E-commerce Transaction Carbon Impact

This dataset provides detailed, transaction-level estimates of carbon emissions for e-commerce orders, including breakdowns by product, packaging, delivery method, and logistics route. It enables sustainability managers and analysts to track, report, and optimize carbon impact across operations, supporting ESG compliance and strategic decision-making for greener supply chains.

  • last updated 23 Nov 2025
  • by GoMask
The brief that made it

ESG and sustainability reporting for e-commerce operations

Sample rows

preview · 8 of 120 rows · all 25 columns
transaction_idstringdelivery_methodstringcarbon_breakdown_transport_kgfloatis_offsetbooleanroute_origin_countrystringtransaction_datetimedatetimecustomer_idstringproduct_idstringproduct_categorystringproduct_weight_kgfloatpackaging_typestringpackaging_weight_kgfloatlogistics_carrierstringroute_distance_kmfloatroute_origin_citystringroute_origin_statestringroute_destination_citystringroute_destination_statestringroute_destination_countrystringtransport_modestringestimated_carbon_kgfloatcarbon_breakdown_packaging_kgfloatcarbon_breakdown_last_mile_kgfloatoffset_typestringesg_reporting_periodstring
TXN0001express96.5trueUSA2024-01-15T11:23:47CST1001PRD-ELC-1001electronics2.8cardboard box0.45AirSwift4132San JoseCALondonEnglandUKair98.20.451.25reforestationQ1-2024
TXN0002standard4.88falseUSA2024-03-02T15:10:02CST1002PRD-HMG-1002home goods6.4cardboard box1.1FastShip279.7DallasTXHoustonTXUSAtruck5.670.320.47noneQ1-2024
TXN0003same-day0.18falseUSA2024-04-18T13:51:29CST1003PRD-APP-1003apparel0.7biodegradable0.09HomeQuick12.8SeattleWASeattleWAUSAelectric-vehicle0.340.090.07noneQ2-2024
TXN0004pickup0falseUSA2024-05-05T16:40:55CST1004PRD-TOY-1004toys0.35plastic wrap0.04StoreSelf0MiamiFLMiamiFLUSAbike0.020.020noneQ2-2024
TXN0005standard0.96falseUSA2024-02-19T09:39:14CST1005PRD-BOK-1005books1.2biodegradable0.18KidsExpress82.3DenverCOColorado SpringsCOUSAtruck1.210.180.07noneQ1-2024
TXN0006express200.3trueGermany2024-03-28T10:17:06CST1006PRD-ELC-1006electronics3.6cardboard box0.7GlobalExpress7008.8HamburgHamburgCape TownWestern CapeSouth Africaair202.80.71.8renewable-energyQ1-2024
TXN0007standard5.65falseUSA2024-04-07T18:32:45CST1007PRD-HMG-1007home goods8.9cardboard box1.35SuperPack315.6PhoenixAZLas VegasNVUSAtruck6.340.350.34noneQ2-2024
TXN0008pickup0falseUSA2024-04-12T09:16:24CST1008PRD-APP-1008apparel0.3plastic wrap0.06StoreSelf0San DiegoCASan DiegoCAUSAbike0.010.010noneQ2-2024

What the 120 rows show

from the 120-row sample

Express (delivery method) stands out: mean carbon_breakdown_transport_kg is 166.1, against 13.6 for the rest.

