Buenos Aires

Buenos Aires is Argentina’s capital and largest urban center, with significant emissions from transport, energy use in buildings, and waste. The city has committed to an 84% emissions reduction by 2050, emphasizing circular economy strategies, low-emission mobility, solar power, and urban greening. The climate action plan integrates equity and public participation, aiming to align with national and C40 goals. Its vulnerabilities include flooding, urban heat, and economic volatility affecting implementation.

Population: 3100000

Emissions per Capita: 3.9 tCO₂e

Total Emissions: 12100000

Vulnerability Score: 0.36

• Original Plan estimated an 8.43 Mt CO₂e reduction at just €11.86/tonne, claiming a 47.51% reduction, but lacked verifiable data to support cost, coverage, or sectoral breakdowns.

• Gaia-Enriched Plan simulated a much lower impact: only 1.1 Mt CO₂e reduction (6.2%) at a more realistic €90.91/tonne, revealing major overestimation in original assumptions.

• In full strategic simulations, up to 8.43 Mt CO₂ could still be achieved by combining: o 5 Mt CO₂ from circular economy (low-carbon construction materials) o 3.43 Mt CO₂ from building retrofits, aligned with IEA and EU Renovation Wave frameworks

• Circular Economy: 59.3%

• Buildings: 40.7%

• Others (Energy, Mobility): included in original plan but contributed less in optimized simulations

• Original plan lacks:

• Cost-per-unit estimates
• Sector-based emissions targets
• Coverage % by population or infrastructure

• Overreliance on ambitious targets without grounding in demographic or infrastructure realities

• Align emissions targets with IPCC 1.5°C pathways

• Ground simulations in local data via pilot projects

• Rebalance sector distribution, ensuring transport and buildings receive equitable attention

• Establish monitoring and evaluation mechanisms for adaptive planning

Gaia analyzes real-world climate plans by simulating:

1. 📉 CO₂e reduction potential
2. 💸 Cost per tonne and ROI
3. 🏥 Healthcare and social co-benefits
4. 🏗️ Infrastructure savings and property uplift
5. 🌡️ Urban temperature mitigation
6. 🧠 Citizen trust and satisfaction outcomes

It does so using:

• Verified scientific baselines (IPCC, AR6, WHO, IEA, Eurostat, etc.)

• Modular rule logic and impact trees

• IoT, satellite, and citizen feedback data streams (when operational)

• AI-powered simulation layers tied to ethics-bound regenerative logic

Gaia is designed to run in a high-security, air-gapped HPC environment with DMZ-controlled gateways. This architecture ensures:

• 🔒 Protection from manipulation
• 🔁 Verifiable, auditable simulations
• 🧾 Immutable public-facing ledgers for regeneration tracking

It is not a marketplace, a crypto token, or a carbon credit trading system. It is a truth layer for climate policy, capable of identifying real impact, revealing false optimism, and helping cities reach Net Zero with clarity, speed, and integrity.

This document presents an independent simulation and analysis of the city’s official Net Zero plan using the Gaia Protocol Evaluation Engine. Our goal was not to critique the city’s ambition, but to test its feasibility, completeness, and efficiency, and to show how advanced modelling and verified climate data can enhance results while saving cost, time, and emissions.

To do this, we followed the process below:

✅ Step-by-Step Methodology

1. Data Extraction We extracted raw action data from the city’s published Net Zero plan and structured it into a standardized JSON dataset.
2. Initial Gaia AI Review We ran the original plan through Gaia’s Evaluation Engine to identify gaps, inconsistencies, or missing elements based on global best practices.
3. Data Injection (Gaia Enhancement) We filled in the missing data using authoritative, peer-reviewed sources including: IPCC AR6 IEA & UN climate datasets WHO health impact baselines EU-level carbon pricing and building standards
4. Enhanced Plan Evaluation We re-ran the now-completed dataset through Gaia to produce a Gaia Enhanced Simulation , a cleaner, more complete version of the same plan, using the same budget and sector goals.
5. Side-by-Side Comparison We compared the original and enhanced plans based on: Projected CO₂e offsets Cost per tonne Sector-level impact ROI across infrastructure, health, housing, and public satisfaction
6. Modular Simulation Scenarios We then tested the plan’s internal logic using Gaia’s modeling engine in three configurations: Budget + Sectors only (not required) CO₂ Target + Sectors only (not required) Budget + CO₂ Target + Sectors

These simulations were run independently of political assumptions or formatting inconsistencies. The goal was to simulate what would happen if each plan were implemented exactly as described, and how performance changes when data is complete.

