Micro-Mobility Carbon Footprint Tracker
This dataset provides granular trip-level and asset-level data to track, compare, and benchmark the carbon footprint of shared micro-mobility fleets (e-scooters, bikes) across smart city zones. It includes emissions, energy source mix, fleet operator details, and ESG intervention flags, enabling transportation planners and sustainability officers to drive data-driven decisions for greener urban mobility.
Sample rows
preview · 8 of 120 rows · all 15 columns| asset_idstring | asset_typestring | carbon_emissions_kgco2efloat | esg_intervention_flagboolean | zone_namestring | zone_idstring | trip_idstring | trip_start_datetimedatetime | trip_end_datetimedatetime | trip_distance_kmfloat | trip_duration_minutesfloat | energy_consumed_kwhfloat | energy_source_typestring | fleet_operatorstring | asset_statusstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AS1001 | e-scooter | 0.11 | true | Central Plaza | Z01 | TRP0001 | 2024-04-01T08:12:00 | 2024-04-01T08:32:00 | 4.2 | 20 | 0.55 | renewable | GreenWheels | active |
| AS1002 | bike | 0 | false | Harbor District | Z02 | TRP0002 | 2024-04-01T09:05:00 | 2024-04-01T09:45:00 | 7.8 | 40 | blank | blank | UrbanCycle | active |
| AS1003 | e-scooter | 0.19 | false | Financial Center | Z03 | TRP0003 | 2024-04-01T10:21:00 | 2024-04-01T10:34:00 | 2.7 | 13 | 0.34 | grid | ScootPilot | active |
| AS1004 | bike | 0 | false | Old Town | Z04 | TRP0004 | 2024-04-01T11:00:00 | 2024-04-01T11:38:00 | 5.1 | 38 | blank | blank | PedalShare | active |
| AS1005 | e-scooter | 0.24 | true | Tech Park | Z05 | TRP0005 | 2024-04-01T12:12:00 | 2024-04-01T12:31:00 | 3.8 | 19 | 0.41 | mixed | GreenWheels | active |
| AS1006 | bike | 0 | false | Riverside | Z06 | TRP0006 | 2024-04-01T13:00:00 | 2024-04-01T13:32:00 | 4.6 | 32 | blank | blank | UrbanCycle | active |
| AS1007 | e-scooter | 0.09 | false | Harbor District | Z02 | TRP0007 | 2024-04-01T14:11:00 | 2024-04-01T14:26:00 | 2.9 | 15 | 0.29 | renewable | ScootPilot | active |
| AS1008 | bike | 0 | true | University Zone | Z07 | TRP0008 | 2024-04-01T14:45:00 | 2024-04-01T15:12:00 | 3.6 | 27 | blank | blank | PedalShare | active |
| AS1009 | e-scooter | 0.14 | false | Market Street | Z08 | TRP0009 | 2024-04-01T15:33:00 | 2024-04-01T15:47:00 | 2.1 | 14 | 0.22 | grid | GreenWheels | active |
| AS1010 | bike | 0 | false | East End | Z09 | TRP0010 | 2024-04-01T16:00:00 | 2024-04-01T16:28:00 | 4.1 | 28 | blank | blank | UrbanCycle | active |
| AS1011 | e-scooter | 0.21 | true | South Loop | Z10 | TRP0011 | 2024-04-02T08:09:00 | 2024-04-02T08:31:00 | 3.7 | 22 | 0.37 | mixed | ScootPilot | active |
| AS1012 | bike | 0 | false | Central Plaza | Z01 | TRP0012 | 2024-04-02T09:14:00 | 2024-04-02T09:52:00 | 5.9 | 38 | blank | blank | PedalShare | active |
| AS1013 | e-scooter | 0.07 | false | Westfield Heights | Z11 | TRP0013 | 2024-04-02T10:22:00 | 2024-04-02T10:39:00 | 2.3 | 17 | 0.28 | renewable | GreenWheels | active |
| AS1014 | bike | 0 | true | Civic Center | Z12 | TRP0014 | 2024-04-02T11:07:00 | 2024-04-02T11:35:00 | 3.9 | 28 | blank | blank | UrbanCycle | active |
| AS1015 | e-scooter | 0.18 | true | Arts Quarter | Z13 | TRP0015 | 2024-04-02T12:19:00 | 2024-04-02T12:41:00 | 4.4 | 22 | 0.47 | grid | ScootPilot | active |
| AS1016 | bike | 0 | false | North Gate | Z14 | TRP0016 | 2024-04-02T13:10:00 | 2024-04-02T13:48:00 | 6.2 | 38 | blank | blank | PedalShare | active |
| AS1017 | e-scooter | 0.2 | false | Central Plaza | Z01 | TRP0017 | 2024-04-02T14:15:00 | 2024-04-02T14:35:00 | 3.7 | 20 | 0.36 | mixed | GreenWheels | active |
| AS1018 | bike | 0 | false | Harbor District | Z02 | TRP0018 | 2024-04-02T14:55:00 | 2024-04-02T15:27:00 | 4 | 32 | blank | blank | UrbanCycle | active |
