At the end of the iterative steps of improving the data set, the finally missing data and the potential use of data estimates to fill data gaps shall be documented in a transparent and consistent way. 3:3:2. MAY—For judging the relevance of an initial data gap, it is necessary to approximate the achieved accuracy, completeness and precision of the M.Z. Hauschild and A. Bjørn


overall environmental impact on system level. This necessarily needs that the subsequent steps of modelling the life cycle and calculating LCI results and LCIA results need to be done first. It is recommended to do this in parallel to developing the unit process data set. For unit processes this means completing the life cycle model around the unit process with background data. Any limited completeness in the used background data shall be not considered when calculating the achieved degree of completeness for the unit process for the final reporting. 3:3:3. MAY—For filling data gaps for single flows estimate data (sets) may be considered to be used. Such may be, e.g.: 3:3:3:1 generic or average data for missing specific data, 3:3:3:2. average data of a group of similar products for missing inventory data for other, not yet analysed products of that group, 3:3:3:3

Hauschild et al., LCA: Theory and Practice


average data of a group of similar products for missing inventory data for other, not yet analysed products of that group, 3:3:3:3. correlation with other, more complete and high quality data for the same or similar process but from other data sources (e.g. industry average data for improving a producer-specific process), 3:3:3:4. justified judgements of technical experts/process operators. 3:3:4. SHALL—Data gaps shall generally be filled with methodologically consistent data. Gaps of low relevance may also be filed with methodologically not fully but sufficiently consistent data sets while being developed along the guidance of this document and meeting the overall quality requirements as detailed below. 3:3:5. SHALL—Only data that increase the overall quality of the final inventory of the analysed system shall be used to fill data gaps. That means that the individual data/data set’s overall quality (i.e


SHALL—Only data that increase the overall quality of the final inventory of the analysed system shall be used to fill data gaps. That means that the individual data/data set’s overall quality (i.e. combined accuracy, precision, completeness and methodological appropriateness and consistency) shall be equivalent to at least the “Data estimate” quality level. Note that this shall include both the quality of the used data estimate and of the amount of the flow. That semi-quantitative approximation of the integrated data estimate plus flow amount quality shall be based at least on an individually, briefly justified expert judgement, explicitly considering the named shortcomings; this may be supported by uncertainty calculation and quantitative calculation of data accuracy. Dealing with remaining unit process data gaps/missing data 4


Dealing with remaining unit process data gaps/missing data 4. SHALL—Document remaining data gaps: If data estimates cannot be made available that would meet the above requirements, the data gap shall be kept and be documented instead. The following provisions are made: [ISO!] 4:1. Missing qualitative information for a unit process inventory item: The respective flow should be created and used in the regular inventory only if it is a product or waste flow. Little specified elementary flows (e.g. “Metals to air”)


shall not be kept in the regular inventory but this information shall be documented in another way. This can be either as clearly marked flows that shall not be combined with the elementary flows of the regular inventory when aggregating the data sets of the analysed system, The flows can be marked, e.g. as “missing important” or “missing unimportant”, as applicable (see more below), and be excluded from the aggregation. Or they can be documented exclusively in the descriptive information of the data set (e.g. as attached lists). 4:2. Missing quantitative information for a unit process inventory item: The flow should be inventoried. If no quantitative information can be given, this has to be documented by marking the flow as “missing important” to avoid misleading readers, as the true value is not zero. The omission must be explicitly addressed and considered in the interpretation of the results


The omission must be explicitly addressed and considered in the interpretation of the results. If a conservative estimate for a missing data fails to show any quantitative importance, a zero value may be entered for this data, but marking it as “missing unimportant”. If a mean value or a wide range of values (Min and Max) can be given, this should be entered in the inventory. Uncertainty information such as standard deviation and distribution type should be given if possible and if this information has sufficient precision. For both the above cases, the values shall not be aggregated when calculating LCI results. This can be achieved, e.g. by marking theses inventory items as “missing important” or “missing unimportant”, as applicable (see more below), and excluding such flows from the aggregation. Or they can be documented exclusively in the descriptive information of the data set (e.g. as attached lists). 4:3


Or they can be documented exclusively in the descriptive information of the data set (e.g. as attached lists). 4:3. Missing qualitative and quantitative information: See preceding two points that are to be combined. 4:4. Missing LCI data for processes/systems in the background system: When aggregating the unit processes of the analysed system to LCI results, product and waste flows for which background data of sufficient quality is not available, these flows shall remain in the aggregated inventory, i.e. making the data set a “partly terminated system”. The user of such data shall be explicitly informed in a prominent place that these parts of the system need to be still completed or the gap be considered in the further use and interpretation


The user of such data shall be explicitly informed in a prominent place that these parts of the system need to be still completed or the gap be considered in the further use and interpretation. Note that any kind of worst case or conservative data and assumptions shall not be kept in the inventory of LCI data that are foreseen to be applicable for comparisons, unless the representing process operators or system producers themselves wish so (e.g. to align LCI data reporting with other values reported on, e.g. site or company level). Note that reasonably worst-case data may, however, be used for scenarios and for checking the robustness of comparisons when doing the sensitivity analysis. Note the specific requirements for product comparisons such as on, e.g. the consistency of methods, data quality, and assumptions across the compared alternatives. M.Z. Hauschild and A. Bjørn


Guidance is offered on the handling of potentially problematic types of substance flows in the inventory analysis of processes—measurement indicators and groups of elementary flows, ionic compounds, airborne particle emissions, resource uses and energy use indicators. Emission of measurement indicators and elementary flow groups (Provisions 7.4.3.3) 1. SHALL—Measurement indicator and substance group elementary flows: These shall be inventoried as follows: [ISO!] 1:1. Avoid indicators and flow groups; with permissible exceptions: Measurement indicator and substance group elementary flows shall be avoided in the inventory by splitting them up to single substances. Exclusively the following exceptions are permissible, while they should be split as well: COD59, BOD, AOX, VOC, NMVOC, PAHs, PCBs, TOC, DOC, Nitrogen in Nitrogen compounds (excluding N2, N20), Phosphorus in Phosphorus compounds, Dioxins (measured as 2,3,7,8-TCDD human toxicity equivalents). 1:2


1:2. Restrictions on partial splitting: A partial splitting up of measurement indicators and substance group flows should be avoided. This is except for singling out exclusively elementary flows that have higher impacts than the average of the indicator/group and that should be singled out. Partial splits with singling out elementary flows with less than average impacts shall not be done. If singling out single substance elementary flows from the above indicators/flow groups, only the remainder amount of the indicator or flow group shall be inventoried. 1:3. No double-counting: Double-counting across the above indicators/flow groups and with the contained individual substances shall be avoided (i.e. correct is to inventory either “BOD” or “COD”42; either “VOC” or “NMVOC” plus “Methane”; either “Nitrate” plus “Ammonia” plus ... or “Nitrogen in Nitrogen compounds”; etc.). 1:4


correct is to inventory either “BOD” or “COD”42; either “VOC” or “NMVOC” plus “Methane”; either “Nitrate” plus “Ammonia” plus ... or “Nitrogen in Nitrogen compounds”; etc.). 1:4. Document composition: If measured composition information of a split measurement indicator or substance flow group is not available, an assumed composition can be used. Approach and assumptions shall be documented. Note that the composition of a measurement indicator or substance flow group can often be derived without direct measurement from process know-how (e.g. processed materials, educts, etc.) or those of sufficiently similar process can be considered.43 42COD = Chemical oxygen demand, BOD = Biological oxygen demand, AOX = Adsorbable organic halogenated compounds, VOC = Volatile organic compounds, NMVOC = Non-methane volatileorganic compounds, PAH = Polycyclic aromatic hydrocarbons, PCB = Polychlorinated biphenyls, TOC = Total organic carbon, DOC = Dissolved organic carbon


43Default-composition tables for different process-types and industries mightbe developed in PCR-type or sector- specific guidance documents.


1:5. Do not combine measured flows: Individually measured substances shall not be integrated/combined into measurement indicators and elementary flow groups but be inventoried individually. Emission of ionic compounds (Provisions 7.4.3.4) 1. SHALL—Inventory easily water-soluble salts as ions: For data sets as deliverables, emissions to air, water, or soil of easily water-soluble ionic compounds (salts) shall be inventoried as separate ions, unless the selected LCIA methods would require otherwise. As convention, the limit is set at a solubility in water at 20 °C of 10 lg/l, above which the ions shall be inventoried separately, below which the compound shall be inventoried. This applies unless the selected LCIA method requires otherwise. [ISO!] Emission of particles to air (Provisions 7.4.3.5) 1


This applies unless the selected LCIA method requires otherwise. [ISO!] Emission of particles to air (Provisions 7.4.3.5) 1. SHALL—Inventory only poorly water-soluble compounds as particles: Particulate matter (PM) emissions to air shall include only poorly water-soluble compounds below a solubility in water at 20 °C of 10 lg/l, as far as feasible. Expert judgement may be needed to identify the composition of the particles. [ISO!] 2. SHOULD—Differentiate particle size classes: Particles should be reported split up by particle size class <0.2, 0.2–2.5, 2.5–10, >10 lm if the information is available. <10 lm may be used alternatively is a more differentiated information below 10 lm is not available. This applies unless the selected LCIA method requires otherwise. [ISO!] 3. SHALL—Inventory particles additionally as the substances they are composed of: Particles shall be inventoried as both PM and additionally as elementary flows of their environmentally relevant components (e.g


metals contributing to cancer effects), i.e. double counting their mass in the inventory, as far as possible. This applies analogously to other emissions with additive action schemes. [ISO!] Resource elementary flows (Provisions 7.4.3.6) 1. SHALL—Provisions for inventorying resource elementary flows: Resource elementary flows shall be inventoried as follows, with exceptions only if necessary to meet the need of the applied LCIA method: [ISO!] 1:1. Energy resources: 1:1:1. Non-renewable: These shall be inventoried as type of energy resource and in few cases (only primary, secondary, tertiary crude oil and open pit or underground mining of hard coal) these should be differentiated exclusively by resource extraction type, if this information is available (e.g. “Crude oil, secondary extraction” but not “Crude, Tia Juana Light”; “Hard coal, underground” but not “Hard coal, Western Germany; 39.4 MJ/kg”). The energy/mass relationship shall be provided for all energy resource flows M.Z


