Methodology

Evidence & Source Provenance

All calculation parameters in this tool are derived from published primary sources. No figures are synthesised without attribution.

Module 1 · Logistics Diversion

Shipping Emissions Sources

Emission factors, fuel consumption profiles, and regulatory frameworks used to calculate the CO₂e cost of route diversions.

IMO Fourth GHG Study 2020

The primary source for vessel fuel consumption profiles, emission factors, and baseline shipping emissions by vessel category. Used for all vessel_profiles in this tool.

primaryhttps://www.imo.org/en/OurWork/Environment/Pages/Fourth-IMO-GHG-Study-2020.aspx

IMO MEPC.1/Circ.684 — Emission Conversion Factors

Official IMO emission conversion factors by fuel type (HFO: 3.114 tCO₂/t, MDO: 3.206, LNG: 2.750). Used in EU MRV compliance and this calculator.

primaryhttps://www.imo.org/en/OurWork/Environment/Pages/EmissionFactors.aspx

EU MRV Regulation 2015/757

Monitoring, reporting and verification framework for CO₂ from maritime transport. The regulatory basis for emission factor selection applied in this tool.

primaryhttps://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32015R0757

GHG Protocol: Scope 3 — Category 4/9 (Upstream/Downstream Transport)

Methodological basis for attributing shipping emissions to corporate Scope 3 accounts. Route diversions increase Category 4/9 emissions for importers and exporters.

primaryhttps://ghgprotocol.org/scope-3-technical-calculation-guidance

UCL Energy Institute: Red Sea Shipping Crisis

Analysis of the 2023–2024 Houthi disruption and its effect on vessel route diversions, fuel consumption, and CO₂ emissions from global container shipping.

analysishttps://www.ucl.ac.uk/energy/

Module 3 · Conflict Reconstruction

Conflict Reconstruction Sources

Satellite damage assessments, post-war needs surveys, and cement-sector emission factor references used to estimate committed reconstruction carbon debt.

UNOSAT Building Damage Assessment — Gaza Governorate (23 Sep 2025)

Satellite-derived damage assessment of 41,221 structures in the 45 km² Gaza Governorate AOI. Primary data source for Gaza City / Gaza Governorate floor-area estimates in Module 3.

primaryhttps://unosat.org/products/4205

World Bank Ukraine Rapid Damage and Needs Assessment — RDNA3 (Feb 2024)

Damage and reconstruction needs assessment covering 2022-02-24 to 2023-12-31. Used as the basis for Ukraine floor-area proxy in Module 3. Confidence: low — 135M m² is an internal proxy derived from RDNA3 housing/infrastructure damage categories, not a direct RDNA3 floor-area figure.

primaryhttps://openknowledge.worldbank.org/entities/publication/817e607e-2933-4b5c-a716-8af453ca1ed0

IEA Cement Sector Report 2023

Industry-wide cement sector carbon intensity data. Central emission factor ~0.60 tCO₂/t at global average clinker ratio (~0.72). The 0.83 tCO₂/t proxy reflects a high-clinker upper bound, not the IEA central value. Reconstruction factors in Module 3 and 4 are calibrated to the 0.30 tCO₂e/m² baseline.

primaryhttps://www.iea.org/reports/cement

Parting the Fog of War: Quantifying Military GHG Emissions

Peer-reviewed framework for estimating conflict-associated carbon costs including operational emissions, supply chain, and post-conflict reconstruction demand. Methodological grounding for Module 3.

researchhttps://www.tandfonline.com/doi/full/10.1080/09636412.2023.2155196

Confidence note. Conflict Reconstruction estimates for Ukraine and Gaza are low-to-medium confidence proxies. Floor-area figures are internal derivations from damage assessment categories, not directly reported floor-area totals. They are intended as order-of-magnitude estimates for methodology demonstration, not official emissions inventories.

Module 4 · Disaster Carbon Liability

Disaster Reconstruction Sources

Official damage statistics, post-disaster reconstruction assessments, and hazard-specific material demand references used in Module 4.

Cabinet Office Japan / Ishikawa Prefecture — Noto Earthquake 2024 Damage Report

Official damage statistics from the January 2024 Noto Peninsula earthquake. Source for building destruction counts used in the Noto 2024 floor-area proxy (~24,000 completely or severely destroyed buildings). Confidence: low — floor area is an internal proxy.

primaryhttps://www.bousai.go.jp/updates/r6_noto_earthquake/index.html

National Police Agency Japan — Great East Japan Earthquake Damage Report

Official NPA damage statistics for the March 2011 earthquake and tsunami: 121,782 completely destroyed buildings. Used as the basis for GEJE 2011 floor-area proxy in Module 4. Confidence: low.

primaryhttps://www.npa.go.jp/news/other/earthquake2011/index.html

World Bank — The Great East Japan Earthquake: Learning from Megadisasters (2012)

World Bank assessment of GEJE reconstruction costs, scope, and methodology. Cross-reference for floor-area and material demand estimates used in Module 4.

primaryhttps://openknowledge.worldbank.org/handle/10986/26981

GFDRR GRADE — Global Rapid Damage Estimation

World Bank / GFDRR methodology for post-disaster building damage assessment and reconstruction cost estimation. Methodological backbone for Module 4 hazard-specific reconstruction coefficients.

primaryhttps://www.gfdrr.org/en/grade

Low-confidence proxy disclaimer. Disaster Reconstruction estimates carbon liabilities from post-disaster rebuilding using damaged floor-area proxies and hazard-specific reconstruction factors. The initial Japanese scenarios (Noto 2024, GEJE 2011) are low-confidence proxies intended for methodology demonstration, not official emissions inventories. Actual committed emissions depend on rebuild scope, material sourcing, and construction timeline.

Research Grounding

Related Research

Academic and analytical work grounding the methodological design of this tool.

Kokubu (2026) — Limited Marginal Benefit of Reasoning-Heavy LLM Deployment in ESG Narrative Scoring

Empirical study scoring ESG narratives of 10 Japanese listed firms across 3 axes using 4-model consensus. Provides methodological grounding for machine-readable carbon accounting as applied in this tool's evidence provenance design.

researchhttps://arxiv.org/abs/2606.13693

Kokubu (2026) — Can Sustainability Disclosure Be Read by Machines? [Data Note 001]

Schema-enforcement audit of EDINET iXBRL sustainability disclosures for 20 Japanese listed firms. Demonstrates the gap between disclosed emissions data and machine-parseable carbon accounting — the core problem this OSINT tool addresses.

researchhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=6761458

Route distances are estimates from Sea-distances.org and cross-referenced with Searoutes. Actual nautical distances vary by port of call and vessel draft. Users should verify against route-specific data before use in formal reporting.