| AS1019 | e-scooter | 0.12 | true | Financial Center | Z03 | TRP0019 | 2024-04-02T15:41:00 | 2024-04-02T16:01:00 | 3.2 | 20 | 0.31 | renewable | ScootPilot | active |
| AS1020 | bike | 0 | false | Old Town | Z04 | TRP0020 | 2024-04-02T16:10:00 | 2024-04-02T16:42:00 | 5.7 | 32 | blank | blank | PedalShare | active |
What the 120 rows show
from the 120-row sampleE-scooter (asset type) stands out: mean carbon_
- 39%esg_
intervention_ flag = true - 0.11median carbon_
emissions_ kgco2e - 3energy source types
- 11fleet operators
- 23zones
- 6.4median trip_
distance_ km
Median 0.11, from 0.0 to 0.49.
- string 8
- float 4
- datetime 2
- boolean 1
Columns
15 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 8 columns | |||
asset_id | string | Unique identifier for the micro-mobility asset (e.g., e-scooter, bike)unique | AS1001 |
asset_type | string | Type of micro-mobility asset (e.g., e-scooter, bike)e-scooter · bike | e-scooter |
zone_id | string | Unique identifier for the smart city zone where the asset is located or operated | Z01 |
zone_name | string | Human-readable name of the smart city zone | Central Plaza |
trip_id | string | Unique identifier for each trip taken by an assetunique | TRP0001 |
energy_source_type | string | Type of energy source used for charging (e.g., renewable, grid, mixed)renewable · grid · mixed · optional | renewable |
fleet_operator | string | Name of the company or organization operating the asset11 operators | GreenWheels |
asset_status | string | Current operational status of the asset (e.g., active, maintenance, retired)active · maintenance · retired · optional | active |
| Numbers 4 columns | |||
trip_distance_km | float | Distance covered during the trip in kilometers0 or more | 4.2 |
trip_duration_minutes | float | Duration of the trip in minutes0 or more | 20 |
energy_consumed_kwh | float | Amount of energy consumed during the trip in kilowatt-hours (kWh)0 or more · optional | 0.55 |
carbon_emissions_kgco2e | float | Estimated carbon emissions for the trip in kilograms of CO2 equivalent0 or more | 0.11 |
| Dates and times 2 columns | |||
trip_start_datetime | datetime | Date and time when the trip started | 2024-04-01T08:12:00 |
trip_end_datetime | datetime | Date and time when the trip ended | 2024-04-01T08:32:00 |
| True or false 1 column | |||
esg_intervention_flag | boolean | Indicates whether the trip or asset is part of an ESG intervention programoptional | true |
Use it for
A transportation dashboard
The esg_
intervention_ flag rate, carbon_ emissions_ kgco2e by asset_ type and a breakdown of zone_ name. Excel, Power BI or Tableau. Why do the 61 e-scooter rows have a mean carbon_
emissions_ kgco2e of 0.22? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Assets120AS10010.11e-scooterAS10020bikeAS10050.24e-scooter
A software demo
Believable assets with asset_
type, zone_ id and zone_ name to fill a screen in front of a buyer.
This dataset120 rows15 columns
Yours1,000 rows15 columns
blueprint · micro-mobility-carbon-footprint-tracker
Behind this dataset
Same schema. As many rows as you need.
These 120 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 micro-mobility trip within a city zone.
- Includes asset type, trip distance, energy consumed, and estimated CO2 emissions.
- Energy source must be classified (renewable, grid, hybrid).
- Trip utilization rates must be calculated per day and per zone.
- Exclude trips under 0.2 km or outside designated city zones.
- Fleet maintenance event logs must link to emission anomalies.
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
- micro-mobility-carbon-footprint-tracker