• All listed actions lack estimated costs per unit, making it impossible to assess the financial requirements or cost-effectiveness of the plan.

• Coverage percentages are absent, creating uncertainty about how much of the city population or infrastructure will benefit from each action.

• The plan does not provide sector-by-sector CO₂ reduction estimates, making it difficult to evaluate which sectors are expected to deliver the majority of savings.

• Introduce cost estimates for each action to enable budgeting, prioritization, and return-on-investment analysis.

• Define action-specific coverage percentages (e.g., percentage of households, buildings, or transit users affected) to contextualize scale and impact.

• Provide sector-based emissions baselines and projected reductions to clarify the relative contribution of each intervention.

- IPCC Special Report on Global Warming of 1.5°C

- IPCC Sixth Assessment Report (AR6)

- World Bank Climate Action Assessment Tools

The main noticeable weakness of the submitted plan is its lack of transparency and detail. It's essential to establish quantifiable targets for CO2 reduction to clarify the planned impact. Furthermore, the indicated cost per tonne of CO2 is approximately €0, which could imply that either the plan does not foresee any cost implications or the cost calculation has not been conducted properly. Both scenarios underline the need for a more comprehensive and in-depth analysis. Also, the plan does not define relevant sectors that should be addressed which is critical for developing an effective, successful, and comprehensive climate plan.

In order to refine Buenos Aires' climate plan, it is recommended that detailed CO2 reduction targets should be set, keeping in line with global recommendations and considering the city's unique features. Secondly, develop an accurate budget to implement measures that will achieve these targets, and share a clear distribution of these costs. Finally, identify the most influential sectors for emission generation in Buenos Aires, such as transport, construction, or energy, and develop comprehensive strategies to address them. This refinement can boost the effectiveness and efficiency of the climate plan while contributing to cost reduction.

• The overall target reduction percentage of 6.2% by 2050 seems low compared to the urgency and scale of emissions reductions suggested by the IPCC for limiting global warming to 1.5°C.

• The reliance on estimated data without localized studies or pilot projects may lead to inaccuracies in the projected impact of the actions.

• Coverage percentages for each sector are not supported by detailed demographic or infrastructural data, which could lead to overestimations of the plan's impact.

• Increase the target reduction percentage to align more closely with the IPCC's recommended pathways for limiting global warming to 1.5°C.

• Conduct localized feasibility studies and pilot projects for each action to gather empirical data, improving the accuracy of cost and savings estimates.

• Develop a detailed demographic and infrastructural analysis to support realistic coverage percentages and ensure efficient allocation of resources.

- IPCC Special Report on Global Warming of 1.5°C

- IPCC Sixth Assessment Report (AR6)

- World Health Organization (WHO) guidelines on urban green spaces

However, the strategy's weaknesses are evident due to the lack of information available, indicating potentially significant oversights in policy planning or reporting. Achievable and quantifiable goals are an integral part of any climate policy as they allow for monitoring progress, and implementing corrective measures if required. Moreover, the declared cost per tonne of CO2 at approximately €0 may suggest an unrealistic budgetary estimate rather than a highly efficient plan.

To enhance this climate initiative, it is recommended to clearly articulate the climate objectives with measurable targets, such as the anticipated CO2 savings and budget for the plan. This will invariably lead to a greater understanding of the climate action strategy's projected impacts on emissions reductions. Furthermore, identifying and focusing on sectors with the highest emissions, like the transport, residential, and energy sectors, will potentially provide the most substantial benefits in terms of CO2 savings. Lastly, it is crucial to carefully estimate the cost per tonne of CO2 emissions reduction, which will help evaluate the plan's cost-effectiveness and identify cost reduction opportunities.

In the Buildings sector, the simulation proposes several deep retrofits for public buildings and subsidized insulation programs. These actions are projected to drastically reduce carbon emissions, improve building maintenance cost efficiency, and increase property values. However, it must be noted that the feasibility of retrofitting a large number of buildings should be investigated further to ensure there's no overreach in the implementation.

The Energy sector plan focuses on the deployment of utility-scale solar installations, offshore wind integration, and district heating networks. These strategies promise significant carbon emission reduction and are derived from the latest IPCC and IEA reports. In Mobility, the proposal includes the electrification of the bus fleet and an expansion of cycle lanes. These strategies not only contribute to carbon reduction but also improve urban temperature mitigation and citizen satisfaction.

