GHG Protocol: Data Requirements - Dcycle API Documentation

Use this guide as a reference when planning your data integration with Dcycle. For each emission category, we list the exact fields Dcycle needs, the typical source systems where that data lives, and the recommended integration method.

Who is this for?This guide is designed for IT and data engineering teams who are planning how to feed data into Dcycle — whether through APIs, bulk CSV uploads, or PDF/OCR processing. Share it with your technical team so they can map their internal data sources to Dcycle’s requirements.

How Dcycle Fits in Your Data Architecture

Dcycle acts as a data processing and calculation engine that sits between your raw data sources and your environmental reporting outputs. You send us raw or semi-structured data, and we handle normalization, enrichment, calculation, and reporting.

┌─────────────────────────────────────────────────────────────────────────────────────────┐
│                          YOUR DATA ARCHITECTURE                                         │
├─────────────────────────────────────────────────────────────────────────────────────────┤
│                                                                                         │
│   DATA SOURCES              DCYCLE                           YOUR OUTPUTS               │
│   ────────────              ──────                           ────────────               │
│                                                                                         │
│   ERP (SAP, Navision...)    ┌─────────────────────────┐                                 │
│   Fuel cards         ──────►│  Ingestion (API / CSV)  │                                 │
│   Utility bills (PDF) ─────►│  OCR & digitization     │     Data Lake (Gold layer)      │
│   Fleet management    ─────►│  Normalization          │──►  Power BI / dashboards       │
│   Travel booking      ─────►│  Enrichment (geocoding, │     Regulatory reports           │
│   HR systems          ─────►│   supplier lookup, etc) │     CSRD / EINF                 │
│   Waste managers      ─────►│  Emission calculation   │     Science-Based Targets       │
│                             │  Quality validation     │                                 │
│                             └─────────────────────────┘                                 │
│                                                                                         │
│   What Dcycle adds automatically:                                                       │
│   • OCR for PDF invoices (electricity, fuel, water)                                    │
│   • Geocoding for logistics (origin/destination → km)                                  │
│   • Supplier enrichment (company name → CNAE/SIC sector code)                          │
│   • Emission factor selection (country + fuel + year → correct EF)                     │
│   • Dual Scope 2 calculation (location-based + market-based)                           │
│   • Scope 3 Cat. 3 (fuel & energy related) — fully automatic from Scope 1 & 2 data    │
│   • Data quality alerts (missing fields, anomalies, outliers)                          │
│                                                                                         │
└─────────────────────────────────────────────────────────────────────────────────────────┘

You don’t need to clean or transform data before sending it to Dcycle.Send us the rawest data you have — PDFs, CSVs from your ERP, fuel card exports. Dcycle handles OCR, normalization, unit conversion, and emission factor matching. This means your Data Lake integration can sit after Dcycle: pull the enriched, calculated results back via our APIs into your Gold layer.

Integration Methods

Dcycle supports four ways to ingest data. Choose the one that best fits each data source:

Method	Best for	Automation	Setup effort
REST API	ERP integrations, real-time data feeds, programmatic access	Full	Medium
Bulk CSV upload	Periodic data dumps, spreadsheet-based workflows	Semi-auto	Low
PDF / file upload	Invoices, utility bills, fuel receipts	Full (OCR)	Low
Manual entry (App)	One-off data, qualitative estimates, small datasets	Manual	None

Recommended approach for data lake architectures:

Configure your Bronze layer ingestion to collect raw data from source systems
Send that raw data to Dcycle via API or CSV (no cleaning needed)
Pull enriched + calculated results from Dcycle’s APIs back into your Gold layer
Build dashboards and reports on top of the Gold layer

This way Dcycle handles all the Silver-layer transformations (OCR, normalization, enrichment, calculation) and you retain full control of the data in your own infrastructure.

Scope 1: Direct Emissions

Stationary Combustion (Fuel Invoices)

Emissions from burning fuels in fixed equipment: boilers, furnaces, generators, heaters.