The energy/mass relationship shall be provided for all energy resource flows M.Z. Hauschild and A. Bjørn


except for nuclear ores. The energy content shall be expressed in the Lower calorific value of the water-free resource, measured in the reference unit MJ. See also separate document “Nomenclature and other conventions”. Note that peat, biomass of primary forests, and some other biogenic energy resources are “non-renewable”. 1:1:2. Renewable: Renewable energy resources shall be inventoried as the amount of usable energy extracted from nature, e.g. for solar electricity and heat this relates to the amount of electricity and/or heat captured by the solar cells (i.e. not the total solar energy, but what is delivered directly by the cells as electricity and/or usable heat). For biomass from nature this is the amount physically embodied, measured as Lower calorific value, however, of the water-free substance (i.e. measured as if the, e.g. wood would be oven-dry). Note that biomass from fields and managed forests is no elementary flow


measured as if the, e.g. wood would be oven-dry). Note that biomass from fields and managed forests is no elementary flow. In that case, the named energy resources shall be inventoried directly as the respective elementary flows, e.g. “Solar energy” as “Renewable energy resources from air”, expressed as Lower calorific value and measured in the reference unit MJ. 1:2. Avoid geographical differentiation: Resources shall not be inventoried geographically differentiated (i.e. “Lignite” but not “Lignite, Eastern Germany”). This applies unless the selected LCIA method requires otherwise. 1:3. Chemical element resources: Resources for production of metals or other chemical elements should be inventoried as chemical element (e.g. “Iron— Resources from ground” elementary flow). 1:4. Functional/material resources: These shall be inventoried as target material resource (e.g. “Schist”, “Lime stone”, “Anhydrite”)


“Iron— Resources from ground” elementary flow). 1:4. Functional/material resources: These shall be inventoried as target material resource (e.g. “Schist”, “Lime stone”, “Anhydrite”). Few exceptions exist where the mineral itself is in industry understood to be the target good; these are reflected in the ILCD reference elementary flows (e.g. “Rock salt”, etc.). Other exceptions and exclusively for resources not included in the ILCD reference elementary flows shall be justified by following analogous logic. 1:5. Flows for completing mass balance: For completion of the mass balance, a complementary amount of “Inert rock”, “Water”, or “Air” (or other, as applicable) shall be inventoried for extracted resources (e.g. 0.96 kg “Inert rock” in case of mining 1 kg copper ore with 4% copper content). 1:6. No minerals or ore bodies: Inventorying of other minerals (unless these are functional/material resources such as “Granite”) or of specific ore, bodies shall not be done (i.e


1:6. No minerals or ore bodies: Inventorying of other minerals (unless these are functional/material resources such as “Granite”) or of specific ore, bodies shall not be done (i.e. “Copper”, but not “Malachite” and not “Sulphidic copper–silver ore (3.5% Cu; 0.20% Ag)”).


Note that when applying the above rules double-counting shall be avoided. Newly created elementary flows shall be checked whether they require carrying a characterisation factor for the applied LCIA method. 2. SHALL—Land use and transformation: Direct land use and land transformation shall be inventoried along the needs of the applied LCIA method (if included in the impact assessment).44 3. SHALL—Emissions from land use and transformation: If land use and/or land transformation are modelled, carbon dioxide and other emissions and related effects should be modelled as follows: [ISO!] 3:1. Soil organic carbon changes from land use and transformation: For CO2 release from or binding in soil organic carbon (SOC) caused by land use and land transformation, the use of the most recent IPCC CO2 emission factors shall be used, unless more accurate, specific data is available. 3:2


3:2. Land use and transformation related CO2 emissions from biomass and litter: For virgin forests and for soil, peat, etc. of all land uses shall be inventoried as “Carbon dioxide (fossil)”. Emissions from biomass and litter of secondary forests shall be inventoried as “Carbon dioxide (biogenic)”. This applies unless the selected LCIA method requires otherwise. 3:3. Nutrient losses: Emissions of nutrients shall be modelled explicitly as part of the land management process. 3:4. Other emissions: Other emissions in result of land transformation (e.g. emissions from biomass burning, soil erosion, etc.) should be measured or modelled for the given case or using authoritative sources. 4. MAY—Water use: It is recommended to differentiate at least: [ISO+] 4:1. on the input side: surface freshwater, renewable groundwater, fossil/deep ground water, sea water 4:2. on the output side: Emission/discharge of water in liquid form emission in form of steam 4:3


on the input side: surface freshwater, renewable groundwater, fossil/deep ground water, sea water 4:2. on the output side: Emission/discharge of water in liquid form emission in form of steam 4:3. other water quality changes, especially by chemical substances shall be inventoried as separate elementary flows. Modelling waste treatment (Provisions 7.4.4.2) 1. SHALL—Waste and end-of-life product deposition: This shall be modelled as follows: [ISO!] 44While this document has been finalised no established and globally applicable practice was available, but several approaches with either only regional applicability or lack of practice experience. These work with fundamentally different inventorying approaches. Any specific recommendation or requirement on inventorying land use and conversion would be implemented and published via revised ILCD reference elementary flows and recommended LCIA methods, and/or a revision of this document. M.Z. Hauschild and A. Bjørn


2. Model waste management completely: Waste and wastewater treatment shall be modelled consistently to the boundary between technosphere and ecosphere; otherwise, this shall be clearly documented and be explicitly considered in later interpretation. This modelling includes all treatment steps up to and including disposal of any remaining waste-to-waste deposits or landfills and inventorying the emissions from these sites to/from the ecosphere. Two exceptions are radioactive wastes and wastes in underground deposits (e.g. mine filling), which should be kept as specific waste flows in the inventory, unless detailed, long-term management and related interventions have been entirely modelled also for these. 3. Modelling discarding of goods into nature: For unmanaged landfilling, discharge and littering (i.e. discarding goods individually into nature) the related individual interventions that enter the ecosphere shall be modelled as part of the LCI model


discarding goods individually into nature) the related individual interventions that enter the ecosphere shall be modelled as part of the LCI model. This also applies analogously to other interventions than emissions, if the used LCIA method covers such. The littered/landfilled good should be additionally inventoried as reminder flow. 4. Modelling waste as output: Waste flows should be modelled following the material flow logic. That means inventorying the waste on the output side of those processes where it is generated (e.g. production waste or end-of-life product as output of the use stage). For waste management processes that means that the waste flows should accordingly be modelled on the input side if the process, with any potentially produced secondary goods and remaining wastes being on the output side. This eases mass and element balancing. For cost calculation purposes, the cost of the waste treatment service may be assigned to the waste flow as additional flow property


This eases mass and element balancing. For cost calculation purposes, the cost of the waste treatment service may be assigned to the waste flow as additional flow property. Secondary LCI data sets originating in other LCA studies or LCI unit process databases are often extensively used in the inventory analysis, in particular for the modelling of the background system. Guidance is offered on how to select such secondary LCI data sets in order to meet the requirements from the goal and scope definition and ensure consistency in the study. Selecting secondary LCI data sets (Provisions 7.6) 1. SHALL—Use consistent secondary data sets: The secondary data (generic, average or specific data sets) to be used in the system model shall be methodologically sufficiently consistent among each other and with the primary data sets that were specifically collected. 2


2. SHOULD—Quality-oriented selection of secondary data sets: Secondary data sets should be selected according to their data quality in a stricter sense, i.e. their technological, geographical and time-related representativeness, completeness and precision. Their reference flow(s) and/or functional unit(s) should moreover be sufficiently representative for the specific processes, good or service that they are meant to represent in the analysed system. 3. MAY—Prefer pre-verified data sets: It is recommended to give preference to already critically reviewed data sets (“pre-verified data”) as this limits the effort for an review of the analysed system: only the appropriate use of these data sets in the analysed system needs to be reviewed. [ISO+]


4. MAY—Prefer well-documented data sets: It is recommended to give preference to data sets that are supported by a comprehensive and efficiently organised documentation. This allows the modeller (and later a reviewer) to judge the data set’s quality and its appropriateness for the analysed system. [ISO+] The combined use of data from different sources is facilitated by using either single operation unit process data set background systems that can be adjusted/remodelled by the user to be consistent with the analysed system, or by using LCI results data sets that are consistent with the methodology applied in the analysed system. 37.4.4 Constructing LCI Model and Calculating LCI Results When all unit processes have been constructed or collected from LCI databases the LCI model can be constructed, using the unit processes as building blocks and scaling them according to the reference flow of the study. Modelling the system (Provisions 7.8) 1


Modelling the system (Provisions 7.8) 1. SHALL—Scale inventories correctly: The inventories of all processes within the system boundary shall be correctly scaled to each other and to the functional unit(s) and/or reference flow(s) of the analysed system.45 2. SHALL—Complete system model: No quantitatively relevant product or waste flows shall be left unmodelled/unconnected, with exception of the reference flow(s) that quantitatively represent(s) the system’s functional unit. Otherwise these flows shall be clearly documented and the resulting lack of accuracy and completeness be considered in the interpretation of results. [ISO!] Note that for unit processes all and for partly terminated systems, selected inventories of the corresponding products and/or wastes modelling processes are intentionally left out of the system boundary. Their systems are nevertheless completed, while only for applying the cut-off rules


Their systems are nevertheless completed, while only for applying the cut-off rules. 45This can be visualised by having all processes connected with each other via their reference flows of interim products and wastes, in the correct amounts. Starting from central process and the amount(s) of the system's functional unit(s) or reference flow(s), all other processes are stepwise, relatively scaled. LCA software with graphical modelling interface shows the system in this way and/or the user is modelling the system explicitly by connecting the processes on that interface. Depending on the modelling approach implemented in the software, other mechanisms can be found that serve the same scaling purpose. M.Z. Hauschild and A. Bjørn


