Barcelona

• Original Plan (as published) reported €0 allocated per tonne, with no emissions reduction target, making results unverifiable.

• Gaia-Enriched Plan filled in data gaps, simulating a 15.52% reduction (665,000 tCO₂e) by 2030 at a highly cost-efficient €150.38 per tonne, well within budget.

• Sector allocation of CO₂ savings: o Mobility: 66% o Urban Green: 17% o Buildings: 5% o Energy: 12%

• Budget Optimization Flags: While total savings were high, full implementation would exceed budget by ~€135 million unless adjustments were made.

• Original plan lacked key metrics (targets, budgets, KPIs), making internal accountability difficult.

• Implementation feasibility for retrofits and transit upgrades may be optimistic given logistical constraints.

• Sector overconcentration on mobility (75% of budget) risks imbalanced climate impact distribution.

• Add explicit CO₂ targets and cost breakdowns to all actions.

• Diversify investment across sectors, including building retrofits and nature-based solutions.

• Deploy robust monitoring frameworks to ensure adaptive, measurable implementation.

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.

• Absence of specific greenhouse gas reduction targets linked to the planned actions.

• Lack of detailed budget allocation and cost estimates per action.

• No clear metrics or indicators for measuring the effectiveness and impact of each action.

• Incorporate specific, measurable emissions reduction targets aligned with the Paris Agreement goals to ensure accountability and effectiveness.

• Detail financial allocations and cost-effectiveness analyses for each action to optimize resource use and attract potential investors.

• Establish clear performance indicators and a monitoring framework to assess progress and make necessary adjustments in real-time.

- IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change

- WHO, 2018: Health in the green economy: health co-benefits of climate change mitigation - Transport sector

Apologies, but it's challenging to provide a comprehensive summary with the given information. There are missing critical details such as the targeted CO2 savings, the budget for the plan, and the target reduction in emissions by 2030. In their absence, I am unable to evaluate the full strengths, weaknesses, and potential cost-saving opportunities within the plan titled "Mesura de Govern per l’Acció Climàtica 2023–2030" for the city of Barcelona.

What is notable though, is that the perceived cost per tonne of carbon dioxide saved is effectively zero. This could potentially be a significant strength if it is accurate, as many climate plans entail significant costs but struggle to achieve meaningful reductions in emissions. However, without detailed information surrounding this figure, it is necessary to approach with caution as it may signal a lack of thorough planning or potentially unrealistic forecasts in the plan.

Given the incomplete information, making sector-specific recommendations is unfeasible. However, I suggest providing a well-defined budget, outlining specific CO2 reduction goals, and more importantly, break down these goals by sector. Once these details are provided, the plan would be easier to assess for efficiency, cost-effectiveness, and room for improvements. It would be wise to conduct a thorough impact assessment for every climate change intervention considered, as well as study other cities with similar demographic and social profiles to Barcelona to see what has worked effectively for them.

Lack of detailed implementation strategies for each sector.

• Insufficient emphasis on monitoring and evaluation frameworks to track progress.

• Potential underestimation of the budget needed for the mobility sector given the high costs associated with electrifying transport.

• Develop a detailed implementation roadmap for each action, specifying timelines, responsible parties, and intermediate milestones.

• Establish a robust monitoring and evaluation framework to regularly assess progress against targets and make adjustments as needed.

• Reassess the budget allocation for the mobility sector to ensure it adequately covers the costs of transitioning to electric vehicles, including infrastructure development.

- IPCC AR6

- WHO Urban Health Initiative

- EU Fit for 55 package

To begin with, it is critical to note that the Barcelona climate plan currently lacks several crucial data elements. The omission of CO2 savings, budgetary allocations, and target reductions does not facilitate a comprehensive assessment of the plan's merits and areas of improvement. However, a notable strength can be found in the reported cost per tonne of CO2 reduction, which is cited as being roughly €0. Assuming this is accurate, Barcelona’s plan is highly efficient when it comes to offsetting or reducing CO2 emissions.

Conversely, the dearth of details in the submitted climate plan points towards significant inadequacies. The N/A entries for the core aspects such as CO2 savings, budget, and target reduction highlight the primary inefficiency: the absence of clearly defined goals. Without these data, it is impossible to assess the plan’s potential efficacy or cost-effectiveness. The inability to specify which sectors the initiative would impact is another significant weakness that would likely lead to untargeted and ineffective policies.

In light of these issues, I would highly recommend that the city of Barcelona thoroughly re-evaluate its climate strategy. To promote cost-reduction and better sector focus, it is essential to develop clear, measurable goals for CO2 reduction and allocate a specific budget to achieve them. In addition, identifying the sectors that could contribute the most to CO2 reduction would allow for the deployment of targeted interventions, significantly improving the efficiency and efficacy of the climate plan. While the reported cost per tonne is an encouraging sign, the climate plan's effectiveness will largely hinge on the careful identification and implementation of these crucial details.

