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G-19 Allocation case: production of renewable energy on-site

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Aspect G-19 Allocation case: production of renewable energy on-site

Description		 The production of on-site renewable energy can occur at different times of the day, month and year, and may or may not meet on-site needs. Renewable energy may be consumed on site, or may be exported to the electricity grid or to a heating network, for example, according to the instantaneous needs of the building. How should this on-site energy production be accounted for, and can the loads and benefits be allocated between the electricity grid and the building?
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☒
goal and scope definition		 ☒
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
not for products
screening LCA
simplified LCA
complete LCA

Provisions		 The amount of renewable energy produced with the help of on-site systems to supply operational energy for the use of the building should be accounted for as part of the LCI of the building being assessed, attributing the on-site production to the building life cycle. The allocation of exported energy follows the case studies of EN 15978, Annex B.

Rules from
EN 15978 7.4.4.7 Boundary for the operational energy use (Module B6)
Annex B (informative) Exported energy – Case studies
ILCD Provisions: 7.9.3 Solving multifunctionality by allocation
Provisions: 7.9.2 Avoiding allocation by subdivision or virtual subdivision

Guidance		 The method for the calculation of on-site renewable energy production should be consistent with [EN 15643-1]. Renewable energy produced by systems located on the building site and supplying energy demand for building uses should be considered (e.g. thermal solar panels, photovoltaic panels, wind turbines…). Other thermal energy gain from on-site renewable energy sources (solar gains through windows or solar walls) can also be accounted for complete LCA. Calculation method should be reported and justified.

Boundary for energy production at operational stage should be consistent with boundary for product (A1–A3) and construction processes (A4–A5) modules:

  • If the energy produced by the on-site system is accounted for in Module B6, the production system should be accounted for in Modules A1–A5.
  • The accounting of renewable primary energy for the operational stage should be consistent with the accounting of renewable primary energy for materials, the amount of renewable primary energy is the measured output energy, not the amount of energy potentially available.

For on-site systems exporting energy outside the building boundary see the aspect described in Module B6: “Operational energy calculation – Allocation of energy production for on-site systems connected to grid”.

G-20 Define reference building

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Aspect G-20 Define reference building

Description		 The whole-life performance of nearly all building products can be assessed only in the context of a specific building. Is it possible to set a reference building for this comparison?
Related
study objective		 ☒ stand-alone LCA ☒ comparative assertion
Related
study phase		 ☒
goal and scope definition		 ☐
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
construction products
screening LCA
simplified LCA
complete LCA

Provisions		 No definition of a general reference building is given, as such a building would not be applicable for all of Europe.

Guidance		 Definition of a reference building may be a feasible way to assess specific products within the context of their particular use. Currently, reference buildings have to be defined individually for each study. Further research may yield a generic European reference building, or perhaps national reference buildings. In defining a study-specific reference building, attention should be paid to the product use that is being assessed. The product, or the compared products, should provide functions relevant to the reference building, in order to assess the product adequately. For the assessment of products with energy-related functions, the LCA practitioner may explore whether national EPBD-related reference buildings exist, and whether they could be of use.

G-20 (Buildings) / G-17 (Products) Allocation case: reuse, recycling and recovery

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Aspect G-20 (Buildings) / G-17 (Products) Allocation case: reuse, recycling and recovery

Description		 When the lifespan of a product ends, it can be reused, recycled, or used for recovery in another product system. These recovery operations entail a benefit for the system that yielded them. How to allocate these benefits to the system under study, or to other product systems that will recover these materials, is still an open topic within the LCA community. What allocation method should be used for the reuse, recycling and recovery of construction waste?
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☒
goal and scope definition		 ☒
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
construction products
screening LCA
simplified LCA
complete LCA

Provisions		 According to EN 15804, components for reuse and materials for recycling and energy recovery are considered as potential resources for future use. The reuse, recycling and recovery operations result in benefits, but also entail environmental loads. In the case of EPDs (products), the net environmental impacts (positive or negative) should be quantified separately in a so-called ‘Module D’. Calculation of Module D impacts should be based on average existing technology, current practice, and the net impacts of the recovery processes in comparison with the impacts of producing the substituted good (energy or primary raw material). EN 15804 provides guidelines for allocation with regard to reuse, recycling and recovery.
EN 15978 refers to EN 15804 to deal with scenarios for reuse, recovery and recycling potentials outside the system boundary of the building under assessment, in order to describe the processes that lead to future substitution of resources.