3. SHALL—Set parameter values: Set the parameter values to the required values in all used parameterised process data sets, if any. [ISO+] 4. MAY—Perform another round of interim quality control: It is recommended to pre-check during modelling whether the data set or system is properly modelled and meets the quality requirements as identified/fine-tuned in the scope phase; the provisions for interim quality control of unit processes apply analogously. For filling initial data gaps of included processes and systems, estimate data sets may be considered to be used. Such may be, e.g. [ISO+] 4:1. generic or average data sets for missing specific processes/systems, 4:2. average data sets of a group of similar processes or systems (e.g. products) for missing processes/systems for other, not yet analysed processes or systems of that group 4:3. correlation with other, more complete and high quality process data sets for the same or similar process but from other data sources (e.g


correlation with other, more complete and high quality process data sets for the same or similar process but from other data sources (e.g. industry average data for improving a producer-specific process). 5. SHALL—Use consistent data to fill data gaps: Data gaps shall be filled with methodologically consistent data sets, while gaps of low relevance may also be filed with methodologically not fully but sufficiently consistent data sets while being developed along the guidance of this document and meeting the overall quality requirements as detailed below. [ISO!] 6. SHALL—Use sufficiently quality LCI data sets to fill gaps: Only data and data sets that increase the overall quality of the final inventory of the analysed system shall be used to fill data gaps. That means that the individual data or data set’s quality shall be equivalent to at least the “Data estimate” quality level. Remaining data gaps shall be reported


That means that the individual data or data set’s quality shall be equivalent to at least the “Data estimate” quality level. Remaining data gaps shall be reported. [ISO!] Note that both the approach(es) used to fill initial data gaps and the resulting lack of representativeness, precision and methodological consistency of the whole data set is later to be clearly documented and explicitly considered when declaring the achieved data set quality or when drawing conclusions or recommendations from an LCA study. Note that the final check on the achieved overall environmental completeness/cut-off is detailed in Sect. 37.6.2. Note that decisions on any omissions of life cycle stages, types of activities, individual processes or elementary flows must be clearly reported and should be justified by the fact that they do not contribute significantly to the LCI results in view of the intended application(s) of the outcome of the LCI/LCA study


Otherwise they need to be reported and considered when declaring the achieved data set quality and/drawing conclusions and recommendations from the study.


Calculating LCI results (Provisions 7.10) 1. SHALL—Apply calculation procedures consistently: The same calculation procedures shall be applied consistently throughout the analysed system(s) when aggregating the processes within the system boundary for obtaining the LCI results. 2. SHALL—Calculate and aggregate the inventory data of the system(s): (If the model is correctly prepared, the first two following sub-bullets can be skipped): 2:1. Determine for each process within the system boundary how much of its reference flow is required for the system to deliver its functional unit(s) and/or reference flows(s) (i.e. the extent to which the process is involved in the system). 2:2. Scale the inventory of each process accordingly. This way it relates to the functional unit(s) and/or reference flow(s) of the system. Note that if parameterised process data sets are used in the system model, the parameter values are to be set before scaling and aggregation. 2:3


Note that if parameterised process data sets are used in the system model, the parameter values are to be set before scaling and aggregation. 2:3. The correctly scaled inventories of all processes within the system boundary shall be aggregated (summed up) for that system. 2:4. If the intended application of the results requires a location non-generic impact assessment, aggregation of the elementary flows above the required location type or level (e.g. the level of a single site/plant, a region, a country, an environmental sub-compartment, etc.) should be avoided in the LCI results calculation. The same applies for other differentiations (e.g. of environmental sub-compartments or archetypes of emission situations) if those are required for the intended application and impact assessment methods to be used. [ISO +] 2:5. If the disaggregated data cannot be publicly disclosed (e.g


[ISO +] 2:5. If the disaggregated data cannot be publicly disclosed (e.g. for confidentiality reasons), it is recommended to foresee performing the impact assessment on the disaggregated level and providing the LCIA results together with the aggregated LCI results. [ISO+] Note that also in this case (as in all cases) the reviewers shall have (at least confidential) access to all underlying data. 2:6. If the disaggregated data cannot be publicly disclosed (e.g. for confidentiality reasons), it is recommended to foresee performing the impact assessment on the disaggregated level and providing the LCIA results together with the aggregated LCI results. [ISO+] M.Z. Hauschild and A. Bjørn


Note that also in this case (as in all cases) the reviewers shall have (at least confidential) access to all underlying data. 3. SHOULD—Ensure that reference flow(s) is/are only product and waste flow(s): Note that after aggregation, the reference flow(s) is/are the only product and/or waste flow(s) that should remain in the LCI results inventory, with two exceptions: 3:1. For partly terminated systems: The inventories of selected products and/or waste flows were left out of the system boundary—typically intentionally—and the flows are kept in the inventory. Note, however, that for the purpose of quantifying the achieved completeness via the cut-off rules of environmental impact, also these selected product and waste flows are to be considered via integrating the inventories of the respective production and waste treatment processes. 3:2. For radioactive waste and waste in underground waste deposits (e.g


3:2. For radioactive waste and waste in underground waste deposits (e.g. mine filling): These waste flows can be kept in the inventory for direct use in interpretation. 4. SHALL—Highlight and explicitly consider remaining non-functional product or waste flows: Any product and waste flows that remain in the inventory and that are non-functional flows shall be highlighted in the report and/or data set: Either they require to be modelled when later using the data set (e.g. by complementing the data set with a yet missing background LCI data set for, e.g. a specific chemical consumed, or modelling the management/ treatment of a specific waste). Alternatively, this gap/missing data needs to be explicitly considered in subsequent interpretation and conclusions drawn. 37.5 Impact Assessment The impact assessment is discussed in Chap. 10 of this book


37.5 Impact Assessment The impact assessment is discussed in Chap. 10 of this book. It is the fourth phase of the LCA, where the elementary flows of the life cycle inventory are translated into potential contributions to the different impact categories that are modelled in the study. The impact assessment consists of five steps: 1. Selection of impact categories, category indicators and characterisation models 2. Classification—assigning LCI results to impact categories 3. Characterisation—calculating category indicator results for the inventory flows 4. Normalisation—expressing LCIA results for the product system relative to those of a reference system 5. Weighting—prioritising or assigning weights to the each impact category The first three steps are mandatory for any LCA according to the ISO 14040 standard, while the last two steps are optional.


37.5.1 Selection of Impact Categories, Classification and Characterisation The mandatory first three steps are typically automated through the choice of the LCIA method in the scope definition (see Sect. 37.3.6). Additional provisions for these steps are thus few. Calculation of LCIA results (Provisions 8.2) 1. SHALL—Classification of elementary flows: All elementary flows of the inventory shall be assigned to those one or more impact categories to which they contribute (“classification”) and that were selected for the impact assessment in the scope definition of the study. 2. SHALL—Characterisation of elementary flows: To all classified elementary flows one quantitative characterisation factor shall be assigned for each category to which the flow relevantly contributes (“characterisation”). That factor expresses how much that flow contributes to the impact category indicator (at midpoint level) or category endpoint indicator (at endpoint level)


That factor expresses how much that flow contributes to the impact category indicator (at midpoint level) or category endpoint indicator (at endpoint level). For midpoint level indicators this relative factor typically relates to a reference flow (e.g. it may be expressed in “kg CO2-equivalents” per kg elementary flow in case of Global Warming Potential). For endpoint level indicators it typically relates to a specific damage that relates to the broader area of protection. Examples are, e.g. species loss measured, e.g. as potentially displaced fraction of species for an affected area and duration (pdf*m2*a), or damage to Human health measured, e.g. in Disability Adjusted Life Years (DALYs). 3. SHALL—Calculate LCIA results per impact category: For each impact category separately, calculate the LCIA indicator results by multiplying46 the amount of each contributing (i.e. classified) elementary flow of the inventory with its characterisation factor


classified) elementary flow of the inventory with its characterisation factor. The results may be summed up per impact category, but summing up shall not be done across impact categories. Note that this is done with either the midpoint level (impact potential) or the endpoint level (damage) factors, as had to be decided in the scope definition. 4. SHALL—Separately calculate LCIA results of long-term emissions: LCIA results of long-term emissions (i.e. beyond 100 years from the time of the study) shall be calculated separately from the LCIA results that relate to interventions that occur within 100 years from the time of study. [ISO!] 46Certain LCIA methods use non-linear relationships for the characterisation; if such are used the calculation is non-linear. M.Z. Hauschild and A. Bjørn


Note: Given the different extent of uncertainty, these two sets of results will later be presented separately while discussed jointly. 5. SHALL—Separately calculate non-generic LCIA results, if included: In the case additional or modified, non-generic (e.g. geographically or otherwise differentiated) characterisation factors or LCIA methods are used, the results applying the original, generic LCIA methods shall be calculated (and later be presented and discussed) separately as well. [ISO!] 6. SHOULD—Keep results of non-LCA impacts separate: For LCIA results of impacts that are outside the LCA frame but that were considered relevant for the analysed or compared system(s) and have been included quantitatively, the inventory, impact assessment, etc. shall be kept separately for clear interpretation. [ISO+] Note that classification and characterisation of all elementary flows is typically already done in combined LCI/LCIA database packages or LCA software


[ISO+] Note that classification and characterisation of all elementary flows is typically already done in combined LCI/LCIA database packages or LCA software. In any case, this is to be checked responsibly by the LCA practitioner. The step of manual classification and assigning characterisation factors applies hence especially to newly created or imported elementary flows. It is one of the most widely found errors to not classify and characterise newly introduced flows despite of their environmental relevance. 37.5.2 Normalisation: Expressing LCIA Results Relative to Those of a Reference System Normalisation is an optional step of the LCIA which is performed in order to relate the impact scores from the characterisation to a common reference, to help put them in perspective showing which are large and which are small (compared to that reference) and possibly to prepare for a subsequent weighting. Normalisation (Provisions 8.3) 1. Normalisation is mainly applied for two purposes: 1:1


Normalisation (Provisions 8.3) 1. Normalisation is mainly applied for two purposes: 1:1. MAY—Normalisation to support interpretation: In support of the interpretation of the results of the study, normalisation is an optional step under ISO. The decision whether to include normalisation in the interpretation has been made in the scope definition.


