Book 10: Country Layers
Country-specific context for each of CTH's 5 operating countries. Colombia fully mapped in v1.0. Peru, Costa Rica, El Salvador, Guatemala in v1.1+.
- Colombia
- Peru
- Peru — Overview & CTH Presence
- Peru — Regulatory & Climate Framework
- Peru — Green Finance Taxonomy Alignment
- Peru — CLP Cohort Data Summary
- Peru — Taxonomy Node Mapping
- Costa Rica
- Costa Rica Green Finance Taxonomy — Overview
- Costa Rica NDC & Carbon Neutrality
- Costa Rica-Colombia Taxonomy Alignment
- Costa Rica Cleantech Taxonomy Crosswalk
- Costa Rica CTH Presence & Data Coverage
- El Salvador
- El Salvador — Overview & CTH Presence
- El Salvador — Regulatory & Climate Framework
- El Salvador — Green Finance Taxonomy Alignment
- El Salvador — CLP Cohort Data Summary
- El Salvador — Taxonomy Node Mapping
- Guatemala
Colombia
Full country mapping — deepest CTH coverage (v1.0)
Peru
Country layer — v1.1
Peru — Overview & CTH Presence
| country | Peru |
| iso_code | PE |
| cth_presence | CLP cohorts (2022–2026) + REIN Hub Peru (active since 2024) |
| gf_taxonomy | None — gap documented |
| ndc_target | 30% unconditional / 40% conditional GHG reduction by 2030 vs BAU |
| eudr_commodities | Coffee, Cacao, Wood, Cattle (partial — Amazon frontier) |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Country Profile
Peru is CTH's second-deepest country engagement after Colombia. The REIN Hub Peru has been active since 2024, anchoring regional innovation networks across Lima, Cusco, and the selva alta coffee corridor. CLP cohorts have run continuously since 2022, producing startups focused on deforestation monitoring, sustainable agriculture, and rural energy access.
Economy and Climate Context
Peru's economy is heavily resource-dependent: mining (copper, gold, zinc) accounts for over 60% of exports, while agriculture — particularly coffee and cacao — provides livelihoods for hundreds of thousands of smallholders in the Amazon basin. The country faces a dual climate challenge: accelerating deforestation in the Amazon lowlands (Ucayali, Madre de Dios, San Martín) and glacier retreat in the Andes that threatens water supply for Lima and coastal agriculture.
CTH Engagement Summary
CTH's Peru footprint includes: (1) CLP cohorts spanning 4 annual cycles with approximately 35 startups supported across AFOLU, energy, and climate intelligence sectors; (2) REIN Hub Peru providing a permanent innovation node for cleantech entrepreneurs; (3) Sustenttia diagnostic platform deployed for Peruvian startups; (4) Data integration with SERNANP for Amazon deforestation monitoring use cases.
EUDR Exposure
Peru has significant EUDR exposure across four commodities. Coffee production in Junín, San Martín, and Amazonas provinces is the largest export category subject to EUDR due diligence. Cacao from San Martín and Ucayali is the second-largest exposure. Timber from the Amazon basin (particularly Ucayali and Loreto) faces EU market access requirements. Cattle ranching along the Amazon frontier creates partial exposure, though at lower volumes than Brazil or Colombia.
{
"country": "peru",
"iso_code": "PE",
"cth_clp": true,
"cth_rein": true,
"gf_taxonomy": false,
"ndc_year": 2020,
"eudr_commodities": ["coffee", "cacao", "wood", "cattle"],
"schema_version": "1.1"
}
Peru — Regulatory & Climate Framework
| country | Peru |
| iso_code | PE |
| cth_presence | CLP cohorts + REIN Hub Peru |
| gf_taxonomy | None — gap documented |
| ndc_target | 30% unconditional / 40% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Cattle |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
National Climate Law
Peru's Ley Marco de Cambio Climático (Ley 30754, enacted April 2018) establishes the legal framework for climate action. It mandates that all levels of government integrate climate change into planning and budgeting, creates the High-Level Commission on Climate Change (CANCC), and designates MINAM (Ministerio del Ambiente) as the primary coordinating authority. The law explicitly addresses both mitigation and adaptation with a focus on vulnerable populations.
NDC Commitments
Peru's updated NDC (2020) commits to a 30% unconditional reduction in GHG emissions by 2030 relative to business-as-usual projections, increasing to 40% conditional on international finance and technology transfer. Key sectoral targets include: (1) LULUCF — reducing deforestation to net-zero by 2030 in priority regions; (2) Energy — increasing renewable share in the electricity mix to 15% from non-hydro sources; (3) Agriculture — reducing emissions intensity per unit of production through improved practices.
Key Institutions
MINAM (Ministerio del Ambiente) is the primary climate authority. SERNANP (Servicio Nacional de Áreas Naturales Protegidas) manages protected areas and Amazon monitoring. OSINFOR regulates forest concessions and timber legality. SERFOR (Servicio Nacional Forestal y de Fauna Silvestre) manages forest governance. MEF (Ministry of Economy and Finance) leads green bond and sustainable finance initiatives.
Climate Plans and Strategies
PLANCC II (Plan de Acción Nacional de Cambio Climático) provides the operational roadmap for NDC implementation. The Plan de Acción en Género y Cambio Climático integrates gender considerations into climate policy. Peru's National Strategy on Forests and Climate Change (ENBCC) specifically targets deforestation reduction in the Amazon. The National Adaptation Plan (NAP) prioritizes water security, agriculture, and health.
Relevant Regulatory Instruments
Decreto Supremo 013-2019-MINAM establishes the carbon market regulation framework. Peru participates in REDD+ through the Forest Investment Program (FIP) and the Green Climate Fund (GCF). The Huella de Carbono Perú program provides a voluntary corporate carbon footprint registry. Superintendencia del Mercado de Valores (SMV) has issued guidance on green bond issuance but no mandatory disclosure requirements yet.
{
"country": "peru",
"iso_code": "PE",
"cth_clp": true,
"cth_rein": true,
"gf_taxonomy": false,
"ndc_year": 2020,
"eudr_commodities": ["coffee", "cacao", "wood", "cattle"],
"schema_version": "1.1"
}
Peru — Green Finance Taxonomy Alignment
| country | Peru |
| iso_code | PE |
| cth_presence | CLP cohorts + REIN Hub Peru |
| gf_taxonomy | None — gap documented |
| ndc_target | 30% unconditional / 40% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Cattle |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Green Finance Taxonomy Status
Peru does not have a national green finance taxonomy as of May 2026. This represents a significant gap given Peru's role as the second-largest economy in the Andean region and its substantial green bond issuance history. Colombia's Taxonomía Verde (2022) remains the only binding national GF taxonomy in the Andean/Pacific Alliance bloc and serves as the nearest regional reference point for Peru.
Gap Analysis
The absence of a Peruvian GF taxonomy creates three operational gaps for Origo: (1) No domestic activity classification to crosswalk against when assigning latam_peru flags — requiring reliance on Colombia's taxonomy as a proxy combined with NDC priorities; (2) No standardized green bond eligibility criteria specific to Peru's LULUCF-heavy emissions profile; (3) No regulatory alignment pathway for Peruvian financial institutions seeking to classify their portfolios as "green" under domestic law.
Nearest Equivalents
In the absence of a formal taxonomy, Peru relies on several proxy frameworks: (1) Colombia's Taxonomía Verde — applicable to many shared Andean commodities and sectors; (2) CBI (Climate Bonds Initiative) criteria — used for Peru's sovereign and corporate green bonds; (3) IFC Performance Standards — applied by development finance institutions operating in Peru; (4) EU Taxonomy — referenced by European importers of Peruvian commodities under EUDR compliance. The Origo taxonomy uses a combination of these to infer latam_peru relevance flags.
Development Prospects
SBS (Superintendencia de Banca, Seguros y AFP) issued Resolución 1928-2021 requiring financial institutions to integrate ESG risk into governance, which could serve as a foundation for taxonomy development. MEF has signaled interest in developing green finance guidelines as part of its sustainable finance roadmap. IDB and GCF technical assistance programs are supporting taxonomy-adjacent work in Peru's financial sector. A formal Peruvian GF taxonomy is estimated at 2–3 years from adoption.
{
"country": "peru",
"iso_code": "PE",
"cth_clp": true,
"cth_rein": true,
"gf_taxonomy": false,
"ndc_year": 2020,
"eudr_commodities": ["coffee", "cacao", "wood", "cattle"],
"schema_version": "1.1"
}
Peru — CLP Cohort Data Summary
| country | Peru |
| iso_code | PE |
| cth_presence | CLP cohorts + REIN Hub Peru |
| gf_taxonomy | None — gap documented |
| ndc_target | 30% unconditional / 40% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Cattle |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
CLP Cohort History
Peru has participated in CLP (Cleantech Leadership Programme) cohorts from 2022 through 2026, making it one of CTH's most consistent country partners. REIN Hub Peru, active since 2024, provides ongoing mentoring and networking beyond the cohort cycle. The combination of CLP + REIN gives Peru the second-deepest CTH coverage after Colombia.
