11. EPD Data Requirements: What You Need to Collect

Data availability determines whether creating an EPD is straightforward or frustratingly difficult. The Life Cycle Assessment underlying every EPD requires detailed information about materials, energy, transport, and waste across your product’s life cycle. Understanding what data you need before starting data collection prevents discovering critical gaps during LCA modelling.

This guide explains exactly what information EPD creation requires, where that data typically comes from, how detailed it needs to be, and what to do when perfect data doesn’t exist. Whether you’re preparing your first EPD or establishing systematic data collection for ongoing programmes, knowing requirements helps you gather appropriate information efficiently.

The good news: if you track production for cost accounting, you already have much of what you need. The challenge: supply chain data often sits with suppliers who may be reluctant to share, and life cycle stages beyond your factory gate require assumptions or scenarios.

Data Categories Overview#

EPD data requirements fall into several categories based on life cycle modules:

Manufacturing data (Module A3) covers processes you control directly. This is usually the easiest data to obtain because you have direct access.

Supply chain data (Module A1-A2) tracks materials and their upstream impacts. This ranges from straightforward (commodity materials with database values) to challenging (custom components from protective suppliers).

Transport data appears in multiple modules: A2 (to your facility), A4 (to construction site), C2 (to disposal). Transport scenarios often need assumptions because you don’t control where products ultimately go.

Use stage data (Module B) depends on how products perform in buildings. Some is technical specification (durability, maintenance needs). Some requires scenarios (replacement intervals, cleaning requirements).

End-of-life data (Module C-D) is almost entirely scenario-based. You rarely know what happens to products decades after installation.

The PCR for your product category specifies exactly what’s required versus optional. Always check PCR requirements before collecting data.

Manufacturing Data: What You Control Directly#

Module A3 captures your manufacturing process. You need detailed information about inputs, outputs, and environmental releases.

Energy Consumption#

What’s needed:

• Total energy consumption by type (electricity, natural gas, diesel, fuel oil, LPG, etc.)
• Reported per unit of production output
• Preferably annual data to average seasonal variations

Level of detail: Good: “Manufacturing uses 250 kWh electricity and 30 m³ natural gas per tonne of product” Better: “Electricity consumption: 150 kWh process equipment, 50 kWh building heating/cooling, 30 kWh lighting, 20 kWh compressed air per tonne”

Detailed breakdowns help identify improvement opportunities but aren’t always essential for EPDs. The total matters most, though understanding major energy consumers aids future optimisation.

Where this data comes from:

• Utility bills (but you need production volumes to calculate per-unit values)
• Sub-metering if available
• Process specifications if measured data unavailable

Common problems: Energy gets measured for whole facilities but you produce multiple products. You’ll need allocation approaches (by mass, by line time, by floor area) to divide energy between products. Document your allocation logic because verifiers will check it.

Material Inputs#

What’s needed:

• Complete bill of materials with quantities per functional unit
• Material specifications (type, grade, purity, etc.)
• Origin information if relevant (domestic versus imported, recycled content percentage)

Level of detail: For a concrete product, you need cement quantity and type, aggregate types and quantities, water content, admixture specifications and amounts, and any supplementary materials.

For a manufactured product, you need specifications for all significant components and materials. “Significant” typically means contributing more than 1% by mass or environmental impact.

Where this data comes from:

• Production records and bills of materials
• Procurement systems
• Quality control specifications
• Supplier declarations for purchased components

Material specifications matter. “Steel” isn’t specific enough. You need whether it’s virgin or recycled, what grade, what production route (electric arc furnace versus blast furnace). These details affect upstream impacts significantly.

Water Consumption#

What’s needed:

• Process water consumption per unit of production
• Cooling water (if not returned to source)
• Cleaning and auxiliary water use

Level of detail: Total freshwater consumption usually suffices unless the PCR requires detailed breakdown. Distinguish between water consumption (water leaving the system through evaporation or incorporation into product) and water use (water returned to source after use).

Common issues: Water comes from municipal supply without sub-metering. You’ll estimate based on process requirements or allocate from total facility consumption.

