Environment Reference tableQC clean AI-training-safe

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.

66K
rows
8
columns
1.2 MB
download
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

ColumnTypeDescriptionFilledDistinct
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