Cohort Summary
| Year | Startups | Primary Sectors | Notes |
|---|---|---|---|
| 2022 | 6 | AF, EN | First Peru cohort; focus on coffee traceability and rural solar |
| 2023 | 8 | AF, IC, EN | Expanded to include climate data/MRV startups |
| 2024 | 10 | AF, IC, EN, XS | REIN Hub launched; carbon market entrants joined |
| 2025 | 7 | AF, IC | EUDR-focused cohort; deforestation monitoring emphasis |
| 2026 | 4 | AF, EN, IC | Current cohort; Amazon sustainability focus |
Sector Distribution
Across all Peru cohorts, sector distribution is: AFOLU (45%) — driven by coffee, cacao, and deforestation monitoring; Energy (25%) — rural electrification, solar, and small hydropower; Climate Intelligence (20%) — MRV platforms, earth observation, and supply chain traceability; Carbon/Offsets (10%) — REDD+ project developers and carbon accounting platforms.
Key Outcomes
Notable outcomes from Peru CLP cohorts include: 3 startups that secured post-cohort investment exceeding $500K; 2 partnerships with SERNANP for Amazon monitoring technology deployment; 1 startup integrated into the Origo platform data pipeline for EUDR compliance services; establishment of REIN Hub Peru as a permanent cleantech innovation node in Lima.
{
"country": "peru",
"iso_code": "PE",
"cth_clp": true,
"cth_rein": true,
"gf_taxonomy": false,
"ndc_year": 2020,
"eudr_commodities": ["coffee", "cacao", "wood", "cattle"],
"schema_version": "1.1"
}
Peru — Taxonomy Node Mapping
| country | Peru |
| mapping_type | taxonomy_node_mapping |
| schema_version | 1.1 |
Node Mapping Summary
Peru's taxonomy node mapping reflects its Amazon-heavy EUDR exposure, its strong AFOLU sector relevance (coffee, cacao, timber, partial cattle), emerging energy transition needs, and its role as a key site for AI/MRV deforestation monitoring. All AFOLU base nodes with coffee, cacao, or wood EUDR flags are tagged Y. Energy nodes are tagged partial reflecting Peru's hydropower-dominant grid with nascent solar/wind growth. IC nodes for Amazon monitoring and MRV are tagged Y.
AFOLU Nodes
| Node ID | Label | latam_peru | Rationale |
|---|---|---|---|
| CT-AF-001 | Land & Soil | Y | Critical for soil management in coffee/cacao regions of Junín and San Martín |
| CT-AF-002 | Forests & Woodlands | Y | Amazon deforestation is Peru's largest emissions source; shade-grown coffee agroforestry |
| CT-AF-003 | Oceans & Water | Y | Water management in coffee processing (beneficio húmedo); El Niño coastal impacts |
| CT-AF-004 | Ice & Snow | Y | Andean glacier retreat directly threatens Lima's water supply and highland agriculture |
| CT-AF-005 | Air & Atmosphere | partial | Limited direct relevance; air quality monitoring in Lima and mining regions |
| CT-AF-006 | Smart Farming | Y | Precision agriculture for smallholder coffee and cacao in selva alta |
| CT-AF-007 | Livestock & Fisheries | partial | Cattle frontier in Amazon (partial EUDR); anchovy fisheries climate-sensitive |
| CT-AF-008 | Crops | Y | Coffee, cacao, and quinoa are major export crops with climate vulnerability |
| CT-AF-009 | Alternative Meat & Seafood | N | Minimal market presence in Peru |
| CT-AF-010 | Alternative Dairy & Egg | N | Minimal market presence in Peru |
Energy Nodes
| Node ID | Label | latam_peru | Rationale |
|---|---|---|---|
| CT-EN-001 | Critical Minerals | Y | Peru is a top-5 global producer of copper, zinc, silver — essential for energy transition |
| CT-EN-002 | Hydrogen | partial | Green hydrogen pilots in southern coastal desert; early stage |
| CT-EN-003 | Nuclear | N | No nuclear energy program |
| CT-EN-004 | Bio & Synthetic Fuels | partial | Biodiesel from palm oil in San Martín; small scale |
| CT-EN-005 | Fossil Fuels (Transition) | partial | Camisea gas field transition planning; LNG export infrastructure |
| CT-EN-006 | Solar | Y | Excellent irradiance in Arequipa, Tacna, Moquegua; rural off-grid solar in Amazon |
| CT-EN-007 | Wind | partial | Ica and Piura wind corridors; 3 GW pipeline but slow permitting |
| CT-EN-008 | Geothermal | partial | Volcanic Andes potential but no operating plants; exploration phase only |
| CT-EN-009 | Biomass | partial | Coffee pulp and cacao husk biomass potential in selva alta |
| CT-EN-010 | Hydro Tidal & Wave | Y | Peru's grid is ~60% hydropower; critical dependency with glacier retreat risk |
| CT-EN-011 | Batteries | partial | Lithium exploration in Puno; battery storage for grid stabilization |
| CT-EN-012 | Alternative Storage | partial | Pumped hydro potential in Andes; early feasibility studies |
| CT-EN-013 | Grids | partial | Grid modernization needed for renewable integration; SEIN interconnection gaps |
| CT-EN-014 | EV Charging | partial | Lima EV adoption nascent; regulatory framework under development |
| CT-EN-015 | Peer-to-Peer Energy | N | No regulatory framework for P2P energy trading |
Climate Intelligence & Carbon Nodes
| Node ID | Label | latam_peru | Rationale |
|---|---|---|---|
| CT-IC-001 | IoT & Earth Observation | Y | SERNANP Amazon monitoring; satellite deforestation detection is core use case |
| CT-IC-002 | Climate Data | Y | SENAMHI climate data infrastructure; glacier monitoring networks |
| CT-IC-003 | Climate Finance | Y | Green bond issuance; GCF project pipeline; sovereign sustainability-linked bonds |
| CT-IC-004 | Climate Risk | Y | El Niño/La Niña exposure; flood risk in Amazon; drought in coastal agriculture |
| CT-IC-005 | Climate Insurance | partial | Parametric insurance pilots for smallholder coffee farmers; limited scale |
| CT-XS-001 | Carbon Capture & Storage | N | No CCS projects or geological storage sites under development |
| CT-XS-002 | B2B Carbon Offsets & Exchanges | Y | Amazon REDD+ project pipeline; voluntary carbon market activity |
| CT-XS-003 | B2C Carbon Offsets | partial | Tourism-linked offsets; limited domestic B2C market |
| CT-XS-004 | Carbon Intelligence | Y | Huella de Carbono Perú program; corporate carbon footprint registry |
| CT-XS-005 | Carbon Accounting | Y | MINAM greenhouse gas inventory system; REDD+ MRV requirements |
Waste, Built Environment & Transport Nodes
| Node ID | Label | latam_peru | Rationale |
|---|---|---|---|
| CT-WA-001 | Waste to Energy | partial | Pilot projects in Lima; coffee processing waste valorization potential |
| CT-WA-002 | Sustainable Materials | partial | Bamboo construction and bio-based materials from Amazon resources |
| CT-WA-003 | Textiles | partial | Alpaca and organic cotton supply chains with sustainability potential |
| CT-WA-004 | Recycling | partial | Lima municipal recycling expansion; informal sector formalization |
| CT-WA-005 | Solid Waste & Water Waste | partial | Coffee processing wastewater (aguas mieles) treatment technology |
| CT-BU-001 | Construction | partial | Green building standards emerging in Lima; seismic resilience overlap |
| CT-BU-002 to CT-BU-005 | Built Environment (remaining) | partial | Urban sustainability nascent; transport infrastructure in expansion |
| CT-TR-001 to CT-TR-005 | Transport (all) | partial | Lima Metro expansion; EV policy under development; limited cleantech startup activity |
Extension Nodes
| Node ID | Label | latam_peru | Rationale |
|---|---|---|---|
| CT-EX-001 | Drought-resistant crop varieties and seed tech | Y | Critical for coastal agriculture under El Niño stress |
| CT-EX-002 | Flood resilience infrastructure (nature-based) | Y | Amazon basin and coastal El Niño flooding |
| CT-EX-003 | Heat adaptation for agriculture | Y | Coffee rust and heat stress moving upslope in Andes |
| CT-EX-004 | Early warning systems for climate events | Y | El Niño early warning critical for agriculture and fisheries |
| CT-EX-005 | Community-led reforestation and agroforestry | Y | Indigenous community forestry in Amazon; shade coffee agroforestry |
| CT-EX-006 | Mangrove restoration and blue carbon | partial | Tumbes mangroves; limited compared to Caribbean nations |
| CT-EX-007 | Silvopastoral systems | partial | Amazon cattle frontier; emerging silvopastoral pilots |
| CT-EX-008 | Bioeconomy: non-timber forest products | Y | Brazil nut, camu camu, sacha inchi — Amazon bioeconomy |
| CT-EX-009 | PES platforms | Y | REDD+ payments; Transferencias Directas Condicionadas program |
| CT-EX-010 | Solar home systems and pico-solar | Y | Rural electrification in Amazon communities without grid access |
| CT-EX-011 | Community biodigesters | partial | Highland livestock communities; limited scale |
| CT-EX-014 | Remote sensing and satellite deforestation monitoring | Y | Core use case: SERNANP Amazon monitoring, GeoBosques platform |
| CT-EX-015 | AI-powered carbon MRV | Y | REDD+ MRV requirements; growing CLP startup activity |
| CT-EX-016 | Supply chain traceability platforms | Y | Coffee and cacao supply chain traceability for EUDR compliance |
| CT-EX-017 | Precision agriculture data platforms | Y | Smallholder coffee/cacao precision agriculture |
