For all transformations included in SiSePuede, capital and operational costs, as well as monetized socioeconomic benefits are specified. Baseline social, environmental, and economic costs and benefits factors are based on estimates found in the literature. However, the framework is built to enable uncertainty exploration over these baseline factors. Additionally, to make the analysis more relevant to a wider set of stakeholders (e.g., ministry of transport or energy departments), factors for costs and benefits are estimated in the natural units in which they are incurred (e.g., cost of clinker substitution per ton of cement produced, cost of managing enteric emissions per head of cattle, and ecosystem services gained or lost per hectare of forest) rather than in costs per unit of GHG emitted or abated. Thus, costs and benefits of transformations depend on their level of implementation and deployment across time.

*SiSePuede contrasts with and complements other modeling approaches*

SiSePuede has several advantages over other modeling frameworks to answer the questions posed in this analysis. First, SiSePuede is designed to assess transformations at the subsector level, addressing the need of modeling actions to reflect tangible goals for sectoral actors while quantifying the system-wide effects, including the social costs and benefits of those actions. Second, SiSePuede is based on IPCC inventory guidelines and emission codes, meaning that it is well suited for comparison to NDCs and other publicly available emissions accounts (including FAO, Climate Watch [CAIT], IEA, and UN Framework Convention on Climate Change [FCCC]). Third, SiSePuede is built on a scalable, open-source platform and driven by simple numerical calculations, facilitating a robust exploration of strategies for specific country contexts by enabling substantive exploration over uncertainties (drivers, transformations, and costs and benefits factors) at highly refined levels (i.e., all sectors and all greenhouse gases). Fourth, SiSePuede simulates the impact of over 50 sectoral transformations that stakeholders can adjust in terms of how quickly and intensively these transformations are implemented in each sector and country and combine them into different portfolios. For all transformations, SiSePuede models required implementation costs and associated economy-wide benefits. Finally, SiSePuede uses hundreds of data points<fnref n="1" /> retrieved from public databases (i.e., FAO, World Bank, and OECD) to capture nations’ and transformations’ characteristics. This data captures both formal and informal sectors. Then each nation is calibrated to historical data from 2015-2020 and rescaled to match its registered emissions inventory in international databases, such as Climate Watch, or as registered in its national archives. Because of data availability 2020 is used as the initial year is simulations. This does not require a special treatment of COVID19 impacts. These elements allow SiSePuede to reflect the set of resources, restrictions, and options that different countries have to meet their mitigation goals.

<footnote n="1">¹ There were 300 variables estimated and retrieved for the AFOLU sector, 73 for Circular Economy, 528 for Energy, 206 for Industrial Processes and Produce Use (IPPU), and 13 for the socioeconomic module. Metadata and processing protocols for this database can be found at https://github.com/milocortes/sisepuede_data.</footnote>
For all transformations included in SiSePuede, capital and operational costs, as well as monetized socioeconomic benefits are specified. Baseline social, environmental, and economic costs and benefits factors are based on estimates found in the literature. However, the framework is built to enable uncertainty exploration over these baseline factors. Additionally, to make the analysis more relevant to a wider set of stakeholders (e.g., ministry of transport or energy departments), factors for costs and benefits are estimated in the natural units in which they are incurred (e.g., cost of clinker substitution per ton of cement produced, cost of managing enteric emissions per head of cattle, and ecosystem services gained or lost per hectare of forest) rather than in costs per unit of GHG emitted or abated. Thus, costs and benefits of transformations depend on their level of implementation and deployment across time.

*SiSePuede contrasts with and complements other modeling approaches*

SiSePuede has several advantages over other modeling frameworks to answer the questions posed in this analysis. First, SiSePuede is designed to assess transformations at the subsector level, addressing the need of modeling actions to reflect tangible goals for sectoral actors while quantifying the system-wide effects, including the social costs and benefits of those actions. Second, SiSePuede is based on IPCC inventory guidelines and emission codes, meaning that it is well suited for comparison to NDCs and other publicly available emissions accounts (including FAO, Climate Watch [CAIT], IEA, and UN Framework Convention on Climate Change [FCCC]). Third, SiSePuede is built on a scalable, open-source platform and driven by simple numerical calculations, facilitating a robust exploration of strategies for specific country contexts by enabling substantive exploration over uncertainties (drivers, transformations, and costs and benefits factors) at highly refined levels (i.e., all sectors and all greenhouse gases). Fourth, SiSePuede simulates the impact of over 50 sectoral transformations that stakeholders can adjust in terms of how quickly and intensively these transformations are implemented in each sector and country and combine them into different portfolios. For all transformations, SiSePuede models required implementation costs and associated economy-wide benefits. Finally, SiSePuede uses hundreds of data points<fnref n="1" /> retrieved from public databases (i.e., FAO, World Bank, and OECD) to capture nations’ and transformations’ characteristics. This data captures both formal and informal sectors. Then each nation is calibrated to historical data from 2015-2020 and rescaled to match its registered emissions inventory in international databases, such as Climate Watch, or as registered in its national archives. Because of data availability 2020 is used as the initial year is simulations. This does not require a special treatment of COVID19 impacts. These elements allow SiSePuede to reflect the set of resources, restrictions, and options that different countries have to meet their mitigation goals.

<footnote n="1">¹ There were 300 variables estimated and retrieved for the AFOLU sector, 73 for Circular Economy, 528 for Energy, 206 for Industrial Processes and Produce Use (IPPU), and 13 for the socioeconomic module. Metadata and processing protocols for this database can be found at https://github.com/milocortes/sisepuede_data.</footnote>
SiSePuede's sectoral transformation-centered approach to modeling emissions contrasts with other common modeling techniques. For example, some integrated assessment models (IAMs) are used to model biophysical emissions processes as driven by anthropogenic activity, and some include biophysical feedbacks. In accordance with IPCC inventory guidelines, SiSePuede bases emissions on emission factors that respond to drivers, though certain phenomena—such as methane emissions from anaerobic decomposition in solid waste landfills, which is modeled using a first-order decay model—include biophysical treatments. Biophysical feedbacks—such as impacts of climate change on hydropower production or crop yield factors—are treated as uncertain factors that can be explored within reasonable expected ranges.

The relative numerical simplicity of calculations in SiSePuede and integrated uncertainty frameworks allows extensive exploration over uncertainties at highly refined levels, facilitating a robust exploration of strategies. SiSePuede endogenizes uncertainty exploration through Latin Hypercube Sampling across exogenous uncertainties and intervention effects, a robust data management system, and scalable computational architecture.

SiSePuede also differs significantly from general and partial equilibrium models (GEMs and PEMs). Equilibrium models, which endogenize economic outcomes such as prices based on factors of production, are another class of models paired with emission factors to estimate how changes in economic activity may drive changes in emissions. However, while GEMs advantageously endogenize demands and prices, they can be difficult to calibrate and solve, especially when exploring large parameter and variable spaces, such as supplies and demands for a refined range of products and services across an entire economy. While SiSePuede does not endogenize prices and quantities through equilibria, it does facilitate exploration over combinations of prices and behaviors that then can be used to identify policy-relevant scenarios across a range of potential futures.

These differences aside, outputs of IAMs or other global modeling exercises (e.g., GCAM, MESSAGE-GLOBIOM, and REMIND-MAgPIE) are comparable to ours. Some of their outputs also can be used as inputs to SiSePuede. For example, GDP, population, and emission trajectories from these modeling exercises can be used in SiSePuede as inputs or as calibration targets, which may be useful in developing a more granular understanding of emission pathways estimated through IAMs.

Appendix A describes SiSePuede in more detail.

### SiSePuede's limitations

SiSePuede and the data that were used in this analysis have some important limitations. First, as noted, SiSePuede does not endogenize market signals and economic feedback loops that could affect costs, benefits, and demands. For example, as renewables are adopted more widely, the price of fossil fuels might decline. This would increase demand for fossil fuels and decrease the cost savings associated with switching to renewables.
SiSePuede's sectoral transformation-centered approach to modeling emissions contrasts with other common modeling techniques. For example, some integrated assessment models (IAMs) are used to model biophysical emissions processes as driven by anthropogenic activity, and some include biophysical feedbacks. In accordance with IPCC inventory guidelines, SiSePuede bases emissions on emission factors that respond to drivers, though certain phenomena—such as methane emissions from anaerobic decomposition in solid waste landfills, which is modeled using a first-order decay model—include biophysical treatments. Biophysical feedbacks—such as impacts of climate change on hydropower production or crop yield factors—are treated as uncertain factors that can be explored within reasonable expected ranges.

The relative numerical simplicity of calculations in SiSePuede and integrated uncertainty frameworks allows extensive exploration over uncertainties at highly refined levels, facilitating a robust exploration of strategies. SiSePuede endogenizes uncertainty exploration through Latin Hypercube Sampling across exogenous uncertainties and intervention effects, a robust data management system, and scalable computational architecture.

SiSePuede also differs significantly from general and partial equilibrium models (GEMs and PEMs). Equilibrium models, which endogenize economic outcomes such as prices based on factors of production, are another class of models paired with emission factors to estimate how changes in economic activity may drive changes in emissions. However, while GEMs advantageously endogenize demands and prices, they can be difficult to calibrate and solve, especially when exploring large parameter and variable spaces, such as supplies and demands for a refined range of products and services across an entire economy. While SiSePuede does not endogenize prices and quantities through equilibria, it does facilitate exploration over combinations of prices and behaviors that then can be used to identify policy-relevant scenarios across a range of potential futures.

These differences aside, outputs of IAMs or other global modeling exercises (e.g., GCAM, MESSAGE-GLOBIOM, and REMIND-MAgPIE) are comparable to ours. Some of their outputs also can be used as inputs to SiSePuede. For example, GDP, population, and emission trajectories from these modeling exercises can be used in SiSePuede as inputs or as calibration targets, which may be useful in developing a more granular understanding of emission pathways estimated through IAMs.

Appendix A describes SiSePuede in more detail.

### SiSePuede's limitations

SiSePuede and the data that were used in this analysis have some important limitations. First, as noted, SiSePuede does not endogenize market signals and economic feedback loops that could affect costs, benefits, and demands. For example, as renewables are adopted more widely, the price of fossil fuels might decline. This would increase demand for fossil fuels and decrease the cost savings associated with switching to renewables.
As another example, SiSePuede simulates the impact of domestic shifts toward healthier diets with less red meat. The resulting impact on household food expenditures is valued based on exogenous food prices, even though a decrease in demand for red meat would endogenously decrease red meat prices and alter that estimate. These feedbacks are not included in the analysis. However, outputs from SiSePuede can be used in specialized economic models to account for such impacts, as well as other macroeconomic impacts such as labor effects and tax revenues.

Second, SiSePuede does not contain inter-region mass balances for goods that are imported and exported (e.g., manufacturing products, crops, and/or livestock) and energy (e.g., trade in electricity and fuels).

Third, our transformations do not distinguish between informal and formal aspects of sectors (e.g., buildings or waste management) and do not differentiate results geographically within a country. Decarbonization strategies at the country, sector, and subnational level will need to include these details.

Fourth, data used to run SiSePuede were derived entirely from public and open sources. Data for many countries were limited in these datasets, and many imputations were used to generate estimates for countries that had no available data. In particular, country-level data for land-use transition matrices were unavailable. To fill this gap, exogenous land-use transitions were developed using an optimization model that explored potential matrices that align with land-use prevalence data found in FAO data. Future iterations could improve on this approach by integrating satellite data.

## Strategies and Transformations

Table 2.3 summarizes the transformations evaluated in the study by sector, subsector (if applicable) and category. For each transformation, we have identified an emissions effect, costs, and benefits per unit of implementation, and a maximum level of implementation by 2050 based on our review of the literature. These are detailed in the technical appendices. Many, if not most, of these transformations are complex to implement, requiring new or different technology, regulatory and infrastructure changes, financing, shifts in public perception and acceptance, and a host of other public and private efforts. Our intent here is not to oversimplify or gloss over the implementation complexities, but to analyze the potential emissions, costs, and benefits of undertaking a particular transformation.
As another example, SiSePuede simulates the impact of domestic shifts toward healthier diets with less red meat. The resulting impact on household food expenditures is valued based on exogenous food prices, even though a decrease in demand for red meat would endogenously decrease red meat prices and alter that estimate. These feedbacks are not included in the analysis. However, outputs from SiSePuede can be used in specialized economic models to account for such impacts, as well as other macroeconomic impacts such as labor effects and tax revenues.

Second, SiSePuede does not contain inter-region mass balances for goods that are imported and exported (e.g., manufacturing products, crops, and/or livestock) and energy (e.g., trade in electricity and fuels).

Third, our transformations do not distinguish between informal and formal aspects of sectors (e.g., buildings or waste management) and do not differentiate results geographically within a country. Decarbonization strategies at the country, sector, and subnational level will need to include these details.

Fourth, data used to run SiSePuede were derived entirely from public and open sources. Data for many countries were limited in these datasets, and many imputations were used to generate estimates for countries that had no available data. In particular, country-level data for land-use transition matrices were unavailable. To fill this gap, exogenous land-use transitions were developed using an optimization model that explored potential matrices that align with land-use prevalence data found in FAO data. Future iterations could improve on this approach by integrating satellite data.

## Strategies and Transformations

Table 2.3 summarizes the transformations evaluated in the study by sector, subsector (if applicable) and category. For each transformation, we have identified an emissions effect, costs, and benefits per unit of implementation, and a maximum level of implementation by 2050 based on our review of the literature. These are detailed in the technical appendices. Many, if not most, of these transformations are complex to implement, requiring new or different technology, regulatory and infrastructure changes, financing, shifts in public perception and acceptance, and a host of other public and private efforts. Our intent here is not to oversimplify or gloss over the implementation complexities, but to analyze the potential emissions, costs, and benefits of undertaking a particular transformation.
<table><caption>Table 2.3 Transformations in Incremental Improvements, Supply-Side Solutions, and Changing Consumption categories</caption><thead><tr><th>Sector</th><th>Subsector</th><th>Incremental improvements</th><th>Supply-Side Solutions</th><th>Changing Consumption</th></tr></thead><tbody><tr><td rowspan="4">Agriculture, forests, and other land use</td><td>Crops</td><td><ul><li>Reduce excess fertilizer use</li><li>Expand conservation agriculture</li><li>Improve rice management</li></ul></td><td></td><td></td></tr><tr><td>Livestock</td><td></td><td><ul><li>Reduce enteric fermentation</li><li>Expand silvopasture</li><li>Manure management</li></ul></td><td></td></tr><tr><td>Forests and land use</td><td></td><td></td><td><ul><li>Halt deforestation</li></ul></td></tr><tr><td>Cross-cutting</td><td><ul><li>Accelerate productivity</li><li>Use gains in productivity to conserve land</li></ul></td><td><ul><li>Reduce supply chain losses</li></ul></td><td><ul><li>Induce afforestation with a shift in agricultural production and consumption</li></ul></td></tr><tr><td rowspan="3">Industry</td><td>Cross-cutting</td><td><ul><li>Shift from virgin to recycled inputs</li><li>Substitute clinker in cement conserve land</li></ul></td><td><ul><li>Increase efficiency of materials use</li></ul></td><td></td></tr><tr><td>Industrial energy</td><td></td><td><ul><li>Fuel shift low-temperature heat to heat pumps</li><li>Fuel shift high-temperature heat to electricity and hydrogen</li></ul></td><td></td></tr><tr><td>Other abatement</td><td></td><td><ul><li>Reduce F-gases</li><li>Abate N2O in chemical production</li><li>CCS for steel, cement, chemicals, and plastics</li></ul></td><td></td></tr><tr><td>Buildings</td><td></td><td><ul><li>Increase energy efficiency of appliances</li><li>Increase building shell efficiency</li></ul></td><td><ul><li>Fuel switch heat to heat pumps</li></ul></td><td></td></tr></tbody></table>
<table><caption>Table 2.3 Transformations in Incremental Improvements, Supply-Side Solutions, and Changing Consumption categories</caption><thead><tr><th>Sector</th><th>Subsector</th><th>Incremental improvements</th><th>Supply-Side Solutions</th><th>Changing Consumption</th></tr></thead><tbody><tr><td rowspan="4">Agriculture, forests, and other land use</td><td>Crops</td><td><ul><li>Reduce excess fertilizer use</li><li>Expand conservation agriculture</li><li>Improve rice management</li></ul></td><td></td><td></td></tr><tr><td>Livestock</td><td></td><td><ul><li>Reduce enteric fermentation</li><li>Expand silvopasture</li><li>Manure management</li></ul></td><td></td></tr><tr><td>Forests and land use</td><td></td><td></td><td><ul><li>Halt deforestation</li></ul></td></tr><tr><td>Cross-cutting</td><td><ul><li>Accelerate productivity</li><li>Use gains in productivity to conserve land</li></ul></td><td><ul><li>Reduce supply chain losses</li></ul></td><td><ul><li>Induce afforestation with a shift in agricultural production and consumption</li></ul></td></tr><tr><td rowspan="3">Industry</td><td>Cross-cutting</td><td><ul><li>Shift from virgin to recycled inputs</li><li>Substitute clinker in cement conserve land</li></ul></td><td><ul><li>Increase efficiency of materials use</li></ul></td><td></td></tr><tr><td>Industrial energy</td><td></td><td><ul><li>Fuel shift low-temperature heat to heat pumps</li><li>Fuel shift high-temperature heat to electricity and hydrogen</li></ul></td><td></td></tr><tr><td>Other abatement</td><td></td><td><ul><li>Reduce F-gases</li><li>Abate N2O in chemical production</li><li>CCS for steel, cement, chemicals, and plastics</li></ul></td><td></td></tr><tr><td>Buildings</td><td></td><td><ul><li>Increase energy efficiency of appliances</li><li>Increase building shell efficiency</li></ul></td><td><ul><li>Fuel switch heat to heat pumps</li></ul></td><td></td></tr></tbody></table>
<table><tr><td>Transport</td><td>Fuels and vehicles</td><td><ul><li>Increase transportation energy efficiency</li></ul></td><td><ul><li>Fuel switch medium- and heavy-duty road transport</li><li>Electrify rail</li><li>Fuel switch maritime</li></ul></td><td><ul><li>Electrify light-duty road transport</li></ul></td></tr><tr><td></td><td>Mode shifting and occupancy</td><td><ul><li>Mode shift freight</li></ul></td><td><ul><li>Increase occupancy for private vehicles</li><li>Mode shift local passenger travel to transit and non-motorized</li><li>Mode shift regional passenger travel to bus and rail</li></ul></td><td></td></tr><tr><td>Energy production</td><td><ul><li>Reduce transmission losses</li></ul></td><td><ul><li>Produce electricity with renewables</li><li>Produce hydrogen with renewables</li><li>Fix leaks of fugitive emissions</li><li>Flare (instead of venting) fugitive emissions that cannot be captured</li></ul></td><td><ul><li>Halt deforestation</li></ul></td><td></td></tr><tr><td>Waste</td><td>Sanitation and wastewater</td><td><ul><li>Universal safe sanitation</li><li>Treat wastewater</li></ul></td><td><ul><li>Recover energy from wastewater treatment</li></ul></td><td></td></tr><tr><td></td><td>Solid waste management</td><td><ul><li>Expand waste collection and end open dumping/burning</li><li>Divert waste to recyclables</li></ul></td><td><ul><li>Increasing capture and use of biogas in digesters and landfills</li></ul></td><td><ul><li>Reduce consumer food waste</li><li>Divert organic material to composting or digesters</li></ul></td></tr></table>
<table><tr><td>Transport</td><td>Fuels and vehicles</td><td><ul><li>Increase transportation energy efficiency</li></ul></td><td><ul><li>Fuel switch medium- and heavy-duty road transport</li><li>Electrify rail</li><li>Fuel switch maritime</li></ul></td><td><ul><li>Electrify light-duty road transport</li></ul></td></tr><tr><td></td><td>Mode shifting and occupancy</td><td><ul><li>Mode shift freight</li></ul></td><td><ul><li>Increase occupancy for private vehicles</li><li>Mode shift local passenger travel to transit and non-motorized</li><li>Mode shift regional passenger travel to bus and rail</li></ul></td><td></td></tr><tr><td>Energy production</td><td><ul><li>Reduce transmission losses</li></ul></td><td><ul><li>Produce electricity with renewables</li><li>Produce hydrogen with renewables</li><li>Fix leaks of fugitive emissions</li><li>Flare (instead of venting) fugitive emissions that cannot be captured</li></ul></td><td><ul><li>Halt deforestation</li></ul></td><td></td></tr><tr><td>Waste</td><td>Sanitation and wastewater</td><td><ul><li>Universal safe sanitation</li><li>Treat wastewater</li></ul></td><td><ul><li>Recover energy from wastewater treatment</li></ul></td><td></td></tr><tr><td></td><td>Solid waste management</td><td><ul><li>Expand waste collection and end open dumping/burning</li><li>Divert waste to recyclables</li></ul></td><td><ul><li>Increasing capture and use of biogas in digesters and landfills</li></ul></td><td><ul><li>Reduce consumer food waste</li><li>Divert organic material to composting or digesters</li></ul></td></tr></table>
## Emissions, Cost, and Benefit Metrics

We evaluate the performance of all strategies in three general dimensions:

1. GHG emissions at 100-year Global Warming Potential (GWP) consistent with the Paris Agreement (Paris Agreement to the United Nations Framework Convention on Climate Change, 2015). GHG emissions include a wide range of gases, e.g., CO2 emissions from electricity production, N2O from cement production, methane (CH4) from enteric fermentation, and F-gases from chemicals production.