Waste Generation#

What’s needed:

• Waste quantities by type (hazardous, non-hazardous, recyclable)
• Treatment methods (recycled, incinerated with or without energy recovery, landfilled)
• Percentages going to each treatment route

Level of detail: “We generate 50 kg waste per tonne of product: 30 kg recycled steel scrap, 15 kg general waste to landfill, 5 kg packaging sent for recycling” provides adequate detail.

Where this data comes from: Waste disposal records, particularly if you pay by weight or volume. Many facilities track waste for cost control or environmental reporting.

Direct Process Emissions#

What’s needed:

• Emissions directly from manufacturing processes (not from energy combustion)
• Examples: CO₂ from cement calcination, VOCs from coating application, methane from biological processes

Level of detail: If your process involves chemical reactions releasing greenhouse gases, you need stoichiometric calculations or measurements. For many products, direct process emissions are negligible or captured through energy and material accounting.

When this matters: Cement, lime, ceramics, and other products with thermal decomposition reactions have significant process emissions. Chemical manufacturing may release specific substances requiring direct measurement or calculation.

Packaging#

What’s needed:

• Primary packaging quantities and materials (product packaging)
• Secondary packaging for shipping (pallets, wrapping, etc.)
• Tertiary packaging if relevant

Level of detail: “Each unit packaged in 0.5 kg LDPE film and corrugated cardboard box (1.2 kg), shipped on wooden pallets (15 kg pallet per 50 units)” provides sufficient detail.

Packaging often gets overlooked in initial data collection but EN 15804 requires including it in Module A3. Add packaging to your data collection checklist.

Supply Chain Data: Upstream Materials and Components#

Module A1 covers raw material extraction and processing up to your factory gate. Module A2 handles transport from suppliers to you.

Material Production Data#

What’s needed: For each significant material input, you need information about its production impacts. Two approaches work:

Approach 1: Supplier-specific data

• Supplier’s own LCA data or EPD
• Manufacturing location and energy sources
• Any specific process information distinguishing this supply from generic database values

This is ideal but often difficult to obtain. Many suppliers lack detailed environmental data or consider it proprietary.

Approach 2: Database selections

• Choose appropriate dataset from LCA databases (Ecoinvent, GaBi, etc.)
• Match material type, production route, and geography as closely as possible
• Document your selection logic

Most EPDs use primarily database values for supply chain data. This is acceptable under ISO 14025 as long as data quality is adequate and documented.

Prioritisation matters. Focus data collection efforts on materials that contribute most to environmental impacts. For many products, a few materials dominate. Getting good data for the top three materials by environmental impact matters more than perfect data for 20 minor inputs.

Recycled Content#

What’s needed:

• Percentage recycled content in materials where applicable (steel, aluminium, glass, plastics, paper)
• Whether pre-consumer (manufacturing scrap) or post-consumer recycled content
• Documentation or supplier certifications

Why this matters: Recycled materials typically have lower production impacts than virgin materials. This shows in Module A1. The PCR specifies how to handle recycled content, often distinguishing between pre-consumer and post-consumer sources.

Common documentation: Mill certificates for steel, supplier declarations for plastics, certifications for recycled content claims. Verifiers will want evidence supporting recycled content claims.

Transport to Manufacturer (Module A2)#

What’s needed:

• Distance from each major supplier to your facility
• Transport mode (truck, rail, ship, air)
• Vehicle type and capacity where relevant
• Load factors (full loads versus partial loads)

Level of detail: “Cement delivered by 20-tonne truck from supplier 150 km away, average load factor 85%” provides adequate detail.

Common approach: Calculate weighted average transport based on material quantities. If you receive 1000 tonnes of Material A from 100 km away and 100 tonnes of Material B from 500 km away, the calculation needs both distances and masses.

When data is uncertain: Reasonable assumptions suffice if documented. “Assumed 500 km truck transport for materials without specific supplier location data” is acceptable if that’s realistic for your supply chain geography.

Transport Scenarios (Modules A4, C2)#

Transport after your product leaves the factory requires scenario-based data because you often don’t know final destinations.