| CT-EX-018 | Deforestation-free certification services | Y | EUDR Article 9 compliance for coffee and cacao exporters |
| CT-EX-019 | Supply chain due diligence platforms | Y | EUDR operator obligations for Peruvian exporters |
| CT-EX-020 | Smallholder technical assistance for EUDR | Y | Hundreds of thousands of smallholder coffee farmers need EUDR support |
| CT-EX-021 | EUDR operator documentation services | Y | Documentation requirements for Peruvian coffee/cacao operators |
| CT-EX-022 | Cacao plot-level geolocation | Y | San Martín and Ucayali cacao polygon mapping |
| CT-EX-023 | Cacao agroforestry monitoring | Y | Cacao agroforestry carbon monitoring in selva alta |
| CT-EX-026 | Cacao climate adaptation | Y | Varietal resilience research for Peruvian fino de aroma cacao |
| CT-EX-029 | Pasture-driven deforestation monitoring | Y | Amazon frontier cattle expansion monitoring |
| CT-EX-032 | Cross-commodity EUDR landscape compliance | Y | Multi-commodity landscapes in Ucayali and San Martín |
| CT-EX-034 | Palm oil mill traceability | Y | San Martín palm oil production |
| CT-EX-035 | RSPO and palm certification | Y | RSPO-certified operations in Peruvian Amazon |
| CT-EX-036 | Imported commodity deforestation risk screening | Y | Peru as origin country for EU-destined commodities |
| CT-EX-039 | Community forest management | Y | Indigenous community forest governance in Amazon basin |
| CT-EX-040 | Smallholder group certification | Y | Coffee cooperative group certification models |
| CT-EX-041 | Alternative development crop compliance | partial | DEVIDA alternative development regions with coca-to-cacao transitions |
Costa Rica
Country layer — v1.1 (incl. Costa Rica GF Taxonomy Aug 2024)
Costa Rica Green Finance Taxonomy — Overview
Overview
| Field | Value |
|---|---|
| country | Costa Rica |
| gf_taxonomy | BCCR Green Finance Taxonomy (Aug 2024) |
| ndc_target | Max 11,380 Gg CO2e by 2030; 53% reduction budget 2025-2035 |
| carbon_neutrality | 2050 |
| last_updated | 2026-05-26 |
Background
Costa Rica launched its Taxonomía de Finanzas Sostenibles in August 2024, making it the third country in Latin America (after Colombia and Mexico) to establish a green finance taxonomy. The taxonomy was developed under the joint leadership of the Ministry of Environment and Energy (MINAE), the Ministry of Finance, the Central Bank of Costa Rica (BCCR), and the four financial regulators (SUGEF, SUGEVAL, SUPEN, SUGESE), with contributions from over 300 experts representing more than 180 organizations across public and private sectors, NGOs, and academia.
Sectors Covered
The taxonomy identifies eight priority economic sectors for sustainable investment:
- Electricity, Gas, Steam & Air Conditioning Supply — renewable energy generation, grid efficiency, geothermal (Costa Rica generates ~95% renewable electricity)
- Construction — green buildings, energy-efficient construction, sustainable materials
- Transport — electromobility, public transit electrification, low-carbon logistics
- Manufacturing — clean industrial processes, resource efficiency
- Solid Waste Management & Emissions Capture — waste-to-energy, circular economy, recycling infrastructure
- Water Supply & Treatment — water infrastructure, wastewater treatment, watershed management
- Information & Communication Technologies — ICT for sustainability monitoring, smart grids, environmental data platforms
- Land Use (Agriculture, Livestock & Forestry) — sustainable agriculture, reforestation, silvopastoral systems, PES programs
Environmental Objectives
The initial phase prioritizes two environmental objectives: (1) climate change mitigation and (2) climate change adaptation. Future phases may incorporate additional objectives including sustainable water use, biodiversity protection, circular economy transition, and pollution prevention — following the EU Taxonomy six-objective structure.
Design Principles
The taxonomy applies a three-step eligibility test for each economic activity: (a) substantial contribution to at least one environmental objective, (b) Do No Significant Harm (DNSH) to other objectives, and (c) minimum social safeguards. This mirrors the EU Taxonomy architecture, ensuring international interoperability. The taxonomy is designed to be interoperable with the EU Taxonomy, Colombia Taxonomía Verde, and Mexico sustainable taxonomy, following the UNEP FI Common Framework for Latin American taxonomies published in 2023.
Institutional Framework
SUGEVAL (securities superintendent) oversees taxonomy application in capital markets. SUGEF applies it to banking supervision. The taxonomy supports: evaluation of credit and investment portfolio alignment, design of new green financial products, climate risk assessment of portfolios, and green bond issuance standards. Costa Rica has been active in the Green Climate Fund and receives technical support for taxonomy implementation.
Costa Rica NDC & Carbon Neutrality
Overview
| Field | Value |
|---|---|
| country | Costa Rica |
| ndc_version | Third NDC (2025-2035), submitted November 2025 |
| ndc_target_2030 | Max 11,380 Gg CO2e net emissions (incl. LULUCF) |
| ndc_budget | 132,700 Gg CO2e cumulative 2025-2035 (~53% reduction) |
| carbon_neutrality | 2050 |
| last_updated | 2026-05-26 |
National Decarbonization Plan 2018-2050
Costa Rica published its Plan Nacional de Descarbonización in February 2019, becoming one of the first countries worldwide to present a long-term decarbonization strategy aligned with the Paris Agreement. The plan targets net-zero emissions by 2050, organized in three stages: initial (2018-2022), inflection (2023-2030), and massive deployment (2031-2050). It operates through 10 decarbonization axes and 8 cross-cutting strategies covering all major economic sectors.
NDC Sectoral Targets
Costa Rica's third NDC (2025-2035), submitted at COP30 in November 2025, establishes an economy-wide emissions budget with sector-specific mitigation contributions:
- Energy: Maintain and expand near-100% renewable electricity (historically ~95% from hydro, geothermal, wind, solar). Diversify away from hydro dependence given climate-induced drought risk. Biofuel mandate of 10% ethanol in gasoline.
- Transport: Electrify public transit as the top priority. EVs reached 12% of vehicle sales in 2023. Targets include zero-emission public bus fleet and expanded electric rail.
- Agriculture & Livestock: Nationally Appropriate Mitigation Actions (NAMAs) for coffee, livestock, and rice. Sustainable agriculture practices, low-carbon livestock management, climate-smart crops.
- FOLU (Forests & Other Land Use): The LULUCF sector is a net carbon sink equivalent to over 20% of economy-wide emissions. The 2050 target requires more than doubling current sink capacity. Costa Rica pioneered Payments for Ecosystem Services (PES) globally through FONAFIFO.
- Waste: Circular economy expansion, waste-to-energy, improved landfill management, methane capture.
- Industry: Clean manufacturing processes, energy efficiency in industrial operations, decarbonization of industrial heat.
- Blue Carbon: Emerging area in the third NDC — mangrove restoration, coastal wetlands, ocean-based climate solutions.
PES Pioneer
Costa Rica's Payments for Ecosystem Services program (Pagos por Servicios Ambientales), administered by FONAFIFO since 1997, is globally recognized as a model for conservation finance. It has channeled over USD 500 million to landowners for forest conservation, reforestation, agroforestry, and watershed protection. This program directly underpins several Cleantech Taxonomy nodes in the EX sector (PES platforms, community reforestation, agroforestry).
Climate Action Context
Costa Rica generates nearly all its electricity from renewable sources and has maintained forest cover above 50% through aggressive conservation policy. The Climate Action Tracker rates Costa Rica's overall climate targets as needing to be approximately 7% more ambitious to align with 1.5°C pathways. The country's unique challenge is transport — the sector accounts for the largest share of fossil fuel use and is the primary decarbonization frontier.
Costa Rica-Colombia Taxonomy Alignment
Overview
| Field | Value |
|---|---|
| country | Costa Rica |
| comparison | Costa Rica GF Taxonomy vs Colombia Taxonomía Verde |
| shared_influence | CBI, EU Taxonomy, UNEP FI LATAM Framework |
| last_updated | 2026-05-26 |
Shared Foundations
Both Costa Rica and Colombia built their green finance taxonomies on common international foundations: the EU Taxonomy architecture (substantial contribution + DNSH + social safeguards), Climate Bonds Initiative sector criteria, and the UNEP FI Common Framework for Sustainable Finance Taxonomies for Latin America and the Caribbean (2023). This shared heritage means approximately 70% of eligible activities overlap between the two taxonomies, particularly in energy, transport, construction, and water sectors.