Rules from
EN 15804 6.4.3 Allocation of input flows and output emissions
6.4.3.1 General
6.4.3.2 Co-product allocation
6.4.3.3 Allocation procedure of reuse, recycling and recovery
ILCD 7.8 Modelling the system
Provisions: 7.9.2 Avoiding allocation by subdivision or virtual subdivision
Provisions: 7.9.3 Solving multifunctionality by allocation
“VI) SHALL – Attributional modelling of reuse, recycling, recovery
VI.a) Follow general rules for multifunctionality, observing specific aspects
VI.a.i) Dealing with waste and end-of-life products of negative market value that generate secondary goods
VI.a.ii) True joint process to be identified
VI.b) Provisions:
VI.b.i) Negative market value
VI.b.i) Market value equal or above zero”
14 ANNEX C: Modelling reuse, recycling, and energy recovery

Guidance		 Allocation can have significant effects on the results of an LCA study. Therefore the allocation method should be documented as transparently as possible, with reference, if possible, to the European standards or the ILCD Handbook. The aspect ‘Allocation example for wooden products’ provides further guidance. A recent article presenting the concept of Module D was presented at the 2012 Symposium on LCA and Construction. For deeper insight into this subject, the interested practitioner may refer to this article: [Leroy 2012].

G-24 Collecting foreground and background data for product LCA

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Aspect G-24 Collecting foreground and background data for product LCA

Description		 Different data need to be collected for a product LCA study. The most important data collection is usually the production stage especially for highly complex manufacturing processes. The data can be based on industry or companies involved in the project else on secondary sources e.g. background databases providing average datasets.
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☐
goal and scope definition		 ☒
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
construction products
screening LCA
simplified LCA
complete LCA

Provisions		 The practitioner should follow ILCD Handbook provisions as well as EN 15804 if more relevant and specific for the goal and scope of the study. The provisions of this aspect is linked to the “definition of system boundaries for product LCA”.

Rules from
EN 15804 6.3.6 Selection of data
CEN/TR 15941 Sustainability of construction works — Environmental product declarations — Methodology for selection and use of generic data
ILCD Provisions 6.8.2 Technological representativeness
“I) SHALL – Good technological representativeness (…)”
III) SHALL – Different technologies for attributional and consequential modelling
III.a) Attributional modelling
III.a.i) Foreground system: (…) technology-specific primary data. (…) Secondary data of the actual suppliers/downstream actors should be preferred to other (third party) secondary data.
III.a.i) Background system: average technology as market consumption mix data should be used (…)
III.c) Using not fully representative data: (…) use justifiable only if this is not relevantly changing the overall LCIA results compared to using fully representative data
Provisions 6.8.3 Geographical representativeness
“I) SHALL – Good geographical representativeness (…)”
II) SHALL – Different technologies for attributional and consequential modelling
II.a) Attributional modelling
II.a.i) Foreground system: (…) site or producer/provider specific data (…) supplier-specific data for the products that connect the foreground with the background system. Generic data of geographical mixes can be used also in parts of the foreground system if for the given case justified as being more accurate, precise, and complete than available specific data (especially for processes operated at suppliers).
II.a.ii) Background system: average market consumption mix data (…)”
Provisions 6.8.4 Time-related representativeness
“I) SHALL – Good geographical representativeness (…)”
II) SHALL – Specific seasonal or diurnal situation?
III) SHOULD – Time-related representativeness of future processes: (…) fully time-representative future data should be used (…). If this is not possible:
III.a) Best Available Technology (BAT) and recent data (…)”
Provisions 6.9 Types, quality and sources of required data and information
“I) MAY – Overview of the principles types of data and information
II) SHOULD – General requirements on data and data set quality
III) SHOULD – Potential sources for the required data, data sets and information
III.a) Well documented data
III.b) Pre-verified data”
Provisions for the foreground system of an analysed system
Provisions 7.3 Planning data collection
“I) SHALL – Identify newly required, study-specific unit processes
II) SHALL – Average and generic data
III) MAY – Identify data and information sources
IV) MAY – SI units
V) SHOULD – Multi-annual or generic data to be preferred?
VI) MAY – Relevance-steered data collection: (…) Building on existing experience that sufficiently reflects the analysed process or system and that is of high quality is an essential guide. (…) PCR can represent this experience (…).”
Provisions 7.4.2.4 Types of input and output flows to collect
“I) SHALL – Types of input and output flows
I.a) Input of “consumed” products
I.b) Input of wastes
I.c) Input of resources from nature
I.b) Emissions to air, water, soil
I.b) Other input and output side interventions with the ecosphere
I.b) Output of wastes
I.b) Output of valuable goods and services provided by the process, as product flows”
Provisions 7.4.2.6 Reference amount of the reference flow
Provisions 7.4.2.7 Representativeness regarding operation conditions
“I) SHALL – Full operational cycle of the process, if required
II) SHOULD – One full year as data basis: for measured data of operated process
III) SHOULD – For parameterised processes”
Provisions 7.4.2.11 Interim quality control
Provisions 7.4.2.11 Emission of particles to air
“I) SHALL – Inventory only poorly water soluble compounds as particles
II) SHOULD – Differentiate particles size classes
III) SHALL – Inventory particles additionally as the substances they are composed of”
Provisions 7.6 Selecting secondary LCI data sets
“I) SHALL – Use consistent secondary data sets
II) SHOULD – Quality-oriented selection of secondary data sets
III) MAY – Prefer pre-verified data sets
IV) MAY – Prefer well-documented data sets”
Provisions 7.8 Modelling the system
“(…) II) SHALL – Complete system model (…) V) SHALL – Use consistent data to fill gaps (…)”
ISO 14044 4.2.3.6 Data quality requirements

