Urban Transit Energy Consumption Log
This dataset provides granular logs of energy consumption for public transit vehicles across multiple modes and routes, including energy type, usage, distance traveled, and estimated carbon emissions. It enables urban planners and sustainability officers to benchmark efficiency, optimize routes, and develop targeted carbon reduction strategies for city transit systems.
Sample rows
preview · 8 of 120 rows · all 18 columns| log_idstring | transit_modestring | energy_consumedfloat | location_countrystring | route_idstring | vehicle_idstring | energy_typestring | energy_unitstring | log_datedate | start_timedatetime | end_timedatetime | distance_traveledfloat | passenger_countinteger | location_citystring | location_statestring | carbon_emissions_estimatedfloat | data_sourcestring | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ENL-0001 | bus | 340.5 | USA | BUS-A1 | BUS-1001 | diesel | liters | 2024-06-10 | 2024-06-10T06:15:00 | 2024-06-10T10:10:00 | 210.2 | 1200 | Los Angeles | CA | 900.2 | onboard_sensor | blank |
| ENL-0002 | subway | 1885.3 | USA | SUB-Red | SUB-2001 | electricity | kWh | 2024-06-09 | 2024-06-09T08:00:00 | 2024-06-09T12:00:00 | 65.7 | 2200 | New York | NY | 565.6 | automated_system | blank |
| ENL-0003 | tram | 350.9 | Austria | TRM-4 | TRM-7001 | electricity | kWh | 2024-06-10 | 2024-06-10T13:00:00 | 2024-06-10T14:45:00 | 34.9 | 240 | Vienna | Vienna | 105.3 | utility_bill | Maintenance period log |
| ENL-0004 | ferry | 915.7 | Australia | FRY-SYD | FRY-301 | diesel | liters | 2024-06-08 | 2024-06-08T09:20:00 | 2024-06-08T17:55:00 | 171.5 | 900 | Sydney | NSW | 2420.4 | automated_system | Harbor event: Vivid Sydney |
| ENL-0005 | light_rail | 175.4 | Norway | LRL-9 | LRL-105 | electricity | kWh | 2024-06-10 | 2024-06-10T07:30:00 | 2024-06-10T08:15:00 | 12.6 | 95 | Oslo | Oslo | 52.2 | onboard_sensor | blank |
| ENL-0006 | trolley | 22.9 | Switzerland | TRY-3 | TRY-412 | electricity | kWh | 2024-06-07 | 2024-06-07T10:45:00 | 2024-06-07T11:30:00 | 4.3 | 32 | Zurich | Zurich | 6.8 | onboard_sensor | blank |
| ENL-0007 | monorail | 39.7 | Canada | MON-Edm | MON-ED002 | electricity | kWh | 2024-06-09 | 2024-06-09T15:10:00 | 2024-06-09T16:00:00 | 5.3 | 45 | Edmonton | Alberta | 11.6 | onboard_sensor | Partial day operation |
| ENL-0008 | bus | 95.6 | United Kingdom | BUS-GL2 | BUS-1022 | hybrid | liters | 2024-06-08 | 2024-06-08T05:30:00 | 2024-06-08T08:15:00 | 51.5 | 320 | London | England | 230.8 | utility_bill | blank |
| ENL-0009 | tram | 48.1 | Germany | TRM-22 | TRM-7020 | hydrogen | kg | 2024-06-07 | 2024-06-07T09:00:00 | 2024-06-07T09:55:00 | 11.8 | 72 | Frankfurt | Hesse | 39.3 | utility_bill | Hydrogen pilot route |
| ENL-0010 | ferry | 120.7 | Finland | FRY-HLN | FRY-888 | hybrid | liters | 2024-06-09 | 2024-06-09T07:00:00 | 2024-06-09T13:50:00 | 98.3 | 380 | Helsinki | Uusimaa | 295.2 | manual_entry | Maintenance log: battery swap |
| ENL-0011 | bus | 210.3 | India | BUS-DEL | BUS-DL09 | cng | kg | 2024-06-10 | 2024-06-10T14:00:00 | 2024-06-10T17:45:00 | 84.6 | 950 | Delhi | Delhi | 122.9 | onboard_sensor | blank |
| ENL-0012 | tram | 225.7 | Italy | TRM-6 | TRM-7066 | electricity | kWh | 2024-06-10 | 2024-06-10T11:00:00 | 2024-06-10T12:10:00 | 21.2 | 135 | Milan | Lombardy | 67.7 | onboard_sensor | blank |
| ENL-0013 | bus | 870.9 | Brazil | BUS-SP | BUS-SP18 | diesel | liters | 2024-06-09 | 2024-06-09T10:00:00 | 2024-06-09T18:30:00 | 405.6 | 2800 | Sao Paulo | Sao Paulo | 2290.1 | automated_system | Holiday rush: June Festival |
| ENL-0014 | subway | 1920.4 | China | SUB-B2 | SUB-2100 | electricity | kWh | 2024-06-08 | 2024-06-08T06:30:00 | 2024-06-08T11:00:00 | 73.8 | 2050 | Shanghai | Shanghai | 576.1 | onboard_sensor | blank |
| ENL-0015 | ferry | 689.3 | Norway | FRY-OSL | FRY-777 | diesel | liters | 2024-06-10 | 2024-06-10T09:00:00 | 2024-06-10T18:00:00 | 152.1 | 810 | Oslo | Oslo | 1821.5 | onboard_sensor | Cruise ship traffic increased |
| ENL-0016 | monorail | 28.4 | USA | MON-LV | MON-LV01 | electricity | kWh | 2024-06-07 | 2024-06-07T08:45:00 | 2024-06-07T09:20:00 | 3.2 | 21 | Las Vegas | NV | 8.3 | manual_entry | Low demand period |