Sector Coverage Comparison
| Sector | Colombia TVC | Costa Rica GF | Notes |
|---|---|---|---|
| Energy | Y | Y | Both cover renewables, grid, storage. CR stronger on geothermal. |
| Transport | Y | Y | Both cover electromobility. CR more advanced in EV adoption. |
| Construction | Y | Y | Green buildings, energy efficiency. Similar criteria. |
| Water | Y | Y | Both cover treatment and supply. CR has stronger watershed focus. |
| Waste | Y | Y | Waste-to-energy, recycling, circular economy. |
| Agriculture | Y (tiered) | Y | Colombia has basic/intermediate/advanced tiers. CR uses PES framework. |
| Livestock | Y (tiered) | Y | Colombia more detailed with practice tiers for cattle. |
| Forestry | Y (tiered) | Y | Both cover reforestation. CR PES model is more established. |
| Manufacturing | Y | Y | Clean industrial processes in both. |
| ICT | Y | Y | Both include ICT for environmental monitoring. |
Key Differences
- Agricultural depth: Colombia's TVC has a three-tier practice classification (basic, intermediate, advanced) for agriculture, livestock, and forestry. Costa Rica does not tier but relies on PES eligibility and NAMA alignment.
- Hydrogen: Both countries are developing hydrogen roadmaps, but Colombia's is more advanced with a published strategy. Costa Rica's hydrogen activities are covered but less detailed.
- Fossil fuel transition: Colombia's taxonomy explicitly addresses transition activities for fossil fuels. Costa Rica, with near-100% renewable electricity, has less need for fossil transition categories.
- Blue carbon: Costa Rica's NDC explicitly includes blue carbon (mangroves, coastal wetlands). Colombia addresses this through biodiversity and LULUCF channels.
- PES integration: Costa Rica's taxonomy benefits from 25+ years of PES implementation through FONAFIFO, giving it stronger forest finance infrastructure than any other LATAM country.
Interoperability Implications for Origo
For the Cleantech Taxonomy crosswalk, the high sector overlap means most nodes that are col_gf_aligned=Y will also be cr_gf_aligned=Y. The main divergences occur in: (a) fossil fuel transition nodes (Colombia Y, Costa Rica N), (b) carbon market nodes (neither taxonomy covers directly), and (c) advanced food-tech nodes like alternative proteins (neither covers). The EX-sector LATAM extensions (PES, agroforestry, silvopastoral) align strongly with both taxonomies.
Costa Rica Cleantech Taxonomy Crosswalk
Overview
| Field | Value |
|---|---|
| country | Costa Rica |
| crosswalk_scope | 71 Cleantech Taxonomy nodes vs CR GF Taxonomy + NDC |
| gf_taxonomy_sectors | Energy, Transport, Construction, Manufacturing, Waste, Water, ICT, Land Use |
| ndc_sectors | Energy, Transport, Agriculture, Waste, LULUCF, Industry, Blue Carbon |
| last_updated | 2026-05-26 |
Methodology
This crosswalk maps each of the 71 Cleantech Taxonomy nodes against two Costa Rica regulatory instruments: (1) the BCCR Green Finance Taxonomy (August 2024) and (2) the National Decarbonization Plan / NDC (third NDC, 2025-2035). For each node, alignment is rated Y (directly covered), partial (indirectly or partially covered), or N (not covered).
Sector Summary — AFOLU (CT-AF)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-AF-001 | Land & Soil | Y | Y |
| CT-AF-002 | Forests & Woodlands | Y | Y |
| CT-AF-003 | Oceans & Water | Y | Y |
| CT-AF-004 | Ice & Snow | N | N |
| CT-AF-005 | Air & Atmosphere | N | partial |
| CT-AF-006 | Smart Farming | Y | Y |
| CT-AF-007 | Livestock & Fisheries | Y | Y |
| CT-AF-008 | Crops | Y | Y |
| CT-AF-009 | Alternative Meat & Seafood | N | N |
| CT-AF-010 | Alternative Dairy & Egg | N | N |
Sector Summary — Waste (CT-WA)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-WA-001 | Waste to Energy | Y | Y |
| CT-WA-002 | Sustainable Materials | Y | partial |
| CT-WA-003 | Textiles | N | N |
| CT-WA-004 | Recycling | Y | Y |
| CT-WA-005 | Solid Waste & Water Waste | Y | Y |
Sector Summary — Cross-Sectoral (CT-XS)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-XS-001 | Carbon Capture & Storage | N | N |
| CT-XS-002 | B2B Carbon Offsets | N | partial |
| CT-XS-003 | B2C Carbon Offsets | N | partial |
| CT-XS-004 | Carbon Intelligence | N | partial |
| CT-XS-005 | Carbon Accounting | N | partial |
Sector Summary — ICT (CT-IC)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-IC-001 | IoT & Earth Observation | Y | Y |
| CT-IC-002 | Climate Data | partial | Y |
| CT-IC-003 | Climate Finance | Y | Y |
| CT-IC-004 | Climate Risk | partial | Y |
| CT-IC-005 | Climate Insurance | N | partial |
Sector Summary — Energy (CT-EN)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-EN-001 | Critical Minerals | N | N |
| CT-EN-002 | Hydrogen | Y | Y |
| CT-EN-003 | Nuclear | N | N |
| CT-EN-004 | Bio & Synthetic Fuels | Y | Y |
| CT-EN-005 | Fossil Fuels (Transition) | N | N |
| CT-EN-006 | Solar | Y | Y |
| CT-EN-007 | Wind | Y | Y |
| CT-EN-008 | Geothermal | Y | Y |
| CT-EN-009 | Biomass | Y | Y |
| CT-EN-010 | Hydro Tidal & Wave | Y | Y |
| CT-EN-011 | Batteries | Y | Y |
| CT-EN-012 | Alternative Storage | partial | partial |
| CT-EN-013 | Grids | Y | Y |
| CT-EN-014 | EV Charging | Y | Y |
| CT-EN-015 | Peer-to-Peer Energy | N | N |
Sector Summary — Buildings (CT-BU)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-BU-001 | Construction | Y | Y |
| CT-BU-002 | Heating & Cooling | Y | Y |
| CT-BU-003 | Residential | Y | Y |
| CT-BU-004 | Commercial | Y | Y |
| CT-BU-005 | Transport Infrastructure | Y | Y |
Sector Summary — Transport (CT-TR)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-TR-001 | Micro Mobility | Y | Y |
| CT-TR-002 | Vehicles | Y | Y |
| CT-TR-003 | Trains & Rolling Stock | Y | Y |
| CT-TR-004 | Boats & Ships | N | partial |
| CT-TR-005 | Aircraft | N | N |
Sector Summary — Origo Extensions (CT-EX)
| Node | Label | cr_gf_aligned | cr_ndc_aligned |
|---|---|---|---|
| CT-EX-001 | Drought-resistant crops | Y | Y |
| CT-EX-002 | Flood resilience (NbS) | Y | Y |
| CT-EX-003 | Heat adaptation agriculture | Y | Y |
| CT-EX-004 | Early warning systems | Y | Y |
| CT-EX-005 | Community reforestation | Y | Y |
| CT-EX-006 | Mangrove & blue carbon | Y | Y |
| CT-EX-007 | Silvopastoral systems | Y | Y |
| CT-EX-008 | Bioeconomy: NTFP | Y | Y |
| CT-EX-009 | PES platforms | Y | Y |
| CT-EX-010 | Solar home systems | Y | Y |
| CT-EX-011 | Community biodigesters | Y | Y |
| CT-EX-012 | Artisanal cleantech | Y | partial |
| CT-EX-013 | Productive energy microenterprises | Y | Y |
| CT-EX-014 | Remote sensing deforestation | Y | Y |
| CT-EX-015 | AI-powered carbon MRV | N | partial |
| CT-EX-016 | Supply chain traceability | N | N |
| CT-EX-017 | Precision agriculture data | Y | Y |
| CT-EX-018 | Deforestation-free certification | N | N |
| CT-EX-019 | Supply chain due diligence | N | N |
| CT-EX-020 | Smallholder EUDR assistance | Y | partial |
| CT-EX-021 | EUDR documentation services | N | N |
Costa Rica CTH Presence & Data Coverage
Overview
| Field | Value |
|---|---|
| country | Costa Rica |
| cth_presence | CLP cohorts, REIN Hub connections |
| clp_status | Active cohorts |
| rein_hubs | Connected via LATAM network |
| last_updated | 2026-05-26 |
CLP Cohort Coverage
CleantechHUB operates Cleantech Leadership Programme (CLP) cohorts that include Costa Rica-based cleantech entrepreneurs and organizations. Costa Rica participants typically operate in renewable energy, sustainable agriculture, waste management, and eco-tourism sectors. The CLP provides mentorship, technical assistance, and market access support that directly maps to multiple Cleantech Taxonomy nodes, particularly in the EN (Energy), AF (AFOLU), and EX (Extensions) sectors.