📋 Data Fields

Field	Type	Required	Description	Example
`type`	string	✅	`"heat"`	`"heat"`
`facility_id`	UUID	✅	Facility where fuel is consumed	From facility setup
`facility_fuel_id`	UUID	✅	Fuel type linked to facility	From `GET /facility_fuels/{facility_id}`
`base_quantity`	number	✅	Amount consumed	`5000`
`unit_id`	UUID	✅	Unit (m³, kWh, kg, liters)	From `GET /units`
`start_date`	date	✅	Consumption period start	`"2024-01-01"`
`end_date`	date	✅	Consumption period end	`"2024-01-31"`
`invoice_id`	string	✅	Your internal reference	`"INV-2024-001"`
`uploaded_by`	UUID	✅	User uploading	User UUID
`custom_emission_factor_id`	UUID	❌	Override default EF	Custom EF UUID

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Natural gas consumption	Gas utility invoices (PDF or digital)	Monthly billing with m³ or kWh
Diesel/gasoil for generators	Fuel delivery receipts, tank readings	Periodic deliveries in liters
LPG/propane	Supplier invoices	Delivery amounts in kg or liters
Fuel oil	Supplier invoices	Bulk deliveries in liters or tonnes

Automation options:

PDF upload → Dcycle OCR extracts consumption, dates, and amounts automatically
API → Push structured data from your ERP or utility data aggregator
CSV → Bulk upload monthly consumption records

⚡ What Dcycle Calculates Automatically

Selects correct emission factors based on facility country (MITECO for Spain, IPCC for others)
Applies fuel-specific factors for CO₂, CH₄, and N₂O
Converts to CO₂e using IPCC AR6 GWP values
Handles unit conversions (e.g., m³ → kWh using calorific values)

Refrigerant Recharges (Fugitive Emissions)

Leaks of high-GWP refrigerants from HVAC and cooling systems.

📋 Data Fields

Field	Type	Required	Description	Example
`type`	string	✅	`"recharge"`	`"recharge"`
`facility_id`	UUID	✅	Facility with equipment	Facility UUID
`facility_fuel_id`	UUID	✅	Refrigerant type (R-410A, R-134a…)	From facility fuels
`base_quantity`	number	✅	Amount recharged (= leaked)	`15`
`unit_id`	UUID	✅	Unit (typically kg)	kg UUID
`start_date`	date	✅	Recharge date	`"2024-03-15"`
`end_date`	date	✅	Same as start	`"2024-03-15"`
`invoice_id`	string	✅	Service invoice reference	`"RECHARGE-001"`
`uploaded_by`	UUID	✅	User uploading	User UUID

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Recharge amounts	HVAC maintenance invoices	Amount refilled = amount leaked
Refrigerant type	Equipment register, maintenance contracts	R-410A, R-404A, R-134a, etc.
Equipment inventory	Facilities/maintenance system	List of all cooling units

Automation options:

API → Push from CMMS (computerized maintenance management system)
CSV → Annual or quarterly recharge register
Manual → Enter from HVAC service reports

Mobile Combustion (Company Vehicles)

Fuel consumed by company-owned or controlled vehicles.

📋 Data Fields — Vehicle Registration

Field	Type	Required	Description	Example
`name`	string	✅	Vehicle identifier	`"Delivery Truck 01"`
`type`	string	✅	Vehicle category	`"truck"`, `"car"`, `"van"`
`license_plate`	string	✅	License plate	`"1234ABC"`
`country`	string	✅	Registration country (ISO)	`"ES"`
`vehicle_fuel_id`	UUID	✅	Fuel type	From `GET /vehicle_fuels`
`ownership`	string	✅	`"owned"` or `"rented"`	`"owned"`

📋 Data Fields — Fuel Consumption

Field	Type	Required	Description	Example
`vehicle_license_plate`	string	✅	Identifies the vehicle	`"1234ABC"`
`start_date_recharge`	date	✅	Period start	`"2024-01-01"`
`end_date_recharge`	date	✅	Period end	`"2024-01-31"`
`quantity`	number	✅	Fuel amount	`450`
`unit_measure`	string	✅	`"l"` (liters) or `"km"`	`"l"`
`organization_id`	UUID	✅	Organization	Org UUID

