Shipment Carbon Footprint Tracking

This dataset provides granular tracking of carbon emissions for individual shipments across diverse transport routes, including detailed origin/destination, carrier, and sustainability certification data. It enables supply chain managers to analyze high-impact routes, optimize logistics decisions, and generate compliance-ready sustainability reports for regulatory and corporate responsibility purposes.

  • last updated 28 Jan 2026
  • by GoMask
The brief that made it

Identifying and optimizing high-emission transport routes

Sample rows

preview · 8 of 120 rows · all 25 columns
shipment_idstringtransport_modestringdistance_kmfloatsustainability_certifiedbooleanorigin_statestringorigin_street_addressstringorigin_citystringorigin_postal_codestringorigin_countrystringdestination_street_addressstringdestination_citystringdestination_statestringdestination_postal_codestringdestination_countrystringshipment_datedatedelivery_datedateroute_idstringshipment_weight_kgfloatshipment_volume_m3floatcarbon_emissions_kgco2efloatemission_factor_kgco2e_per_kmfloatcarrier_namestringshipment_statusstringreporting_periodstringnotesstring
SHIP-0001air861.5trueCA1427 Market StSan Francisco94103US3 Abbey RoadLondonblankNW8 9AYGB2024-01-052024-01-06RTE-AIR-USGB-001630.52.1197.7730.2295TransAtlantic Air CargodeliveredQ1-2024Fragile goods, expedited delivery
SHIP-0002truck337.9falseON75 King St WTorontoM5K1A1CA4317 Main StVancouverBCV5V3P9CA2024-02-202024-02-21RTE-TRUCK-CACA-002261415.487.8540.26Maple FreightwaysdeliveredQ1-2024Standard delivery
SHIP-0003rail1105.7trueblank5 Rue de RivoliParis75001FR12 AlexanderplatzBerlinblank10178DE2024-03-122024-03-12RTE-RAIL-FRDE-003893588.188.4560.08EuroRail LogisticsdeliveredQ1-2024Bulk shipment of electronics
SHIP-0004sea3923.1falseSH888 Nanjing RdShanghai200001CN2 Changi AveSingaporeblank499598SG2024-01-282024-01-31RTE-SEA-CNSG-00420145210.5470.7720.12Asia Ocean Linesin_transitQ1-2024Delayed due to weather
SHIP-0005truck227.4trueNY1799 BroadwayNew York10019US2300 Wilshire BlvdLos AngelesCA90057US2024-02-032024-02-03RTE-TRUCK-USUS-005382011.959.1240.26West Coast ExpressdeliveredQ1-2024Same-day local delivery
SHIP-0006air264.8falseblank17 O'Connell StDublinD01F5P2IE23 Oxford StManchesterblankM13 9PLGB2024-01-172024-01-17RTE-AIR-IEGB-006240.21.660.8130.2295Emerald AirdeliveredQ1-2024Hazmat shipment, certified route
SHIP-0007other1311.2trueblank4 BahnhofstrasseZurich8001CH10 Fjord AveOsloblank0255NO2024-03-152024-03-19RTE-OTHER-CHNO-007154.21.2104.8960.08Nordic Medical Courierdelivered2024Medical supplies, certified
SHIP-0008air2164.7falseVIC101 Collins StMelbourne3000AU67 Queen StAucklandblank1010NZ2024-03-112024-03-12RTE-AIR-AUNZ-008470.33.2497.0020.2295Austral Skiesin_transitQ1-2024Fragile goods, expedited

What the 120 rows show

from the 120-row sample

Sea (transport mode) stands out: mean distance_km is 4,382, against 770.3 for the rest.

  • 42%sustainability_certified = true
  • 894.0median distance_km
  • 3shipment statuses
  • 4reporting periods
  • 19destination countries
  • 21origin countries
Mean distance_km by transport_mode120 rows
04,0008,000217.4truck46 rows1,228rail23 rows1,046air17 rows4,382sea16 rows1,337other18 rows
distance_km120 rows, in bands of 1,000
035706436563603,0006,000distance_km →

Median 894.0, from 97.9 to 5,838.

origin_state61 rows with a value · 59 left blank
  1. CA8
  2. ON7
  3. TX5
  4. NSW5
  5. SH3
  6. VIC3
  7. TK3
  8. MH3
  9. MA3
  10. QC3
25 columns by typefrom the column list below
  • string 17
  • float 5
  • date 2
  • boolean 1

Columns

25 columns in four groups
blueprint · 25 columns
columntypedescriptionexample
Text 17 columns
shipment_idstringUnique identifier for each shipmentuniqueSHIP-0001
origin_street_addressstringStreet address of shipment origin1427 Market St
origin_citystringCity of shipment originSan Francisco
origin_statestringState or province of shipment originoptionalCA
origin_postal_codestringPostal code of shipment originoptional94103
origin_countrystringCountry of shipment originUS
destination_street_addressstringStreet address of shipment destination3 Abbey Road
destination_citystringCity of shipment destinationLondon
destination_statestringState or province of shipment destinationoptionalBC
destination_postal_codestringPostal code of shipment destinationoptionalNW8 9AY
destination_countrystringCountry of shipment destinationGB
transport_modestringPrimary mode of transport used (e.g., truck, rail, air, sea)truck · rail · air · sea · otherair
route_idstringUnique identifier for the transport route takenRTE-AIR-USGB-001
carrier_namestringName of the logistics carrier or provideroptionalTransAtlantic Air Cargo
shipment_statusstringCurrent status of the shipmentin_transit · delivered · cancelled · pendingdelivered
reporting_periodstringReporting period or compliance cycle (e.g., Q1-2024, 2024)4 periods · optionalQ1-2024
notesstringAdditional notes or comments about the shipmentoptionalStandard delivery
Numbers 5 columns
distance_kmfloatDistance covered by the shipment in kilometers0 or more861.5
shipment_weight_kgfloatWeight of the shipment in kilograms0 or more630.5
shipment_volume_m3floatVolume of the shipment in cubic meters0 or more · optional2.1
carbon_emissions_kgco2efloatEstimated carbon emissions for the shipment in kilograms of CO2 equivalent0 or more197.773
emission_factor_kgco2e_per_kmfloatEmission factor used for calculation (kg CO2e per km for given transport mode)0 or more · optional0.2295
Dates and times 2 columns
shipment_datedateDate the shipment was dispatched2024-01-05
delivery_datedateDate the shipment was deliveredoptional2024-01-06
True or false 1 column
sustainability_certifiedbooleanIndicates if the carrier or route is certified for sustainabilityoptionaltrue

Use it for

  • sustainability…42%50 of 120 rowsmean distance km by t…217.4truck1.2krail1kair4.4ksea

    A logistics dashboard

    The sustainability_certified rate, distance_km by transport_mode and a breakdown of origin_state. Excel, Power BI or Tableau.

  • Why do the 16 sea rows have a mean distance_km of 4,382?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable shipments with origin_street_address, origin_city and origin_state to fill a screen in front of a buyer.

Not quite right?

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This dataset120 rows25 columns
Yours10,000 rows25 columnsorigin_street_address: UK only

blueprint · shipment-carbon-footprint-tracking

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 25 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
  • Calculate emissions based on route distance, transport mode, and shipment weight.
  • Include both direct (vehicle) and indirect (fuel type) emission factors.
  • Flag shipments exceeding company-set carbon thresholds.
  • Allow for multiple transport modes per shipment.
  • Log anomalies such as route disruptions affecting emissions.
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
shipment-carbon-footprint-tracking

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