2. Technical costs or benefits, which generally are experienced by actors within a sector and also are generally internal to markets. These include capital, operational, maintenance, and fuel-related expenditures and savings, as well as changes in value added in different sectors or subsectors.

3. Non-technical costs or benefits that are essential to economic development and human welfare, but generally accrue to non-sector actors and/or may be entirely external to the market.

Table 2.4 presents a summary of the costs and benefits of transformations across different sectors. Appendices A-G provide additional detail on each of these performance metrics, costs, and benefits.

## Exogenous Uncertainties

Many transformations' effects, costs, and benefits are deeply uncertain. To address uncertainty, the strategies' performances were evaluated under 1,000 different futures to identify conditions in which they may fail to meet either economic or emissions goals. Each future was generated with a combination of three types of uncertainties:

1. Emission driver uncertainties, which control demand for goods and services and technical or environmental factors that determine the emissions intensity of producing these goods and services. Examples include demand for beef in consumers' diets, demand for transportation, waste production, productivity improvements in agriculture, and sequestration capacity of different forest types.

2. Transformation effect uncertainties, which determine sectorial transformations' effectiveness in reducing emissions. Examples of these uncertainties include the effect that conservation agriculture and rice management have on emissions reductions in the agricultural sector, the effect that enteric fermentation management has on reducing emissions from livestock, or the extent to which the investments in public transport would lead people to shift to transit away from private vehicles.

3. Transformation costs uncertainties include factors that determine the cost and benefits of different transformations such as fuel costs, renewable energy production costs, human health and pollution externalities' economic value, and ecosystem services' value.
## Emissions, Cost, and Benefit Metrics

We evaluate the performance of all strategies in three general dimensions:

1. GHG emissions at 100-year Global Warming Potential (GWP) consistent with the Paris Agreement (Paris Agreement to the United Nations Framework Convention on Climate Change, 2015). GHG emissions include a wide range of gases, e.g., CO2 emissions from electricity production, N2O from cement production, methane (CH4) from enteric fermentation, and F-gases from chemicals production.

2. Technical costs or benefits, which generally are experienced by actors within a sector and also are generally internal to markets. These include capital, operational, maintenance, and fuel-related expenditures and savings, as well as changes in value added in different sectors or subsectors.

3. Non-technical costs or benefits that are essential to economic development and human welfare, but generally accrue to non-sector actors and/or may be entirely external to the market.

Table 2.4 presents a summary of the costs and benefits of transformations across different sectors. Appendices A-G provide additional detail on each of these performance metrics, costs, and benefits.

## Exogenous Uncertainties

Many transformations' effects, costs, and benefits are deeply uncertain. To address uncertainty, the strategies' performances were evaluated under 1,000 different futures to identify conditions in which they may fail to meet either economic or emissions goals. Each future was generated with a combination of three types of uncertainties:

1. Emission driver uncertainties, which control demand for goods and services and technical or environmental factors that determine the emissions intensity of producing these goods and services. Examples include demand for beef in consumers' diets, demand for transportation, waste production, productivity improvements in agriculture, and sequestration capacity of different forest types.

2. Transformation effect uncertainties, which determine sectorial transformations' effectiveness in reducing emissions. Examples of these uncertainties include the effect that conservation agriculture and rice management have on emissions reductions in the agricultural sector, the effect that enteric fermentation management has on reducing emissions from livestock, or the extent to which the investments in public transport would lead people to shift to transit away from private vehicles.

3. Transformation costs uncertainties include factors that determine the cost and benefits of different transformations such as fuel costs, renewable energy production costs, human health and pollution externalities' economic value, and ecosystem services' value.
Table 2.5 describes in detail the factors included in each group. A key concern for policymakers will be how and how effectively different transformations can be implemented. For this study’s aims of understanding transformation effects, however, we treat the level of implementation of each transformation as a policy lever rather than an exogenous uncertainty.

We discount future costs and benefits using a fixed 7% discount rate, a rate that is at the higher bound of the range of values of midcentury evaluation of climate policy portfolios (Emmerling, et al., 2019). We do not explore over the discount rate in uncertainty experiments because, in this study, the discount rate does not have an ordinal impact on results, as transformations’ implementation and timing are specified exogenously. Thus, the discount rate would affect the magnitude of costs and benefits but would not change our findings’ arc. In other studies where climate policy response is modeled as an optimal response to damages induced by climate change, the discount rate’s magnitude impacts policies’ timing and intensity over time. While there is debate among climate specialists regarding the discount rate’s appropriate value (e.g., Sterner, 2008; Nordhaus, 2007), studies show that in the context of deep uncertainty, other parameters such as the rate of technological change and climate sensitivity are significantly more impactful in mitigation trajectories (Molina-Perez, 2016).
Table 2.5 describes in detail the factors included in each group. A key concern for policymakers will be how and how effectively different transformations can be implemented. For this study’s aims of understanding transformation effects, however, we treat the level of implementation of each transformation as a policy lever rather than an exogenous uncertainty.

We discount future costs and benefits using a fixed 7% discount rate, a rate that is at the higher bound of the range of values of midcentury evaluation of climate policy portfolios (Emmerling, et al., 2019). We do not explore over the discount rate in uncertainty experiments because, in this study, the discount rate does not have an ordinal impact on results, as transformations’ implementation and timing are specified exogenously. Thus, the discount rate would affect the magnitude of costs and benefits but would not change the our findings’ arc. In other studies where climate policy response is modeled as an optimal response to damages induced by climate change, the discount rate’s magnitude impacts policies’ timing and intensity over time. While there is debate among climate specialists regarding the discount rate’s appropriate value (e.g., Sterner, 2008; Nordhaus, 2007), studies show that in the context of deep uncertainty, other parameters such as the rate of technological change and climate sensitivity are significantly more impactful in mitigation trajectories (Molina-Perez, 2016).
<table><caption>Table 2.4 Transformation costs and benefits by sector</caption><thead><tr><td>Sector</td><td>Technical Costs and Benefits</td><td>Non-Technical Costs and benefits</td></tr></thead><tbody><tr><td>Agriculture, forests, and other land use</td><td><ul><li>Investment cost of transformations</li><li>Value of agricultural inputs, such as fuel and fertilizer</li><li>Value of agricultural outputs (crops and livestock produced)</li><li>Technical cost of reforestation</li></ul></td><td><ul><li>Nitrate leaching and runoff from fertilizer</li><li>Soil health benefits of conservation agriculture</li><li>Ecosystem services of forests</li><li>Human health and productivity of better diets</li><li>Household grocery costs from improved</li></ul></td></tr><tr><td>Industry</td><td><ul><li>Investment cost of transformations</li><li>Maintenance savings of transformations, e.g., from lower maintenance of heat pumps</li><li>Value of industrial inputs, such as fuel</li><li>Value of industrial outputs</li></ul></td><td><ul><li>Air quality changes from industrial energy and production</li></ul></td></tr><tr><td>Buildings</td><td><ul><li>Investment cost of transformations</li><li>Maintenance savings of transformations, e.g., from lower maintenance of heat pumps</li><li>Value of building inputs, such as fuel</li></ul></td><td><ul><li>We did not assess non-technical benefits and costs in buildings such as indoor air</li></ul></td></tr><tr><td>Transport</td><td><ul><li>Investment cost of transformations</li><li>System cost of transportation service provisioning</li><li>Maintenance savings, e.g., from lower maintenance of electric vehicles</li><li>Value of transport inputs, such as fuel</li></ul></td><td><ul><li>Health impacts of changing air quality</li><li>Health and productivity impacts of avoided crashes</li><li>Productivity impacts from congestion</li></ul></td></tr><tr><td>Energy production</td><td><ul><li>Capital and operating expenditures of electricity production</li><li>Cost of fuels used to produce electricity and other fuel production</li><li>Investment cost of other transformations</li></ul></td><td><ul><li>Health benefit of avoided air pollution</li></ul></td></tr><tr><td>Waste</td><td><ul><li>Technical costs of transformations</li><li>Value of energy recovery</li></ul></td><td><ul><li>Health impacts of universal safe sanitation</li><li>Health and environmental impacts of ending open dumping</li><li>Water quality impacts of wastewater treatment</li></ul></td></tr></tbody></table>
<table><caption>Table 2.4 Transformation costs and benefits by sector</caption><thead><tr><td>Sector</td><td>Technical Costs and Benefits</td><td>Non-Technical Costs and benefits</td></tr></thead><tbody><tr><td>Agriculture, forests, and other land use</td><td><ul><li>Investment cost of transformations</li><li>Value of agricultural inputs, such as fuel and fertilizer</li><li>Value of agricultural outputs (crops and livestock produced)</li><li>Technical cost of reforestation</li></ul></td><td><ul><li>Nitrate leaching and runoff from fertilizer</li><li>Soil health benefits of conservation agriculture</li><li>Ecosystem services of forests</li><li>Human health and productivity of better diets</li><li>Household grocery costs from improved</li></ul></td></tr><tr><td>Industry</td><td><ul><li>Investment cost of transformations</li><li>Maintenance savings of transformations, e.g., from lower maintenance of heat pumps</li><li>Value of industrial inputs, such as fuel</li><li>Value of industrial outputs</li></ul></td><td><ul><li>Air quality changes from industrial energy and production</li></ul></td></tr><tr><td>Buildings</td><td><ul><li>Investment cost of transformations</li><li>Maintenance savings of transformations, e.g., from lower maintenance of heat pumps</li><li>Value of building inputs, such as fuel</li></ul></td><td><ul><li>We did not assess non-technical benefits and costs in buildings such as indoor air</li></ul></td></tr><tr><td>Transport</td><td><ul><li>Investment cost of transformations</li><li>System cost of transportation service provisioning</li><li>Maintenance savings, e.g., from lower maintenance of electric vehicles</li><li>Value of transport inputs, such as fuel</li></ul></td><td><ul><li>Health impacts of changing air quality</li><li>Health and productivity impacts of avoided crashes</li><li>Productivity impacts from congestion</li></ul></td></tr><tr><td>Energy production</td><td><ul><li>Capital and operating expenditures of electricity production</li><li>Cost of fuels used to produce electricity and other fuel production</li><li>Investment cost of other transformations</li></ul></td><td><ul><li>Health benefit of avoided air pollution</li></ul></td></tr><tr><td>Waste</td><td><ul><li>Technical costs of transformations</li><li>Value of energy recovery</li></ul></td><td><ul><li>Health impacts of universal safe sanitation</li><li>Health and environmental impacts of ending open dumping</li><li>Water quality impacts of wastewater treatment</li></ul></td></tr></tbody></table>
<table><caption>Table 2.5. Uncertainties</caption><thead><tr><th>Sector</th><th>Emissions driver uncertainties</th><th>Transformation effect uncertainties</th><th>Transformation cost uncertainties</th></tr></thead><tbody><tr><td>Cross-cutting</td><td></td><td></td><td><ul><li>Fuel costs</li><li>Renewables</li><li>Fossil fuels</li><li>Hydrogen</li><li>Renewable electricity production costs (battery and production)</li><li>Value of human health externalities</li><li>Value of environmental pollution externalities</li><li>Value of industrial outputs</li></ul></td></tr><tr><td>Agriculture, forests, and other land use</td><td><ul><li>Annual change in crop and livestock productivity</li><li>Overall demand for agricultural products</li><li>Demand for beef in diets as a function of wealth, which drives deforestation</li><li>Emissions and sequestration from different land use</li><li>Emission of land-use conversion</li></ul></td><td><ul><li>Effect of conservation agriculture and rice management</li><li>Effect of enteric fermentation interventions productivity of better diets</li><li>Household grocery costs from improved diets</li></ul></td><td><ul><li>Cost of transformations</li><li>Benefit of transformations</li><li>Value of ecosystem services</li></ul></td></tr><tr><td>Transport</td><td><ul><li>Demand for transport</li><li>Demand for car/air travel</li></ul></td><td></td><td><ul><li>Cost of transport by mode</li></ul></td></tr><tr><td>Industry</td><td><ul><li>Demand for industrial output</li></ul></td><td><ul><li>Availability of clinker substitutes</li></ul></td><td><ul><li>Cost of efficiency improvements</li><li>Cost of clinker substitutes</li></ul></td></tr><tr><td>Buildings</td><td><ul><li>Demand for heating/cooling</li></ul></td><td></td><td><ul><li>Cost of efficiency improvements</li></ul></td></tr><tr><td>Electricity and energy production</td><td><ul><li>Productivity of hydropower</li></ul></td><td></td><td><ul><li>Transmission cost</li><li>Cost of abating fugitive emissions</li></ul></td></tr><tr><td>Waste</td><td><ul><li>Waste production</li></ul></td><td></td><td><ul><li>Cost of sanitation and waste infrastructure</li></ul></td></tr></tbody></table>
<table><caption>Table 2.5. Uncertainties</caption><thead><tr><th>Sector</th><th>Emissions driver uncertainties</th><th>Transformation effect uncertainties</th><th>Transformation cost uncertainties</th></tr></thead><tbody><tr><td>Cross-cutting</td><td></td><td></td><td><ul><li>Fuel costs</li><li>Renewables</li><li>Fossil fuels</li><li>Hydrogen</li><li>Renewable electricity production costs (battery and production)</li><li>Value of human health externalities</li><li>Value of environmental pollution externalities</li><li>Value of industrial outputs</li></ul></td></tr><tr><td>Agriculture, forests, and other land use</td><td><ul><li>Annual change in crop and livestock productivity</li><li>Overall demand for agricultural products</li><li>Demand for beef in diets as a function of wealth, which drives deforestation</li><li>Emissions and sequestration from different land use</li><li>Emission of land-use conversion</li></ul></td><td><ul><li>Effect of conservation agriculture and rice management</li><li>Effect of enteric fermentation interventions productivity of better diets</li><li>Household grocery costs from improved diets</li></ul></td><td><ul><li>Cost of transformations</li><li>Benefit of transformations</li><li>Value of ecosystem services</li></ul></td></tr><tr><td>Transport</td><td><ul><li>Demand for transport</li><li>Demand for car/air travel</li></ul></td><td></td><td><ul><li>Cost of transport by mode</li></ul></td></tr><tr><td>Industry</td><td><ul><li>Demand for industrial output</li></ul></td><td><ul><li>Availability of clinker substitutes</li></ul></td><td><ul><li>Cost of efficiency improvements</li><li>Cost of clinker substitutes</li></ul></td></tr><tr><td>Buildings</td><td><ul><li>Demand for heating/cooling</li></ul></td><td></td><td><ul><li>Cost of efficiency improvements</li></ul></td></tr><tr><td>Electricity and energy production</td><td><ul><li>Productivity of hydropower</li></ul></td><td></td><td><ul><li>Transmission cost</li><li>Cost of abating fugitive emissions</li></ul></td></tr><tr><td>Waste</td><td><ul><li>Waste production</li></ul></td><td></td><td><ul><li>Cost of sanitation and waste infrastructure</li></ul></td></tr></tbody></table>
<figure><img src="image_18.png" /></figure>

# Understanding the Effects of Transformations on Decarbonization and Development
<figure><img src="image_18.png" /></figure>

# Understanding the Effects of Transformations on Decarbonization and Development
In this chapter, we analyze the region's decarbonization and economic potential. We evaluate the emissions, costs, and benefits of different categories of transformations relative to a traditional development trajectory. The analysis uses nominal values for each uncertain variable and assumes each transformation is implemented to its maximum potential level. Chapter 4 explores the effects of transformations under uncertainty and with varying levels of implementation.

**Emissions Under a Traditional Development Trajectory**

Under a Traditional Development trajectory, one that is unconcerned with decarbonization, we estimate emissions would increase in Latin American and the Caribbean by 70% from 4.1 GtCO2e in 2020 to 6.9 GtCO2e by 2050 (see Figure 3.1). This increase is driven by projected population and GDP growth, which results in more activity overall and a shift in the structure of that activity associated with increasing wealth. This includes, for example, a shift toward more travel in private automobiles and more production and consumption of beef, with associated deforestation for grazeland. These trends are counteracted by increases in energy efficiency and productivity through improved technology, and a modest increase in the use of renewables for electricity production.

**Exploring Transformations' Emissions, Costs, and Benefits**

Against the backdrop of traditional development, we evaluate the emissions and economic effect of transformations, some of which are already underway in the region. We first examine the effects of maximally implementing each transformation category—Incremental Improvements, Supply-Side Solutions, and Changing Consumptions—and then of maximally implementing all transformations simultaneously. This helps explore these questions: How far can incremental improvements alone take the region toward its decarbonization and development goals? Are structural changes to the economy necessary to reach net zero? How do these approaches' costs and benefits compare? What are the effects of maximally implementing all actions? These results use nominal assumptions for all exogenous uncertainties.

Four figures illustrate our findings. Figure 3.2 shows the emission trajectory under each category of transformations alongside the emissions under Traditional Development (shown alone in Figure 3.1). Emissions are disaggregated by sector and net CO2e emissions are indicated by a solid blue line. Values less than zero indicate negative emissions, i.e., sequestration and offsets. Figure 3.3 shows land use by type under each category over time. The trends in this figure help explain some of the emissions results, as preservation of primary forests and expansion of secondary forests plays a pivotal role in the region's emissions and development.

