This solution meets all of Project Drawdown’s criteria for global climate solutions.

Use Smart & Programmable Thermostats

Sector
Buildings & Electricity
Mode
Cut Emissions
Cluster
Enhance Efficiency
Image
Hand pointing to smart thermostat on the wall
Coming Soon
On
Summary

We define Use Smart & Programmable Thermostats as reducing energy use and associated GHG emissions from heating and cooling by automatically making adjustments to the set temperature of a residential building. Smart thermostats can be remotely controlled and can adjust indoor temperature settings in response to learned occupancy patterns, while programmable thermostats require a user to manually program a temperature schedule.

Income & work,Health
Air quality
Description for Social and Search
Using smart or programmable thermostats to regularly adjust residential temperature settings for energy savings also reduces the emissions from heating and cooling residential buildings.
Overview

Residential buildings directly and indirectly generate GHG emissions through the fuels and electricity used for heating, cooling, and other functions. These emissions accounted for 12.5% of global emissions in 2021 (Ge et al., 2026). Heating is the largest residential source of operational emissions, with cooling being another major contributor (Energy Transitions Commission, 2025).

Smart and programmable thermostats reduce energy use by allowing temperatures to drift when occupants are away or asleep and restoring optimal temperatures in anticipation of occupants returning or waking. Since heating systems often rely on burning fossil fuels for heat (International Energy Agency [IEA], 2023), the emissions affected are primarily CO₂. Similarly, the emissions affected when cooling demands are reduced are primarily CO₂ from the electricity generated to power heat pumps and air conditioners. 

The amount of CO₂ saved with smart and programmable thermostats can vary substantially with occupant behavior, set points, occupancy levels, and climate (Pritoni et al., 2015; Stopps & Touchie, 2021). We used the minimum performance standard for Energy Star–certified smart thermostats, namely 8% run-time reduction for heating and 10% for cooling (Energy Star, n.d.), with run time being used as a proxy for energy savings. This is a conservative value; many studies have measured or modeled higher savings (Alhamayani et al., 2021; Pang et al., 2021). 

Owning a smart or programmable thermostat does not guarantee it will be used to adjust temperatures to save energy (Pritoni et al., 2015; Stopps & Touchie, 2021). For example, while 53% of U.S. homes own a smart or programmable thermostat, only 16% report using a smart or programmable thermostat to automatically adjust temperatures (U.S. Energy Information Administration [U.S. EIA], 2023a). We also assumed that households that do not have a smart or programmable thermostat are not manually adjusting temperatures to save energy. 

As societies electrify, smart and programmable thermostats may play an increasingly important role in shifting demand away from grid peak periods (Stopps & Touchie, 2022). This can reduce emissions even further because grids often depend more on fossil fuel peaker plants during these times. This analysis does not include such emissions reductions. 

Solution in Action

References

Alhamayani, A. D., Sun, Q., & Hallinan, K. P. (2021). Estimating smart Wi-Fi thermostat-enabled thermal comfort control savings for any residence. Clean Technologies, 3(4), 743–760. Link to source: https://doi.org/10.3390/cleantechnol3040044  

Allcott, H., & Rogers, T. (2014). The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation. American Economic Review, 104(10), 3003–3037. Link to source: https://doi.org/10.1257/aer.104.10.3003  

Bergeron, R. (2024, May 9). Installation obligatoire d’un thermostat connecté en 2027. Expertise Rénovation. Link to source: https://www.expertise-renovation.com/actualites/installation-thermostat-connecte  

Bielig, M., Kutzner, F., Klingert, S., & Kacperski, C. (2025). Understanding intention to adopt smart thermostats: The role of individual predictors and social beliefs across five EU countries: Proceedings of the 14th International Conference on Smart Cities and Green ICT Systems, 1, 36–47. Link to source: https://doi.org/10.5220/0013356200003953  

Blonz, J., Palmer, K., Wichman, C. J., & Wietelman, D. C. (2025). Smart thermostats, automation, and time-varying prices. American Economic Journal: Applied Economics, 17(1), 90–125. Link to source: https://doi.org/10.1257/app.20210618  

Chassin, D. P., Stoustrup, J., Agathoklis, P., & Djilali, N. (2015). A new thermostat for real-time price demand response: Cost, comfort and energy impacts of discrete-time control without deadband. Applied Energy, 155, 816–825. Link to source: https://doi.org/10.1016/j.apenergy.2015.06.048 

EGIA Contractor University. (2025). Average service life of residential HVAC equipment. Link to source: https://library.mycontractoruniversity.com/wp-content/uploads/2025/10/EGIA-AverageServiceLife.pdf  

Ellsworth, R. (2026, February 12). Residential HVAC industry statistics. ZipDo Education Reports. Link to source: https://zipdo.co/residential-hvac-industry-statistics/  

Energy Star. (n.d.). Energy Star® program requirements for connected thermostat products: Partner commitments. Link to source: https://www.energystar.gov/sites/default/files/asset/document/ENERGY%20STAR%20Program%20Requirements%20for%20Connected%20Thermostats%20Version%201.0_0.pdf  

Energy Transitions Commission. (2025). Achieving zero-carbon buildings: Electric, efficient and flexible [Report]. Link to source: https://static.energy-transitions.org/uploads/resources/ETC_Buildings-Decarbonisation-Report_DIGITALFINAL.pdf  

Falchetta, G., Cian, E. D., Pavanello, F., & Wing, I. S. (2024). Inequalities in global residential cooling energy use to 2050. Nature Communications, 15(1), Article 7874. Link to source: https://doi.org/10.1038/s41467-024-52028-8  

Fine, J. P., & Touchie, M. F. (2020). A grouped control strategy for the retrofit of post-war multi-unit residential building hydronic space heating systems. Energy and Buildings, 208, Article 109604. Link to source: https://doi.org/10.1016/j.enbuild.2019.109604  

Ge, M., Friedrich, J., & Vigna, L. (2026, April 27). Where do emissions come from? These charts explain greenhouse gas emissions by sector. World Resources Institute. Link to source: https://www.wri.org/insights/4-charts-explain-greenhouse-gas-emissions-countries-and-sectors   

Government of Canada. (2025). Heating and cooling with a heat pump. Link to source: https://natural-resources.canada.ca/energy-efficiency/energy-star/heating-cooling-heat-pump#hds  

Hendron, R., German, A., & Pereira, J. (2021). Modeling savings for Energy Star smart home energy management systems. National Renewable Energy Laboratory. Link to source: https://docs.nlr.gov/docs/fy21osti/79534.pdf 

Henneman, L., Choirat, C., Dedoussi, I., Dominici, F., Roberts, J., & Zigler, C. (2023). Mortality risk from United States coal electricity generation. Science, 382(6673), 941–946. Link to source: https://doi.org/10.1126/science.adf4915  

International Energy Agency. (2023). Space heating. Link to source: https://www.iea.org/reports/space-heating#dashboard  

Kini, R. L., Vlachokostas, A., Brambley, M. R., & Rogers, A. (2025). Occupant-centric demand response for thermostatically-controlled home loads. IEEE Transactions on Smart Grid, 16(3), 2234–2245. Link to source: http://doi.org/10.1109/TSG.2025.3540427  

Lee, Z. E., & Max Zhang, K. (2022). Unintended consequences of smart thermostats in the transition to electrified heating. Applied Energy, 322, Article 119384. Link to source: https://doi.org/10.1016/j.apenergy.2022.119384  

Lee, Z. E., Sun, Q., Ma, Z., Wang, J., MacDonald, J. S., & Max Zhang, K. (2020). Providing grid services with heat pumps: A review. ASME Journal of Engineering for Sustainable Buildings and Cities, 1(1), Article 011007. Link to source: https://doi.org/10.1115/1.4045819  

Lu, J., Sookoor, T., Srinivasan, V., Gao, G., Holben, B., Stankovic, J., Field, E., & Whitehouse, K. (2010). The smart thermostat: Using occupancy sensors to save energy in homes. Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, SenSys ’10, 211–224. Link to source: https://doi.org/10.1145/1869983.1870005

Mourshed, M. (2016). Climatic parameters for building energy applications: A temporal-geospatial assessment of temperature indicators. Renewable Energy, 94, 55–71. Link to source: https://doi.org/10.1016/j.renene.2016.03.021  

Nägele, F., Kasper, T., & Girod, B. (2017). Turning up the heat on obsolete thermostats: A simulation-based comparison of intelligent control approaches for residential heating systems. Renewable and Sustainable Energy Reviews, 75, 1254–1268. Link to source: https://doi.org/10.1016/j.rser.2016.11.112  

Lockheed Martin Energy. (2017). Home energy management system savings validation pilot [NYSERDA Report 17-16]. New York State Energy Research and Development Authority. Link to source: https://www.ashb.com/wp-content/uploads/2020/04/IS-2019-05.pdf  

Pang, Z., Chen, Y., Zhang, J., O’Neill, Z., Cheng, H., & Dong, B. (2021). How much HVAC energy could be saved from the occupant-centric smart home thermostat: A nationwide simulation study. Applied Energy, 283, Article 116251. Link to source: https://doi.org/10.1016/j.apenergy.2020.116251  

Peffer, T., Perry, D., Pritoni, M., Aragon, C., & Meier, A. (2013). Facilitating energy savings with programmable thermostats: Evaluation and guidelines for the thermostat user interface. Ergonomics, 56(3), 463–479. Link to source: https://doi.org/10.1080/00140139.2012.718370  

Pew Research Center. (2019). Religion and living arrangements around the world. Link to source: https://www.pewresearch.org/wp-content/uploads/sites/20/2019/12/PF_12.12.19_religious.households.FULL_.pdf  

Pritoni, M., Meier, A. K., Aragon, C., Perry, D., & Peffer, T. (2015). Energy efficiency and the misuse of programmable thermostats: The effectiveness of crowdsourcing for understanding household behavior. Energy Research & Social Science, 8, 190–197. Link to source: https://doi.org/10.1016/j.erss.2015.06.002  

Pritoni, M., Woolley, J. M., & Modera, M. P. (2016). Do occupancy-responsive learning thermostats save energy? A field study in university residence halls. Energy and Buildings, 127, 469–478. Link to source: https://doi.org/10.1016/j.enbuild.2016.05.024  

Statistics Canada. (2025). Use of thermostats [Data set]. Link to source: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3810004901  

Stopps, H., & Touchie, M. F. (2021). Residential smart thermostat use: An exploration of thermostat programming, environmental attitudes, and the influence of smart controls on energy savings. Energy and Buildings, 238, Article 110834. Link to source: https://doi.org/10.1016/j.enbuild.2021.110834  