Guidance		 ILCD guidance should be followed. It needs to be precised that the data collection is a very time consuming step in the LCA. However, this step is highly linked to the overall quality of the study. The practitioner may face different challenges for collecting foreground or background data in practice.

Generally speaking, the foreground data collection at the manufacturer plant should follow consistent rules (e.g. see ILCD provisions 7.4.2.8 Checking legal limits; provisions 7.4.2.11 Interim quality control).

General guidance for product LCA studies

The data collection should be conducted depending on the goal and scope of the study.

Specific guidance for EPD studies

Depending on the EPD program, some already pre-verified background data may be made available for the practitioner. If so, there is no need to comprehensively review the background data as they are supposed to meet the quality guidelines and goal and scope of the PCR (e.g. EN 15804).

It is very important to comply as much as possible to the specific rules given in the PCR (EN 15804 but also national implementation). One key issue is to know where we need to stop collecting data from the manufacturer. Usually, he controls only the gate-to-gate processes. However, under some circumstances, he may also be responsible of upstream process e.g. extraction of clay. In that context, it may be relevant to collect primary data for this process instead of using secondary data available in background databases.

For the gate-to-gate stage (under the control of the manufacturer), the data collection is function of the type of EPD.

For single manufacturer’s EPD, data can be taken from 1 production site or averaged across more than one the production sites.

For group of manufacturer’s EPD, data are taken from different companies (their data may be already averaged internally if they have more than one production site). They need to be averaged (horizontal averaging according to the ILCD). In that case, it is very important to make sure that the different companies have similar environmental impacts for the production of the product. PCR (in every national context) may provide more specific rules than EN 15804 to calculate these group of manufacturer’s EPD. This issue being to make sure that the declaration is representative of the companies with a limited variability. By requesting a low variability on the final results (e.g. 10% for GWP, 20% for acidification) it leads to differentiate different group of companies that have different technologies and related environmental impacts. Otherwise, the issue is to have a company that has higher impacting production process being hidden under the “average” value thanks to the more efficient/less impacting production processes.

Guidance for E2B EI research projects

Within E2B EI research projects, some confidentiality reasons may lead the use only of generic data for both foreground and background system. In some cases, where the company is keen on giving the gate to gate information for the LCA study, the modelling will be more representative of the product.

The limits encountered during the data collection step should be part of the LCA report. The interpretation of results should be made according to the quality of data collected during the inventory analysis.