Figures 3.4 and 3.5 show the costs and benefits of each of the four categories of transformations relative to Traditional Development over the period of 2025-2050 in 2019 US dollars. Figure 3.4 shows the nominal undiscounted benefits in 5-year increments, while Figure 3.5 shows these benefits' net present value using a 7% discount rate.
In this chapter, we analyze the region's decarbonization and economic potential. We evaluate the emissions, costs, and benefits of different categories of transformations relative to a traditional development trajectory. The analysis uses nominal values for each uncertain variable and assumes each transformation is implemented to its maximum potential level. Chapter 4 explores the effects of transformations under uncertainty and with varying levels of implementation.

**Emissions Under a Traditional Development Trajectory**

Under a Traditional Development trajectory, one that is unconcerned with decarbonization, we estimate emissions would increase in Latin American and the Caribbean by 70% from 4.1 GtCO2e in 2020 to 6.9 GtCO2e by 2050 (see Figure 3.1). This increase is driven by projected population and GDP growth, which results in more activity overall and a shift in the structure of that activity associated with increasing wealth. This includes, for example, a shift toward more travel in private automobiles and more production and consumption of beef, with associated deforestation for grazeland. These trends are counteracted by increases in energy efficiency and productivity through improved technology, and a modest increase in the use of renewables for electricity production.

**Exploring Transformations' Emissions, Costs, and Benefits**

Against the backdrop of traditional development, we evaluate the emissions and economic effect of transformations, some of which are already underway in the region. We first examine the effects of maximally implementing each transformation category—Incremental Improvements, Supply-Side Solutions, and Changing Consumptions—and then of maximally implementing all transformations simultaneously. This helps explore these questions: How far can incremental improvements alone take the region toward its decarbonization and development goals? Are structural changes to the economy necessary to reach net zero? How do these approaches' costs and benefits compare? What are the effects of maximally implementing all actions? These results use nominal assumptions for all exogenous uncertainties.

Four figures illustrate our findings. Figure 3.2 shows the emission trajectory under each category of transformations alongside the emissions under Traditional Development (shown alone in Figure 3.1). Emissions are disaggregated by sector and net CO2e emissions are indicated by a solid blue line. Values less than zero indicate negative emissions, i.e., sequestration and offsets. Figure 3.3 shows land use by type under each category over time. The trends in this figure help explain some of the emissions results, as preservation of primary forests and expansion of secondary forests plays a pivotal role in the region's emissions and development.

Figures 3.4 and 3.5 show the costs and benefits of each of the four categories of transformations relative to Traditional Development over the period of 2025-2050 in 2019 US dollars. Figure 3.4 shows the nominal undiscounted benefits in 5-year increments, while Figure 3.5 shows these benefits' net present value using a 7% discount rate.
<figure><img src="image_19.png" /><figcaption>Figure 3.1 Emissions under Traditional Development.</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>Figure 3.2 Emissions under maximum implementation of transformations by category.</figcaption></figure>
<figure><img src="image_19.png" /><figcaption>Figure 3.1 Emissions under Traditional Development.</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>Figure 3.2 Emissions under maximum implementation of transformations by category.</figcaption></figure>
<figure><img src="image_21.png" /><figcaption>Figure 3.3 Land use in hectares (ha) under maximum implementation of transformations by category.</figcaption></figure>

<figure><img src="image_22.png" /></figure>

Note: This figure shows annual benefits in 5-year time slices in each category of transformations, compared to a future under Traditional Development. These benefits are undiscounted, and negative benefits imply costs. The black line shows the net benefit across all categories.

<caption>Figure 3.4 Nominal costs and benefits under maximum implementation of transformations by category.</caption>
<figure><img src="image_21.png" /><figcaption>Figure 3.3 Land use in hectares (ha) under maximum implementation of transformations by category.</figcaption></figure>

<figure><img src="image_22.png" /></figure>

Note: This figure shows annual benefits in 5-year time slices in each category of transformations, compared to a future under Traditional Development. These benefits are undiscounted, and negative benefits imply costs. The black line shows the net benefit across all categories.

<caption>Figure 3.4 Nominal costs and benefits under maximum implementation of transformations by category.</caption>
<figure><img src="image_23.png" /></figure>

Note: This figure shows the present value of costs and benefits in each category of transformations, compared to a future under Traditional Development. These benefits are discounted at 7%, and negative values imply costs. The black line shows the net value of all costs and benefits; the labeled red lines show the net value of costs and benefits that are incurred by sector actors and excluding hard-to-value (and largely external) costs and benefits of health, safety, and productivity; avoided pollution; and ecosystem services.

<caption>**Figure 3.5 Discounted costs and benefits under maximum implementation of transformations by category.**</caption>

*Maximizing Incremental Improvements*

Maximum implementation of transformations in Incremental Improvements reduces emissions in 2050 by 36% to 4.5 GtCO2e. The gains from maximizing efficiency and productivity meaningfully reduce emissions in every sector, including in agriculture, where productivity gains reduce land-use needs, which are directed toward slowing deforestation and increasing secondary forests. However, the reductions are not enough, and significant residual emissions remain in all sectors. Simultaneously, continued (albeit slower) deforestation (see Figure 3.3) means that the land-use and forestry sector continues to be a net emitter and not the sink the region needs it to be to offset those residual emissions (Dumas et al., 2022).
<figure><img src="image_23.png" /></figure>

Note: This figure shows the present value of costs and benefits in each category of transformations, compared to a future under Traditional Development. These benefits are discounted at 7%, and negative values imply costs. The black line shows the net value of all costs and benefits; the labeled red lines show the net value of costs and benefits that are incurred by sector actors and excluding hard-to-value (and largely external) costs and benefits of health, safety, and productivity; avoided pollution; and ecosystem services.

<caption>**Figure 3.5 Discounted costs and benefits under maximum implementation of transformations by category.**</caption>

*Maximizing Incremental Improvements*

Maximum implementation of transformations in Incremental Improvements reduces emissions in 2050 by 36% to 4.5 GtCO2e. The gains from maximizing efficiency and productivity meaningfully reduce emissions in every sector, including in agriculture, where productivity gains reduce land-use needs, which are directed toward slowing deforestation and increasing secondary forests. However, the reductions are not enough, and significant residual emissions remain in all sectors. Simultaneously, continued (albeit slower) deforestation (see Figure 3.3) means that the land-use and forestry sector continues to be a net emitter and not the sink the region needs it to be to offset those residual emissions (Dumas et al., 2022).
While far from reaching net zero, Incremental Improvements offers significant net benefits across the region's economies of approximately $1.8 trillion, net of the technical investment costs in energy efficiency, agricultural productivity and efficiency, and basic civic infrastructure (sanitation, waste management, and wastewater treatment). Two effects are at play. First, an increase in agricultural productivity results in more agricultural output in the near term than under Traditional Development, while also slowing deforestation and providing ecosystem service benefits (see Figure 3.4). Second, the energy-efficiency gains result in significant savings in avoided energy costs throughout the economy. Increases in energy efficiency means Latin America and the Caribbean can spend less on new and expensive electricity-production capacity than it would otherwise. The avoided energy production and consumption have subsequent benefits in terms of cleaner air. Investments in sanitation and waste management reduce pollution and offer benefits to human health, safety, and productivity.

## Maximizing Supply-Side Solutions

Maximizing transformations in Supply-Side Solutions reduces emissions to 4.4 Gt CO2e by 2050, a 36% reduction compared to 2050. (That Supply-Side Solutions and Incremental Improvements lead to similar reduction in emissions is an unintended coincidence because they have entirely different transformations). These reductions are the combined effect of switching to electricity and hydrogen throughout the economy and simultaneously producing electricity and hydrogen almost entirely with renewables. In addition, industrial emissions reductions are achieved by capturing process emissions in select industries and destroying particularly potent F-gases and N2O. Despite these gains, agriculture and land-use changes remain major emitters as their emissions are not primarily driven by energy use, but by biological processes of livestock and crop production and the deforestation they induce. These emissions only partly can be abated with technological solutions to enteric fermentation and livestock manure management.

On their own, transformations in Supply-Side Solutions pose a net cost. Whereas Incremental Improvements reduce the cost of electricity production by reducing overall demand through efficiency measures, Supply-Side Solutions require more electricity production because of fuel switching across the economy and making major investments to produce renewable electricity and hydrogen. This requires added capacity, storage, transmission, and other investments. Fuel switching also involves significant investment costs that are only partly recovered by other sector savings.

Supply-Side Solutions also offer smaller social and environmental co-benefits than transformations in Incremental Improvements. Many transformations—such as destroying F-gases and N2O in industry and reducing enteric fermentation—have no social and environmental co-benefits outside of emissions reductions.
While far from reaching net zero, Incremental Improvements offers significant net benefits across the region's economies of approximately $1.8 trillion, net of the technical investment costs in energy efficiency, agricultural productivity and efficiency, and basic civic infrastructure (sanitation, waste management, and wastewater treatment). Two effects are at play. First, an increase in agricultural productivity results in more agricultural output in the near term than under Traditional Development, while also slowing deforestation and providing ecosystem service benefits (see Figure 3.4). Second, the energy-efficiency gains result in significant savings in avoided energy costs throughout the economy. Increases in energy efficiency means Latin America and the Caribbean can spend less on new and expensive electricity-production capacity than it would otherwise. The avoided energy production and consumption have subsequent benefits in terms of cleaner air. Investments in sanitation and waste management reduce pollution and offer benefits to human health, safety, and productivity.

## Maximizing Supply-Side Solutions

Maximizing transformations in Supply-Side Solutions reduces emissions to 4.4 Gt CO2e by 2050, a 36% reduction compared to 2050. (That Supply-Side Solutions and Incremental Improvements lead to similar reduction in emissions is an unintended coincidence because they have entirely different transformations). These reductions are the combined effect of switching to electricity and hydrogen throughout the economy and simultaneously producing electricity and hydrogen almost entirely with renewables. In addition, industrial emissions reductions are achieved by capturing process emissions in select industries and destroying particularly potent F-gases and N2O. Despite these gains, agriculture and land-use changes remain major emitters as their emissions are not primarily driven by energy use, but by biological processes of livestock and crop production and the deforestation they induce. These emissions only partly can be abated with technological solutions to enteric fermentation and livestock manure management.

On their own, transformations in Supply-Side Solutions pose a net cost. Whereas Incremental Improvements reduce the cost of electricity production by reducing overall demand through efficiency measures, Supply-Side Solutions require more electricity production because of fuel switching across the economy and making major investments to produce renewable electricity and hydrogen. This requires added capacity, storage, transmission, and other investments. Fuel switching also involves significant investment costs that are only partly recovered by other sector savings.

Supply-Side Solutions also offer smaller social and environmental co-benefits than transformations in Incremental Improvements. Many transformations—such as destroying F-gases and N2O in industry and reducing enteric fermentation—have no social and environmental co-benefits outside of emissions reductions.
*Maximizing Changes in Consumption*

Transformations in Changing Consumption achieve greater reductions through a few key strategies. Changes to food production and consumption and changes to transport consumption combine with a slowing of deforestation to reduce emissions to 1.9 GtCO2e by 2050. This is a reduction of 73% compared to Traditional Development. Even more importantly, halting deforestation and shifting production and consumption from beef to crops makes room for secondary afforestation, converting forests and land use from significant net emitters to net sequesters. This is essential to offset residual emissions and reach net zero. However, this transformations category does little to abate emissions in other sectors, and thus the residual emissions are far too high to be offset by improvements in forests and land use.

These transformations offer significant net benefits, primarily from social and environmental benefits, such as $75 billion in avoided pollution costs from improving transport and waste management; $800 billion in other avoided health, safety, and productivity costs, including household savings from healthier diets and avoided food waste and avoided congestion and crash costs from changes to transport; and $290 billion in ecosystem services from preserved primary forests and new secondary forests.

Savings in fuel costs and other technical costs, primarily from transforming transportation, lead to additional benefits. In this strategy, mode shifting passenger transport yields significant economic savings, because it often costs less to transport people via transit than by private auto (Jakob, 2006), although the costs are differently borne by the private and public sectors.

The transformations also pose some costs—in terms of electricity production to meet higher electricity demands ($60 billion); the foregone cost of agricultural output ($185 billion); and the technical investment costs of, for example, electrifying transport ($70 billion), but total costs are far less than total benefits.

The overarching conclusion is that, while each of these categories of transformations can achieve significant reductions, even at maximum implementation, none approach net-zero because each one focuses transformations on only part of the ASIF framework. Instead, a whole-economy approach that transforms activities, structure, and intensity is necessary to achieve net-zero emissions.

*Maximizing All Actions*

The All Actions trajectory implements all transformations to achieve a whole-economy approach to decarbonization and provides a sense of the emissions reduction and economic potential in the region. Net zero is achieved in 2040 when all transformations are implemented to maximum effect. This simultaneously minimizes emissions from each economic sector (industry, transport, waste, buildings, and energy production) and makes changes to livestock production and land use to halt deforestation and accelerate reforestation sufficiently to offset any residual emissions from all sectors. Despite the substantial political, financing, logistics,
*Maximizing Changes in Consumption*

Transformations in Changing Consumption achieve greater reductions through a few key strategies. Changes to food production and consumption and changes to transport consumption combine with a slowing of deforestation to reduce emissions to 1.9 GtCO2e by 2050. This is a reduction of 73% compared to Traditional Development. Even more importantly, halting deforestation and shifting production and consumption from beef to crops makes room for secondary afforestation, converting forests and land use from significant net emitters to net sequesters. This is essential to offset residual emissions and reach net zero. However, this transformations category does little to abate emissions in other sectors, and thus the residual emissions are far too high to be offset by improvements in forests and land use.

These transformations offer significant net benefits, primarily from social and environmental benefits, such as $75 billion in avoided pollution costs from improving transport and waste management; $800 billion in other avoided health, safety, and productivity costs, including household savings from healthier diets and avoided food waste and avoided congestion and crash costs from changes to transport; and $290 billion in ecosystem services from preserved primary forests and new secondary forests.

Savings in fuel costs and other technical costs, primarily from transforming transportation, lead to additional benefits. In this strategy, mode shifting passenger transport yields significant economic savings, because it often costs less to transport people via transit than by private auto (Jakob, 2006), although the costs are differently borne by the private and public sectors.

The transformations also pose some costs—in terms of electricity production to meet higher electricity demands ($60 billion); the foregone cost of agricultural output ($185 billion); and the technical investment costs of, for example, electrifying transport ($70 billion), but total costs are far less than total benefits.

The overarching conclusion is that, while each of these categories of transformations can achieve significant reductions, even at maximum implementation, none approach net-zero because each one focuses transformations on only part of the ASIF framework. Instead, a whole-economy approach that transforms activities, structure, and intensity is necessary to achieve net-zero emissions.

*Maximizing All Actions*

The All Actions trajectory implements all transformations to achieve a whole-economy approach to decarbonization and provides a sense of the emissions reduction and economic potential in the region. Net zero is achieved in 2040 when all transformations are implemented to maximum effect. This simultaneously minimizes emissions from each economic sector (industry, transport, waste, buildings, and energy production) and makes changes to livestock production and land use to halt deforestation and accelerate reforestation sufficiently to offset any residual emissions from all sectors. Despite the substantial political, financing, logistics,
regulatory, and other important barriers, this suggests that reaching net zero by 2050 may remain within reach in Latin America and the Caribbean. At $2.7 trillion, All Actions' net benefits are also much higher than any of the three categories alone, suggesting that not only is a whole-economy approach better for emissions, it also is better for development. Figure 3.6 shows the net 2050 emissions and benefits for each transformation category.

For instance, emissions from the electricity sector can be eliminated by only switching to renewables, as under Supply-Side Solutions, but this approach comes at a high cost for the sector (see the pink bars in Figure 3.5). By simultaneously increasing energy efficiency (as in Incremental Improvements) and switching to renewables (as in Supply-Side Solutions), All Actions shows that the sector can reduce emissions by 95% at a net benefit compared to a traditional development scenario—even as total demand for electricity increases from fuel switching to electricity across the economy.

<figure><img src="image_24.png" /><figcaption>Figure 3.6 Net benefits vs. net 2050 emissions under maximum implementation of transformations by category.</figcaption></figure>
regulatory, and other important barriers, this suggests that reaching net zero by 2050 may remain within reach in Latin America and the Caribbean. At $2.7 trillion, All Actions' net benefits are also much higher than any of the three categories alone, suggesting that not only is a whole-economy approach better for emissions, it also is better for development. Figure 3.6 shows the net 2050 emissions and benefits for each transformation category.

For instance, emissions from the electricity sector can be eliminated by only switching to renewables, as under Supply-Side Solutions, but this approach comes at a high cost for the sector (see the pink bars in Figure 3.5). By simultaneously increasing energy efficiency (as in Incremental Improvements) and switching to renewables (as in Supply-Side Solutions), All Actions shows that the sector can reduce emissions by 95% at a net benefit compared to a traditional development scenario—even as total demand for electricity increases from fuel switching to electricity across the economy.

<figure><img src="image_24.png" /><figcaption>**Figure 3.6 Net benefits vs. net 2050 emissions under maximum implementation of transformations by category.**</figcaption></figure>
Similarly, All Actions also reaches net-zero emissions without affecting the total value of agricultural output (purple bars in Figure 3.5). Under incremental improvements, the increase in agricultural productivity induces an increase in agricultural output value, primarily from crops. (The increase in livestock productivity partly is redirected to slow deforestation.) This slows land-use conversion but does not return forests and land use to net sequesterers. In contrast, Changing Consumption sees major reductions in agricultural emissions primarily from foregone livestock production, but this is accompanied by a significant loss in agricultural value. When combined, the value of increasing crop output offsets the foregone livestock output's value, with no net effect. This finding confirms the relevance of a decarbonization strategy focused on dramatically increasing livestock yields, moderating beef-demand growth, and ensuring that the land saved is directed toward land sparing and ecosystem restoration (Searchinger et al., 2019; Dumas et al., 2022). It also suggests that decarbonizing agriculture warrants attention to shifting sector activity and that a key issue for governments is managing distributional effects of decarbonization actions rather than managing an overall loss of value in the sector.

These phenomena merit a more detailed look at sector effects. Figure 3.7 compares emissions produced in each sector in 2020 under Traditional Development and All Actions, with Agriculture separated from Forests and Other Land Use. Note that electricity and fuel production emissions are accounted for in the Energy Production sector. The largest changes (-4.9 GtCO2e) occur in Forests and Land Use, where halting deforestation and expanding secondary forests turn the sector from the region's largest emitter to an even larger sink. In the other sectors, the largest absolute reductions come from the other three largest emitting sectors: transport (-1.2 GtCO2e), agriculture (-0.8 GtCO2e), and industry (-0.6 GtCO2e). As a percentage, however, the largest reductions come from buildings (100%) and industry (94%) as they switch to electricity and green hydrogen, and from energy production (96%), where electricity and hydrogen are produced almost entirely with renewables.
Similarly, All Actions also reaches net-zero emissions without affecting the total value of agricultural output (purple bars in Figure 3.5). Under incremental improvements, the increase in agricultural productivity induces an increase in agricultural output value, primarily from crops. (The increase in livestock productivity partly is redirected to slow deforestation.) This slows land-use conversion but does not return forests and land use to net sequesterers. In contrast, Changing Consumption sees major reductions in agricultural emissions primarily from foregone livestock production, but this is accompanied by a significant loss in agricultural value. When combined, the value of increasing crop output offsets the foregone livestock output's value, with no net effect. This finding confirms the relevance of a decarbonization strategy focused on dramatically increasing livestock yields, moderating beef-demand growth, and ensuring that the land saved is directed toward land sparing and ecosystem restoration (Searchinger et al., 2019; Dumas et al., 2022). It also suggests that decarbonizing agriculture warrants attention to shifting sector activity and that a key issue for governments is managing distributional effects of decarbonization actions rather than managing an overall loss of value in the sector.

