Question: In life-cycle-assessment, what characterizes Situation B as a context for life cycle based decision support?

Situation B refers to life cycle based decision support whose consequences are so extensive that they overcome thresholds and result in additionally installed or decommissioned equipment/capacity (e.g. production infrastructure) outside the foreground system of the analysed system.

In LCA-based decision support, Situation B is characterized by **small-scale, incremental decisions where the overall market is not significantly affected**.

Key features:
- The decision causes **only marginal changes** in demand or supply.
- The surrounding production system is assumed to remain **essentially unchanged**.
- The relevant modelling approach is typically **attributional / accounting-oriented LCA**, or a simplified consequential view using **average data** when no important market consequences occur.
- Examples: choosing between materials for a product with low market influence, improving a process within an existing production setup.

In short, **Situation B = decisions with limited consequences beyond the product system, without major structural market effects**.

Situation B is characterized as life cycle based decision support with consequences “so extensive that they overcome thresholds and result in additionally installed or additionally decommissioned equipment / capacity (e.g. production infrastructure) outside the foreground system of the analysed system.” It is associated with meso-/macro-level, strategic or policy decision support.

Cited: ILCD Handbook, ch. 5.3, p.40; Hauschild et al., *LCA: Theory and Practice*, ch. 27, p.676.

Situation B is characterized as life cycle based decision support where the consequences of the decision are extensive enough to overcome thresholds and cause additional installation or decommissioning of equipment/capacity outside the foreground system, e.g. production infrastructure. It is associated with meso-/macro-level, strategic or policy decision support rather than product/process-level decisions.
(ILCD Handbook, p.40; Hauschild et al., *LCA of Electromobility*, p.676)


Question: What are the three approaches illustrated for solving the multifunctionality problem in a process?

Subdivision of the black box unit process, substitution of the not required co-functions (system expansion), and allocation of the inventory to the co-functions.

In LCA, the three standard approaches for handling **multifunctionality** in a process are:

1. **Subdivision or system disaggregation**
   - Split the unit process into smaller subprocesses and assign inputs/outputs separately where possible.

2. **System expansion / substitution**
   - Expand the system boundary to include the additional functions, or credit the system for avoiding production of an alternative product.

3. **Allocation**
   - Partition the environmental burdens among co-products using a rule such as:
     - **Physical relationships** (e.g. mass, energy content)
     - **Economic value**

These are typically applied in that order in ISO 14044: avoid allocation where possible, then allocate if necessary.

The three illustrated approaches are:

1. Subdivision of the black box unit process
2. Substitution of the not required co-functions
3. Allocation of the inventory to the co-functions

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.16 (Figure 8, Figure 9, Figure 11).

The three illustrated approaches are:

1. **Subdivision of the black box unit process**
2. **Substitution of the not required co-functions**
3. **Allocation of the inventory to the co-functions**

(ILCD Handbook, p.16)


Question: When multiple crops are harvested in a single year, how should the calculated inventory for that year be distributed among them?

It should be linearly allocated between the crops over the portion of the year that they use or block the land, with no further differentiation between earlier and later months.

When **multiple crops are harvested in the same year**, the **annual inventory** should generally be **shared among those crops by allocation**.

Most common approaches:

- **Physical allocation**: distribute by a physical basis such as
  - harvested mass/yield,
  - area occupied,
  - nutrient content,
  - energy content.

- **Economic allocation**: distribute according to the **relative market value** of each crop.

Which method to use depends on the **goal and scope of the study** and the relevant LCA standard or product rules.

If the yearly inventory contains **crop-specific inputs** (for example, fertilizer or irrigation applied only to one crop), those should be assigned **directly to that crop**, and only the **shared/background annual inventory** should be allocated among all crops.

So in short:
**calculate the total inventory for the year, assign crop-specific flows directly, and allocate the remaining shared flows among the harvested crops using a justified allocation key.**

When more than one crop is harvested in a single year, “the calculated inventory for that year shall be linearly allocated between these crops over the time of that year that they use the land or block it for other uses”; no further differentiation between earlier and later months in that year is needed.
— European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.100, chapter 7 Life Cycle Inventory analysis

When more than one crop is harvested in a year, “the calculated inventory for that year … shall be linearly allocated between these crops over the time of that year that they use the land or block it for other uses”; for simplification, no further differentiation between earlier and later months in that year is needed.
(European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, chapter 7, p.100)


Question: Why are midpoint impact categories for human toxicity and ecotoxicity associated with considerably larger uncertainties than categories such as acidification, photochemical ozone formation, or global warming?