1:2. MAY—Normalisation use in cut-off quantification: For quantification of the achieved completeness/cut-off, in a first step the indicator results for the different impact categories may be normalised by expressing them relative to a common reference, the normalisation basis (“normalisation”). [ISO+] The decision whether to include normalisation in the cut-off has been made in the scope definition where the specific normalisation basis has also been identified. 2. SHALL—Calculate normalised LCIA results per impact category: If normalisation is applied, the “normalised LCIA results” shall be calculated by dividing the LCIA results by the normalisation basis. This shall be done separately for each impact category (for midpoint level approaches) or area of protection (for endpoint level approaches). Note that normalised results shall not directly be summed up across different impact categories, as this would imply an even weighting of all impact categories


Note that normalised results shall not directly be summed up across different impact categories, as this would imply an even weighting of all impact categories. This is unless this even weighting is intended and identified explicitly as weighting when communicating the results. 37.5.3 Weighting Weighting is the last and optional step of the LCIA and it may be used in order to allow aggregation of multiple impact category results into one score or help identify the impact scores that are most important based on a preselected set of values. Weighting (Provisions 8.4) 1. Weighting is mainly applied for two purposes: 1:1. MAY—Weighting to support interpretation: In support of the interpretation of the results of the study, as an additional, optional element one may perform a “weighting” or other valuation of the—method-wise normalised or not normalised—indicator results. The decision whether to include weighting in the interpretation has been made in the scope definition. M.Z


The decision whether to include weighting in the interpretation has been made in the scope definition. M.Z. Hauschild and A. Bjørn


1:2. MAY—Weighting use in cut-off quantification: For quantification of the achieved completeness/cut-off, as second47 step the normalised indicator results for the different impact categories may be weighted across the indicators (“weighting”). [ISO+] The decision whether to include weighting in the cut-off has been made in the scope definition where the specific weighting set has also been identified 2. SHALL—Calculate weighted LCIA results per impact category: If weighting is applied, to obtain “weighted LCIA results”, the (typically normalised) LCIA results shall be multiplied by the weighting set, separately for each impact category (for midpoint level approaches and in case of having calculated category-wise endpoint results) or Area of protection (for endpoint results that cover each a whole area of protection). The resulting weighted LCIA results can be summed up across the impact categories or areas of protection, respectively. 3


The resulting weighted LCIA results can be summed up across the impact categories or areas of protection, respectively. 3. SHALL—No weighting in published comparative assertions: Weighting shall not be used in studies leading to comparative assertions intended to be disclosed to the public. Note that the setting or selection of weighting factors necessarily involves value choices. 37.6 Interpretation The interpretation is discussed in Chap. 12 of this book. It is the fifth phase of the LCA, where the results of the other phases are considered together and analysed in the light of the uncertainties of the applied data and the assumptions that have been made and documented throughout the study. The interpretation involves the following five activities: 1. Identification of significant issues 2. Completeness check 3. Sensitivity analysis 4. Consistency check 5


The interpretation involves the following five activities: 1. Identification of significant issues 2. Completeness check 3. Sensitivity analysis 4. Consistency check 5. Conclusions, limitations and recommendations 47Note that some weighting methods work without a separate, preceding normalisation, as the normalisation is part of the weighting step.


37.6.1 Identification of Significant Issues The process of interpretation starts with identification of potentially significant issues in the goal and scope definition, inventory analysis and impact assessment phases, understood as methodological choices, assumptions and specific data used in the model that have a potential to influence the outcome of the study in a significant way. Identification of significant issues (Provisions 9.2) 1. SHALL—Identify significant issues: These can be among the following: 1:1. Inventory items: Main contributing “key” life cycle stages, processes, product, waste and elementary flows, parameters. This part is also known as weak point analysis or gravity analysis. Use contribution analysis techniques. 1:2. Impact categories: Main contributing “key” impact categories (only identifiable if weighting was applied). Use contribution analysis techniques. 1:3


Use contribution analysis techniques. 1:2. Impact categories: Main contributing “key” impact categories (only identifiable if weighting was applied). Use contribution analysis techniques. 1:3. Modelling choices and method assumptions: Relevant modelling choices, such as applied allocation criteria/substitution approaches in the inventory analysis, assumptions made when collecting and modelling inventory data for key processes and flows, selecting secondary data, systematic choices on technological, geographical and time-related representativeness, methodological consistency, extrapolations, etc. Use scenario analysis techniques. 1:4. Commissioner and interested parties: The influence of the commissioner and interested parties on decisions in goal and scope definition, modelling choices, weighting sets and the like


1:4. Commissioner and interested parties: The influence of the commissioner and interested parties on decisions in goal and scope definition, modelling choices, weighting sets and the like. Discuss influences on final results and recommendations [ISO!] Note: For analysing the significant issues of unit processes and partly terminated systems, complete the system model as appropriate (e.g. cradle-to-gate) with a background system before the contribution analysis is done. Focus the contribution analysis to the unit process/partly terminated system itself (i.e. the significant flows, assumptions, parameters, processes, etc. within the original system boundary). The identification of significant issues is followed by an evaluation of these issues through a check of completeness and consistency in the handling of the issues and an analysis of the sensitivity of the outcome of the study to the significant issues


The outcome of the evaluation is used to inform previous methodological phases on the needs for strengthening the data basis of the study, driving the iterative approach that is inherent to LCA. M.Z. Hauschild and A. Bjørn


37.6.2 Completeness Check Completeness checks are performed for the inventory and the impact assessment in order to determine the degree to which the available data is complete for the processes and impacts, which were identified as significant issues. Completeness check (Provisions 9.3.2) 1. SHALL—Evaluate LCI model completeness (cut-off): The cut-off rules as defined in the scope phase shall be systematically applied to ensure that the final data set inventory/ies meets the predefined or goal-derived data quality requirements. Evaluate the completeness of the inventory data in relation to the initially defined cut-off criteria in terms of: 1:1. Process coverage: Coverage of all relevant processes in the system 1:2


Evaluate the completeness of the inventory data in relation to the initially defined cut-off criteria in terms of: 1:1. Process coverage: Coverage of all relevant processes in the system 1:2. Elementary flow coverage: Coverage of all relevant elementary flows in the inventories for the processes of the system (and in particular the key processes identified under Significant issues), that have characterisation factors for the relevant impact categories (according to the goal of the LCI/LCA study) 1:3. Operationalise cut-off approximation: The cut-off criteria/approach and percentage as defined in the scope phase shall be used. This may be operationalised using stepwise the following cut-off rules for flow properties, pre-checking property by property the achieved completeness across all flow types and balancing the aggregated numbers in the inputs against those of the outputs: [ISO+] 1:3:1


For product flows: “mass” (of individual key chemical elements), “energy content”, “market value” (or “production/provision cost”, especially for purchased services). 1:3:2. For waste flows: “mass” (of individual key chemical elements), “energy content”, “treatment cost”. 1:3:3. For elementary flows: “mass” (of individual key chemical elements and only for the environmentally relevant flows, i.e. excluding not or less relevant flows such as, e.g. incineration air consumed and waste steam leaving the process as emission to air), “energy content”. 1:4. Cut-off for comparative assertions: The cut-off shall always be met also by mass and energy, in addition to environmental impact. 1:5. Additional relevance criteria for elementary and waste flows: Also those emissions and wastes should be include in the data collection that have a low mass and energy content but a known relevance for the respective type of processes or industry (using, e.g. legal limits and expert judgement). [ISO +] 1:6


legal limits and expert judgement). [ISO +] 1:6. Approximating the 100% value: The 100% reference of completeness may be approximated by using “best approximation” values for all initially missing information and data, using among others information from similar


processes and expert judgement. This missing information and data can be especially: [ISO+] 1:6:1. kind and quantity of initially missing flows, 1:6:2. element composition and energy content of all flows that relevantly contribute to the total mass of the flows, 1:6:3. cost of all goods and services that relevantly contribute to the total production cost and production value 1:6:4. environmental impact of yet missing background data sets for consumed goods and services. 1:7. Estimating precision of 100% value approximation: The precision of the 100% approximation may be judged from analysing the share of the different quality levels of the data that make up the inventory: a higher share of low quality data also makes the 100% approximation less precise. [ISO+] 1:8. Completeness of impact: As last step, and using the quantitative cut-off value decided upon in the scope definition, approximate the achieved degree of completeness/cut-off. [ISO+] 1:9


[ISO+] 1:8. Completeness of impact: As last step, and using the quantitative cut-off value decided upon in the scope definition, approximate the achieved degree of completeness/cut-off. [ISO+] 1:9. Leaving out negligible flows: It is an option to leave out negligible flows that jointly make up less than 10% of the share of impact that is cut-off (e.g. if the completeness is 95%, 5% are cut-off. 10% of these 5% are 0.5% that are considered negligible.) It is recommended, however, to not leave them out. [ISO+] Note that the LCIA methods and (potentially) normalisation and weighting for use in defining the cut-off was decided in the scope phase. Note that for unit processes and partly terminated systems the completeness is to be judged in relation to the unit process and partly terminated system itself, i.e


Note that for unit processes and partly terminated systems the completeness is to be judged in relation to the unit process and partly terminated system itself, i.e. any lack of completeness of other processes that were added exclusively to complete the system model for the completeness check shall be disregarded when quantifying the achieved completeness. 2. SHOULD—Improve completeness, if needed: In the case of insufficient completeness, the inventory analysis (and sometimes the impact assessment) phases should be revisited to increase the degree of completeness. It is recommended to focus on the key life cycle stages, processes and flows identified as significant issues. This improvement of the LCI data is, however, to be started by potentially fine-tuning or revising goal and scope, i.e. with a complete iteration. 3


