Overview

Toola is a decision-support tool designed for research infrastructures, large-scale laboratories, and energy-intensive facilities across the EU 27. It combines user-defined operational profiles with publicly available climate projections, national electricity mix data, and a curated energy asset reference database to produce transparent CO₂ and energy balance estimates.

The tool is intended for facility managers, sustainability officers, and strategic planners who need to evaluate the environmental and financial impact of different energy mix configurations under plausible future climate scenarios. All inputs are editable, all data sources are cited, and results are exportable.

Step-by-Step Process

Toola guides the user through a five-step workflow:

1. Step 1 — Project Context: The user selects a planning horizon (start / end year, max 2055), the facility country within the EU 27, a socio-economic scenario (SSP), and the exact facility coordinates via an interactive map. This triggers a server-side query that retrieves location-specific climate projections (Copernicus PECD 4.2) and the national electricity mix and carbon intensity (Ember 2025) for the selected country.
2. Step 2 — Operational Power Profile: The user defines the facility’s power demand across three operational levels: Level 1 (Safety) — critical systems, alarms, minimal ventilation; Level 2 (Essential) — cooling, servers, baseline laboratory operations; Level 3 (Full Ops) — peak research activity including lasers, accelerators, and full-power equipment. Both maximum load (kW) and annual consumption (kWh) are specified per level.
3. Step 3 — Energy Mix Configuration: The user configures individual energy sources — national grid connection, solar PV (FVE), wind, cogeneration (CHP), and optionally battery storage. Each source can have multiple instances with different asset types selected from the reference database. A “No Battery” option allows excluding storage entirely.
4. Step 4 — CO₂ Balance & Energy Mix: Toola displays the national energy mix breakdown, grid carbon intensity, key metrics (total demand, local generation, self-sufficiency percentage, CO₂ savings), an energy supply breakdown bar, and an operational CO₂ table. The table total is grid + CHP + diesel + HVAC fuel; solar/wind figures are avoided-grid credit only.
5. Step 5 — Results: The final dashboard presents three exportable tables: (a) Climate Development & Projected Impact — showing how climate variables evolve over the project horizon and their effect on energy output; (b) Carbon Overview — full lifecycle CO₂ per source (manufacturing, operation, disposal); (c) Investment Overview — indicative CAPEX and O&M (not full OPEX), area and mass. Price basis is shown under the table.

Climate Data

Data retrieval & interpolation

When the user selects coordinates and proceeds from Step 1, the application sends the latitude, longitude, and country code to a server-side API (AWS Lambda). The API maps coordinates to the nearest 0.25° PECD grid cell (climate data) and to the corresponding P2ON region (wind onshore data). Capacity factors for the selected SSP scenario are returned for available reference years (2025, 2030, 2035, 2045, 2055).

For project years falling between reference years, Toola applies linear interpolation:

If the target year falls outside the available range, the nearest boundary value is used (clamping, no extrapolation). The start year value serves as the operational baseline; the end year value is used for trend analysis.

Nearest-neighbour fallback

When the exact grid cell contains no data for one or more climate measures, Toola applies a nearest-neighbour fallback strategy, searching adjacent grid cells in expanding rings until data is found. The substitution is logged with the origin grid key and distance (number of grid steps). If no data is found within the search radius, the measure is marked as unavailable.

Electricity Mix & Carbon Intensity

Country-level data is fetched in real time via the Toola back-end (AWS Lambda) which queries Ember-derived datasets. The API returns both the grid carbon intensity (gCO₂/kWh) and the fuel-type percentage breakdown for the selected country. If the API is unavailable, Toola falls back to static approximations embedded in the client code; these are clearly marked. Both the carbon intensity and energy mix values are sourced from Ember (2025) and may be updated as new data becomes available.

Energy Asset Reference Database

Each energy asset type in the Toola database includes the following standardised fields: reference name, category, electrical output (kW), efficiency (%), CAPEX (€/kW), O&M cost (€/kW/yr), CO₂ from manufacturing (kg/kW), CO₂ from operation (kg/kW/yr), CO₂ from disposal (kg/kW), footprint area (m²/kW), and mass (kg/kW). Sources per asset category:

Price basis

CAPEX and O&M in the Investment Overview are indicative EUR, without VAT, grid connection or financing, and are not indexed to the project start year. Solar PV and onshore wind follow IRENA installed-cost ranges for 2023 (report published 2024). Other assets, including HVAC plant, are ballpark values from this register. Toola reports O&M, not full OPEX — electricity purchase, fuel and staff are excluded. Lifetime O&M is annual O&M × project duration, undiscounted. Battery unit costs are per kWh; generation and diesel per kW or kWp.