These phenomena merit a more detailed look at sector effects. Figure 3.7 compares emissions produced in each sector in 2020 under Traditional Development and All Actions, with Agriculture separated from Forests and Other Land Use. Note that electricity and fuel production emissions are accounted for in the Energy Production sector. The largest changes (-4.9 GtCO2e) occur in Forests and Land Use, where halting deforestation and expanding secondary forests turn the sector from the region's largest emitter to an even larger sink. In the other sectors, the largest absolute reductions come from the other three largest emitting sectors: transport (-1.2 GtCO2e), agriculture (-0.8 GtCO2e), and industry (-0.6 GtCO2e). As a percentage, however, the largest reductions come from buildings (100%) and industry (94%) as they switch to electricity and green hydrogen, and from energy production (96%), where electricity and hydrogen are produced almost entirely with renewables.
<figure><img src="image_25.png" /><figcaption>**Figure 3.7 Emissions by sector in 2050 under Traditional Development and All Actions.**</figcaption></figure>

Figure 3.8 shows the net benefits by sector under All Actions, relative to Traditional Development. Here, we reallocate the costs and benefits of electricity and energy production to energy-consuming sectors to reflect more accurately the costs and benefits those sectors will face. The largest gains are in transport, where electrification and adoption of transit lead to significant fuel cost savings ($775 billion), transport system savings ($215 billion), safety and congestion benefits ($200 billion), and avoided air pollution benefits ($150 billion). The costs are, by comparison, modest: $100 billion in technical investments, such as electrification of vehicles, and $70 billion in electricity expenditures.

Net benefits are large in Agriculture, Forests, and Land Use as well: more than $900 billion, which includes the benefits of people shifting to healthier patterns of food consumption and ecosystem services of forests. Other sectors have more modest but still significant benefits: $150 billion in buildings, primarily from energy savings in electricity, $215 billion in industry, and $180 billion in waste.
<figure><img src="image_25.png" /><figcaption>**Figure 3.7 Emissions by sector in 2050 under Traditional Development and All Actions.**</figcaption></figure>

Figure 3.8 shows the net benefits by sector under All Actions, relative to Traditional Development. Here, we reallocate the costs and benefits of electricity and energy production to energy-consuming sectors to reflect more accurately the costs and benefits those sectors will face. The largest gains are in transport, where electrification and adoption of transit lead to significant fuel cost savings ($775 billion), transport system savings ($215 billion), safety and congestion benefits ($200 billion), and avoided air pollution benefits ($150 billion). The costs are, by comparison, modest: $100 billion in technical investments, such as electrification of vehicles, and $70 billion in electricity expenditures.

Net benefits are large in Agriculture, Forests, and Land Use as well: more than $900 billion, which includes the benefits of people shifting to healthier patterns of food consumption and ecosystem services of forests. Other sectors have more modest but still significant benefits: $150 billion in buildings, primarily from energy savings in electricity, $215 billion in industry, and $180 billion in waste.
<figure><img src="image_26.png" /><figcaption>Figure 3.8 Net benefits by sector under All Actions.</figcaption></figure>

Note that costs and benefits associated with a particular sector do not mean those costs and benefits will accrue to actors in that sector. As one example, a change in the types of foods people consume will have significant consequences for farmers, ranchers, and others in the agricultural sector, but the health benefits will accrue to the healthcare system and to households. Other benefits such as forest ecosystem services are generally external and experienced diffusely throughout society.
<figure><img src="image_26.png" /><figcaption>Figure 3.8 Net benefits by sector under All Actions.</figcaption></figure>

Note that costs and benefits associated with a particular sector do not mean those costs and benefits will accrue to actors in that sector. As one example, a change in the types of foods people consume will have significant consequences for farmers, ranchers, and others in the agricultural sector, but the health benefits will accrue to the healthcare system and to households. Other benefits such as forest ecosystem services are generally external and experienced diffusely throughout society.
Sector Snapshots

In the remainder of this chapter, we discuss how to transform each sector, identify who might need to be mobilized to achieve decarbonization and development goals, and explore the extent to which the costs and benefits of those transformations might motivate or hinder change. To this end, this chapter uses sector-level results to address the following questions:

* What kinds of transformations drive the largest changes in emissions in each sector and yield the largest net benefits?

* Which transformations are in the hands of sector actors, and which are driven by those outside the sector?

* What are the net benefits of transformations?

* What are the costs and benefits that accrue to the actors within each sector, what are other internal costs and benefits experienced by other actors in the economy, and which costs and benefits are largely external?

The answers are complex, as transformations made in one sector have emissions, costs, and benefits in other sectors. For example, the emissions from concrete production are attributed to industry, and industry actors largely undertake transformations, such to concrete production by fuel switching, using CCS to capture process emissions, and substituting clinker. However, the costs of these transformations mostly are passed on to consumers of concrete in the building and transport sectors, who may then be incentivized to use concrete more efficiently, which in turn could reduce the extent to which industry needs to transform how it produces concrete.

These issues parallel the long-running complexities around producer versus consumer carbon accounting at the national and international levels (Davis and Caldeira, 2010; Bastianoni et al., 2004; Jakob et al., 2021), and the need for governments to take the lead in setting the right incentives through public investments, market design, capacity building, and price signals (Fazekas et al., 2022). In the following sections, we discuss emissions, costs, and benefits in the sector in which they are accrued, except for electricity and fuels which we describe in the “Energy Production” section and then pass on to each sector that consumes energy.

Energy production

Under nominal assumptions, taking All Actions reduces emissions from electricity and fuel productions from 1 GtCO2e to 0.1 GtCO2e in 2050. Emissions reductions are achieved by switching to renewable electricity and hydrogen production and abating fugitive emissions, while other sectors simultaneously increase their energy efficiency and reduce their use of fossil fuels. This yields a net benefit of $500 billion, almost all of which is from electricity and fuel cost savings to the economy.
## Sector Snapshots

In the remainder of this chapter, we discuss how to transform each sector, identify who might need to be mobilized to achieve decarbonization and development goals, and explore the extent to which the costs and benefits of those transformations might motivate or hinder change. To this end, this chapter uses sector-level results to address the following questions:

* What kinds of transformations drive the largest changes in emissions in each sector and yield the largest net benefits?

* Which transformations are in the hands of sector actors, and which are driven by those outside the sector?

* What are the net benefits of transformations?

* What are the costs and benefits that accrue to the actors within each sector, what are other internal costs and benefits experienced by other actors in the economy, and which costs and benefits are largely external?

The answers are complex, as transformations made in one sector have emissions, costs, and benefits in other sectors. For example, the emissions from concrete production are attributed to industry, and industry actors largely undertake transformations, such to concrete production by fuel switching, using CCS to capture process emissions, and substituting clinker. However, the costs of these transformations mostly are passed on to consumers of concrete in the building and transport sectors, who may then be incentivized to use concrete more efficiently, which in turn could reduce the extent to which industry needs to transform how it produces concrete.

These issues parallel the long-running complexities around producer versus consumer carbon accounting at the national and international levels (Davis and Caldeira, 2010; Bastianoni et al., 2004; Jakob et al., 2021), and the need for governments to take the lead in setting the right incentives through public investments, market design, capacity building, and price signals (Fazekas et al., 2022). In the following sections, we discuss emissions, costs, and benefits in the sector in which they are accrued, except for electricity and fuels which we describe in the “Energy Production” section and then pass on to each sector that consumes energy.

### Energy production

Under nominal assumptions, taking All Actions reduces emissions from electricity and fuel productions from 1 GtCO2e to 0.1 GtCO2e in 2050. Emissions reductions are achieved by switching to renewable electricity and hydrogen production and abating fugitive emissions, while other sectors simultaneously increase their energy efficiency and reduce their use of fossil fuels. This yields a net benefit of $500 billion, almost all of which is from electricity and fuel cost savings to the economy.
The energy production sector includes emissions from electricity generation, fuel mining and extraction, fuel processing and refinement, and fugitive emissions from these activities. Most energy is used domestically in the region, but some countries are significant exporters (Solano-Rodríguez et al, 2019; Welsby et al., 2021). As Figure 3.9 shows, under Traditional Development, emissions from energy production in 2020 are approximately 0.6 GtCO2e and rise to approximately 1 GtCO2e with population and GDP growth. Most of these emissions are from electricity production.

The transformations in Incremental Improvements include energy-efficiency improvements throughout the economy. In the energy production sector, the key transformation is reducing technical electricity transmission losses to OECD levels compared to much higher levels in the region today (Jiménez et al., 2014). Together, these transformations reduce emissions by 50% in 2050, to 0.6 GtCO2e, and significantly reduce capital and operating costs in the electricity sector and fuel costs (Figure 3.10).

<figure><img src="image_27.png" /><figcaption>Figure 3.9 Emissions from energy production by transformation category.</figcaption></figure>
The energy production sector includes emissions from electricity generation, fuel mining and extraction, fuel processing and refinement, and fugitive emissions from these activities. Most energy is used domestically in the region, but some countries are significant exporters (Solano-Rodríguez et al, 2019; Welsby et al., 2021). As Figure 3.9 shows, under Traditional Development, emissions from energy production in 2020 are approximately 0.6 GtCO2e and rise to approximately 1 GtCO2e with population and GDP growth. Most of these emissions are from electricity production.

The transformations in Incremental Improvements include energy-efficiency improvements throughout the economy. In the energy production sector, the key transformation is reducing technical electricity transmission losses to OECD levels compared to much higher levels in the region today (Jiménez et al., 2014). Together, these transformations reduce emissions by 50% in 2050, to 0.6 GtCO2e, and significantly reduce capital and operating costs in the electricity sector and fuel costs (Figure 3.10).

<figure><img src="image_27.png" /><figcaption>Figure 3.9 Emissions from energy production by transformation category.</figcaption></figure>
<figure><img src="image_28.png" /><figcaption>Figure 3.10 Costs and benefits in energy production by transformation category.</figcaption></figure>

Transformations under Supply-Side Solutions primarily involve transitioning electricity production away from fossil fuels to renewables (solar, wind, and geothermal), as Figure 3.9 shows, while producing hydrogen through electrolysis using renewables. (We exclude expansion of large hydropower given the climate pressures faced in the region, as well as concerns about environmental justice, biodiversity, and other issues that make hydropower expansion difficult in practice. We exclude expansion of nuclear power plants for similar reasons.) Simultaneously, other sectors progressively are switching from fossil fuels to electricity and hydrogen, increasing production demands. These shifts are expensive (Figure 3.10), costing a net of $640 billion. This comes from the large costs in electricity capital and operating expenditures (capex and opex) required to reach 95% of renewable production in the electricity mix, which are only partly offset by fuel-cost savings. Other sector investment costs and benefits are negligible by comparison. Importantly, decarbonizing the electricity sector reduces emissions from other sectors as they shift energy use to electricity (Audoly et al., 2018).
<figure><img src="image_28.png" /><figcaption>Figure 3.10 Costs and benefits in energy production by transformation category.</figcaption></figure>

Transformations under Supply-Side Solutions primarily involve transitioning electricity production away from fossil fuels to renewables (solar, wind, and geothermal), as Figure 3.9 shows, while producing hydrogen through electrolysis using renewables. (We exclude expansion of large hydropower given the climate pressures faced in the region, as well as concerns about environmental justice, biodiversity, and other issues that make hydropower expansion difficult in practice. We exclude expansion of nuclear power plants for similar reasons.) Simultaneously, other sectors progressively are switching from fossil fuels to electricity and hydrogen, increasing production demands. These shifts are expensive (Figure 3.10), costing a net of $640 billion. This comes from the large costs in electricity capital and operating expenditures (capex and opex) required to reach 95% of renewable production in the electricity mix, which are only partly offset by fuel-cost savings. Other sector investment costs and benefits are negligible by comparison. Importantly, decarbonizing the electricity sector reduces emissions from other sectors as they shift energy use to electricity (Audoly et al., 2018).
Changing Consumption has modest implications for the sector, stemming from greater demand for electricity from private vehicles' electrification. This added demand poses $65 billion in costs to the sector. (The savings in transport fuel costs from fuel switching are discussed in the transport section).

All Actions abates emissions in this sector to 0.1 GtCo2e by 2050. While the reductions relative to Supply-Side Solutions are modest, the cost implications are significant. Economy-wide efforts to reduce energy consumption mean that transitioning to a fully renewable grid and green hydrogen have no net capital or non-fuel operating costs over Traditional Development, while providing significant fuel savings. These findings are consistent with those from previous research (McCollum et al., 2018). The net benefit is $500 billion, almost entirely in the form of fuel savings in the sector. As in other sectors, the often-high cost of fuel switching can be offset meaningfully with simultaneous and cost-effective energy-efficiency efforts.

Because this sector produces energy for other sectors’ use, the costs and benefits will be passed through to those consuming sectors. Therefore, in the remaining sector snapshots, we distribute these costs and benefits to the sectors that consume energy, based on their level of consumption.

*Agriculture, forests, and other land use*

Under nominal assumptions, taking All Actions reduces emissions from agriculture, forests, and land use in 2050 from a net positive of 3 GtCO2e to a net negative of -2.6 GtCO2e, primarily from a combination of halting deforestation and, over time, shifting agricultural patterns, which frees land to increase the cultivation of secondary forest. This yields a net benefit to the region's economies of $940 billion, primarily from health benefits, household savings, and ecosystem services from forests. This also includes a cost to the agricultural sector of $200 billion from a combination of expensive technical interventions such as mitigating enteric fermentation and supply-side food losses.

Agriculture, forest, and land use are entwined in Latin America and the Caribbean, as the need for pastures and cropland drives rapid deforestation (Armenteras et al., 2017; Zalles et al., 2021; Dumas et al, 2022). Domestic demands and exports for the region's agricultural products have grown as populations and wealth increase, both in the region and in key export markets such as China (OECD and FAO, 2022).

This sector is a major source of emissions in the region. Figure 3.11 shows the emissions in this sector, which come from producing crops (including soil disturbances and application of fertilizers and other amendments), livestock (principally from enteric fermentation and manure), and converting land from forests to pasture or cropland. Note that energy used in agriculture is included in industry (e.g., for food processing) and in transport (e.g., for vehicles).
Changing Consumption has modest implications for the sector, stemming from greater demand for electricity from private vehicles' electrification. This added demand poses $65 billion in costs to the sector. (The savings in transport fuel costs from fuel switching are discussed in the transport section).

All Actions abates emissions in this sector to 0.1 GtCo2e by 2050. While the reductions relative to Supply-Side Solutions are modest, the cost implications are significant. Economy-wide efforts to reduce energy consumption mean that transitioning to a fully renewable grid and green hydrogen have no net capital or non-fuel operating costs over Traditional Development, while providing significant fuel savings. These findings are consistent with those from previous research (McCollum et al., 2018). The net benefit is $500 billion, almost entirely in the form of fuel savings in the sector. As in other sectors, the often-high cost of fuel switching can be offset meaningfully with simultaneous and cost-effective energy-efficiency efforts.

Because this sector produces energy for other sectors’ use, the costs and benefits will be passed through to those consuming sectors. Therefore, in the remaining sector snapshots, we distribute these costs and benefits to the sectors that consume energy, based on their level of consumption.

### Agriculture, forests, and other land use

Under nominal assumptions, taking All Actions reduces emissions from agriculture, forests, and land use in 2050 from a net positive of 3 GtCO2e to a net negative of -2.6 GtCO2e, primarily from a combination of halting deforestation and, over time, shifting agricultural patterns, which frees land to increase the cultivation of secondary forest. This yields a net benefit to the region's economies of $940 billion, primarily from health benefits, household savings, and ecosystem services from forests. This also includes a cost to the agricultural sector of $200 billion from a combination of expensive technical interventions such as mitigating enteric fermentation and supply-side food losses.

Agriculture, forest, and land use are entwined in Latin America and the Caribbean, as the need for pastures and cropland drives rapid deforestation (Armenteras et al., 2017; Zalles et al., 2021; Dumas et al, 2022). Domestic demands and exports for the region's agricultural products have grown as populations and wealth increase, both in the region and in key export markets such as China (OECD and FAO, 2022).

This sector is a major source of emissions in the region. Figure 3.11 shows the emissions in this sector, which come from producing crops (including soil disturbances and application of fertilizers and other amendments), livestock (principally from enteric fermentation and manure), and converting land from forests to pasture or cropland. Note that energy used in agriculture is included in industry (e.g., for food processing) and in transport (e.g., for vehicles).
Importantly, while afforestation is needed to sequester residual emissions that cannot be abated in other sectors, forest and land-use changes together are currently a net emitter, given that deforestation and climate-induced tree mortality outpace remaining forests' sequestration (Gatti et al., 2021).

Many transformations to this sector increase agricultural productivity or decrease demand for agricultural products (mainly beef), creating a gap between what can be produced and anticipated levels of demand. Over time, this excess in production capacity is used to slow forests' conversion into cropland or pastureland, and to return cropland and pasture that is not needed for production back into secondary forest. This differs from historical development patterns in which gains in productivity have been directed toward increasing agricultural output to meet growing demand for agricultural products domestically and abroad, without fully valuing the primary or secondary forest ecosystem services. This work makes these tradeoffs explicit, consistent with previous research (Searchinger et al., 2019).

Figure 3.12 shows ecosystem services and other costs and benefits, compared to a future under Traditional Development. Other costs and benefits are the value of agricultural output; health, safety, and productivity benefits; avoided pollution; other sector savings in the form of reduced labor and other inputs; and sector investment costs.

<figure><img src="image_29.png" /><figcaption>Figure 3.11 Emissions produced by agriculture, forests, and land use by transformation category.</figcaption></figure>
Importantly, while afforestation is needed to sequester residual emissions that cannot be abated in other sectors, forest and land-use changes together are currently a net emitter, given that deforestation and climate-induced tree mortality outpace remaining forests' sequestration (Gatti et al., 2021).

Many transformations to this sector increase agricultural productivity or decrease demand for agricultural products (mainly beef), creating a gap between what can be produced and anticipated levels of demand. Over time, this excess in production capacity is used to slow forests' conversion into cropland or pastureland, and to return cropland and pasture that is not needed for production back into secondary forest. This differs from historical development patterns in which gains in productivity have been directed toward increasing agricultural output to meet growing demand for agricultural products domestically and abroad, without fully valuing the primary or secondary forest ecosystem services. This work makes these tradeoffs explicit, consistent with previous research (Searchinger et al., 2019).

Figure 3.12 shows ecosystem services and other costs and benefits, compared to a future under Traditional Development. Other costs and benefits are the value of agricultural output; health, safety, and productivity benefits; avoided pollution; other sector savings in the form of reduced labor and other inputs; and sector investment costs.

<figure><img src="image_29.png" /><figcaption>Figure 3.11 Emissions produced by agriculture, forests, and land use by transformation category.</figcaption></figure>
<figure><img src="image_30.png" /><figcaption>Figure 3.12 Costs and benefits of agriculture, forest, and land-use transformations by transformation category.</figcaption></figure>

Under Incremental Improvements, gains in crop and livestock productivity are accelerated, fertilizer is used more effectively, conservation agriculture is practiced over larger areas, and rice management practices are improved. These changes offer meaningful reductions in emissions as deforestation is slowed, but the effects are neither enough to mitigate agriculture and livestock emissions nor to turn forests from net emitters to net sequesters. This strategy offers more than half a trillion dollars in economy-wide savings, as reducing supply-chain waste and increasing productivity leads to more agricultural output than under Traditional Development, while also slowing deforestation over time. The strategy also offers other savings, in terms of avoided labor and other inputs from conservation agriculture and rice management, and higher values of land that have better soil health. The result is that Incremental Improvements yield significant net benefits to the sector alone ($280 billion) and the economy overall ($400 billion).