G-21 Background databases in LCA studies

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Aspect G-21 Background databases in LCA studies

Description		 According to the ILCD Handbook, the background system comprises those processes that are not under the direct control or decisive influence of the producer of the good. For attributional modelling these are typically processes for both the upstream and downstream parts of the entire life cycle of a product. For comparative assertions, the use of consistent background data is crucial. Generally, a product or a building process tree always includes intermediate flows (according to ISO 14044), such as energy, electricity, transport and raw materials. These processes may be modelled using background data available in generic databases.
In this context, which database should be used for background data in an LCA study? Which database should be chosen, or which rules should be defined for the use of a database for comparative assertions?
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☐
goal and scope definition		 ☒
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
construction products
screening LCA
simplified LCA
complete LCA

Provisions		 All data used in an LCA study should be modelled with a uniform methodology. This can typically be achieved by using a public or commercially available background database and modelling the foreground system in a consistent way.
For comparative studies (in simplified or complete LCA studies), it is highly recommended, or even essential, to use datasets that are consistent, e.g. consistent within one database. If this is not possible (e.g. because of data gaps or incomplete documentation), any other data should comply with the methodological rules of the database used for the study.

Rules from
ILCD 9 Life cycle interpretation
Provisions: 9.3.4 Consistency check

Guidance		 In general, the LCA practitioner should use consistent data from a single source. For European research projects, the use of European databases such as ecoinvent, GaBi, ELCD or ESUCO may be appropriate. The mixing of background data from different databases should be avoided for comparative assertions. This is especially true if data from different databases are not used similarly in the compared models, or if the methodological rules and the quality guidelines do not match between the mixed data.

However, in practice the mixing of background data can occur. For example:

  • if one background dataset (e.g. raw material production, or energy supply) is more representative for the context of the study than the one in the main database being used;
  • for EPD databases where no mandatory background database is provided. In this case the background data provider should ensure that the use of their data does not lead to bias in the comparative assertions (as the practitioner cannot influence the background data).

In general, the use of different background data is not a problem; it is more the adaptation of data in terms of methodology and cut-off rules that can be a problem (for the LCA study). Some databases providing unit process data can easily be adapted to the goal and scope of the LCA study, and to the other background data that cannot be modified, but some databases cannot be adapted in this way.

If the lack of specific datasets in a background database leads practitioners to combine data from different literature sources, they need to decide whether it is more important to use a consistent but roughly estimated dataset (and possibly data that are not relevant for the context of the study), or to use a dataset that may be better in terms of representativeness, but which is methodologically inconsistent with the alternative data.

In this context, one possible solution is to use data quality indicators for assessing both the representativeness of the data and the consistency of the methodology, compared with the goal and scope of the study: for example, is the dataset compliant with the national context in terms of representativeness?

G-22 (Buildings) / G-23 (Products) Data quality

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Aspect G-22 (Buildings) / G-23 (Products) Data quality

Description		 Generally speaking, the data quality in LCA refers to the relevance of generic or specific LCA data in accordance with the goal and scope of the study. Depending on the background data sources (literature, industry data), and the boundaries and context of the study (e.g. for which purposes or countries are the data being used?), the data quality can be very different within one study. Although data may be of good quality for context Y, this will not necessarily be the case for context Z, as the requirements (e.g. geographical representativeness) may be different. The practitioner should keep in mind that data quality is always a relative concept. In order to point out this aspect as transparently as possible, the quality of the data has to be justified in the context of its use. How should the quality of the LCA data be described, and can the practitioner ensure that data of a specific quality are needed and produced?
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☐
Goal and scope definition		 ☒
Inventory analysis (LCI)		 ☐
Impact assessment (LCIA)		 ☐
Interpretation		 ☐
Reporting
Relevant for
New buildings
Existing buildings
Building products
Screening LCA
Simplified LCA
Complete LCA

Provisions		 The data quality of LCA studies should at least meet the requirements of EN 15978 and EN 15804, and the documentation, nomenclature, method and review should be implemented accordingly.

Rules from		 EN 15978
10.3 Data quality
Different criteria are given in EN 15978, e.g. technological, geographical and temporal coverage (the data should be not older than 10 years). The data should be based on a one-year average (if relevant); check the plausibility and the significance of the data in the final result.