Transport to Site (Module A4)#

What’s needed:

• Typical or average transport distance from your facility to construction sites
• Transport mode and vehicle type
• Load factors

Scenario development: The PCR may specify default scenarios or require you to develop reasonable assumptions. “Average 500 km by truck” might be appropriate for regional products. “1000 km mixed truck and rail” might suit products shipping nationally.

Regional variations: If you sell into distinct geographic markets, you might develop separate scenarios for each. “UK sales: 300 km average. Continental Europe: 800 km average.”

Transport to Disposal (Module C2)#

What’s needed:

• Distance from demolition site to disposal, recycling, or recovery facilities
• Transport mode

Typical approach: PCRs often provide default scenarios like “50 km transport to waste processing facility” because actual distances decades in the future are unknowable. Use PCR defaults unless you have better regional data.

Use Stage Data (Module B)#

Use stage data requirements vary dramatically by product type. Passive products with long life need minimal use stage data. Products requiring maintenance, consuming energy, or needing replacement require detailed scenarios.

Reference Service Life#

What’s needed:

• Expected product lifespan under typical conditions
• Basis for the lifespan claim (testing, experience, standards)

Why this matters: Reference service life determines replacement intervals in Module B4. A product claiming 60-year life needs no replacement in a 60-year building assessment. A product with 20-year life gets replaced twice.

Common sources:

• Industry standards or guidance
• Testing data (accelerated aging, durability tests)
• Historical performance data
• Conservative estimates if uncertain

Be realistic. Overstating lifespan creates verification problems if evidence doesn’t support claims.

Maintenance Requirements (Module B2)#

What’s needed:

• Frequency of maintenance activities
• Materials consumed during maintenance (cleaning products, touch-up materials)
• Energy and water for maintenance
• Waste generated

Example: “Exterior coating requires cleaning every 5 years with water (50 litres per m²) and mild detergent (0.1 kg per m²), no waste generated beyond wash water.”

For products not requiring maintenance: State this explicitly. “No routine maintenance required over 60-year reference service life” is valid for many construction products.

Replacement Intervals (Module B4)#

What’s needed:

• Calculation showing replacement frequency based on reference service life
• Full environmental profile for replacement units (identical to original product unless specified otherwise)

Calculation: Building service life ÷ Reference service life = Number of replacements

60-year building ÷ 15-year product life = 4 replacements during building life

Operational Energy/Water (Module B6/B7)#

What’s needed: For passive products affecting building energy performance:

• Thermal properties, acoustic properties, or other performance characteristics affecting operational energy
• Basis for performance claims (testing, calculations)

For active products:

• Energy consumption during operation
• Water consumption if relevant

Challenge: Operational impacts depend on building design, climate, usage patterns, and systems integration. PCRs typically require stating product properties that enable building-level calculations rather than claiming specific operational impacts.

End-of-Life Data (Modules C and D)#

End-of-life data is almost entirely scenario-based since you can’t know what actually happens decades in the future.

End-of-Life Scenarios#

What’s needed:

• Deconstruction/demolition method and energy requirements (Module C1)
• Transport to waste facilities (Module C2)
• Waste processing approach (Module C3)
• Final disposal routes with percentages (Module C4)
• Material recovery rates and quality (Module D)

Scenario development: Use current regional practice as baseline. “Based on current UK construction waste management, assumed 70% steel recycling, 20% mixed construction waste to landfill, 10% incineration with energy recovery.”

PCR guidance: Many PCRs provide default end-of-life scenarios reflecting typical practice. Use these unless you have product-specific information justifying different scenarios.

Module D Calculations#

What’s needed:

• Quantities of materials leaving the system for recycling or recovery
• Quality of recycled material (virgin-equivalent, downcycled, etc.)
• Energy recovery efficiency for incinerated materials
• Biogenic carbon content for bio-based materials

Calculation approach: Module D credits avoided impacts from recycling or recovery. You need the avoided virgin production impacts (from databases) minus the recycling process impacts (also from databases).

PCRs specify calculation methods. Follow them precisely.

Data Quality Requirements#

ISO 14040/44 and PCRs specify data quality criteria:

Coverage: Have you included all significant processes and materials? Cut-off typically allows excluding inputs <1% by mass if they’re also <1% by environmental impact.