Supply-Side Solutions involve several transformations that change how livestock are raised: reducing enteric fermentation through interventions such as vaccination and livestock diet change (EPA, 2019), using better manure-management methods with biogas recovery and use, and expanding silvopasture, which can increase land's carrying capacity while also reforesting pastures. It also involves technical interventions to reduce food loss in the agricultural supply chain, which reduces the amount of food that needs to be grown.
<figure><img src="image_30.png" /><figcaption>Figure 3.12 Costs and benefits of agriculture, forest, and land-use transformations by transformation category.</figcaption></figure>

Under Incremental Improvements, gains in crop and livestock productivity are accelerated, fertilizer is used more effectively, conservation agriculture is practiced over larger areas, and rice management practices are improved. These changes offer meaningful reductions in emissions as deforestation is slowed, but the effects are neither enough to mitigate agriculture and livestock emissions nor to turn forests from net emitters to net sequesters. This strategy offers more than half a trillion dollars in economy-wide savings, as reducing supply-chain waste and increasing productivity leads to more agricultural output than under Traditional Development, while also slowing deforestation over time. The strategy also offers other savings, in terms of avoided labor and other inputs from conservation agriculture and rice management, and higher values of land that have better soil health. The result is that Incremental Improvements yield significant net benefits to the sector alone ($280 billion) and the economy overall ($400 billion).

Supply-Side Solutions involve several transformations that change how livestock are raised: reducing enteric fermentation through interventions such as vaccination and livestock diet change (EPA, 2019), using better manure-management methods with biogas recovery and use, and expanding silvopasture, which can increase land's carrying capacity while also reforesting pastures. It also involves technical interventions to reduce food loss in the agricultural supply chain, which reduces the amount of food that needs to be grown.
Supply-Side Solutions mitigates emissions less than Incremental Improvements and has modest costs on both industry and the economy overall. Significant residual emissions remain large because land use is mostly unchanged and emissions from enteric fermentation are difficult and expensive to abate—interventions reduce methane emissions on average by less than 25% (Arndt et al., 2022, Beauchemin et al., 2020), although some specific interventions report higher effectiveness (Vijn et al., 2020).

Changing Consumption involves eventually halting deforestation and shifting patterns of food production and consumption away from beef and toward healthier food alternatives, based on Springmann et al. (2016). This transformation halves regional consumption of meat and reduces sugar consumption while increasing fruit, vegetable, and plant protein intake. Recent research suggests that a large share of the dietary and environmental benefits of shifting foods could be attained with minor adjustments, such as substituting chicken for beef in mixed dishes, but making no other dietary changes (Grummon et al., 2023). These transformations dramatically reduce emissions by eliminating land-use conversion emissions, a necessary step to returning the forests of Latin America and the Caribbean into the net carbon sink needed to offset residual emissions, consistent with findings by Dumas et al. (2022). Simultaneously, the shrinking production and consumption of beef returns grazeland and crops used as feed, such as soybean, to secondary forests, which adds to the annual sequestration capacity. These changes have a larger effect on emissions in the region than any others in our analysis.

Halting deforestation and changing patterns of food production and consumption have enormous social and environmental benefits. Given the region's high rates and costs of obesity (Popkin and Reardon, 2018), a shift to healthier diets, compared to a Traditional Development diet that increases red meat consumption per capita by 2050, offers more than $200 billion dollars in health savings benefits alone over this period, even when the per capita health benefits are valued modestly. Much of these benefits will be recouped by the healthcare sector in avoided healthcare costs. Savings in grocery bills result in a separate benefit of approximately $240 billion, given the generally higher price of meat compared to other food choices (Springmann et al., 2016; Springmann et al., 2017).

Ecosystem services are a significant benefit, but monetizing their value is difficult and particularly fraught for services that are highly subjective and hard to value—such as the value of biodiversity or spiritual and cultural value of forests (Taye et al., 2021). Taye et al., for example, find that the value of tropical rainforests found in the literature can range from under $100 per hectare (ha) to well over $10,000/ha, and a median value of all services provided by tropical forests is approximately $1,600/ha. We find that the total value of ecosystem services is large: a present value of $300 billion, even when we use conservative per-hectare values of $500/ha and $300/ha for primary and secondary forests, respectively (Taye et al, 2021; Costanza et al., 2014). The changes pose a cost to the agricultural sector, which forgoes $185 billion in agricultural output, primarily in the form of foregone beef production. Further research should investigate means to manage a rural transition in the region.
Supply-Side Solutions mitigates emissions less than Incremental Improvements and has modest costs on both industry and the economy overall. Significant residual emissions remain large because land use is mostly unchanged and emissions from enteric fermentation are difficult and expensive to abate—interventions reduce methane emissions on average by less than 25% (Arndt et al., 2022, Beauchemin et al., 2020), although some specific interventions report higher effectiveness (Vijn et al., 2020).

Changing Consumption involves eventually halting deforestation and shifting patterns of food production and consumption away from beef and toward healthier food alternatives, based on Springmann et al. (2016). This transformation halves regional consumption of meat and reduces sugar consumption while increasing fruit, vegetable, and plant protein intake. Recent research suggests that a large share of the dietary and environmental benefits of shifting foods could be attained with minor adjustments, such as substituting chicken for beef in mixed dishes, but making no other dietary changes (Grummon et al., 2023). These transformations dramatically reduce emissions by eliminating land-use conversion emissions, a necessary step to returning the forests of Latin America and the Caribbean into the net carbon sink needed to offset residual emissions, consistent with findings by Dumas et al. (2022). Simultaneously, the shrinking production and consumption of beef returns grazeland and crops used as feed, such as soybean, to secondary forests, which adds to the annual sequestration capacity. These changes have a larger effect on emissions in the region than any others in our analysis.

Halting deforestation and changing patterns of food production and consumption have enormous social and environmental benefits. Given the region's high rates and costs of obesity (Popkin and Reardon, 2018), a shift to healthier diets, compared to a Traditional Development diet that increases red meat consumption per capita by 2050, offers more than $200 billion dollars in health savings benefits alone over this period, even when the per capita health benefits are valued modestly. Much of these benefits will be recouped by the healthcare sector in avoided healthcare costs. Savings in grocery bills result in a separate benefit of approximately $240 billion, given the generally higher price of meat compared to other food choices (Springmann et al., 2016; Springmann et al., 2017).

Ecosystem services are a significant benefit, but monetizing their value is difficult and particularly fraught for services that are highly subjective and hard to value—such as the value of biodiversity or spiritual and cultural value of forests (Taye et al., 2021). Taye et al., for example, find that the value of tropical rainforests found in the literature can range from under $100 per hectare (ha) to well over $10,000/ha, and a median value of all services provided by tropical forests is approximately $1,600/ha. We find that the total value of ecosystem services is large: a present value of $300 billion, even when we use conservative per-hectare values of $500/ha and $300/ha for primary and secondary forests, respectively (Taye et al, 2021; Costanza et al., 2014). The changes pose a cost to the agricultural sector, which forgoes $185 billion in agricultural output, primarily in the form of foregone beef production. Further research should investigate means to manage a rural transition in the region.
Taking All Actions results in further sequestration as increased productivity, wider use of silvopasture, and changing food production together halt the loss of primary forest and increase secondary forests. Notably, the economic value added from increased agricultural output from productivity gains is more than the economic value foregone from the decline in domestic demand for meat. These transformations in combination also have enormous social and environmental benefits. The public health and household savings of changing diets combined are half a trillion dollars, and ecosystem service benefits increase to $415 billion dollars. Industry, however, faces a technical cost of $265 billion. The result is a net profit of approximately $930 billion.

## Buildings

Under nominal assumptions, taking All Actions reduces building emissions (including electricity production for use in buildings) in 2050 from 500 MtCO2e to less than 5 MtCO2e. This essentially eliminates building emissions by increasing energy efficiency and fuel switching to electricity, while the electricity sector simultaneously switches to renewables. These transformations have a net benefit of approximately $150 billion—primarily from fuel and electricity cost savings over time.

As Figure 3.13 shows, under Traditional Development, Latin America and the Caribbean industrial emissions grow with population and GDP growth, from approximately 0.3 GtCO2e in 2020 to 0.5 GtCO2e 2050. This includes emissions from using fossil fuels in buildings, and the emissions associated with buildings' electricity consumption. It does not include embodied emissions associated with building materials, which are included in industry.

Transformations in Incremental Improvements that reduce emissions include using energy more efficiently within buildings and improving building shells to require less heating and cooling. These actions cut building emissions by over half (see Figure 3.13). Furthermore, as Figure 3.14 shows, incremental improvements in building energy efficiency have significant net benefits of $700 billion: the cost of achieving energy efficiency can be offset entirely by the direct electricity and fuel-cost savings from lower consumption, and savings in energy production from the energy sector. We do not put a monetary value on better comfort levels, better indoor air quality from shifting away from traditional biomass or biofuels, or mental health benefits from reducing indoor noise thanks to better-insulated buildings.
Taking All Actions results in further sequestration as increased productivity, wider use of silvopasture, and changing food production together halt the loss of primary forest and increase secondary forests. Notably, the economic value added from increased agricultural output from productivity gains is more than the economic value foregone from the decline in domestic demand for meat. These transformations in combination also have enormous social and environmental benefits. The public health and household savings of changing diets combined are half a trillion dollars, and ecosystem service benefits increase to $415 billion dollars. Industry, however, faces a technical cost of $265 billion. The result is a net profit of approximately $930 billion.

## Buildings

Under nominal assumptions, taking All Actions reduces building emissions (including electricity production for use in buildings) in 2050 from 500 MtCO2e to less than 5 MtCO2e. This essentially eliminates building emissions by increasing energy efficiency and fuel switching to electricity, while the electricity sector simultaneously switches to renewables. These transformations have a net benefit of approximately $150 billion—primarily from fuel and electricity cost savings over time.

As Figure 3.13 shows, under Traditional Development, Latin America and the Caribbean industrial emissions grow with population and GDP growth, from approximately 0.3 GtCO2e in 2020 to 0.5 GtCO2e 2050. This includes emissions from using fossil fuels in buildings, and the emissions associated with buildings' electricity consumption. It does not include embodied emissions associated with building materials, which are included in industry.

Transformations in Incremental Improvements that reduce emissions include using energy more efficiently within buildings and improving building shells to require less heating and cooling. These actions cut building emissions by over half (see Figure 3.13). Furthermore, as Figure 3.14 shows, incremental improvements in building energy efficiency have significant net benefits of $700 billion: the cost of achieving energy efficiency can be offset entirely by the direct electricity and fuel-cost savings from lower consumption, and savings in energy production from the energy sector. We do not put a monetary value on better comfort levels, better indoor air quality from shifting away from traditional biomass or biofuels, or mental health benefits from reducing indoor noise thanks to better-insulated buildings.
<figure><img src="image_31.png" /><figcaption>Figure 3.13 Emissions produced by buildings by transformation category.</figcaption></figure>

<figure><img src="image_32.png" /><figcaption>Figure 3.14 Costs and benefits of building transformations by transformation category.</figcaption></figure>
<figure><img src="image_31.png" /><figcaption>Figure 3.13 Emissions produced by buildings by transformation category.</figcaption></figure>

<figure><img src="image_32.png" /><figcaption>Figure 3.14 Costs and benefits of building transformations by transformation category.</figcaption></figure>
However, fully abating building emissions requires adopting some transformations contained in Supply-Side Solutions. These transformations include fuel switching buildings' heat energy from fossil fuels to electricity, primarily via heat pumps (and not electrical resistance heating), while simultaneously switching electricity production to renewables in the Energy Production subsector (Audoly et al., 2018). This essentially eliminates building emissions, but the costs of higher electricity consumption and increased costs in producing that electricity result in a net cost of approximately $480 billion.

All Actions couples energy-efficiency gains with fully switching to electricity, resulting in an almost complete abatement of emissions and net benefits of $150 billion. This net benefit occurs because the savings in electricity from efficiency interventions outpace the additional need for more electricity resulting from fuel switching and are combined with passthrough savings in the energy sector.

*Industry*

Under nominal assumptions, taking All Actions reduces industrial emissions (including from electricity production for use in industry) in 2050 from almost 400 MtCO2e to 40MtCO2e, a reduction of 90%, from actions including materials efficiency and substitution, energy efficiency and fuel switching, and capturing or destroying remaining emissions. These transformations offer a net benefit of $213 billion from fuel, electricity, and output savings and avoided pollution, which offset the costs of $200 billion for efficiency, CCS, and other technical changes.

As Figure 3.15 shows, the industrial sector was responsible for approximately 0.4 GtCO2e of emissions in Latin America and the Caribbean in 2020. This includes emissions from the consumption of energy; the processes used to make industrial products; and the use of products, such as hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) in aerosols and refrigerants, which can have hundreds to thousands of times the warming potential of CO2. It also includes emissions from the production of electricity used in industry. Under Traditional Development, these emissions rise with population and GDP growth to 680 MtCO2e by 2050.

Emissions produced in the sector can be reduced through several transformations. With transformations in Incremental Improvements, transformations include increasing industrial energy efficiency and substituting waste materials for virgin materials, particularly in the substitution of fly ash or other industrial byproducts for clinker in cement. Figure 3.16 shows that improvements in energy and product-use efficiency can yield net benefits of approximately $160 billion: the cost of achieving efficiency can be offset by the fuel cost savings, on top of which are the benefits of avoided air pollution. Nearly all these benefits will accrue to the industrial sector, which may pass on benefits to sectors that use industrial products.
However, fully abating building emissions requires adopting some transformations contained in Supply-Side Solutions. These transformations include fuel switching buildings' heat energy from fossil fuels to electricity, primarily via heat pumps (and not electrical resistance heating), while simultaneously switching electricity production to renewables in the Energy Production subsector (Audoly et al., 2018). This essentially eliminates building emissions, but the costs of higher electricity consumption and increased costs in producing that electricity result in a net cost of approximately $480 billion.

All Actions couples energy-efficiency gains with fully switching to electricity, resulting in an almost complete abatement of emissions and net benefits of $150 billion. This net benefit occurs because the savings in electricity from efficiency interventions outpace the additional need for more electricity resulting from fuel switching and are combined with passthrough savings in the energy sector.

*Industry*

Under nominal assumptions, taking All Actions reduces industrial emissions (including from electricity production for use in industry) in 2050 from almost 400 MtCO2e to 40MtCO2e, a reduction of 90%, from actions including materials efficiency and substitution, energy efficiency and fuel switching, and capturing or destroying remaining emissions. These transformations offer a net benefit of $213 billion from fuel, electricity, and output savings and avoided pollution, which offset the costs of $200 billion for efficiency, CCS, and other technical changes.

As Figure 3.15 shows, the industrial sector was responsible for approximately 0.4 GtCO2e of emissions in Latin America and the Caribbean in 2020. This includes emissions from the consumption of energy; the processes used to make industrial products; and the use of products, such as hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) in aerosols and refrigerants, which can have hundreds to thousands of times the warming potential of CO2. It also includes emissions from the production of electricity used in industry. Under Traditional Development, these emissions rise with population and GDP growth to 680 MtCO2e by 2050.

Emissions produced in the sector can be reduced through several transformations. With transformations in Incremental Improvements, transformations include increasing industrial energy efficiency and substituting waste materials for virgin materials, particularly in the substitution of fly ash or other industrial byproducts for clinker in cement. Figure 3.16 shows that improvements in energy and product-use efficiency can yield net benefits of approximately $160 billion: the cost of achieving efficiency can be offset by the fuel cost savings, on top of which are the benefits of avoided air pollution. Nearly all these benefits will accrue to the industrial sector, which may pass on benefits to sectors that use industrial products.
<figure><img src="image_33.png" /><figcaption>Figure 3.15 Emissions produced by industry by transformation category.</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>Figure 3.16 Costs and benefits of industry transformations by transformation category.</figcaption></figure>
<figure><img src="image_33.png" /><figcaption>Figure 3.15 Emissions produced by industry by transformation category.</figcaption></figure>

<figure><img src="image_34.png" /><figcaption>Figure 3.16 Costs and benefits of industry transformations by transformation category.</figcaption></figure>
Under Supply-Side Solutions, transformations induce more significant changes to production, including fuel switching, from fossil fuels to electricity and hydrogen; capturing and using CO2 emissions from key industrial processes and energy use (CCS); destroying or otherwise abating N2O and F-Gases; and using industrial products more efficiently. Changes in Supply-Side Solutions are made alongside a shift in energy production to electricity and hydrogen produced with renewables.

This package of transformations reduces industrial emissions in 2050 by almost 90%. These transformations come at substantial cost to the sector. The cost of producing electricity and green hydrogen to meet industrial demands results in a net cost of $155 billion, which is only partly offset by direct fuel savings of $40 billion. Adopting carbon capture and sequestration poses another significant cost of $60 billion. More efficient use of industrial materials, on the other hand, leads to $90 billion in avoided production costs and $75 billion in avoided air pollution.

The All Actions strategy also reduces emissions to 40 MtCO2e, a reduction of 90% compared to Traditional Development. It reduces the technical costs of transforming industry by combining fuel switching and other high-cost changes with cost-effective energy-efficiency transformations that reduce the extent to which those more expensive transformations must be applied. This full industry transformation achieves decarbonization goals at a lower cost to the economy. Most of these transformations involve changes in industrial production, and their technical costs and benefits will be experienced within the industrial sector. One key exception is industrial materials' efficient use. This largely will be driven by how efficiently industrial products such as cement and steel are used in other sectors—mainly transport and buildings—and the direct costs and benefits of increasing material efficiency would accrue to those sectors.

## Transport

Under nominal assumptions, taking All Actions reduces emissions from transport from 1.3 GtCO2e to 0.2 GtCO2e by increasing energy efficiency, expanding the use of electricity and hydrogen in all surface modes, and expanding the use of transit for passenger transport. These transformations yield a net benefit of more than $1.2 trillion—the largest sector benefits—by combining fuel cost savings (net hydrogen costs), transport system cost savings, and broader benefits of reduced air pollution, congestion, and crashes that eclipse the investment costs of $95 billion in energy efficiency and fuel switching.
Under Supply-Side Solutions, transformations induce more significant changes to production, including fuel switching, from fossil fuels to electricity and hydrogen; capturing and using CO2 emissions from key industrial processes and energy use (CCS); destroying or otherwise abating N2O and F-Gases; and using industrial products more efficiently. Changes in Supply-Side Solutions are made alongside a shift in energy production to electricity and hydrogen produced with renewables.

This package of transformations reduces industrial emissions in 2050 by almost 90%. These transformations come at substantial cost to the sector. The cost of producing electricity and green hydrogen to meet industrial demands results in a net cost of $155 billion, which is only partly offset by direct fuel savings of $40 billion. Adopting carbon capture and sequestration poses another significant cost of $60 billion. More efficient use of industrial materials, on the other hand, leads to $90 billion in avoided production costs and $75 billion in avoided air pollution.

The All Actions strategy also reduces emissions to 40 MtCO2e, a reduction of 90% compared to Traditional Development. It reduces the technical costs of transforming industry by combining fuel switching and other high-cost changes with cost-effective energy-efficiency transformations that reduce the extent to which those more expensive transformations must be applied. This full industry transformation achieves decarbonization goals at a lower cost to the economy. Most of these transformations involve changes in industrial production, and their technical costs and benefits will be experienced within the industrial sector. One key exception is industrial materials' efficient use. This largely will be driven by how efficiently industrial products such as cement and steel are used in other sectors—mainly transport and buildings—and the direct costs and benefits of increasing material efficiency would accrue to those sectors.

