from mangroves could be replaced with wood sourced from other forested ecosystems.
ha protected
CO₂
ha protected
CO₂
ha protected
CO₂
Trade-offs associated with protection of coastal wetlands include emission of other GHGs not quantified in this solution that have higher global warming potentials (GWP) than CO₂. Methane and nitrous oxide emissions can be measurable in coastal wetland ecosystems, though it is important to recognize that degradation can significantly impact the magnitude and types of effluxes, too. In mangroves, methane evasion can offset carbon burial by almost 20% based on a 20-yr GWP (Rosentreter et al., 2018). In seagrasses, methane and nitrous oxide effluxes can offset burial on average, globally, by 33.4% based on a 20-yr GWP and 7.0% based on a 100-yr GWP (Eyre et al., 2023). Finally, conservation of coastal land can also restrict development of desirable coastal property for other uses.
Consensus of effectiveness in sequestering carbon from coastal wetlands: High
There is high scientific consensus that coastal wetland protection is an important strategy for reducing wetland loss due to degradation and that degradation results in carbon stock loss from coastal wetlands. Rates of wetland loss are generally lower inside PAs than outside them. An analysis of over 4,000 PAs (wetland and non-wetland area) showed 59% of sites are in “sound management,” which generally reflects PAs with strong enforcement, management implementation, and conservation outcome indicators (Leverington et al., 2010). Here we used a conservative effectiveness of 59% for salt marshes and mangroves that are under legal protection, consistent with the value from Leverington et al. (2010). Other regional studies show similar PA effectiveness values, with 25–50% of wetland PAs in China exhibiting moderate to very high conservation effectiveness (Lu et al., 2016).
Seagrasses differ from mangroves and salt marshes in that they fall under MPA designation because they are subtidal, or submerged. In an analysis of effectiveness of 66 MPAs in 18 countries, nearly 53% of MPAs reported positive or slightly positive ecosystem outcomes (Rodríguez-Rodríguez & Martínez-Vega, 2022). Less is known about MPA effectiveness for seagrass meadows specifically; we assumed an effectiveness of 53% – similar to other MPAs.
Prevention of degradation via legal coastal wetlands protection avoids emissions by preserving carbon stocks while also retaining carbon sequestration capacity. Degradation of coastal wetlands results in measurable loss of short- and long-lived carbon stocks, with emissions that vary based on ecosystem and degradation type (Donato et al., 2011, Holmquist et al., 2023, Lovelock et al., 2017, Mcleod et al., 2011, Pendleton et al., 2012). Estimates of existing carbon stocks in coastal wetlands are substantial, ranging between 8.97–32.7 Gt of carbon (32.9–120 Gt CO₂‑eq ), most of which is likely susceptible to degradation (Macreadie et al., 2021).
The results presented in this document synthesize findings from 14 global datasets. 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 and understudied ecosystems.
In this analysis, we integrated global land cover data; shapefiles of PAs, MPAs, and IPLs; and ecosystem type (mangroves, salt marshes, seagrasses) data on carbon emissions and sequestration rates to calculate currently protected coastal wetland area, total global coastal wetland area, and avoided emissions and additional sequestration from coastal wetland protection by ecosystem type (mangroves, salt marshes, and seagrasses).
We used two land cover data products to estimate coastal wetland extent by ecosystem type (mangroves, salt marshes, seagrasses) inside and outside of PAs, MPAs, and IPLs: 1) a global 30 m wetland map, GWL_FCS30, for mangroves and salt marshes (Zhang et al., 2023), and 2) the global distribution of seagrasses map from UN Environment World Conservation Monitoring Centre (UNEP-WCMC & Short, 2021).
The IUCN defines PAs, including MPAs, as geographically distinct areas managed primarily for the long-term conservation of nature and ecosystem services. They are further disaggregated into six levels of protection, ranging from strict wilderness preserves to sustainable use areas that allow for some natural resource extraction (including logging). We calculated all levels of protection but only considered protection categories I–IV in our analysis of adoption. We recognized that other protection categories might provide conservation benefits. We excluded categories labeled as “Not Applicable (NAP),” “Not Reported (NR),” “Not Assigned (NAS),” as well as categories VI and VII. We also estimated IPL area based on available data, but emphasized that much of their extent has not been fully mapped nor recognized for its conservation benefits (Garnett et al., 2018). Additionally, the IPL dataset only covered land and therefore did not include seagrass ecosystems explicitly beyond the extent that ecosystems bordering terrestrial IPL areas were captured within the 1 km pixels of analysis. Coastal wetlands also lack data on the effectiveness of protection with IPLs, so we did not include IPL data as currently protected in our estimates.
We identified protected coastal wetland areas using the World Database on PAs (UNEP-WCMC & IUCN, 2024), which contains boundaries for each PA or MPA and additional information, including their establishment year and IUCN management category (Ia to VI, NAP, NR, and NAS). For each PA or MPA polygon, we extracted the coastal wetland area based on the datasets in section 1. Our spatial analysis required the center point of the pixel of each individual ecosystem under consideration to be covered by the PA or MPA polygon in order to be classified as protected, which is a relatively strict spatial extraction technique that likely leads to lower estimates of conservation compared to previous work with differing techniques (Dabalà et al., 2023).
We used the maps of IPLs from Garnett et al. (2018) to identify IPLs that were not inside of established PAs. We calculated the total coastal wetland area within IPLs (excluding PAs and MPAs) using the same coastal wetland data sources.
We aggregated coastal wetland loss rates by ecosystem type (mangroves, salt marshes, seagrasses). We used data on PA and MPA effectiveness to calculate the difference in coastal wetland loss rates attributable to protection (Equation S1). We compiled baseline estimates of current rates of coastal wetland degradation from all causes (%/yr)from existing literature as shown in the “Detailed coastal wetland loss data” tab of the Supporting Data spreadsheet and used in conjunction with estimates of reductions in loss, 53–59%, associated with protection.
Wetland lossavoided = Wetland lossbaseline ✕ Reduction in loss
We then used the ratio of coastal wetland loss in unprotected areas versus PAs to calculate avoided CO₂ emissions and additional carbon sequestration for each adoption unit. Specifically, we estimated the carbon benefits of avoided coastal wetland loss by multiplying avoided coastal wetland loss by avoided CO₂ emissions (30-yr time horizon; Equation S2) and carbon sequestration rates (30-yr time horizon; Equation S3) for each ecosystem type. Importantly, the emissions factors we used account for carbon in above- and below-ground biomass and generally do not assume 100% loss of carbon stocks because many land use impacts may retain some stored carbon, some of which is likely resistant to degradation (see the “2. current state effectiveness tab” in the spreadsheet for more information). We derived our estimates of retained carbon sequestration from global databases on sediment organic carbon burial rates in each ecosystem (see the “2. current state effectiveness tab” in the spreadsheet for more information).
Avoided emissions = Wetland lossavoided t=130(Emissions)
Sequestration = Wetland lossavoided t=130(Sequestration)
We then estimated effectiveness (Equation S4) as the avoided CO₂ emissions and the retained carbon sequestration capacity attributable to the reduction in wetland loss conferred by protection estimated in Equations S1–S3.
Effectiveness = (Wetland lossavoided) * (Carbonavoided emissions+ Carbonsequestration)
Finally, we calculated climate impact (Equation S5) by multiplying the adoption area under consideration by the estimated effectiveness from Equation S4.
Climate Impact = (Effectiveness) * (Adoption )
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The Protect Peatlands solution is defined as legally protecting peatland ecosystems through establishment of protected areas (PAs), which preserves stored carbon and ensures continued carbon sequestration by reducing degradation of the natural hydrology, soils, and/or vegetation. This solution focuses on non-coastal peatlands that have not yet been drained or otherwise severely degraded. Reducing emissions from degraded peatlands is addressed in the Restore Peatlands solution, and mangroves located on peat soils are addressed in the Protect Coastal Wetlands solution.
Peatlands are diverse ecosystems characterized by waterlogged, carbon-rich peat soils consisting of partially decomposed dead plant material (Figure 1). They are degraded or destroyed through clearing of vegetation and drainage for agriculture, forestry, peat extraction, or other development. An estimated 600 Gt carbon (~2,200 Gt CO₂‑eq ) is stored in peatlands, twice as much as the carbon stock in all forest biomass (Yu et al., 2010; Pan et al., 2024). Because decomposition occurs very slowly under waterlogged conditions, large amounts of plant material have accumulated in a partially decomposed state over millennia. These carbon-rich ecosystems occupy only 3–4% of land area (Xu et al., 2018b; United Nations Environment Programme [UNEP], 2022). Their protection is both feasible due to their small area and highly impactful due to their carbon density.
Figure 1. These photos show the diversity of peatlands that occur in different places, including a fen peatland and meadow complex in California (top left), a peat swamp in Indonesia (top right), a peat fen and forest in Canada (bottom left), and a peat bog in New Hampshire (bottom right).
Photo credits: Catie and Jim Bishop | U.S. Department of Agriculture; Rhett A. Butler; Garth Lenz; Linnea Hanson | U.S. Department of Agriculture
When peatlands are drained or disturbed, the rate of carbon loss increases sharply as the accumulated organic matter begins decomposing (Figure 2). Removal of overlying vegetation produces additional GHG emissions while also slowing or stopping carbon uptake. Whereas emissions from vegetation removal occur rapidly following disturbance, peat decomposition and associated emissions can continue for centuries depending on environmental conditions and peat thickness. Peat decomposition after disturbance occurs faster in warmer climates because cold temperatures slow microbial activity. In this analysis, we evaluated tropical, subtropical, temperate, and boreal regions separately.
Figure 2. Greenhouse gas emissions and sequestration in intact peatlands (left) and a drained peatland (right). Intact peatlands are a net greenhouse gas sink, sequestering carbon in peat through photosynthesis but also emitting methane due to waterlogged soils. Drained peatlands are a greenhouse gas source, producing emissions from peat decomposition and drainage canals. Modified from IUCN UK Peatland Programme (2024).
Source: IUCN UK Peatland Programme. (2024, July 10). New briefing addresses the peatlands and methane debate.
In addition to peat decomposition, biomass removal, and lost carbon sequestration, peatland disturbance impacts methane and nitrous oxide emissions and carbon loss through waterways (Figure 2; Intergovernmental Panel on Climate Change [IPCC], 2014; UNEP, 2022). Intact peatlands are a methane source because of methane-producing microbes, which thrive under waterlogged conditions. However, carbon uptake typically outweighs methane emissions. Leifield et al. (2019) found that intact peatlands are a net carbon sink of 0.77 ± 0.15 t CO₂‑eq /ha/yr in temperate and boreal regions and 1.65 ± 0.51 t CO₂‑eq /ha/yr in tropical regions after accounting for methane emissions. Peatland drainage reduces methane emissions from the peatland itself, but the drainage ditches can become potent methane sources (Evans et al., 2015; Peacock et al., 2021). Dissolved and particulate organic carbon also run off through drainage ditches, increasing CO₂ emissions in waterways from microbial activity and abiotic processes. Finally, rates of nitrous oxide emissions increase following drainage as the nitrogen stored in the peat becomes available to microbes.
Patterns of ongoing peatland drainage are poorly understood at the global scale, but rates of ecosystem disturbance are generally lower in PAs and on Indigenous peoples’ lands than outside of them (Li et al., 2024b; Wolf et al., 2021; Sze et al., 2021). The International Union for Conservation of Nature (IUCN) defines six levels of PAs that vary in their allowed uses, ranging from strict wilderness preserves to sustainable use areas that allow for some extraction of natural resources. All PA levels were included in this analysis (UNEP World Conservation Monitoring Center [UNEP-WCMC] and IUCN, 2024). Due to compounding uncertainties in the distributions of peatlands and Indigenous peoples’ lands, which have not yet been comprehensively mapped, and unknown rates of peatland degradation within Indigenous people’s lands, peatlands within Indigenous peoples’ lands were excluded from the tables but are discussed in the text (Garnett et al., 2018; UNEP-WCMC and IUCN, 2024).
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Avery Driscoll
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Daniel Jasper
Alex Sweeney
Aiyana Bodi
Hannah Henkin
Megan Matthews, Ph.D.
Ted Otte
Christina Swanson, Ph.D.
Paul C. West, Ph.D.
We estimated that protecting a ha of peatland avoids 0.92–13.47 t CO₂‑eq /ha/yr, with substantially higher emissions reductions in subtropical and tropical regions and lower emissions reductions in boreal regions (100-yr GWP; Table 1a–d; Appendix).
We estimated effectiveness as the avoided emissions attributable to the reduction in peatland loss conferred by protection (Equation 1). First, we calculated the biome-specific difference between the annual rate of peatland loss outside PAs (Peatland lossbaseline) versus inside PAs (Peatland lossprotected) (Appendix; Conchedda & Tubellio, 2020; Davidson et al., 2014; Miettinen et al., 2011; Miettinen et al., 2016; Uda et al., 2017, Wolf et al., 2021). We then multiplied the avoided peatland loss by the total emissions from one ha of drained peatland over 30 years. This is the sum of the total biomass carbon stock (Carbonbiomass), which degrades relatively quickly; 30 years of annual emissions from peat itself (Carbonflux); and 30 years of lost carbon sequestration potential, reflecting the carbon that would have been taken up by one ha of intact peatland in the absence of degradation (Carbonuptake) (IPCC 2014; UNEP, 2022). The carbon flux includes CO₂‑eq emissions from: 1) peat oxidation, 2) dissolved organic carbon loss through drainage, 3) the net change in on-field methane between undrained and drained states, 4) methane emissions from drainage ditches, and 5) on-field nitrous oxide emissions.
Equation 1.
Without rewetting, peat loss typically persists beyond 30 years and can continue for centuries (Leifield & Menichetti, 2018). Thus, this is a conservative estimate of peatland protection effectiveness that captures near-term impacts, aligns with the 30-yr cost amortization time frame, and is roughly consistent with commonly used 2050 targets. Using a longer time frame produces larger estimates of emissions from degraded peatlands and therefore higher effectiveness of peatland protection.
The effectiveness of peatland protection as defined here reflects only a small percentage of the carbon stored in peatlands because we account for the likelihood that the peatland would be destroyed without protection. Peatland protection is particularly impactful for peatlands at high risk of drainage.
Table 1. Effectiveness of peatland protection at avoiding emissions and sequestering carbon. Regional differences in values are driven by variation in emissions factors and baseline rates of peatland drainage.
Unit: t CO₂‑eq , 100-yr basis/ha of peatland protected/yr
| Estimate | 0.92 |
Unit: t CO₂‑eq , 100-yr basis/ha of peatland protected/yr
| Estimate | 4.42 |
Unit: t CO₂‑eq , 100-yr basis/ha of peatland protected/yr
| Estimate | 13.47 |
Unit: t CO₂‑eq , 100-yr basis/ha of peatland protected/yr
| Estimate | 13.23 |
We estimated that the net cost of peatland protection is approximately US$1.5/ha/yr, or $0.25/t CO₂‑eq avoided (Table 2). Data related to the costs of peatland protection are very limited. These estimates reflect global averages rather than regionally specific values, and rarely include data specific to peatlands. The costs of peatland protection include up-front costs of land acquisition and ongoing costs of management and enforcement. The market price of land reflects the opportunity cost of not using the land for other purposes, such as agriculture, forestry, peat extraction, or urban development. Protecting peatlands can also generate revenue through increased tourism. Costs and revenues are highly variable across regions, depending on the costs of land and enforcement and potential for tourism.
Dienerstein et al. (2024) estimated the initial cost of establishing a protected area for 60 high-biodiversity ecoregions. Amongst the 33 regions that were likely to contain peatlands, the median acquisition cost was US$957/ha, which we amortized over 30 years. Costs of protected area maintenance were estimated at US$9–17/ha/yr (Bruner et al., 2004; Waldron et al., 2020), though these estimates were not specific to peatlands. Additionally, these estimates reflect the costs of effective enforcement and management, but many existing protected areas lack adequate funds for effective enforcement (Adams et al., 2019; Barnes et al., 2018; Burner et al., 2004). Waldron et al. (2020) estimated that, across all ecosystems, tourism revenues directly attributable to protected area establishment were US$43/ha/yr, not including downstream revenues from industries that benefit from increased tourism. Inclusion of a tourism multiplier would substantially increase the estimated economic benefits of peatland protection.
Table 2. Cost per unit climate impact for peatland protection.
Unit: 2023 US$/t CO₂‑eq , 100-yr basis
| median | 0.25 |
A learning curve is defined here as falling costs with increased adoption. The costs of peatland protection do not fall with increasing adoption, so 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 gradual, emergency brake, or delayed.
Protect Peatlands 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.