Calculation Methodology

Energy output formulas

• Solar PV output:
  Annual output (MWh) = kWp × SPV × 8,760 h/yr ÷ 1,000
  Where SPV is the PV capacity factor (dimensionless 0–1) from PECD 4.2 at the project location. It is not solar irradiance (W/m²). PECD reports the same value as MW/MWp. Panel tilt: 10°; orientation: 50% south, 25% east, 25% west.
• Wind output:
  Annual output (MWh) = kWp × WON × 8,760 h/yr ÷ 1,000
  Where WON is the onshore wind capacity factor (dimensionless 0–1) from the P2ON regional aggregation. It is not surface wind speed (m/s). PECD reports the same value as MW/MW. The turbine Cp in the asset database is not applied as a second multiplier.
• CHP output:
  Annual output (MWh) = kWp × 4,000 h/yr ÷ 1,000
  Standard assumption of 4,000 full-load hours per year for gas-fired cogeneration units.
• Grid import:
  Grid import (MWh) = max(0, Total demand − Local generation)
  Where total demand is the highest operational level consumption (Level 3) converted to MWh, and local generation is the sum of Solar PV + Wind + CHP annual outputs.

CO₂ balance

Sign convention: positive = emission; negative = avoided-grid credit (informational, not added to the operational total).

• Grid CO₂: Grid import (MWh) × grid intensity (gCO₂/kWh) ÷ 1,000 = tonnes CO₂/yr. Local solar, wind and CHP already reduce this import.
• Solar / Wind credit: −credited MWh × grid intensity ÷ 1,000. Only MWh that displace import are credited; surplus is not exported. Shown in the table, not added to the operational total.
• CHP CO₂: kWp × asset operational CO₂ (kg/kW/yr) ÷ 1,000
• Diesel CO₂: kW × backup run-hours × emission factor (kgCO₂/kWh) ÷ 1,000
• HVAC fuel CO₂: direct combustion / district-heat emissions from accepted HVAC packages. HVAC electricity is part of total demand and therefore of Grid CO₂, not a second HVAC line.
• Operational CO₂ (table total): Grid + CHP + diesel + HVAC fuel
• Baseline CO₂: Total demand (MWh) × grid intensity ÷ 1,000 (100% grid scenario)
• CO₂ savings: Baseline CO₂ − Operational CO₂

Self-sufficiency

Battery backup duration

For each operational level, batteries that cover that level contribute their effective energy capacity (rated kWh × round-trip efficiency). The backup duration is:

Battery Advisor

The Step 2 backup proposal sizes a battery and/or diesel solution from the selected operating levels, load and required autonomy. The Step 3 Battery Advisor evaluates manually selected use-cases and ranks compatible battery chemistries. It does not replace grid-code studies, protection coordination, vendor engineering or safety design.

• Step 2 proposal: uses the current load, autonomy and preference inputs when applied to Step 3.
• Use-cases: calculate required power and usable energy, then rank battery chemistries.
• RTE: Step 3 stores rated capacity; effective backup capacity is rated kWh multiplied by RTE.

Lifecycle Carbon Assessment

The Results step (Step 5) presents a full lifecycle CO₂ assessment for each configured energy asset, broken down into three phases:

• Manufacturing CO₂: Embodied carbon from raw material extraction, component fabrication, and assembly. Expressed as kg CO₂/kW (or kg CO₂/kWh for batteries). Total = capacity × manufacturing factor.
• Operational CO₂: Annual direct emissions during operation (e.g. fuel combustion in CHP units). Renewables and batteries have zero or near-zero operational CO₂. Lifecycle total = annual operational CO₂ × project duration (years).
• Disposal CO₂: End-of-life emissions from decommissioning, recycling, or landfill. Total = capacity × disposal factor.

The CO₂ payback period indicates how many years of operational CO₂ savings are required to offset the total manufacturing embodied carbon:

Socio-Economic Scenarios (SSP)

Climate socio-economic scenarios (often called SSPs – Shared Socioeconomic Pathways) are not predictions. They are structured “what-if” storylines that help scientists and policymakers explore how the world could develop over this century — in population, economy, technology, energy use, and environmental policy — and what that would mean for greenhouse-gas emissions and climate impacts.

