Rail Freight Carbon Tracking Logs
This dataset provides detailed, real-time logs of carbon emissions from rail freight journeys, including train identifiers, freight details, energy sources, and compliance status. It enables sustainability managers and logistics leaders to monitor, analyze, and report on decarbonization efforts, supporting regulatory and ESG requirements across transportation supply chains.
Sample rows
preview · 8 of 122 rows · all 24 columns| log_idstring | energy_sourcestring | emissions_factorfloat | regulatory_complianceboolean | departure_countrystring | train_idstring | operator_namestring | departure_datetimedatetime | arrival_datetimedatetime | departure_stationstring | departure_citystring | departure_statestring | arrival_stationstring | arrival_citystring | arrival_statestring | arrival_countrystring | distance_kmfloat | freight_typestring | freight_weight_tonsfloat | carbon_emissions_kgfloat | esg_report_referencestring | data_sourcestring | created_atdatetime | updated_atdatetime |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TR-DE-0013456 | electric | 0.017 | true | Germany | TR-DE-3531 | Deutsche Bahn Cargo | 2023-04-03T08:15:00+02:00 | 2023-04-03T16:40:00+02:00 | Hamburg Hbf | Hamburg | DE-HH | Munich Hbf | Munich | DE-BY | Germany | 698.2 | containers | 84.5 | 995.26 | ESG-DE-23-3001 | sensor | 2023-04-03T17:01:00+02:00 | 2023-04-03T17:15:00+02:00 |
| TR-FR-0032983 | electric | 0.021 | true | France | TR-FR-6217 | SNCF Fret | 2023-05-11T09:05:00+02:00 | 2023-05-11T13:20:00+02:00 | Paris Bercy | Paris | DE-IDF | Lyon Part Dieu | Lyon | DE-ARA | France | 463.1 | containers | 48.3 | 464.44 | ESG-FR-23-1111 | sensor | 2023-05-11T13:35:00+02:00 | 2023-05-11T13:45:00+02:00 |
| TR-UK-0093827 | electric | 0.028 | true | UK | TR-UK-1283 | DB Schenker UK | 2023-06-22T06:45:00+01:00 | 2023-06-22T11:25:00+01:00 | London Gateway | London | ENG | Manchester Piccadilly | Manchester | ENG | UK | 338.6 | containers | 29.1 | 275.82 | ESG-UK-23-0219 | sensor | 2023-06-22T11:43:00+01:00 | 2023-06-22T12:05:00+01:00 |
| TR-NL-0002389 | electric | 0.0125 | true | Netherlands | TR-NL-4572 | Rail Cargo NL | 2023-07-15T10:30:00+02:00 | 2023-07-15T19:15:00+02:00 | Rotterdam Centraal | Rotterdam | NL-ZH | Amsterdam Zuid | Amsterdam | NL-NH | Netherlands | 82.4 | containers | 15.2 | 15.76 | ESG-NL-23-0840 | sensor | 2023-07-15T19:20:00+02:00 | 2023-07-15T20:00:00+02:00 |
| TR-CH-0023946 | electric | 0.012 | true | Switzerland | TR-CH-3849 | SBB Cargo | 2023-08-01T07:35:00+02:00 | 2023-08-01T12:45:00+02:00 | Zurich HB | Zurich | CH-ZH | Geneva Cornavin | Geneva | CH-GE | Switzerland | 276.7 | containers | 67.4 | 222.56 | ESG-CH-23-0623 | sensor | 2023-08-01T13:15:00+02:00 | 2023-08-01T13:40:00+02:00 |
| TR-ES-0038472 | electric | 0.015 | true | Spain | TR-ES-7732 | Renfe Mercancias | 2023-09-10T05:55:00+02:00 | 2023-09-10T11:35:00+02:00 | Madrid Chamartín | Madrid | ES-MD | Barcelona Sants | Barcelona | ES-CT | Spain | 624.3 | containers | 98.7 | 922.2 | ESG-ES-23-0901 | sensor | 2023-09-10T12:05:00+02:00 | 2023-09-10T12:45:00+02:00 |
| TR-US-0021937 | diesel | 0.04 | true | USA | TR-US-4794 | Union Pacific Freight | 2023-10-14T07:33:00-07:00 | 2023-10-15T02:41:00-07:00 | Seattle King St | Seattle | WA | Chicago Union | Chicago | IL | USA | 3344.8 | bulk | 285.9 | 38153.5 | ESG-US-23-0933 | operator_report | 2023-10-15T03:10:00-07:00 | 2023-10-15T03:50:00-07:00 |
| TR-CA-0038472 | diesel | 0.02 | true | Canada | TR-CA-7751 | Canadian National Rail | 2023-11-05T08:10:00-05:00 | 2023-11-05T17:35:00-05:00 | Toronto Union | Toronto | ON | Montreal Central | Montreal | QC | Canada | 543.5 | bulk | 104.2 | 1125.77 | ESG-CA-23-7711 | operator_report | 2023-11-05T17:45:00-05:00 | blank |
| TR-MX-0014885 | diesel | 0.2 | false | Mexico | TR-MX-1334 | Ferromex | 2023-12-06T04:40:00-06:00 | 2023-12-06T15:25:00-06:00 | Mexico City Buenavista | Mexico City | CMX | Guadalajara Central | Guadalajara | JAL | Mexico | 550.1 | bulk | 92 | 10192.52 | blank | estimate | 2023-12-06T15:38:00-06:00 | blank |