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Vehicle register	Fleet management system, vehicle leasing contracts	Make, model, fuel type, plate
Fuel consumption	Fuel cards (Solred, Repsol, Cepsa…), expense reports	Liters per vehicle per period
Kilometers	Odometer readings, GPS/telematics	For distance-based calculation
EV charging	Charging station data, electricity bills	kWh consumed per vehicle

Automation options:

CSV → Monthly fuel card export (license plate + liters + dates)
API → Push from fleet management or telematics systems
Manual → Enter from fuel receipts

Waste Water Treatment

CH₄ and N₂O from on-site wastewater treatment facilities.

📋 Data Fields (Daily Records)

Field	Type	Required	Description	Example
`facility_id`	UUID	✅	WWT facility	Facility UUID
`name`	string	✅	Record identifier	`"WWT-2024-01-01"`
`measurement_date`	date	✅	Measurement date	`"2024-01-01"`
`m3_water_in`	number	✅	Daily influent (m³)	`10000`
`m3_water_out`	number	✅	Daily effluent (m³)	`9500`
`kg_bod_per_m3_wwt_line`	number	✅	BOD concentration	`0.25`
`kg_n_per_m3_wwt_line`	number	✅	Nitrogen concentration	`0.04`
`kg_sludge`	number	✅	Sludge produced (kg)	`500`
`kg_bod_per_kg_sludge_line`	number	✅	BOD in sludge	`0.6`
`kg_bod_per_m3_wwd_line`	number	✅	BOD in discharge	`0.02`
`kg_n_per_m3_wwd_line`	number	✅	Nitrogen in discharge	`0.01`
`m3_biogas_engine`	number	❌	Biogas to engine (m³)	`200`
`m3_biogas_flare`	number	❌	Biogas flared (m³)	`50`
`m3_biogas_boiler`	number	❌	Biogas to boiler (m³)	`100`

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Flow data	SCADA systems, flow meters	Inlet/outlet m³ per day
BOD/Nitrogen	Laboratory analyses, online sensors	mg/L converted to kg/m³
Sludge	Weighing systems, sludge removal records	kg per day
Biogas	Gas meters on digesters/engines/flares	m³ per day

Automation options:

API → Push daily records from SCADA/PLC systems
CSV → Bulk upload from laboratory information system (LIMS)

Process Emissions

Emissions from industrial chemical/physical transformations (not from combustion).

📋 Data Fields

Field	Type	Required	Description	Example
`type`	string	✅	`"process"`	`"process"`
`facility_id`	UUID	✅	Facility with the process	Facility UUID
`facility_fuel_id`	UUID	✅	Process source	Process fuel UUID
`base_quantity`	number	✅	Emission quantity	`250`
`unit_id`	UUID	✅	Unit (typically kg)	kg UUID
`start_date`	date	✅	Period start	`"2024-01-01"`
`end_date`	date	✅	Period end	`"2024-03-31"`
`custom_emission_factor_id`	UUID	⚠️	Often required for processes	Custom EF UUID

Typical sources: Environmental permits, production records, mass balance calculations.

Scope 2: Purchased Energy

Electricity

📋 Data Fields

Field	Type	Required	Description	Example
`type`	string	✅	`"electricity"`	`"electricity"`
`facility_id`	UUID	✅	Facility consuming electricity	Facility UUID
`base_quantity`	number	✅	kWh consumed	`10000`
`unit_id`	UUID	✅	kWh unit	`"ba80e6cb-..."`
`start_date`	date	✅	Billing period start	`"2024-01-01"`
`end_date`	date	✅	Billing period end	`"2024-01-31"`
`supplier_id`	UUID	❌	Electricity supplier (Spain: enables CNMC market-based)	Supplier UUID
`custom_emission_factor_id`	UUID	❌	Custom EF (non-Spain: enables market-based)	Custom EF UUID
`invoice_id`	string	❌	Your reference	`"ELEC-2024-001"`
`uploaded_by`	UUID	✅	User uploading	User UUID