REIN Hub Connections
Costa Rica connects to the CTH REIN (Red de Emprendimiento e Innovación) Hub network through cross-border cleantech partnerships. Costa Rica's strong institutional framework for environmental innovation — including CINDE (investment promotion), PROCOMER (trade), and the Costa Rican Chamber of Technology — creates entry points for REIN Hub activities. Priority connection areas include: PES platform technology, agroforestry monitoring tools, and renewable energy microgrids.
Data Availability Assessment
Costa Rica has relatively strong public environmental data infrastructure compared to other LATAM countries:
- National GHG Inventory: Published regularly through SINAMECC (National Climate Change Metrics System)
- Forest Cover: SINAC/FONAFIFO maintain detailed forest cover and PES data
- Energy: ICE (Costa Rican Electricity Institute) publishes detailed generation mix data
- EV Adoption: MINAE tracks electric vehicle registrations and charging infrastructure
- Financial: BCCR and SUGEVAL publish green bond and sustainable finance data
Gaps remain in: disaggregated agricultural emissions by practice type, smallholder-level PES data, and real-time waste management metrics.
Taxonomy Node Coverage
Of the 71 Cleantech Taxonomy nodes, Costa Rica's GF taxonomy covers approximately 44 nodes (62%) and the NDC covers approximately 50 nodes (70%). The strongest coverage is in Energy (13/15 GF, 12/15 NDC), Buildings (5/5 both), and the EX extensions (15/21 GF, 16/21 NDC). The weakest coverage is in Cross-Sectoral (0/5 GF, 0/5 NDC for carbon markets) and niche food-tech categories (alternative proteins).
El Salvador
Country layer — v1.2
El Salvador — Overview & CTH Presence
| country | El Salvador |
| iso_code | SV |
| cth_presence | CLP cohorts only (no REIN Hub) |
| gf_taxonomy | None — emerging interest post-COP28 |
| ndc_target | 30% unconditional / 50% conditional GHG reduction by 2030 |
| eudr_commodities | Coffee (high exposure), Cacao (minor), Wood (partial — firewood/charcoal) |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Country Profile
El Salvador is CTH's smallest country engagement by coverage depth — CLP cohorts only, with no REIN Hub established. Despite this, El Salvador offers a unique cleantech profile: it is the only dollarized economy in the CTH portfolio, which simplifies green bond issuance and international investor access. The country's small geographic size (21,041 km²) and flat-to-hilly Pacific slope terrain create favorable conditions for solar energy deployment.
Economy and Climate Context
El Salvador's economy is driven by remittances (~26% of GDP), services, and agriculture. Coffee, historically the dominant export commodity, has declined due to coffee leaf rust (roya) and climate variability but remains the primary EUDR-exposed commodity. The country is highly vulnerable to ENSO-driven drought, tropical storms, and coastal flooding. Deforestation has reduced forest cover to approximately 12% of total land area — one of the lowest in the Americas.
CTH Engagement Summary
CTH's El Salvador footprint consists of CLP cohort participation since 2023. Startup participation has focused on solar energy, specialty coffee traceability, and drought adaptation technologies. The absence of a REIN Hub limits post-cohort support infrastructure. El Salvador startups have accessed Sustenttia diagnostics through the regional CLP platform.
EUDR Exposure
El Salvador's EUDR exposure is concentrated in specialty coffee, which is the country's most valuable agricultural export to the EU. Coffee farms are predominantly small-scale (70% under 5 hectares), creating significant challenges for plot-level geolocation and documentation requirements under EUDR Article 9. Cacao production is minor but growing in eastern departments. Wood exposure relates primarily to firewood and charcoal production, not industrial timber.
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"iso_code": "SV",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood"],
"schema_version": "1.1"
}
El Salvador — Regulatory & Climate Framework
| country | El Salvador |
| iso_code | SV |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — emerging interest post-COP28 |
| ndc_target | 30% unconditional / 50% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
National Environmental Law
El Salvador's Ley de Medio Ambiente (Decreto Legislativo 233, 1998, reformed multiple times) provides the foundational environmental regulatory framework. The law establishes MARN (Ministerio de Medio Ambiente y Recursos Naturales) as the lead environmental authority and mandates environmental impact assessments for development projects. Subsequent reforms have incorporated climate change considerations, though the law predates modern climate policy frameworks.
NDC Commitments
El Salvador's updated NDC (2021) commits to a 30% unconditional and 50% conditional reduction in GHG emissions by 2030. Priority sectors include: (1) Energy — increasing renewable energy share to 74% of generation capacity, leveraging geothermal and solar; (2) AFOLU — reducing emissions from deforestation and land-use change through landscape restoration programs; (3) Waste — expanding methane capture from landfills. The conditional target is ambitious relative to the economy's size and depends heavily on international climate finance.
Key Institutions
MARN is the primary climate authority, responsible for NDC implementation and environmental regulation. The Consejo Nacional de Sustentabilidad Ambiental y Vulnerabilidad (CONASAV) provides cross-sectoral coordination. The Superintendencia del Sistema Financiero (SSF) regulates the financial sector but has not yet issued green finance guidance. The Consejo Salvadoreño del Café (CSC) manages coffee sector policy.
Climate Plans and Strategies
The Plan Nacional de Cambio Climático (PNCC) provides the strategic framework for climate action. El Salvador's Nationally Appropriate Mitigation Actions (NAMAs) focus on energy efficiency and renewable energy. The Plan Nacional de Restauración de Ecosistemas y Paisajes (Plan de Restauración) targets restoration of 1 million hectares through agroforestry and landscape approaches. The Estrategia Nacional de Medio Ambiente (ENMA) integrates climate resilience into environmental governance.
Dollarization and Green Finance Implications
El Salvador's dollarized economy (since 2001) creates unique green finance dynamics: (1) No exchange rate risk for international green bond investors; (2) Simplified cross-border investment structures for climate finance; (3) Federal Reserve monetary policy pass-through limits domestic monetary tools for green stimulus. The introduction of Bitcoin as legal tender (2021) has created regulatory uncertainty that may complicate green finance development.
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"iso_code": "SV",
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"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood"],
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}
El Salvador — Green Finance Taxonomy Alignment
| country | El Salvador |
| iso_code | SV |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — emerging interest post-COP28 |
| ndc_target | 30% unconditional / 50% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Green Finance Taxonomy Status
El Salvador does not have a national green finance taxonomy as of May 2026. There is emerging interest post-COP28, with MARN and SSF participating in IDB-sponsored regional workshops on sustainable finance classification. However, no formal development process has been initiated. The country's Bitcoin-as-legal-tender experiment has absorbed regulatory bandwidth that might otherwise support GF taxonomy development.
Gap Analysis
The absence of a GF taxonomy creates several gaps for Origo country mapping: (1) No domestic classification system to crosswalk — El Salvador's latam_el_salvador flags must rely entirely on NDC priorities, CBI criteria, and regional proxies; (2) No green bond framework specific to El Salvador's economy, though dollarization means USD-denominated green bonds face no currency risk; (3) Limited institutional capacity for taxonomy development given MARN's resource constraints.
Nearest Equivalents
El Salvador references the following proxy frameworks: (1) Costa Rica's green finance guidelines — most relevant Central American reference; (2) CBI taxonomy — applied for any future green bond issuance; (3) EU Taxonomy — applicable to coffee exports under EUDR compliance pathways; (4) SICA (Central American Integration System) regional sustainability frameworks. The Origo taxonomy assigns latam_el_salvador flags based on NDC priorities, EUDR commodity exposure, and CLP sector activity.
Development Prospects
A Salvadoran GF taxonomy is likely 4–5 years from adoption given current institutional capacity and competing regulatory priorities. The CABEI (Central American Bank for Economic Integration) green bond program may provide an external catalyst by requiring taxonomy-aligned classification for financed projects. IDB Invest has signaled interest in supporting Central American taxonomy harmonization efforts that could accelerate El Salvador's timeline.
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"iso_code": "SV",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood"],
"schema_version": "1.1"
}
El Salvador — CLP Cohort Data Summary
| country | El Salvador |
| iso_code | SV |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — emerging interest post-COP28 |
| ndc_target | 30% unconditional / 50% conditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
CLP Cohort History
El Salvador joined the CLP program in 2023, making it the newest country in CTH's portfolio. Cohort participation has been smaller in scale than Colombia, Costa Rica, or Peru — reflecting both the country's smaller cleantech ecosystem and the absence of a REIN Hub to provide sustained post-cohort support. Startup quality has been concentrated in solar energy and specialty coffee technology.