Permanence, or the durability of stored carbon, is a caveat for emissions avoidance through peatland protection that is not addressed in this analysis. Protected peatlands could be drained if legal protections are reversed or inadequately enforced, resulting in the loss of stored carbon. Additionally, fires on peatlands have become more frequent due to climate change (Turetsky et al., 2015; Loisel et al., 2021), and can produce very large emissions pulses (Konecny et al., 2016; Nelson et al., 2021). In boreal regions, permafrost thaw can trigger large, sustained carbon losses from previously frozen peat (Hugelius et al., 2020; Jones et al., 2017). In tropical regions, climate change-induced changes in precipitation can lower water tables in intact peatlands, increasing risks of peat loss and reducing sequestration potential (Deshmukh et al., 2021).
Additionality, or the degree to which emissions reductions are above and beyond a baseline, is another important caveat for emissions avoidance through ecosystem protection (Atkinson & Alibašić, 2023; Fuller et al., 2020; Williams et al., 2023). In this analysis, additionality was addressed by using baseline rates of peatland degradation in calculating effectiveness. Evaluating additionality is challenging and remains an active area of research.
Finally, there are substantial uncertainties in the available data on peatland areas and distributions, peatland loss rates, the drivers of peatland loss, the extent and boundaries of PAs, and the efficacy of PAs at reducing peatland disturbance. Emissions dynamics on both intact and cleared peatlands are also uncertain, particularly under different land management practices and in the context of climate change.
Because peatlands are characterized by their soils rather than by overlying vegetation, they are difficult to map at the global scale (Minasny et al., 2024). Mapping peatlands remains an active area of research, and the adoption values presented here are uncertain. We estimated that 22.6 Mha of peatlands are located within strictly protected PAs (IUCN classes I or II), and 82.3 Mha are within other or unknown PA classes (Table 3a–e; UNEP, 2022; UNEP-WCMC & IUCN, 2024), representing 22% of total global peatland area (482 Mha). Because of data limitations, we did not include Indigenous peoples’ lands in subsequent analyses despite their conservation benefits. There are an additional 186 Mha of peatlands within Indigenous peoples’ lands that are not classified as PAs, with a large majority (155 Mha) located in boreal regions (Table 3; Garnett et al., 2018; UNEP, 2022).
Given the uncertainty in the global extent of peatlands, estimates of peatland protection vary. The Global Peatlands Assessment estimated that 19% (90.7 Mha) of peatlands are protected (UNEP, 2022), with large regional variations ranging from 35% of peatlands protected in Africa to only 10% in Asia. Using a peatland map from Melton et al. (2012), Austin et al. (2025) estimated that 17% of global peatlands are within PAs, and an additional 27% are located in Indigenous peoples’ lands (excluding Indigenous peoples’ lands in Canada covering large peatland areas).
Table 3. Current peatland area under protection by biome (circa 2023). Estimates are provided for two different forms of protection: “strict” protection, including IUCN classes I and II, and “nonstrict” protection, including all other IUCN classes. Regional values may not sum to global totals due to rounding.
Unit: Mha protected
| Area within strict PAs | 12.4 |
| Area within non-strict PAs | 41.7 |
Unit: Mha protected
| Area within strict PAs | 3.0 |
| Area within non-strict PAs | 10.1 |
Unit: Mha protected
| Area within strict PAs | 1.1 |
| Area within non-strict PAs | 1.6 |
Unit: Mha protected
| Area within strict PAs | 6.1 |
| Area within non-strict PAs | 28.9 |
Unit: Mha protected
| Area within strict PAs | 22.6 |
| Area within non-strict PAs | 82.3 |
We calculated the annual rate of new peatland protection based on the year of PA establishment for areas established in 2000–2020. The median annual increase in peatland protection was 0.86 Mha (mean 2.0 Mha; Table 4a–d). This represents a roughly 0.8%/yr increase in peatlands within PAs, or protection of an additional 0.2%/yr of total global peatlands. This suggests that peatland protection is likely occurring at a somewhat slower rate than peatland degradation – which is estimated to be around 0.5% annually at the global scale – though this estimate is highly uncertain and spatially variable (Davidson et al., 2014).
There were large year-to-year differences in how much new peatland area was protected over this period, ranging from only 0.2 Mha in 2016 to 7.9 Mha in 2007. The rate at which peatland protection is increasing has been decreasing, with a median increase of 1.7 Mha/yr between 2000 and 2010 declining to 0.7 Mha/yr during 2010–2020. Recent median adoption of peatland protection by area is highest in boreal (0.5 Mha/yr, Table 4a) and tropical regions (0.2 Mha/yr, Table 4d), followed by temperate regions (0.1 Mha/yr, Table 4b) and subtropical regions (0.01 Mha/yr, Table 4c) (2010–2020). Scaled by total peatland area, however, recent rates of peatland protection are lowest in the subtropics (0.04%/yr), followed by the boreal (0.14%/yr), the tropics (0.16%/yr), and temperate regions (0.19%/yr).
Table 4. Adoption trend for peatland protection in PAs of any IUCN class (2000–2020). The 25th and 75th percentiles reflect only interannual variance.
Unit: Mha of peatland protected/yr
| 25th percentile | 0.24 |
| mean | 0.87 |
| median (50th percentile) | 0.50 |
| 75th percentile | 0.89 |
Unit: Mha of peatland protected/yr
| 25th percentile | 0.07 |
| mean | 0.23 |
| median (50th percentile) | 0.10 |
| 75th percentile | 0.28 |
Unit: Mha of peatland protected/yr
| 25th percentile | 0.00 |
| mean | 0.04 |
| median (50th percentile) | 0.01 |
| 75th percentile | 0.04 |
Unit: Mha of peatland protected/yr
| 25th percentile | 0.05 |
| mean | 0.84 |
| median (50th percentile) | 0.25 |
| 75th percentile | 0.83 |
We considered the adoption ceiling to include all undrained, non-coastal peatlands and estimated this to be 425 Mha, based on the Global Peatlands Database and Global Peatlands Map (UNEP, 2022; Table 5e; Appendix). We estimated that 284 Mha of undrained peatlands remain in boreal regions (Table 5a), 26 Mha in temperate regions (Table 5b), 12 Mha in the subtropics (Table 5c), and 103 Mha in the tropics (Table 5d). The adoption ceiling represents the technical upper limit to adoption of this solution.
There is substantial uncertainty in the global extent of peatlands, which is not quantified in these adoption ceiling values. Estimates of global peatland extent from recent literature include 404 Mha (Melton et al., 2022), 423 Mha (Xu et al., 2018b), 437 Mha (Müller & Joos, 2021), 463 Mha (Leifield & Menichetti, 2018), and 488 Mha (UNEP, 2022). Several studies suggest that the global peatland area may still be underestimated (Minasny et al., 2024; UNEP, 2022).
Table 5. Adoption ceiling: upper limit for adoption of legal protection of peatlands by biome. Values may not sum to global totals due to rounding.
Unit: Mha protected
| Peatland area (Mha) | 284 |
Unit: Mha protected
| Peatland area (Mha) | 26 |
Unit: Mha protected
| Peatland area (Mha) | 12 |
Unit: Mha protected
| Peatland area (Mha) | 103 |
Unit: Mha protected
| Peatland area (Mha) | 425 |
UNEP (2022) places a high priority on protecting a large majority of remaining peatlands for both climate and conservation objectives. We defined the achievable range for peatland protection as 70% (low achievable) to 90% (high achievable) of remaining undrained peatlands. Only ~19% of peatlands are currently under formal protection within PAs (UNEP, 2022; UNEP-WCMC and IUCN, 2024). However, approximately 60% of undrained peatlands are under some form of protection if peatlands within Indigenous peoples’ lands are considered (Garnett et al., 2018; UNEP, 2022; UNEP-WCMC and IUCN, 2024). While ambitious, this provides support for our selected achievable range of 70–90% (Table 6a-e).
Ensuring effective and durable protection of these peatlands from drainage and degradation, including secure land tenure for Indigenous peoples who steward peatlands and other critical ecosystems, is a critical first step. Research suggests that local community leadership, equitable stakeholder engagement, and cross-scalar governance are needed to achieve conservation goals while also balancing social and economic outcomes through sustainable use (Atkinson & Alibašić, 2023; Cadillo & Bennett, 2024; Girkin et al., 2023; Harrison et al., 2019; Suwarno et al., 2015). Sustainable uses of peatlands include some forms of paludiculture, which can involve peatland plant cultivation, fishing, or gathering without disturbance of the hydrology or peat layer (Tan et al., 2021).
Table 6. Range of achievable adoption of peatland protection by biome.
Unit: Mha protected
| Current Adoption | 54 |
| Achievable – Low | 199 |
| Achievable – High | 255 |
| Adoption Ceiling | 284 |
Unit: Mha protected
| Current Adoption | 13 |
| Achievable – Low | 18 |
| Achievable – High | 24 |
| Adoption Ceiling | 26 |
Unit: Mha protected
| Current Adoption | 3 |
| Achievable – Low | 9 |
| Achievable – High | 11 |
| Adoption Ceiling | 12 |
Unit: Mha protected
| Current Adoption | 35 |
| Achievable – Low | 72 |
| Achievable – High | 92 |
| Adoption Ceiling | 103 |
Unit: Mha protected
| Current Adoption | 105 |
| Achievable – Low | 297 |
| Achievable – High | 382 |
| Adoption Ceiling | 425 |
We estimated that PAs currently reduce emissions from peatland degradation by 0.6 Gt CO₂‑eq/yr (Table 7a-e). Achievable levels of peatland protection have the potential to reduce emissions 1.3–1.7 Gt CO₂‑eq/yr, with a technical upper bound of 1.9 Gt CO₂‑eq/yr. The estimate of climate impacts under current adoption does not include the large areas of peatlands protected by Indigenous peoples but not legally recognized as PAs. Inclusion of these areas would increase the current estimated impact of peatland protection to 0.9 Gt CO₂‑eq/yr.
Other published estimates of additional emissions reductions through peatland protection are somewhat lower, with confidence intervals of 0–1.2 Gt CO₂‑eq/yr (Griscom et al., 2017; Humpenöder et al., 2020; Loisel et al., 2021; Strack et al., 2022). These studies vary in their underlying methodology and data, including the extent of peatland, the baseline rate of peatland loss, the potential for protected area expansion, which GHGs are considered, the time frame over which emissions are calculated, and whether they account for vegetation carbon loss or just emissions from the peat itself.
Table 7. Climate impact at different levels of adoption.
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current Adoption | 0.05 |
| Achievable – Low | 0.18 |
| Achievable – High | 0.24 |
| Adoption Ceiling | 0.26 |
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current Adoption | 0.06 |
| Achievable – Low | 0.08 |
| Achievable – High | 0.11 |
| Adoption Ceiling | 0.12 |
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current Adoption | 0.04 |
| Achievable – Low | 0.12 |
| Achievable – High | 0.15 |
| Adoption Ceiling | 0.17 |
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current Adoption | 0.46 |
| Achievable – Low | 0.95 |
| Achievable – High | 1.22 |
| Adoption Ceiling | 1.36 |
Unit: Gt CO₂ ‑eq/yr, 100-yr basis
| Current Adoption | 0.61 |
| Achievable – Low | 1.33 |
| Achievable – High | 1.71 |
| Adoption Ceiling | 1.90 |
Peatland protection can help communities adapt to extreme weather. Because peatlands regulate water flows, they can reduce the risk of droughts and floods (IUCN, 2021; Ritson et al., 2016). Evidence suggests that peatlands can provide a cooling effect to the immediate environment, lowering daytime temperatures and reducing temperature extremes between day and night (Dietrich & Behrendt, 2022; Helbig et al., 2020; Worrall et al., 2022).
When peatlands are drained they are susceptible to fire. Peatland fires can significantly contribute to air pollution because of the way these fires smolder (Uda et al., 2019). Smoke and pollutants, particularly PM2.5, from peatland fires can harm respiratory health and lead to premature mortality (Marlier et al., 2019). A study of peatland fires in Indonesia estimated they contribute to the premature mortality of about 33,100 adults and about 2,900 infants annually (Hein et al., 2022). Researchers have linked exposure to PM2.5 from peatland fires to increased hospitalizations, asthma, and lost workdays (Hein et al., 2022). Peatland protection mitigates exposure to air pollution and can save money from reduced health-care expenditures (Kiely et al., 2021).
Peatlands support the livelihoods of nearby communities, especially those in low- and middle-income countries. In the peatlands of the Amazon and Congo basins, fishing livelihoods depend on aquatic wildlife (Thornton et al., 2020). Peatlands in the Peruvian Amazon provide important goods for trade, such as palm fruit and timber, and are used for hunting by nearby populations (Schulz et al., 2019). Peatlands can also support the livelihoods of women and contribute to gender equality. For example, raw materials – purun – from Indonesian peatlands are used by women to create and sell mats used in significant events such as births, weddings, and burials (Goib et al., 2018).
Peatlands are home to a wide range of species, supporting biodiversity of flora and an abundance of wildlife (UNEP, 2022; Minayeva et al., 2017; Posa et al., 2011). Because of their unique ecosystem, peatlands provide a habitat for many rare and threatened species (Posa et al., 2011). A study of Indonesian peat swamps found that the IUCN Red List classified approximately 45% of mammals and 33% of birds living in these ecosystems as threatened, vulnerable, or endangered (Posa et al., 2011). Peatlands also support a variety of insect species (Spitzer & Danks, 2006). Because of their sensitivity to environmental changes, some peatland insects can act as indicators of peatland health and play a role in conservation efforts (Spitzer & Danks, 2006).
Peatlands can filter water pollutants and improve water quality and are important sources of potable water for some populations (Minayeva et al., 2017). Xu et al. (2018a) estimated that peatlands store about 10% of freshwater globally, not including glacial water. Peatlands are a significant drinking water source for people in the United Kingdom and Ireland, where they provide potable water for about 71.4 million people (Xu et al., 2018a).
Leakage occurs when peatland drainage and clearing moves outside of protected area boundaries and is a risk of relying on peatland protection as an emissions reduction strategy (Harrison & Paoli, 2012; Strack et al., 2022). If the relocated clearing also occurs on peat soils, emissions from peatland drainage and degradation are relocated but not actually reduced. If disturbance is relocated to mineral soils, however, the disturbance-related emissions will typically be lower. Combining peatland protection with policies to reduce incentives for peatland clearing can help avoid leakage.
Peatland protection must be driven by or conducted in close collaboration with local communities, which often depend on peatlands for their livelihoods and economic advancement (Jalilov et al., 2025; Li et al., 2024a; Suwarno et al., 2016). Failure to include local communities in conservation efforts violates community sovereignty and can exacerbate existing socioeconomic inequities (Felipe Cadillo & Bennet, 2024; Thorburn & Kull, 2015). Effective peatland protection requires development of alternative income opportunities for communities currently dependent on peatland drainage, such as tourism; sustainable peatland use practices like paludiculture; or compensation for ecosystem service provisioning, including carbon storage (Evers et al., 2017; Girkin et al., 2023; Suwarno et al., 2016; Syahza et al., 2020; Tan et al., 2021; Uda et al., 2017).
Protected areas often include multiple ecosystems. Peatland protection will likely lead to protection of other ecosystems within the same areas, and the health of nearby ecosystems is improved by the services provided by intact peatlands.
Restored peatlands need protection to reduce the risk of future disturbance, and the health of protected peatlands can be improved through restoration of adjacent degraded peatlands.
Reducing food loss and waste and improving diets reduce demand for agricultural land. These solutions reduce pressure to convert peatlands to agriculture use, easing expansion of protected areas.
None
ha protected
CO₂ , CH₄, N₂O
ha protected
CO₂ , CH₄, N₂O
ha protected
CO₂ , CH₄, N₂O
ha protected
CO₂ , CH₄, N₂O
None
There is high scientific consensus that protecting peatland carbon stocks is a critical component of mitigating climate change (Girkin & Davidson, 2024; Harris et al., 2022; Leifield et al., 2019; Noon et al., 2022; Strack et al., 2022). Globally, an estimated 11–12% of peatlands have been drained for uses such as agriculture, forestry, and harvesting of peat for horticulture and fuel, with much more extensive degradation in temperate and tropical regions (~45%) than in boreal regions (~4%) (Fluet-Chouinard et al., 2023; Leifield & Menichetti, 2018; UNEP, 2022). Rates of peatland degradation are highly uncertain, and the effectiveness of PAs at reducing drainage remains unquantified. In lieu of peatland-specific data on the effectiveness of PAs at reducing drainage, we used estimates from Wolf et al. (2021), who found that PAs reduce forest loss by approximately 40.5% at the global average.
Carbon stored in peatlands has been characterized as “irrecoverable carbon” because it takes centuries to millennia to accumulate and could not be rapidly recovered if lost (Goldstein et al., 2020; Noon et al., 2021). Degraded peatlands currently emit an estimated 1.3–1.9 Gt CO₂‑eq/yr (excluding fires), equal to ~2–4% of total global emissions (Leifield and Menichetti., 2018; UNEP, 2022). Leifield et al. (2019) projected that without protection or restoration measures, emissions from drained peatlands could produce enough emissions to consume 10–41% of the remaining emissions budget for keeping warming below 1.5–2.0 °C. Peatland drainage had produced a cumulative 80 Gt CO₂‑eq by 2015, equal to nearly two years worth of total global emissions. In a modeling study, Humpenöder et al. (2020) projected that an additional 10.3 Mha of peatlands would be degraded by 2100 in the absence of new protection efforts, increasing annual emissions from degraded peatlands by ~25% (an additional 0.42 Gt CO₂‑eq/yr in their study).