🏢 Typical Data Sources

Data	Where it typically lives	Notes
kWh consumed	Electricity bills (PDF), smart meters, utility portals	Monthly billing cycle
Supplier name	Electricity contract	Needed for market-based in Spain
Billing period	Invoice dates	Start and end of billing cycle

Automation options:

PDF upload → Dcycle OCR extracts kWh, dates, and supplier from electricity bills
Datadis (Spain) → Automatic import from smart meters via Datadis integration
API → Push from energy management system or building management system (BMS)
CSV → Bulk upload monthly readings across facilities

⚡ What Dcycle Calculates Automatically

Dual calculation: Both location-based and market-based are computed simultaneously
Location-based: Uses country grid EF (Ecoinvent for global, REE for Spain)
Market-based (Spain): Uses CNMC supplier-specific EFs when supplier_id is provided
Market-based (other): Uses your custom EF when custom_emission_factor_id is provided
Scope 3 Cat. 3: Well-to-tank and T&D losses are auto-calculated from the same data

District Heating / Cooling

📋 Data Fields

Field	Type	Required	Description	Example
`type`	string	✅	`"district_heating"` or `"district_cooling"`	`"district_heating"`
`facility_id`	UUID	✅	Facility receiving the service	Facility UUID
`facility_fuel_id`	UUID	✅	Heating/cooling fuel type	Fuel UUID
`base_quantity`	number	✅	Energy consumed (kWh or MJ)	`5000`
`unit_id`	UUID	✅	kWh or MJ	Unit UUID
`start_date`	date	✅	Service period start	`"2024-01-01"`
`end_date`	date	✅	Service period end	`"2024-03-31"`

Typical sources: District heating/cooling provider invoices, BMS.

Scope 3: Value Chain Emissions

Category 1: Purchased Goods and Services

Typically 40-80% of total emissions. Three calculation methods available depending on your data quality.

📋 Data Fields — Spend-Based (fastest to start)

Field	Type	Required	Description	Example
`description`	string	❌	Purchase description	`"IT consulting Q1"`
`sector`	string	✅	Exiobase economic sector	`"Computer programming, consultancy"`
`product_name`	string	✅	Product/service name	`"Computer programming services"`
`quantity`	number	✅	Monetary value (€)	`15000`
`unit_id`	UUID	✅	Currency unit (€)	EUR unit UUID
`country`	string	✅	Supplier country (ISO)	`"ES"`
`purchase_date`	date	✅	Purchase date	`"2024-03-15"`
`purchase_type`	string	✅	`"spend_based"`	`"spend_based"`
`supplier_id`	UUID	❌	Linked supplier	Supplier UUID

Accuracy: ±50-100%. Use as a starting point, then improve high-impact categories.

📋 Data Fields — Activity-Based (higher accuracy)

Field	Type	Required	Description	Example
`sector`	string	✅	Product sector	`"Manufacture of basic metals"`
`product_name`	string	✅	Specific product	`"Aluminium and aluminium products"`
`quantity`	number	✅	Physical quantity	`1000`
`unit_id`	UUID	✅	Physical unit (kg, m³, etc.)	kg unit UUID
`country`	string	✅	Country of origin	`"ES"`
`purchase_date`	date	✅	Purchase date	`"2024-03-15"`
`purchase_type`	string	✅	`"activity_based"`	`"activity_based"`
`supplier_id`	UUID	❌	Linked supplier	Supplier UUID
`recycled`	number	❌	Recycled content (0-1)	`0.3`

Accuracy: ±20-40%. Requires physical quantities from procurement records.