EN 15804
6.3.7 Data quality requirements

ILCD Handbook
6.8 Representativeness and appropriateness of LCI data provisions
6.8.2 Technological representativeness
6.8.3 Geographical representativeness
6.8.4 Time-related representativeness

Annex A: Data quality concept and approach
12.1 Introduction and overview
In the ILCD Handbook, two approaches are defined – 1) data quality in a stricter sense; and 2) the data quality documentation and review:
1) ILCD overall data quality indicators include: technological, geographical, time-related representativeness, completeness, precision/uncertainty, methodological appropriateness and consistency.
2) Data quality documentation aspects cover: documentation, review, nomenclature (e.g. same list of elementary flows)
12.2 Data quality aspects
The ILCD Handbook defines ‘accuracy’ as a term covering all the related data quality aspects, such as:
“Representativeness (technological, geographical, time-related)
Completeness
Methodological appropriateness and consistency”
The ILCD Handbook also provides rules for not mixing the data quality aspects (falling under the term ‘accuracy’) with the other concept of ‘precision’ (or ‘uncertainty’). A graphical illustration (see Figure 11) illustrates this point.

Guidance		 In current practice it is usually not possible to choose datasets for quality reasons, but for availability in the construction sector. The practitioner should keep in mind that data quality is crucial for the LCA study. The most appropriate data should be chosen (in terms of representativeness and consistency) as far as possible. Documentation of the used datasets and the quality level is needed as far as possible.
The ILCD Handbook provides some recommendations on data quality, depending on the relative significance of the data in the final results. A graphical illustration (see Figure 12) illustrates this point.

G-23 Choice of LCI/LCIA datasets for screening LCA

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Aspect G-23 Choice of LCI/LCIA datasets for screening LCA

Description		 Different LCI/LCA data are needed to assess the environmental impacts of buildings. They make it possible to quantify the different impacts related to the building products and equipment, the construction site, the operational energy and water uses, and the deconstruction of the building. Depending on the study type (screening, simplified, complete), different types of data can be used in practice, depending on their availabilities at the European level but also in a national context (average, generic or specific LCI/LCIA data for the building materials, products and processes). How can this be addressed for screening LCA?
Related
Study Goal		 ☒ stand-alone LCA ☒ comparative assertion
Related
Study Phase		 ☐
Goal and scope definition		 ☒
Life cycle inventory analysis (LCI)		 ☐
Life cycle impact assessment (LCIA)		 ☐
Interpretation		 ☐
Reporting
Relevant for
New buildings
Existing buildings
Building products
Screening LCA
Simplified LCA
Complete LCA

Provisions		 The LCA practitioner or the user of dedicated building LCA tools should use adapted data for the description of the building components in screening LCA. They can either represent a major part of the building (e.g. statistical data, such as a specified level of kWh/m² for the interior walls), a full building component (e.g. 1 m2 concrete block wall insulated with wood wool), a building product (e.g. 1 m2 of rock wool) or a building material (1 m3 of ready-mixed concrete), depending on the need of the practitioner and the stage of the building project. Provisions for the choice of data to use for screening LCA for the construction site, the operational energy and water uses, and the deconstruction activities are described in the corresponding aspects.
Generic LCA data for the building elements cited above should come from available European or national generic LCA databases where the building is built. It is possible to use average data (e.g. average EPD) if generic LCA are missing, or are less appropriate to the context of the study. Generic LCA data may represent (if possible and if relevant) the total consumption mix in Europe (if the study is used for European projects) or in every European country, or the production mix in Europe or in every European country, or the production mix of a neighbouring country using appropriate rules to adapt the generic data to the new context.

Rules from
EN 15978 9.4 Type of data for the assessment
The type of LCA data for the assessment referred in EN 15978 to CEN/TR 15941. The choice of the data will depend on several aspects, including the stage of the building project, the intended use/scope etc. According to EN 15978 the data (bill of quantities, building description of components, or the LCA data) may be given in different types: aggregated, specific, generic, or average. They describe different levels of specificity concerning the description of the building components as well as the representativeness of the LCA data.
ILCD 7.5 Developing generic LCI data
7.6. Selection of secondary LCI datasets
7.7 Averaging LCI data
According to the ILCD Handbook, a dataset is a generic dataset if “it has been developed using at least partly other information than those measured for the specific process. This other information can be stoichiometric or other calculation models, patents and other plans for processes or products, expert judgements etc. Generic process can aim at representing a specific process or system or an average situation.”
ILCD also states that “a generic dataset represents a typical variant of the process or the system, an average dataset represents the average situation for the process or the system, in both cases within a specified geographic region and time. The difference lies in how the dataset is modelled: in the first case the product and its life cycle is specified with typical (or representative) characteristics and the inventory is modelled accordingly. In the second case several products (or technology or production plants) are separately modelled and the inventories are subsequently averaged.”