Stopps, H., & Touchie, M. F. (2022). Load shifting and energy conservation using smart thermostats in contemporary high-rise residential buildings: Estimation of runtime changes using field data. Energy and Buildings, 255, Article 111644. Link to source: https://doi.org/10.1016/j.enbuild.2021.111644  

Tamas, R., O’Brien, W., & Quintero, M. S. (2021). Residential thermostat usability: Comparing manual, programmable, and smart devices. Building and Environment, 203, Article 108104. Link to source: https://doi.org/10.1016/j.buildenv.2021.108104  

World Bank. (n.d.). Mapping energy efficiency: A global dataset on building code effectiveness and compliance [Methodology note]. Link to source: https://www.worldbank.org/content/dam/sites/buildinggreen/doc/building_green_methodology.pdf  

United Nations. (2024). World population prospects 2024 - Special aggregates [Data set]. Link to source: https://population.un.org/wpp/downloads?folder=Special%20Aggregates&group=UN-related%20groups   

U.S. Energy Information Administration. (2018a). Table HC6.1 Space heating in U.S. homes, by housing unit type, 2015 [Data set]. Link to source: https://www.eia.gov/consumption/residential/data/2015/  

U.S. Energy Information Administration. (2018b). Table HC7.1 Air conditioning in U.S. homes by housing unit type, 2015 [Data set]. Link to source: https://www.eia.gov/consumption/residential/data/2015/  

U.S. Energy Information Administration. (2023a). Table HC6.1 Space heating in U.S. homes, by housing unit type, 2020 [Data set]. Link to source: https://www.eia.gov/consumption/residential/data/2020/hc/pdf/HC%206.1.pdf  

U.S. Energy Information Administration. (2023b). Table HC7.1 Air conditioning in U.S. homes, by housing unit type, 2020 [Data set]. Link to source: https://www.eia.gov/consumption/residential/data/2020/hc/pdf/HC%207.1.pdf  

U.S. Environmental Protection Agency. (2024). Power sector programs—Progress report. Link to source: https://www.epa.gov/power-sector/progress-report  

Wang, C., Pattawi, K., & Lee, H. (2020). Energy saving impact of occupancy-driven thermostat for residential buildings. Energy and Buildings, 211, Article 109791. Link to source: https://doi.org/10.1016/j.enbuild.2020.109791  

Yuan, Y., Song, C., Gao, L., Zeng, K., & Chen, Y. (2024). A review of current research on occupant-centric control for improving comfort and energy efficiency. Building Simulation, 17(10), 1675–1692. Link to source: https://doi.org/10.1007/s12273-024-1170-1  

Credits

Lead Fellow

  • Heather McDiarmid, Ph.D

Contributors

  • Ruthie Burrows, Ph.D.

  • James Gerber, Ph.D.

  • Daniel Jasper

  • Alex Sweeney

Internal Reviewers

  • Henry Igugu, Ph.D.

  • Amanda D. Smith, Ph.D.

  • Christina Swanson, Ph.D.

Effectiveness

For heating, 0.23 t CO₂‑eq/yr (20- and 100-yr basis) is reduced for every smart or programmable thermostat in use (Table 1a). This is a weighted global average based on the proportion of homes that use different sources of energy for space heating and assumes an 8% reduction in heating energy with a smart or programmable thermostat (Energy Star, n.d.). 

For cooling, 0.091 t CO₂‑eq/yr is reduced for every smart or programmable thermostat in use (100-year basis, 0.092 t CO₂‑eq/yr on a 20-yr basis) (Table 1b). This is a weighted global average based on regional electricity demand for space cooling and regional electricity grid emission factors. The analysis assumes a 10% reduction in cooling energy with a smart or programmable thermostat (Energy Star, n.d.).

The effectiveness of smart or programmable thermostats at reducing emissions will vary based on total heating and cooling demand. This is a function of climate and building performance as well as occupant behaviors (Hendron et al., 2021). Occupants may, for example, differ in how much they allow temperatures to drift while away or at night, how frequently overrides are used, and the schedules on which programming is based (Hendron et al., 2021).

Table 1. Effectiveness at reducing emissions from heating and cooling.

Unit: t CO₂‑eq /smart or programmable thermostat used to save energy for heating/yr, 100-yr basis

Mean 0.23

Unit: t CO₂‑eq )/smart or programmable thermostat used to save energy on cooling/yr, 100-yr basis

Mean 0.091
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Cost

A smart or programmable thermostat for heating will save an average household US$370/t CO₂‑eq reduced (Table 2a). A smart or programmable thermostat for heating has an average initial cost of US$74, and households that adopt and use these thermostats to save on energy will spend on average US$89 less per year on heating. Assuming a 15-year lifespan (EGIA Contractor University, 2025), this results in a net US$84/yr savings.

We assumed that half of adopting households worldwide purchase a smart or programmable thermostat to use in their homes and the other half already own a smart or programmable thermostat and start using them to save energy with programmed setbacks. This is consistent with US statistics that show 55% of households with heating have a smart or programmable thermostat but only 16% use one to adjust heating temperatures, with most using one set temperature most of the time (U.S. EIA, 2023a). 

A smart or programmable thermostat for cooling will save a household US$230/t CO₂‑eq reduced (see Table 2a). The average initial cost for a smart or programmable thermostat for cooling is US$58, and will save a household an average of US$25/yr on cooling. Assuming a 15-year lifespan, this results in a net US$21/yr savings for the household.

For cooling, the initial cost assumes one-third of homes purchase a smart or programmable thermostat for a central air conditioning system, one-third purchase such a thermostat for a window or portable air conditioner, and one third use an existing smart or programmable thermostat but change behaviors to start using the programming feature. Similar to heating, 60% of U.S. households with cooling have a smart or programmable thermostat but only 15% use one to adjust cooling temperatures (U.S. EIA, 2023b). 

Table 2. Cost per unit climate impact for heating and cooling. Negative values reflect cost savings.

Unit: 2023 US$/t CO₂‑eq , 100-year basis

Mean -370

Unit: 2023 US$/t CO₂‑eq , 100-year basis

Mean -230
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Learning Curve

Insufficient data exist to quantify the learning curve for smart or programmable thermostats. 

Speed of Action

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.

Use Smart & Programmable Thermostats is a GRADUAL climate solution. It has a steady, linear impact on the atmosphere. 

Caveats

Smart or programmable thermostats may be more difficult to implement in multiunit residential buildings with centralized heating and cooling systems in which units do not have temperature control (Fine & Touchie, 2020). Additionally, some existing space heating systems such as fireplaces and wood stoves may not be compatible with programmable thermostats. 

The Government of Canada (2025) recommends minimizing temperature setbacks for heat pumps or programming the return to normal temperatures in stages to avoid triggering the use of less efficient backup heating systems. 

This solution depends on households programming their thermostat or directing a smart thermostat to save energy. As with any outcome that depends on behavior change, post-intervention persistence can decay over time (Allcott & Rogers, 2014). Comfort concerns, changes to schedules, low perceived benefits, and lack of perceived control over heating and cooling systems are common reasons why households inactivate thermostat programming (Heatherly et al., 2023; Peffer et al., 2013; Pritoni et al., 2015; Stopps & Touchie, 2021). 

Some studies show little to no change in energy use with programmable thermostats, particularly if the thermostats are not easy to use (Peffer et al., 2013). Energy savings setbacks are more likely to be used with smart thermostats than programmable ones (Stopps & Touchie, 2021; Tamas et al., 2021), likely because of improved ease of use and increased automation. 

Use of smart and programmable thermostats reduces the emissions from operating buildings. However, these reductions pale in comparison to those offered by heat pumps and decarbonizing the electricity sector by adopting solutions such as distributed solar PV, utility-scale solar PV, onshore wind, and offshore wind.

Current Adoption

We estimated that 140 million households worldwide use smart or programmable thermostats to save energy for heating (Table 3a) and 30 million use them to save energy for cooling (Table 3b). 

The climate impact of this solution depends on households not only adopting the technology, but also using it to regularly adjust temperatures with the goal of saving energy. Where only adoption values exist, we assumed use patterns are similar to those in the United States, where 25–29% households that own a smart or programmable thermostat are using the programming feature (U.S. EIA, 2023a; U.S. EIA, 2023b).

For adoption, we estimated the number of households with smart or programmable thermostats in high-income countries separately from low- and middle-income countries and combined them to get a global total. In each case, we applied the average smart or programmable thermostat use rate for the group of countries to their estimated number of households that require heating or cooling. 

These estimates are based on data from seven studies covering different geographies and spanning 2017–2025. 

Table 3. Current adoption level (2025).

Unit: smart or programmable thermostats used for the purposes of saving energy on heating 

Total 140,000,000

Unit: smart or programmable thermostats used for the purposes of saving energy on cooling

Total 30,000,000
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Adoption Trend

We estimate that globally, each year 1.4 million households start using smart or programmable thermostats to save on heating (Table 4a) and 0.60 million households start using them to save on cooling (Table 4b).

These data are based on surveys for heating and cooling covering 2015–2020 in the United States (U.S. EIA 2018b, 2018a, 2023b, 2023a) and 2007–2023 in Canada (Statistics Canada, 2025). Due to lack of data, we were not able to estimate adoption trends for low- and middle-income countries, and assumed the trend is negligible. 

Table 4. Current adoption trend (2007–2023).

Unit: smart or programmable thermostats put to use for saving energy on heating/yr 

Total 1,400,000

Unit: smart or programmable thermostats put to use for saving energy on cooling/yr

Total 600,000
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Adoption Ceiling

If every household that currently relies on heating were to adopt and use smart or programmable thermostats to save energy, the total adoption would be 650 million households (Table 5a). This is based on the IEA’s estimate that 40% of households worldwide require space heating (World Bank, n.d.), combined with regional population estimates (United Nations, 2024), and estimates for household sizes by region (Pew Research Center, 2019).

Similarly for cooling, if every household that currently uses air conditioning were to adopt and use smart or programmable thermostats to save energy, the total adoption would be 580 million households (Table 5b). This is based on Falchetta et al.’s (2024) estimate that 35% of households worldwide currently have space cooling, combined with population and household size estimates (Pew Research Center, 2019; United Nations, 2024). This analysis does not reflect anticipated growing demand for space cooling with rising populations, rising affluence in low- and middle-income countries, and rising temperatures (Falchetta et al., 2024).

Table 5. Adoption ceiling: upper limit for adoption level.