The results presented in this document synthesize findings from 11 global datasets, supplemented by four regional studies on peatland loss rates in Southeast Asia. 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.
This analysis quantifies the emissions associated with peatland degradation and their potential reduction via establishment of Protected Areas (PAs). We leveraged multiple data products, including national-scale peatland area estimates, a peatland distribution map, shapefiles of PAs and Indigenous peoples’ lands, available data on rates of peatland degradation by driver, country-scale data on reductions in ecosystem degradation inside of PAs, maps of biomass carbon stocks, and biome-level emissions factors from disturbed peat soils. This appendix describes the source data products and how they were integrated.
The global extent and distribution of peatlands is highly uncertain, and all existing peatland maps have limitations. Importantly, there is no globally accepted definition of a peatland, and different countries and data products use variable thresholds for peat depth and carbon content to define peatlands. The Global Peatland Assessment was a recent comprehensive effort to compile and harmonize existing global peatland area estimates (UNEP, 2022). We rely heavily on two products resulting from this effort: a national-scale dataset of peatland area titled the Global Peatland Database (GPD) and a map of likely peatland areas titled the Global Peatlands Map (GPM; 1 km resolution).
The GPM represents a known overestimate of the global peatland area, so we scaled area estimates derived from spatially explicit analyses dependent on the GPM to match total areas from the GPD. To develop a map of country-level scaling factors, we first calculated the peatland area within each country from the GPM. We calculated the country-level scaling factors as the country-level GPD values divided by the associated GPM values and converted them to a global raster. Some countries had peatland areas represented in either the GPD or GPM, but not both. Four countries had peatland areas in the GPM that were not present in the GPD, which contained 0.51 Mha of peatlands per the GPM. These areas were left unscaled. There were 38 countries with peatland areas in the GPD that did not have areas in the GPM, containing a total 0.70 Mha of peatlands. These areas, which represented 0.14% of the total peatland area in the GPD, were excluded from the scaled maps. We then multiplied the pixel-level GPM values by the scalar raster. Because of the missing countries, this scaling step very slightly overestimated (by 0.4%) total peatlands relative to the GPD. To account for this, we multiplied this intermediate map by a final global scalar (calculated as the global GPM total divided by the GPD total). This process produced a map with the same peatland distribution as the GPM but a total area that summed to that reported in the GPD.
Many coastal wetlands have peat soils, though the extent of this overlap has not been well quantified. Coastal wetlands are handled in the Protect Coastal Wetlands solution, so we excluded them from this solution to avoid double-counting. Because of the large uncertainties in both the peatland maps and available maps of coastal wetlands, we were not confident that the overlap between the two sets of maps provided a reliable estimate of the proportion of coastal wetlands located on peat soils. Therefore, we took the conservative approach of excluding all peatland pixels that were touching or overlapping with the coastline. This reduced the total peatland area considered in this solution by 5.33 Mha (1.1%). We additionally excluded degraded peatlands from the adoption ceiling and achievable range using country-level data from the GPD. Degraded peatlands will continue to be emissions sources until they are restored, so protection alone will not confer an emissions benefit.
We conducted the analyses by latitude bands (tropical: –23.4° to 23.4°; subtropical: –35° to –23.4° and 23.4° to 35°; temperate: –35° to –50° and 35° to 50°; boreal: <–50° and >50°) in order to retain some spatial variability in emissions factors and degradation rates and drivers. We calculated the total peatland area within each latitude band based on both the scaled and unscaled peatland maps with coastal pixels excluded. We used these values as the adoption ceiling and for subsequent calculations of protected areas.
We identified protected peatland areas using the World Database on Protected Areas (WDPA, 2024), which contains boundaries for each PA and additional information, including their establishment year and IUCN management category (Ia to VI, not applicable, not reported, and not assigned). For each PA polygon, we extracted the peatland area from the unscaled version of the GPM with coastal pixels removed.
Each PA was classified into climate zones (described above) based on the midpoint between its minimum and maximum latitude. Then, protected peatland areas were summed to the IUCN class-climate zone level, and the proportion of peatlands protected within each was calculated by dividing the protected area by the unscaled total area in each climate zone. The proportion of area protected was then multiplied by the scaled total area for each zone to calculate adoption in hectares within each IUCN class and climate zone. To evaluate trends in adoption over time, we aggregated protected areas by establishment year as reported in the WDPA. We used the same procedure to calculate the proportion of area protected using the unscaled maps, and then scale for the total area by biome.
We used the maps of Indigenous people’s lands from Garnett et al. 2018 to identify Indigenous people’s lands that were not inside of established PAs. The total peatland area within Indigenous people’s lands process as above.
Broadly, we estimated annual, per-ha emissions savings from peatland protection as the difference between net carbon exchange in a protected peatland versus an unprotected peatland, accounting for all emissions pathways, the drivers of disturbance, the baseline rates of peatland disturbance, and the effectiveness of PAs at reducing ecosystem degradation. In brief, our calculation of the effectiveness of peatland protection followed Equation S1, in which the annual peatland loss avoided due to protection (%/yr) is multiplied by the 30-yr cumulative sum of emissions per ha of degraded peatland (CO₂‑eq /ha over a 30-yr period). These two terms are described in depth in the subsequent sections.
Equation S1. Effectiveness= Peatland lossavoided t=130(Emissions)
We calculated the avoided rate of peatland loss (%/yr) as the difference between the baseline rate of peatland loss without protection and the estimated rate of peatland loss within PAs (Equation S2), since PAs do not confer complete protection from ecosystem degradation.
Equation S2. Peatland lossavoided =Peatland lossbaseline ✕ Reduction in loss
We compiled baseline estimates of the current rates of peatland degradation from all causes (%/yr) from the existing literature (Table S1). Unfortunately, data on the rate of peatland loss within PAs are not available. However, satellite data have enabled in-depth, global-scale studies of the effectiveness of PAs at reducing tree cover loss. While not all peatlands are forested and degradation dynamics on peatlands can differ from those on forests writ large, these estimates are a reasonable approximation of the effectiveness of PAs at reducing peatland loss. We used the country-level estimates of the proportionate reduction in loss inside versus outside of PAs from Wolf et al. (2021), which we aggregated to latitude bands based on the median latitude of each country (Table S1).
Table S1. Biome-level annual baseline rate of peatland loss, the effectiveness of protection at reducing loss, and the annual avoided rate of peatland loss under protection.
| Climate Zone | Mean Annual Peatland Loss (%/yr) | Proportionate Reduction in Loss Under Protection | Avoided Loss Under Protection (%/yr) |
|---|---|---|---|
| Boreal | 0.3% | 0.44 | 0.13% |
| Subtropic | 1.2% | 0.60 | 0.73% |
| Temperate | 0.6% | 0.56 | 0.33% |
| Tropic | 1.5% | 0.41 | 0.63% |
Emissions Factors for Peatland Degradation
Equation S3 provides an overview of the calculation of emissions from degraded peatlands. In brief, we calculated cumulative emissions as the biomass carbon stock plus the 30-yr total of CO₂‑equivalent fluxes from peat oxidation (Pox), dissolved organic carbon losses (DOC), methane from drainage ditches (Mditch), on-field methane (Mfield), on-field nitrous oxide (N) and the lost net sequestration from an intact peatland, accounting for carbon sequestration in peat and methane emissions from intact peatlands (Seqloss).
Equation S3. t=130(Emissions)=Biomass+t=130(Pox+DOC+Mditch+Mfield+N+Seqloss)
The IPCC Tier 1 emissions factors for peatland degradation are disaggregated by climate zone (tropical, temperate, and boreal), soil fertility status (nutrient-poor versus nutrient rich), and the driver of degradation (many subclasses of forestry, cropland, grassland, and peat extraction) (IPCC 2014; Tables 2.1–2.5). Table III.5 of Annex III of the Global Peatlands Assessment provides a summarized set of emissions factors based directly on the IPCC values but aggregated to the four coarser classes of degradation drivers listed above (UNEP, 2022), which we use for our analysis. They include the following pathways: CO₂ from peat oxidation, off-site emissions from lateral transport of dissolved organic carbon (DOC), methane emissions from the field and drainage ditches, and nitrous oxide emissions from the field. Particulate organic carbon (POC) losses may be substantial, but were not included in the IPCC methodology due to uncertainties about the fate of transported POC. These emissions factors are reported as annual rates per disturbed hectare, and emissions from these pathways continue over long periods of time.
Three additional pathways that are not included in the IPCC protocol are relevant to the emissions accounting for this analysis: the loss of carbon sequestration potential from leaving the peatland intact, the methane emissions that occur from intact peatlands, and the emissions from removal of the vegetation overlying peat soils. Leifield et al. (2019) reported the annual net carbon uptake per hectare of intact peatlands, including sequestration of carbon in peat minus naturally occurring methane emissions due to the anoxic conditions. If the peatland is not disturbed, these methane emissions and carbon sequestration will persist indefinitely on an annual basis.
We accounted for emissions from removal of biomass using a separate protocol than emissions occurring from the peat soil due to differences in the temporal dynamics of loss. While all other emissions from peat occur on an annual basis and continue for many decades or longer, emissions from biomass occur relatively quickly. Biomass clearing produces a rapid pulse of emissions from labile carbon pools followed by a declining, but persistent, rate of emissions as more recalcitrant carbon pools decay over subsequent years. The entire biomass carbon stock is likely to be lost within 30 years. Average biomass carbon stocks over the extent of the peatland distribution in the GPM were calculated by latitude band based on the above and below ground biomass carbon stock data from Spawn et al. (2020). We presumed 100% of the biomass carbon stock is lost from peatland degradation, though in many cases some amount of biomass remains following degradation, depending on the terminal land use.
Peatland Degradation Drivers
Emissions from peatland loss depend on the driver of degradation (e.g., forestry, cropland, peat extraction; IPCC 2014). The GPD contains national-scale estimates of historical peatland loss by driver, which we used to calculate weights for each driver, reflecting the proportion of peatland loss attributable to each driver by latitude band. We took the weighted average of the driver-specific peatland emissions factors, calculated as the sum of the products of the weights and the driver-specific emissions factors.
Appendix References
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Equation X.
Equation Y.
Equation Z.
We define the Protect Forests solution as the long-term protection of tree-dominated ecosystems through establishment of protected areas (PAs), managed with the primary goal of conserving nature, and land tenure for Indigenous peoples. These protections reduce forest degradation, avoiding GHG emissions and ensuring continued carbon sequestration by healthy forests. This solution addresses protection of forests on mineral soils. The Protect Peatlands and Protect Coastal Wetlands solutions address protection of forested peatlands and mangrove forests, respectively, and the Restore Forests solution addresses restoring degraded forests.
Forests store carbon in biomass and soils and serve as carbon sinks, taking up an estimated 12.8 Gt CO₂‑eq/yr (including mangroves and forested peatlands; Pan et al., 2024). Carbon stored in forests is released into the atmosphere through deforestation and degradation, which refer to forest clearing or reductions in ecosystem integrity from human influence (DellaSala et al., 2025). Humans cleared an average of 0.4% (16.3 Mha) of global forest area annually from 2001–2019 (excluding wildfire but including mangroves and forested peatlands; Hansen et al., 2013). This produced a gross flux of 7.4 Gt CO₂‑eq/yr (Harris et al., 2021), equivalent to ~14% of total global GHG emissions over that period (Dhakal et al., 2022). Different forest types store varying amounts of carbon and experience different rates of clearing; in this analysis, we individually evaluate forest protection in boreal, temperate, subtropical, and tropical regions. We included woodlands in our definition of forests because they are not differentiated in the satellite-based data used in this analysis.
We consider forests to be protected if they 1) are formally designated as PAs (UNEP-WCMC and IUCN, 2024), or 2) are mapped as Indigenous peoples’ lands in the global study by Garnett et al. (2018). The International Union for Conservation of Nature defines PAs as areas managed primarily for the long-term conservation of nature and ecosystem services. They are disaggregated into six levels of protection, ranging from strict wilderness preserves to sustainable-use areas that allow for some natural resource extraction, including logging. We included all levels of protection in this analysis, primarily because not all PAs have been classified into these categories. We rely on existing maps of Indigenous peoples’ lands but emphasize that much of their extent has not been fully mapped nor recognized for its conservation benefits (Garnett et al., 2018). Innovative and equity-driven strategies for forest protection that recognize the land rights, sovereignty, and stewardship of Indigenous peoples and local communities are critical for achieving just and effective forest protection globally (Dawson et al., 2024; Fa et al., 2020; FAO, 2024; Garnett et al., 2018; Tran et al., 2020; Zafra-Calvo et al., 2017).
Indigenous peoples’ lands and PAs reduce, but do not eliminate, forest clearing relative to unprotected areas (Baragwanath et al., 2020; Blackman & Viet 2018; Li et al., 2024; McNicol et al., 2023; Sze et al. 2022; Wolf et al., 2023; Wade et al., 2020). We rely on estimates of how effective PA are currently for this analysis but highlight that improving management to further reduce land use change within PAs is a critical component of forest protection (Jones et al., 2018; Meng et al., 2023; Vijay et al., 2018; Visconti et al., 2019; Watson et al., 2014).
Market-based strategies and other policies can complement legal protections by increasing the value of intact forests and reducing incentives for clearing (e.g., Garett et al., 2019; Golub et al., 2021; Heilmayr et al., 2020; Lambin et al., 2018; Levy et al., 2023; Macdonald et al., 2024; Marin et al., 2022; Villoria et al., 2022; West et al., 2023). The estimates in this report are based on legal protection alone because the effectiveness of market-based strategies is difficult to quantify, but strategies such as sustainable commodities programs, reducing or redirecting agricultural subsidies, and strategic infrastructure planning will be further discussed in a future update.
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Avery Driscoll
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Hannah Henkin
Megan Matthews, Ph.D.
Ted Otte
Christina Swanson, Ph.D.
Paul C. West, Ph.D.
We estimated that one ha of forest protection provides total carbon benefits of 0.299–2.204 t CO₂‑eq/yr depending on the biome (Table 1a–d; Appendix). This effectiveness estimate includes avoided emissions and preserved sequestration capacity attributable to the reduction in forest loss conferred by protection (Equation 1). First, we calculated the difference between the rate of human-caused forest loss outside of PAs (Forest lossbaseline) and the rate inside of PAs (Forest lossprotected). We then multiplied the annual rate of avoided forest loss by the sum of the carbon stored in one hectare of forest (Carbonstock) and the amount of carbon that one hectare of intact forest takes up over a 30-yr timeframe (Carbonsequestration).
Equation 1.
Each of these factors varies across biomes. Based on our definition, for instance, the effectiveness of forest protection in boreal forests is lower than that in tropical and subtropical forests primarily because the former face lower rates of human-caused forest loss (though greater wildfire impacts). Importantly, the effectiveness of forest protection as defined here reflects only a small percentage of the carbon stored (394 t CO₂‑eq ) and absorbed (4.25 t CO₂‑eq/yr ) per hectare of forest (Harris et al., 2021). This is because humans clear ~0.4% of forest area annually, and forest protection is estimated to reduce human-caused forest loss by an average of 40.5% (Curtis et al., 2018; Wolf et al., 2023).
Table 1. Effectiveness at reducing emissions and sequestering carbon, with carbon sequestration calculated over a 30-yr timeframe. Differences in values between biomes are driven by variation in forest carbon stocks and sequestration rates, baseline rates of forest loss, and effectiveness of PAs at reducing forest loss. See the Appendix for source data and calculation details. Emissions and sequestration values may not sum to total effectiveness due to rounding.
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| Avoided emissions | 0.207 |
| Sequestration | 0.091 |
| Total effectiveness | 0.299 |
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| Avoided emissions | 0.832 |
| Sequestration | 0.572 |
| Total effectiveness | 1.403 |
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| Avoided emissions | 1.860 |
| Sequestration | 0.344 |
| Total effectiveness | 2.204 |
Unit: t CO₂‑eq/ha/yr, 100-yr basis
| Avoided emissions | 1.190 |
| Sequestration | 0.300 |
| Total effectiveness | 1.489 |
We estimated that forest protection costs approximately US$2/t CO₂‑eq (Table 2). Data related to the costs of forest protection are limited, and these estimates are uncertain. The costs of forest protection include up-front costs of land acquisition and ongoing costs of management and enforcement. The market price of land reflects the opportunity cost of not using the land for other purposes (e.g., agriculture or logging). Protecting forests also generates revenue, notably through increased tourism. Costs and revenues vary across regions, depending on the costs of land and enforcement and potential for tourism.