  • 37%is_offset = true
  • 2.5median carbon_breakdown_transport_kg
  • 3packaging types
  • 4offset types
  • 5product categories
  • 6transport modes
Mean carbon_breakdown_transport_kg by delivery_method120 rows
010020022.0standard63 rows166.1express18 rows0.18same-day19 rows0.0pickup20 rows
carbon_breakdown_transport_kg120 rows, in bands of 25
045908310274315230125250carbon_breakdown_transport_kg →

Median 2.5, from 0.0 to 244.9.

route_origin_country120 rows · top 10 of 29 values
  1. USA35
  2. Germany10
  3. Canada10
  4. Italy7
  5. UK6
  6. Belgium6
  7. France3
  8. Australia3
  9. Spain3
  10. China3
25 columns by typefrom the column list below
  • string 16
  • float 7
  • datetime 1
  • boolean 1

Columns

25 columns in four groups
blueprint · 25 columns
columntypedescriptionexample
Text 16 columns
transaction_idstringUnique identifier for each e-commerce transactionuniqueTXN0001
customer_idstringUnique identifier for the customer making the purchaseCST1001
product_idstringUnique identifier for the product purchasedPRD-ELC-1001
product_categorystringCategory of the product (e.g., electronics, apparel, home goods)5 categorieselectronics
packaging_typestringType of packaging used (e.g., cardboard box, plastic wrap, biodegradable)3 typescardboard box
delivery_methodstringMethod of delivery (e.g., standard, express, same-day, pickup)standard · express · same-day · pickupexpress
logistics_carrierstringName of the logistics provider or carrierAirSwift
route_origin_citystringCity where the shipment originatedSan Jose
route_origin_statestringState or region where the shipment originatedCA
route_origin_countrystringCountry where the shipment originatedUSA
route_destination_citystringCity where the shipment was deliveredLondon
route_destination_statestringState or region where the shipment was deliveredEngland
route_destination_countrystringCountry where the shipment was deliveredUK
transport_modestringPrimary mode of transport used (e.g., truck, air, rail, ship)6 valuesair
offset_typestringType of offset applied (e.g., reforestation, renewable energy, none)reforestation · renewable-energy · none · other · optionalreforestation
esg_reporting_periodstringESG reporting period (e.g., Q1-2024, FY2023) associated with the transaction7 periods · optionalQ1-2024
Numbers 7 columns
product_weight_kgfloatWeight of the product in kilograms0 or more2.8
packaging_weight_kgfloatWeight of the packaging in kilograms0 or more0.45
route_distance_kmfloatTotal distance traveled for delivery in kilometers0 or more4132
estimated_carbon_kgfloatEstimated total carbon footprint of the transaction in kilograms CO2 equivalent0 or more98.2
carbon_breakdown_packaging_kgfloatEstimated carbon emissions from packaging in kilograms CO2 equivalent0 or more0.45
carbon_breakdown_transport_kgfloatEstimated carbon emissions from transport in kilograms CO2 equivalent0 or more96.5
carbon_breakdown_last_mile_kgfloatEstimated carbon emissions from last-mile delivery in kilograms CO2 equivalent0 or more1.25
Dates and times 1 column
transaction_datetimedatetimeDate and time when the transaction occurred2024-01-15T11:23:47
True or false 1 column
is_offsetbooleanIndicates whether the carbon footprint of this transaction was offset (e.g., via carbon credits)true

Use it for

  • is offset37%44 of 120 rowsmean carbon breakdown…22.0stan…166.1expr…0.18same…0.0pick…

    An e-commerce dashboard

    The is_offset rate, carbon_breakdown_transport_kg by delivery_method and a breakdown of route_origin_country. Excel, Power BI or Tableau.

  • Why do the 18 express rows have a mean carbon_breakdown_transport_kg of 166.1?

    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 transactions with transaction_datetime, customer_id and product_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 25 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset120 rows25 columns
Yours1,000 rows25 columnsroute_origin_city: UK only

blueprint · e-commerce-transaction-carbon-impact

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
  • Each transaction includes product category, weight, packaging type, delivery method, logistics distance, and calculated CO2e emissions.
  • Packaging types have distinct emission factors applied to overall footprint.
  • Delivery methods (bike, van, drone, EV) influence logistics emissions.
  • Orders with multiple products aggregate weights and adjust carbon calculation.
  • Exclude any basic sales or financial metrics; focus exclusively on carbon-related features.
Rows
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
e-commerce-transaction-carbon-impact

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