Unit: smart or programmable thermostats put to use for saving energy on heating

Total 650,000,000

Unit: smart or programmable thermostats put to use for saving energy on cooling

Total 580,000,000
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Achievable Adoption

For heating, we estimate that use of smart or programmable thermostats to save on energy could reach 290 to 510 million households globally (Table 6a). In high income countries, this assumes 65–100% of households with heating needs adopt and use thermostats to save energy. At the low end, this represents the reported rate of regular setback use for heating homes in the state of New York (Lockheed Martin Energy, 2017), and we assume all heating households could program thermostats to save energy at the high end. In low and middle income countries, we assume 16–48% of households with heating needs adopt and use smart or programmable thermostats to save energy. This is based on today’s estimated smart and programmable thermostat adoption and use rate in the United States and Canada respectively (Statistics Canada, 2025; U.S. EIA, 2023a).

For cooling, we estimate that use of smart or programmable thermostats to save on energy could reach 190–510 million households globally (see Table 6b). In high income countries, this assumes 75–100% of households with cooling systems use thermostats to save energy for cooling. At the low end, this represents the reported rate of regular setback use for cooling homes in the state of New York (Lockheed Martin Energy, 2017) and we assume all households adopt and use smart or programmable thermostats at the high end. In low and middle income countries, we assume households adopt and use smart and programmable thermostats at a rate of 15 and 75%, representing the current rates for the United States and the state of New York, respectively (Lockheed Martin Energy, 2017; U.S. EIA, 2023a).

Table 6. Range of achievable adoption levels. 

Unit: smart or programmable thermostats put to use for saving energy on heating

Current adoption 140,000,000
Achievable – low 290,000,000
Achievable – high 510,000,000
Adoption ceiling 650,000,000

Unit: smart or programmable thermostats put to use for saving energy on cooling

Current adoption 30,000,000
Achievable – low 190,000,000
Achievable – high 510,000,000
Adoption ceiling 580,000,000
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For space heating, current adoption and use of a smart or programmable thermostat to save energy has an estimated climate impact of 0.033 Gt CO₂‑eq/yr globally (100- and 20-year basis; Table 7a). If all households with heating were to adopt and use these thermostats, the estimated climate impact would be 0.15 Gt CO₂‑eq/yr (100- and 20-year basis). We estimate the achievable range to be 0.065–0.12 Gt CO₂‑eq/yr (100- and 20-year basis). 

For space cooling, current adoption and use of a smart or programmable thermostat to save energy has an estimated climate impact of 0.0028 Gt CO₂‑eq/yr globally (100- and 20-year basis;Table 7a). If all households with heating were to adopt and use these thermostats, the estimated climate impact would be 0.052 Gt CO₂‑eq/yr (100-year basis) and 0.053 Gt CO₂‑eq/yr (20-year basis). We estimate the achievable range to be 0.017–0.46 Gt CO₂‑eq/yr (100-year basis) and 0.018–0.47 Gt CO₂‑eq/yr (20-year basis). 

The impact from heating is greater than the impact from cooling because there are more households that use heating and more energy is needed on average per household for heating. 

Table 7. Climate impact at different levels of adoption.

Unit: Gt CO₂‑eq )/yr for heating, 100-yr basis

Current adoption 0.033
Achievable – low 0.065
Achievable – high 0.12
Adoption ceiling 0.15

Unit: Gt CO₂‑eq/yr for cooling, 100-yr basis

Current adoption 0.0028
Achievable – low 0.017
Achievable – high 0.046
Adoption ceiling 0.052
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Additional Benefits

Income and Work

When used as intended, smart and programmable thermostats can save money by saving energy (Blonz et al., 2025; Lu et al., 2010; Wang et al., 2020). The cost savings can vary depending on the type of thermostat, fuel used for heating, geographic location, and sources of energy used to generate electricity. In our estimates, on average, households using smart or programmable thermostats could save US$84/yr on heating and US$21/yr on cooling (see Table 2a). Where time-of-use electricity pricing exists, smart and programmable thermostats can be used to heat or cool a home in advance of peak periods to save even more (Chassin et al., 2015). 

Health

A reduction in energy demand from smart thermostats may lower air pollution and limit exposure to pollutants such as lead and fine particulate matter generated by fossil fuel-based power plants, thereby improving health in nearby communities (Henneman et al., 2023; U.S. Environmental Protection Agency [U.S. EPA], 2024). 

Air Quality

Reducing energy use can reduce climate and air pollutants associated with burning fossil fuels, such as CO₂, nitrogen oxides, methane, lead, and fine particulate matter (U.S. EPA, 2024).

Risks

Smart and programmable thermostats have the potential to increase peak demand for electricity when programmed around common schedules. For example, thermostats may be programmed to raise temperatures in the early morning in winter when electricity grids are already strained (Lee & Max Zhang, 2022). Conversely, grid-integrated thermostats can reduce grid peaks by optimizing when heating or cooling occurs while maintaining occupant comfort (Kini et al., 2025).

Interactions with Other Solutions

Competing

There are diminishing returns as solutions that reduce heating and cooling loads are combined. When smart or programmable thermostats reduce the energy and emissions from heating and cooling, they also reduce the emissions savings these other solutions achieve. 

Consensus
Dashboard

Solution Basics

smart or programmable thermostat programmed to adjust temperatures

t CO₂-eq (100-yr)/unit/yr
0.23
units
Current 1.4×10⁸ 02.9×10¹⁰5.1×10⁸
Achievable (Low to High)

Climate Impact

Gt CO₂-eq (100-yr)/yr
Current 0.033 0.0650.12
US$ per t CO₂-eq
-370
Gradual

CO₂ , CH₄, N₂O

Solution Basics

smart or programmable thermostat programmed to adjust temperatures

t CO₂-eq (100-yr)/unit/yr
0.091
units
Current 3.0×10⁷ 01.9×10⁸5.1×10⁸
Achievable (Low to High)

Climate Impact

Gt CO₂-eq (100-yr)/yr
Current 0.003 0.0170.046
US$ per t CO₂-eq
-230
Gradual

CO₂ , CH₄, N₂O

Trade-offs

When large numbers of households use smart or programmable thermostats to save energy, it can unintentionally cause spikes in electricity demand when heating systems are simultaneously turned on to return temperatures to normal (Lee & Max Zhang, 2022). These spikes can increase overall grid capacity needs and increase demand from fossil-fueled peaking generation. Grid-interactive smart thermostats can reduce these spikes through grid level energy management (Lee et al., 2020). 

Action Word
Use
Solution Title
Smart & Programmable Thermostats
Classification
Highly Recommended

Lawmakers and Policymakers
  • Offer one-stop educational resources for thermostats; offer demonstrations for installation and programming through online videos and in-person demos; clearly state benefits of smart and programmable thermostats, highlighting the cost savings, social benefits, and environmental impacts.
  • Set clear and measurable targets for building efficiency, emissions reduction, and deployment of smart and programmable thermostats.
  • Ensure public procurement standards require smart and programmable thermostats for new construction; require retrofits for existing public buildings.
  • Create regulatory standards and building codes that encourage, incentivize, and/or require the use of smart and programmable thermostats, especially in new construction.
  • Periodically update codes, policies, and public guidance to keep pace with adoption and technology advances.
  • Encourage utilities to incentivize smart and programmable thermostat uptake and use for demand management.
  • Consider offering subsidies that allow for flexible implementation or selective applicability within national systems; ensure subsidy programs are designed based on scientific evidence showing they will have a positive impact on adoption for the intended beneficiaries; target subsidies to low- and middle-income households and simultaneously offer incentives for broadband and digital connectivity; ensure financial incentives cover both new installations and retrofits.
  • Focus broader policies on energy efficiency through the use of intelligent control.
  • Create regulatory standards and building codes that encourage, incentivize, and/or require the use of smart and programmable thermostats, especially in new construction.

Further information:

