Urban Mobility Sustainability Logs
This dataset provides detailed, daily sustainability logs for urban transportation routes, including CO₂ emissions, renewable energy usage, passenger volumes, and operational metrics. Designed for urban planners and sustainability officers, it enables comprehensive analysis and optimization of public transit systems to support climate goals and improve operational efficiency.
Sample rows
preview · 8 of 130 rows · all 15 columns| log_idstring | transport_modestring | vehicle_countinteger | citystring | route_idstring | route_namestring | countrystring | datedate | co2_emissions_kgfloat | renewable_energy_pctfloat | total_energy_consumed_kwhfloat | passenger_volumeinteger | distance_kmfloat | average_speed_kmhfloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SLG-00001 | bus | 9 | Chicago | RT001 | Central Loop Express | USA | 2023-09-12 | 420.7 | 37 | 2100.2 | 1520 | 33.4 | 27.2 | Rainy evening, minor delays |
| SLG-00002 | tram | 4 | Sydney | RT002 | Harbour Tramline | Australia | 2023-10-01 | 210.3 | 49 | 1230.9 | 890 | 29.7 | 19.5 | blank |
| SLG-00003 | ferry | 3 | Stockholm | RT003 | Seaside Ferry Link | Sweden | 2023-07-25 | 0 | 100 | 340.8 | 160 | 17 | 24.4 | Electric ferry trial |
| SLG-00004 | metro | 8 | Berlin | RT004 | Metro Greenline | Germany | 2023-11-03 | 194.5 | 63 | 2780.1 | 2760 | 41.2 | 39.1 | Holiday peak |
| SLG-00005 | train | 10 | San Francisco | RT005 | Bay Area Rapid | USA | 2023-09-17 | 620.3 | 28 | 3320.8 | 2180 | 52.5 | 56.3 | Morning rush, increased service |
| SLG-00006 | bike-share | 36 | Copenhagen | RT006 | Downtown BikeShare | Denmark | 2023-08-09 | 0 | 100 | 29.3 | 113 | 11.6 | 17.3 | Pilot test: solar charging |
| SLG-00007 | bus | 12 | London | RT007 | Riverside Shuttle | UK | 2023-10-15 | 534.9 | 16 | 2501.6 | 1830 | 44.8 | 26.1 | blank |
| SLG-00008 | bus | 17 | Los Angeles | RT008 | Sunset Express | USA | 2023-09-27 | 1190.1 | 0 | 4150.4 | 3090 | 58.3 | 23.7 | Heatwave, A/C usage high |
| SLG-00009 | metro | 6 | Denver | RT009 | Mountain Metro | USA | 2023-11-20 | 315.8 | 46 | 1810 | 1580 | 30.2 | 35.4 | Snowstorm, reduced speed |
| SLG-00010 | other | 2 | Abu Dhabi | RT010 | Harbour Hyperloop | UAE | 2023-07-19 | 0 | 100 | 322.2 | 7 | 41 | 280 | Hyperloop demo run |
| SLG-00011 | ferry | 5 | Amsterdam | RT011 | Canal Ferry Line | Netherlands | 2023-08-12 | 740.2 | 18 | 2250.7 | 410 | 32.5 | 27.5 | High tourist volume |
| SLG-00012 | train | 8 | Madrid | RT012 | City Rail Mainline | Spain | 2023-10-08 | 801.8 | 34 | 2780.3 | 1990 | 72.1 | 62.2 | blank |
| SLG-00013 | tram | 5 | Vienna | RT013 | Green Tramway | Austria | 2023-11-25 | 180.4 | 52 | 1130 | 970 | 28.6 | 18.1 | Vintage fleet |
| SLG-00014 | bus | 19 | Tijuana | RT014 | Borderline | Mexico | 2023-08-03 | 3670.6 | 0 | 10090.1 | 15580 | 122.3 | 18.3 | Cross-border surge |
| SLG-00015 | bike-share | 44 | Toronto | RT015 | Riverfront BikeShare | Canada | 2023-09-04 | 0 | 100 | 32.7 | 85 | 14.2 | 15.8 | blank |
| SLG-00016 | metro | 7 | Paris | RT016 | Metro Redlink | France | 2023-11-12 | 252.9 | 58 | 1950.3 | 1840 | 37.1 | 33.9 | blank |
| SLG-00017 | bus | 10 | Beijing | RT017 | Sunrise Shuttle | China | 2023-10-27 | 420.6 | 41 | 1810.2 | 1100 | 29 | 21.7 | blank |
| SLG-00018 | tram | 3 | Zurich | RT018 | Lakeview Tram | Switzerland | 2023-09-23 | 144.7 | 59 | 970.9 | 715 | 22.8 | 17.4 | Rain showers |