Because the uncertainty of characterisation factors varies between impact categories depending on the state of the art in modelling the underlying impact pathway and on the availability and quality of substance data used to calculate the characterisation factors. The chemical-related toxicity and ecotoxicity categories carry larger uncertainties than the often energy-conversion related categories like acidification, photochemical ozone formation, and global warming.

Human toxicity and ecotoxicity have much larger uncertainty mainly because they require modeling a much longer and more complex cause-effect chain than categories like climate change or acidification.

### Why toxicity categories are more uncertain
1. **Complex fate and transport**
   - A toxic substance can move between air, water, soil, sediment, and biota in many ways.
   - Its behavior depends strongly on local conditions such as temperature, pH, organic matter, and hydrology.

2. **Variable exposure pathways**
   - Humans and ecosystems can be exposed through inhalation, drinking water, food, soil, etc.
   - Estimating actual exposure is difficult and highly location-dependent.

3. **Large differences among substances**
   - Toxic effects vary enormously by chemical.
   - For many substances, toxicity data are limited, incomplete, or extrapolated from lab tests, animal studies, or structurally similar compounds.

4. **Dose-response uncertainty**
   - Translating an emitted mass into actual health or ecological damage involves uncertain assumptions about thresholds, chronic exposure, mixtures, bioaccumulation, and species sensitivity.

5. **Spatial and temporal dependence**
   - Toxicity impacts depend strongly on where and when the emission occurs.
   - A kilogram emitted to a remote area is not equivalent to a kilogram emitted near people or sensitive ecosystems.

### Why categories like global warming, acidification, and photochemical ozone formation are less uncertain
- Their mechanisms are **better understood** and often more directly linked to emissions.
- Characterization factors are based on **more stable and measurable atmospheric chemistry**.
- Impacts are generally **less dependent on local exposure details** than toxicity.
- For climate change especially, greenhouse gases can be compared using relatively robust radiative forcing models.

### In short
Toxicity categories have higher uncertainty because they must model:
**emission → environmental fate → exposure → intake/effect → damage**,
with large variability and limited data at each step.

By contrast, categories such as **global warming, acidification, and photochemical ozone formation** rely on better-established, more homogeneous, and less site-specific environmental mechanisms.

Midpoint impact categories for human toxicity and ecotoxicity have considerably larger uncertainties because the uncertainty of characterisation factors depends on the maturity of impact pathway modelling and on the availability and quality of substance data. For chemical-related categories such as human toxicity and ecotoxicity, both the underlying modelling and substance data are more uncertain than for often energy-conversion-related categories like acidification, photochemical ozone formation, or global warming.
(Source 1: European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.297)

A further reason is the sheer number of substances covered in toxicity categories and the very large variation in their environmental persistence and toxicity. Other categories typically involve only a limited number of elementary flows with a narrower range of impact potentials, making them easier to characterise consistently.
(Source 5: Hauschild et al., LCA: Theory and Practice, Ch. 10, p.187)

Midpoint impact categories for human toxicity and ecotoxicity have considerably larger uncertainties because their characterisation factors depend on more uncertain modelling of the underlying impact pathways and on the availability and quality of substance-specific data. In addition, toxicity categories cover a very large number of elementary flows/substances with widely varying persistence and toxicity, which makes consistent characterisation much harder than for categories like acidification, photochemical ozone formation, or global warming, where fewer flows are involved and impacts vary over a much narrower range. (European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.297; Hauschild et al., 10 Life Cycle Impact Assessment, p.187)


Question: What two aspects distinguish the three decision-context situations of practical relevance in LCA?

They differ regarding (1) whether the LCI/LCA study is to be used to support a decision on the analysed system, and (2) if so, the extent of changes the decision implies in the background system and other systems via market mechanisms—either small (small-scale, non-structural) or big (large-scale, structural).

The **three decision-context situations in practical LCA** are mainly distinguished by **two aspects**:

1. **The scale of the change**
   - Whether the decision causes a **small/marginal change** or a **large/system-changing change**.