The City of Barcelona, with an allocated climate budget of €100,000,000, can undertake a series of actions across various sectors to address climate change and enhance the quality of life for its residents. The simulation results show a clear distribution of funds across sectors including buildings, energy, mobility, and urban green.

In the building sector, an optimised deep retrofit of public buildings stands out as a highly efficient action, reducing CO₂ emissions by up to 9803 tons per action, while also contributing to healthcare cost savings, property value increase, urban temperature mitigation, and improved citizen satisfaction. This is closely aligned with the International Energy Agency's (IEA) retrofit guidelines and the IPCC's reports on building emissions.

The energy sector sees significant benefits from actions like district heating network deployment and utility-scale solar installation, which align with IEA's urban energy systems and photovoltaic outlook strategies, respectively. The sector's actions also provide a robust return on investment (ROI) in terms of maintenance cost reduction, healthcare cost savings, and increased citizen satisfaction.

Mobility initiatives, such as electrifying the bus fleet and expanding cycle lanes, are expected to result in substantial emissions reduction. However, it's important to note that the urban rail electrification and modal shift action, despite its impressive CO₂ reduction potential, may overreach given its high cost and the city's existing infrastructure. These actions are supported by the World Health Organization's (WHO) urban transport health study and the European Union's cycling strategy.

The urban green sector also shows promise, with urban forestation expected to reduce CO₂ emissions by 100,000 tons. While the delay in seeing results is three years, the long-term benefits in terms of urban temperature mitigation and citizen satisfaction are noteworthy. This aligns with the IPCC's sixth assessment report and the WHO's study on urban heat.

The estimated average ROI impacts are as follows: Maintenance Cost Reduction (3.2%), Healthcare Cost Savings (2.46%), Property Value Increase (2.83%), Urban Temperature Mitigation (0.09°C), and Citizen Satisfaction Score (5.29).

This comprehensive approach to climate action, guided by evidence and optimized for ROI, can help Barcelona make significant strides in climate mitigation and adaptation while improving the quality of life for its residents.

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

• Deep retrofit for public buildings – 651 tCO₂ @ €1,999,872 (€3072/t)

• Subsidised insulation program – 1,194 tCO₂ @ €1,998,756 (€1674/t)

• Deep retrofit of public buildings – Optimized – 7,843 tCO₂ @ €1,999,965 (€255/t)

• Deep retrofit of public buildings – Heritage-Grade Model (€3000/t) – 707 tCO₂ @ €1,997,982 (€2826/t)

• Deep retrofit of public buildings – Optimized – 9,803 tCO₂ @ €1,999,812 (€204/t)

• Deep retrofit of public buildings – Historical Conservation Model (€3000/t) – 655 tCO₂ @ €1,997,095 (€3049/t)

• Private building retrofit – Optimized – 3,921 tCO₂ @ €1,999,710 (€510/t)

• Private building retrofit – Standard – 2,547 tCO₂ @ €1,999,395 (€785/t)

• Private building retrofit – Ambitious – 2,030 tCO₂ @ €1,999,550 (€985/t)

• Utility-scale solar installation – 11,922 tCO₂ @ €7,999,662 (€671/t)

• Offshore wind integration – 5,457 tCO₂ @ €7,999,962 (€1466/t)

• District heating network deployment – 27,210 tCO₂ @ €7,999,740 (€294/t)

• District heating network deployment – 25,723 tCO₂ @ €7,999,853 (€311/t)

• Electrify bus fleet – 84,364 tCO₂ @ €74,999,596 (€889/t)

• Expand cycle lanes – 50,000 tCO₂ @ €23,550,000 (€471/t)

• Urban rail electrification and modal shift – 252,525 tCO₂ @ €74,999,925 (€297/t)

Based on the simulation results, the city of Barcelona has the potential to reduce CO₂ emissions by 0.7Mt through urban forestation and the deep retrofitting of public buildings. Importantly, these efforts also promise significant return on investment (ROI) impacts across various sectors.

The urban forestation strategy is projected to sequester 100,000 tons of CO₂ at a cost of €12,000,000. This action not only contributes to lower urban temperatures by an estimated 0.4°C, as per the IPCC AR6 and WHO Urban Heat 2021 report, but also generates healthcare cost savings of 0.3% and a 2.5-point increase in citizen satisfaction score.

Furthermore, the deep retrofit of public buildings – optimized, is expected to reduce CO₂ emissions by 565,000 tons at a cost of €135,600,000. This action, guided by the IEA Retrofit Guidelines, offers an array of benefits. We anticipate a reduction in maintenance costs by 6%, healthcare cost savings of 4%, an increase in property values by 8%, a further reduction in urban temperatures by 0.6°C, and a significant boost in citizen satisfaction by 7 points.