The Circular Economy sector strategy highlights the importance of city-wide waste reuse incentives and low-carbon material substitution in construction. These actions are projected to have a significant impact on carbon emission reduction while improving citizen satisfaction. The simulation suggests an average Return on Investment (ROI) impacts across all sectors as follows: Maintenance Cost Reduction at 3.32%, Healthcare Cost Savings at 2.38%, Property Value Increase at 3.91%, Urban Temperature Mitigation at 0.17°C, and Citizen Satisfaction Score at 4.72.

This comprehensive plan, based on scientific evidence and ROI optimization, illustrates the potential for Buenos Aires to significantly reduce its carbon footprint, improve the quality of life for its citizens, and make a valuable contribution to global climate change mitigation efforts.

This simulation was produced using Gaia Protocol, an open simulation engine based on scientific evidence and ROI optimization.

• Deep retrofit for public buildings – 4,258 tCO₂ @ €12,999,674 (€3053/t)

• Subsidised insulation program – 7,115 tCO₂ @ €12,999,105 (€1827/t)

• Deep retrofit of public buildings – Optimized – 50,193 tCO₂ @ €12,999,987 (€259/t)

• Deep retrofit of public buildings – Heritage-Grade Model (€3000/t) – 4,194 tCO₂ @ €12,997,206 (€3099/t)

• Deep retrofit of public buildings – Optimized – 45,774 tCO₂ @ €12,999,816 (€284/t)

• Deep retrofit of public buildings – Historical Conservation Model (€3000/t) – 4,517 tCO₂ @ €12,999,926 (€2878/t)

• Private building retrofit – Optimized – 22,375 tCO₂ @ €12,999,875 (€581/t)

• Private building retrofit – Standard – 17,663 tCO₂ @ €12,999,968 (€736/t)

• Private building retrofit – Ambitious – 13,131 tCO₂ @ €12,999,690 (€990/t)

• Utility-scale solar installation – 32,432 tCO₂ @ €17,999,760 (€555/t)

• Offshore wind integration – 13,483 tCO₂ @ €17,999,805 (€1335/t)

• District heating network deployment – 69,767 tCO₂ @ €17,999,886 (€258/t)

• District heating network deployment – 53,892 tCO₂ @ €17,999,928 (€334/t)

• Electrify bus fleet – 36,585 tCO₂ @ €38,999,610 (€1066/t)

• Expand cycle lanes – 50,000 tCO₂ @ €21,050,000 (€421/t)

• Urban rail electrification and modal shift – 144,981 tCO₂ @ €38,999,889 (€269/t)

• City-wide waste reuse incentives – 31,982 tCO₂ @ €29,999,116 (€938/t)

• Low-carbon material substitution in construction – 160,427 tCO₂ @ €29,999,849 (€187/t)

The Circular Economy sector can contribute to this reduction by deploying 5 million tons of CO₂ through low-carbon material substitution in construction, a strategy that has its roots in the UNEP Resource Efficiency Pathways. However, while the cost per ton of CO₂ reduction is estimated at €220, the cost stands at an estimated €1.1 billion. Even so, the positive implications of this action are likely to outweigh the initial costs, with promising returns on investment particularly in terms of citizen satisfaction, maintenance cost reduction, and healthcare cost savings.

In the Buildings sector, an optimized deep retrofit of public buildings can lead to a CO₂ reduction of 3,432,502 tons. This action, guided by the IEA Retrofit Guidelines, may require an investment of approximately €823,800,480 but promises significant returns. The projected benefits include a 6% reduction in maintenance costs, 4% in healthcare cost savings, an 8% increase in property value, a reduction of 0.6°C in urban temperature, and an impressive hike in citizen satisfaction.

While these strategies show potential, it is important to proceed with caution. The simulation indicates a gradual decrease in annual CO₂ reduction from 2026 to 2050. This could imply that there may be more buildings retrofitted than is realistically feasible. Policymakers should consider this in their planning to avoid overreach.

Taking into account the anticipated average ROI impacts, such as 3.77% in maintenance cost reduction, 2.38% in healthcare cost savings, 4.4% in property value increase, and a significant improvement in citizen satisfaction, the proposed actions are well-aligned with the city's sustainability goals. Furthermore, the estimated 0.22°C reduction in urban temperature aligns with global targets set by climate science bodies like the IPCC, EU, and UN.

However, it is crucial to remember that these projections are based on a simulation and therefore should be seen as indicative rather than definitive. They provide a sound basis for further investigation and planning, but real-world implementation will need to be accompanied by rigorous monitoring and evaluation.

This simulation was produced using Gaia Protocol, an open simulation engine based on scientific evidence and ROI optimization.