This improvement of the LCI data is, however, to be started by potentially fine-tuning or revising goal and scope, i.e. with a complete iteration. 3. SHALL—Report final completeness; potentially revise scope or goal: If the aimed at completeness has been achieved, or if it cannot be increased further, the finally achieved degree of completeness shall be reported (as % degree of completeness/cut-off). For LCA studies, it shall be considered when later formulating the limitations in the conclusions and recommendations. If the aimed M.Z. Hauschild and A. Bjørn


at or necessary completeness cannot be achieved, it shall be decided whether the scope or even the goal needs to be revised or redefined. 37.6.3 Sensitivity Analysis Sensitivity analysis has the purpose of identifying the key processes and most important elementary flows as those elements which contribute most to the overall impacts from the product system. Sensitivity check (of accuracy and precision) (Provisions 9.3.3) 1. SHALL—Check sensitivity of results: Check to what extent the accuracy and precision of the overall results meets the requirements posed by the intended applications. Aim at improving it to the required level, as follows: 1:1. Sensitivity of significant issues: Identify the most sensitive among the significant issues identified earlier and analyse the sensitivity of these for the overall results, along with their stochastic and systematic uncertainty estimates


The outcome is determining for the accuracy and precision of the overall results and the strength of the conclusions, which can be drawn from the LCI/LCA study and must be reported together with these. Be aware that calculated uncertainty figures may not include the often-determining systematic uncertainties caused by model assumptions, data gaps and lack of accuracy. 1:1:1. Sensitivity of LCI items: Evaluate the sensitivity of the LCIA results (or weighted LCIA results, if applied) to key flows, process parameter settings, flow properties and other data items such as recyclability, life-time of goods, duration of services steps and the like. Assess how sensitive inventory items influence the data representativeness, and precision. [ISO!] 1:1:2. Sensitivity of LCIA factors: Evaluate the sensitivity of the LCIA results (or weighted LCIA results, if applied) considering the often widely differing uncertainty of the results due to uncertainties in the impact assessment (e.g


Human toxicity, Ecotoxicity, etc. with high uncertainties and Global warming, Acidification, etc. with lower uncertainty). [ISO!] 1:1:3. Sensitivity of modelling choices and assumptions: Evaluate the sensitivity of the LCIA results (or weighted LCIA results, if applied) to different modelling choices and method assumptions (“method issues”), e.g. quantitative and qualitative aspects of the functional unit, superseded processes, allocation criteria, etc. [ISO!] 1:2. Improve robustness of sensitive issues data, parameters, impact factors, assumptions, etc. as possible: In the case of lack of quality for some of the significant issues, revisit the inventory analysis and/or the impact assessment phases to improve the concerned data (for data issues), impact factors (for LCIA issues), or try to qualify and discuss the sensitive assumption or


choice (for method issues). As for data completeness, also the improvement of the LCI data precision is, however, to be started by potentially fine-tuning or revising goal and scope, i.e. with a complete iteration. 1:3. Report final achievements; potentially revise scope or goal: If the certainty of key issues does not meet the needs, or if it cannot be increased to obtain the accuracy and precision that is required by the application of the LCI/LCA study, it shall be decided whether the scope or even the goal needs to be revised or redefined. This shall be reported and for LCA studies later be considered when formulating the limitations in the conclusions and recommendations from the LCA. 37.6.4 Consistency Check A consistency check is performed to investigate whether the assumptions, methods and data, which have been applied in the study, are consistent with the goal and scope and whether they have been performed consistent for the compared product systems in comparative studies


Consistency check (Provisions 9.3.4) For partly terminated systems, LCI results and LCIA results data sets these provisions serve in addition to ensure method consistency across the processes of the model. For LCA studies, they serve in addition to ensure method consistency across the models of the compared systems. 1. SHALL—Data quality sufficiently consistent? Check whether any differences in data quality per se (i.e. accuracy, completeness and precision) and in the selected data sources for the different processes in the system(s) are consistent with the goal and scope of the study. This is especially relevant for comparative studies. 2. SHALL—Method choices consistent? Check whether all methodological choices (e.g. LCI modelling principles, allocation criteria or system expansion/substitution approach, system boundary, etc.) are consistent with the goal and scope of the study including the intended applications and target audience


This shall be judged by checking whether the method provisions have been met that are given in relation to the applicable Situation A, B, or C1/C2. [ISO!] M.Z. Hauschild and A. Bjørn


Note that method consistency applies on both unit process level (i.e. consistent approach to develop unit process from raw data) and system level (i.e. consistently modelling the system). This aspect is especially relevant when combining data from different sources. 3. SHALL—Consistent impact assessment? Check whether the steps of impact assessment (including normalisation and weighting, if included) have been consistently applied and in line with goal and scope. 4. SHALL—Evaluate relevance of inconsistencies: Evaluate the relevance/significance of any identified inconsistencies (as above) for the results and document them, including when reporting the achieved method consistency and appropriateness. For LCA studies additionally consider these findings when drawing conclusions or recommendations from the results


For LCA studies additionally consider these findings when drawing conclusions or recommendations from the results. 37.6.5 Conclusions, Limitations and Recommendations Building on the outcome of the other elements of the interpretation, and drawing on the main findings from the earlier phases of the LCA, the final element of the interpretation has to draw conclusions and identify limitations of the study, and develop recommendations to the intended audience in accordance with the goal definition and the intended applications of the results. Conclusions, limitations and recommendations (Provisions 9.4) Note the limitations for Situation C1 and C2 studies in their use for direct decision support. These provisions apply only to comparative and non-comparative LCA studies. 1


These provisions apply only to comparative and non-comparative LCA studies. 1. SHALL—Analyse the results in a systems perspective: Separately analyse and jointly discuss the results obtained in the main system(s) model(s) and— if performed—with the corresponding reasonably worst and best case assumption scenarios and possibly further assumption scenarios. Integrate the results of any potentially performed uncertainty calculations into the analysis. [ISO!] 1:1. Items that require special or separate analysis: 1:1:1. Non-generic LCIA: Separately analyse and jointly discuss the results obtained with the default LCIA methods and those obtained including any


potential additional or modified/non-generic (e.g. spatially or otherwise differentiated) LCIA methods. 1:1:2. Long-term emissions: Separately analyse and jointly discuss the results for interventions within the first 100 years from the time of the study and those beyond that time limit. 1:1:3. Carbon storage and delayed emissions: Only if such is included in line with an explicit goal requirement: Separately analyse and jointly discuss the results including and excluding carbon storage and delayed emissions/reuse/recycling/reuse credits. 1:2. Draw conclusions, if foreseen: Take into account the findings of the earlier elements of the interpretation phase. Draw conclusions in accordance with the goal defined for the LCA study and with the definitions of the scope, in particular those related to data quality requirements, and with the predefined assumptions and known limitations in the methodology and its application in the LCA


Consider all assumptions and related limitations that were noted down in the course of the study. 1:3. Address impacts outside the LCA scope, if any: Name any potential or actual effects on the three areas of protection that are based on other mechanisms than those covered by LCA (e.g. accidents, direct application of products to humans, etc.) and that are considered relevant by the interested parties. Clarify that these are outside the scope of LCA. Note that within the ILCD Handbook, not quantified effects outside the scope of LCA cannot be explicitly or implicitly assessed regarding their relevance in comparison to the LCA results.48 1:4. Conclusions for comparisons: Differences in data quality and methodological choices between compared systems shall be consistent with the goal and scope of the study, especially: 1:4:1. The functional unit of the compared alternatives shall be sufficiently similar to allow for comparisons, especially in view of stakeholders and potential users


The functional unit of the compared alternatives shall be sufficiently similar to allow for comparisons, especially in view of stakeholders and potential users. 1:4:2. The setting of system boundaries shall be consistently applied to all systems. 1:4:3. The inventory data should be of comparable quality (i.e. accuracy, completeness, precision, methodological consistency) for all compared alternatives. 48Effects outside the scope of LCA may be—if available and quantified in a comparable manner (e.g. quantitatively related to the functional unit, considering the whole life cycle etc.)—integrated with LCA results in an additional evaluation and report beyond the scope of LCA and outside the scope of the ILCD. This should consider the relative accuracy and precision of the different approaches and effects. M.Z. Hauschild and A. Bjørn


1:4:4. The steps of impact assessment shall be consistently applied for all systems. 1:4:5. The significance of any above identified inconsistencies to the results of the comparison shall be evaluated and considered when drawing conclusions and giving recommendations from the results. 2. SHALL—Recommend strictly based on conclusions and limitations: 2:1. Base any recommendations made in the LCA study exclusively on these conclusions and respecting the limitations. Derive recommendations unambiguously and in a stepwise logical and reasonable consequence of the conclusions. Do so in accordance with the defined goal of the LCA study and specially the intended applications and target audience. 2:2. Recommendations shall be made in a conservative way, only based on significant findings. Any relevant limitations found during the study are to be stated explicitly and clearly in the key message of the LCA study including in the executive summary. [ISO!] 2:3


Any relevant limitations found during the study are to be stated explicitly and clearly in the key message of the LCA study including in the executive summary. [ISO!] 2:3. Special care must be taken to avoid misinterpretations also by a non-technical audience, to avoid interpretation beyond the scope of the LCA study and beyond what is supported by its outcome. 2:4. Equality of compared alternatives shall not be stated, unless it has been shown to be significant: the lack of significant differences alone shall not be misinterpreted as equality of the analysed options. It shall only be stated that with the given data restrictions and/or uncertainties or other causes no significant differences could be identified. [ISO!] 3. SHALL—Comparisons of systems with dominant subjective preference: The results and recommendations of comparative studies on not objectively comparable alternatives (e.g