📋 Data Fields — Supplier-Specific (highest accuracy)

Field	Type	Required	Description	Example
`quantity`	number	✅	Physical quantity	`1000`
`unit_id`	UUID	✅	Physical unit	kg unit UUID
`purchase_date`	date	✅	Purchase date	`"2024-03-15"`
`supplier_id`	UUID	✅	Linked supplier	Supplier UUID
`custom_emission_factor_id`	UUID	✅	From supplier EPD/PCF	Custom EF UUID

Accuracy: ±5-15%. Requires Environmental Product Declarations (EPDs) or Product Carbon Footprints from suppliers.

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Spend by category	ERP (SAP, Navision, A3…), accounts payable	€ per supplier per category
Physical quantities	Delivery notes, bills of materials, inventory systems	kg, m³, units
Supplier details	ERP vendor master, procurement system	Company name, country, tax ID
Supplier CNAE/SIC code	Company registry, Dcycle auto-enriches from company name	Needed for sector classification
EPDs / PCFs	Supplier sustainability reports, EPD databases	For supplier-specific method

Automation options:

CSV → Export from ERP: supplier name + amount + category + date
API → Push from procurement system or accounts payable
Dcycle enrichment → Send supplier name, Dcycle auto-resolves CNAE/SIC sector code

Category 2: Capital Goods

Same data structure as Category 1, but for capital assets (equipment, machinery, buildings).

📋 Key Differences from Category 1

Aspect	Category 1	Category 2
What	Operating expenses, materials	Capital expenditures, fixed assets
Examples	Office supplies, raw materials	Machinery, vehicles (as assets), buildings
Reporting	Same year as purchase	Full in year of purchase, or depreciated
Data source	Operating purchase orders	Capital investment records, asset register

Same API and fields as Category 1 — the classification is done by your accounting team.

Fully automatic — no additional data needed.Dcycle calculates Category 3 (well-to-tank emissions for fuels, upstream electricity, T&D losses) automatically from your Scope 1 and Scope 2 data. Just ensure complete fuel and electricity data.

Category 4 & 9: Upstream and Downstream Transportation

Emissions from transporting goods to/from your facilities.

📋 Data Fields — Logistics Shipments

Field	Type	Required	Description	Example
`origin`	string	✅	Origin address or city	`"Madrid, Spain"`
`destination`	string	✅	Destination address or city	`"Barcelona, Spain"`
`weight`	number	✅	Shipment weight (kg)	`500`
`transport_mode`	string	✅	Mode of transport	`"road"`, `"rail"`, `"air"`, `"sea"`
`vehicle_type`	string	❌	Specific vehicle type	`"articulated_truck"`
`date`	date	✅	Shipment date	`"2024-03-15"`
`client_reference`	string	❌	Your shipment reference	`"SHIP-2024-001"`

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Shipment details	TMS (transport management system), logistics ERP	Origin, destination, weight
Carrier/mode	Shipping contracts, carrier invoices	Road, rail, air, sea
Distances	Dcycle auto-calculates from origin/destination	No need to provide km
Supplier deliveries	Purchase orders with delivery addresses	For upstream (Cat. 4)
Customer deliveries	Sales orders with shipping addresses	For downstream (Cat. 9)

Automation options:

CSV → Export from TMS: origin + destination + weight + mode + date
API → Real-time push from logistics/shipping system
Dcycle enrichment → Auto-geocodes addresses and calculates distances

Category 5: Waste Generated in Operations

📋 Data Fields

Field	Type	Required	Description	Example
`facility_id`	UUID	✅	Facility generating waste	Facility UUID
`waste_code`	string	✅	LER code (European List of Waste)	`"150101"` (paper/cardboard)
`quantity`	number	✅	Waste amount	`500`
`unit_id`	UUID	✅	Unit (kg or tonnes)	kg UUID
`treatment_code`	string	✅	R-code (recovery) or D-code (disposal)	`"R03"` (recycling)
`start_date`	date	✅	Period start	`"2024-01-01"`
`end_date`	date	✅	Period end	`"2024-03-31"`
`waste_manager_name`	string	❌	Treatment company	`"Waste Co S.L."`
`transport_distance`	number	❌	Distance to treatment (km)	`50`