## Transport

Under nominal assumptions, taking All Actions reduces emissions from transport from 1.3 GtCO2e to 0.2 GtCO2e by increasing energy efficiency, expanding the use of electricity and hydrogen in all surface modes, and expanding the use of transit for passenger transport. These transformations yield a net benefit of more than $1.2 trillion—the largest sector benefits—by combining fuel cost savings (net hydrogen costs), transport system cost savings, and broader benefits of reduced air pollution, congestion, and crashes that eclipse the investment costs of $95 billion in energy efficiency and fuel switching.
Transport includes passenger and freight movement by various modes. These include air, rail, light-, medium-, and heavy-dusty vehicles, maritime, motorcycles, and walking and biking. Figure 3.17 shows transport emissions by mode (walking and biking have no emissions and are excluded, and electricity emissions are included separately as they are passed through from the energy production sector). Under Traditional Development, emissions double from 0.64 GtCO2e in 2020 to 1.3 GtCO2e by 2050, driven by GDP and population growth and a mode shift toward more travel by personal vehicle associated with increased wealth (Dargay and Gately, 2007).

Under Incremental Improvements, an increase in energy efficiency reduces emissions by 25% to 1 GtCO2e, with net benefits of $270 billion (Figure 3.18) from fuel savings and associated avoided air pollution benefits. However, these reductions fall far short of the abatement required to reach net-zero emissions.

<figure><img src="image_35.png" /><figcaption>**Figure 3.17 Emissions by transport mode by transformation category.**</figcaption></figure>
Transport includes passenger and freight movement by various modes. These include air, rail, light-, medium-, and heavy-dusty vehicles, maritime, motorcycles, and walking and biking. Figure 3.17 shows transport emissions by mode (walking and biking have no emissions and are excluded, and electricity emissions are included separately as they are passed through from the energy production sector). Under Traditional Development, emissions double from 0.64 GtCO2e in 2020 to 1.3 GtCO2e by 2050, driven by GDP and population growth and a mode shift toward more travel by personal vehicle associated with increased wealth (Dargay and Gately, 2007).

Under Incremental Improvements, an increase in energy efficiency reduces emissions by 25% to 1 GtCO2e, with net benefits of $270 billion (Figure 3.18) from fuel savings and associated avoided air pollution benefits. However, these reductions fall far short of the abatement required to reach net-zero emissions.

<figure><img src="image_35.png" /><figcaption>Figure 3.17 Emissions by transport mode by transformation category.</figcaption></figure>
<figure><img src="image_36.png" /><figcaption>Figure 3.18 Costs and benefits of transforming transport by transformation category.</figcaption></figure>

Under Supply-Side Solutions, transport is transformed through fuel switching away from diesel and gasoline to electricity and hydrogen across all freight modes and public passenger modes, as Figure 3.17 shows. This reduces emissions by 40%. These transformations cost the sector $100 billion in investment costs, but the resulting fuel cost savings, avoided air pollution, and system cost savings lead to a net benefit of $480 billion. (To elaborate, we define system costs as the public and private cost of transporting people and goods by different modes, including infrastructure requirements but excluding fuel to avoid double counting. Based on the literature and data described in the technical appendices, air and private auto tend to be the most expensive per passenger or freight kilometer, while transit and rail are much less expensive, so mode switching offers systemwide savings. This, of course, depends upon what kinds of transit are provided and how. We explore these assumptions and others in our uncertainty analysis.)
<figure><img src="image_36.png" /><figcaption>Figure 3.18 Costs and benefits of transforming transport by transformation category.</figcaption></figure>

Under Supply-Side Solutions, transport is transformed through fuel switching away from diesel and gasoline to electricity and hydrogen across all freight modes and public passenger modes, as Figure 3.17 shows. This reduces emissions by 40%. These transformations cost the sector $100 billion in investment costs, but the resulting fuel cost savings, avoided air pollution, and system cost savings lead to a net benefit of $480 billion. (To elaborate, we define system costs as the public and private cost of transporting people and goods by different modes, including infrastructure requirements but excluding fuel to avoid double counting. Based on the literature and data described in the technical appendices, air and private auto tend to be the most expensive per passenger or freight kilometer, while transit and rail are much less expensive, so mode switching offers systemwide savings. This, of course, depends upon what kinds of transit are provided and how. We explore these assumptions and others in our uncertainty analysis.)
Transformations in Changing Consumption focus on changes in transport activity and mode, and involve increasing occupancy for private vehicles; mode shifting local transport to transit, walking, and biking; mode shifting regional passenger travel to bus and rail; and electrifying light-duty vehicles. This strategy decreases emissions by 35% to 0.85 GtCO2e and incurs costs of $25 billion, mostly stemming from light-duty vehicles' electrification. However, the broader benefits, particularly from adopting transit, result in a net benefit of $730 billion from both technical savings such as avoided fuel costs, vehicle maintenance costs, and system costs, and broader benefits of avoided air pollution, crashes, and time wasted in congestion and valued based on productivity. The healthcare sector and employers have much to gain from transport transformations that increase social productivity and health.

Taking All Actions results in a reduction in transport emissions of 85% to 0.2 GtCO2e. The significant and potentially hard to abate residual emissions in this sector may require offsets elsewhere. These changes together yield the largest benefits of any sector of more than $1.2 trillion dollars, from a combination of fuel savings, transport system costs, and avoided air pollution, congestion, and crash costs that dramatically outweigh the investment costs of fuel switching, energy efficiency, and other technical investments. However, these transformations will impose quite different costs on various actors. In particular, a move to transit may pose significant costs to public transport authorities, even as it reduces consumer costs of private vehicle ownership and operation costs.

## Waste

Under nominal assumptions, taking All Actions reduces emissions from waste from 0.4 GtCO2e to 0.1 GtCO2e by achieving universal safe sanitation, wastewater treatment, and solid waste management; reducing consumer food waste; and by capturing biogas from waste facilities. These transformations yield a net benefit of $180 billion. Universal waste management and water treatment are expensive, but not only are such actions essential for basic development, they yield significant net benefits in terms of health and avoided pollution.

The waste sector covers liquid and solid waste management, including sanitation and sewage, wastewater treatment, solid waste collection, and solid waste management through landfilling, recycling, composting, and other waste management streams. As Figure 3.19 shows, under Traditional Development, emissions from this sector grow from 0.23 GtCO2e in 2020 to 0.41 GtCO2e with population and economic growth.

Incremental Improvements achieves universal safe sanitation by 2030, consistent with the UN's Development Program SDGs (WHO, 2021), as well as treating all wastewater and ending unmanaged solid waste streams. It also expands recycling. These changes reduce emissions by 20% (Figure 3.19) but are expensive (Figure 3.20), costing $385 billion in civic infrastructure and operations. The health benefits associated with safe sanitation (Hutton & Varughese, 2016) and avoided pollution associated with open dumping (Wilson et al., 2015) outweigh the costs. The result is a $160 billion net benefit.
Transformations in Changing Consumption focus on changes in transport activity and mode, and involve increasing occupancy for private vehicles; mode shifting local transport to transit, walking, and biking; mode shifting regional passenger travel to bus and rail; and electrifying light-duty vehicles. This strategy decreases emissions by 35% to 0.85 GtCO2e and incurs costs of $25 billion, mostly stemming from light-duty vehicles' electrification. However, the broader benefits, particularly from adopting transit, result in a net benefit of $730 billion from both technical savings such as avoided fuel costs, vehicle maintenance costs, and system costs, and broader benefits of avoided air pollution, crashes, and time wasted in congestion and valued based on productivity. The healthcare sector and employers have much to gain from transport transformations that increase social productivity and health.

Taking All Actions results in a reduction in transport emissions of 85% to 0.2 GtCO2e. The significant and potentially hard to abate residual emissions in this sector may require offsets elsewhere. These changes together yield the largest benefits of any sector of more than $1.2 trillion dollars, from a combination of fuel savings, transport system costs, and avoided air pollution, congestion, and crash costs that dramatically outweigh the investment costs of fuel switching, energy efficiency, and other technical investments. However, these transformations will impose quite different costs on various actors. In particular, a move to transit may pose significant costs to public transport authorities, even as it reduces consumer costs of private vehicle ownership and operation costs.

## Waste

Under nominal assumptions, taking All Actions reduces emissions from waste from 0.4 GtCO2e to 0.1 GtCO2e by achieving universal safe sanitation, wastewater treatment, and solid waste management; reducing consumer food waste; and by capturing biogas from waste facilities. These transformations yield a net benefit of $180 billion. Universal waste management and water treatment are expensive, but not only are such actions essential for basic development, they yield significant net benefits in terms of health and avoided pollution.

The waste sector covers liquid and solid waste management, including sanitation and sewage, wastewater treatment, solid waste collection, and solid waste management through landfilling, recycling, composting, and other waste management streams. As Figure 3.19 shows, under Traditional Development, emissions from this sector grow from 0.23 GtCO2e in 2020 to 0.41 GtCO2e with population and economic growth.

Incremental Improvements achieves universal safe sanitation by 2030, consistent with the UN's Development Program SDGs (WHO, 2021), as well as treating all wastewater and ending unmanaged solid waste streams. It also expands recycling. These changes reduce emissions by 20% (Figure 3.19) but are expensive (Figure 3.20), costing $385 billion in civic infrastructure and operations. The health benefits associated with safe sanitation (Hutton & Varughese, 2016) and avoided pollution associated with open dumping (Wilson et al., 2015) outweigh the costs. The result is a $160 billion net benefit.
<figure><img src="image_37.png" /><figcaption>Figure 3.19 Emissions produced by waste by transformation category.</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>Figure 3.20 Costs and benefits of transforming the waste sector by transformation category.</figcaption></figure>
<figure><img src="image_37.png" /><figcaption>Figure 3.19 Emissions produced by waste by transformation category.</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>Figure 3.20 Costs and benefits of transforming the waste sector by transformation category.</figcaption></figure>
Supply-Side Solutions involve increased energy recovery from pre-existing wastewater treatment and waste management facilities, reducing sector emissions to 0.22 GtCO2e by 2050. This strategy does not expand sanitation, waste management, or water treatment systems, as these are included in Incremental Improvements. Waste-to-energy recovery on its own poses a net cost of $90 billion, as waste recovery's cost may not be outweighed by the recovery energy's economic value (IEA, 2020).

Changing Consumption involves changes to consumer behavior that reduce food waste and divert organic food waste to composters and digesters. On their own, these transformations reduce emissions by about 10% to 0.37 GtCO2e. While the emissions effects are modest, the benefits to consumers are significant, saving $150 billion in avoided food waste costs. Benefits also include avoided waste management costs.

All Actions combines these transformations to reduce emissions by 75% to 0.1 GtCO2e. In combination, these actions have net benefits of $180 billion dollars—with $600 billion in technical costs outweighed by $780 billion in health and pollution savings and avoided fuel and food production costs. Most importantly, many of these transformations are an essential part of development.
Supply-Side Solutions involve increased energy recovery from pre-existing wastewater treatment and waste management facilities, reducing sector emissions to 0.22 GtCO2e by 2050. This strategy does not expand sanitation, waste management, or water treatment systems, as these are included in Incremental Improvements. Waste-to-energy recovery on its own poses a net cost of $90 billion, as waste recovery's cost may not be outweighed by the recovery energy's economic value (IEA, 2020).

Changing Consumption involves changes to consumer behavior that reduce food waste and divert organic food waste to composters and digesters. On their own, these transformations reduce emissions by about 10% to 0.37 GtCO2e. While the emissions effects are modest, the benefits to consumers are significant, saving $150 billion in avoided food waste costs. Benefits also include avoided waste management costs.

All Actions combines these transformations to reduce emissions by 75% to 0.1 GtCO2e. In combination, these actions have net benefits of $180 billion dollars—with $600 billion in technical costs outweighed by $780 billion in health and pollution savings and avoided fuel and food production costs. Most importantly, many of these transformations are an essential part of development.
<figure><img src="image_39.png" /></figure>

# A Robust Path to Net Zero in Latin America and the Caribbean
<figure><img src="image_39.png" /></figure>

# A Robust Path to Net Zero in Latin America and the Caribbean
Countries' decarbonization strategies, including their NDCs and LTSs, will involve transformations across the economy. Whether they reach net-zero emissions, and at what costs and benefits, will be shaped by many deeply uncertain factors related to underlying social and economic drivers, transformations' effects on emissions, and the costs and benefits of different actions.

In this chapter, we hope to help countries in Latin America and the Caribbean chart a robust path to decarbonization that reaches net-zero emissions and provides net economic benefits, despite these uncertainties. To that end, we first identify the region's key ingredients for decarbonization strategies, asking what transformations are critical to reach net zero?

We next ask questions to formulate a strategy that robustly meets net-zero targets in the face of deep uncertainty.

* Do strategies organized around critical transformations reach net-zero emissions under uncertainty?

* What exogenous conditions most threaten net-zero goals?

* What is a robust strategy for reaching net-zero emissions in the region?

With such a strategy, we can assess the costs and benefits of decarbonizing Latin America and the Caribbean, by understanding the following:

* What are the range of costs and benefits of reaching net zero with this strategy?

* What conditions might cause decarbonization to pose net costs?

* To whom do costs and benefits accrue?

## Key Ingredients of Decarbonization Strategies for the Region

As Chapter 2 describes, we developed 1,000 decarbonization strategies that implement all transformations simultaneously but to different degrees, ranging from no (0%) to maximum (100%) implementation. (Maximum implementation differs for each transformation and is defined in the technical appendices). Of these simulations, we omit 17 that failed to complete successfully. Figure 4.1 shows the emissions of the remaining 983 as blue trajectories, alongside the five trajectories discussed in Chapter 3.

Results show that doing some of everything can reduce emissions at least as well as doing a few key transformations in Incremental Improvements or Supply-Side Solutions to maximum effect. However, fewer than 1% of these strategies reach net zero by 2050. Clearly, some transformations are more important than others.
Countries' decarbonization strategies, including their NDCs and LTSs, will involve transformations across the economy. Whether they reach net-zero emissions, and at what costs and benefits, will be shaped by many deeply uncertain factors related to underlying social and economic drivers, transformations' effects on emissions, and the costs and benefits of different actions.

In this chapter, we hope to help countries in Latin America and the Caribbean chart a robust path to decarbonization that reaches net-zero emissions and provides net economic benefits, despite these uncertainties. To that end, we first identify the region's key ingredients for decarbonization strategies, asking what transformations are critical to reach net zero?

We next ask questions to formulate a strategy that robustly meets net-zero targets in the face of deep uncertainty.

* Do strategies organized around critical transformations reach net-zero emissions under uncertainty?

* What exogenous conditions most threaten net-zero goals?

* What is a robust strategy for reaching net-zero emissions in the region?

With such a strategy, we can assess the costs and benefits of decarbonizing Latin America and the Caribbean, by understanding the following:

* What are the range of costs and benefits of reaching net zero with this strategy?

* What conditions might cause decarbonization to pose net costs?

* To whom do costs and benefits accrue?

## Key Ingredients of Decarbonization Strategies for the Region

As Chapter 2 describes, we developed 1,000 decarbonization strategies that implement all transformations simultaneously but to different degrees, ranging from no (0%) to maximum (100%) implementation. (Maximum implementation differs for each transformation and is defined in the technical appendices). Of these simulations, we omit 17 that failed to complete successfully. Figure 4.1 shows the emissions of the remaining 983 as blue trajectories, alongside the five trajectories discussed in Chapter 3.

Results show that doing some of everything can reduce emissions at least as well as doing a few key transformations in Incremental Improvements or Supply-Side Solutions to maximum effect. However, fewer than 1% of these strategies reach net zero by 2050. Clearly, some transformations are more important than others.
<figure><img src="image_40.png" /><figcaption>**Figure 4.1 Emissions trajectories of 1,000 decarbonization strategies.**</figcaption></figure>

Regression and clustering analyses reveal that, of the 50+ individual transformations, four are the primary drivers of decarbonization: ending deforestation, shifting food production and consumption patterns, producing electricity and hydrogen with renewables, and electrifying transport. Table 4.1 details these transformations and their levels of implementation, with further elaborations in the appendices.
<figure><img src="image_40.png" /><figcaption>Figure 4.1 Emissions trajectories of 1,000 decarbonization strategies.</figcaption></figure>

Regression and clustering analyses reveal that, of the 50+ individual transformations, four are the primary drivers of decarbonization: ending deforestation, shifting food production and consumption patterns, producing electricity and hydrogen with renewables, and electrifying transport. Table 4.1 details these transformations and their levels of implementation, with further elaborations in the appendices.
<table><caption>Table 4.1 Critical transformations and explanation of implementation levels</caption><thead><tr><td>Critical Transformation</td><td>Description</td><td>Explanation of implementation levels</td></tr></thead><tbody><tr><td>Ending deforestation</td><td>The average annual rate of deforestation of the region is approximately 2.6 million hectares (ha) per year (ECLAC, 2021). This transformation sets a limit on the number of hectares that can be deforested each year. This limit is phased in over five years between 2025 and 2030.</td><td>At maximum implementation, deforestation after 2030 is limited to less than 10,000 ha/year, effectively ending deforestation. A 70% level of implementation, for example, sets the cap at 780,000 ha/year (30% of 2.6 million).</td></tr><tr><td>Shifting food production and consumption patterns</td><td>This transformation reduces beef production in the region and adjusts regional diets accordingly, increasing the intake of fruits, vegetables, legumes, and other more healthful options. These shifts make room for afforestation and reduce emissions from enteric fermentation and manure.</td><td>At maximum implementation, production of meat is reduced in 2050 by reducing 50% of domestic demand for meat, compared to consumption under Traditional Development, with corresponding increases in intake of other fruits, vegetables, and legumes. A 70% implementation, for example, corresponds to reducing production by 35% of domestic demand by 2050.</td></tr><tr><td>Producing renewable energy</td><td>This transformation increases the fraction of electricity (and hydrogen) produced with solar, wind, and geothermal energy, using storage as necessary. Given climate stressors and socio-political barriers, this transformation does not include increases in hydropower or nuclear power. CCS for power plants is not included, given the much higher cost compared to renewables and technological immaturity.</td><td>At maximum implementation, by 2050 95% of electricity and 100% of hydrogen is produced with renewables as coal, gas, and other fossil fuel plants are phased out. At 70% implementation, for example, 66% of power and 70% of hydrogen is produced with renewables.</td></tr><tr><td>Fuel shifting in transport</td><td>This transformation shifts all transport toward electricity and hydrogen.</td><td>At maximum implementation, by 2050, 70% of light-duty vehicle transport is electric; 70% of heavy-duty and maritime transport is electric; the remaining 30% is powered by hydrogen; and 25% of rail is electrified. At 70% implementation, for example, those figures shift from 70% to 49%; 30% to 21%; and from 25% to 17.5%.</td></tr></tbody></table>
<table><caption>Table 4.1 Critical transformations and explanation of implementation levels</caption><thead><tr><td>Critical Transformation</td><td>Description</td><td>Explanation of implementation levels</td></tr></thead><tbody><tr><td>Ending deforestation</td><td>The average annual rate of deforestation of the region is approximately 2.6 million hectares (ha) per year (ECLAC, 2021). This transformation sets a limit on the number of hectares that can be deforested each year. This limit is phased in over five years between 2025 and 2030.</td><td>At maximum implementation, deforestation after 2030 is limited to less than 10,000 ha/year, effectively ending deforestation. A 70% level of implementation, for example, sets the cap at 780,000 ha/year (30% of 2.6 million).</td></tr><tr><td>Shifting food production and consumption patterns</td><td>This transformation reduces beef production in the region and adjusts regional diets accordingly, increasing the intake of fruits, vegetables, legumes, and other more healthful options. These shifts make room for afforestation and reduce emissions from enteric fermentation and manure.</td><td>At maximum implementation, production of meat is reduced in 2050 by reducing 50% of domestic demand for meat, compared to consumption under Traditional Development, with corresponding increases in intake of other fruits, vegetables, and legumes. A 70% implementation, for example, corresponds to reducing production by 35% of domestic demand by 2050.</td></tr><tr><td>Producing renewable energy</td><td>This transformation increases the fraction of electricity (and hydrogen) produced with solar, wind, and geothermal energy, using storage as necessary. Given climate stressors and socio-political barriers, this transformation does not include increases in hydropower or nuclear power. CCS for power plants is not included, given the much higher cost compared to renewables and technological immaturity.</td><td>At maximum implementation, by 2050 95% of electricity and 100% of hydrogen is produced with renewables as coal, gas, and other fossil fuel plants are phased out. At 70% implementation, for example, 66% of power and 70% of hydrogen is produced with renewables.</td></tr><tr><td>Fuel shifting in transport</td><td>This transformation shifts all transport toward electricity and hydrogen.</td><td>At maximum implementation, by 2050, 70% of light-duty vehicle transport is electric; 70% of heavy-duty and maritime transport is electric; the remaining 30% is powered by hydrogen; and 25% of rail is electrified. At 70% implementation, for example, those figures shift from 70% to 49%; 30% to 21%; and from 25% to 17.5%.</td></tr></tbody></table>
Figures 4.2 and 4.3 illustrate this finding. Figure 4.2 shows the net emissions in 2050 (vertical axis) against a simple average level of implementation across these four critical transformations (horizontal axis). Each dot represents one of the 1,000 strategies simulated. The average level of implementation of these four transformations explains 75% of a strategy's emissions trajectory; the dozens of other transformations account for only about 25% of the emissions outcome. Furthermore, the few strategies that reach net zero all implement critical transformations to at least 70% of their maximum level.