| ENL-0017 | bus | 132.7 | Japan | BUS-TOK | BUS-TK09 | cng | kg | 2024-06-10 | 2024-06-10T12:00:00 | 2024-06-10T16:00:00 | 75.3 | 820 | Tokyo | Tokyo | 77.4 | automated_system | blank |
| ENL-0018 | light_rail | 31.5 | Finland | LRL-FIN | LRL-909 | hydrogen | kg | 2024-06-08 | 2024-06-08T17:05:00 | 2024-06-08T18:00:00 | 10.9 | 67 | Helsinki | Uusimaa | 23.6 | utility_bill | Hydrogen test run |
| ENL-0019 | subway | 1662.8 | United Kingdom | SUB-Blue | SUB-2050 | electricity | kWh | 2024-06-09 | 2024-06-09T07:05:00 | 2024-06-09T11:30:00 | 60.2 | 1720 | London | England | 505.6 | onboard_sensor | blank |
| ENL-0020 | trolley | 13.2 | Switzerland | TRY-7 | TRY-419 | hybrid | liters | 2024-06-09 | 2024-06-09T12:25:00 | 2024-06-09T13:00:00 | 1.3 | 13 | Basel | Basel-Stadt | 31.2 | manual_entry | Startup test |
What the 120 rows show
from the 120-row sampleSubway (transit mode) stands out: mean energy_
- 177.9median energy_
consumed - 3energy units
- 4data sources
- 6energy types
- 51.9median distance_
traveled - 275median passenger_
count
Median 177.9, from 0.0 to 2,108.
- string 11
- integer 1
- float 3
- date 1
- datetime 2
Columns
18 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 11 columns | |||
log_id | string | Unique identifier for each energy consumption log entryunique | ENL-0001 |
transit_mode | string | Type of public transit (e.g., bus, subway, tram, ferry)7 values | bus |
route_id | string | Identifier for the transit route | BUS-A1 |
vehicle_id | string | Unique identifier for the vehicle used on the route | BUS-1001 |
energy_type | string | Type of energy consumed (e.g., electricity, diesel, CNG, hybrid)6 values | diesel |
energy_unit | string | Unit of measurement for energy consumed (e.g., kWh, liters, kg)kWh · liters · kg | liters |
location_city | string | City where the transit route operates | Los Angeles |
location_state | string | State or region where the transit route operatesoptional | CA |
location_country | string | Country where the transit route operates | USA |
data_source | string | Source of the energy consumption data (e.g., onboard sensor, manual entry, utility bill)4 values · optional | onboard_sensor |
notes | string | Additional notes or comments about the log entryoptional | Maintenance period log |
| Numbers 4 columns | |||
energy_consumed | float | Total energy consumed during the log period (in kWh, liters, or kg depending on energy_type)0 or more | 340.5 |
distance_traveled | float | Total distance traveled during the log period (in kilometers)0 or more | 210.2 |
passenger_count | integer | Total number of passengers transported during the log period0 or more · optional | 1200 |
carbon_emissions_estimated | float | Estimated carbon emissions for the log period (in kg CO2 equivalent)0 or more · optional | 900.2 |
| Dates and times 3 columns | |||
log_date | date | Date of the energy consumption log | 2024-06-10 |
start_time | datetime | Start timestamp for the energy consumption measurement period | 2024-06-10T06:15:00 |
end_time | datetime | End timestamp for the energy consumption measurement period | 2024-06-10T10:10:00 |
Use it for
A transportation dashboard
Energy_
consumed by transit_ mode and a breakdown of location_ country. Excel, Power BI or Tableau. Why do the 12 subway rows have a mean energy_
consumed of 1,565? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Logs120ENL-0001340.5busENL-00021885.3subwayENL-0003350.9tram
A software demo
Believable logs with transit_
mode, route_ id and vehicle_ id to fill a screen in front of a buyer.
This dataset120 rows18 columns
Yours1,000 rows18 columnslocation_city: UK only
blueprint · urban-transit-energy-consumption-log
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 18 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 one transit vehicle's daily energy usage.
- Energy consumption recorded in kWh for buses, trams, and trains.
- Include route type (urban, suburban, express) and passenger count.
- Flag records exceeding predefined energy efficiency thresholds.
- Missing passenger data must be marked as 'Unknown'.
- Outlier energy readings require verification status.
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
- urban-transit-energy-consumption-log