Cohort Summary
| Year | Startups | Primary Sectors | Notes |
|---|---|---|---|
| 2023 | 3 | EN, AF | First cohort; solar installers and coffee traceability |
| 2024 | 4 | EN, AF, IC | Solar-focused; one climate data startup entered |
| 2025 | 3 | AF, EN | Drought adaptation and agroforestry focus |
| 2026 | 2 | EN, AF | Current cohort; solar + specialty coffee |
Sector Distribution
Across El Salvador CLP cohorts, sector distribution is: Energy (42%) — dominated by solar deployment and distribution startups leveraging flat terrain and high irradiance; AFOLU (42%) — specialty coffee traceability, drought-resistant agriculture, and agroforestry; Climate Intelligence (16%) — climate data and early warning systems for drought/ENSO events.
Key Observations
El Salvador's CLP participation reveals several patterns: (1) The cleantech ecosystem is early-stage — most startups are pre-revenue or early-revenue; (2) Solar energy has outsized representation due to favorable geography (Pacific-facing, flat terrain, 5.5+ kWh/m²/day irradiance); (3) Coffee sector startups are increasingly EUDR-motivated; (4) The absence of a REIN Hub limits sustained engagement — startups lose momentum between cohort cycles; (5) Dollarization simplifies international investor engagement for those startups that reach investment readiness.
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"iso_code": "SV",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood"],
"schema_version": "1.1"
}
El Salvador — Taxonomy Node Mapping
| country | El Salvador |
| mapping_type | taxonomy_node_mapping |
| schema_version | 1.1 |
Node Mapping Summary
El Salvador's taxonomy node mapping reflects its concentrated EUDR exposure in specialty coffee, its strong solar energy potential, and its high climate vulnerability (drought, ENSO, coastal flooding). The node mapping is narrower than Peru or Colombia given El Salvador's smaller economy and limited cleantech ecosystem. AFOLU nodes for coffee are tagged Y; solar energy nodes are tagged Y; adaptation-relevant extension nodes are tagged Y; most other sectors are partial or N.
AFOLU Nodes
| Node ID | Label | latam_el_salvador | Rationale |
|---|---|---|---|
| CT-AF-001 | Land & Soil | Y | Soil degradation from intensive coffee cultivation; restoration needs |
| CT-AF-002 | Forests & Woodlands | Y | 12% forest cover remaining — shade coffee agroforestry is primary restoration pathway |
| CT-AF-003 | Oceans & Water | partial | Coastal flooding and Pacific fisheries; limited cleantech activity |
| CT-AF-004 | Ice & Snow | N | No relevance — tropical lowland country |
| CT-AF-005 | Air & Atmosphere | N | No significant cleantech activity in air quality |
| CT-AF-006 | Smart Farming | Y | Precision agriculture for specialty coffee; drought monitoring for smallholders |
| CT-AF-007 | Livestock & Fisheries | N | Livestock sector small and not EUDR-exposed |
| CT-AF-008 | Crops | Y | Coffee is the primary export crop; cacao growing; drought-resistant staples needed |
| CT-AF-009 | Alternative Meat & Seafood | N | No market presence |
| CT-AF-010 | Alternative Dairy & Egg | N | No market presence |
Energy Nodes
| Node ID | Label | latam_el_salvador | Rationale |
|---|---|---|---|
| CT-EN-001 | Critical Minerals | N | No significant mineral reserves; mining ban in effect since 2017 |
| CT-EN-002 | Hydrogen | N | No hydrogen development programs |
| CT-EN-003 | Nuclear | N | No nuclear program |
| CT-EN-004 | Bio & Synthetic Fuels | partial | Sugarcane ethanol potential; small scale |
| CT-EN-005 | Fossil Fuels (Transition) | partial | Oil-dependent transport sector needs transition planning |
| CT-EN-006 | Solar | Y | Excellent irradiance (5.5+ kWh/m²/day); flat Pacific terrain; strong CLP pipeline |
| CT-EN-007 | Wind | partial | Metapán wind corridor; limited compared to solar potential |
| CT-EN-008 | Geothermal | Y | ~25% of electricity from geothermal (Berlín, Ahuachapán plants); volcanic ring potential |
| CT-EN-009 | Biomass | partial | Coffee husk and sugarcane bagasse; small scale |
| CT-EN-010 | Hydro Tidal & Wave | partial | Small hydropower on Lempa River; limited expansion potential |
| CT-EN-011 | Batteries | N | No battery production or significant storage deployment |
| CT-EN-012 | Alternative Storage | N | No alternative storage projects |
| CT-EN-013 | Grids | partial | SIEPAC regional grid interconnection; needs modernization for solar integration |
| CT-EN-014 | EV Charging | N | Minimal EV adoption; no charging infrastructure |
| CT-EN-015 | Peer-to-Peer Energy | N | No regulatory framework |
Climate Intelligence & Carbon Nodes
| Node ID | Label | latam_el_salvador | Rationale |
|---|---|---|---|
| CT-IC-001 | IoT & Earth Observation | partial | MARN environmental monitoring; limited satellite coverage programs |
| CT-IC-002 | Climate Data | Y | Drought and ENSO monitoring critical for agriculture; early warning systems |
| CT-IC-003 | Climate Finance | partial | CABEI green bond access; limited domestic green finance infrastructure |
| CT-IC-004 | Climate Risk | Y | High vulnerability to drought, tropical storms, coastal flooding, volcanic risk |
| CT-IC-005 | Climate Insurance | partial | CCRIF SPC Caribbean/Central America parametric insurance; emerging |
| CT-XS-001 | Carbon Capture & Storage | N | No CCS activity |
| CT-XS-002 | B2B Carbon Offsets | partial | Small-scale forestry offset projects; limited market |
| CT-XS-003 | B2C Carbon Offsets | N | No domestic B2C carbon market |
| CT-XS-004 | Carbon Intelligence | N | No national carbon registry or intelligence platform |
| CT-XS-005 | Carbon Accounting | partial | National GHG inventory exists but limited granularity |
Waste, Built Environment & Transport Nodes
| Node ID | Label | latam_el_salvador | Rationale |
|---|---|---|---|
| CT-WA-001 to CT-WA-005 | Waste (all) | partial | Landfill methane capture potential; coffee processing waste; limited cleantech |
| CT-BU-001 to CT-BU-005 | Built Environment (all) | N | Minimal green building activity; no cleantech startup presence |
| CT-TR-001 to CT-TR-005 | Transport (all) | N | No significant cleantech transport activity |
Extension Nodes
| Node ID | Label | latam_el_salvador | Rationale |
|---|---|---|---|
| CT-EX-001 | Drought-resistant crop varieties | Y | Critical — ENSO drought is the primary agricultural risk |
| CT-EX-002 | Flood resilience (nature-based) | Y | Coastal and riverine flooding from tropical storms |
| CT-EX-003 | Heat adaptation for agriculture | Y | Coffee rust and heat stress at lower elevations |
| CT-EX-004 | Early warning systems | Y | Drought/ENSO early warning critical for 400K+ smallholders |
| CT-EX-005 | Community-led reforestation | Y | Priority: El Salvador has lowest forest cover in Americas; shade coffee reforestation |
| CT-EX-006 | Mangrove restoration | Y | Pacific coast mangroves for storm surge protection and blue carbon |
| CT-EX-007 | Silvopastoral systems | partial | Small-scale livestock; limited compared to larger countries |
| CT-EX-008 | Bioeconomy: NTFPs | N | Limited forest resources for non-timber products |
| CT-EX-009 | PES platforms | partial | Small-scale PES pilots; limited government funding |
| CT-EX-010 | Solar home systems | Y | Rural electrification gaps; strong solar resource |
| CT-EX-014 | Remote sensing deforestation monitoring | partial | Small land area limits complexity; basic MARN monitoring exists |
| CT-EX-016 | Supply chain traceability | Y | Specialty coffee traceability for EUDR compliance |
| CT-EX-017 | Precision agriculture platforms | Y | Smallholder coffee farm management and drought adaptation |
| CT-EX-018 | Deforestation-free certification | Y | EUDR compliance for specialty coffee exports to EU |
| CT-EX-019 | Supply chain due diligence | Y | EUDR operator obligations for Salvadoran coffee exporters |
| CT-EX-020 | Smallholder EUDR assistance | Y | 70% of coffee farms under 5 ha — massive EUDR support need |
| CT-EX-025 | Cacao smallholder digital inclusion | Y | Growing cacao sector needs digital tools for emerging EUDR requirements |
| CT-EX-030 | Pasture restoration and livestock intensification | Y | Land-scarce country benefits from intensification to free land for reforestation |
| CT-EX-031 | Cattle deforestation-free verification | Y | Even small cattle sector needs verification given minimal remaining forest |
| CT-EX-038 | Timber legality verification | Y | Firewood/charcoal supply chain legality verification |
Guatemala
Country layer — v1.2
Guatemala — Overview & CTH Presence
| country | Guatemala |
| iso_code | GT |
| cth_presence | CLP cohorts only (no REIN Hub) |
| gf_taxonomy | None — opportunity: largest Central American capital market |
| ndc_target | 22.6% unconditional GHG reduction by 2030 |
| eudr_commodities | Coffee (high — Huehuetenango, Antigua), Cacao (moderate), Wood (Petén), Rubber (minor) |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Country Profile
Guatemala is Central America's largest economy by GDP and population (~18 million). CTH engagement consists of CLP cohorts only, with no REIN Hub established. Despite this, Guatemala presents the most diverse cleantech opportunity set of the three Central American countries in the Origo taxonomy: world-leading cardamom exports, highland specialty coffee, the Maya Biosphere Reserve (Petén), and the region's strongest geothermal energy capacity after Costa Rica.