[ISO!] 3. SHALL—Comparisons of systems with dominant subjective preference: The results and recommendations of comparative studies on not objectively comparable alternatives (e.g. personal services, fashion items, jewellery) shall be presented with the explicit statement that comparability is not assumed per se, but lies with the individual preference and judgement. [ISO!] 4. SHALL—Conclusions on basket-of-product type of studies: For studies that analyse several processes or systems in a non-competitive manner, i.e. processes/systems that perform clearly different functions (e.g. basket-ofproducts, identifying priority products) it shall be clearly reported that no comparability exists in terms of preferability among the processes/systems. EC-JRC European Commission-Joint Research Centre—Institute for Environment and Sustainability.: International Reference Life Cycle Data System (ILCD) Handbook—General guide for Life Cycle Assessment—Detailed guidance. First edition March 2010


First edition March 2010. EUR 24708 EN. Luxembourg. Publications Office of the European Union (2010) ISO 14001:2015.: Environmental Management Systems—Requirements with Guidance for Use. The International Organization for Standardization, Geneva ISO 14015:2001.: Environmental Management—Environmental Assessment of Sites and Organizations (EASO). The International Organization for Standardization, Geneva


ISO 14024:1999.: Environmental labels and declarations—type I environmental labelling— principles and procedures. The International Organization for Standardization, Geneva ISO 14025:2006.: Environmental Labels and Declarations—Type III Environmental Declarations —Principles and Procedures. The International Organization for Standardization, Geneva ISO 14031:2013.: Environmental Management—Environmental Performance Evaluation— Guidelines. The International Organization for Standardization, Geneva ISO 14040:2006.: Environmental Management—Life Cycle Assessment—Principles and Framework. The International Organization for Standardization, Geneva ISO 14044:2006.: Environmental Management—Life Cycle Assessment—Requirements and Guidelines. The International Organization for Standardization, Geneva ISO/TR 14062:2002.: Environmental management—Integrating Environmental Aspects into Product Design and Development


The International Organization for Standardization, Geneva ISO/TR 14062:2002.: Environmental management—Integrating Environmental Aspects into Product Design and Development. The International Organization for Standardization, Geneva Author Biographies Michael Z. Hauschild involved in development of LCIA methodology since the early 1990s. Has led several SETAC and UNEP/SETAC working groups and participated in the development of the ISO standards and the ILCD methodological guidelines. Main LCA interests are chemical impacts, spatial differentiation and science-based boundaries in LCIA. Anders Bjørn part of the LCA community since the early 2010s. Main focus is interpretations of sustainability and integration of sustainability targets in LCA to enable absolute sustainability assessments. M.Z. Hauschild and A. Bjørn


Part V


Chapter 38 Report Template Anders Bjørn, Alexis Laurent and Mikołaj Owsianiak Abstract To ensure consistent reporting of life cycle assessment (LCA), we provide a report template. The report includes elements of an LCA study as recommended but the ILCD Handbook. Illustrative case study reported according to this template is presented in Chap. 39. The following LCA report template presents the structure and summarised content of an LCA report that is recommended in the ILCD Handbook1. The content should be covered by any LCA report, but the proposed sub-subsections (level 3) may be merged or divided and their sequence may be changed if appropriate. The ILCD Handbook operates with three reporting levels: 1. Internal use by commissioner of study. 2. Third party, i.e. a limited, well-defined list of recipients with at least one organisation that has not participated in the study. 3. Comparative studies to be disclosed to the public


2. Third party, i.e. a limited, well-defined list of recipients with at least one organisation that has not participated in the study. 3. Comparative studies to be disclosed to the public. There are no formal ILCD reporting requirements for level 1, but ILCD recommends following the requirements of level 2. More requirements apply to level 3 than to level 2. The following template applies to both level 2 and level 3 studies (special requirements for level 3 are highlighted here for the reader). The reporting template has been used in the reporting of the illustrative case on window frames in Chap. 39. A. Bjørn  A. Laurent  M. Owsianiak Division for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark A


39. A. Bjørn  A. Laurent  M. Owsianiak Division for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark A. Bjørn (&) CIRAIG, Polytechnique Montréal, 3333 Chemin Queen-Mary, Montreal, QC, Canada e-mail: anders.bjoern@polymtl.ca 1EC-JRC (2010) European Commission—Joint Research Centre—Institute for Environment and Sustainability: International Reference Life Cycle Data System (ILCD) Handbook—General guide for Life Cycle Assessment—Detailed guidance. First edition March 2010. EUR 24708 EN. Luxembourg. Publications Office of the European Union. © Springer International Publishing AG 2018 M.Z. Hauschild et al. (eds.), Life Cycle Assessment, DOI 10.1007/978-3-319-56475-3_38


38.1 Executive Summary Summarises in a non-technical language the key elements of the goal and scope of the studied system (including the definition of functional unit), the main results from the inventory analysis (including data sources for the foreground system) and the impact assessment components and major conclusions and/or recommendations made. 38.2 Technical Summary Summarises in a technical language the goal and scope, with relevant limitations and assumptions, a flow diagram of the studied system, the main results from the inventory and impact assessment components (including data sources, major assumptions, and key figures or tables) with consideration of the sensitivity and uncertainty analyses and conclusions and/or recommendations made. 38.3 Main Report 38.3.1 Goal Definition 38.3.1.1 Intended Application(s) States in a precise and unambiguous way the intended application (e.g


38.3 Main Report 38.3.1 Goal Definition 38.3.1.1 Intended Application(s) States in a precise and unambiguous way the intended application (e.g. comparison of specific goods or services, weak point analysis of a specific product or greening the supply chain). 38.3.1.2 Method Assumptions and Impact Limitations States limitations of the study’s usability due to (1) choice of methods implying, for example, a limited representation of temporal/spatial variations, and (2) limited impact coverage, e.g. only performing carbon footprinting. 38.3.1.3 Reasons for Carrying Out the LCA Study and Decision Context Explains why the study was commissioned and classifies its decision context to Situation A, B, C1 or C2.


38.3.1.4 Target Audience States to whom the results of the study are intended to be communicated in order to help identifying the requirements to a critical review (if any) and the appropriate form and technical level of reporting. 38.3.1.5 Comparative Assertions to be Disclosed to the Public States if the LCA study includes a comparative assertion intended to be disclosed to the public, since stricter reporting requirements exist for such studies compared to studies only intended for internal use by the commissioner or for specified third parties. 38.3.1.6 Commissioner of the LCA Study and Other Influential Actors Identifies commissioner(s), including co-financers, and other actors having an influence on the study. 38.3.2 Scope Definition 38.3.2.1 Deliverables Lists the required deliverables of the study (typically LCI and LCIA results), which should be derived from the intended application (Sect. 3.1.1)


38.3.2 Scope Definition 38.3.2.1 Deliverables Lists the required deliverables of the study (typically LCI and LCIA results), which should be derived from the intended application (Sect. 3.1.1). 38.3.2.2 Function, Functional Unit and Reference Flows States the function(s) of the assessed product system(s), associated functional unit (“what”, “how much”, “how well”, “where” and “how long/many times”?) and derived reference flow(s), to which all other flows quantitatively relate. 38.3.2.3 LCI Modelling Framework Based on the identified decision context (Sect. 3.1.1), it is specified whether an attributional or consequential modelling framework (or a combination of the two) is to be followed in the inventory analysis. Report Template


38.3.2.4 System Boundaries and Completeness Requirements Presents system boundaries, including a schematic representation and associated choices of completeness requirements, that are used to determine which processes should be within the system boundaries and which may be excluded. 38.3.2.5 Representativeness of LCI Data Describes the requirements of inventory data with respect to spatial, temporal and technological representativeness in accordance with the goal of the study. 38.3.2.6 Basis for Impact Assessment Describes the selection of impact categories and corresponding LCIA models in accordance with the goal of the study for which compatible inventory data is collected. 38.3.2.7 Requirements for Comparative Studies Only applicable to level 3 studies according to ISO standards. However, in line with ILCD requirements, we recommend to include this section for all comparative studies. It presents special considerations for comparative studies related to, e.g


However, in line with ILCD requirements, we recommend to include this section for all comparative studies. It presents special considerations for comparative studies related to, e.g. data quality requirements, exclusion of identical processes and interpretation in light of affected stakeholders. 38.3.2.8 Critical Review Needs Describes the requirements for critical review (for example in case of public disclosure), the form of the review and who is eligible to perform it. 38.3.3 Life Cycle Inventory Analysis 38.3.3.1 LCI Model at System Level Presents one or more flow diagrams that clearly describe the details of the foreground system and links to the background system, and all major inputs and outputs. For simple systems, such a diagram may already have been presented in sufficient detail under “System boundaries and completeness requirements” (Sect. 3.2.4), in which case, it should be skipped here. For complex systems, the


use of an Annex can be useful to detail graphically the different parts of the system (so as not to overload the main report); cross-references to the Annex should be made when describing the system modelling and inventory building. 38.3.3.2 Data Collection Presents in a table format a synthetic overview (1 page max.) of the data sources in terms of specificity, type, source and access. This part can provide the reader with a brief overview of the data collected and processed in the modelling of the system. Dividing the table between the different life cycle stages can help structuring this overview and outline the different elements to address in Sect. 3.3.3


Dividing the table between the different life cycle stages can help structuring this overview and outline the different elements to address in Sect. 3.3.3. 38.3.3.3 System Modelling Per Life Cycle Stage Details in plain text for each life cycle stage (raw materials stage, production stage, use stage, disposal stage, etc.) the data collected and their further treatment, including main assumptions and evaluations of their reliability (based on data sources used) and uncertainty (to prepare the basis of sensitivity and uncertainty analyses). For clarity, a division of this section into subsections is advocated: a subsection addressing each life cycle stage, and possibly others focusing on key modelling aspects (e.g. electricity supply modelling, when complex scenarios are analysed). From this section, the reader should be able to get a clear and comprehensive overview of the system modelling over its entire life cycle, including all the major assumptions and underlying uncertainties