The cost of land acquisition for ecosystem protection was estimated by Dienerstein et al. (2024), who found a median cost of US$988/ha (range: US$59–6,616/ha), which we amortized over 30 years. Costs of PA maintenance were estimated at US$9–17/ha/yr (Bruner et al., 2004; Waldron et al., 2020). These estimates reflect the costs of effective enforcement and management, but many existing PAs do not have adequate funds for effective enforcement (Adams et al., 2019; Barnes et al., 2018; Burner et al., 2004). Tourism revenues directly attributable to forest protection were estimated to be US$43/ha/yr (Waldron et al., 2020), not including downstream revenues from industries that benefit from increased tourism. Inclusion of a tourism multiplier would substantially increase the estimated economic benefits of forest protection.
Table 2. Cost per unit of climate impact.
Unit: 2023 US$/t CO₂‑eq, 100-yr basis
| median | 2 |
A learning curve is defined here as falling costs with increased adoption. The costs of forest protection do not fall with increasing adoption, so 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.
Protect Forests 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.
Additionality, or the degree to which emissions reductions are above and beyond a baseline, is a key caveat for emissions avoided through forest protection (e.g., Fuller et al., 2020; Ruseva et al., 2017). Emissions avoided via forest protection are only considered additional if that forest would have been cleared or degraded without protection (Delacote et al., 2022; Delacote et al., 2024; Gallemore et al., 2020). In this analysis, additionality is addressed by using baseline rates of forest loss outside of PAs in the effectiveness calculation. Additionality is particularly important when forest protection is used to generate carbon offsets. However, the likelihood of forest removal in the absence of protection is often difficult to determine at the local level.
Permanence, or the durability of stored carbon over long timescales, is another important consideration not directly addressed in this solution. Carbon stored in forests can be compromised by natural factors, like drought, heat, flooding, wildfire, pests, and diseases, which are further exacerbated by climate change (Anderegg et al., 2020; Dye et al., 2024). Forest losses via wildfire in particular can create very large pulses of emissions (e.g., Kolden et al. 2024; Phillips et al. 2022) that negate accumulated carbon benefits of forest protection. Reversal of legal protections, illegal forest clearing, biodiversity loss, edge effects from roads, and disturbance from permitted uses can also cause forest losses directly or reduce ecosystem integrity, further increasing vulnerability to other stressors (McCallister et al., 2022).
We estimated that approximately 1,673 Mha of forests are currently recognized as PAs or Indigenous peoples’ lands (Table 3e; Garnett et al., 2018; UNEP-WCMC and IUCN, 2024). Using two different maps of global forests that differ in their methodologies and definitions (ESA CCI, 2019; Hansen et al., 2013), we found an upper-end estimate of 1,943 Mha protected and a lower-end estimate of 1,404 Mha protected. These two maps classify forests using different thresholds for canopy cover and vegetation height, different satellite data, and different classification algorithms (see the Appendix for details).
Based on our calculations, tropical forests make up the majority of forested PAs, with approximately 936 Mha under protection (Table 3d), followed by boreal forests (467 Mha, Table 3a), temperate forests (159 Mha, Table 3b), and subtropical forests (112 Mha, Table 3c). We estimate that 49% of all forests have some legal protection, though only 7% of forests are under strict protection (IUCN class I or II), with the remaining area protected under other IUCN levels, as OECMs, or as Indigenous peoples’ lands.
Table 3. Current (circa 2023) forest and woodland area under legal protection by biome (Mha). The low and high values are calculated using two different maps of global forest cover that differ in methodology for defining a forest (ESA CCI, 2019; Hansen et al., 2013). Biome-level values may not sum to global totals due to rounding.
Unit: Mha
| low | 313 |
| mean | 467 |
| high | 621 |
Unit: Mha
| low | 135 |
| mean | 159 |
| high | 183 |
Unit: Mha
| low | 85 |
| mean | 112 |
| high | 138 |
Unit: Mha
| low | 872 |
| mean | 936 |
| high | 1,000 |
Unit: Mha
| low | 1,404 |
| mean | 1,673 |
| high | 1,943 |
We calculated the rate of PA expansion based on the year the PA was established. We do not have data on the expansion rate of Indigenous peoples’ lands, so the calculated adoption trend reflects only PAs. An average of 19 Mha of additional forests were protected each year between 2000 and 2020 (Table 4a–e; Figure 1), representing a roughly 2% increase in PAs per year (excluding Indigenous peoples’ lands that are not located in PAs). There were large year-to-year differences in how much new forest area was protected over this period, ranging from only 6.4 Mha in 2020 to over 38 Mha in both 2000 and 2006. Generally, the rate at which forest protection is increasing has been decreasing, with an average increase of 27 Mha/yr between 2000–2010 declining to 11 Mha/yr between 2010–2020. Recent rates of forest protection (2010–2020) are highest in the tropics (5.6 Mha/yr), followed by temperate regions (2.4 Mha/yr) and the boreal (2.0 Mha/yr), and lowest in the subtropics (0.7 Mha/yr).
Figure 1. Trend in forest protection by climate zone. These values reflect only the area located within PAs; Indigenous peoples’ lands, which were not included in the calculation of the adoption trend, are excluded.
Table 4. 2000–2020 adoption trend.
Unit: Mha protected/yr
| 25th percentile | 1.3 |
| mean | 2.8 |
| median (50th percentile) | 2.0 |
| 75th percentile | 3.4 |
Unit: Mha protected/yr
| 25th percentile | 1.9 |
| mean | 2.8 |
| median (50th percentile) | 2.5 |
| 75th percentile | 3.1 |
Unit: Mha protected/yr
| 25th percentile | 0.5 |
| mean | 1.0 |
| median (50th percentile) | 0.7 |
| 75th percentile | 1.1 |
Unit: Mha protected/yr
| 25th percentile | 5.4 |
| mean | 12.5 |
| median (50th percentile) | 7.7 |
| 75th percentile | 17.8 |
Unit: Mha protected/yr
| 25th percentile | 9.1 |
| mean | 19.0 |
| median (50th percentile) | 12.9 |
| 75th percentile | 25.4 |
We estimated an adoption ceiling of 3,370 Mha of forests globally (Table 5e), defined as all existing forest areas, excluding peatlands and mangroves. Of the calculated adoption ceiling, 469 Mha of boreal forests (Table 5a), 282 Mha of temperate forests (Table 5b), 211 Mha of subtropical forests (Table 5c), and 734 Mha of tropical forests (Table 5d) are currently unprotected. The high and low values represent estimates of currently forested areas from two different maps of forest cover that use different methodologies and definitions (ESA CCI, 2019; Hansen et al., 2013). While it is not socially, politically, or economically realistic that all existing forests could be protected, these values represent the technical upper limit to adoption of this solution. Additionally, some PAs allow for ongoing sustainable use of resources, enabling some demand for wood products to be met via sustainable use of trees in PAs.
Table 5. Adoption ceiling.
Unit: Mha protected
| low | 686 |
| mean | 936 |
| high | 1,186 |
Unit: Mha protected
| low | 385 |
| mean | 441 |
| high | 498 |
Unit: Mha protected
| low | 260 |
| mean | 323 |
| high | 385 |
Unit: Mha protected
| low | 1,557 |
| mean | 1,669 |
| high | 1,782 |
Unit: Mha protected
| low | 2,889 |
| mean | 3,370 |
| high | 3,851 |
We defined the lower end of the achievable range for forest protection as all high integrity forests in addition to forests in existing PAs and Indigenous peoples’ lands, totaling 2,297 Mha (Table 6a–e). We estimated that there are 624 Mha of unprotected high integrity forests, based on maps of forest integrity developed by Grantham et al. (2020). High integrity forests have experienced little disturbance from human pressures (i.e., logging, agriculture, and buildings), are located further away from areas of human disturbance, and are well-connected to other forests. High integrity forests are a top priority for protection as they have particularly high value with respect to biodiversity and ecosystem service provisioning. These forests are also not currently being used to meet human demand for land or forest-derived products, and thus their protection may be more feasible.
To estimate the upper end of the achievable range, we excluded the global areas of planted trees and tree crops from the adoption ceiling (Richter et al., 2024), comprising approximately 335 Mha globally (Table 6a–e). Planted trees include tree stands established for crops such as oil palm, products such as timber and fiber production, and those established as windbreaks or for ecosystem services such as erosion control. These stands are often actively managed and are unlikely to be protected.
Table 6. Range of achievable adoption levels.
Unit: Mha protected
| Current Adoption | 467 |
| Achievable – Low | 847 |
| Achievable – High | 861 |
| Adoption ceiling | 936 |
Unit: Mha protected
| Current Adoption | 159 |
| Achievable – Low | 204 |
| Achievable – High | 378 |
| Adoption ceiling | 441 |
Unit: Mha protected
| Current Adoption | 112 |
| Achievable – Low | 126 |
| Achievable – High | 219 |
| Adoption ceiling | 323 |
Unit: Mha protected
| Current Adoption | 936 |
| Achievable – Low | 1,120 |
| Achievable – High | 1,577 |
| Adoption ceiling | 1,669 |
Unit: Mha protected
| Current Adoption | 1,673 |
| Achievable – Low | 2,297 |
| Achievable – High | 3,035 |
| Adoption ceiling | 3,370 |
We estimated that forest protection currently avoids approximately 2.00 Gt CO₂‑eq/yr, with potential impacts of 2.49 Gt CO₂‑eq/yr at the low-achievable scenario, 3.62 Gt CO₂‑eq/yr at the high-achievable scenario, and 4.10 Gt CO₂‑eq/yr at the adoption ceiling (Table 7a–e). Although not directly comparable due to the inclusion of different land covers, these values are aligned with Griscom et al. (2017) estimates that forest protection could avoid 3.6 Gt CO₂‑eq/yr and the IPCC estimate that protection of all ecosystems could avoid 6.2 Gt CO₂‑eq/yr (Nabuurs et al., 2022).
Note that the four adoption scenarios vary only with respect to the area under protection. Increases in either the rate of forest loss that would have occurred if the area had not been protected or in the effectiveness of PAs at avoiding forest loss would substantially increase the climate impacts of forest protection. For instance, a hypothetical 50% increase in the rate of forest loss outside of PAs would increase the carbon impacts of the current adoption, low achievable, high achievable, and adoption ceiling scenarios to 3.0, 3.7, 5.4, and 6.1 Gt CO₂‑eq/yr, respectively. Similarly, if legal forest protection reduced forest loss twice as much as it currently does, the climate impacts of the four scenarios would increase to 3.9, 4.8, 7.0, and 7.8 Gt CO₂‑eq/yr, respectively.
Table 7. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Boreal | 0.14 |
| Achievable – Low | 0.25 |
| Achievable – High | 0.26 |
| Adoption ceiling | 0.28 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.22 |
| Achievable – Low | 0.29 |
| Achievable – High | 0.53 |
| Adoption ceiling | 0.62 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.25 |
| Achievable – Low | 0.28 |
| Achievable – High | 0.48 |
| Adoption ceiling | 0.71 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 1.39 |
| Achievable – Low | 1.67 |
| Achievable – High | 2.35 |
| Adoption ceiling | 2.49 |
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 2.00 |
| Achievable – Low | 2.49 |
| Achievable – High | 3.62 |
| Adoption ceiling | 4.10 |
Protected forests are more biodiverse and therefore more resilient and adaptable, providing higher-quality ecosystem services to surrounding communities (Gray et al., 2016). Protected forests can also buffer surrounding areas from the effects of extreme weather events. By increasing plant species richness, forest preservation can contribute to drought and fire tolerance (Buotte et al., 2020). Forests help regulate local climate by reducing temperature extremes (Lawrence et al., 2022). Studies have shown that the extent of forest coverage helps to alleviate vulnerability associated with heat effects (Walton et al., 2016). Tropical deforestation threatens human well-being by removing critical local cooling effects provided by tropical forests, exacerbating extreme heat conditions in already vulnerable regions (Seymour et al., 2022).
Protecting forests in predominantly natural areas can improve food security by supporting crop pollination of nearby agriculture. Sarira et al. (2022) found that protecting 58% of threatened forests in Southeast Asia could support the dietary needs of about 305,000–342,000 people annually. Forests also provide a key source of income and livelihoods for subsistence households and individuals (de Souza et al., 2016; Herrera et al., 2017; Naidoo et al., 2019). By maintaining this source of income through forest protection, households can earn sufficient income that contributes to food security.
Protected forests can benefit the health and well-being of surrounding communities through impacts on the environment and local economies. 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. Proximity to PAs can benefit local tourism, which may provide more economic resources to surrounding households. Naidoo et al. (2019) found that households near PAs in low- and middle-income countries were more likely to have higher levels of wealth and were less likely to have children who were stunted. Reducing deforestation can improve health by lowering vector-borne diseases, mitigating extreme weather impacts, and improving air quality (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). Indigenous communities provide vital ecological functions for preserving biodiversity, like seed dispersal and predation (Bliege Bird & Nimmo, 2018). Indigenous peoples also have spiritual and cultural ties to their lands (Garnett et al., 2018). Establishing protected areas must prioritize the return of landscapes to Indigenous peoples so traditional owners can feel the benefits of biodiversity. However, the burden of conservation should not be placed on Indigenous communities without legal recognition or support (Fa et al., 2020). In fact, land grabs and encroachments on Indigenous lands have led to greater deforestation pressure (Sze et al., 2022). Efforts to protect these lands must include legal recognition of Indigenous ownership to support a just and sustainable conservation process (Fletcher et al., 2021).
Forests are home to a wide range of species and habitats and are essential for safeguarding biodiversity. Forests have high above- and below-ground carbon density, high tree species richness, and often provide habitat to threatened and endangered species (Buotte et al., 2020). PAs can aid in avoiding extinctions by protecting rare and threatened species (Dinerstein et al. 2024). In Southeast Asia, protecting 58% of threatened forests could safeguard about half of the key biodiversity areas in the region (Sarira et al., 2022).
Forests act as a natural water filter and can maintain and improve water quality (Melo et al., 2021). Forests can also retain nutrients from polluting the larger watershed (Sweeney et al., 2004). For example, forests can uptake excess nutrients like nitrogen, reducing their flow into surrounding water (Sarira et al., 2022). These excessive nutrients can cause eutrophication and algal blooms that negatively impact water quality and aquatic life.
Ecosystem protection initiatives that are not led by or undertaken in close collaboration with local communities can compromise community sovereignty and create injustice and inequity (Baragwanath et al., 2020; Blackman & Viet 2018; Dawson et al., 2024; Fa et al., 2020; FAO, 2024; Garnett et al. 2018; Sze et al. 2022; Tauli-Corpuz et al., 2020). Forest protection has the potential to be a win-win for climate and communities, but only if PAs are established with respect to livelihoods and other socio-ecological impacts, ensuring equity in procedures, recognition, and the distribution of benefits (Zafra-Calvo et al., 2017).
Leakage is a key risk of relying on forest protection as a climate solution. Leakage occurs when deforestation-related activities move outside of PA boundaries, resulting in the relocation of, rather than a reduction in, emissions from forest loss. If forest protection efforts are not coupled with policies to reduce incentives for forest clearing, leakage will likely offset some of the emissions avoided through forest protection. Additional research is needed to comprehensively quantify the magnitude of leakage effects, though two regional-scale studies found only small negative effects (Fuller et al., 2020; Herrera et al., 2019).
Other intact and degraded ecosystems often occur within areas of forest protection. Therefore, forest protection can facilitate natural restoration of these other degraded ecosystems, and increase the health of adjacent ecosystems.
Reducing the demand for agricultural land will reduce barriers to forest protection.
Forest protection will decrease the availability and increase the prices of wood feedstocks for other applications.
ha protected
CO₂
ha protected
CO₂
ha protected
CO₂
ha protected
CO₂
We exclude mangroves and peatlands because they are addressed in other solutions.
Global Forest Watch (2023). Global peatlands [Data set]. Retrieved December 6, 2024 from Link to source: https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about
Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., and Townshend, J.R.G. (2013). High-resolution global maps of 21st-century forest cover change [Data set]. Science 342 (15 November): 850-53. Link to source: https://glad.earthengine.app/view/global-forest-change
UNEP-WCMC (2025). Ocean+ habitats (version 1.3) [Data set]. Retrieved November 2024 from habitats.oceanplus.org
We exclude mangroves and peatlands because they are addressed in other solutions.
Global Forest Watch (2023). Global peatlands [Data set]. Retrieved December 6, 2024 from Link to source: https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about
Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., and Townshend, J.R.G. (2013). High-resolution global maps of 21st-century forest cover change [Data set]. Science 342 (15 November): 850-53. Link to source: https://glad.earthengine.app/view/global-forest-change
UNEP-WCMC (2025). Ocean+ habitats (version 1.3) [Data set]. Retrieved November 2024 from habitats.oceanplus.org
The adoption, potential adoption, and effectiveness of forest protection are highly geographically variable. While forest protection can help avoid emissions anywhere that forests occur, areas with high rates of forest loss from human drivers and particularly carbon-rich forests have the greatest potential for avoiding emissions via forest protection. The tropics and subtropics are high-priority areas for forest protection as they contain 55% of currently unprotected forest area, forest loss due to agricultural expansion is particularly concentrated in these regions (Curtis et al., 2018; West et al., 2014; Gibbs et al., 2010), and tend to have larger biomass carbon stocks than boreal forests (Harris et al., 2021).