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Waste type (LER code)	Waste manager reports, regulatory filings	6-digit European waste codes
Quantities	Weighing records, waste collection receipts	kg or tonnes per period
Treatment method	Waste manager certificates, transfer notes	R01-R13 or D01-D15 codes
Transport distance	Waste manager contract, facility locations	km to treatment plant

Automation options:

CSV → Quarterly waste register from waste manager
API → Push from environmental management system
Manual → Enter from waste collection certificates (quarterly/annual)

Category 6: Business Travel

📋 Data Fields

Field	Type	Required	Description	Example
`origin`	string	✅	Departure city/airport	`"Madrid"`
`destination`	string	✅	Arrival city/airport	`"London"`
`transport_type`	string	✅	Travel mode	`"flight"`, `"train"`, `"rental_car"`
`distance`	number	❌	Distance in km (auto-calculated if not provided)	`1260`
`flight_class`	string	❌	Cabin class (for flights)	`"economy"`, `"business"`
`round_trip`	boolean	❌	Return included	`true`
`start_date`	date	✅	Travel date	`"2024-03-15"`
`travelers_count`	number	❌	Number of travelers	`1`

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Flight bookings	Corporate travel agency, booking platform (Amex GBT, BCD…)	Origin, destination, class
Train bookings	Rail booking system, travel agency	Origin, destination
Rental car usage	Rental company reports, expense reports	km driven, fuel type
Hotel stays	Hotel booking platform, expense reports	Nights per city
Expense reports	ERP, expense management tool (SAP Concur, Rydoo…)	May have trip details

Automation options:

CSV → Export from travel booking platform or expense tool
API → Push from corporate travel management system
Manual → Enter from travel itineraries or expense reports

Category 7: Employee Commuting

📋 Data Fields — Employee Setup

Field	Type	Required	Description	Example
`name`	string	✅	Employee name or ID	`"EMP-001"`
`facility_id`	UUID	✅	Office/work location	Facility UUID
`work_regime`	string	✅	Work arrangement	`"on_site"`, `"hybrid"`, `"remote"`
`days_per_week`	number	✅	Days in office per week	`4`

📋 Data Fields — Commuting Periods

Field	Type	Required	Description	Example
`employee_id`	UUID	✅	Employee	Employee UUID
`transport_mode`	string	✅	How they commute	`"car_diesel"`, `"train"`, `"bike"`
`distance_km`	number	✅	One-way distance (km)	`25`
`start_date`	date	✅	Period start	`"2024-01-01"`
`end_date`	date	✅	Period end	`"2024-12-31"`

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Employee list	HR system (SAP HR, Workday, Factorial…)	Name, work location, work regime
Commute details	Employee survey, HR form	Transport mode, distance
Office days	HR system, attendance tracking	Hybrid/remote schedule
Employee home location	HR records (postal code is enough)	For distance estimation

Automation options:

CSV → Export from HR system + survey results
API → Push from HR system
Survey → Use Dcycle’s survey feature (employees fill in commute details)

Category 11: Use of Sold Products

Downstream emissions from the use phase of energy-consuming products your organization sells. Often the largest Scope 3 category for manufacturers of equipment, appliances, or vehicles.

📋 Data Fields — Product & Sales

Field	Type	Required	Description	Example
`name`	string	✅	Product name or family	`"Industrial Compressor X200"`
`start_date`	date	✅	Period start	`"2024-01-01"`
`end_date`	date	✅	Period end	`"2024-12-31"`
`country`	string	✅	Country where sold (ISO)	`"ES"`, `"DE"`, `"FR"`
`quantity`	number	✅	Units sold in that country	`250`
`unit_id`	UUID	✅	Unit of measurement	Unit UUID