To make the study fully reproducible, it is recommended to complement this part with an Annex detailing all the assumptions (including minor assumptions), calculations made, detailed unit process data collected for the foreground system, detailed data for modelling of the background system (e.g. detailed scenario description for the disposal stages or for energy systems), and any other relevant information for the system modelling. Cross-references to those different elements in Annex should be made in the main report. 38.3.3.4 Calculated LCI Results Contains the final LCI results at a level of aggregation required for the intended applications. This section is particularly relevant for studies only aiming at deriving LCI results, where the LCI results should provide a comprehensive listing of elementary flows for the entire system


This section is particularly relevant for studies only aiming at deriving LCI results, where the LCI results should provide a comprehensive listing of elementary flows for the entire system. For studies performing an impact assessment, this section may still be relevant to capture the resulting LCI results for the foreground system that may not be available in existing LCI databases and may thus serve as input data for other LCA studies. Tables detailing these LCI results for Report Template


each process should be documented in Annex and cross-references should be done in this brief section. 38.3.3.5 Basis for Sensitivity and Uncertainty Analyses Describes how sensitivity and uncertainty analyses are conducted. Sensitivity and uncertainty analyses should be documented by listing the different parameters tested and describing their uncertainty characteristics such as statistical distribution and variance (for example in a table format), and the methods adopted to conduct these analyses. This section can then be referenced in other sections of the report (e.g. sensitivity check) as the place to find all the methodological details for the sensitivity and uncertainty analyses. 38.3.4 Life Cycle Impact Assessment Presents characterised, normalised (optional) and weighted (optional) results graphically or in table format at a level and type of aggregation that reflects the goal and scope of the study (e.g


results split per life cycle stage, product flows or elementary flows of interest, as relevant). It is often beneficial to merge this section with the section “Interpretation” (see Sect. 3.5) to improve the readability of the report. The results can then be displayed alongside their interpretation and associated intermediate conclusions. 38.3.5 Interpretation 38.3.5.1 Significant Issues Identifies the issues (e.g. methodological choices and assumptions, inventory data, and characterisation or normalisation factors), which have the potential to change the final results of the LCA. The identification of issues often relies on contribution analyses, at a process level (which process contributes the most to the impact indicators?) and/or at a substance level (which substance is the largest contributor to a given impact indicator result?). Such analysis should be documented here


Such analysis should be documented here. 38.3.5.2 Sensitivity and Uncertainty Analyses Checks Quantify the sensitivity of results to different elements of the LCA based on information about the uncertainties of significant issues among inventory data, impact assessment data and methodological assumptions and choices. Calculate the


uncertainty of the study’s central conclusions (e.g. how certain is it that Product A has a lower environmental impact than Product B?). Cross-references to the Sect. 3.3.5 can be made to ease the readability and understanding of the uncertainty and sensitivity analyses. 38.3.5.3 Completeness and Consistency Checks Consists in two separate sub-sections that briefly document that both completeness and consistency checks have been done. The completeness check aims to ensure, in light of the goals and scope of the study, a sufficient completeness of the inventory and impact assessment data that have been identified as necessary for performing the LCA study. The consistency check investigates whether the assumptions, methods and data have been applied in a consistent way, e.g. consistent choice of the LCI modelling framework, well-argued setting of system boundaries, consistence across all LCIA steps (characterisation, normalisation, weighting), etc


consistent choice of the LCI modelling framework, well-argued setting of system boundaries, consistence across all LCIA steps (characterisation, normalisation, weighting), etc. 38.3.6 Conclusions, Limitations and Recommendations Presents conclusions encompassing the entire study, limitations for the usability of these conclusions, based on the above interpretation sections, and resulting recommendations, based on the intended application of the study. Annex (Public) Serves to document elements that would inappropriately interrupt the reading flow of the main part of the report and should include questionnaire/data collection template and raw data, full list of all assumptions and full LCI details and results. Cross-references to the different elements of the Annex should be made in the main report. Note that only non-confidential data should be reported in this appendix


Cross-references to the different elements of the Annex should be made in the main report. Note that only non-confidential data should be reported in this appendix. Annex (Confidential) This Annex is complementary to the main Annex (public), and only applicable in case confidential data were used in the study. This confidential Annex contains all those data and information that are sensitive or proprietary and cannot be made externally available (only available to the critical reviewers under confidentiality agreements). Report Template


List of all sources referred to in the report Author Biographies Anders Bjørn part of the LCA community since the early 2010s. Main focus is interpretations of sustainability and integration of sustainability targets in LCA to enable absolute sustainability assessments. Alexis Laurent working with LCA since 2010 with a strong LCIA focus, particularly on normalisation aspects. Main LCA interests include development of LCIA methods, LCA applications and footprinting of large-scale systems for policy-making (e.g. nations, sectors), and LCA applied to various technology domains, including energy systems. Mikołaj Owsianiak involved in development and application of life cycle impact assessment methods in sustainability assessment of technologies. Has worked on issues associated with: soils (remediation), metals (toxic impact assessment), biodiesel (fate in the environment), and carbonaceous materials (biochar and hydrochar).


Chapter 39 Illustrative Case Study: Life Cycle Assessment of Four Window Alternatives Mikołaj Owsianiak, Anders Bjørn, Heidi B. Bugge, Sónia M. Carvalho, Leise Jebahar, Jon Rasmussen, Caroline M. White and Stig Irving Olsen Abstract This report serves as an example report on how to perform an LCA according to the guidance given in Chap. 37 and how to structure the report according to the reporting template in Chap. 38. The goals of the LCA were (i) to perform a benchmarking of a prototype wood/composite (W/C) window made out of glass fibre against three alternative window types currently offered in the market (made of wood (W), wood/aluminium (W/ALU), and PVC) and (ii) to identify environmental hotspots for each window system


39.1 Executive Summary Nor-win, a Danish-based windows manufacturer, commissioned an LCA study with the goals (i) to perform a benchmarking of a prototype wood/composite (W/C) window made out of glass fibre against three alternative window types currently offered in the market (made of wood (W), wood/aluminium (W/ALU), and PVC) and (ii) to identify environmental hotspots for each window system. The compared windows differ regarding their ability to prevent heat from escaping the building (insulation performance). The four window types are compared on the basis of their main function, which is allowing daylight inside the building. The functional unit is thus “Allow daylight M. Owsianiak (&)  A. Bjørn  S.M. Carvalho  L. Jebahar  J. Rasmussen  C.M. White  S.I. Olsen Division for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark e-mail: miow@dtu.dk A


White  S.I. Olsen Division for Quantitative Sustainability Assessment, Department of Management Engineering, Technical University of Denmark, Kongens Lyngby, Denmark e-mail: miow@dtu.dk A. Bjørn CIRAIG, Polytechnique Montréal, 3333 Chemin Queen-Mary, Montréal, QC, Canada H.B. Bugge Ecolabelling Denmark, Danish Standards Foundation, Göteborg Plads 1, Nordhavn, Denmark © Springer International Publishing AG 2018 M.Z. Hauschild et al. (eds.), Life Cycle Assessment, DOI 10.1007/978-3-319-56475-3_39


into a residential building through a physical barrier, equivalent to light being transmitted through an area of 1.82 m2 with visible light transmittance of at least 0.6, for 20 years”. System boundaries comprise all life cycle stages from cradle to grave, including transportation and provision of utilities (electricity or heat). The manufacturing technology for all four windows, including the elements composing the pane and the frame, represent the technology, which is currently used by Nor-win and its suppliers. Nor-win is the provider of primary data used in the product system model. Generic databases were used for background processes and for some foreground processes for which no primary data could be retrieved from the suppliers. The results show that for most impact categories the impact scores follow the order W/C < W = W/ALU < PVC


The results show that for most impact categories the impact scores follow the order W/C < W = W/ALU < PVC. The W/C window has the lowest environmental impact in all 14 impact categories, while the PVC window system has the highest impact for 10 impact categories. For nearly all the non-toxicity-related impact categories, the life cycle impacts of the four windows correspond to approximately 10% of the total annual average impacts of an average EU27 citizen in the year 2010. The main contributor of environmental impacts is the generation of indoor heating to compensate for heat losses through the window. The contribution of this process to the total life cycle impact is for all four windows around 90% for climate change, freshwater eutrophication, or resource depletion, and above 50% for nearly all other impact categories


The manufacturing stage is relevant for impacts on stratospheric ozone depletion, and ionising radiation (human health) across all windows, for impacts on freshwater ecotoxicity and human toxicity (PVC window), and land use (W window). Several assumptions had to be made for the modelling of the product systems. While most of them were not found to be important for our conclusions, the modelling of chromium steel and galvanised steel using the same processes may influence impact scores in the categories human health (cancer effects) and freshwater ecotoxicity due to associated differences in emissions of chromium (VI) and zinc (II). The impact scores were the most sensitive to the insulation capacity (Uvalue) of the window, and the ranking of the window alternatives does not change when the EU27 heat mix is used instead of the Danish mix. Overall, results show that there is a trade-off between types of material used and improved insulation properties of windows


Overall, results show that there is a trade-off between types of material used and improved insulation properties of windows. The use of glass fibre-based composite in the W/C has some contribution (up to 12%) to total impacts, depending on the impact category, but the use of the composite substantially improves insulation properties causing an overall reduction in environmental impacts, and leading to the superiority of this window type. The design of windows to ensure better environmental performance should focus on optimising insulation properties of windows, which can be done either by improving the design of the frame or by introducing an additional pane that helps improving insulation properties of the whole window.


