Factory Carbon Benchmark Scorecard
This dataset provides detailed carbon emissions and benchmarking metrics for small and medium manufacturing facilities, enabling ESG officers and operations managers to track, compare, and report carbon reduction progress against operational benchmarks. It supports cross-plant analysis, peer group comparisons, and performance scorecards, making it ideal for sustainability reporting and improvement planning.
Sample rows
preview · 8 of 75 rows · all 24 columns| factory_idstring | industry_sectorstring | scorecard_ratingfloat | address_countrystring | factory_namestring | address_streetstring | address_citystring | address_statestring | address_postal_codestring | reporting_period_startdate | reporting_period_enddate | total_carbon_emissions_tonnesfloat | carbon_emissions_scope1_tonnesfloat | carbon_emissions_scope2_tonnesfloat | carbon_emissions_scope3_tonnesfloat | production_output_unitsfloat | carbon_intensity_per_unitfloat | benchmark_groupstring | benchmark_carbon_intensity_per_unitfloat | carbon_reduction_target_tonnesfloat | carbon_reduction_achieved_tonnesfloat | esg_officer_namestring | esg_officer_emailstring | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TXE-001 | textiles | 85.2 | United States | Texel Loomworks | 45 Industrial Ave | Greenville | TX | 75401 | 2023-01-01 | 2023-03-31 | 187.4 | 53.1 | 112.4 | 21.9 | 48000 | 0.0039 | Southwest textiles | 0.0045 | 20 | 18 | Linda Carter | lcarter@ | Implemented high-efficiency boiler in Q1 |
| ELC-101 | electronics | 91.7 | United States | Electra Components | 890 Silicon Dr | San Mateo | CA | 94403 | 2022-10-01 | 2022-12-31 | 276.8 | 67 | 187.8 | 22 | 152000 | 0.0018 | California electronics | 0.002 | 30 | 32 | Tom Pineda | tpineda@ | blank |
| FPS-208 | food processing | 77.5 | United States | FreshPack Foods | 312 Orchard Rd | Akron | OH | 44307 | 2023-04-01 | 2023-06-30 | 144.1 | 40.2 | 89.9 | 14 | 51000 | 0.0028 | Midwest food | 0.0032 | 15 | 12.5 | Kathy Lin | klin@ | Seasonal spike due to heating demand |
| TXE-002 | textiles | 82.6 | United States | Lone Star Textiles | 226 W Cotton St | Tyler | TX | 75702 | 2022-07-01 | 2022-09-30 | 165.3 | 47 | 99.8 | 18.5 | 41000 | 0.004 | Southwest textiles | 0.0043 | 17 | 16.2 | Jose Mendez | jmendez@ | blank |
| ELC-102 | electronics | 88.5 | United States | Pinnacle Circuits | 15 Ridgeway Blvd | Austin | TX | 78701 | 2023-04-01 | 2023-06-30 | 215.6 | 56 | 149.6 | 10 | 113000 | 0.0019 | Texas electronics | 0.0021 | 22 | 20 | Raymond Yu | ryu@ | Solar panels commissioned mid-period |
| FPS-209 | food processing | 75.1 | United States | Spring Harvest Foods | 770 Maple Dr | Madison | WI | 53703 | 2022-10-01 | 2022-12-31 | 121.7 | 34.8 | 73.9 | 13 | 38000 | 0.0032 | Great Lakes food | 0.0034 | 12 | 10 | Francis Dalton | fdalton@ | blank |
| TXE-003 | textiles | 79.4 | United States | Panhandle Weavers | 701 Lone Rd | Amarillo | TX | 79101 | 2023-07-01 | 2023-09-30 | 101.6 | 29.1 | 58.3 | 14.2 | 25000 | 0.0041 | Southwest textiles | 0.0047 | 10 | 7.5 | Marsha O'Brien | mobrien@ | New dyeing process reduced Scope 1 |
| ELC-103 | electronics | 93 | United States | Sunrise Microfab | 4 Innovation Pkwy | Phoenix | AZ | 85003 | 2023-01-01 | 2023-03-31 | 139.2 | 45.1 | 87.1 | 7 | 86000 | 0.0016 | Arizona electronics | 0.0019 | 14 | 15 | Jill Sanderson | jsanderson@ | blank |