Economy and Climate Context
Guatemala's economy is diversified across agriculture (10% of GDP but 30% of employment), remittances (~18% of GDP), manufacturing, and services. Coffee from highland regions (Huehuetenango, Antigua, Cobán) is a major export commodity and the primary EUDR exposure. Guatemala is the world's largest cardamom exporter — a commodity NOT on the EUDR list but economically significant. The Petén department contains the Maya Biosphere Reserve, one of the largest contiguous forest areas in Mesoamerica, under severe deforestation pressure.
CTH Engagement Summary
CTH's Guatemala footprint includes CLP cohort participation since 2023. Startups have focused on geothermal energy applications, coffee traceability, and Maya forest conservation technologies. Guatemala has the largest untapped cleantech potential of the three Central American countries due to its market size, geothermal resources, and forest conservation needs. A REIN Hub for Guatemala could serve as a Central American anchor node.
EUDR Exposure
Guatemala has significant EUDR exposure across four commodities. Highland coffee (Huehuetenango, Antigua Guatemala, Cobán) is the highest-exposure commodity, with EU as a major destination market. Cacao production in Alta Verapaz represents moderate exposure. Wood from Petén and other forested departments faces EUDR requirements, particularly timber from community forest concessions in the Maya Biosphere Reserve's multiple-use zone. Rubber production is minor but present. Notably, cardamom — Guatemala's other major agricultural export — is not subject to EUDR.
{
"country": "guatemala",
"iso_code": "GT",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood", "rubber"],
"schema_version": "1.1"
}
Guatemala — Regulatory & Climate Framework
| country | Guatemala |
| iso_code | GT |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — opportunity: largest Central American capital market |
| ndc_target | 22.6% unconditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Rubber |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Climate Framework
Guatemala's climate governance is anchored in Acuerdo Gubernativo 329-2009, which created the institutional framework for climate change response. This is one of the older climate instruments in the region and predates the Paris Agreement — it needs updating to reflect current ambitions. The Ley Marco para Regular la Reducción de la Vulnerabilidad, la Adaptación Obligatoria ante los Efectos del Cambio Climático y la Mitigación de Gases de Efecto Invernadero (Decreto 7-2013) provides a more recent legal foundation but implementation has been slow.
NDC Commitments
Guatemala's updated NDC (originally 2019, updated 2021) commits to a 22.6% unconditional GHG reduction by 2030 relative to BAU. This is the most modest unconditional target among the three countries in this phase, reflecting institutional and fiscal constraints. Key sectoral priorities: (1) LULUCF — reducing deforestation in Petén and the northern lowlands, which account for the majority of Guatemala's emissions; (2) Energy — expanding geothermal, solar, and biomass generation; (3) Agriculture — improved practices in coffee and staple crop production to reduce emissions intensity.
Key Institutions
MARN Guatemala (Ministerio de Ambiente y Recursos Naturales) is the primary climate and environmental authority. CONAP (Consejo Nacional de Áreas Protegidas) manages the Maya Biosphere Reserve and other protected areas. INAB (Instituto Nacional de Bosques) governs forest management and community forestry concessions. ANACAFÉ (Asociación Nacional del Café) manages coffee sector policy and export standards. The Superintendencia de Bancos regulates the financial sector but has limited green finance mandates.
Climate Plans and Strategies
Guatemala's Política Nacional de Cambio Climático provides the strategic vision. The Plan de Acción Nacional de Cambio Climático (PANCC) operationalizes NDC commitments. The Estrategia Nacional para la Reducción de la Deforestación (ENREDD+) targets reduced deforestation through REDD+ mechanisms, with Petén as the priority landscape. Guatemala's National Adaptation Plan focuses on water security, food sovereignty, and disaster risk reduction — reflecting the country's high vulnerability to hurricanes, drought, and volcanic activity.
Community Forest Concessions
Guatemala's community forest concession model in the Maya Biosphere Reserve's multiple-use zone is internationally recognized as one of the most successful community-managed forest governance systems in the tropics. ACOFOP (Asociación de Comunidades Forestales de Petén) coordinates 12 community concessions covering over 400,000 hectares. This model has demonstrated deforestation rates near zero within concession areas, significantly lower than surrounding unmanaged areas. It is directly relevant to EUDR timber compliance and REDD+ carbon market activity.
{
"country": "guatemala",
"iso_code": "GT",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood", "rubber"],
"schema_version": "1.1"
}
Guatemala — Green Finance Taxonomy Alignment
| country | Guatemala |
| iso_code | GT |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — opportunity: largest Central American capital market |
| ndc_target | 22.6% unconditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Rubber |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
Green Finance Taxonomy Status
Guatemala does not have a national green finance taxonomy as of May 2026. However, this represents a significant opportunity: Guatemala has the largest capital market in Central America, with the Bolsa de Valores Nacional and a banking sector large enough to support green bond issuance. The Superintendencia de Bancos has not yet issued green finance guidance, but the institutional infrastructure exists for taxonomy development if political will materializes.
Gap Analysis
The absence of a Guatemalan GF taxonomy creates these gaps for Origo: (1) No domestic activity classification for crosswalking — latam_guatemala flags rely on NDC priorities, community forestry governance frameworks, and EUDR commodity exposure; (2) The largest Central American economy lacks a green finance standard, creating a regional gap that ripples through CABEI-financed programs; (3) No taxonomy means no standardized eligibility criteria for the community forest concession model — which could be a globally significant green finance use case.
Nearest Equivalents
Guatemala references the following proxy frameworks: (1) Costa Rica's green finance guidelines — the most developed Central American reference; (2) CBI taxonomy — applicable through CABEI bond programs; (3) EU Taxonomy — referenced by European coffee importers under EUDR compliance; (4) REDD+ safeguards and benefit-sharing standards — particularly relevant for Petén community forestry; (5) FSC (Forest Stewardship Council) certification — several community concessions in Petén hold FSC certification, which serves as a de facto green standard for timber.
Development Prospects
Guatemala could leapfrog other Central American countries in GF taxonomy development due to its capital market size and the internationally recognized community forestry model that provides a ready-made green activity classification template. IDB and World Bank technical assistance programs are supporting sustainable finance development in Guatemala. A realistic timeline for taxonomy adoption is 3–4 years, potentially accelerated if CABEI mandates taxonomy alignment for its regional lending programs.
{
"country": "guatemala",
"iso_code": "GT",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood", "rubber"],
"schema_version": "1.1"
}
Guatemala — CLP Cohort Data Summary
| country | Guatemala |
| iso_code | GT |
| cth_presence | CLP cohorts only |
| gf_taxonomy | None — opportunity: largest Central American capital market |
| ndc_target | 22.6% unconditional by 2030 |
| eudr_commodities | Coffee, Cacao, Wood, Rubber |
| schema_version | 1.1 |
| last_updated | 2026-05-27 |
CLP Cohort History
Guatemala has participated in CLP cohorts since 2023. While lacking a REIN Hub, Guatemala produces a more diverse startup pipeline than El Salvador due to its larger economy and varied geography — highland coffee, Petén forests, Pacific coast agriculture, and volcanic geothermal resources create distinct cleantech niches. Guatemala's CLP cohorts have been moderately sized, reflecting an ecosystem with more entrepreneurs than El Salvador but less institutional support than Peru.
Cohort Summary
| Year | Startups | Primary Sectors | Notes |
|---|---|---|---|
| 2023 | 4 | AF, EN | First cohort; coffee traceability and geothermal applications |
| 2024 | 5 | AF, EN, IC | Maya forest conservation tech; solar deployment |
| 2025 | 4 | AF, IC | EUDR-focused; community forest governance platforms |
| 2026 | 3 | AF, EN | Current cohort; geothermal + coffee |
Sector Distribution
Across Guatemala CLP cohorts, sector distribution is: AFOLU (50%) — highland coffee, Maya forest conservation, community forestry governance, cacao agroforestry; Energy (31%) — geothermal applications, solar, biomass from agricultural waste; Climate Intelligence (19%) — deforestation monitoring for Petén, supply chain traceability, and REDD+ MRV platforms.
Key Observations
Guatemala's CLP participation reveals distinct patterns: (1) Community forestry governance technology is a unique niche — no other CTH country has this focus; (2) Geothermal startups reflect Guatemala's volcanic geology and existing geothermal infrastructure; (3) Highland specialty coffee (Huehuetenango, Antigua) creates premium market access that motivates EUDR compliance investment; (4) The Maya Biosphere Reserve generates carbon market activity (REDD+) that attracts climate intelligence startups; (5) Cardamom, Guatemala's most distinctive agricultural export, falls outside the EUDR framework but could benefit from Origo-style traceability infrastructure for voluntary sustainability markets.