| TR-CN-0029847 | diesel | 0.04 | false | China | TR-CN-4871 | China Railway Freight | 2022-03-12T09:15:00+08:00 | 2022-03-13T02:40:00+08:00 | Beijing South | Beijing | BJ | Shanghai Hongqiao | Shanghai | SH | China | 1210 | hazardous | 124.7 | 6014.24 | blank | estimate | 2022-03-13T03:05:00+08:00 | 2022-03-13T03:40:00+08:00 |
| TR-IN-0002397 | diesel | 0.4 | false | India | TR-IN-5934 | Indian Railways Freight | 2022-04-28T13:30:00+05:30 | 2022-04-28T20:45:00+05:30 | Delhi Hazrat Nizamuddin | Delhi | DL | Mumbai CST | Mumbai | MH | India | 1387.5 | liquid | 81.6 | 45118.8 | blank | estimate | 2022-04-28T21:05:00+05:30 | blank |
| TR-RU-0040012 | diesel | 0.04 | true | Russia | TR-RU-1183 | Russian Railways Bulk | 2022-05-20T23:15:00+03:00 | 2022-05-21T11:25:00+03:00 | Moscow Leningradsky | Moscow | MOW | St Petersburg Moskovsky | St Petersburg | SPE | Russia | 635.2 | liquid | 54.8 | 1380.52 | ESG-RU-22-0083 | sensor | 2022-05-21T11:33:00+03:00 | 2022-05-21T12:10:00+03:00 |
| TR-JP-0001827 | electric | 0.01 | true | Japan | TR-JP-8832 | JR Freight | 2022-06-03T12:20:00+09:00 | 2022-06-03T15:55:00+09:00 | Tokyo Station | Tokyo | 13 | Osaka Station | Osaka | 27 | Japan | 508.7 | hazardous | 37.5 | 190.73 | ESG-JP-22-1101 | sensor | 2022-06-03T16:10:00+09:00 | blank |
| TR-KY-0012309 | diesel | 0.01 | true | Kenya | TR-KY-9432 | Kenya Railways | 2022-07-16T07:12:00+03:00 | 2022-07-16T13:45:00+03:00 | Nairobi Central | Nairobi | blank | Mombasa Terminus | Mombasa | blank | Kenya | 485.6 | containers | 42.1 | 203.95 | ESG-KY-22-8332 | operator_report | 2022-07-16T14:00:00+03:00 | blank |
| TR-ZA-0029874 | diesel | 0.01 | false | South Africa | TR-ZA-2358 | Transnet Freight Rail | 2022-08-05T08:44:00+02:00 | 2022-08-05T19:05:00+02:00 | Johannesburg Park | Johannesburg | blank | Cape Town Central | Cape Town | blank | South Africa | 1260.4 | other | 101.2 | 1275.7 | blank | estimate | 2022-08-05T19:30:00+02:00 | blank |
| TR-BR-0031847 | diesel | 0.015 | true | Brazil | TR-BR-5581 | Rumo Logistica | 2022-09-17T05:23:00-03:00 | 2022-09-17T16:17:00-03:00 | Sao Paulo Luz | Sao Paulo | blank | Curitiba Central | Curitiba | blank | Brazil | 409.7 | containers | 35.8 | 220.78 | ESG-BR-22-0059 | estimate | 2022-09-17T16:45:00-03:00 | blank |
| TR-TL-0000001 | other | 0.15 | false | Testland | TR-TL-0001 | Testland Rails | 2022-10-22T09:05:00+00:00 | 2022-10-22T09:13:00+00:00 | Testville East | Testville | blank | Testopolis West | Testopolis | blank | Testland | 2.7 | other | 3.5 | 1.42 | blank | other | 2022-10-22T09:15:00+00:00 | blank |
| TR-NW-0000002 | other | 0.1 | true | Nowhere | TR-NW-0002 | Nowhere Railways | 2022-11-01T10:00:00+00:00 | 2022-11-01T10:11:00+00:00 | Nulltown | Nulltown | blank | Voidville | Voidville | blank | Nowhere | 6.4 | hazardous | 6.1 | 3.91 | ESG-NW-22-0002 | other | 2022-11-01T10:20:00+00:00 | blank |
| TR-DE-0048729 | electric | 0.0163 | true | Germany | TR-DE-9823 | DB Cargo AG | 2023-01-10T14:45:00+01:00 | 2023-01-10T20:01:00+01:00 | Frankfurt Hbf | Frankfurt | DE-HE | Stuttgart Hbf | Stuttgart | DE-BW | Germany | 205.3 | bulk | 37.6 | 123.18 | ESG-DE-23-9823 | sensor | 2023-01-10T20:10:00+01:00 | blank |
| TR-FR-0092837 | electric | 0.0075 | true | France | TR-FR-2048 | Fret SNCF | 2023-02-18T07:10:00+01:00 | 2023-02-18T13:55:00+01:00 | Marseille St Charles | Marseille | DE-PAC | Toulouse Matabiau | Toulouse | DE-OCC | France | 404.7 | bulk | 45.5 | 138.37 | ESG-FR-23-2048 | sensor | 2023-02-18T14:15:00+01:00 | 2023-02-18T14:41:00+01:00 |
What the 122 rows show
from the 122-row sampleOther (energy source) stands out: mean emissions_
- 74%regulatory_
compliance = true - 0.04median emissions_
factor - 4data sources
- 5freight types
- 19arrival countries
- 424.4median distance_
km
Median 0.04, from 0.00 to 0.50.