Practitioners
  • Offer one-stop educational resources for thermostats; offer demonstrations for installation and programming through online videos and in-person demos; clearly state benefits of smart and programmable thermostats highlighting the cost savings, social benefits, and environmental impacts.
  • Offer free or discounted thermostats in electrically heated homes and homes with cooling in exchange for control when the electricity grid is strained. 
  • Ensure customers know they can upgrade their thermostats; provide recommendations to customers on purchasing, installing, and using smart and programmable thermostats; inform customers of public or private incentives for purchases and/or installation; educate customers on the savings, social, and environmental benefits of installation. 
  • Develop or offer easy-to-use smart and programmable thermostat systems; provide scheduled maintenance services for customers; bundle services with heating and cooling system services when possible; ensure customers have the option to review products and services online.
  • Offer thermostats that are compatible with widely used electronic devices such as laptops and smart phones; incorporate Wi-Fi, bluetooth, and the Internet of Things into thermostats, allow for remote control and visibility via smartphone apps.
  • Provide 0% financing options for bundled services, including thermostats and/or related energy efficiency measures.
  • Ease the learning curve for customers by providing clear, concise instructions; ensure elderly customers are comfortable with using the thermostat before leaving after installation.
  • Use customer feedback and work with manufacturers to simplify interface designs and improve functionality. 
  • Advertise for smart and programmable thermostats depicting individual savings on heating and cooling; use social media to reach broader audiences.
  • Create algorithms that can save energy and money for consumers by responding to time of use, customer behavior, and current weather; ensure thermostats have the ability to be updated for future improvements to the software.
  • When installing a thermostat, ensure it is easily accessible and will not be obstructed.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Business Leaders
  • Help socialize the importance of smart and programmable thermostats by incorporating them into corporate net zero strategies; highlight the use of smart and programmable thermostats in public communications.
  • Invest in or offer grants to start-ups seeking to deploy smart and programmable thermostats; invest in research and development to determine optimal user interfaces and/or algorithms for smart and programmable thermostats.
  • Offer pro bono business advice to nonprofit organizations working to improve building efficiency and deploy smart and programmable thermostats.
  • Offer employees information or benefits for upgrading their thermostats at home.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Nonprofit Leaders
  • Offer one-stop educational resources for thermostats; offer demonstrations for installation and programming through online videos and in-person demos; clearly state benefits of smart and programmable thermostats highlighting the cost savings, social benefits, and environmental impacts.
  • Help policymakers set clear and measurable targets for building efficiency, emissions reduction, and the deployment of smart and programmable thermostats.
  • Advocate for and help design regulatory standards and building codes that encourage, incentivize, and/or require the use of smart and programmable thermostats, especially in new construction.
  • Assist regulators in periodically updating codes, policies, and public guidance to keep pace with adoption and technology advances.
  • Advocate for subsidies that allow for flexible implementation or selective applicability within national systems; help ensure subsidy programs are designed based on scientific-evidence showing they will have a positive impact on adoption for the intended beneficiaries; recommend that subsidies be targeted to low- and middle-income households and simultaneously offer incentives for broadband and digital connectivity; help ensure financial incentives cover both new installations and retrofits.
  • Help shift policy frameworks to focus on energy efficiency through the use of intelligent control.
  • Conduct research to improve adoption and use of smart and programmable thermostats, paying close attention to how user interfaces impact behavior.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Investors
  • Finance only new construction and retrofits that use smart or programmable thermostats as well as other energy-efficient heating and cooling technologies and practices.
  • Invest in research and development to improve smart and programmable thermostat design and user interface.
  • Invest in or offer grants to start-ups seeking to deploy smart and programmable thermostats.
  • Issue or buy green bonds to deploy capital to projects that use smart or programmable thermostats and integrate other energy-efficient heating and cooling technologies and practices.
  • Offer preferential loan agreements for developers using smart or programmable thermostats, energy efficient building practices, and other related climate solutions.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Philanthropists and International Aid Agencies
  • Offer one-stop educational resources for thermostats; offer demonstrations for installation and programming through online videos and in-person demos; clearly state benefits of smart and programmable thermostats, highlighting the cost savings, social benefits, and environmental impacts.
  • Offer grants or access to no-interest financing for retrofits and installations of smart and programmable thermostats; ensure financial support for projects involving building retrofits or new construction require the use of smart or programmable thermostats.
  • Offer grants of financing for research and development to improve smart and programmable thermostat design and user interface.
  • Invest in or offer grants to start-ups seeking to deploy smart or programmable thermostats.
  • Issue or buy green bonds to deploy capital to projects that use smart or programmable thermostats and integrate other energy-efficient heating and cooling technologies and practices.
  • Offer preferential loan agreements for developers using smart or programmable thermostats, energy efficient building practices, and other related climate solutions.
  • Help policymakers set clear and measurable targets for building efficiency, emissions reduction, and deployment of smart and programmable thermostats.
  • Advocate for and help design regulatory standards and building codes that encourage, incentivize, and/or require the use of smart and programmable thermostats, especially in new construction.
  • Help regulators periodically update codes, policies, and public guidance to keep pace with adoption and technology advances.
  • Advocate for subsidies that allow for flexible implementation or selective applicability within national systems; help ensure subsidy programs are designed based on scientific evidence showing they will have a positive impact on adoption for the intended beneficiaries; recommend that subsidies be targeted to low- and middle-income households and simultaneously offer incentives for broadband and digital connectivity; help ensure financial incentives cover both new installations and retrofits.
  • Help shift policy frameworks to focus on energy efficiency through the use of intelligent control.
  • Conduct research to improve adoption and use of smart and programmable thermostats, paying close attention to how user interfaces impact behavior.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Thought Leaders
  • Help create educational efforts and resources for smart and programmable thermostats; offer demonstrations for installation and programming through online videos and in-person demos; clearly state benefits of smart and programmable thermostats, highlighting the cost savings, social benefits, and environmental impacts.
  • Help policymakers set clear and measurable targets for building efficiency, emissions reduction, and deployment of smart and programmable thermostats.
  • Advocate for and help design regulatory standards and building codes that encourage, incentivize, and/or require the use of smart or programmable thermostats, especially in new construction.
  • Help regulators periodically update codes, policies, and public guidance to keep pace with adoption and technology advances.
  • Advocate for subsidies that allow for flexible implementation or selective applicability within national systems; help ensure subsidy programs are designed based on scientific evidence showing they will have a positive impact on adoption for the intended beneficiaries; recommend that subsidies be targeted to low- and middle-income households and simultaneously offer incentives for broadband and digital connectivity; help ensure financial incentives cover both new installations and retrofits.
  • Help shift policy frameworks to focus on energy efficiency through the use of intelligent control.
  • Conduct research to improve adoption and use of smart and programmable thermostats, paying close attention to how user interfaces impact behavior.
  • Create or join green building certification schemes, green building councils, and/or public-private partnerships that offer information, training, and general support for smart and programmable thermostats.

Further information:

Technologists and Researchers
  • Develop smart systems that integrate thermostats into a systems level perspective, allowing thermostats to make adjustments based on household energy consumption; design these systems for automatic adjustments to energy usage depending on price signals, energy spikes, appliance use, charging time (e.g., for EVs), weather patterns, occupancy, and related factors; ensure thermostats can automatically update utility rates, weather forecasts, and other data that support cost- and energy-efficient use.
  • Develop smart thermostats and smart home systems that can be grid-integrated for demand management. 
  • Design software for smart and programmable thermostats that provides detailed feedback and individualized suggestions to consumers on energy usage, costs, and estimated savings.
  • Research how users interact with smart and programmable thermostats; examine impact of user interfaces (UIs) on consumer use; develop simplified UIs to facilitate adoption.
  • Research the relationship between household decision-making and smart or programmable thermostat adoption; highlight recommendations for reaching household decision-makers.

Further information:

Communities, Households, and Individuals
  • Upgrade to a smart or programmable thermostat, learn how to use its features, set the programming accordingly, and override the system as little as possible.
  • Consult and work with licensed heating and cooling system installers to determine best available options for smart or programmable thermostats, installation, and maintenance.
  • Make sure your thermostat is installed in a position that allows for easy, unobstructed access.
  • Take advantage of public incentives such as subsidies or low-interest financing for installation, retrofits, and/or maintenance.
  • If provided by your smart thermostat or energy provider, opt into alerts that inform you of abnormally high energy usage which can be an early warning of problems with a heating and cooling system.
  • Take time to understand your smart or programmable thermostat; use profile settings and scheduling to optimize energy and money savings.
  • If you own a smart thermostat, opt into demand response programs to lower energy consumption during peak times; turn on notifications for heating and cooling system maintenance.
  • Share your experience with your neighbors, community, and social networks, and offer help in programming a thermostat where appropriate.
  • If possible, regularly schedule heating and cooling system maintenance and upgrades, including for related equipment such as thermostats. 
  • If smart or programmable thermostats are not an option, manually adjust your thermostat to reduce energy consumption when you’re not home, during peak hours, or to reflect weather conditions; consult your energy provider for tips on thermostat adjustments that can save money and energy.

Further information:

“Take Action” Sources
Evidence Base

Consensus of effectiveness in reducing GHG emissions: High 

There is strong consensus that smart and programmable thermostats will reduce energy use and associated emissions when used to regularly adjust temperatures. 

Numerous studies have demonstrated that energy savings with smart or programmable thermostats can be significant but also vary significantly. For example, Yuan et al.’ (2024)’s review of occupancy-based control studies for heating, air conditioning and ventilation systems found energy savings of 7–44%. (Pang et al., 2021) noted that factors such as climate conditions, building characteristics, occupant behaviors, and setback temperatures can affect energy savings outcomes. 

Pritoni et al. (2016) found that field study outcomes for smart thermostats can differ from the outcomes predicted by models, which are the most common approach to estimating energy savings and, by extension, emissions savings. Factors that can account for some of this discrepancy include comfort preferences, overrides, poor programming, and occupancy (Pritoni et al., 2015; Stopps & Touchie, 2021). 

A major barrier to realizing energy savings with smart or programmable thermostats is getting households to use the programming feature. Bielig et al. (2025) demonstrated that smart thermostat adoption and use are tied to perceived value, usefulness, and ease of use in European Union countries. Meanwhile, Pritoni et al. (2015) highlighted how many U.S. households have a poor understanding of how and when programmed set points save energy, and identified challenges with programming thermostats and comfort concerns as barriers to their use. Smart thermostats that learn occupant behaviors and preferences have shown to be easier to use than programmable thermostats (Tamas et al., 2021) and can achieve higher energy savings with higher thermal comfort (Nägele et al., 2017).

The results presented in this document summarize findings from five original studies, 10 reports, nine databases, two market research reports, and 11 product information web pages. This reflects current evidence from 11 countries, primarily high-income countries, and seven global regions. We recognize this limited geographic scope creates bias, and hope this work inspires research and data sharing on this topic in underrepresented regions.

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Deploy Precision Fermentation

Sector
Food, Agriculture, Land & Ocean (FALO)
Mode
Cut Emissions
Cluster
Curb Growing Demands
Image
Peatland
Coming Soon
On
Description for Social and Search
The Drawdown Explorer’s Deploy Precision Fermentation assessment will be coming soon.
Solution in Action
Speed of Action
Caveats
Risks
Consensus
Trade-offs
Action Word
Deploy
Solution Title
Precision Fermentation
Classification
Highly Recommended

Lawmakers and Policymakers

Practitioners

Business Leaders

Nonprofit Leaders

Investors

Philanthropists and International Aid Agencies

Thought Leaders

Technologists and Researchers

Communities, Households, and Individuals
Coming Soon Label
Coming Soon

Mobilize Electric Buses

Sector
Transportation
Mode
Cut Emissions
Cluster
Fuel Switching
Image
Peatland
Coming Soon
On
Description for Social and Search
Mobilize Electric Buses is a Highly Recommended climate solution.
Solution in Action
Speed of Action
Caveats
Risks
Consensus
Trade-offs
Action Word
Mobilize
Solution Title
Electric Buses
Classification
Highly Recommended

Lawmakers and Policymakers

Practitioners

Business Leaders

Nonprofit Leaders

Investors

Philanthropists and International Aid Agencies

Thought Leaders

Technologists and Researchers

Communities, Households, and Individuals
Coming Soon Label
Coming Soon

Increase Urban Trees

Sector
Nature-Based Carbon Removal
Cluster
Restore & Manage Ecosystems
Image
Peatland
Coming Soon
On
Description for Social and Search
Increase Urban Vegetation is a Highly Recommended climate solution.
Solution in Action

Methods and Supporting Data

Methods and Supporting Data

Speed of Action
Caveats
Risks
Consensus
Trade-offs
Action Word
Increase
Solution Title
Urban Trees
Classification
Highly Recommended

Lawmakers and Policymakers

Practitioners

Business Leaders

Nonprofit Leaders

Investors

Philanthropists and International Aid Agencies

Thought Leaders

Technologists and Researchers

Communities, Households, and Individuals
Updated Date
Coming Soon Label
Coming Soon

Deploy Agrivoltaics

Sector
Electricity
Mode
Cut Emissions
Cluster
Shift Production
Image
Peatland
Coming Soon
On
Description for Social and Search
The Deploy Agrivoltaics solution is coming soon.
Solution in Action

Methods and Supporting Data

Methods and Supporting Data

Speed of Action
Caveats
Additional Benefits
Risks
Consensus
Trade-offs
Action Word
Deploy
Solution Title
Agrivoltaics
Classification
Highly Recommended
Updated Date
Coming Soon Label
Coming Soon

Deploy Biomass Crops on Degraded Land

Sector
Nature-Based Carbon Removal
Mode
Remove Carbon
Cluster
Use Degraded Land
Image
Tree plantation
Coming Soon
On
Description for Social and Search
The Deploy Biomass Crops on Degraded Land solution is coming soon.