Developed countries also have significant potential to protect remaining old and long unlogged forests and foster recovery in secondary natural forests. The top 10 forested countries include Canada, the USA, Russia and even Australia, with the latter moving towards ending commodity production in its natural forests and increasing formal protection. Restoration of degraded forests is addressed in the Forest Restoration solution, but including regenerating forests in well designed protected areas is well within the capacity of every developed country.
Buffering and reconnecting existing high integrity forests is a low risk climate solution that increases current and future forest ecosystem resilience and adaptive capacity (Brennan et al., 2022; Brink et al., 2017; Grantham et al., 2020; Rogers et al., 2022). Forests with high ecological integrity provide outsized benefits for carbon storage and biodiversity and have greater resilience, making them top priorities for protection (Grantham et al., 2020; Rogers et al., 2022). Within a given forest, large-diameter trees similarly provide outsized carbon storage and biodiversity benefits, comprising only 1% of trees globally but storing 50% of the above ground forest carbon (Lutz et al., 2018). Additionally, forests that improve protected area connectivity (Brennan et al., 2022; Brink et al., 2017), areas at high risk of loss (particularly to expansion of commodity agriculture; Curtis et al., 2018; Hansen et al., 2013), and areas with particularly large or specialized benefits for biodiversity, ecosystem services, and human well-being (Dinerstein et al., 2024; Sarira et al., 2022; Soto-Navarro et al., 2020) may be key targets for forest protection.
There is high scientific consensus that forest protection is a key strategy for reducing forest loss and addressing climate change. Rates of forest loss are lower inside of PAs and Indigenous peoples’ lands than outside of them. Globally, Wolf et al. (2021) found that rates of forest loss inside PAs are 40.5% lower on average than in unprotected areas, and Li et al. (2024) estimated that overall forest loss is 14% lower in PAs relative to unprotected areas. Regional studies find similar average effects of PAs on deforestation rates. For instance, McNichol et al. (2023) reported 39% lower deforestation rates in African woodlands in PAs relative to unprotected areas, and Graham et al. (2021) reported 69% lower deforestation rates in PAs relative to unprotected areas in Southeast Asia. In the tropics, Sze et al. (2022) found that rates of forest loss were similar between Indigenous lands and PAs, with forest loss rates reduced 17–29% relative to unprotected areas. Baragwanath & Bayi (2020) reported a 75% decline in deforestation in the Brazilian Amazon when Indigenous peoples are granted full property rights.
Reductions in forest loss lead to proportionate reductions in CO₂ emissions. The Intergovernmental Panel on Climate Change (IPCC) estimated that ecosystem protection, including forests, peatlands, grasslands, and coastal wetlands, has a technical mitigation potential of 6.2 Gt CO₂‑eq/yr, 4.0 Gt of which are available at a carbon price less than US$100 tCO₂‑eq/yr (Nabuurs et al., 2022). Similarly, Griscom et al. (2017) found that avoiding human-caused forest loss is among the most effective natural climate solutions, with a potential impact of 3.6 Gt CO₂‑eq/yr (including forests on peatlands), nearly 2 Gt CO₂‑eq/yr of which is achievable at a cost below US$10/t CO₂‑eq/yr.
The results presented in this document were produced through analysis of 12 global datasets. We recognize that geographic biases can influence the development of global datasets and hope this work inspires research and data sharing on this topic in underrepresented regions.
In this analysis, we integrated global land cover data, maps of forest loss rates, shapefiles of PAs and Indigenous people’s lands, country-scale data on reductions in forest loss inside of PAs, and biome-scale data on forest carbon stocks and sequestration rates to calculate currently protected forest area, total global forest area, and avoided emissions from forest protection. Forested peatlands and mangroves are excluded from this analysis and addressed in the Protect Peatlands and Protect Coastal Wetlands solutions, respectively.
We used two land cover data products to estimate forest extent inside and outside of PAs and Indigenous people’s lands, including: 1) the Global Forest Watch (GFW) tree cover dataset (Hansen et al., 2013), resampled to 30 second resolution, and 2) the 2022 European Space Agency Climate Change Initiative (ESA CCI) land cover dataset at native resolution (300 m). For the ESA CCI dataset, all non-flooded tree cover classes (50, 60, 70, 80, 90) and the “mosaic tree and shrub (>50%)/herbaceous cover (<50%)” class (100) and associated subclasses were included as forests. Both products are associated with uncertainty, which we did not address directly in our calculations. We include estimates from both products in order to provide readers with a sense of the variability in values that can stem from different land cover classification methods, which are discussed in more detail below.
These two datasets have methodological differences that result in substantially different classifications of forest extent, including their thresholds for defining forests, their underlying satellite data, and the algorithms used to classify forests based on the satellite information. For example, the ESA CCI product classifies 300-meter pixels with >15% tree cover as forests (based on our included classes), attempts to differentiate tree crops, relies on a 2003–2012 baseline land cover map coupled with a change-detection algorithm, and primarily uses imagery from MERIS, PROBA-V, and Sentinel missions (ESA CCI 2019). In contrast, the Global Forest Watch product generally requires >30% tree cover at 30-meter resolution, does not exclude tree crops, relies on a regression tree model for development of a baseline tree cover map circa 2010, and primarily uses Landsat ETM+ satellite imagery (Hansen et al., 2013). We recommend that interested readers refer to the respective user guides for each data product for a comprehensive discussion of the complex methods used for their development.
We used the Forest Landscape Integrity Index map developed by Grantham et al. (2020), which classifies forests with integrity indices ≥9.6 as high integrity. These forests are characterized by minimal human disturbance and high connectivity. Mangroves and peatlands were excluded from this analysis. We used a map of mangroves from Giri et al. (2011) and a map of peatlands compiled by Global Forest Watch to define mangrove and peatland extent (accessed at https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about). The peatlands map is a composite of maps from five publications: Crezee et al. (2022), Gumbricht et al. (2017), Hastie et al. (2022), Miettinen et al. (2016), and Xu et al. (2018). For each compiled dataset, the data were resampled to 30-second resolution by calculating the area of each grid cell occupied by mangroves or peatlands. For each grid cell containing forests, the “eligible” forest area was calculated by subtracting the mangrove and peatland area from the total forest area for each forest cover dataset (GFW, ESA CCI, and high-integrity forests).
We identified protected forest areas using the World Database on Protected Areas (WDPA, 2024), which contains boundaries for each PA and additional information, including their establishment year and IUCN management category (Ia to VI, not applicable, not reported, and not assigned). For each PA polygon, we extracted the forest area from the GFW, ESA CCI, and high-integrity dataset (after removing the peatland and mangrove areas).
Each protected area was classified into a climate zone based on the midpoint between its minimum and maximum latitude. Zones included tropical (23.4°N–23.4°S), subtropical (23.4°–35° latitude), temperate (35°–50° latitude), and boreal (>50° latitude) in order to retain some spatial variability in emissions factors. We aggregated protected forest cover areas (from each of the two forest cover datasets and the high-integrity forest data) by IUCN class and climate zone. To evaluate trends in adoption over time, we also aggregated protected areas by establishment year. We used the same method to calculate the forest area that could be protected, extracting the total area of each land cover type by climate zone (inside and outside of existing PAs).
We used maps from Garnett et al. (2018) to identify Indigenous people’s lands that were not inside established PAs. We calculated the total forest area within Indigenous people’s lands (excluding PAs, mangroves, and peatlands) using the same three forest area data sources.
Forest loss rates were calculated for unprotected areas using the GFW forest loss dataset for 2001–2022, resampled to 1 km resolution. Forest losses were reclassified according to their dominant drivers based on the maps originally developed by Curtis et al. (2018), with updates accessible through GFW. Dominant drivers of forest loss include commodity agriculture, shifting agriculture, urbanization, forestry, and wildfire. We classified all drivers except wildfire as human-caused forest loss for this analysis. We calculated the area of forest loss attributable to each driver within each climate zone, which represented the “baseline” rate of forest loss outside of PAs.
To calculate the difference in forest loss rates attributable to protection, we used country-level data from Wolf et al. (2021) on the ratio of forest loss in unprotected areas versus PAs, controlling for a suite of socio-environmental characteristics. We classified countries into climate zones based on their median latitude and averaged the ratios within climate zones. We defined the avoided forest loss attributable to protection as the product of the baseline forest loss rate and the ratio of forest loss outside versus inside of PAs.
We calculated the carbon benefits of avoided forest loss by multiplying avoided forest loss by average forest carbon stocks and sequestration rates. Harris et al. (2021) reported carbon stocks and sequestration rates by climate zone (boreal, temperate, subtropical, and tropical), and forest type. Carbon stocks and sequestration rates for primary and old secondary (>20 years old) forests were averaged for this analysis. We calculated carbon sequestration over a 20-yr period to provide values commensurate with the one-time loss of biomass carbon stocks.
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More than one-third of all food produced for human consumption is lost or wasted before it can be eaten. This means that the GHGs emitted during the production and distribution of that particular food – including emissions from agriculture-related deforestation and soil management, methane emissions from livestock and rice production, and nitrous oxide emissions from fertilizer management – are also wasted. This solution reduces emissions by lowering the amount of food and its associated emissions that are lost or wasted across the supply chain, from production through consumption.
The global food system, including land use, production, storage, and distribution, generates more than 25% of global GHG emissions (Poore and Nemecek, 2018). More than one-third of this food is lost or wasted before it can be eaten, with estimated associated emissions being recorded at 4.9 Gt CO₂‑eq/yr (our own calculation). FLW emissions arise from supply chain embodied emissions (i.e., the emissions generated from producing food and delivering to consumers). Reducing food loss and waste avoids the embodied emissions while simultaneously increasing food supply and reducing pressure to expand agricultural land use and intensity.
FLW occurs at each stage of the food supply chain (Figure 1). Food loss refers to the stages of production, handling, storage, and processing within the supply chain. Food waste occurs at the distribution, retail, and consumer stages of the supply chain.
Figure 1. GHG emissions occur at each stage of the food supply chain. Food loss occurs at the pre-consumer stages of the supply chain, whereas food waste occurs at the distribution, market, and consumption stages. Credit: Project Drawdown
Food loss can be reduced through improved post-harvest management practices, such as increasing the number and storage capacity of warehouses, optimizing processes and equipment, and improving packaging to increase shelf life. Retailers can reduce food waste by improving inventory management, forecasting demand, donating unsold food to food banks, and standardizing date labeling. Consumers can reduce food waste by educating themselves, making informed purchasing decisions, and effectively planning meals. The type of interventions to reduce FLW will depend on the type(s) of food product, the supply chain stage(s), and the location(s).
When FLW cannot be prevented, organic waste can be managed in ways that limit its GHG emissions. Waste management is not included in this solution but is addressed in other Drawdown Explorer solutions (see Deploy Methane Digesters, Improve Landfill Management, and Increase Centralized Composting).
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Erika Luna
Aishwarya Venkat, Ph.D.
Ruthie Burrows, Ph.D.
Emily Cassidy, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Eric Toensmeier
Paul C. West, Ph.D.
Aiyana Bodi
Hannah Henkin
Megan Matthews, Ph.D.
Heather McDiarmid, Ph.D.
Ted Otte
Christina Swanson, Ph.D.
Paul C. West, Ph.D.
Our analysis estimates that reducing FLW reduces emissions 2.82 t CO₂‑eq (100-yr basis) for every metric ton of food saved (Table 1). This estimate is based on selected country and global assessments from nongovernmental organizations (NGOs), public agencies, and development banks (ReFED, 2024; World Bank, 2020; WRAP, 2024). All studies included in this estimate reported a reduction in both volumes of FLW and GHG emissions. However, it is important to recognize that the range of embodied emissions varies widely across foods (Poore & Nemecek, 2018). For example, reducing meat waste can be more effective than reducing fruit waste because the embodied emissions are much higher.
Effectiveness is only reported on a 100-yr time frame here because our data sources did not include enough information to separate out the contribution of different GHGs and calculate the effectiveness on a 20-yr time frame.
Table 1. Effectiveness at reducing emissions.
Unit: t CO₂‑eq /t reduced FLW, 100-yr basis
| 25th percentile | 2.75 |
| mean | 3.11 |
| median (50th percentile) | 2.82 |
| 75th percentile | 3.30 |
The net cost of baseline FLW is US$932.56/t waste, based on values from the Food and Agriculture Organization of the United Nations (FAO, 2014) and Hegensholt et al. (2018). The median net cost of implementing strategies and practices that reduce FLW is US$385.5/t waste reduced, based on values from ReFED (2024) and Hanson and Mitchell (2017). These costs include, but are not limited to, improvements to inventory tracking, storage, and diversion to food banks. Therefore, the net cost of the solution compared to baseline is a total savings of US$547.0/t waste reduced.
Therefore, reducing emissions for FLW is cost-effective, saving US$194.0/t avoided CO₂‑eq on a 100-yr basis (Table 2).
Table 2. Net cost per unit climate impact.
Unit: US$/t CO₂‑eq , 2023
| Median (100-yr basis) | -194.0 |
Learning curve data were not yet available for this solution.
Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.
At Project Drawdown, we define the speed of action for each climate solution as emergency brake, gradual, or delayed.
Reduce Food Loss and Waste is an EMERGENCY BRAKE climate solution. It has the potential to deliver a more rapid impact than nominal and delayed solutions. Because emergency brake solutions can deliver their climate benefits quickly, they can help accelerate our efforts to address dangerous levels of climate change. For this reason, they are a high priority.
Reducing FLW through consumer behavior, supply chain efficiencies, or other means can lead to lower food prices, creating a rebound effect that leads to increased consumption and GHG emissions (Hegwood et al., 2023). This rebound effect could offset around 53–71% of the mitigation benefits (Hegwood et al., 2023). Population and economic growth also increase FLW. The question remains however, who should bear the cost of implementing FLW solutions. A combination of value chain investments by governments and waste taxes for consumers may be required for optimal FLW reduction (Gatto, 2023; Hegwood, 2023; The World Bank, 2020).
Strategies for managing post-consumer waste through composting and landfills are captured in other Project Drawdown solutions (see Improve Landfill Management, Increase Centralized Composting, and Deploy Methane Digesters).
Due to a lack of data we were not able to quantify current adoption for this solution.
Data on adoption trends were not available.
We assumed an adoption ceiling of 1.75 Gt of FLW reduction in 2023, which reflects a 100% reduction in FLW (Table 3). While reducing FLW by 100% is unrealistic because some losses and waste are inevitable (e.g., trimmings, fruit pits and peels) and some surplus food is needed to ensure a stable food supply (HLPE, 2014), we kept that simple assumption because there wasn’t sufficient information on the amount of inevitable waste, and it is consistent with other research used in this assessment.
Table 3. Adoption ceiling.
Unit: t reduced FLW/yr
| Median | 1,750,000,000 |
Studies consider that halving the reduction in FLW by 2050 is extremely ambitious and would require “breakthrough technologies,” whereas a 25% reduction is classified as highly ambitious, and a 10% reduction is more realistic based on coordinated efforts (Searchinger, 2019; Springmann et al., 2018). With our estimate of 1.75 Gt of FLW per year, a 25% reduction equals 0.48 Gt, while a 50% reduction would represent 0.95 Gt of reduced FLW.
It is important to acknowledge that, 10 years after the 50% reduction target was set in the Sustainable Development Goals (SDGs, Goal 12.3), the world has not made sufficient progress. The challenge has therefore become larger as the amounts of FLW keep increasing at a rate of 2.2%/yr (Gatto & Chepeliev, 2023; Hegnsholt, et al. 2018; Porter et al., 2016).
As a result of these outcomes, we have selected a 25% reduction in FLW as our Achievable – Low and 50% as our Achievable – High. Reductions in FLW are 437.5, 875.0, and 1,750 Mt FLW/year for Achievable – Low, Achievable – High, and Adoption Ceiling, respectively (Table 4).
Table 4. Adoption levels.
Unit: t reduced FLW/yr
| Current adoption (baseline) | Not determined |
| Achievable – Low (25% of total FLW) | 437,500,000 |
| Achievable – High (50% of total FLW) | 875,000,000 |
| Adoption ceiling (100% of total FLW) | 1,750,000,000 |
An Achievable – Low (25% FLW reduction) could represent 1.23 Gt CO₂‑eq/yr (100-yr basis) of reduced emissions, whereas an Achievable – High (50% FLW reduction) could represent up to 2.47 Gt CO₂‑eq/yr. The adoption potential (100% FLW reduction) would result in 4.94 Gt CO₂‑eq/yr (Table 5). We only report emissions outcomes on a 100-yr basis here because most data sources did not separate the percentage of type of food wasted or disaggregate their associated emissions factors by GHG type. Estimated impacts would be higher on a 20-yr basis due to the higher GWP of methane associated with meat and rice production.