39.2 Technical Summary Nor-win, a Danish-based windows manufacturer, wishes to position itself as a proactive company on the market in terms of environmental sustainability, with the ambition to attract customers demanding more environmentally friendly products. For this purpose, an LCA study was commissioned with the goals (i) to perform a benchmarking of a prototype of a wood/composite (W/C) window made out of glass fibre against three window types currently offered in the market (made of wood (W), wood/aluminium (W/ALU), and PVC) and (ii) to identify environmental hotspots for each window system. The deliverables include (i) detailed life cycle inventory model of the compared systems, including unit process data; (ii) life cycle impact assessment results (in both characterised and normalised forms). We follow EU-recommended practice for characterisation modelling at midpoint to quantify life cycle impacts of four window alternatives, referred to as ILCD


We follow EU-recommended practice for characterisation modelling at midpoint to quantify life cycle impacts of four window alternatives, referred to as ILCD. Normalisation was carried out using a set of normalisation references for the year 2010. The functional unit is “Allow daylight into a residential building through a physical barrier, equivalent to light being transmitted through an area of 1.82 m2 with visible light transmittance of at least 0.6, for 20 years”. Decision context is micro-level, product or process-related decision support studies, i.e. situation A of the ILCD guideline (EC-JRC 2010). Consequently, the attributional principle was chosen as LCI modelling principle. Major properties of the four window alternatives are presented in Table 39.1. The window’s ability to prevent heat from escaping the building is described by its heat transfer coefficient—the U-value (W m−2 K−1)


The window’s ability to prevent heat from escaping the building is described by its heat transfer coefficient—the U-value (W m−2 K−1). The fraction of light that enters through the window into the building is characterised by its visible light transmittance (Tvis)


The fraction of light that enters through the window into the building is characterised by its visible light transmittance (Tvis). Table 39.1 Major properties of the four window alternatives Properties Window type W W/ALU PVC W/C Frame material Mainly wood Mainly wood and aluminium Mainly polyvinyl chloride and galvanised steel Mainly wood and polyamide/glass fibre composite Glass material 2-layered, coated, sealed with silicone, filled with argon 2-layered, coated, sealed with silicone, filled with argon 2-layered, coated, sealed with silicone, filled with argon 2-layered, coated, sealed with silicone, filled with argon U-value (W m−2 K−1) 1.29 1.31 1.36 1.08 Tvis (fraction) 0.8 0.8 0.8 0.8 Glass dimensions (m) 1.23  1.48 1.23  1.48 1.23  1.48 1.23  1.48 Wood (W), wood/aluminium (W/ALU), polyvinyl chloride (PVC) and wood/composite (W/C) Illustrative Case Study: Life Cycle Assessment ...


The analysis comprises all life cycle stages from cradle to grave, including transportation and provision of utilities (electricity or heat). The manufacturing technology for all four windows, including the elements composing the pane and the frame, represent the technology, which is currently used by Nor-win and its suppliers. Nor-win is the supplier of primary data used to model the LCI. Ecoinvent and Plastics Europe databases were used for background processes and as source of data for some foreground processes for which no primary data could be retrieved from the suppliers (PlasticsEurope Database 2016; Ecoinvent 2010)


The major assumptions made in inventory modelling include (i) the wood-based windows are sold mainly in Scandinavian countries and Germany, but the use and disposal stages for all windows are modelled using data from processes representative for Denmark; (ii) windows are used only in buildings that are heated by district heating (in Denmark district heating delivers ca


55% of the total heat demand for buildings); (iii) processes used to model the district heat mix technologies were representative for Norway (except for incineration of bio-waste, which was representative for Switzerland); (iv) energy used for operation of the manufacturing and disassembly facilities for the W/C window is assumed equal to those for other windows, while energy requirements for window disassembly are assumed equal to 1 MJ per kg of dismounted window; (v) losses of materials during production are not considered and all recycled materials replace virgin materials in Extraction of crude oil Extraction of bauxite Refining Chemicals & polymers Forestry Production of aluminium Aluminium parts Production of wood Wooden parts Mining of silica Mining of iron Surface treatment Production of chrom


steel Steel parts Production of glass Extraction of argon Window frame Window assembly Use (heat loss) Dissasembly Recycling of glass Recycling of aluminium Recycling of steel Landfilling Incineration Window pane Packaging Production of cardboard Production of GFK Heat and power Glass cullets Steel billet Aluminium ingot background processes foreground processes Fig. 39.1 Flow diagram for the wood/composite window (W/C) product system. Red line indicates foreground processes. Grey boxes indicate avoided processes


the market at a 1:1 ratio without considering any loss of material functionality in the recycling; and (vi) production of chromium steel and galvanised steel was modelled using the same process, while landfilling of EDPM rubber was modelled as that of polypropylene. The flow diagram of the prototype W/C window is presented in Fig. 39.1. All four window alternatives have impacts within the same order of magnitude, and for most impact categories the impact scores follow the order W/C < W = W/ALU < PVC (Table 39.2). The W/C window has the lowest environmental impact in all 14 impact categories, while the PVC window system has the highest impact scores for 10 impact categories. For nine out of these 10 impact categories the differences in impact scores between the W/C and PVC windows are deemed statistically significant (i.e. the calculated 95% probability ranges of the impact scores do not overlap)


the calculated 95% probability ranges of the impact scores do not overlap). For nearly all the non-toxicity-related impact categories, the life cycle impacts of the four windows correspond to approximately 0.1 person equivalents. Process contribution analysis showed that the main driver of environmental impacts was the production of house heating to compensate for heat losses through the window. The contribution of this process to the total impact is around 90% for climate change, freshwater eutrophication, or resource depletion across all four windows, and above 50% for nearly all other impact categories. The manufacturing stage was relevant for impacts on stratospheric ozone depletion, and ionising radiation (human health) across all windows, and for the impacts on freshwater ecotoxicity, human toxicity (PVC window), and land use (W window)


Most of the assumptions made when modelling the LCI were not found to be important for the conclusions, except that modelling of chromium steel and galvanised steel using the same processes may influence impact scores in human health (cancer effects) and freshwater ecotoxicity due to associated differences in emissions of chromium (VI) and zinc (II). The impact scores were the most sensitive to the U-value of the window, and the ranking of window alternatives does not change when the EU27 heat mix is used instead of the Danish mix. Overall, the major conclusions of this LCA are: I. The W/C window performs significantly better compared to its alternatives in all 14 impact categories. The W/C window is thus the preferable option from an environmental perspective. II. The PVC window is the least preferred option, as it performs the worst in 11 out of 14 impact categories


The W/C window is thus the preferable option from an environmental perspective. II. The PVC window is the least preferred option, as it performs the worst in 11 out of 14 impact categories. This conclusion, however, might change if land use, freshwater ecotoxicity and human health (non-cancer) (where the W window performs significantly worse) are given a higher weight than the rest of the impact categories. III. The overall environmental performance of the windows is mainly determined by the demand for heat to compensate for heat losses through the window during its use stage. This is true for nearly all impact categories. The U-value determines demand for heat, and can thus be considered a key environmental performance indicator of windows. Illustrative Case Study: Life Cycle Assessment ...


Table 39.2 Characterised impacts and accompanying 95% probability ranges from Monte Carlo simulations, expressed in category-specific units for each window alternative Impact category Unit Impact score (95% probability range) W W/ALU PVC W/C Climate change kg CO2 eq. 1162 (1134–1189) 1158 (1129–1188) 1232 (1203–1260) 978 (933–1023) Stratospheric ozone depletion kg CFC-11 eq. 1.9e−5 (1.8e−5–1.9e−5) 1.6e−5 (1.5e−5–1.6e−5) 1.6e−5 (1.5e−5–1.6e−5) 1.4e−5 (1.4e−5–1.4e−5) Photochemical ozone formation kg NMVOC eq. 1.59 (1.55–1.63) 1.57 (1.53–1.61) 1.72 (1.67–1.76) 1.33 (1.26–1.4) Terrestrial acidification AE 2.00 (1.95–2.04) 2.00 (1.95–2.05) 2.31 (2.26–2.36) 1.67 (1.6–1.75) Terrestrial eutrophication AE 7.14 (6.94–7.35) 7.04 (6.83–7.24) 7.79 (7.56–8.02) 5.96 (5.61–6.32) Freshwater eutrophication kg P eq. 0.042 (0.041–0.043) 0.043 (0.041–0.044) 0.046 (0.044–0.047) 0.035 (0.033–0.037) Marine eutrophication kg N eq


0.042 (0.041–0.043) 0.043 (0.041–0.044) 0.046 (0.044–0.047) 0.035 (0.033–0.037) Marine eutrophication kg N eq. 0.65 (0.63–0.67) 0.62 (0.60–0.64) 0.68 (0.66–0.7) 0.54 (0.51–0.57) Freshwater ecotoxicity CTUe 2675 (2605–2745) 1755 (1706–1805) 1852 (1809–1895) 1545 (1461–1630) Human toxicity (cancer) CTUh 2e−5 (1.9e−5–2e−5) 1.8e−5 (1.8e−5–1.9e−5) 3.4e−5 (3.3e−5–3.5e−5) 1.6e−5 (1.5e−5–1.7e−5) Human toxicity (non-cancer) CTUh 1.5e−4 (1.5e−4–1.6e−4) 1.3e−4 (1.2e−4–1.3e−4) 1.3e−4 (1.3e−4–1.3e−4) 1.0e−4 (9.9e−5–1.1e−4) Particulate matter formation kg PM2.5 eq. to air 0.085 (0.083–0.087) 0.082 (0.080–0.084) 0.116 (0.114–0.119) 0.070 (0.067–0.073) Ionising radiation (human health) kBq U235 eq. 7.69 (7.56–7.81) 7.99 (7.86–8.12) 8.63 (8.49–8.77) 6.26 (6.07–6.45) Land use kg C year 657 (646–668) 405 (399–410) 386 (384–387) 364 (351–377) Resource depletion (minerals, fossils) kg Sb eq


7.69 (7.56–7.81) 7.99 (7.86–8.12) 8.63 (8.49–8.77) 6.26 (6.07–6.45) Land use kg C year 657 (646–668) 405 (399–410) 386 (384–387) 364 (351–377) Resource depletion (minerals, fossils) kg Sb eq. 0.0072 (0.0070–0.0073) 0.0074 (0.0072–0.0076) 0.0081 (0.0080–0.0083) 0.0063 (0.0060–0.0066) W Wood, W/ALU wood/aluminium, PVC polyvinyl chloride, W/C wood/composite The probability ranges represent the modelled inventory uncertainty, as the uncertainties in the characterisation factors were not known