emission-factors

Evidence-governed carbon-factor retrieval and qualification engine for materials, energy, transport and processes.

Official Python & JavaScript/TypeScript SDKs for the GreenCalculus carbon API — sourced emission factors + audit-traced calculations.

Emission and water factors for AI inference by model class and cloud region. CC BY 4.0. Companion to arXiv:2606.10660

Find greenhouse-gas warming-potential tables that contradict the IPCC assessment report they name. Not a staleness check — AR4 and AR5 values are often correct by law.

Formal methodology, emission factor datasets, and GHG Protocol alignment documentation for GreenCalculus.com

CarbonCampus — campus-calibrated urban carbon footprint calculator (PWA + emission engine). Avinya 2026, Prakriti EcoInnovate Challenge, IIT Guwahati.

Keyless MCP server for US electricity data by ZIP code: EPA eGRID emission factors, EIA rates, hourly grid carbon intensity, EPA CAMD plant emissions, and utility tariffs. For Claude, Cursor, Cline and other MCP clients.

What the GreenCalculus corpus covers — 16,673 sourced emission factors from 137 publishers, with each publisher's licence and whether it may be republished. Metadata only, no values.

Run the GreenCalculus MCP server over stdio — sourced carbon emission factors and audit-traced calculations an AI can cite.

Scope 1, 2 and 3 carbon accounting in Julia: emission-factor libraries, calculation engines, audit trails and security, data parsing and normalisation, integration and connectivity, a neural soft sensor for the annual analyzer campaign and anomaly detection - with Pluto notebooks and a PDF printout.

European grid emission factors, ENTSO-E bidding-zone and TSO mappings, and the SDA energy, token and MiCA glossary. Static reference data, CC BY 4.0.

Scheduled carbon factor ingestion and parsing reference project with independent Python and .NET implementations for GHG Protocol, DEFRA/DESNZ, and IPCC EFDB datasets.

Calculate your corporate carbon footprint using UBA emission factors.

How wrong are LLMs about emission factors — and how often do they name the wrong source for a number? 467 questions, five models, scored against sourced ground truth.