Toola uses SSP-labelled climate projections from CMIP6, downscaled in the Copernicus PECD 4.2 dataset. The selected SSP affects only the climate capacity factors (SPV, WON, temperature, wind speed, humidity); the national electricity mix and carbon intensity are based on current observed data (Ember 2025) and do not vary by SSP.

SSP2-4.5 — your “optimistic” case

What the world looks like: SSP2 is often summarised as a “middle-of-the-road” future: society and the economy keep developing in broadly familiar ways, without dramatic shifts toward either strong sustainability or strong fragmentation. The “-4.5” part means global forcing stabilises around 4.5 W/m² by 2100, which typically implies some climate policies and gradual decarbonisation, but not the fastest possible transition.

What it means for warming: The IPCC AR6 Synthesis Report gives a best estimate of about 2.7°C global warming by 2081–2100 (relative to 1850–1900), with a very likely range of 2.1–3.5°C for SSP2-4.5.

SSP3-7.0 — your “current” case

What the world looks like: SSP3 is often described as “regional rivalry”: more nationalism, weaker international cooperation, slower technology diffusion, and more difficulty coordinating climate action. The “-7.0” indicates 7.0 W/m² forcing by 2100, representing a high-emissions / high-warming pathway.

Why it can be used as a “current-trajectory proxy”: The IPCC AR6 reports that policies implemented by the end of 2020, without strengthening, are associated with around 3.2°C warming by 2100 (5–95% range 2.2–3.5°C). That sits above SSP2-4.5’s best estimate and below SSP3-7.0’s best estimate — which is why people sometimes use high scenarios to stress-test what happens if progress remains uneven and insufficient.

What it means for warming: IPCC AR6 gives a best estimate of about 3.6°C by 2081–2100 for SSP3-7.0, with a very likely range of 2.8–4.6°C.

SSP5-8.5 — your “pessimistic” case

What the world looks like: SSP5 is known as “fossil-fuelled development”: rapid economic growth and energy demand, with heavy reliance on fossil fuels and very high emissions unless strong mitigation is added (which SSP5-8.5 does not). The “-8.5” means 8.5 W/m² forcing by 2100, the very high end of ScenarioMIP’s core scenarios.

What it means for warming: IPCC AR6 gives a best estimate of about 4.4°C warming by 2081–2100 for SSP5-8.5, with a very likely range of 3.3–5.7°C.

Data Pipeline & Architecture

Toola uses a serverless back-end hosted on AWS. When the user advances from Step 1, a POST request is sent to an API Gateway endpoint backed by an AWS Lambda function. The Lambda performs:

1. Mapping the user’s coordinates to the nearest 0.25° PECD grid cell and P2ON wind region.
2. Querying a DynamoDB table containing pre-processed Copernicus PECD 4.2 data for the matched grid cell and region, filtered by the relevant SSP scenario codes (SP245, SP370, SP585).
3. Applying the nearest-neighbour fallback if the primary grid cell has missing measures.
4. Querying Ember-derived tables for the national electricity mix and carbon intensity for the selected country.
5. Returning a unified JSON response containing climate data, P2ON data, electricity maps, and fallback diagnostics.

All calculations (energy output, CO₂ balance, lifecycle assessment, investment metrics) are performed client-side in the browser using the calculations.js engine. No user data is stored on the server.

Limitations & Disclaimer

• Static fallback energy mix values are approximate and may lag behind the latest Ember publication by up to one year.
• Climate capacity factors are median-ensemble estimates; actual year-to-year variability may differ. The raw PECD data includes q10/q90 quantile ranges which are not currently exposed in the UI.
• Both the electricity mix and carbon intensity are based on current observed data (Ember 2025) and are not projected into the future. Actual grid decarbonisation trajectories will affect real-world CO₂ outcomes.
• Battery degradation over time, calendar ageing, depth-of-discharge effects, curtailment, demand-response scheduling, and real-time electricity market dynamics are not modelled.
• CHP output assumes a fixed 4,000 full-load hours per year regardless of heat demand profile or seasonal variation.
• Solar PV output uses a fixed panel tilt (10°) and orientation split; tracking systems, shading effects, inverter losses, and soiling are not individually modelled.
• Wind output does not account for wake effects, turbine-specific power curves, or hub-height adjustments beyond the PECD regional aggregation.
• Financial metrics (CAPEX, O&M) do not include financing costs, inflation, discount rates, incentives, feed-in tariffs, or electricity price projections.
• Results are indicative estimates intended for strategic planning and feasibility screening, not as a substitute for detailed engineering studies or bankable energy audits.

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References

Glossary of Key Terms