- string 15
- float 4
- datetime 4
- boolean 1
Columns
24 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 15 columns | |||
log_id | string | Unique identifier for each carbon tracking log entryunique | TR-DE-0013456 |
train_id | string | Unique identifier for the train involved in the freight operation | TR-DE-3531 |
operator_name | string | Name of the rail freight operator | Deutsche Bahn Cargo |
departure_station | string | Name of the departure station | Hamburg Hbf |
departure_city | string | City of the departure station | Hamburg |
departure_state | string | State or region of the departure stationoptional | DE-HH |
departure_country | string | Country of the departure station | Germany |
arrival_station | string | Name of the arrival station | Munich Hbf |
arrival_city | string | City of the arrival station | Munich |
arrival_state | string | State or region of the arrival stationoptional | DE-BY |
arrival_country | string | Country of the arrival station | Germany |
freight_type | string | Type of freight being transported (e.g., containers, bulk, hazardous)containers · bulk · hazardous · liquid · other | containers |
energy_source | string | Primary energy source for the train (e.g., diesel, electric, hybrid)diesel · electric · hybrid · other | electric |
esg_report_reference | string | Reference ID for related ESG report (if applicable)optional | ESG-DE-23-3001 |
data_source | string | Source of the carbon emissions data (e.g., sensor, estimate, operator report)sensor · estimate · operator_report · other | sensor |
| Numbers 4 columns | |||
distance_km | float | Total distance traveled in kilometers0 or more | 698.2 |
freight_weight_tons | float | Total weight of the freight in metric tons0 or more | 84.5 |
carbon_emissions_kg | float | Total carbon emissions for the journey in kilograms0 or more | 995.26 |
emissions_factor | float | Emissions factor used for calculation (kg CO2 per ton-km)0 or more | 0.017 |
| Dates and times 4 columns | |||
departure_datetime | datetime | Date and time when the train departed | 2023-04-03T08:15:00+02:00 |
arrival_datetime | datetime | Date and time when the train arrived | 2023-04-03T16:40:00+02:00 |
created_at | datetime | Timestamp when the log entry was created | 2023-04-03T17:01:00+02:00 |
updated_at | datetime | Timestamp when the log entry was last updatedoptional | 2023-04-03T17:15:00+02:00 |
| True or false 1 column | |||
regulatory_compliance | boolean | Indicates if the journey complies with relevant carbon regulations | true |
Use it for
A transportation dashboard
The regulatory_
compliance rate, emissions_ factor by energy_ source and a breakdown of departure_ country. Excel, Power BI or Tableau. Why do the 10 other rows have a mean emissions_
factor of 0.28? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Logs122TR-DE-00134560.017electricTR-FR-00329830.021electricTR-MX-00148850.2diesel
A software demo
Believable logs with train_
id, operator_ name and departure_ datetime to fill a screen in front of a buyer.
This dataset122 rows24 columns
Yours1,000 rows24 columnsdeparture_city: UK only
blueprint · rail-freight-carbon-tracking-logs
Behind this dataset
Same schema. As many rows as you need.
These 122 rows came out of a blueprint — 24 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Each row represents a unique freight journey segment
- Carbon emissions calculated based on distance and cargo type
- Include timestamp, route ID, and train type for each entry
- Validate emission values against industry benchmarks
- Journeys must be verifiable through sensor or operator logs
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- rail-freight-carbon-tracking-logs