Methods and Supporting Data

Methods and Supporting Data

Action Word
Deploy
Solution Title
Biomass Crops on Degraded Land
Classification
Highly Recommended
Updated Date
Coming Soon Label
Coming Soon

Deploy Silvopasture

Sector
Nature-Based Carbon Removal
Mode
Remove Carbon
Cluster
Shift Agriculture Practices
Image
Cows grazing among trees
Coming Soon
Off
Summary

We define the Deploy Silvopasture solution as the adoption of agroforestry practices that add trees to grazing land, including planted pastures and natural rangelands. (Note that this solution does NOT include creating forested grazing land by thinning existing forest; this is a form of deforestation and not desirable in terms of climate.) Some silvopastures are open savannas, while others are dense, mature tree plantations. The trees may be planted or managed to naturally regenerate. Some silvopasture systems have been practiced for thousands of years, while others have been recently developed. All provide shade to livestock; in some systems, the trees feed livestock, produce timber or crops for human consumption, or provide other benefits. New adoption is estimated from the 2025 level as a baseline which is therefore set to zero.

Income & work,Food security
Nature protection,Animal well-being,Water quality
Description for Social and Search
Deploy Silvopasture is a Highly Recommended climate solution. It enhances carbon storage by adding trees to grazing land, including planted pastures and natural rangelands.
Overview

In silvopasture systems, trees are planted or allowed to naturally regenerate on existing pasture or rangeland. Tree density is generally less than forest, allowing sunlight through for good forage growth.

Silvopasture has multiple climate impacts, though carbon sequestration is the only one which has been thoroughly studied across all climates and sub-practices.

Silvopasture sequesters carbon in both soil and woody biomass. Carbon sequestration rates are among the highest of any farming system (Toensmeier, 2017). The lifetime accumulation of carbon in both soils and biomass is higher than for managed grazing alone (Montagnini et al., 2019; Nair et al., 2012).

Silvopasture can also reduce GHG emissions, though not in every case. We do not include emissions reductions in this analysis.

Conversion from pasture to silvopasture slightly increases capture and storage of methane in soils (Bentrup and Shi, in press). In addition, in fodder subtypes of silvopasture systems, ruminant livestock consume tree leaves or pods. Many, but not all, of the tree species used in these systems have tannin content that reduces emissions of methane from enteric fermentation (Jacobsen et al., 2019). 

Some subtypes of silvopasture reduce nitrous oxide emissions from manure and urine, as grasses and trees capture nitrogen that microbes would otherwise convert to nitrous oxide. There are also reductions to nitrous oxide emissions from soils: 76–95% in temperate silvopastures and 16–89% in tropical-intensive silvopastures (Ansari et al., 2023; Murguietio et al., 2016).

Many silvopasture systems increase productivity of milk and meat. Yield increases can reduce emissions from deforestation by growing more food on existing farmland, but in some cases can actually worsen emissions if farmers clear forests to adopt the profitable practice (Intergovernmental Panel on Climate Change [IPCC], 2019). The yield impact of silvopasture varies with tree density, climate, system type, and whether the yields of other products (e.g., timber) are counted as well (Rojas et al., 2022). 

References

Ansari, J., Udawatta, R. P., & Anderson, S. H. (2022). Soil nitrous oxide emission from agroforestry, rowcrop, grassland and forests in North America: a review. Agroforestry Systems, 97(8), 1465–1479. Link to source: https://doi.org/10.1007/s10457-023-00870-y

Basche, A., Tully, K., Álvarez-Berríos, N. L., Reyes, J., Lengnick, L., Brown, T., Moore, J. M., Schattman, R. E., Johnson, L. K., & Roesch-McNally, G. (2020). Evaluating the untapped potential of US conservation investments to improve soil and environmental health. Frontiers in Sustainable Food Systems, 4, 547876. Link to source: https://doi.org/10.3389/fsufs.2020.547876 

Batcheler, M., Smith, M. M., Swanson, M. E., Ostrom, M., & Carpenter-Boggs, L. (2024). Assessing silvopasture management as a strategy to reduce fuel loads and mitigate wildfire risk. Scientific Reports, 14(1), 5954. Link to source: https://doi.org/10.1038/s41598-024-56104-3

Bentrup, G. & Shi, X. (in press). Multifunctional buffers: Design guidelines for buffers, corridors and greenways. USDA Forest Service. 

Bostedt, G., Hörnell, A., & Nyberg, G. (2016). Agroforestry extension and dietary diversity–an analysis of the importance of fruit and vegetable consumption in West Pokot, Kenya. Food Security, 8, 271–284. Link to source: https://doi.org/10.1007/s12571-015-0542-x

Briske, D. D., Vetter, S., Coetsee, C., & Turner, M. D. (2024). Rangeland afforestation is not a natural climate solution. Frontiers in Ecology and the Environment. Link to source: https://doi.org/10.1002/fee.2727

Cadavid, Z., & BE, S. T. (2020). Sistemas silvopastoriles: aspectos teóricos y prácticos. CIPAV. Link to source: https://cipav.org.co/sdm_downloads/sistemas-silvopastoriles-aspectos-teoricos-y-practicos/

Cardinael, R., Umulisa, V., Toudert, A., Olivier, A., Bockel, L., & Bernoux, M. (2019). Revisiting IPCC Tier 1 coefficients for soil organic and biomass carbon storage in agroforestry systems. Environmental Research Letters, 13(12), 124020. Link to source: https://doi.org/10.1088/1748-9326/aaeb5f

Chapman, M., Walker, W.S., Cook-Patton, S.C., Ellis, P.W., Farina, M., Griscom, B.W., & Baccani, A. (2019). Large climate mitigation potential from adding trees to agricultural lands Global Change Biology, 26(80), 4357–4365. Link to source: https://doi.org/10.1111/gcb.15121

Chatterjee, N., Nair, P. R., Chakraborty, S., & Nair, V. D. (2018). Changes in soil carbon stocks across the forest-agroforest-agriculture/pasture continuum in various agroecological regions: A meta-analysis. Agriculture, ecosystems & environment, 266, 55–67. Link to source: https://doi.org/10.1016/j.agee.2018.07.014

Damania, Richard; Polasky, Stephen; Ruckelshaus, Mary; Russ, Jason; Amann, Markus; Chaplin-Kramer, Rebecca; Gerber, James; Hawthorne, Peter; Heger, Martin Philipp; Mamun, Saleh; Ruta, Giovanni; Schmitt, Rafael; Smith, Jeffrey; Vogl, Adrian; Wagner, Fabian; Zaveri, Esha. (2023). Nature's Frontiers: Achieving Sustainability, Efficiency, and Prosperity with Natural Capital. Environment and Sustainable Development series. Washington, DC: World Bank Link to source: https://hdl.handle.net/10986/39453

de Sherbinin, A., VanWey, L. K., McSweeney, K., Aggarwal, R., Barbieri, A., Henry, S., Hunter, L. M., Twine, W., & Walker, R. (2008). Rural household demographics, livelihoods and the environment. Global Environmental Change, 18(1), 38–53. Link to source: https://doi.org/10.1016/j.gloenvcha.2007.05.005

Den Herder, M., Moreno, G., Mosquera-Losada, R. M., Palma, J. H., Sidiropoulou, A., Freijanes, J. J. S., & Burgess, P. J. (2017). Current extent and stratification of agroforestry in the European Union. Agriculture, Ecosystems & Environment, 241, 121–132. Link to source: https://doi.org/10.1016/j.agee.2017.03.005

Di Prima, S., Wright, E. P., Sharma, I. K., Syurina, E., & Broerse, J. E. W. (2022). Implementation and scale-up of nutrition-sensitive agriculture in low- and middle-income countries: A systematic review of what works, what doesn’t work and why. Global Food Security, 32, 100595. Link to source: https://doi.org/10.1016/j.gfs.2021.100595

deStefano, A, & Jacobson, M.G. (2018). Soil carbon sequestration in agroforestry systems: A review. Agroforestry Systems, 92, 285–299. Link to source: https://doi.org/10.1007/s13593-014-0212-y

Dudley, N., Eufemia, L., Fleckenstein, M., Periago, M. E., Petersen, I., & Timmers, J. F. (2020). Grasslands and savannahs in the UN Decade on Ecosystem Restoration. Restoration Ecology, 28(6), 1313–1317. Link to source: https://doi.org/10.1111/rec.13272

Dupraz, C, and Liagre, F.(2011). Agroforesterie: Des Arbres et des Cultures. Editions France Agricole. Link to source: https://agroboutique.com/agroecologie-catalogue/12-agroforesterie-des-arbres-et-des-cultures.html

FAO Statistical Service (2024). FAOStat. Link to source: https://www.fao.org/faostat/en/

Feliciano, D., Ledo, A., Hillier, J., & Nayak, D. R. (2018). Which agroforestry options give the greatest soil and above ground carbon benefits in different world regions?. Agriculture, ecosystems & environment, 254, 117–129. Link to source: https://doi.org/10.1016/j.agee.2017.11.032

Frelat, R., Lopez-Ridaura, S., Giller, K. E., Herrero, M., Douxchamps, S., Djurfeldt, A. A., Erenstein, O., Henderson, B., Kassie, M., Paul, B. K., Rigolot, C., Ritzema, R. S., Rodriguez, D., Van Asten, P. J. A., & Van Wijk, M. T. (2016). Drivers of household food availability in sub-Saharan Africa based on big data from small farms. Proceedings of the National Academy of Sciences of the United States of America, 113(2), 458–463. Link to source: https://doi.org/10.1073/pnas.1518384112

Garrett, H. E., Kerley, M. S., Ladyman, K. P., Walter, W. D., Godsey, L. D., Van Sambeek, J. W., & Brauer, D. K. (2004). Hardwood silvopasture management in North America. In New Vistas in Agroforestry: A Compendium for 1st World Congress of Agroforestry, 2004 (pp. 21–33). Springer Netherlands. Link to source: https://doi.org/10.1007/978-94-017-2424-1_2

Goracci, J., & Camilli, F. (2024). Agroforestry and animal husbandry. IntechOpen. Link to source: https://doi.org/10.5772/intechopen.1006711