However, the potential for overreach should be addressed. The feasibility of retrofitting a large number of public buildings within the stipulated time frame needs to be thoroughly evaluated against available resources, logistics, and potential public disruptions.

The ROI summary reveals substantial positive impacts in maintenance cost reduction, healthcare cost savings, property value increase, urban temperature mitigation, and citizen satisfaction. These benefits underscore the synergistic advantages of addressing climate change through multi-sectoral interventions.

The annual curve of CO₂ reduction demonstrates a consistent decrease in emissions from 2025 through 2050, aligning with the global climate goals set by the UN. However, the real-world implementation of these strategies requires an adaptive management approach to accommodate uncertainties and emerging challenges.

In conclusion, Barcelona's climate strategy, as simulated, offers both environmental and socio-economic benefits. It aligns with global guidelines and research from renowned institutions such as the IPCC, IEA, and WHO. However, careful planning and assessment are necessary to ensure feasibility and community acceptance.

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

The city of Barcelona can significantly lower its CO2 emissions and achieve a multitude of other benefits by investing €100,000,000 into various climate strategies. The simulation reveals that the city can aim for a CO2 reduction target of 0.7Mt.

The majority of the budget will be allocated towards Mobility initiatives. The electrification of the bus fleet and urban rail, along with the expansion of cycle lanes, will cost approximately €99,500,000, contributing to approximately 420,370 tons of CO2 reduction. It is important to note the high cost per ton of these actions, with the bus fleet electrification being €1,018 per ton. However, these initiatives will lead to significant healthcare cost savings and an increase in citizen satisfaction.

A significant portion of the remaining budget will be invested in the Energy sector with the deployment of a district heating network and utility-scale solar installations. According to data from the International Energy Agency (IEA) and Intergovernmental Panel on Climate Change (IPCC), this will result in approximately 76,109 tons of CO2 reduction at a lower cost per ton than Mobility actions.

Investments in the Buildings sector, such as deep retrofits for public buildings and private building retrofits, will result in approximately 31,925 tons of CO2 reduction, with actions having various costs per ton. These retrofits not only aid in the reduction of CO2 emissions but also increase property value and citizen satisfaction, while decreasing maintenance and healthcare costs.

Lastly, Urban Green initiatives will contribute to approximately 100,000 tons of CO2 reduction. The urban forestation project is the most cost-effective action, with the cost per ton being only €111, according to IPCC and World Health Organization (WHO) data.

The simulation indicates that these actions will lead to an average reduction in maintenance costs by 3.2%, healthcare cost savings of 2.46%, a property value increase of 2.83%, and an urban temperature mitigation of 0.08°C. Furthermore, these initiatives are estimated to increase the Citizen Satisfaction Score by 5.29 points.

However, it is crucial to consider the feasibility of retrofitting a large number of buildings within a short period. This requires careful planning and effective implementation strategies.

This simulation was produced using Gaia Protocol, an open simulation engine based on scientific evidence and ROI optimization, ensuring that the actions proposed are grounded in real-world science and are economically viable.

• Deep retrofit for public buildings – 679 tCO₂ @ €1,998,976 (€2944/t)

• Subsidised insulation program – 1,098 tCO₂ @ €1,999,458 (€1821/t)

• Deep retrofit of public buildings – Optimized – 7,633 tCO₂ @ €1,999,846 (€262/t)

• Deep retrofit of public buildings – Heritage-Grade Model (€3000/t) – 645 tCO₂ @ €1,997,565 (€3097/t)

• Deep retrofit of public buildings – Optimized – 9,615 tCO₂ @ €1,999,920 (€208/t)

• Deep retrofit of public buildings – Historical Conservation Model (€3000/t) – 649 tCO₂ @ €1,999,569 (€3081/t)

• Private building retrofit – Optimized – 2,967 tCO₂ @ €1,999,758 (€674/t)

• Private building retrofit – Standard – 2,395 tCO₂ @ €1,999,825 (€835/t)

• Private building retrofit – Ambitious – 2,173 tCO₂ @ €1,999,160 (€920/t)

• Utility-scale solar installation – 13,468 tCO₂ @ €7,999,992 (€594/t)

• Offshore wind integration – 7,174 tCO₂ @ €7,999,010 (€1115/t)

• District heating network deployment – 20,460 tCO₂ @ €7,999,860 (€391/t)

• District heating network deployment – 31,007 tCO₂ @ €7,999,806 (€258/t)

• Electrify bus fleet – 73,673 tCO₂ @ €74,999,114 (€1018/t)

• Expand cycle lanes – 50,000 tCO₂ @ €24,550,000 (€491/t)

• Urban rail electrification and modal shift – 290,697 tCO₂ @ €74,999,826 (€258/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.