Precision: Are measurements accurate? Manufacturing data from meters is more precise than estimates.

Completeness: Have you captured full annual cycles? Missing seasonal variations reduces representativeness.

Representativeness: Does data reflect actual production? Data from trial runs or theoretical processes isn’t representative.

Consistency: Have you used consistent methods across all data collection? Mixed approaches reduce comparability.

Reproducibility: Could someone else reproduce your results with your documentation? This requires thorough documentation.

Sources: Are data sources appropriate and credible? Peer-reviewed databases are better than uncited websites.

Uncertainty: Have you assessed and documented uncertainty in your data?

Verifiers check these criteria systematically. Good documentation demonstrating data quality makes verification smoother.

Primary Versus Secondary Data#

Primary data: Measured or collected directly from your operations.

Secondary data: Generic data from databases or literature.

PCRs typically require minimum percentages of primary data for processes you control. Module A3 manufacturing should be primarily (>50%) primary data. Supply chain (Module A1) can rely more heavily on database values.

The requirement recognises that you can measure your manufacturing but may lack access to supplier process data. Using appropriate database values for supply chain inputs is standard practice.

When Data Doesn’t Exist#

Perfect data availability is rare. Pragmatic approaches handle gaps:

Use database proxies. If you can’t get supplier-specific data, use database values for similar materials from similar regions. Document your selection logic.

Make conservative assumptions. If uncertain, choose assumptions that don’t favour your product unrealistically. “Assumed longest typical transport distance” is defensible.

Document limitations. State clearly where you used estimates, proxies, or assumptions. Transparency about limitations is better than appearing to hide them.

Prioritise high-impact data. Perfect data for minor components matters less than reasonable data for major environmental contributors.

Develop data collection systems. First EPDs often struggle with data availability. Establish systems to collect better data for future updates.

Data Organisation and Documentation#

How you organise data affects how efficiently you create EPDs and undergo verification.

Create structured templates matching PCR life cycle stages. Spreadsheets with clear sections for Module A1, A2, A3, etc. help organise information.

Document sources for every data point. “Source: production records January-December 2024” or “Source: Ecoinvent 3.9.1, process ID XXX” provides verification trail.

Record units clearly. Mixing kg and tonnes, or MJ and kWh, causes calculation errors. State units explicitly.

Keep raw data. Don’t just record calculated per-unit values. Keep absolute data and production volumes so you can recalculate if needed.

Version control. If data updates, maintain version history. Verifiers may ask about changes between drafts.

Good data documentation reduces verification time, supports future updates, and demonstrates quality to verifiers.

Building Data Collection Systems#

First EPDs involve substantial data collection effort. Subsequent EPDs get easier if you establish systematic collection:

Integrate into operational tracking. Many facilities already track production, materials, energy, and waste for cost control. Ensure this data is in formats supporting EPD calculations.

Engage suppliers proactively. Rather than requesting data during EPD projects, establish ongoing supplier environmental data requirements.

Standardise templates. If you’ll create multiple EPDs, develop standard data collection templates reusable across products.

Assign responsibility. Someone needs to own EPD data collection. Production managers, environmental coordinators, or quality teams often take this role.

Plan for updates. EPDs expire after five years. Establish processes to collect updated data as expiry approaches.

Systematic data collection transforms EPDs from one-off projects into integrated environmental management.

Starting Your Data Collection#

Before beginning EPD creation:

1. Read the PCR completely to understand requirements
2. Assess what data you already have from production tracking
3. Identify supply chain data needs and prioritise by environmental significance
4. Develop scenarios for life cycle stages beyond your control
5. Create documentation systems supporting verification
6. Allow adequate time for data collection (weeks to months, not days)

Thorough data preparation prevents mid-project delays when you discover missing information. The time invested in systematic data collection pays back through smoother EPD creation, easier verification, and faster updates.

Data is the foundation. Everything else in EPD creation builds on it. Get the data right, and the rest follows. Cut corners on data quality, and problems compound throughout LCA, documentation, and verification. Investing in proper data collection and documentation is investing in EPD success.