Government of Colombia (2020). Actualización de la Contribución Determinada a Nivel Nacional de Colombia. Government of Colombia. Link to source: https://unfccc.int/sites/default/files/NDC/2022-06/NDC%20actualizada%20de%20Colombia.pdf

Greene, H., Kazanski, C. E., Kaufman, J., Steinberg, E., Johnson, K., Cook-Patton, S. C., & Fargione, J. (2023). Silvopasture offers climate change mitigation and profit potential for farmers in the eastern United States. Frontiers in Sustainable Food Systems, 7, 1158459. Link to source: https://doi.org/10.3389/fsufs.2023.1158459

Hart, D.R.T, Yeo, S, Almaraz, M, Beillouin, D, Cardinael, R, Garcia, E, Kay, S, Lovell, S.T., Rosenstock, T.S., Sprenkle-Hyppolite, S, Stolle, F, Suber, M, Thapa, B, Wood, S & Cook-Patton, S.C (2023). “Priority science can accelerate agroforestry as a natural climate solution”. Nature Climate Change. Link to source: https://doi.org/10.5281/zenodo.8209212

Husak, A. L., & Grado, S. C. (2002). Monetary benefits in a southern silvopastoral system. Southern Journal of Applied Forestry, 26(3), 159–164. Link to source: https://doi.org/10.1093/sjaf/26.3.159

IPCC (2019). Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M. Belkacemi, J. Malley, (eds.)]. Link to source: https://www.ipcc.ch/srccl/

IPCC AR6 WG3 (2022). Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. Link to source: https://doi.org/10.1017/9781009157926

Jacobsen (2019). Secondary metabolites in leaf hay as a mitigation option for enteric methane production in ruminants. Aarhus University. Link to source: https://pure.au.dk/ws/portalfiles/portal/197235590/Secondary_Metabolites_in_Leaf_Hay_as_a_Mitigation_Option_for_Enteric_Methane_Production_in_Ruminants.pdf

Jose, S., & Dollinger, J. (2019). Silvopasture: a sustainable livestock production system. Agroforestry systems, 93, 1-9. Link to source: https://doi.org/10.1007/s10457-019-00366-8

Lal, R., Smith, P., Jungkunst, H. F., Mitsch, W. J., Lehmann, J., Nair, P. R., & Ravindranath, N. H. (2018). The carbon sequestration potential of terrestrial ecosystems. Journal of soil and water conservation, 73(6), 145A–152A. Link to source: https://doi.org/10.2489/jswc.73.6.145A

Lee, S., Bonatti, M, Löhe, K, Palacios, V., Lana, M.A., and Sieber, S (2020). Adoption potentials and barriers of silvopastoral systems in Colombia: Case of Cundinamarca region. Cogent Environmental Science 6(1). Link to source: https://doi.org/10.1080/23311843.2020.1823632

Lemes, A. P., Garcia, A. R., Pezzopane, J. R. M., Brandão, F. Z., Watanabe, Y. F., Cooke, R. F., Sponchiado, M., Paz, C. C. P., Camplesi, A. C., Binelli, M., & Gimenes, L. U. (2021). Silvopastoral system is an alternative to improve animal welfare and productive performance in meat production systems. Scientific Reports, 11(1), 14092. Link to source: https://doi.org/10.1038/s41598-021-93609-7

Lorenz, K., & Lal, R. (2018). Carbon sequestration in agricultural ecosystems. Springer, Cham. Link to source: https://link.springer.com/book/10.1007/978-3-319-92318-5

Mehrabi, Z., Tong, K., Fortin, J., Stanimirova, R., Friedl, M., & Ramankutty, N. (2024). Global agricultural lands in the year 2015. Earth System Science Data Discussions, 2024, 1–44. Link to source: https://doi.org/10.5194/essd-2024-279

Montagnini, F (2019). Función de los sistemas agroforestales en la adaptación y mitigación del cambio climático. Sistemas agroforestales: Funciones productivas, socioeconómicas y ambientales, 269-299. Link to source: https://cipav.org.co/wp-content/uploads/2020/08/sistemas-agroforestales-funciones-productivas-socioeconomicas-y-ambientales.pdf

Morena, G., & Rolo, V. (2019). Agroforestry practices: Silvopastoralism. In Agroforestry for sustainable agricultura (1st ed.). Burleigh Dodds Science Publishing. Link to source: https://doi.org/10.1201/9780429275500

Murgueitio, E., Uribe, F., Molina, C., Molina, E., Galindo, W., Chará, J., & González, J. (2016). Establecimiento y manejo de sistemas silvopastoriles intensivos con Leucaena. Editorial CIPAV, Cali, Colombia. Link to source: https://www.researchgate.net/profile/Juan-Naranjo-R/publication/310460876_Establecimiento_y_manejo_de_sistemas_silvopastoriles_intensivos_con_leucaena/links/582e30cb08ae138f1c01d8b9/Establecimiento-y-manejo-de-sistemas-silvopastoriles-intensivos-con-leucaena.pdf

Nair, P.K. R. (2012). Climate change mitigation: A low-hanging fruit of agroforestry. Agroforestry: The future of global land use, 31–69. Link to source: https://doi.org/10.1007/978-94-007-4676-3_7

Ortiz, J., Neira, P., Panichini, M., Curaqueo, G., Stolpe, N. B., Zagal, E., & Gupta, S. R. (2023). Silvopastoral systems on degraded lands for soil carbon sequestration and climate change mitigation. Agroforestry for Sustainable Intensification of Agriculture in Asia and Africa, 207–242. Link to source: https://doi.org/10.1007/978-981-19-4602-8_7

Pent, G. J. (2020). Over-yielding in temperate silvopastures: a meta-analysis. Agroforestry Systems, 94(5), 1741–1758. Link to source: https://doi.org/10.1007/s10457-020-00494-6

Pezo, D., Ríos, N., Ibrahim, M., & Gómez, M. (2018). Silvopastoral systems for intensifying cattle production and enhancing forest cover: the case of Costa Rica. Washington, DC: World Bank. Link to source: https://www.profor.info/sites/default/files/Silvopastoral%2520systems_Case%2520Study_LEAVES_2018.pdf

Poudel, S., Pent, G., & Fike, J. (2024). Silvopastures: Benefits, past efforts, challenges, and future prospects in the United States. Agronomy, 14(7), 1369. Link to source: https://doi.org/10.3390/agronomy14071369

Quandt, A, Neufeldt, G, & Gorman, K (2023). Climate change adaptation through agroforestry: Opportunities and gaps. Current Opinion in Environmental Sustainability. 60, 101244. Link to source: https://doi.org/10.1016/j.cosust.2022.101244

Rivera, J. E., Serna, L., Arango, J., Barahona, R., Murgueitio, E., Torres, C. F., & Chará, J. (2023). Silvopastoral systems and their role in climate change mitigation and Nationally Determined Contributions in Latin America. In Silvopastoral systems of Meso America and Northern South America (pp. 25–53). Cham: Springer International Publishing. Link to source: https://doi.org/10.1007/978-3-031-43063-3_2

Rojas, D, & Rodriguez Anido, N. (2022) Potential of silvopastoral systems for the mitigation of greenhouse gasses generated in the production of bovine meat. In Sistemas silvopastoriles: Hacia una diversificación sostenible. CIPAV. Link to source: https://cipav.org.co/sistemas-silvopastoriles-hacia-una-diversificacion-sostenible/

Riset, J.Å., Tømmervik, H. & Forbes, B.C. (2019). Sustainable and resilient reindeer herding. Reindeer Caribou Health Dis, (23–43). Link to source: https://www.researchgate.net/publication/344787755_Ch13_Sustainable_and_resilient_reindeer_herding

Shelton, M., Dalzell, S., Tomkins, N. and Buck, S. R. (2021). Leucaena: The productive and sustainable forage legume. University of Queensland. Link to source: https://era.dpi.qld.gov.au/id/eprint/9425/

Shi, L., Feng, W., Xu, J., & Kuzyakov, Y. (2018). Agroforestry systems: Meta‐analysis of soil carbon stocks, sequestration processes, and future potentials. Land Degradation & Development, 29(11), 3886–3897. Link to source: https://doi.org/10.1002/ldr.3136

Smith, M. M., Bentrup, G., Kellerman, T., MacFarland, K., Straight, R., Ameyaw, L., & Stein, S. (2022). Silvopasture in the USA: A systematic review of natural resource professional and producer-reported benefits, challenges, and management activities. Agriculture, Ecosystems & Environment, 326, 107818. Link to source: https://doi.org/10.1016/j.agee.2021.107818

Sprenkle-Hyppolite, S. Griscom, B., Griffey, V., Munshi, E., Chapman, M. (2024). Maximizing tree carbon in cropland and grazing lands while sustaining yields. Carbon Balance and Management 19:23. Link to source: https://doi.org/10.1186/s13021-024-00268-y

Toensmeier, E. (2017). Perennial staple crops and agroforestry for climate change mitigation. Integrating landscapes: Agroforestry for biodiversity conservation and food sovereignty, 439-451. Link to source: https://doi.org/10.1007/978-3-319-69371-2_18

U.S. Department of Agriculture Natural Resources Conservation Service [USDA NRCS]. (2025). Conservation Practice Physical Effects [Dataset]. Link to source: https://www.nrcs.usda.gov/resources/guides-and-instructions/conservation-practice-physical-effects

Udawatta, R. P., Walter, D., & Jose, S. (2022). Carbon sequestration by forests and agroforests: A reality check for the United States. Carbon footprints, 1(8). Link to source: https://doi.org/10.20517/cf.2022.06 

Zeppetello, L. R. V., Cook-Patton, S. C., Parsons, L. A., Wolff, N. H., Kroeger, T., Battisti, D. S., Bettles, J., Spector, J. T., Balakumar, A., & Masuda, Y. J. (2022). Consistent cooling benefits of silvopasture in the tropics. Nature communications, 13(1), 708. Link to source: https://doi.org/10.1038/s41467-022-28388-4

Zhu, X., Liu, W., Chen, J., Bruijnzeel, L. A., Mao, Z., Yang, X., Cardinael, R., Meng, F.-R., Sidle, R. C., Seitz, S., Nair, V. D., Nanko, K., Zou, X., Chen, C., & Jiang, X. J. (2020). Reductions in water, soil and nutrient losses and pesticide pollution in agroforestry practices: A review of evidence and processes. Plant and Soil, 453(1–2), 45–86. Link to source: https://doi.org/10.1007/s11104-019-04377-3

Credits

Lead Fellow

  • Eric Toensmeier

Contributors

  • Ruthie Burrows, Ph.D.