Table 5. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current adoption (1.5% of total FLW) | Not determined |
| Achievable – Low (25% of total FLW) | 1.23 |
| Achievable – High (50% of total FLW) | 2.47 |
| Adoption ceiling (100% of total FLW) | 4.94 |
We also compiled studies that have modeled the climate impacts of different FLW reduction scenarios, from 10% to 75%. For an achievable 25% reduction, Scheringer (2019) estimated a climate impact of 1.6 Gt CO₂‑eq/yr. Studies that modeled the climate impact of a 50% reduction by 2050 estimated between 0.5 Gt CO₂‑eq/yr (excluding emissions from agricultural production and land use change; Roe at al., 2021) to 3.1–4.5 Gt CO₂‑eq/yr (including emissions from agricultural production and land use change; Roe at al., 2021; Searchinger et al., 2019).
Multiple studies stated that climate impacts from FLW reduction would be greater when combined with the implementation of dietary changes (see the Improve Diets solution; Almaraz et al., 2023; Babiker et al.; 2022; Roe et al., 2021; Springmann et al., 2018; Zhu et al., 2023).
Households and communities can strengthen adaptation to climate change by improving food storage, which helps reduce food loss (Ziervogel & Ericksen, 2010). Better food storage infrastructure improves food security from extreme weather events such as drought or floods which make it more difficult to grow food and can disrupt food distribution (Mbow et al., 2019).
FLW accounts for a loss of about US$1 trillion annually (World Bank, 2020). In the United States, a four-person household spends about US$2,913 on food that is wasted (Kenny, 2025). These household-level savings are particularly important for low-income families because they commonly spend a higher proportion of their income on food (Davidenko & Sweitzer, 2024). Reducing FLW can improve economic efficiency (Jaglo et al., 2021). In fact, a report by Champions 12.3 found efforts to reduce food waste produced positive returns on investments in cities, businesses, and households in the United Kingdom (Hanson & Mitchell, 2017). FLW in low- and middle-income countries mostly occurs during the pre-consumer stages, such as storage, processing, and transport (Kaza et al., 2018). Preventive measures to reduce these losses have been linked to improved incomes and profits (Rolker et al., 2022).
Reducing FLW increases the amount of available food, thereby improving food security without requiring increased production (Neff et al., 2015). The World Resources Institute estimated that halving the rate of FLW could reduce the projected global need for food approximately 20% by 2050 (Searchinger et al., 2019). In the United States, about 30–40% of food is wasted (U.S. Food and Drug Administration [U.S. FDA], 2019) with this uneaten food accounting for enough calories to feed more than 150 million people annually (Jaglo et al., 2021). These studies demonstrate that reducing FLW can simultaneously decrease the demand for food production while improving food security.
Policies that reduce food waste at the consumer level, such as those that improve food packaging and require clearer information on shelf life and date labels, can reduce the number of foodborne illnesses (Neff et al., 2015; U.S. FDA, 2019). Additionally, efforts to improve food storage and food handling can further reduce illnesses and improve working conditions for food-supply-chain workers (Neff et al., 2015). Reducing FLW can lower air pollution from food production, processing, and transportation and from disposal of wasted food (Nutrition Connect, 2023). Gatto and Chepeliev (2024) found that reducing FLW can improve air quality (primarily through reductions in carbon monoxide, ammonia, nitrogen oxides, and particulate matter), which lowers premature mortality from respiratory infections. These benefits were primarily observed in China, India, and Indonesia, where high FLW-embedded air pollution is prevalent across all stages of the food supply chain (Gatto & Chepeliev, 2024).
For a description of the land resources benefits, please refer to the “water resources” subsection below.
Reducing FLW can conserve resources and improve biodiversity (Cattaneo, Federighi, & Vaz, 2021). A reduction in FLW reflects improvements in resource efficiency of freshwater, synthetic fertilizers, and cropland used for agriculture (Kummu et al., 2012). Reducing the strain on freshwater resources is particularly relevant in water-scarce areas such as North Africa and West-Central Asia (Kummu et al., 2012). In the United States, halving the amount of FLW could reduce approximately 290,000 metric tons of nitrogen from fertilizers, thereby reducing runoff, improving water quality, and decreasing algal blooms (Jaglo et al., 2021).
Interventions to address FLW risk ignoring economic factors such as price transmission mechanisms and cascading effects, both upstream and downstream in the supply chain. The results of a FLW reduction policy or program depend greatly on the commodity, initial FLW rates, and market integration (Cattaneo, 2021; de Gorter, 2021).
On the consumer side, there is a risk of a rebound effect: Avoiding FLW can lower food prices, leading to increased consumption and net increase in GHG emissions (Hegwood et al., 2023). Available evidence is highly contextual and often difficult to scale, so relevant dynamics must be studied with care (Goossens, 2019).
The production site is a critical loss point, and farm incomes, scale of operations, and expected returns to investment affect loss reduction interventions (Anriquez, 2021; Fabi, 2021; Sheahan and Barrett, 2017).
Food waste is used as raw material for methane digesters and composting. Reducing FLW may reduce the impact of those solutions as a result of decreased feedstock availability.
t reduced FLW
CO₂ , CH₄ , N₂O
Some FLW reduction strategies have trade-offs for emission reductions (Cattaneo, 2021; de Gorter et al., 2021). For example, improved cold storage and packaging are important interventions for reducing food loss, yet they require additional electricity and refrigerants, which can increase GHG emissions (Babiker et al., 2022; FAO, 2019).
A large volume of scientific research exists regarding reducing emissions of FLW effectively. The IPCC Sixth Assessment Report (AR6) estimates the mitigation potential of FLW reduction (through multiple reduction strategies) to be 2.1 Gt CO₂‑eq/yr (with a range of 0.1–5.8 Gt CO₂‑eq/yr ) (Nabuurs et al., 2022). This accounts for savings along the whole value chain.
Following the 2011 FAO report – which estimated that around one-third (1.3 Gt) of food is lost and wasted worldwide per year – global coordination has prioritized the measurement of the FLW problem. This statistic has served as a baseline for multiple FLW reduction strategies. However, more recent studies suggest that the percentage of FLW may be closer to 40% (WWF, 2021). The median of the studies included in our analysis is 1.75 Gt/yr of FLW (FAO, 2024; Gatto & Chepeliev, 2024; Guo et al., 2020; Porter et al., 2016; UNEP, 2024; WWF, 2021; Zhu et al., 2023), with an annual increasing trend of 2.2%.
Only one study included in our analysis calculated food embodied emissions from all stages of the supply chain, while the rest focused on the primary production stages. Zhu et al. (2023) estimated 6.5 Gt CO₂‑eq/yr arising from the supply chain side, representing 35% of total food system emissions.
When referring to food types, meat and animal products were estimated to emit 3.5 Gt CO₂‑eq/yr compared to 0.12 Gt CO₂‑eq/yr from fruits and vegetables (Zhu et al., 2023). Although meat is emissions-intensive, fruits and vegetables are the most wasted types of food by volume, making up 37% of total FLW by mass (Chen et al., 2020). The consumer stage is associated with the highest share of global emissions at 36% of total supply-embodied emissions from FLW, compared to 10.9% and 11.5% at the retail and wholesale levels, respectively (Zhu et al., 2023).
While efforts to measure the FLW problem are invaluable, critical gaps exist regarding evidence of the effectiveness of different reduction strategies across supply chain stages ( Cattaneo, 2021; Goossens, 2019; Karl et al., 2025). To facilitate impact assessments and cost-effectiveness, standardized metrics are required to report actual quantities of FLW reduced as well as resulting GHG emissions savings (Food Loss and Waste Protocol, 2024).
The results presented in this document summarize findings across 22 studies. These studies are made up of eight academic reviews and original studies, eight reports from NGOs, and six reports from public and multilateral organizations. This reflects current evidence from five countries, primarily the United States and the United Kingdom. We recognize this limited geographic scope creates bias, and hope this work inspires research for meta-analyses and data sharing on this topic in underrepresented regions and stages of the supply chain.
Oil and gas methane management is the process of reducing methane emissions from oil and gas (O&G) supply chains. These supply chains release methane when pipes and other system parts leak or methane is intentionally vented for operation and safety reasons. We define the Manage Oil & Gas Methane solution as adopting approaches to reduce methane emissions, including fixing leaks in components, upgrading control equipment, changing procedures, and destroying methane by burning methane as a fuel or in flares.
Methane can be unintentionally released due to imperfections and faults along the supply chain or intentionally released as part of operations and maintenance. Atmospheric methane has a GWP of 81 over a 20-yr time basis and a GWP of 28 over a 100-yr time basis (IPCC, 2023). This means methane is 81 times more effective at trapping heat than CO₂. Because methane is a short-lived climate pollutant that has a much stronger warming effect than CO₂ over a given time period, abating methane will have a relatively large near-term impact on slowing global climate change (IEA, 2023b).
The first step to reduce methane releases from O&G production is to identify where releases occur along the supply chain. Many occur during O&G extraction as methane is either intentionally vented or unintentionally emitted. The International Energy Agency (IEA, 2024) estimated more than 60% of global energy-related methane emissions originated from the O&G sector in 2023, with the remaining emissions mostly coming from coal use and some bioenergy (Figure 1). The United Nations Environment Programme (UNEP) has formed a transparency and accountability initiative whose members are responsible for 42% of global O&G production. It reported that activities involved in exploration and processing of O&G accounted for 83% of total reported O&G emissions from 2020 to 2023, with production processes being responsible for 90% of those emissions (UNEP 2024). Alvarez et al. (2018) found that in the United States, more than 58% of O&G methane emissions came from production and about 20% came from extraction in 2015.
Figure 1. Methane emissions (kt) from energy sources (IEA, 2025).
Source: International Energy Agency. (2025). Methane tracker: Data tools. https://www.iea.org/data-and-statistics/data-tools/methane-tracker
O&G producers can reduce their methane emissions by preventing its release or by converting it to CO₂ through combustion. Strategies for reducing O&G methane emissions can be put into two broad categories (Climate & Clean Air Coalition [CCAC], 2021):
Device conversion, replacement, and installation is the practice of fixing leaks in pipes, valves, compressors, pumps, and other equipment. This can include converting natural gas–powered devices to electric, driving compressors/pneumatics with air instead of natural gas, or replacing emitting components with non-emitting ones (Pembina Institute, 2024).
Changes to operations and maintenance practices seek to reduce the intentional venting of methane. They include eliminating the need for blow-down (releasing gases during the maintenance or operation of pipe infrastructure), reducing venting, and capturing methane before it is released into the atmosphere, then using it as fuel for product refining or burning it to convert it into CO₂.
Leak detection and repair (LDAR) is the practice of regularly monitoring for methane leaks and modifying or replacing leaking equipment.
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Jason Lam
Ruthie Burrows, Ph.D.
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Daniel Jasper
Alex Sweeney
Aiyana Bodi
Hannah Henkin
Ted Otte
Amanda D. Smith, Ph.D.
Paul C. West, Ph.D.
James Gerber, Ph.D.
Each Mt of methane that is not emitted avoids 81.2 million t CO₂‑eq on a 20-yr basis and 27.9 million t CO₂‑eq on a 100-yr basis (Smith et al., 2021). The GWP of methane is shown in Table 1. If the methane is burned (converted into CO₂ ), the contribution to climate change will still be less than that of methane released directly into the atmosphere. Methane abatement can have a more immediate impact on future global temperature rise because it has a larger and faster warming effect than CO₂. Mitigating methane emissions in the near term can give us more time for reducing GHG emissions in hard-to-abate sectors.
Table 1. Effectiveness at reducing emissions.
Unit: t CO₂‑eq /Mt of methane abated
| 100-yr GWP | 27,900,000 |
| 20-yr GWP | 81,200,000 |
The cost of methane abatement will vary depending on the type of O&G production, the methane content of the O&G resource, and the strategies used to address it. We averaged the costs for various abatement strategies; methane content is sufficiently high to utilize methane abatement strategies, and energy infrastructure is available to utilize abated methane. The initial cost to abate 1 Mt of methane is US$594 million, the revenue is about US$193 million, and the overall net savings over a 30-yr amortization period is US$173 million. This means that reducing O&G methane emissions offers a net economic gain for O&G producers. We were not able to find operating cost information for the solution, meaning the net economic gain may be lower in practice.
We considered the baseline scenario where O&G producers do not have systems or practices in place to monitor or stop methane from escaping to the atmosphere and found very limited cost data. We assumed baseline costs to be 0 for initial costs, operational costs, and revenue because current practices and infrastructure are releasing methane to the atmosphere as a part of their existing cost of doing business.
Many of the initial cost data for methane abatement come from studies estimating how much capital would be required to reach methane emission targets for the O&G industry. These costs are for the global scale of O&G methane abatement and not from the point of view of an individual O&G producer. These studies do not go into detail about the cost of specific abatement strategies or their potential revenues. The context and assumptions are difficult to identify, since the abatement strategies must be tailored to each site. Ocko et al (2021) noted that most (around 80%) of economically feasible methane abatement actions are from the O&G sector.
Table 2 shows the costs per t CO₂‑eq. The value of the methane sold, instead of released, will often bring in revenue that covers the costs of abatement. Refer to the Appendix for information on the proportion of strategies that O&G producers could implement at low to no cost.
Table 2. Net cost per unit of climate impact.
Unit: 2023 US$/t CO₂‑eq
| median (100-yr basis) | -6.20 |
Many of the technology solutions for reducing methane emissions are mature, and we were unable to find literature suggesting the costs to implement these solutions will fall in the future. There may be efficiencies to be gained in LDAR, but little research offers insights into the costs of LDAR programs (Delphi Group, 2017, ICF, 2016).
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.
Manage OIl & Gas Methane 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.
Burning methane produces CO₂.
Though the GWP is far less than that of releasing methane into the atmosphere, the practice still creates a negative climate impact. Depending on the type of O&G production, methane abatement is already practiced with natural gas production and is likely to bring added profit. However, oil producers who are not already producing methane for profit may not be able to abate methane at a profit.
Avoiding fossil fuel extraction, transport, and use is the only way to permanently reduce emissions from O&G production. For many low- and middle-income countries (LMICs), O&G is the main source of energy, and it is challenging for them to completely eliminate O&G from their energy mix while they are simultaneously working to improve living standards. High-income countries can help LMICs develop clean energy infrastructure by providing financial and technological support. This will prevent new investments in O&G infrastructure (Laan, et al., 2024), which would result in ongoing emissions for decades. It would also allow LMICs a realistic pathway to transition away from their existing O&G usage. O&G demand must fall by 80% between 2022 and 2050 to stay in alignment with the net-zero emissions scenarios modeled by IEA (2023c). O&G methane abatement will decrease over time as the O&G industry produces less methane to be abated.
Our assessment does not include the impact of the CO₂ created from the destruction of methane.
We found little literature quantifying the current adoption of methane management; much of the methane abatement research revolves around the amount of methane that needs to be abated to reach certain climate targets. Based on data from Global Methane Initiative (GMI, 2024), 0 Mt of methane was abated in 2023 but due to lack of data we consider current adoption to be not determined in Table 3.
GMI (2024) provided a conservative estimate of cumulative methane emissions abated each year, with a total of 153.6 Mt CO₂‑eq (5.51 Mt methane) abated as of 2023. The methane is given as a cumulative value to show the incremental increase in total methane abated and to avoid double counting methane abated. GMI members only cover 70% of human-caused methane emissions, and the organization does not capture methane mitigation that occurs outside of GMI members. This suggests that even in years where methane was abated, it would likely still be an underestimate of what may have actually occurred globally. The untapped potential for methane abatement suggests that O&G companies are investing in increasing natural gas production, which may be due to relatively smaller profits from abatement and nonbinding regulations (Shindell et al., 2024).
Table 3. Current (2023) adoption level.
Unit: Mt of methane abated/yr
| median (50th percentile) | not determined |
Although there is little research specifically quantifying the adoption of methane abatement strategies over time, we estimate the average adoption trend in recent years to be about 0.35 Mt/yr of methane abated. To create this estimate, we relied on GMI analysis (GMI, 2024). GMI showed methane abatement gradually increasing from 2011 to 2023, then tapering off around 2020 and beginning to decrease among its member organizations. Table 4 shows the adoption trend for O&G methane abatement.
The IEA (2025) compiled country-level reporting for GHG emissions with data up to 2024. However, we were not able to use the data for the adoption trend because the changes in methane emissions could have been due to reasons other than methane abatement. In reality, methane emissions may be affected by multiple factors such as natural disasters, political conditions, changes in O&G demand, and changes in O&G industry practices.
Oil and Gas Climate Initiative (2023) data on methane abatement to date for 12 major O&G companies indicate that methane emissions decreased 50% from 2017 to 2022; however, we cannot assume the rest of the O&G industry has made the same level of progress.
Table 4. Adoption trend, 2011–2022.