| SLG-00019 | train | 9 | Vancouver | RT019 | Pacific Express | Canada | 2023-08-17 | 760.2 | 32 | 3040.6 | 1720 | 61 | 49.1 | blank |
| SLG-00020 | ferry | 6 | Oslo | RT020 | Fjord Ferry Line | Norway | 2023-07-30 | 910.2 | 70 | 3430.2 | 670 | 39.9 | 26.5 | blank |
What the 130 rows show
from the 130-row sampleBike-share (transport mode) stands out: mean vehicle_
- 8median vehicle_
count - 23countries
- 296.6median co2_
emissions_ kg - 44.5median renewable_
energy_ pct - 1,810median total_
energy_ consumed_ kwh - 981.5median passenger_
volume
Median 8, from 0 to 49.
- string 7
- integer 2
- float 5
- date 1
Columns
15 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
log_id | string | Unique identifier for each sustainability log entry.unique | SLG-00001 |
route_id | string | Unique identifier for the transportation route. | RT001 |
route_name | string | Descriptive name of the transportation route. | Central Loop Express |
city | string | Name of the city where the route operates. | Chicago |
country | string | Country where the city and route are located. | USA |
transport_mode | string | Type of transportation mode (e.g., bus, tram, metro, ferry, bike-share).7 values | bus |
notes | string | Additional notes or comments about the log entry (e.g., disruptions, special events, weather conditions).optional | Electric ferry trial |
| Numbers 7 columns | |||
co2_emissions_kg | float | Total CO₂ emissions in kilograms for the route on the given date.0 or more | 420.7 |
renewable_energy_pct | float | Percentage of energy consumed from renewable sources (0-100).0 to 100 | 37 |
total_energy_consumed_kwh | float | Total energy consumed by the route in kilowatt-hours (kWh) on the given date.0 or more | 2100.2 |
passenger_volume | integer | Number of passengers transported on the route during the recorded date.0 or more | 1520 |
distance_km | float | Total distance covered by the route in kilometers on the given date.0 or more | 33.4 |
average_speed_kmh | float | Average speed of vehicles on the route in kilometers per hour.0 or more · optional | 27.2 |
vehicle_count | integer | Number of vehicles operating on the route during the recorded date.0 or more · optional | 9 |
| Dates and times 1 column | |||
date | date | Date for which the sustainability metrics are recorded. | 2023-09-12 |
Use it for
A transportation dashboard
Vehicle_
count by transport_ mode and a breakdown of city. Excel, Power BI or Tableau. Why do the 14 bike-share rows have a mean vehicle_
count of 34.8? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Logs130SLG-000019busSLG-000024tramSLG-000033ferry
A software demo
Believable logs with route_
id, route_ name and city to fill a screen in front of a buyer.
This dataset130 rows15 columns
Yours1,000 rows15 columnscity: UK only
blueprint · urban-mobility-sustainability-logs
Behind this dataset
Same schema. As many rows as you need.
These 130 rows came out of a blueprint — 15 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 urban route and time period
- CO₂ emissions calculated based on vehicle type and passenger count
- Renewable energy usage logged for electric or hybrid routes
- Routes flagged if exceeding emissions thresholds
- Passenger volume must be non-negative and realistic per route
- Include timestamps for weekday/weekend differentiation
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-mobility-sustainability-logs