"AI estimates, Blockchain tracks, Finance connects."
CarbonCast is a CBAM (Carbon Border Adjustment Mechanism) transition risk analysis platform developed for the Hana Financial Group Youth Talent Development Project. It helps Korean export companies and financial institutions quantify, verify, and simulate the cost impact of the EU's carbon border tax.
The EU Carbon Border Adjustment Mechanism (EU Regulation 2023/956) imposes carbon costs on imports of steel, cement, aluminum, fertilizers, hydrogen, and electricity starting January 2026. The phase-in schedule gradually increases from 2.5% (2026) to 100% (2034).
The core problem: 87% of Korean SME exporters don't know how to calculate their emissions (KIEP survey). Without verified data, the EU applies default values with a +30% markup — meaning companies pay 2x or more in carbon costs compared to their actual emissions.
CarbonCast consists of three layers:
┌─────────────────────────────────────────────────────┐
│ CarbonCast │
│ │
│ ┌───────────────────────────────────────────────┐ │
│ │ AI Engine │ │
│ │ Emission estimation (Conformal Prediction) │ │
│ │ Industry impact analysis (I-O + GNN) │ │
│ │ Compliance Agent (LLM + RAG) │ │
│ └───────────────────────────────────────────────┘ │
│ ↕ │
│ ┌───────────────────────────────────────────────┐ │
│ │ Trust Layer │ │
│ │ Blockchain audit trail (SHA-256) │ │
│ │ Digital Product Passport (DPP) │ │
│ │ Federated Learning │ │
│ └───────────────────────────────────────────────┘ │
│ ↕ │
│ ┌───────────────────────────────────────────────┐ │
│ │ Financial Layer │ │
│ │ READIT OCR integration │ │
│ │ PCAF portfolio carbon analysis │ │
│ │ Credit assessment + ESG finance │ │
│ └───────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────┘
Pre-screens emission data reliability before EU accredited verifier review. Uses Isolation Forest + rule-based checks on emission factors, energy intensity, and production volumes. Outputs a 0-100 quality score.
- Training data: K-ETS registry (~800 facilities, data.go.kr)
- Scoring: z-score based weighted sum across 4 criteria (emission factor range, energy range, energy-emission consistency, production scale)
Records quality-verified emission data on blockchain for tamper-proof audit trails. Stores SHA-256 hashes on-chain with metadata; full data remains off-chain.
- Prototype: Ethereum Sepolia testnet
- Production target: Hyperledger Fabric (permissioned)
Calculates year-by-year CBAM cost paths (2026-2034) under 4 NGFS climate scenarios.
CBAM Cost = Export Volume × [Emission Factor − Benchmark × (1 − Phase-in Rate)]
× EUA Price × Exchange Rate
- Phase-in rates: 2.5% (2026) → 100% (2034) per EU Regulation 2023/956, Annex IV
- Scenarios: Net Zero 2050, Below 2°C, Delayed Transition, Current Policies (NGFS Phase V)
├── README.md
├── index.html # Interactive demo (standalone HTML)
├── CarbonCast_app.html # Full demo application
├── CarbonCast_v2.html # Demo v2
├── src/
│ ├── 01_fetch_data.py # EU ETS + market data collection
│ ├── 02_model.py # LightGBM quantile price model
│ ├── 03_cbam_engine.py # CBAM cost calculation engine
│ ├── 04_synthetic_data.py# Synthetic K-ETS data generation
│ ├── 05_emission_model.py# Emission factor prediction model
│ ├── app.py # Streamlit dashboard v1
│ └── app_v2.py # Streamlit dashboard v2
├── data/
│ ├── cbam_scenarios.json # NGFS scenario parameters
│ ├── cbam_analysis.csv # CBAM cost analysis results
│ ├── predictions.csv # Model predictions
│ ├── model_results.json # Market model metrics
│ └── emission_model_results.json
└── docs/
├── CarbonCast_Architecture.md
└── [최종] CarbonCast 통합 제안서.md
| Metric | Value |
|---|---|
| Emission model (with energy data) | R² = 0.778, MAPE 8.0% |
| EU ETS price model (LightGBM) | MAE 3.15 EUR, MAPE 4.4% |
| Steel: EU default vs actual savings | ~€154/ton (~22억 won per 10,000t) |
| Conformal prediction coverage | ≥90% (distribution-free guarantee) |
| Year | 2026 | 2027 | 2028 | 2029 | 2030 | 2031 | 2032 | 2033 | 2034 |
|---|---|---|---|---|---|---|---|---|---|
| Rate | 2.5% | 5% | 10% | 22.5% | 48.5% | 61% | 73.5% | 86% | 100% |
Source: EU Regulation 2023/956, Annex IV
- ML/AI: LightGBM, XGBoost, MAPIE (Conformal Prediction), Isolation Forest
- Visualization: Streamlit, Plotly, HTML/JS Canvas
- Blockchain: Web Crypto API (SHA-256), Ethereum Sepolia (prototype)
- Data Sources: K-ETS registry, NGFS Phase V, EU ETS (ICE), DART Open API
| Data | Source | Access |
|---|---|---|
| K-ETS facility data | data.go.kr/15053947 | Public API |
| NGFS scenarios | ngfs.net | Public |
| EU ETS prices | ICE Endex / Yahoo Finance | Free (delayed) |
| Industry I-O table | Bank of Korea (ecos.bok.or.kr) | Public |
| Company financials | DART Open API | Public |
| CBAM HS code mapping | Korea Customs Service | Public (2026.02) |
This project was developed for the Hana Youth Financial Talent Development Project (하나 청년 금융인재 양성 프로젝트), a competition organized by Hana Financial Group. The platform is part of the broader ESG TradeGuard system, which provides end-to-end trade finance compliance checking including OCR document parsing, regulation matching, carbon verification, and satellite environmental monitoring.
- EU Regulation 2023/956 (CBAM)
- EU IR 2025/2621 (Default values and benchmarks)
- NGFS Phase V Scenarios (2024.11)
- ESPR 2024/1781 (Digital Product Passport)
- Angelopoulos & Bates (2021) "Conformal Prediction" arXiv:2107.07511
- Stanford AAAI 2025: "Learning Production Functions for Supply Chains with GNNs"
This project is for educational and competition purposes.