US Energy CO2 Emissions by State, Sector & Fuel (EIA)
US energy-related carbon dioxide emissions for every state, split by economic sector (residential, commercial, industrial, transportation, electric power) and fuel (coal, petroleum, natural gas), annually. From EIA's state CO2 dataset: one fat, tidy row per (state × sector × fuel × year) with emissions in million metric tons CO2 - the state-and-sector view that complements our facility-level EPA GHGRP product and the US power suite. The decarbonisation-tracking panel for climate and energy analysis. Public domain.
- Source
- EIA_CO2
- Licence
- Redistributable open data
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- US energy CO2 by state × sector × fuel × year (~66k rows) - one clean row each
- Sectors: residential, commercial, industrial, transportation, electric power
- Fuels: coal, petroleum, natural gas; emissions in million metric tons CO2
- The state/sector view - complements facility-level EPA GHGRP + the US power suite
- Audiences: climate-risk / ESG, energy analysts, policy, decarbonisation research
- Public domain (U.S. EIA) - free commercial reuse & resale
- Source: U.S. Energy Information Administration - State Energy-Related CO2 Emissions
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| state | str | US state code (with sector_id + fuel_id + year, the primary key) | 100.0% | 52 |
| state_name | str | State name | 100.0% | 52 |
| sector_id | str | Sector code (RC/CC/IC/TC/EC, or TT = total) | 100.0% | 6 |
| sector | str | Sector name (Residential, Commercial, Industrial, Transportation, Electric Power) | 100.0% | 6 |
| fuel_id | str | Fuel code (CO/PE/NG, or TO = total) | 100.0% | 4 |
| fuel | str | Fuel (Coal, Petroleum, Natural Gas, All Fuels) | 100.0% | 4 |
| year | int | Year | 100.0% | 53 |
| co2_million_metric_tons | float | CO2 emissions (million metric tons) | 100.0% | 59,965 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: EIA_CO2 (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("us-co2-emissions-by-state_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
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