Guidance

In practice the data for a screening LCA can be based on generic assumptions, as they are used only for obtaining a rough estimate of the environmental impacts of a product system. Three different practical recommendations can be given for the use of data on the building elements, the associated LCA data and the currently available generic LCA databases.

1) Practical guidance for the use of data describing the building elements

The data describing the part of the building can be estimated using either the statistical results of a comprehensive study of newly constructed buildings, or a sample of representative buildings.

The data describing the building components can correspond to generic typical components, using default values for the main included products (width, thickness etc.). It may be possible to parameterize the thickness of the key included products (e.g. insulation or structural products) for each study or use.

Other data include building products and materials LCA data. These ‘raw’ data usually serve when deriving data for building components or part of the building. Consistency should be ensured between the different levels of data (part of the building, components, products and materials).

2) Practical guidance for the use of generic LCA data for a European or national context

Examples of generic data on building products representing the ‘consumption mix’ can be found, for example, for the reinforcing steel sold on the French market in [Gomès 2012]. However, generally speaking, generic national data representing the ‘consumption mix’ in the various European countries may be missing. In this case, the use of existing generic LCA data (from neighbouring European countries) or industry-based data (from the national context) can be used as proxy data, using appropriate adaptation/contextualization rules. More guidelines on this topic can be found e.g. in [Hodkova 2012].

3) Practical availability of generic databases in Europe that can be used by the practitioner

The building practitioner may use existing European or national databases to collect generic LCA data to describe the building elements, products and materials, depending on the needs. Examples of such databases can be found e.g. on the LCA resources directory of the European Commission – Joint Research Centre, section Databases. Generic databases (mainly at the global or European levels) include, for example, ELCD, ESUCO and ecoinvent.

Other generic databases developed in some European countries include, for example: the German Ökobau.dat, the Swiss Catalogue Construction/KBOB databases, the French DIOGEN generic LCA database for construction materials used in civil engineering applications, and the various generic databases that are included in LCA software for buildings.

G-22 Data selection for a product LCA

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Aspect G-22 Data selection for a product LCA

Description		 Various data sources exist for the calculation of product LCA data. They differ for example in terms of specificity, age, completeness and certainty. What data requirements apply for the production of product LCA data?
Related study
objective		 ☒ stand-alone LCA ☒ comparative assertion
Related study
phase		 ☒
goal and scope definition		 ☐
inventory analysis (LCI)		 ☐
impact assessment (LCIA)		 ☐
interpretation		 ☐
reporting
Relevant for
new buildings
existing buildings
construction products
screening LCA
simplified LCA
complete LCA

Provisions		 In general, specifications are given with regard to EPD: see 6.3.7 ‘Quality requirements’ in EN 15804. National EPD programmes that apply to the context of the LCA study may give more specific guidance.

Rules from
EN 15978 6.3.6 Selection of data
6.3.7 Data quality requirements
CEN/TR 15941 Sustainability of construction works — Environmental product declarations — Methodology for selection and use of generic data
ILCD
ISO 14044 4.2.3.6 Data quality requirements

Guidance		 Specific data are data relating to the specific process being studied. Generic data are more general data – they may for example be an average from a trade association, a specific dataset that is used as a proxy for typical production, or a dataset developed from literature sources. Data quality considers the relevance and quality of the dataset relative to the process being considered, taking account of a) age of data; b) geography; c) technology; d) precision; e) completeness; f) representativeness; g) consistency; h) reproducibility; i) sources of the data; j) uncertainty.

For screening and simplified LCA, it can be appropriate to use lower data quality requirements: for example, a single database for upstream and downstream data may be used without considering further data quality or appropriateness of individual datasets. For complete LCA, it is necessary to consider and report on the data quality.

In some circumstances, where a dataset is of particular relevance to a study, or where no suitable dataset is available, it may be necessary to collect data from upstream or downstream processes rather than use generic data. The scope of this data collection will depend on the detail required.

EPD programmes may require specific databases to be used for comparability purposes in terms of methodology until EN 15804 compliant data are widely available. Once EN 15804 compliant databases are available, there should be no differentiation between EN 15804 compliant datasets, other than the scope of the data used.

It may be advisable to use the background database that is required from the EPD programme that lies within the context of the LCA study. This means that, for improved consistency, a product LCA study may/should be based on the national EPD programme’s background study. ILCD already provides guidance on sources of generic data such as the ELCD and proprietary databases.