📋 Data Fields — Use-Phase Consumption

Field	Type	Required	Description	Example
`lifespan`	number	✅	Product lifespan	`10`
`lifespan_unit_id`	UUID	✅	Temporal unit (day/week/month/year)	Year UUID
`consumes_electricity`	boolean	✅	Does it consume electricity?	`true`
`electricity_quantity`	number	✅*	Amount per frequency	`2400`
`electricity_unit_id`	UUID	✅*	Unit (kWh)	kWh UUID
`electricity_frequency`	enum	✅*	`daily`/`weekly`/`monthly`/`yearly`/`all_life`	`"yearly"`
`consumes_combustion`	boolean	✅	Does it burn fuel?	`false`
`combustion_fuel_id`	UUID	✅*	Fuel type	Natural gas UUID
`combustion_quantity`	number	✅*	Amount per frequency	`1200`
`combustion_unit_id`	UUID	✅*	Unit (liters, m³, kWh)	m³ UUID
`combustion_frequency`	enum	✅*	Frequency	`"yearly"`
`consumes_water`	boolean	✅	Does it consume water?	`false`
`water_quantity`	number	✅*	Amount per frequency	`10`
`water_unit_id`	UUID	✅*	Unit (m³)	m³ UUID
`water_frequency`	enum	✅*	Frequency	`"yearly"`

*Required only when the corresponding consumes_* flag is true.

🏢 Typical Data Sources

Data	Where it typically lives	Notes
Product catalog	PLM, ERP, product management	Product names and families
Units sold by country	ERP, CRM, sales reporting	Quantity per market per period
Product lifespan	Product specs, warranty terms, LCA studies	Expected useful life
Electricity consumption	Product testing, energy labels (EU), spec sheets	kWh per year or per cycle
Fuel consumption	Product testing, performance certificates	Liters/m³ per year
Water consumption	Product testing, water labels	m³ per year or per cycle

Automation options:

CSV → Upload country sales data via Dcycle App
API → Push from ERP/CRM for sales; configure use-phase via API
Manual → Use-phase data typically comes from R&D or product engineering

Company Structure (Prerequisite)

Before loading emission data, configure your organizational hierarchy.

📋 Organization Setup

Field	Type	Required	Description	Example
`company_name`	string	✅	Legal entity name	`"Holding Corp S.A."`
`country`	string	✅	Country (ISO code)	`"ES"`
`sector`	string	❌	Business sector	`"Technology"`
`vat`	string	❌	Tax identification	`"A12345678"`
`employee_count_signup`	number	❌	Number of employees	`200`

📋 Facility Setup

Field	Type	Required	Description	Example
`name`	string	✅	Facility name	`"Madrid HQ"`
`country`	string	✅	Country (ISO code)	`"ES"`
`address`	string	✅	Full address	`"Calle Gran Vía 1, Madrid"`
`type`	string	✅	Facility type	`"office"`, `"warehouse"`, `"factory"`
`surface_m2`	number	❌	Floor area (m²)	`2000`
`fuel_types`	list	✅	Fuels consumed at this facility	Natural gas, diesel, etc.

Required for: All Scope 1 and Scope 2 calculations. Each invoice/consumption record is linked to a facility.

📋 Parent-Child Relationships (Groups)

Field	Type	Required	Description	Example
`share`	number	✅	Ownership percentage (0-1)	`0.75` (75%)
`investment_scopes`	list	✅	Scopes to consolidate	`[1, 2, 3]`
`tag`	string	❌	Relationship type	`"subsidiary"`, `"joint-venture"`
`status`	string	✅	Must be `"accepted"` to consolidate	`"accepted"`

Required for: Multi-entity organizations (holding companies, groups with subsidiaries).