Figure 4.3 shows the importance of these critical transformations by classifying strategies that have “high” or “low” implementations of each of the four critical transformations, where “high” corresponds to an implementation of at least 50%. It shows that 90% of strategies that have high implementation of all four critical transformations reach net zero (lower right box). The percentage reaching net zero drops precipitously to 40% if even one of the four critical transformations is implemented at a low level. (Here, 40% is the average number of strategies reaching net zero across the 4 boxes with only three critical transformations implemented to a high degree, shown on the bottom and right edges with individual percentages of 52%, 56%, 17%, and 38%).

To be clear, high implementation of these four transformations is necessary for reaching net zero, but insufficient on its own. Transformations must occur throughout the economy in every sector, from using materials and energy efficiently to adopting CCS in certain industries to shifting to public transit and non-motorized transport. However, the extent to which other transformations are implemented to reach net zero can vary and be tailored—more efficient use of steel and cement, for example, may allow for lower CCS rates in steel and cement production. These tradeoffs can be governed by considerations of cost, financing, equity, infrastructure, technological feasibility, and other factors.

<figure><img src="image_41.png" /><figcaption>Figure 4.2. Emissions in 2050 vs. implementation of four critical transformations.</figcaption></figure>
Figures 4.2 and 4.3 illustrate this finding. Figure 4.2 shows the net emissions in 2050 (vertical axis) against a simple average level of implementation across these four critical transformations (horizontal axis). Each dot represents one of the 1,000 strategies simulated. The average level of implementation of these four transformations explains 75% of a strategy's emissions trajectory; the dozens of other transformations account for only about 25% of the emissions outcome. Furthermore, the few strategies that reach net zero all implement critical transformations to at least 70% of their maximum level.

Figure 4.3 shows the importance of these critical transformations by classifying strategies that have “high” or “low” implementations of each of the four critical transformations, where “high” corresponds to an implementation of at least 50%. It shows that 90% of strategies that have high implementation of all four critical transformations reach net zero (lower right box). The percentage reaching net zero drops precipitously to 40% if even one of the four critical transformations is implemented at a low level. (Here, 40% is the average number of strategies reaching net zero across the 4 boxes with only three critical transformations implemented to a high degree, shown on the bottom and right edges with individual percentages of 52%, 56%, 17%, and 38%).

To be clear, high implementation of these four transformations is necessary for reaching net zero, but insufficient on its own. Transformations must occur throughout the economy in every sector, from using materials and energy efficiently to adopting CCS in certain industries to shifting to public transit and non-motorized transport. However, the extent to which other transformations are implemented to reach net zero can vary and be tailored—more efficient use of steel and cement, for example, may allow for lower CCS rates in steel and cement production. These tradeoffs can be governed by considerations of cost, financing, equity, infrastructure, technological feasibility, and other factors.

<figure><img src="image_41.png" /><figcaption>Figure 4.2. Emissions in 2050 vs. implementation of four critical transformations.</figcaption></figure>
<figure><img src="image_42.png" /><figcaption>Figure 4.3 Percent of strategies reaching net zero via intensity of critical transformations.</figcaption></figure>

## Robustly Meeting Net-Zero Targets Amid Deep Uncertainty

Having identified four critical transformations, our next steps help formulate a strategy that meets net-zero targets in the face of deep uncertainty. We examine the how different levels of implementation of critical transformations and other transformations reach or fail to reach net zero amid uncertainty, what exogenous uncertainties best explain a failure to reach net zero, and what a robust strategy might look like for the region.
<figure><img src="image_42.png" /><figcaption>Figure 4.3 Percent of strategies reaching net zero via intensity of critical transformations.</figcaption></figure>

## Robustly Meeting Net-Zero Targets Amid Deep Uncertainty

Having identified four critical transformations, our next steps help formulate a strategy that meets net-zero targets in the face of deep uncertainty. We examine the how different levels of implementation of critical transformations and other transformations reach or fail to reach net zero amid uncertainty, what exogenous uncertainties best explain a failure to reach net zero, and what a robust strategy might look like for the region.
*Do critical transformations robustly reach net-zero emissions under uncertainty?*

We use the label “Critical Actions” to describe a strategy that has high implementation of the four critical transformations previously identified, and some implementation of all other transformations. Here, we examine how Critical Actions perform in terms of emissions, costs, and benefits, when we introduce the many deep uncertainties that challenge decarbonization planning. As described in Chapter 2, we generate 1,000 variants of Critical Actions, where the four critical transformations are implemented from 50% to 100%, and all other transformations are implemented between 25% and 100%. We evaluate Critical Actions against Traditional Development under 1,000 different futures representing uncertainty around factors that affect emissions, costs, and benefits (Table 2.4). Of these, we omit 16 simulations that failed to complete successfully.

Figure 4.4 shows the emissions trajectories of the remaining 984 Critical Action variants and Traditional Development in different future conditions. The results show that the range of emissions under Traditional Development is quite large, ranging from a future in which emissions are stabilized versus increasing manyfold, depending on assumptions about future growth, elasticities of demand, and other emissions drivers. However, Critical Actions consistently drive emissions close to net zero, with emissions in 2050 ranging from 2 to -2 GtCO2e, depending upon the future.

We classify Critical Action variants into three groups distinguished by how closely they reach net zero emissions in 2050. Forty-five percent of Critical Actions variants reach net zero at approximately 2050 (in blue; emissions in 2050 range from 0.5 and— 0.5 GtCO2e). Another 13% reach net zero sooner than 2050. These “overshoots” have emissions in 2050 of less than -0.5GtCO2e. Finally, 42% of Critical Action variants miss net zero, with 2050 emissions higher than 0.5 GtCO2e.
*Do critical transformations robustly reach net-zero emissions under uncertainty?*

We use the label “Critical Actions” to describe a strategy that has high implementation of the four critical transformations previously identified, and some implementation of all other transformations. Here, we examine how Critical Actions perform in terms of emissions, costs, and benefits, when we introduce the many deep uncertainties that challenge decarbonization planning. As described in Chapter 2, we generate 1,000 variants of Critical Actions, where the four critical transformations are implemented from 50% to 100%, and all other transformations are implemented between 25% and 100%. We evaluate Critical Actions against Traditional Development under 1,000 different futures representing uncertainty around factors that affect emissions, costs, and benefits (Table 2.4). Of these, we omit 16 simulations that failed to complete successfully.

Figure 4.4 shows the emissions trajectories of the remaining 984 Critical Action variants and Traditional Development in different future conditions. The results show that the range of emissions under Traditional Development is quite large, ranging from a future in which emissions are stabilized versus increasing manyfold, depending on assumptions about future growth, elasticities of demand, and other emissions drivers. However, Critical Actions consistently drive emissions close to net zero, with emissions in 2050 ranging from 2 to -2 GtCO2e, depending upon the future.

We classify Critical Action variants into three groups distinguished by how closely they reach net zero emissions in 2050. Forty-five percent of Critical Actions variants reach net zero at approximately 2050 (in blue; emissions in 2050 range from 0.5 and— 0.5 GtCO2e). Another 13% reach net zero sooner than 2050. These “overshoots” have emissions in 2050 of less than -0.5GtCO2e. Finally, 42% of Critical Action variants miss net zero, with 2050 emissions higher than 0.5 GtCO2e.
<figure><img src="image_43.png" /><figcaption>Figure 4.4 Emissions trajectories of 1,000 Critical Actions variants amid uncertainty.</figcaption></figure>

*What combination of conditions most threaten net-zero goals?*

We use RDM's scenario discovery techniques to describe specific combinations of transformations and exogenous conditions that lead Critical Actions trajectories to reach or miss net zero. Figure 4.5 shows the Critical Actions variants. Consistent with Figure 4.4., by 2050 the trajectories that reach net zero are blue; the ones that miss net zero are orange, and the ones that overshoot net zero are gray.

We find two opposing forces at work. The first is the extent to which critical actions of halting deforestation and shifting food production patterns are taken by 2050. Figure 4.4 shows this as an average implementation level of these transformations on the vertical axis. Implementing these transformations at higher levels means that more forest land remains available to sequester and offset residual emissions in other sectors, making it more likely that net zero is achieved.
<figure><img src="image_43.png" /><figcaption>Figure 4.4 Emissions trajectories of 1,000 Critical Actions variants amid uncertainty.</figcaption></figure>

*What combination of conditions most threaten net-zero goals?*

We use RDM's scenario discovery techniques to describe specific combinations of transformations and exogenous conditions that lead Critical Actions trajectories to reach or miss net zero. Figure 4.5 shows the Critical Actions variants. Consistent with Figure 4.4., by 2050 the trajectories that reach net zero are blue; the ones that miss net zero are orange, and the ones that overshoot net zero are gray.

We find two opposing forces at work. The first is the extent to which critical actions of halting deforestation and shifting food production patterns are taken by 2050. Figure 4.4 shows this as an average implementation level of these transformations on the vertical axis. Implementing these transformations at higher levels means that more forest land remains available to sequester and offset residual emissions in other sectors, making it more likely that net zero is achieved.
The second is the extent to which the exogenous uncertainties of livestock productivity and forest sequestration rates shape forests' abilities to expand and offset emissions. Figure 4.5 shows this on the horizontal axis as an average change in rates of livestock productivity (head per hectare) and rates of sequestration (CO2 per hectare) relative to nominal assumptions. As productivity declines, a larger forest area is required to meet any demand for beef, adding to deforestation. As sequestration rates decline, each hectare of forest is less effective at serving as an emissions sink.

Whether net zero is achieved depends on these forces' relative balance. As we move closer to Figure 4.5's top-right corner, lower deforestation rates, lower beef consumption, and higher productivity of pastures and forests lead to higher likelihoods of reaching net zero by or before 2050.

<figure><img src="image_44.png" /><figcaption>Figure 4.5 Conditions driving emissions of Critical Action variants under uncertainty.</figcaption></figure>
The second is the extent to which the exogenous uncertainties of livestock productivity and forest sequestration rates shape forests’ abilities to expand and offset emissions. Figure 4.5 shows this on the horizontal axis as an average change in rates of livestock productivity (head per hectare) and rates of sequestration (CO2 per hectare) relative to nominal assumptions. As productivity declines, a larger forest area is required to meet any demand for beef, adding to deforestation. As sequestration rates decline, each hectare of forest is less effective at serving as an emissions sink.

Whether net zero is achieved depends on these forces' relative balance. As we move closer to Figure 4.5's top-right corner, lower deforestation rates, lower beef consumption, and higher productivity of pastures and forests lead to higher likelihoods of reaching net zero by or before 2050.

<figure><img src="image_44.png" /><figcaption>Figure 4.5 Conditions driving emissions of Critical Action variants under uncertainty.</figcaption></figure>
*What strategy robustly reaches net-zero goals?*

RDM's scenario-discovery techniques can help summarize information in these results and identify areas of vulnerability and robustness. Figure 4.6 replicates Figure 4.5 and highlights two regions of interest. On the left is a vulnerable region where 90% of trajectories fail to reach net zero. In this region, the stressors of reduced productivity and sequestration rates are not compensated for with higher levels of implementation to end deforestation and shift production and consumption of meat.

On the right in Figure 4.6 is a region of robustness. It shows that sufficiently implementing transformations of ending deforestation and shifting production and consumption of meat provides robustness against these stressors. There are 270 trajectories that have implementation of these two critical transformations at 80% or higher (the shaded area in the figure). In these trajectories, production and consumption of meat is reduced by 40% and deforestation is slowed by 2030 to 780,000 ha/year. Roughly 85% of these trajectories reach or overshoot net zero by 2050, regardless of the change in productivity and sequestration rates explored.

This analysis suggests that livestock productivity and forest sequestration rates may be difficult headwinds against which to navigate to net-zero emissions, but that strong efforts to halt deforestation and shift food production and consumption patterns to lower emitting foods, coupled with transitions to renewable energy and fuel shifts in transport, can provide a robust path to net zero.

<figure><img src="image_45.png" /><figcaption>**Figure 4.6** Vulnerable conditions (left) and robust levels of implementation (right) of Critical Actions.</figcaption></figure>
*What strategy robustly reaches net-zero goals?*

RDM's scenario-discovery techniques can help summarize information in these results and identify areas of vulnerability and robustness. Figure 4.6 replicates Figure 4.5 and highlights two regions of interest. On the left is a vulnerable region where 90% of trajectories fail to reach net zero. In this region, the stressors of reduced productivity and sequestration rates are not compensated for with higher levels of implementation to end deforestation and shift production and consumption of meat.

On the right in Figure 4.6 is a region of robustness. It shows that sufficiently implementing transformations of ending deforestation and shifting production and consumption of meat provides robustness against these stressors. There are 270 trajectories that have implementation of these two critical transformations at 80% or higher (the shaded area in the figure). In these trajectories, production and consumption of meat is reduced by 40% and deforestation is slowed by 2030 to 780,000 ha/year. Roughly 85% of these trajectories reach or overshoot net zero by 2050, regardless of the change in productivity and sequestration rates explored.

This analysis suggests that livestock productivity and forest sequestration rates may be difficult headwinds against which to navigate to net-zero emissions, but that strong efforts to halt deforestation and shift food production and consumption patterns to lower emitting foods, coupled with transitions to renewable energy and fuel shifts in transport, can provide a robust path to net zero.

<figure><img src="image_45.png" /><figcaption>**Figure 4.6** Vulnerable conditions (left) and robust levels of implementation (right) of Critical Actions.</figcaption></figure>
Costs and Benefits of Decarbonizing Latin America and the Caribbean

We next examine the macroeconomic implications of decarbonizing the region. We assess the range of costs and benefits that might result from implementing Critical Action strategies, the conditions that might result in net costs to the region, and to whom those costs and benefits accrue.

What are the range of costs and benefits of reaching net zero with this strategy?

Figure 4.7 shows the discounted net benefits (horizontal axis) against net emissions in 2050 (vertical axis) for each of the previous section's Critical Actions trajectories. Marks are shaded based on whether they reach, overshoot, or miss net zero by 2050. In addition, marks are represented by circles when net benefits are positive (to the right of the reference line at 0) and by squares when net benefits are negative (i.e., strategies pose a net cost).

<figure><img src="image_46.png" /><figcaption>Figure 4.7 Net benefits and net 2050 emissions of Critical Action variants under uncertainty.</figcaption></figure>
Costs and Benefits of Decarbonizing Latin America and the Caribbean

We next examine the macroeconomic implications of decarbonizing the region. We assess the range of costs and benefits that might result from implementing Critical Action strategies, the conditions that might result in net costs to the region, and to whom those costs and benefits accrue.

What are the range of costs and benefits of reaching net zero with this strategy?

Figure 4.7 shows the discounted net benefits (horizontal axis) against net emissions in 2050 (vertical axis) for each of the previous section's Critical Actions trajectories. Marks are shaded based on whether they reach, overshoot, or miss net zero by 2050. In addition, marks are represented by circles when net benefits are positive (to the right of the reference line at 0) and by squares when net benefits are negative (i.e., strategies pose a net cost).

<figure><img src="image_46.png" /><figcaption>Figure 4.7 Net benefits and net 2050 emissions of Critical Action variants under uncertainty.</figcaption></figure>
Figure 4.7 shows first that 96% of Critical Actions trajectories result in positive net benefits, and the median net benefit across all trajectories is $1 trillion with a maximum of $2.5 trillion. This level of benefits has no relationship to the emissions reductions achieved (a simple regression between emissions and benefits has an R-squared value of 10-5 and a p-value of 0.8). This suggests that Critical Actions are not only robustly beneficial compared to a future with Traditional Actions, but that overshooting net zero is not associated with lower net benefits.

*What conditions might cause decarbonization to pose net costs?*

There are only 38 trajectories of 984 in which Critical Actions variants pose net costs. Our analysis of these trajectories reveals no specific, summarizable set of drivers of high cost. Each one presents a unique combination of exogenous emissions drivers, transformation effects, and cost uncertainties. This is similar to the findings in Groves et al. (2020), which analyzed the costs and benefits of Costa Rica's decarbonization plan and found few net cost futures, and the conditions that led to them were difficult to summarize.

*To whom do costs and benefits accrue?*

Figure 4.8 describes the range of benefits across these results by category of costs and benefits used in Chapter 3. Several categories of benefits are positive across all futures: health safety and productivity; avoided pollution; ecosystem services; and fuel costs. This is consistent with the fact that Critical Actions strategies reduce fossil fuel dependency and increase forestation, with corresponding benefits in those categories. The benefits in terms of sector investment are, by definition, negative across all futures, as this category captures capital and other investments' costs.

The benefits in the other categories vary by future. The electricity sector can experience net costs if capital costs, particularly for transmission and system upgrades, are extremely high and not offset by maintenance and fuel-cost savings. In agriculture, the net impact of implementing the Critical Actions on output is typically positive, but can be negative in some futures, if livestock's foregone value is not outpaced by increased output in crops. The other sector savings or costs include avoiding industrial activity because of more efficient material use, maintenance savings from electrification, and the system costs of transport by mode. Whether these lead to net costs or net benefits depends on how far related transformations are implemented, and the exogenous values of costs and benefits per unit of implementation.
Figure 4.7 shows first that 96% of Critical Actions trajectories result in positive net benefits, and the median net benefit across all trajectories is $1 trillion with a maximum of $2.5 trillion. This level of benefits has no relationship to the emissions reductions achieved (a simple regression between emissions and benefits has an R-squared value of 10-5 and a p-value of 0.8). This suggests that Critical Actions are not only robustly beneficial compared to a future with Traditional Actions, but that overshooting net zero is not associated with lower net benefits.