• Low-carbon material substitution in construction – 5,000,000 tCO₂ @ €1,100,000,000 (€220/t)

In the Buildings sector, significant CO₂ reduction can be achieved through deep retrofitting of public buildings and a subsidized insulation program, with the former yielding the highest return on investment (ROI) in terms of maintenance cost reduction, healthcare cost savings, property value increase, urban temperature mitigation and citizen satisfaction. However, the simulation also includes several instances of retrofitting public buildings using different models, which could potentially exceed the number of feasible targets, warranting a careful evaluation.

The Energy sector offers promising strategies including utility-scale solar installation, offshore wind integration, and district heating network deployment, with the latter yielding the best results. The Mobility sector presents the electrification of the bus fleet, expansion of cycle lanes, and urban rail electrification as viable and impactful interventions.

The Circular Economy sector proposes city-wide waste reuse incentives and low-carbon material substitution in construction, with the latter offering the highest CO₂ reduction.

The simulation also projects an incremental annual decrease in CO₂ emissions, starting with 10,987 tons in 2021 and reaching 902 tons by 2050.

The estimated average ROI impacts are as follows: Maintenance Cost Reduction (3.32%), Healthcare Cost Savings (2.38%), Property Value Increase (3.91%), Urban Temperature Mitigation (0.17°C), and Citizen Satisfaction Score (4.72%).

Importantly, the simulation suggests that the selected interventions could help mitigate urban temperatures by an estimated 0.17°C, contributing to global efforts against climate change.

Close attention should be paid to ensuring the feasibility of the proposed actions, particularly in the Buildings sector, to ensure the most efficient use of the available budget.

In conclusion, the simulation offers an evidence-based, strategic roadmap for Buenos Aires to significantly reduce its CO₂ emissions, enhance the quality of life for its citizens, and contribute to global climate change mitigation efforts.

This simulation was produced using Gaia Protocol, an open simulation engine based on scientific evidence and ROI optimization.

• Deep retrofit for public buildings – 4,534 tCO₂ @ €12,998,978 (€2867/t)

• Subsidised insulation program – 7,226 tCO₂ @ €12,999,574 (€1799/t)

• Deep retrofit of public buildings – Optimized – 60,185 tCO₂ @ €12,999,960 (€216/t)

• Deep retrofit of public buildings – Heritage-Grade Model (€3000/t) – 4,517 tCO₂ @ €12,999,926 (€2878/t)

• Deep retrofit of public buildings – Optimized – 59,633 tCO₂ @ €12,999,994 (€218/t)

• Deep retrofit of public buildings – Historical Conservation Model (€3000/t) – 4,253 tCO₂ @ €12,997,168 (€3056/t)

• Private building retrofit – Optimized – 19,345 tCO₂ @ €12,999,840 (€672/t)

• Private building retrofit – Standard – 15,873 tCO₂ @ €12,999,987 (€819/t)

• Private building retrofit – Ambitious – 14,023 tCO₂ @ €12,999,321 (€927/t)

• Utility-scale solar installation – 27,734 tCO₂ @ €17,999,366 (€649/t)

• Offshore wind integration – 13,274 tCO₂ @ €17,999,544 (€1356/t)

• District heating network deployment – 71,713 tCO₂ @ €17,999,963 (€251/t)

• District heating network deployment – 47,244 tCO₂ @ €17,999,964 (€381/t)

• Electrify bus fleet – 34,883 tCO₂ @ €38,999,194 (€1118/t)

• Expand cycle lanes – 50,000 tCO₂ @ €20,600,000 (€412/t)

• Urban rail electrification and modal shift – 141,818 tCO₂ @ €38,999,950 (€275/t)

• City-wide waste reuse incentives – 43,227 tCO₂ @ €29,999,538 (€694/t)

• Low-carbon material substitution in construction – 166,666 tCO₂ @ €29,999,880 (€180/t)

This report includes one or more retrofit actions labeled as:

• “Heritage-Grade Model (€3000/t)”

• “Historical Conservation Model(€3000/t)”

These action types represent atypically high-cost retrofit scenarios, generally only appropriate for protected buildings or architecturally constrained heritage zones.

Gaia includes these profiles not as recommendations, but as part of its evolving knowledge base. These models emerged through repeated simulations across multiple cities, where retrofit assumptions far above international benchmarks were detected and flagged.

Gaia learns from pattern frequency — but does not endorse patterns that conflict with empirical data. By naming and isolating these edge-case models, Gaia enables transparent evaluation and prevents inflated assumptions from being applied indiscriminately.

As the platform matures, Gaia will continue refining these profiles using verified costs, city-specific constraints, and architectural typologies.