Unit: Mt methane abated/yr
| median (50th percentile) | 0.35 |
We found an adoption ceiling of 80.7 Mt/yr of methane based on the IEA’s (2025) estimate for total methane emissions from the O&G sector. We assumed that current O&G methane emissions would remain the same into the future with no changes in O&G production or demand. Table 5 shows the adoption ceiling for O&G methane abatement.
Even in the IEA’s (2023c) highest methane abatement energy scenario, only 93% of the methane emissions are reduced by 2050. This would still leave methane emissions being released into the atmosphere by the O&G sector. Reduced O&G production will reduce the amount of methane emissions produced by the O&G sector and consequently reduce the amount of methane that needs to be controlled with methane abatement.
Table 5. Adoption ceiling.
Unit: Mt methane abated/yr
| median (50th percentile) | 80.7 |
Based on the limited data available for current adoption and adoption trend, we expect 3.26–8.84 Mt/yr of methane abated. The Achievable – Low value aligns with the IEA (2023c) baseline energy scenario (STEPS), in which partial methane abatement is used but not all technically possible methane is abated. The Achievable – High value aligns with the IEA (2023c) baseline scenario (STEPS), in which full methane abatement is employed (all technically possible methane is abated). We determined this range by taking the total methane abated in these scenarios and dividing by the difference between the target year and 2024 to determine an average amount of methane abated each year to reach the scenario target. Under both scenarios, reduced demand for O&G would reduce methane emissions produced and lower the adoption ceiling possible for methane abatement. Even in scenarios where there is reduced O&G demand, methane abatement would still be required to control fugitive methane emissions from O&G infrastructure and limit global climate change.
The amount of methane that can be abated varies greatly depending on how much methane the O&G industry produces. If O&G production remains steady, cumulative methane abatement could be 21–81 Mt, according to the IEA energy scenarios. If O&G demand drops 80% (IEA’s Net Zero Emissions scenario), total methane emissions would decline to 18 Mt, and the use of methane abatement would reduce methane emissions further by 17 Mt, leaving only 1 Mt of methane emitted in 2050.
There has been growing interest from governments and academia to more accurately identify methane emissions using technologies such as satellite sensing (MethaneSat, 2024); UNEP (2024) has set up a monitoring and operator’s alliance group that will share best practices among O&G producers. This alliance group has identified more than 1,200 methane releases, but only 15 responses from government or companies provided detail about the source of the emissions or whether any mitigation action was considered or taken. This shows there are still many opportunities to abate methane emissions.
More than 150 countries (representing 50% of the world’s human-caused methane emissions) have joined the Global Methane Pledge to reduce methane emissions 30% from 2020 to 2030 (UNEP, 2021). The IEA (2023b) found that many governments already have announced or put into place measures to cut methane emissions, so we expect global methane abatement to grow.
Conrad et al. (2023) found that the emission inventories reported by the Alberta, Canada, government underestimate the methane emissions from the O&G sector, with a large portion coming from venting. These sources of methane are relatively easier to address and can allow the O&G sector to quickly reduce methane emissions. Table 6 shows the statistical low and high achievable ranges for O&G methane abatement based on different sources for future uptake of O&G methane abatement.
Table 6. Achievable adoption.
Unit: Mt methane abated/yr
| Current Adoption | not determined |
| Achievable – Low | 3.26 |
| Achievable – High | 8.84 |
| Adoption Ceiling | 80.66 |
We estimate that the O&G industry is currently abating approximately 0 Gt CO₂‑eq/yr on a 100-yr basis and 0 Gt CO₂‑eq/yr on a 20-yr basis using methane abatement strategies.
As the O&G industry grows or shrinks its emissions, the amount of methane available to abate will change accordingly. If O&G demand and production stay constant to 2050, we estimate 0.09–0.25 Gt CO₂‑eq/yr of methane could be abated.
However, if O&G demand drops, the methane abatement potential would drop because the O&G sector is producing less methane. This is projected in the different energy scenarios modeled by the IEA (2023). The range between the current O&G methane abatement and the adoption ceiling is shown in Table 7.
Table 7. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | not determined |
| Achievable – Low | 0.09 |
| Achievable – High | 0.25 |
| Adoption Ceiling | 2.25 |
Methane reacts with other pollutants to create ground-level ozone (Mar et al., 2022), and incomplete combustion of methane (Figure 2) releases other pollutants such as CO₂, carbon monoxide, black carbon, and volatile organic compounds (Fawole et al., 2016; Johnson and Coderre, 2012; Motte et al., 2021). These pollutants cause respiratory, reproductive, and neurological diseases; cancer; and premature death (Michanowicz et al., 2021; Motte et al., 2021; Tran et al., 2024), so reducing methane release can improve human health. Reducing or stopping flaring at a small number of the largest active sites can significantly reduce air pollution (Anejionu et al., 2015; Johnson and Coderre, 2012). Van Dingenen et al. (2018) estimate that ambitious methane reduction could prevent 70,000 to 130,000 ozone-related deaths worldwide each year.
Figure 2. Air pollutants emitted along the O&G life cycle (Moore et al., 2014). BTEX = benzene, toluene, ethylbenzene, xylene.
Source: Moore, C. W., Zielinska, B., Pétron, G., & Jackson, R. B. (2014). Air impacts of increased natural gas acquisition, processing, and use: A critical review. Environmental Science & Technology, 48(15), 8349–8359. Link to source: https://doi.org/10.1021/es4053472
If natural gas prices drop there would be less economic reason for industries to voluntarily abate methane (IEA, 2021). Without policy support enforcing the use of methane abatement technologies, methane could continue to be released into the atmosphere. The use of methane abatement will be needed regardless of whether O&G demand remains the same or decreases over time because it has an immediate effect on reducing global temperature rise in the near term.
Managing O&G methane can reinforce other solutions that reduce the amount of methane released to the atmosphere. The use of solutions such as applying changes to operations and maintenance; converting, replacing, and installing devices; and LDAR in the O&G industry can help demonstrate the effectiveness and economic case for methane abatement elsewhere and build momentum for adoption of methane abatement in other sectors.
Managing O&G methane has the potential to compete with solutions that provide clean electricity and solutions that focus on fuel switching in transportation because this solution increases O&G supply and can reduce the cost of O&G products. As a result, it could prolong the use of fossil fuels and slow down the transition to clean electricity.
Mt methane abated
CH₄, N₂O, BC
Methane abatement could increase the use of O&G resources without a broader strategy to reduce reliance on O&G as an energy resource. The use of methane abatement strategies to extend the use of existing O&G infrastructure, or building new O&G infrastructure, will not result in a net decrease in emissions. Beck et al. (2020) found that more than 57% of the GHG emissions from the O&G supply chain are from methane emissions, while the rest is due to CO₂ emissions (15% from the extraction process and 28% from O&G energy use). Even with methane mitigation, continued use of O&G will generate CO₂ emissions and will contribute to global temperature rise.
Globally, oil and gas sources, including production, refining, and transport, were responsible for 81 Mt out of the 354 Mt of anthropogenic methane emissions in 2024. This is equivalent to 2,250 Mt CO2-eq based on a 100-year GWP time scale. Methane emissions occur throughout the supply chain due to equipment imperfections, leaks, and intentional venting.
International Energy Agency. (2025). Global Methane tracker 2025: Data tools. Link to source: https://www.iea.org/data-and-statistics/data-tools/methane-tracker
Schmeisser, L., Tecza, A., Huffman, M., Bylsma, S., Delang, M., Stanger, J., Conway, TJ, and Gordon, D. (2024). Fossil fuel operations sector: Oil and gas production and transport emissions [Data set]. RMI, Climate TRACE Emissions Inventory. Retrieved April 18, 2025 from Link to source: https://climatetrace.org
Wang, J., Fallurin, J., Peltier, M., Conway, TJ, and Gordon, D. (2024). Fossil fuel operations sector: Refining emissions [Data set]. RMI, Climate TRACE Emissions Inventory. Retrieved April 18, 2025 from Link to source: https://climatetrace.org
Globally, oil and gas sources, including production, refining, and transport, were responsible for 81 Mt out of the 354 Mt of anthropogenic methane emissions in 2024. This is equivalent to 2,250 Mt CO2-eq based on a 100-year GWP time scale. Methane emissions occur throughout the supply chain due to equipment imperfections, leaks, and intentional venting.
International Energy Agency. (2025). Global Methane tracker 2025: Data tools. Link to source: https://www.iea.org/data-and-statistics/data-tools/methane-tracker
Schmeisser, L., Tecza, A., Huffman, M., Bylsma, S., Delang, M., Stanger, J., Conway, TJ, and Gordon, D. (2024). Fossil fuel operations sector: Oil and gas production and transport emissions [Data set]. RMI, Climate TRACE Emissions Inventory. Retrieved April 18, 2025 from Link to source: https://climatetrace.org
Wang, J., Fallurin, J., Peltier, M., Conway, TJ, and Gordon, D. (2024). Fossil fuel operations sector: Refining emissions [Data set]. RMI, Climate TRACE Emissions Inventory. Retrieved April 18, 2025 from Link to source: https://climatetrace.org
Methane abatement is recommended for all oil and gas (O&G) production. The levels of achievable abatement can vary geographically, depending on the extraction technology used (i.e., conventional drilling versus hydraulic fracturing). The Middle East, Europe, Asia, and North America are among the largest O&G producers and have the highest related methane emissions, according to the IEA (2025). Research from Shindell et al. (2024) found that North America, Russia, and several countries in the Middle East and Africa have the most methane abatement potential in O&G. O&G methane abatement could be accelerated if technologies and strategies used in high-income countries are shared with other O&G producing countries.
There is a high level of consensus about the effectiveness of methane abatement strategies. These strategies can be deployed cost effectively in many cases and have an immediate impact on reducing global temperature rise.
Authoritative sources such as the IEA (2023d), UNEP (2021), and Global Methane Hub (2024) agree that reducing methane emissions can noticeably reduce the rate of global temperature rise. DeFabrizio et al. (2021) identified that methane abatement strategies such as LDAR, switching from natural gas fuel to electric power, using air for pneumatic devices, and using vapor recovery units could reduce O&G methane emissions by 40% by 2030 based on global 2017 O&G emissions. With methane being the second largest contributor to climate change after CO₂, reductions in methane emissions can quickly reduce global temperature rise.
Others (Marks Levi, 2022; DeFabrizio et al., 2021; Malley et al., 2023) have identified that many methane abatement strategies can use existing technologies, often at low cost. Dunsky (2023) found that implementing 24 of the least expensive abatement measures in the exploration and production phases of Canada’s O&G industry could help Canada achieve its 2030 methane target. The IEA (2023a) noted that the O&G industry was responsible for 80 Mt of methane in 2022 and had the largest potential for abatement in the near term. The O&G industry has the potential to abate 60 Mt of methane by 2030 using abatement strategies; 40% of that could be abated at no net cost based on average natural gas prices from 2017 to 2021 (IEA, 2023a).
The results presented in this document summarize findings from more than 15 reviews and meta-analyses and more than 10 original studies reflecting current evidence from two countries, primarily from the United States and Canada, and from global sources. We recognize this limited geographic scope creates bias, and hope this work inspires research and data-sharing on this topic in underrepresented regions.
Data describing methane abatement potential in the O&G industry are often shown in marginal abatement cost curves (MACCs), which incorporate the initial cost, operating cost, revenue, and any extra costs per unit of emissions reduced as one value.
Figure A1. Marginal abatement cost curves (MACC) for methane abatement in the O&G industry (IEA, 2024).
Source: International Energy Agency (Global Methane Tracker 2024).
MACCs indicate a range of potential climate actions and show at a glance the magnitude of financial return or financial cost across that range. In Figure A1, for the blocks below the horizontal axis, the value received from the sale of the captured methane is greater than the cost of the solution employed. The width of a block shows the annual amount of emissions a technology can abate, with wider blocks abating more emissions than narrower blocks.
MACCs are useful for identifying which climate action could have the most impact at reducing emissions or which options have a net economic gain. However, they do not illustrate the intricacies that may be in play among different climate actions and can lead users to ignore hard-to-abate emissions. The World Bank (2023) identified that MACCs are useful to find which option will reduce emissions by a set percentage but less useful for reducing absolute emissions to near zero.
Managing coal mine methane (CMM) is the process of reducing methane emissions released from coal deposits and surrounding rock layers due to mining activities. CMM is naturally found in coal seams and released into the atmosphere when the coal seams are disturbed. Coal mines can continue to emit methane even after being closed or abandoned, which is known as abandoned mine methane (AMM). CMM and AMM can be captured and then utilized as a fuel source or destroyed before they reach the atmosphere [U.S. Environmental Protection Agency (EPA), 2024a].
CMM is released from coal mines before, during, and after active coal mining and from coal being transported (EPA, 2024a). Atmospheric methane has a GWP of 81 on a 20-yr basis and a GWP of 28 on a 100-yr basis (Intergovernmental Panel on Climate Change [IPCC], 2023). This means methane is 81 times more effective at trapping heat than CO₂. Because methane is a short-lived climate pollutant that has a much stronger warming effect than CO₂ over a given time period, abating methane from coal mines will have a powerful near-term impact on slowing global climate change. If capturing methane is not possible, destroying the methane by burning it is preferable to releasing it.
CMM comes from five major sources throughout the coal mine’s life cycle (Figure 1):
Figure 1. Percent breakdown of CMM sources in the United States, 2021.
Source: U.S. Environmental Protection Agency (2024d). Sources of coal mine methane. Retrieved November 5, 2024. https://www.epa.gov/cmop/sources-coal-mine-methane
CMM management relies on several practices and technologies to reduce the amount of methane released into the atmosphere. The CMM that is captured can be used as a fuel at high concentrations and destroyed through flaring or oxidation at low concentrations. The methane captured from degasification systems typically has a high concentration while fugitive and ventilation methane sources are low concentration. CMM management also includes leak detection and repair using satellites, drones, or other technologies to prevent methane from escaping into the atmosphere.
Underground coal mines have more methane abatement strategies available due to higher average methane concentrations and relative ease of capture. Surface coal mines are exposed directly to the atmosphere and can cover large areas, making them more difficult to abate methane, though there are technologies that can reduce CMM emissions. See the Appendix for more details on the abatement technologies specific to underground and surface coal mines.
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Jason Lam
James Gerber, Ph.D.
Yusuf Jameel, Ph.D.
Ruthie Burrows, Ph.D.
Daniel Jasper
Alex Sweeney
Sarah Gleeson, Ph.D.
Aiyana Bodi
Hannah Henkin
Ted Otte
Amanda D. Smith, Ph.D.
Paul C. West, Ph.D.
Each Mt of methane that is not emitted avoids 81.2 Mt CO₂‑eq on a 20-yr basis and 27.9 Mt CO₂‑eq on a 100-yr basis (Smith et al., 2021). The GWP of methane is shown in Table 1. If the methane is converted into CO₂ through burning the contribution to global climate change will still be less than if the methane were released into the atmosphere. Methane abatement can have a more immediate impact on future global temperature rise because it has a larger and faster warming effect than CO₂. Mitigating methane emissions in the near term can give us more time for reducing GHG emissions in hard-to-abate sectors.
Table 1. Effectiveness at reducing emissions.
Unit: t CO₂‑eq/Mt methane abated
| 100-yr GWP | 27,900,000 |
| 20-yr GWP | 81,200,000 |
The cost of methane abatement will vary depending on the type of coal mine, the methane content of the coal seam, the strategies used, and the availability of financial support for methane abatement. For our analysis, we average the costs for various feasible abatement strategies under two general assumptions: sufficiently high methane content for any of the major abatement strategies to be applied (IEA, 2024a) and the ability to use the abated methane on-site or sell it to natural gas companies. The initial cost to abate 1 Mt of methane is US$1.5 billion, the operating cost is about US$130 million, revenue is about US$260 million and the overall net savings over a 30-yr amortization period is US$90 million. We were only able to find revenue information from the IEA (2023b, 2024a), meaning the net cost could be different than shown here due to the site specific nature of methane abatement strategies.
We considered the baseline scenario to be coal mining practices without methane abatement; all cost estimates here are relative to that scenario.
Cost data were limited for this solution. The available costs for a specific abatement strategy were normalized according to the cost of abating one Mt of methane, and it was assumed that a single strategy abated all of the methane for the coal mine. This results in an overestimate of the effectiveness of any individual strategy. In reality, multiple strategies are likely to be used. The costs shown in Table 2 are for the global scale of coal methane abatement and not from the point of view of an individual coal producer. Many studies that look at global coal methane abatement put multiple abatement strategies together and do not go into detail about the individual technology costs. The IEA (2024a) included costs for individual CMM abatement strategies; however, the costs were only applicable for coal mines that produce enough methane for it to be economically feasible to deploy the specific abatement strategy. Flaring is an effective strategy for destroying captured methane, but will not create revenue in the absence of a carbon market. For more details on important aspects for coal methane abatement strategies, refer to the Appendix.
Table 2. Cost per unit climate impact.