  • Yusuf Jameel, Ph.D.

  • Daniel Jasper

Internal Reviewers

  • Aiyana Bodi

  • Hannah Henkin

  • Ted Otte

  • Paul C. West, Ph.D.

Effectiveness

We found a median carbon sequestration rate of 9.81 t CO₂‑eq /ha/yr (Table 1). This is based on an above-ground biomass (tree trunks and branches) accumulation rate of 6.43 t CO₂‑eq /ha/yr and a below-ground biomass (roots) accumulation rate of 1.61 t CO₂‑eq /ha/yr using a root-to-shoot ratio of 0.25 (Cardinael et al., 2019). These are added to the soil organic carbon sequestration rate of 1.76 t CO₂‑eq /ha/yr to create the combined total.

Table 1. Effectiveness at carbon sequestration.

Unit: t CO₂-eq/ha/yr, 100-yr basis

25th percentile 4.91
Mean 14.70
Median (50th percentile) 9.81
75th percentile 20.45

100-yr basis

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Reductions in nitrous oxide and methane and sustainable intensification impacts are not yet quantifiable to the degree that they can be used in climate mitigation projections.

Cost

Because baseline grazing systems are already extensive and well established, we assumed there is no cost to establish new baseline grazing land. In the absence of global data sets on costs and revenues of grazing systems, we used a global average profit per hectare of grazing land of US$6.28 from Damania et al. (2023).

Establishment costs of silvopasture vary widely. We found the cost to establish one hectare of silvopasture to be US$1.06–4,825 (Dupraz & Liagre, 2011; Lee et al., 2011). Reasons for this wide range include the low cost of natural regeneration and the broad range in tree density depending on the type of system. We collected costs by region and used a weighted average to obtain a global net net cost value of US$424.20.

Cost and revenue data for silvopasture were insufficient. However, data on the impact on revenues per hectare are abundant. Our analysis found a median 8.7% increase in per-hectare profits from silvopasture compared with conventional grazing, which we applied to the average grazing value to obtain a net profit of US$6.82/ha. This does not reflect the very high revenues of silvopasture systems in some countries.

We calculated cost per t CO₂‑eq sequestered by dividing net net cost/ha by total CO₂‑eq sequestered/ha.

Table 2. Cost per unit of climate impact.

Unit: 2023 US$/t CO₂-eq

Median $43.25

100-yr basis & 20-yr basis are the same.

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Methods and Supporting Data

Methods and Supporting Data

Learning Curve

There is not enough information available to determine a learning curve for silvopasture. However, anecdotal evidence showed establishment costs decreasing as techniques for broadscale mechanized establishment were developed in Australia and Colombia (Murguietio et al., 2016; Shelton et al., 2021).

Speed of Action

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.

Deploy Silvopasture is a DELAYED climate solution. It works more slowly than gradual or emergency brake solutions. Delayed solutions can be robust climate solutions, but it’s important to recognize that they may not realize their full potential for some time.

Caveats

Permanence

Living biomass and soil organic matter only temporarily hold carbon (decades to centuries for soil organic matter, and for the life of the tree or any long-lived products made from its wood in the case of woody biomass). Sequestered carbon in both soils and biomass is vulnerable to fire, drought, long-term shifts to a drier precipitation regime, and other climate change impacts, as well as to a return to the previous farming or grazing practices. Such disturbances can cause carbon to be re-emitted to the atmosphere (Lorenz & Lal, 2018). 

Saturation

Like all upland, terrestrial agricultural systems, over the course of decades, silvopastures reach saturation and net sequestration slows to nearly nothing (Lorenz & Lal, 2018). 

Current Adoption

Lack of data on the current adoption of silvopasture is a major gap in our understanding of the potential of this solution. One satellite imaging study found 156 million ha of grazing land with more than 10 t C/ha in above-ground biomass, which is the amount that indicates more than grass alone (Chapman et al., 2019). However, this area includes natural savannas, which are not necessarily silvopastures, and undercounts the existing 15.1 million ha of silvopasture known to be present in Europe (den Herder et al., 2017).

Sprenkle-Hippolite et al. (2024) estimated a current adoption of 141.4 Mha, or 6.0% of grazing land (Table 3). We have chosen this more recent figure as the best available estimate of current adoption. Note that in Solution Basics in the dashboard above we set current adoption at zero. This is a conservative assumption to avoid counting carbon sequestration from land that has already ceased to sequester net carbon due to saturation, which takes place after 20–50 years (Lal et al., 2018).

Table 3. Current (2023) adoption level.

Unit: million ha

Mean 141.4
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Adoption Trend

There is little quantifiable information reported about silvopasture adoption trends.

Adoption Ceiling

Grazing is the world’s largest land use at 2,986 Mha (Mehrabi et al., 2024). Much grazing land is too dry for trees, while other grasslands that were not historically forest or savanna should not be planted with trees in order to minimize water use and protect grassland habitat (Dudley et al., 2020). Three studies estimated the total potential area suitable for silvopasture (including current adoption). 

Lal et al. (2018) estimated the technical potential for silvopasture adoption at 550 Mha.

Chapman et al. (2019) estimated the suitable area for increased woody biomass on grazing land as 1,890 Mha. 

Sprenkle-Hippolite (2024) assessed the maximum area of grazing land to which trees could be added without reducing livestock productivity. They calculated a total of 1,589 Mha, or 67% of global grazing land (Table 4). To our knowledge, this is the most accurate estimate available. 

Table 4. Adoption ceiling.

Unit: ha converted

25th percentile 1069000000
Mean 1343000000
Median (50th percentile) 1588000000
75th percentile 1739000000

Unit: % of grazing land

25th percentile 45
Mean 36
Median (50th percentile) 53
75th percentile 58
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Achievable Adoption

In our Achievable – High scenario, global silvopasture starts at 141.4 Mha and grows at the Colombian Nationally Determined Contribution growth rate of 6.5%/yr. This would provide the high end of the achievable potential at 206.3 Mha by 2030, of which 64.9 million ha are newly adopted (Table 5). For the Achievable – Low scenario, we chose 1/10 of Colombia’s projected growth rate. This would provide 147.0 Mha of adoption by 2030, of which 5.6 Mha are new.

Few estimates of the global adoption potential of silvopasture are available, and even those for the broader category of agroforestry are rare due to the lack of solid data on current adoption and growth rates (Shi et al., 2018; Hart et al., 2023). The IPCC estimates that, for agroforestry overall, 19.5% of the technical potential is economically achievable (IPCC AR6 WG3, 2022). Applying this rate to Sprenkle-Hippolite’s estimated 1,588 Mha technical potential yields an achievable potential of 310 Mha of convertible grazing land.

Our high adoption rate reaches 13% of the adoption ceiling by 2030. This suggests that silvopasture represents a large but relatively untapped potential that will require aggressive policy action and other incentives to spur scaling.

Table 5. Range of achievable adoption levels.

Unit: Mha

Current adoption 141.4
Achievable – low 147.0
Achievable – high 206.3
Adoption ceiling 1,588.0

Unit: Mha

Current adoption 0.00
Achievable – low 5.6
Achievable – high 64.9
Adoption ceiling 1,447.4
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Carbon sequestration continues only for a period of decades; because silvopasture is an ancient practice with some plantings centuries old, we could not assume that previously adopted hectares continue to sequester carbon indefinitely. Much of the current adoption of silvopasture has been in place for centuries and sequestration there has presumably already slowed down to almost zero. We apply an adoption adjustment factor of 0.25 to current adoption (see Methodology) to reflect that most current adoption is no longer sequestering significant carbon, yet there is substantial new adoption within the past 20–50 years.

For new adoption the calculation is effectiveness * new adoption = climate impact.

For current adoption the calculation is effectiveness * 0.25 * current adoption = climate impact

Climate impacts shown in Table 6 are the sum of current and new adoption impacts. Carbon sequestration impact is 0.35 Gt CO₂‑eq/yr for current adoption, 0.40 Gt CO₂‑eq/yr for Achievable – Low, 0.98 Gt CO₂‑eq/yr for Achievable – High, and 14.54 Gt CO₂‑eq/yr for our Adoption Ceiling. 

Table 6. Climate impact at different levels of adoption.

Unit: Gt CO₂‑eq/yr

Current adoption 0.35
Achievable – low 0.40
Achievable – high 0.98
Adoption ceiling 14.54

100-yr basis, New adoption only 

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Lal et al. (2018) estimated a technical global carbon sequestration potential of 0.3–1.0 Gt CO₂‑eq/yr. Sprenkle-Hyppolite et al. (2024) estimated a silvopasture technical potential of 1.4 Gt CO₂‑eq/yr ; this assumes a tree density of 2–6 trees/ha, which is substantially lower than typical silvopasture. For agroforestry overall (including silvopasture and other practices), the IPCC (2022) estimates an achievable potential of 0.8 Gt CO₂‑eq/yr and a technical potential of 4.0 Gt CO₂‑eq/yr.

Additional Benefits

Income and Work 

Silvopasture can also increase and diversify farmer income. Tree fruit and timber often provide income for ranchers. A study in the southern United States showed that silvopasture systems generated 10% more income than standalone cattle production (Husak & Grado, 2002). A more comprehensive analysis across the eastern United States (Greene et al., 2023) found that virtually all silvopasture systems assessed had a positive 20- and 30-yr internal rate of return (IRR). For some systems, the 30-yr IRR can be >15% (Greene et al., 2023).

Food Security

While evidence on the impact of silvopasture on yields is mixed, this practice can improve food security by diversifying food production and income sources (Bostedt et al., 2016; Smith et al., 2022). In pastoralists in Kenya, Bostedt et al. (2016) found that agroforestry practices were associated with increased dietary diversity, an important aspect of food and nutrition security. Diverse income streams can mediate household food security during adverse conditions, such as droughts or floods, especially in low- and middle-income countries (de Sherbinin et al., 2008; Di Prima et al., 2022; Frelat et al., 2016). 

Nature Protection

Trees boost habitat availability, enhance landscape connectivity, and aid in forest regeneration and restoration. In most climates they provide a major boost to biodiversity compared with pasture alone (Smith et al., 2022; Pezo et al., 2018). 