{
"country": "guatemala",
"iso_code": "GT",
"cth_clp": true,
"cth_rein": false,
"gf_taxonomy": false,
"ndc_year": 2021,
"eudr_commodities": ["coffee", "cacao", "wood", "rubber"],
"schema_version": "1.1"
}
Guatemala — Taxonomy Node Mapping
| country | Guatemala |
| mapping_type | taxonomy_node_mapping |
| schema_version | 1.1 |
Node Mapping Summary
Guatemala's taxonomy node mapping reflects its diverse EUDR exposure (coffee, cacao, wood, rubber), its unique community forest concession model in Petén, strong geothermal energy potential, and highland agricultural adaptation needs. AFOLU nodes for coffee and forestry are tagged Y. Geothermal and solar energy nodes are tagged Y. NbS/bioeconomy extension nodes related to the Maya forest are tagged Y. Community forest governance creates a distinct node relevance pattern not seen in the other two countries.
AFOLU Nodes
| Node ID | Label | latam_guatemala | Rationale |
|---|---|---|---|
| CT-AF-001 | Land & Soil | Y | Highland coffee soil management; Petén land restoration after slash-and-burn |
| CT-AF-002 | Forests & Woodlands | Y | Maya Biosphere Reserve — one of Mesoamerica's largest forests; community concessions |
| CT-AF-003 | Oceans & Water | partial | Motagua and Polochic river basin management; Pacific coast fisheries |
| CT-AF-004 | Ice & Snow | N | No relevance — tropical country |
| CT-AF-005 | Air & Atmosphere | partial | Guatemala City air quality; volcanic emissions monitoring |
| CT-AF-006 | Smart Farming | Y | Precision agriculture for highland coffee and cacao; cardamom production data |
| CT-AF-007 | Livestock & Fisheries | partial | Petén cattle ranching contributes to deforestation; not a major EUDR exposure |
| CT-AF-008 | Crops | Y | Coffee, cacao, cardamom — major export crops with climate vulnerability |
| CT-AF-009 | Alternative Meat & Seafood | N | No market presence |
| CT-AF-010 | Alternative Dairy & Egg | N | No market presence |
Energy Nodes
| Node ID | Label | latam_guatemala | Rationale |
|---|---|---|---|
| CT-EN-001 | Critical Minerals | partial | Nickel (Izabal), some metallic mineral reserves; controversial mining sector |
| CT-EN-002 | Hydrogen | N | No hydrogen development programs |
| CT-EN-003 | Nuclear | N | No nuclear program |
| CT-EN-004 | Bio & Synthetic Fuels | partial | Sugarcane ethanol and palm oil biodiesel; controversial social impacts |
| CT-EN-005 | Fossil Fuels (Transition) | partial | Oil production in Petén; transition planning needed |
| CT-EN-006 | Solar | Y | Good irradiance across Pacific slope; rural off-grid solar for remote communities |
| CT-EN-007 | Wind | partial | San Marcos wind corridor; 2 operating wind farms |
| CT-EN-008 | Geothermal | Y | Strongest geothermal potential in Central America after Costa Rica; Zunil, Amatitlán |
| CT-EN-009 | Biomass | Y | Sugarcane bagasse, coffee husk, and palm waste; significant installed capacity |
| CT-EN-010 | Hydro Tidal & Wave | partial | Hydropower significant (~30% of generation); Chixoy dam; social controversy |
| CT-EN-011 | Batteries | N | No battery production or significant storage deployment |
| CT-EN-012 | Alternative Storage | N | No alternative storage projects |
| CT-EN-013 | Grids | partial | SIEPAC interconnection; grid modernization for renewable integration |
| CT-EN-014 | EV Charging | N | Minimal EV adoption |
| CT-EN-015 | Peer-to-Peer Energy | N | No regulatory framework |
Climate Intelligence & Carbon Nodes
| Node ID | Label | latam_guatemala | Rationale |
|---|---|---|---|
| CT-IC-001 | IoT & Earth Observation | Y | CONAP Petén monitoring; satellite deforestation detection for Maya Biosphere Reserve |
| CT-IC-002 | Climate Data | Y | INSIVUMEH climate/volcanic monitoring; drought early warning for Dry Corridor |
| CT-IC-003 | Climate Finance | Y | Largest Central American capital market; CABEI green bond access; REDD+ finance |
| CT-IC-004 | Climate Risk | Y | Hurricane, drought (Corredor Seco), volcanic, and seismic risk — extremely high vulnerability |
| CT-IC-005 | Climate Insurance | partial | CCRIF SPC parametric insurance; agricultural index insurance pilots |
| CT-XS-001 | Carbon Capture & Storage | N | No CCS activity |
| CT-XS-002 | B2B Carbon Offsets | Y | Maya Biosphere Reserve REDD+ projects; active carbon credit generation |
| CT-XS-003 | B2C Carbon Offsets | partial | Tourism-linked offsets; limited scale |
| CT-XS-004 | Carbon Intelligence | partial | Limited national carbon registry; REDD+ reporting systems |
| CT-XS-005 | Carbon Accounting | partial | National GHG inventory; community forest carbon accounting for REDD+ |
Waste, Built Environment & Transport Nodes
| Node ID | Label | latam_guatemala | Rationale |
|---|---|---|---|
| CT-WA-001 | Waste to Energy | partial | Guatemala City landfill methane; sugarcane waste cogeneration |
| CT-WA-002 | Sustainable Materials | partial | Timber from community concessions (FSC-certified); bamboo potential |
| CT-WA-003 to CT-WA-005 | Waste (remaining) | partial | Municipal waste challenges in Guatemala City; coffee processing waste |
| CT-BU-001 to CT-BU-005 | Built Environment (all) | partial | Guatemala City green building emerging; seismic resilience technology overlap |
| CT-TR-001 to CT-TR-005 | Transport (all) | partial | Transmetro BRT expansion; limited cleantech transport startup activity |
Extension Nodes
| Node ID | Label | latam_guatemala | Rationale |
|---|---|---|---|
| CT-EX-001 | Drought-resistant crop varieties | Y | Corredor Seco drought affecting staple crops and coffee; critical food security |
| CT-EX-002 | Flood resilience (nature-based) | Y | Hurricane and tropical storm flooding; Polochic/Motagua basins |
| CT-EX-003 | Heat adaptation for agriculture | Y | Coffee rust at lower elevations; heat stress in Corredor Seco |
| CT-EX-004 | Early warning systems | Y | Volcanic, seismic, hurricane, and drought early warning critical |
| CT-EX-005 | Community-led reforestation | Y | Maya Biosphere community concession model — global best practice |
| CT-EX-006 | Mangrove restoration | partial | Pacific coast mangroves; smaller scale than Caribbean nations |
| CT-EX-007 | Silvopastoral systems | Y | Petén cattle ranching — silvopastoral as deforestation alternative |
| CT-EX-008 | Bioeconomy: NTFPs | Y | Petén community concessions: xate palm, chicle, allspice — globally significant |
| CT-EX-009 | PES platforms | Y | REDD+ payments for Maya Biosphere conservation; PINPEP incentive program |
| CT-EX-010 | Solar home systems | Y | Rural electrification gaps in Alta Verapaz, Petén, and western highlands |
| CT-EX-011 | Community biodigesters | partial | Highland livestock communities; limited scale |
| CT-EX-014 | Remote sensing deforestation monitoring | Y | Petén deforestation monitoring; CONAP surveillance; fire detection |
| CT-EX-015 | AI-powered carbon MRV | Y | Maya Biosphere REDD+ MRV requirements; community concession verification |
| CT-EX-016 | Supply chain traceability | Y | Coffee, cacao, and timber traceability for EUDR and voluntary markets |
| CT-EX-017 | Precision agriculture platforms | Y | Highland coffee, cacao, and cardamom farm management |
| CT-EX-018 | Deforestation-free certification | Y | EUDR compliance for coffee and cacao; FSC for community timber |
| CT-EX-019 | Supply chain due diligence | Y | EUDR operator obligations for Guatemalan exporters |
| CT-EX-020 | Smallholder EUDR assistance | Y | Highland coffee smallholders need EUDR compliance support |
| CT-EX-021 | EUDR operator documentation | Y | Documentation for coffee, cacao, and timber operators |
| CT-EX-022 | Cacao geolocation | Y | Alta Verapaz cacao plot mapping |
| CT-EX-023 | Cacao agroforestry monitoring | Y | Cacao under forest canopy in Alta Verapaz |
| CT-EX-032 | Cross-commodity landscape compliance | Y | Multi-commodity landscapes in Petén and Alta Verapaz |
| CT-EX-038 | Timber legality verification | Y | Community concession timber legality — FSC-certified operations in Petén |
| CT-EX-039 | Community forest management | Y | ACOFOP community concessions — global best practice for forest governance |
| CT-EX-040 | Smallholder group certification | Y | Highland coffee cooperatives; community forestry group certification |