*What conditions might cause decarbonization to pose net costs?*

There are only 38 trajectories of 984 in which Critical Actions variants pose net costs. Our analysis of these trajectories reveals no specific, summarizable set of drivers of high cost. Each one presents a unique combination of exogenous emissions drivers, transformation effects, and cost uncertainties. This is similar to the findings in Groves et al. (2020), which analyzed the costs and benefits of Costa Rica's decarbonization plan and found few net cost futures, and the conditions that led to them were difficult to summarize.

*To whom do costs and benefits accrue?*

Figure 4.8 describes the range of benefits across these results by category of costs and benefits used in Chapter 3. Several categories of benefits are positive across all futures: health safety and productivity; avoided pollution; ecosystem services; and fuel costs. This is consistent with the fact that Critical Actions strategies reduce fossil fuel dependency and increase forestation, with corresponding benefits in those categories. The benefits in terms of sector investment are, by definition, negative across all futures, as this category captures capital and other investments' costs.

The benefits in the other categories vary by future. The electricity sector can experience net costs if capital costs, particularly for transmission and system upgrades, are extremely high and not offset by maintenance and fuel-cost savings. In agriculture, the net impact of implementing the Critical Actions on output is typically positive, but can be negative in some futures, if livestock's foregone value is not outpaced by increased output in crops. The other sector savings or costs include avoiding industrial activity because of more efficient material use, maintenance savings from electrification, and the system costs of transport by mode. Whether these lead to net costs or net benefits depends on how far related transformations are implemented, and the exogenous values of costs and benefits per unit of implementation.
<figure><img src="image_47.png" /><figcaption>Figure 4.8 Major categories of costs and benefits under uncertainty.</figcaption></figure>

Figure 4.8 classifies benefits into those that are incurred by actors in our key sectors—agriculture, buildings, industry, transport, and energy production sectors (right box plot), and benefits that are external to those sectors (left box plot), including avoided pollution; other health, safety, and productivity benefits; and ecosystem services. These benefits tend to accrue to the public and the healthcare system.

Figure 4.9 shows that while external benefits are large and positive in all scenarios, internal benefits vary. In some futures, actors can enjoy positive internal benefits, particularly when energy cost savings recoup technical investments. But many futures pose net technical costs to sector actors. While the external benefits almost always outweigh these costs, and typically by a large margin (see Figure 4.8), the cost to sector actors may prohibit climate action, regardless of the broader benefits that might accrue to a nation.

This points to the significance of government interventions to redistribute benefits through society, through fiscal policy, tariff structure, and social policy. For instance, governments could internalize some of the social benefits of reduced congestion and air pollution by adjusting taxes on fuel and vehicle ownership (e.g., Victor-Gallardo et al., 2022) or reforming fossil fuel subsidies while reinforcing cash transfers or subsidizing adoption of clean technology (Missbach et al., 2024).
<figure><img src="image_47.png" /><figcaption>Figure 4.8 Major categories of costs and benefits under uncertainty.</figcaption></figure>

Figure 4.8 classifies benefits into those that are incurred by actors in our key sectors—agriculture, buildings, industry, transport, and energy production sectors (right box plot), and benefits that are external to those sectors (left box plot), including avoided pollution; other health, safety, and productivity benefits; and ecosystem services. These benefits tend to accrue to the public and the healthcare system.

Figure 4.9 shows that while external benefits are large and positive in all scenarios, internal benefits vary. In some futures, actors can enjoy positive internal benefits, particularly when energy cost savings recoup technical investments. But many futures pose net technical costs to sector actors. While the external benefits almost always outweigh these costs, and typically by a large margin (see Figure 4.8), the cost to sector actors may prohibit climate action, regardless of the broader benefits that might accrue to a nation.

This points to the significance of government interventions to redistribute benefits through society, through fiscal policy, tariff structure, and social policy. For instance, governments could internalize some of the social benefits of reduced congestion and air pollution by adjusting taxes on fuel and vehicle ownership (e.g., Victor-Gallardo et al., 2022) or reforming fossil fuel subsidies while reinforcing cash transfers or subsidizing adoption of clean technology (Missbach et al., 2024).
<figure><img src="image_48.png" /><figcaption>Figure 4.9 Internal and external costs and benefits.</figcaption></figure>
<figure><img src="image_48.png" /><figcaption>Figure 4.9 Internal and external costs and benefits.</figcaption></figure>
<figure><img src="image_49.png" /></figure>
<figure><img src="image_49.png" /></figure>
This chapter explores how the regional strategies from Chapters 3 and 4 have different outcomes and implications for individual countries based on their underlying socioeconomic, geographic, development, and other differences.

We illustrate results in three countries: Brazil, the Dominican Republic, and Mexico. For each country we provide a summary of its NDC, focusing on their mitigation targets and their stated actions for achieving these targets. Also, if available, we discuss their LTS objectives. We then summarize the country-level results of the five strategies analyzed in Chapter 3, and then of the Core Actions strategy described in Chapter 4.

These differences reiterate that while some common actions are critical to reach net zero, the specific implementation levels of these and other actions across the economy will depend on local conditions, and their success will be challenged by different uncertainties and conditions. Overall, decarbonization planning cannot be a copy-paste exercise; it should be based on national deliberation and tailored for local priorities and challenges.

## Brazil

Brazil, the largest economy in Latin America, faces various economic, political, and environmental challenges in the context of climate change. Economically, Brazil depends on industries such as agriculture, mining, and energy production, which contribute significantly to GHG emissions and environmental degradation. Brazil has made progress in addressing climate change through commitments under the Paris Agreement and implementing national policies to reduce the Amazon's deforestation. However, political challenges and competing interests pose barriers to effective enforcement and regulation (Gallo and Albrecht, 2019).

Environmentally, Brazil is home to the Amazon, the world's largest tropical rainforest. The Amazon plays a critical role in global climate regulation, storing about 25% of the world's above-ground biomass carbon, 64% of which is in Brazil (Fawcett et al., 2023). Deforestation, illegal logging, and land encroachment pose significant threats to the region's biodiversity and its ability to meet its GHG emissions targets (Cardil et al, 2020). Adaptation efforts require sustainable land-use practices, conservation measures, and increased resilience in vulnerable communities (Niemeyer and Vale, 2022; Di Gregorio et al, 2016). Brazil's unique position as a global environmental steward and major emitter of GHGs highlights the need for comprehensive strategies that integrate economic development, political will, and environmental protection to address the complex challenges of mitigating and adapting to climate change (Gallo and Albrecht, 2019).
This chapter explores how the regional strategies from Chapters 3 and 4 have different outcomes and implications for individual countries based on their underlying socioeconomic, geographic, development, and other differences.

We illustrate results in three countries: Brazil, the Dominican Republic, and Mexico. For each country we provide a summary of its NDC, focusing on their mitigation targets and their stated actions for achieving these targets. Also, if available, we discuss their LTS objectives. We then summarize the country-level results of the five strategies analyzed in Chapter 3, and then of the Core Actions strategy described in Chapter 4.

These differences reiterate that while some common actions are critical to reach net zero, the specific implementation levels of these and other actions across the economy will depend on local conditions, and their success will be challenged by different uncertainties and conditions. Overall, decarbonization planning cannot be a copy-paste exercise; it should be based on national deliberation and tailored for local priorities and challenges.

## Brazil

Brazil, the largest economy in Latin America, faces various economic, political, and environmental challenges in the context of climate change. Economically, Brazil depends on industries such as agriculture, mining, and energy production, which contribute significantly to GHG emissions and environmental degradation. Brazil has made progress in addressing climate change through commitments under the Paris Agreement and implementing national policies to reduce the Amazon's deforestation. However, political challenges and competing interests pose barriers to effective enforcement and regulation (Gallo and Albrecht, 2019).

Environmentally, Brazil is home to the Amazon, the world's largest tropical rainforest. The Amazon plays a critical role in global climate regulation, storing about 25% of the world's above-ground biomass carbon, 64% of which is in Brazil (Fawcett et al., 2023). Deforestation, illegal logging, and land encroachment pose significant threats to the region's biodiversity and its ability to meet its GHG emissions targets (Cardil et al, 2020). Adaptation efforts require sustainable land-use practices, conservation measures, and increased resilience in vulnerable communities (Niemeyer and Vale, 2022; Di Gregorio et al, 2016). Brazil's unique position as a global environmental steward and major emitter of GHGs highlights the need for comprehensive strategies that integrate economic development, political will, and environmental protection to address the complex challenges of mitigating and adapting to climate change (Gallo and Albrecht, 2019).
In 2020, Brazil's total emissions stood at 1.45 GtCO2eq, accounting for 2.92% of global emissions, marking a decline of 28% compared to 2005. Brazil's NDC targets the major sectors contributing to its emissions. The main drivers of emissions identified in the NDC's business-as-usual (BAU) scenario include agriculture, energy, land-use change and forestry, waste, and industrial processes. Agriculture alone accounted for 35.3% of emissions, followed by energy at 29.9% and land-use change and forestry at 27.5%. By 2025, Brazil commits to reducing emissions by 37% compared to 2005 levels, while aiming for a substantial GHG emission reduction of 50% by 2030. Furthermore, Brazil envisions achieving a long-term objective of carbon neutrality by 2050 (UNFCCC, 2022a). However, Climate Action Tracker's overall rating of Brazil's climate policies and commitments currently is deemed insufficient, requiring substantial improvements to meet its 2030 NDC target (Climate Action Tracker, 2022a).

To mitigate emissions, Brazil has implemented various actions across key sectors. In agriculture and forestry, the country provides incentives to reduce deforestation, enhances afforestation and reforestation efforts, promotes sustainable agricultural practices, sets sustainability standards for biomass use, and encourages reducing CO2, CH4, and N2O emissions from agricultural activities. In the electricity and heat sector, Brazil has established a support scheme for renewables, focusing on highly efficient power plant infrastructure, investing in grid infrastructure development, exploring non-renewable low-carbon alternatives, and encouraging electricity storage. In transport, the country promotes energy-efficient heavy- and light-duty vehicles, encourages a switch to low-emissions land transportation, and aims to shift the modal share, among others. The industry sector receives support for energy efficiency in production, material efficiency, establishing performance and equipment standards, incentives to reduce methane emissions from fuel exploration and production, landfill methane reduction, and a support scheme for CCS and fuel-switching initiatives. Lastly, in buildings, Brazil focuses on implementing performance and equipment standards, while providing support for highly efficient appliances (Bezerra et al, 2021; Silvero et al, 2019). Brazil has not yet submitted an LTS that could further outline its plans for achieving carbon neutrality and sustainability in the coming decades.

Our findings for Brazil track closely with regional findings, given that Brazil constitutes 40% of the region's emissions. Figure 5.1 shows results of our Chapter 3 analysis for Brazil. It shows that, under initial conditions, the Agriculture and Forest and Other Land Use sector accounts for the country's largest share of emissions. None of the three individual categories of transformation analyzed in this report (Incremental Improvements, Supply-Side Solutions, and Changing Consumption) reach net zero, though Changing Consumption comes close as it returns massive amounts of land to secondary forests that can offset emissions in the rest of the economy. However, taking All Actions achieves the 2050 carbon-neutrality objective, suggesting that actions from across these categories can enable Brazil to reach its targets.
In 2020, Brazil's total emissions stood at 1.45 GtCO2eq, accounting for 2.92% of global emissions, marking a decline of 28% compared to 2005. Brazil's NDC targets the major sectors contributing to its emissions. The main drivers of emissions identified in the NDC's business-as-usual (BAU) scenario include agriculture, energy, land-use change and forestry, waste, and industrial processes. Agriculture alone accounted for 35.3% of emissions, followed by energy at 29.9% and land-use change and forestry at 27.5%. By 2025, Brazil commits to reducing emissions by 37% compared to 2005 levels, while aiming for a substantial GHG emission reduction of 50% by 2030. Furthermore, Brazil envisions achieving a long-term objective of carbon neutrality by 2050 (UNFCCC, 2022a). However, Climate Action Tracker's overall rating of Brazil's climate policies and commitments currently is deemed insufficient, requiring substantial improvements to meet its 2030 NDC target (Climate Action Tracker, 2022a).

To mitigate emissions, Brazil has implemented various actions across key sectors. In agriculture and forestry, the country provides incentives to reduce deforestation, enhances afforestation and reforestation efforts, promotes sustainable agricultural practices, sets sustainability standards for biomass use, and encourages reducing CO2, CH4, and N2O emissions from agricultural activities. In the electricity and heat sector, Brazil has established a support scheme for renewables, focusing on highly efficient power plant infrastructure, investing in grid infrastructure development, exploring non-renewable low-carbon alternatives, and encouraging electricity storage. In transport, the country promotes energy-efficient heavy- and light-duty vehicles, encourages a switch to low-emissions land transportation, and aims to shift the modal share, among others. The industry sector receives support for energy efficiency in production, material efficiency, establishing performance and equipment standards, incentives to reduce methane emissions from fuel exploration and production, landfill methane reduction, and a support scheme for CCS and fuel-switching initiatives. Lastly, in buildings, Brazil focuses on implementing performance and equipment standards, while providing support for highly efficient appliances (Bezerra et al, 2021; Silvero et al, 2019). Brazil has not yet submitted an LTS that could further outline its plans for achieving carbon neutrality and sustainability in the coming decades.

Our findings for Brazil track closely with regional findings, given that Brazil constitutes 40% of the region's emissions. Figure 5.1 shows results of our Chapter 3 analysis for Brazil. It shows that, under initial conditions, the Agriculture and Forest and Other Land Use sector accounts for the country's largest share of emissions. None of the three individual categories of transformation analyzed in this report (Incremental Improvements, Supply-Side Solutions, and Changing Consumption) reach net zero, though Changing Consumption comes close as it returns massive amounts of land to secondary forests that can offset emissions in the rest of the economy. However, taking All Actions achieves the 2050 carbon-neutrality objective, suggesting that actions from across these categories can enable Brazil to reach its targets.
<figure><img src="image_50.png" /><figcaption>Figure 5.1 Emissions under maximum implementation of transformations by category, Brazil.</figcaption></figure>

We find that Brazil would benefit from implementing the sectoral transformations analyzed in this report. As Figure 5.2 shows, all categories of transformations yield positive net benefits for Brazil under nominal assumptions. The biggest benefits will be generated in the avoided pollution, health, safety and productivity, and other sectors' savings categories. Implementing All Actions would require US$709 billion (1.92% of today's GDP per year) in sector-specific investments, yielding $1 trillion in net benefits.
<figure><img src="image_50.png" /><figcaption>Figure 5.1 Emissions under maximum implementation of transformations by category, Brazil.</figcaption></figure>

We find that Brazil would benefit from implementing the sectoral transformations analyzed in this report. As Figure 5.2 shows, all categories of transformations yield positive net benefits for Brazil under nominal assumptions. The biggest benefits will be generated in the avoided pollution, health, safety and productivity, and other sectors' savings categories. Implementing All Actions would require US$709 billion (1.92% of today's GDP per year) in sector-specific investments, yielding $1 trillion in net benefits.
<figure><img src="image_51.png" /><figcaption>**Figure 5.2 Discounted costs and benefits under maximum Implementation of transformations by category, Brazil.**</figcaption></figure>

Figures 5.3 and 5.4 present results under uncertainty for Brazil and provide country-level versions of our Chapter 4 analysis. Figure 5.3 shows the emissions over time and under uncertainty of 1,000 variants of the Critical Actions strategy described in Chapter 4: shifting food-production patterns, altering deforestation, decarbonizing electricity production, and electrifying transport. Approximately 90% of these variants reach or overshoot net-zero emissions by 2050, with only 10% of trajectories falling short of this target. Figure 5.4 shows this strategy results in positive net benefits in nearly all variants and conditions. Here again, emission reductions benefit from efforts to boost agricultural productivity, shift diets toward foods that require less space to grow, and afforest the freed-up land.
<figure><img src="image_51.png" /><figcaption>Figure 5.2 Discounted costs and benefits under maximum Implementation of transformations by category, Brazil.</figcaption></figure>

Figures 5.3 and 5.4 present results under uncertainty for Brazil and provide country-level versions of our Chapter 4 analysis. Figure 5.3 shows the emissions over time and under uncertainty of 1,000 variants of the Critical Actions strategy described in Chapter 4: shifting food-production patterns, altering deforestation, decarbonizing electricity production, and electrifying transport. Approximately 90% of these variants reach or overshoot net-zero emissions by 2050, with only 10% of trajectories falling short of this target. Figure 5.4 shows this strategy results in positive net benefits in nearly all variants and conditions. Here again, emission reductions benefit from efforts to boost agricultural productivity, shift diets toward foods that require less space to grow, and afforest the freed-up land.
<figure><img src="image_52.png" /><figcaption>Figure 5.3 Emissions trajectories of 1,000 Critical Action variants amid uncertainty, Brazil.</figcaption></figure>

<figure><img src="image_53.png" /><figcaption>Figure 5.4 Net benefits and net 2050 emissions of Critical Action variants under uncertainty, Brazil.</figcaption></figure>
<figure><img src="image_52.png" /><figcaption>Figure 5.3 Emissions trajectories of 1,000 Critical Action variants amid uncertainty, Brazil.</figcaption></figure>

<figure><img src="image_53.png" /><figcaption>Figure 5.4 Net benefits and net 2050 emissions of Critical Action variants under uncertainty, Brazil.</figcaption></figure>
Figure 5.5 identifies combinations of lever intensities and exogenous conditions that lead the Critical Actions strategy to miss net-zero emissions. In Brazil’s case, these vulnerable conditions resemble the vulnerable conditions identified for the overall region because of Brazil’s importance in both emissions and sequestration potential. In this respect, shifting agricultural production and consumption and halting deforestation are critical transformations for reaching net zero, and net zero is most challenged by the lower livestock productivity and lower sequestration potential of primary and secondary forests.

Figure 5.5 highlights one vulnerable region in the lower left corner where productivity and sequestration rates are lower than 20% of nominal and transformations are implemented at less than 40% of maximum. Sixty-eight percent of the trajectories in this region fail to reach net zero. This region describes 53% of the trajectories that fail to meet net-zero targets.

<figure><img src="image_54.png" /><figcaption>Figure 5.5 Vulnerable conditions of Critical Actions, Brazil.</figcaption></figure>
Figure 5.5 identifies combinations of lever intensities and exogenous conditions that lead the Critical Actions strategy to miss net-zero emissions. In Brazil’s case, these vulnerable conditions resemble the vulnerable conditions identified for the overall region because of Brazil’s importance in both emissions and sequestration potential. In this respect, shifting agricultural production and consumption and halting deforestation are critical transformations for reaching net zero, and net zero is most challenged by the lower livestock productivity and lower sequestration potential of primary and secondary forests.

Figure 5.5 highlights one vulnerable region in the lower left corner where productivity and sequestration rates are lower than 20% of nominal and transformations are implemented at less than 40% of maximum. Sixty-eight percent of the trajectories in this region fail to reach net zero. This region describes 53% of the trajectories that fail to meet net-zero targets.

<figure><img src="image_54.png" /><figcaption>Figure 5.5 Vulnerable conditions of Critical Actions, Brazil.</figcaption></figure>