Unit: 2023 US$/t CO₂‑eq, 100-yr basis
| median | -3.17 |
Many of the solutions for reducing methane emissions from coal mining are mature. Research from Rystad (2023) found that technologies for abating CMM emissions, such as drainage gas utilization, sealing and rerouting, and flaring, were considered mature in Australian coal mines. Regenerative thermal oxidation technology is in commercial use for destroying volatile organic compounds and can be used for destroying ventilation air methane (VAM), but the manufacturers have little interest in improving the technology for use in coal mines without confirmed markets (GMI, 2018; Rystad, 2023). We do not foresee the costs of implementing these solutions falling in the future. CMM regulations may encourage manufacturers to improve oxidation technology, but the technology is already used commercially, so there may not be large efficiency gains.
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.
Manage Coal Mine Methane 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.
CMM abatement consists of capturing methane that would otherwise be released into the atmosphere. If the methane is burned, CO₂ will be emitted as a byproduct; however, this provides a net climate benefit compared to the methane that would be emitted. CMM emissions management can be avoided by not extracting, transporting, or using coal in the first place.
As coal demand drops, the number of closed or abandoned coal mines will increase. These mines will continue to release AMM into the atmosphere for many decades. Sealing underground mines can stop methane from being released, but seals have been known to fail and require ongoing monitoring to verify methane is not escaping (Kholod et al., 2020). Gas collection systems can be used to capture AMM, but the CO₂ produced will need to be captured for complete emission reductions. Flooding underground coal mines is very effective at stopping methane from being released; however, there are concerns about water contamination (McKinsey, 2021).
Our assessment does not include the impact of the CO₂ created from the destruction of methane.
We estimated that the coal sector abated 0.59 Mt of methane in 2023 and released 40 Mt in 2024 (IEA, 2025). Reports from EPA (2022), and GMI (2023) estimated the amount of CMM abated to date, and the statistical ranges from the sources are shown in Table 3. However, most of the data focused on coal mines in the United States. The EPA (2024b) stated that 0.3 Mt of methane was captured in 2021 due to the Coalbed Methane Outreach Program. CMM is controlled at coal mines for health and safety reasons, but only in 2024 was regulation introduced for reducing methane emissions from the energy sector in the European Union (Assan, 2024).
GMI (2024a) reports that 0.79 Mt of methane was abated from coal mines in 2023 among its member countries. The organization includes 48 GMI member countries but covers only 70% of human-caused methane emissions and does not track methane mitigation that has occurred outside of the group. GMI (2024b) currently lists more than 471 CMM abatement projects in 20 countries worldwide. According to Global Energy Monitor (n.d.), over 6,000 coal mines were active in more than 70 countries as of April 2024. With these data sources, we consider our analysis of the current adoption of CMM abatement as conservative.
Table 3. Current (2023) adoption level.
Unit: Mt/yr of methane abated
| 25th percentile | 0.49 |
| mean | 0.59 |
| median (50th percentile) | 0.59 |
| 75th percentile | 0.69 |
Although there are little data specifically quantifying the adoption trend of methane abatement strategies, we estimate the median adoption trend to be about 0.60 Mt/yr of methane abated. Table 4 shows the adoption trend for CMM abatement.
GMI (2024) reported methane abatement staying relatively stable from 2016 to 2023 at about 0.8 Mt/yr, with a small increase to 1.0 Mt of methane in 2019–2022 before decreasing back to 0.8 Mt in 2023, causing the adoption trend to be higher than the current adoption value we state above. The EPA (2024a) Coalbed Methane Outreach Program showed fairly stable emission reductions of around 0.33 Mt/yr between 2016 and 2022. The annual methane emission abatement from this program gradually increased 2003–2011, followed by a continued trend of methane abatement at a slower rate 2011–2022. The IEA (2024b) found that almost 2.0 Mt of methane was emitted in 2023 by the United States coal industry, and 60% of those emissions could be abated.
Table 4. (2016–2023) adoption trend.
Unit: Mt/yr methane abated
| 25th percentile | 0.46 |
| mean | 0.60 |
| median (50th percentile) | 0.60 |
| 75th percentile | 0.73 |
We found an adoption ceiling of about 40.3 Mt/yr of methane based on the IEA’s (2025) estimate for total methane emissions from the coal mine sector. We assumed that current CMM emissions would remain the same into the future with no changes in coal production or demand. Table 5 shows the adoption ceiling for coal mine methane abatement.
Even in the IEA’s (2023c) highest methane abatement energy scenario, only 93% of the methane emissions are reduced by 2050. This would still leave the coal sector releasing methane into the atmosphere. Reduced coal production will reduce the amount of methane emissions produced by the coal sector and consequently reduce the amount of methane that needs to be controlled with methane abatement. However, methane abatement will still be important for abating the remaining CMM emissions and the growing proportion of AMM emissions (IEA, 2023c, Kholod et al., 2020).
Table 5. Adoption ceiling.
Unit: Mt/yr of methane abated
| median (50th percentile) | 40.30 |
The amount of methane that could be abated from CMM varies greatly depending on global coal demand. We estimate an achievable adoption range of 2.83–4.40 Mt/yr of methane abated.The Achievable – Low value aligns with the IEA (2023c) Announced Pledges scenario, in which all announced climate policies are met and full methane abatement is employed, but net-zero emissions are not achieved. This range of high and low values was determined by taking the total methane abated in these scenarios and dividing by the difference between the target year and 2024 to determine an average amount of methane abated each year to reach the scenario target.
The Achievable – High value aligns with Ocko et al.(2021), where all economically and technically feasible methane abatement is employed by 2030. DeFabrizio et al. (2021) estimated that the degasification of underground mines and flaring would be the source of most methane abatement from coal mining, with degasification of surface mines abating a smaller proportion of methane over time. However, research from Kholod et al. (2020) suggested there will be an increase in AMM emissions as coal mines are closed. Methane emissions from AMM are not extensively monitored right now, and there is limited research on the topic. Methane abatement strategies will be needed to abate growing AMM emissions (Zhu et al, 2023).
In addition, some research suggested CMM is being underestimated, with global emissions being as high as 67 Mt/yr (Assan & Whittle, 2023). If coal demand drops by 90%, as outlined in IEA’s Net Zero Emissions scenario, total coal methane emissions would decline to 3 Mt/yr, and the use of methane abatement would reduce emissions by 2 Mt/yr, leaving only 1 Mt/yr of CMM emitted in 2050.
With growing interest and investment from governments and academia in identifying methane leaks using technologies such as satellite sensing (MethaneSAT, 2024), the opportunities for methane abatement will increase. Over 150 countries have joined the Global Methane Pledge (representing 50% of the world’s human-caused methane) to reduce methane emissions by 30% of 2020 emissions by 2030 (UNEP, 2021). The IEA (2023a) found that even in a baseline scenario, many governments have announced or put in place measures to cut methane emissions; we would expect a growing trend in global methane abatement to occur. The IEA (2024c) states that in all scenarios global coal demand will decrease. Table 6 shows the statistical low and high achievable ranges for CMM abatement based on different sources for future uptake of CMM abatement.
Table 6. Range of achievable adoption levels.
Unit: Mt/yr methane abated
| Current Adoption | 0.59 |
| Achievable – Low | 2.83 |
| Achievable – High | 4.40 |
| Adoption Ceiling | 40.30 |
We estimate that the coal industry is currently abating approximately 0.02 Gt CO₂‑eq/yr on a 100-yr basis and 0.03 Gt CO₂‑eq/yr on a 20-yr basis using methane abatement strategies. This is about 1% of total methane emissions emitted in 2024 (IEA, 2025).
As the coal industry opens or closes coal mines due to changing coal demand, the opportunities for CMM abatement projects will change along with it. If coal demand gradually drops by 2050, more than 0.12 Gt CO₂‑eq/yr of methane could be abated. However, if coal demand drops more quickly from the implementation of energy and climate policies, the methane abatement potential would drop because the coal sector is producing less methane. This is projected in the different energy scenarios modeled by the IEA (2023c). The range between the current CMM abatement and the adoption ceiling is shown in Table 7.
Table 7. Climate impact at different levels of adoption.
Unit: Gt CO₂‑eq/yr, 100-yr basis
| Current Adoption | 0.02 |
| Achievable – Low | 0.08 |
| Achievable – High | 0.12 |
| Adoption Ceiling | 1.12 |
Methane reacts with chemicals like VOCs to form tropospheric, or ground-level ozone (Fiore et al., 2002). Ground-level ozone has been linked to reduced crop growth and yields (Mills et al., 2018; Samperdo et al., 2023; Tai et al., 2021). Mitigating methane emissions from coal mines could improve food security by reducing ground-level ozone and its harmful impacts on agricultural productivity (Tai et al., 2014; Ramya et al., 2023).
Around 10% of anthropogenic methane comes from coal mines (IEA, 2024a). Methane released from coal mines contributes to ground-level ozone pollution, which can harm lung function, exacerbating conditions like asthma, bronchitis, and emphysema, and can contribute to premature mortality (Mar et al., 2022). Domingo et al. (2024) estimated that ground-level ozone accounted for about 6,600 excess deaths per year in about 400 cities globally.
Methane released from coal mines also endangers workers’ safety in the mines, increasing the possibility of explosions, which are a significant source of fatalities and injuries (CDC, 2024). In the United States, from 2006 to 2011, mine explosions were responsible for about 25% of fatalities in the mining industry (CDC, 2024). While advances in methane mitigation technologies can prevent explosions and fatalities, mines across LMICs usually do not have methane mitigation protocols in place. Installing methane abatement strategies can potentially protect workers from such explosions (Tate, 2022).
CMM abatement strategies could be implemented on a voluntary basis due to favorable natural gas prices, but if natural gas prices drop there is less economic incentive to abate methane (IEA, 2021). Without policy support enforcing methane abatement, emissions could continue, especially from VAM and AMM, which are more difficult to capture and use. Ensuring long-term monitoring and abatement of CMM can be challenging if coal mines are abandoned due to owners going bankrupt, leaving environmental damages unpaid for and remediation up to nearby communities or taxpayers (Ward et al., 2023).
Managing coal methane can have a positive impact on other solutions that reduce methane release to the atmosphere. The use of technologies such as degasification systems, methane destruction, and Leak Detection and Repair (LDAR) in the coal mine sector can demonstrate the effectiveness and economic case for employing methane abatement. This would build momentum for the widespread adoption of methane abatement because successes in the coal sector can be leveraged and applied to other sectors. In addition, LDAR is a key part in identifying where we can abate methane emissions and lessons learned from the coal sector can be applied to other sites, as well as identifying methane leaks in general.
CMM management interacts negatively with solutions that provide clean electricity as this solution captures methane that can be used as an energy source, prolonging the use of natural gas infrastructure and reducing the cost of methane as a fuel source.
Mt methane abated
CH₄ , N₂O, BC
Methane abatement strategies are a powerful tool to reduce methane emissions; however, providing a secondary source of revenue for coal mining could increase the profitability and longevity of some coal mines. A broad strategy to reduce reliance on coal as an energy resource is needed to reduce the amount of CMM generated. Even with methane abatement strategies in place, methane used as a fuel or destroyed through flaring will still emit GHGs and contribute to global climate change.
Globally, coal mines are responsible for 40 of the 354 Mt of anthropogenic methane emissions in 2024. This is equivalent to 1,116 Mt CO2-eq based on a 100-year GWP time scale. Methane emissions occur throughout the life of a coal mine and can continue after mines are closed or abandoned.
Lewis, C., Tate, R.D., and Mei, D.L. (2024). Fuel operations sector: Coal mining emissions methodology [Data set]. WattTime and Global Energy Monitor, Climate TRACE Emissions Inventory. Retrieved April 18, 2025, from Link to source: https://climatetrace.org
International Energy Agency. (2025). Global methane tracker documentation 2025 version. Link to source: https://iea.blob.core.windows.net/assets/2c0cf2d5-3910-46bc-a271-1367edfed212/GlobalMethaneTracker2025.pdf
Globally, coal mines are responsible for 40 of the 354 Mt of anthropogenic methane emissions in 2024. This is equivalent to 1,116 Mt CO2-eq based on a 100-year GWP time scale. Methane emissions occur throughout the life of a coal mine and can continue after mines are closed or abandoned.
Lewis, C., Tate, R.D., and Mei, D.L. (2024). Fuel operations sector: Coal mining emissions methodology [Data set]. WattTime and Global Energy Monitor, Climate TRACE Emissions Inventory. Retrieved April 18, 2025, from Link to source: https://climatetrace.org
International Energy Agency. (2025). Global methane tracker documentation 2025 version. Link to source: https://iea.blob.core.windows.net/assets/2c0cf2d5-3910-46bc-a271-1367edfed212/GlobalMethaneTracker2025.pdf
Coal mine methane abatement is applicable in any area with coal mines. While China and the United States are the largest coal producers, Russia, Ukraine, Kazakhstan, and India also generated more than 10 Mt CO₂‑eq (100-yr) from coal mines in 2015 (GMI, 2015).
Levels of methane emissions from coal mines can vary geographically. The greatest abatement potential is in China, Kazakhstan, Australia, and several countries in Eastern Europe and Africa (Shindell et al., 2024). However, methane abatement is recommended for all coal mining activities, and high-income countries are in a position to share supportive technologies and practices for coal mine methane abatement with other coal-producing countries to reduce methane emissions from active and abandoned or closed mines.
There is a high level of consensus about the effectiveness of methane abatement strategies. These strategies can be deployed cost effectively in many cases and have an immediate impact on reducing global temperature rise.
Authoritative sources such as the IEA (2024c) and UNEP (2021) agree that reducing methane emissions can noticeably slow global climate change. Methane is a short-lived climate pollutant that has a much stronger warming effect than CO₂ over a given time period. IEA (2023d) identified that close to 55% (22 Mt) of CMM emissions could be abated with existing technologies. However, there are significant challenges in measuring and recovering methane emissions in the coal sector. Analysis from Assan & Whittle (2023) found that global CMM emissions could be significantly higher than reported, 38–67 Mt/yr compared with the 40 Mt/yr reported by the IEA (2025).
The IEA (2023a) noted that more than half of CMM emissions could be abated through utilization, flaring, or oxidation technologies, with abatement being more practical for underground mines. Many studies (DeFabrizio et al., 2021; Malley et al., 2023; Shindell et al., 2024) have shown that methane abatement strategies can use existing technologies, often at low cost. In some countries, coal operators already identify the location and sources of CMM to meet health and safety regulations (Assan & Whittle, 2023); Setiawan & Wright (2024) noted that existing technologies such as pre-mine drainage and VAM mitigation have been proven in various places around the world over the past 25 years. According to UNEP (2021), coal methane abatement could reduce emissions by 12–25 Mt/yr, with up to 98% of the measures implemented at low cost. However, costs may vary significantly based on the available infrastructure and characteristics of an individual coal mine.
The results presented in this document summarize findings from 21 reviews and meta-analyses and 20 original studies reflecting current evidence from three countries (Australia, China, and the United States) as well as from sources examining global CMM emissions. We recognize this limited geographic scope creates bias, and hope this work inspires research and data sharing on this topic in underrepresented regions.
The type of coal mine, the amount of methane produced, and the available infrastructure greatly affect which abatement strategies are economical. Underground coal mines often produce more CMM and are likely to capture CMM using degasification systems and use it for productive purposes such as electricity generation or selling captured methane. However, VAM, which is a major part of CMM emissions, can be challenging to use for productive purposes due to the low methane concentrations. VAM requires regenerative thermal oxidation technology to effectively destroy and with more gassy coal mines. According to the IEA (2023b), technologies such as flaring and drained CMM can be used at less gassy mines with lower initial capital cost. Capturing methane for destruction has the disadvantage of not creating a source of revenue to offset the capital cost of methane abatement without a form of carbon markets in place.
More than 60% of methane-related emissions from coal mining are from the ventilation of underground coal mines. Large amounts of fresh air are used to lower the concentration of methane and reduce the risk of explosions in underground mines. This makes it challenging to destroy or use the low concentrations of VAM (UNEP, 2022). It is also challenging to capture methane from surface mines because the coal is in direct contact with the atmosphere and over a larger surface area. However, thermal oxidation systems have been used to destroy VAM (U.S. EPA, 2019) and there have been examples of degasification systems used for surface mines as well (IEA, 2023b). Methane emissions from AMM can be dealt with by flooding underground mines with water (Kholod et al., 2020) or by sealing and using capture and utilization projects (Zhu et al., 2023).
Technologies for reducing methane emissions can be divided between underground and surface coal mines:
CNX. (2024, March 20). Jumpstarting coal mine methane capture projects for beneficial end use [PowerPoint slides].Global Methane Initiative. https://www.globalmethane.org/resources/details.aspx?resourceid=5386
United Nations Economic Commission for Europe (UNECE). (2019). Best practice guidance for effective methane recovery and use from abandoned coal mines. https://unece.org/fileadmin/DAM/energy/images/CMM/CMM_CE/Best_Practice_Guidance_for_Effective_Methane_Recovery_and_Use_from_Abandoned_Coal_Mines_FINAL__with_covers_.pdf