Animal Well-being

By providing shade, silvopasture systems reduce heat stress experienced by livestock. Heat stress for cattle begins at 30 °C or even lower in some circumstances (Garrett et al., 2004). In the tropics, the cooling effect of integrating trees into a pastoral system is 0.32–2.4 °C/t of woody carbon added/ha (Zeppetello et al., 2022). Heifers raised in silvopasture systems had higher body mass and more optimal body temperature than those raised in intensive rotational grazing systems (Lemes et al., 2021). Improvement in livestock physiological conditions probably results from access to additional forage, increased livestock comfort, and reduced heat stress in silvopastoral systems. Silvopasture is highly desirable for its improvements to animal welfare (Goracci & Camilli, 2024).

Land Resources

Silvopasture and agroforestry are important for ensuring soil health (Basche et al., 2020). These practices improve soil health by reducing erosion and may also contribute to soil organic matter retention (U.S. Department of Agriculture Natural Resource Conservation Service ([USDA NRCS], 2025). There is evidence that silvopasture may improve soil biodiversity by preventing soil organism habitat loss and degradation (USDA NRCS, 2025).

Water Quality

Perennials in silvopasture systems could reduce runoff and increase water infiltration rates relative to open rangelands (Smith et al., 2022; Pezo et al., 2018). This increases the resilience of the system during drought and high heat. Silvopasture can improve water quality by retaining soil sediments and filtering pollutants found in runoff (USDA NRCS, 2025). On average, silvopasture and agroforestry practices can reduce runoff of sediments and excess nutrients into water 42–47% (Zhu et al., 2020). The filtering benefits of silvopasture can also mitigate pollution of antibiotics from livestock operations from entering waterways (Moreno & Rolo, 2019). 

Risks

Some of the tree and forage species used in silvopastures are invasive in certain contexts. For example, river tamarind (Leucaena leucocephala) is a centerpiece in intensive silvopasture in Latin America, where it is native, but also in Australia, where it is not. Australian producers have developed practices to limit or prevent its spread (Shelton et al., 2021).

Livestock can damage or kill young trees during establishment. Protecting trees or excluding grazing animals during this period increases costs (Smith et al., 2022).

Poorly designed tree layout can make herding, haying, fencing, and other management activities more difficult. Tree densities that are too high can reduce livestock productivity (Cadavid et al., 2020).

Interactions with Other Solutions

Reinforcing

Silvopasture represents a way to produce some ruminant meat and dairy in a more climate-friendly way. This impact can contribute to addressing emissions from ruminant production, but only as part of a program that strongly emphasizes diet change and food waste reduction.

Forms of silvopasture that increase milk and meat yields can reduce pressure to convert undeveloped land to agriculture.

Silvopasture is a technique for restoring farmland.

Silvopasture is a form of savanna restoration.

Competing

Expanding silvopasture could restrict land availability for renewable energy or raw material and food production, since many technologies and practices could be sited on grazing lands. Silvopasture and forest restoration can also compete for the same land.

Silvopasture is a kind of agroforestry, though in this iteration of Project Drawdown “Deploy Agroforestry” refers to crop production systems only. With that said, some agroforestry systems integrate both crops and livestock with the trees, such as the widespread parkland systems of the African Sahel.

Dashboard

Solution Basics

ha converted from grazing land to silvopasture

t CO₂-eq (100-yr)/unit/yr
04.919.81median
units
Current 1.414×10⁸ 01.47×10⁸2.063×10⁸
Achievable (Low to High)

Climate Impact

Gt CO₂-eq (100-yr)/yr
Current 0.35 0.40.98
US$ per t CO₂-eq
43
Delayed

CO₂

Trade-offs

Solutions that improve ruminant production could undermine the argument for reducing ruminant protein consumption in wealthy countries. 

Certain silvopasture systems reduce per-hectare productivity of meat and milk, even if overall productivity increases when the yields of timber or food from the tree component are included. For example, silvopasture systems that are primarily focused on timber production, with high tree densities, will have lower livestock yields than pasture alone - though they will have high timber yields.

The costs of establishment are much higher than those of managed grazing. There is also a longer payback period (Smith et al., 2022). These limitations mean that secure land tenure is even more important than usual, to make adoption worthwhile (Poudel et al., 2024).

Maps Introduction

Silvopasture is primarily appropriate for grazing land that receives sufficient rainfall to support tree growth. While it can be implemented on both cropland and grassland, if adopted on cropland, it will reduce food yield because livestock produce much less food per hectare than crops. In the humid tropics, a particularly productive and high-carbon variation called intensive silvopasture is an option. Ideally, graziers will have secure land tenure, though pastoralist commons have been used successfully.

Areas too dry to establish trees (<450 mm annual precipitation) are not suitable for silvopasture by tree planting, but regions that can support natural savanna may be suitable for managed natural regeneration.

Most silvopasture today appears in sub-Saharan Africa (Chapman et al., 2019), though this may reflect grazed natural savannas rather than intentional silvopasture. This finding neglects well-known systems in Latin America and Southern Europe. 

Chapman et al. (2019) listed world grasslands by their potential to add woody biomass. According to their analysis, the countries with the greatest potential to increase woody biomass carbon in grazing land are, in order: Australia, Kazakhstan, China, the United States, Mongolia, Iran, Argentina, South Africa, Sudan, Afghanistan, Russia, and Mexico. Tropical grazing land accounts for 73% of the potential in one study. Brazil, China, and Australia have the highest areas, collectively accounting for 37% of the potential area (Sprenkle-Hippolite 2024).

We do not present any maps for the silvopasture solution due to the uncertainties in identifying current areas where silvopasture is practiced, and in identifying current grasslands that were historically forest or savanna. 

Action Word
Deploy
Solution Title
Silvopasture
Classification
Highly Recommended

Lawmakers and Policymakers
  • Lower the risk for farmers transitioning from other pastoral systems.
  • Increase understanding of silvopasture.
  • Reduce technical and bureaucratic complexity.
  • Establish or expand technical assistance programs.
  • Simplify incentive programs.
  • Ensure an appropriate and adequate selection of tree species are eligible for incentives.
  • Establish a silvopasture certification program.
  • Create demonstration farms.
  • Strengthen land tenure laws.
  • Incentivize lease structures to facilitate silvopasture transitions on rented land.

Further information:

Practitioners
  • Seek support from technical assistance programs and extension services.
  • Seek out networks of adopters to share information, resources, best practices, and collective marketing.
  • If available, leverage incentive programs such as subsidies, tax rebates, grants, and carbon credits.
  • Negotiate new lease agreements to accommodate silvopasture techniques or advocate for public incentives to reform lease structures.

Further information:

Business Leaders
  • Prioritize suppliers and source from farmers who use silvopasture.
  • Provide innovative financial mechanisms to encourage adoption.
  • Participate in and help create high-quality carbon credit programs.
  • Incentivize silvopasture transitions in lease agreements.
  • Support the creation of a certification system to increase the marketability of silvopasture products.
  • Join coalitions with other purchasers to grow demand.
  • Collaborate with public and private agricultural organizations on education and training programs. 

Further information:

Nonprofit Leaders
  • Educate farmers and those who work in the food industry about the benefits of silvopasture.
  • Communicate any government incentives for farmers to transition to silvopasture.
  • Explain how to take advantage of incentives.
  • Provide training material and/or work with extension services to support farmers transitioning to silvopasture, such as administering certification programs.
  • Advocate to policymakers for improved incentives for farmers, stronger land tenure laws, and flexible lease agreements.

Further information:

Investors
  • Use capital like low-interest or favorable loans to support farmers and farmer cooperatives exploring silvopasture projects.
  • Invest in credible, high-quality carbon reduction silvopasture projects.
  • Invest in silvopasture products (e.g., fruits, berries, and other tree products)
  • Encourage favorable lease agreements between landowners or offer favorable costs and benefit-sharing structures.
  • Consider banking through community development financial institutions or other institutions that support farmers. 

Further information:

Philanthropists and International Aid Agencies
  • Provide grants and loans for establishing silvopasture and support farmland restoration projects that include silvopasture.
  • Support capacity-building, market access, education, and training opportunities for smallholder farmers – especially those historically underserved – through activities like farmer cooperatives, demonstration farms, and communal tree nurseries.
  • Consider banking through Community Development Financial Institutions or other institutions that support farmers. 

Further information:

Thought Leaders
  • Use your platform to build awareness of silvopasture and its benefits, incentive programs, and regulatory standards.
  • Provide technical information to practitioners.
  • Host community dialogues such as Edible Connections to engage the public about silvopasture and other climate-friendly farming practices.

Further information:

Technologists and Researchers
  • Improve the affordability and equipment needed to plant and manage trees.
  • Refine satellite tools to improve silvopasture detection.
  • Develop ways to monitor changes in soil and biomass.
  • Standardize data collection protocols.
  • Create a framework for transparent reporting and reliable verification.
  • Fill gaps in data, such as quantifying the global adoption potential of silvopasture and regional analysis of revenue and operating costs/hectare. 

Further information:

Communities, Households, and Individuals
  • Purchase silvopasture products and support farmers who use the practice.
  • Request silvopasture products at local markets.
  • Encourage policymakers to help farmers transition.
  • Encourage livestock farmers to adopt the practice.
  • Host community dialogues such as Edible Connections to engage the public about silvopasture and other climate-friendly farming practices.

Further information:

“Take Action” Sources
Evidence Base

Consensus of effectiveness in sequestering carbon: Mixed to High 

There is a high level of consensus about the carbon biosequestration impacts of silvopasture, including for the higher per-hectare sequestration rates relative to improved grazing systems alone. A handful of reviews, expert estimations, and meta-analyses have been published on the subject. These include:

Cardinael et al. (2018) assembled data by climate and region for use in the national calculations and reporting. 

Chatterjee et al. (2018) found that converting from pasture to silvopasture increases carbon stocks. 

Lal et al. ( 2018) estimated the technical adoption and mitigation potential of silvopasture and other practices.

Udawatta et al. (2022) provided an up-to-date meta-analysis for temperate North America. 

The results presented in this document summarize findings from two reviews, two meta-analyses, one expert opinion and three original studies reflecting current evidence from a global scale. We recognize this limited geographic scope creates bias, and hope this work inspires research and data sharing on this topic in underrepresented regions.

Consensus regarding other climate impacts: Low

There is low consensus on the reduction of methane from enteric emissions, nitrous oxide from manure, and CO₂ from avoided deforestation due to increased productivity. We do not include these climate impacts in our calculations.

Consensus regarding adoption potential: Low

Until recently there was little understanding of the current adoption of silvopasture. Sprenkle-Hyppolite et al. (2024) used Delphi expert estimation to determine current adoption and technical potential. Rates of adoption and achievable potential are still largely unreported or uninvestigated. See the Adoption section for details.

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Deploy Agroforestry

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Shift Agriculture Practices
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Methods and Supporting Data

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