| FPS-210 | food processing | 80.6 | United States | Green Valley Foods | 1200 Spruce St | St. Louis | MO | 63103 | 2022-01-01 | 2022-03-31 | 188 | 53 | 120 | 15 | 67000 | 0.0028 | Midwest food | 0.003 | 21 | 19.9 | Janet Crenshaw | jcrenshaw@ | Expanded cold storage in Q1 |
| TXE-004 | textiles | 77.8 | United States | Bluebonnet Mills | 3202 River Rd | Waco | TX | 76708 | 2022-04-01 | 2022-06-30 | 132.4 | 38.3 | 75.9 | 18.2 | 31000 | 0.0043 | Southwest textiles | 0.0045 | 9 | 8 | Erica Washington | ewashington@ | blank |
| ELC-104 | electronics | 89 | United States | Canyon Tech | 2110 Saguaro Ct | Tucson | AZ | 85716 | 2022-07-01 | 2022-09-30 | 118.3 | 37.1 | 76.2 | 5 | 69000 | 0.0017 | Arizona electronics | 0.0019 | 10 | 9.5 | Rachel Perez | rperez@ | blank |
| FPS-211 | food processing | 76.2 | United States | Harvest Circle | 5214 Wheatland Ave | Boise | ID | 83709 | 2023-07-01 | 2023-09-30 | 99.7 | 28.8 | 62.9 | 8 | 29000 | 0.0034 | Mountain West food | 0.0036 | 8 | 7 | Brian McCoy | bmccoy@ | Shorter reporting period due to renovations |
| TXE-005 | textiles | 80.1 | United States | Rio Grande Textiles | 1860 Valley Rd | McAllen | TX | 78501 | 2023-10-01 | 2023-12-31 | 166.8 | 41.6 | 103.9 | 21.3 | 38000 | 0.0044 | Southwest textiles | 0.0045 | 15 | 15.5 | Diana Martinez | dmartinez@ | Target exceeded due to process optimization |
| ELC-105 | electronics | 92 | United States | Mesa Electronix | 505 Desert Ave | Mesa | AZ | 85210 | 2023-07-01 | 2023-09-30 | 127.5 | 32.6 | 89.2 | 5.7 | 71000 | 0.0018 | Arizona electronics | 0.002 | 12 | 13 | Anita Singh | asingh@ | blank |
| FPS-212 | food processing | 82.3 | United States | Riverbend Foods | 399 Riverfront Dr | Memphis | TN | 38103 | 2023-01-01 | 2023-03-31 | 135.6 | 37.9 | 85.2 | 12.5 | 46000 | 0.0029 | Southeast food | 0.0031 | 13 | 11 | Elliot Parks | eparks@ | Increased output from automation |
| TXE-006 | textiles | 76.4 | United States | Sunset Spinners | 88 Sunrise Ln | El Paso | TX | 79901 | 2022-04-01 | 2022-06-30 | 120.9 | 31 | 79.6 | 10.3 | 30500 | 0.004 | Southwest textiles | 0.0046 | 10 | 8.1 | Victor Herrera | vherrera@ | blank |
| ELC-106 | electronics | 90.5 | United States | CircuitVibe | 3200 Tech Loop | Tempe | AZ | 85281 | 2022-10-01 | 2022-12-31 | 144.9 | 43.8 | 96.1 | 5 | 81000 | 0.0018 | Arizona electronics | 0.002 | 13 | 12 | Derek Lin | dlin@ | Scope 3 not fully reported |
| FPS-213 | food processing | 78.9 | United States | Pioneer Foods | 88 Pioneer Way | Omaha | NE | 68102 | 2023-04-01 | 2023-06-30 | 146.3 | 39.5 | 91.8 | 15 | 50000 | 0.0029 | Midwest food | 0.0032 | 14 | 13.1 | Teresa Ford | tford@ | blank |
| TXE-007 | textiles | 75.7 | United States | Alamo Fabrics | 182 Mission St | San Antonio | TX | 78205 | 2022-01-01 | 2022-03-31 | 112.1 | 28.7 | 74.8 | 8.6 | 27000 | 0.0042 | Southwest textiles | 0.0044 | 8 | 7 | Miguel Estrada | mestrada@ | blank |
| ELC-107 | electronics | 90 | United States | MicroSpark Labs | 1110 Spark Dr | Scottsdale | AZ | 85251 | 2023-04-01 | 2023-06-30 | 102.2 | 29.1 | 68.1 | 5 | 56000 | 0.0018 | Arizona electronics | 0.002 | 9 | 8 | Casey Jamison | cjamison@ | blank |
What the 75 rows show
from the 75-row sampleElectronics (industry sector) stands out: mean scorecard_
- 81.7median scorecard_
rating - 655.1median total_
carbon_ emissions_ tonnes - 269.4median carbon_
emissions_ scope1_ tonnes - 358.7median carbon_
emissions_ scope2_ tonnes - 25.7median carbon_
emissions_ scope3_ tonnes - 137,000median production_
output_ units
Median 81.7, from 64.2 to 93.0.