Summary: Data Source Mapping

Use this table to map your internal systems to Dcycle data requirements:

GHG Category	Data Needed	Typical Source	Integration	Dcycle Adds
S1: Stationary combustion	Fuel type + quantity + dates	Utility invoices (PDF), ERP	PDF/API/CSV	EF selection, unit conversion
S1: Refrigerants	Refrigerant type + kg recharged	HVAC maintenance records	CSV/API	GWP lookup
S1: Vehicles	License plate + fuel type + liters/km	Fuel cards, fleet system	CSV/API	EF by fuel and vehicle type
S1: Wastewater	Daily flow + BOD + nitrogen + biogas	SCADA, laboratory (LIMS)	API/CSV	CH₄ + N₂O calculation
S1: Process	Process type + quantity	Production records, permits	API/CSV	Custom EF application
S2: Electricity	kWh + dates + supplier (optional)	Electricity bills, Datadis	PDF/API/CSV	Dual location + market calc
S2: District heat/cool	kWh or MJ consumed	Provider invoices	API/CSV	EF selection
S3.1: Purchases	€ or kg + category + supplier country	ERP, accounts payable	CSV/API	Sector enrichment, EF match
S3.2: Capital goods	Same as S3.1	Asset register, capex records	CSV/API	Same as S3.1
S3.3: Fuel & energy	(automatic from S1 + S2 data)	—	—	Fully automatic
S3.4/9: Transport	Origin + destination + weight + mode	TMS, logistics ERP	CSV/API	Geocoding, km calculation
S3.5: Waste	LER code + kg + treatment method	Waste manager reports	CSV/API	EF by waste + treatment
S3.6: Business travel	Origin + destination + mode + class	Travel agency, expense tool	CSV/API	Distance calc, EF by mode
S3.7: Commuting	Employee + transport mode + km	HR system + survey	CSV/API	EF by mode, work-day calc
S3.11: Use of sold products	Lifespan + energy consumption + units sold by country	Product specs, ERP/CRM sales	CSV/API	Country-specific EF, lifespan calc

Progressive approach: start broad, then deepen

Month 1: Upload PDFs (invoices, bills) + basic CSVs from ERP (purchases, fuel cards)
Month 2-3: Set up API integrations for high-volume data (logistics, vehicles, electricity)
Month 4+: Engage suppliers for EPDs, connect IoT/SCADA for real-time data
Ongoing: Pull calculated results back to your Data Lake via Dcycle APIs

You don’t need 100% automation on day one. Dcycle is designed to work with whatever data format you have today and improve over time.

Next Steps

GHG Protocol Tutorial

Step-by-step implementation guide with API examples

API Reference

Full API documentation for all endpoints

Automation & AI

Set up automated pipelines and multi-org management

Custom Emission Factors

Use supplier EPDs and PCFs for highest accuracy

Documentation Index

​How Dcycle Fits in Your Data Architecture

​Integration Methods

​Scope 1: Direct Emissions

​Stationary Combustion (Fuel Invoices)

​Refrigerant Recharges (Fugitive Emissions)

​Mobile Combustion (Company Vehicles)

​Waste Water Treatment

​Process Emissions

​Scope 2: Purchased Energy

​Electricity

​District Heating / Cooling

​Scope 3: Value Chain Emissions

​Category 1: Purchased Goods and Services

​Category 2: Capital Goods

​Category 3: Fuel and Energy-Related Activities

​Category 4 & 9: Upstream and Downstream Transportation

​Category 5: Waste Generated in Operations

​Category 6: Business Travel

​Category 7: Employee Commuting

​Category 11: Use of Sold Products

​Company Structure (Prerequisite)

​Summary: Data Source Mapping

​Next Steps

GHG Protocol Tutorial

API Reference

Automation & AI

Custom Emission Factors

How Dcycle Fits in Your Data Architecture

Integration Methods

Scope 1: Direct Emissions

Stationary Combustion (Fuel Invoices)

Refrigerant Recharges (Fugitive Emissions)

Mobile Combustion (Company Vehicles)

Waste Water Treatment

Process Emissions

Scope 2: Purchased Energy

Electricity

District Heating / Cooling

Scope 3: Value Chain Emissions

Category 1: Purchased Goods and Services

Category 2: Capital Goods

Category 3: Fuel and Energy-Related Activities

Category 4 & 9: Upstream and Downstream Transportation

Category 5: Waste Generated in Operations

Category 6: Business Travel

Category 7: Employee Commuting

Category 11: Use of Sold Products

Company Structure (Prerequisite)

Summary: Data Source Mapping

Next Steps