0xCarbon
CC BY 4.0 · generated 2026-09-03

Take the data

The complete 0xCarbon dataset is free to download and reuse under CC BY 4.0: 2,368 destinations across 46 countries, each with monthly temperature, sunshine and rainfall, return CO₂e and journey time by rail and air from 32 departure cities across 16 countries, and 3072 precomputed frontiers.

This dataset did not exist before. If it is useful to you — a newsroom, a paper, a tool, an argument with a colleague — use it. Attribution is the only condition.

2,368destinations across 46 countries, each with twelve months of temperature, sunshine and rainfall — drawn from a pool of 2,754 candidates
3,072precomputed frontiers: 2 questions × 32 cities × 12 months × 4 time budgets
86,762origin–destination journeys costed by rail and by air

What is not in it

A further 386 settlements clear the size and distance filters but do not yet have twelve months of climate data. They are excluded from every ranking rather than estimated, and are added as the data arrives. Nothing in this dataset is interpolated, imputed or filled from a neighbouring town: a destination is either measured or absent.

Download

FileWhat's in itFormat
frontiers.jsonEvery frontier, self-describing: licence, model parameters and emission factors travel with the dataJSON

How to cite

0xCarbon (2026). European travel carbon and climate dataset. Derived from UK Government GHG Conversion Factors 2026 (OGL v3.0), ERA5 via Open-Meteo (CC BY 4.0) and GeoNames (CC BY 4.0). Available at https://0xcarbon.com/data/

Shape of the data

Frontiers are keyed question:origin:month:hours — so warmest:london:1:15 is the warmest January options from London within a fifteen-hour one-way journey, and sunniest:london:11:10the sunniest November options within ten hours. Each entry carries the destination's name, country, return kg CO₂e, mean temp in °C, the mode (rail or fly), modelled hours, the quality it was ranked on as q, its temp, sunand rain for that month, and a URL for the destination page.

Read the methodology before using these numbers in anything that matters — particularly the section on what the method gets wrong. Rail journey times are modelled, not timetabled.