- string 12
- float 10
- date 2
Columns
24 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 12 columns | |||
factory_id | string | Unique identifier for each manufacturing facilityunique | TXE-001 |
factory_name | string | Official name of the manufacturing facility | Texel Loomworks |
industry_sector | string | Industry sector classification of the facility (e.g., textiles, electronics, food processing)6 sectors | textiles |
address_street | string | Street address of the facility | 45 Industrial Ave |
address_city | string | City where the facility is located | Greenville |
address_state | string | State or province of the facility | TX |
address_postal_code | string | Postal code of the facility | 75401 |
address_country | string | Country where the facility is located | United States |
benchmark_group | string | Benchmark group or peer cluster for comparison (e.g., region, sector, size class) | Southwest textiles |
esg_officer_name | string | Name of the ESG officer responsible for reportingoptional | Linda Carter |
esg_officer_email | string | Contact email of the ESG officeroptional | lcarter@ |
notes | string | Additional notes or comments for the reporting periodoptional | LED lighting upgrades |
| Numbers 10 columns | |||
total_carbon_emissions_tonnes | float | Total carbon emissions for the reporting period, measured in metric tonnes CO2e0 or more | 187.4 |
carbon_emissions_scope1_tonnes | float | Direct emissions (Scope 1) for the reporting period, in metric tonnes CO2e0 or more | 53.1 |
carbon_emissions_scope2_tonnes | float | Indirect emissions from purchased energy (Scope 2), in metric tonnes CO2e0 or more | 112.4 |
carbon_emissions_scope3_tonnes | float | Other indirect emissions (Scope 3), in metric tonnes CO2e0 or more · optional | 21.9 |
production_output_units | float | Total production output during the reporting period (in facility-specific units)0 or more | 48000 |
carbon_intensity_per_unit | float | Carbon emissions per unit of production (tonnes CO2e per unit)0 or more | 0.0039 |
benchmark_carbon_intensity_per_unit | float | Benchmark carbon intensity per unit for the peer group (tonnes CO2e per unit)0 or more | 0.0045 |
carbon_reduction_target_tonnes | float | Carbon reduction target for the reporting period (tonnes CO2e)0 or more · optional | 20 |
carbon_reduction_achieved_tonnes | float | Actual carbon reduction achieved during the reporting period (tonnes CO2e)0 or more · optional | 18 |
scorecard_rating | float | Benchmark scorecard rating (e.g., percentile or normalized score)0 to 100 | 85.2 |
| Dates and times 2 columns | |||
reporting_period_start | date | Start date of the carbon reporting period | 2023-01-01 |
reporting_period_end | date | End date of the carbon reporting period | 2023-03-31 |
Use it for
A manufacturing dashboard
Scorecard_
rating by industry_ sector and a breakdown of address_ country. Excel, Power BI or Tableau. Why do the 18 electronics rows have a mean scorecard_
rating of 88.2? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Factories75TXE-00185.2textilesELC-10191.7electron…FPS-20877.5food pro…
A software demo
Believable factories with factory_
name, industry_ sector and address_ street to fill a screen in front of a buyer.
This dataset75 rows24 columns
Yours1,000 rows24 columnsaddress_street: UK only
blueprint · factory-carbon-benchmark-scorecard
Behind this dataset
Same schema. As many rows as you need.
These 75 rows came out of a blueprint — 24 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 factory with unique identifier
- Monthly total CO2e emissions must be recorded
- Include primary manufacturing process category (e.g., machining, assembly)
- Benchmark score calculated by emissions per production unit
- Flag for facilities with implemented emission reduction technology
- Mandatory reporting of most recent carbon audit year
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
- factory-carbon-benchmark-scorecard