2. **The time horizon of the effects**
   - Whether the consequences occur in the **short term** or **long term**.

These two aspects determine which decision-context situation applies and influence the appropriate modeling approach.

The three decision-context situations are distinguished by two aspects:

1. Whether the LCI/LCA study is to be used to support a decision on the analysed system.
2. If yes, the extent of changes implied in the background system and other systems via market mechanisms—either small-scale/non-structural or large-scale/structural.

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), chapter 5.3.1, p.36.

The three practical decision-context situations in LCA are distinguished by two aspects:

1. Whether the LCI/LCA study is used to support a decision on the analysed system.
2. If yes, the extent of changes caused in the background system and other systems via market mechanisms — either “small” (small-scale, non-structural) or “big” (large-scale, structural).

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), Chapter 5.3.1, p. 36.


Question: When inventorying CO2 release caused by land use and land transformation, which emission factors should be used unless more accurate, specific data is available?

The most recent IPCC CO2 emission factors.

Use the **IPCC default carbon stock factors** unless you have better site-specific data.

In practice, estimate CO₂ from land use / land transformation using default values for:

- **Above-ground biomass carbon**
- **Below-ground biomass carbon**
- **Dead organic matter / litter**
- **Soil organic carbon**

These defaults are typically taken from the **IPCC Guidelines for National Greenhouse Gas Inventories** (Tier 1 default factors), and the CO₂ release is calculated from the **change in carbon stocks between the original and transformed land use**.

So, unless more accurate data is available, use **IPCC default carbon stock and stock-change factors for the relevant climate zone, vegetation type, and land use category**.

Use the most recent IPCC CO2 emission factors, unless more accurate, specific data is available.
Cited in ILCD Handbook, chapter 7.4.3.6.3, p.221 and p.224.

Use **the most recent IPCC CO2 emission factors**, unless more accurate, specific data is available.
Cited in **ILCD Handbook, chapter 7.4.3.6.3 “Land use,” p.221** and also **p.224**.


Question: When environmental legislation is limited in the country where a process is operated, which jurisdictions' existing legal limits may be used as guidance, provided they are technically transferable?

The existing legal limits of jurisdictions such as Japan, the EU, and the US may be used.

If local environmental legislation is lacking, you may use legal limits from other jurisdictions as guidance, typically:

- **The country where the company is headquartered**
- **The country where the technology or process was developed**
- **Well-established international jurisdictions with comparable technical and environmental conditions** (e.g. **EU**, **US**, **Japan**)

The key condition is that the limits must be **technically transferable** to the process and local context.

Existing legal limits from Japan, the EU, or the US may be used as guidance, provided they are technically transferable.
(Source 1: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.202)

When environmental legislation is limited in the country where the process is operated, existing legal limits of “e.g. Japan, the EU, the US” may be used as guidance, provided “the limits are technically transferable” (European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), p. 202).


Question: In the context of LCA studies, what does the term "comparative study" cover?

It covers both assertive and non-assertive studies that compare alternatives.

In LCA, a **comparative study** is any study that **compares the environmental performance of two or more products, processes, or services** that fulfill the **same function**.

Key points:
- The comparison must be based on an equivalent **functional unit**.
- It can compare **alternative products**, **design options**, **technologies**, **waste treatments**, etc.
- The term is especially important when results are used to support **comparative assertions** disclosed to the public, because then stricter ISO requirements apply.

So, “comparative study” broadly covers **LCAs intended to evaluate and contrast alternatives serving the same purpose**.

In this context, “comparative study” covers both assertive and non-assertive studies that compare alternatives.

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), section 6.10.2, p.140.

In the ILCD Handbook, the term **“comparative study”** covers **both assertive and non-assertive studies that compare alternatives**.
(European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), p.140)

Relatedly, the handbook notes that such comparisons often involve **systems or processes with the same or similar functional unit compared with each other**.
(European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), p.140)


Question: In an LCA comparing alternative systems, what does the overall data quality requirement depend on, and how can the requirement change for ecodesign decisions when one alternative has much lower impacts?

The overall data quality requirement depends on the relative difference of the overall environmental impact between the compared systems; for ecodesign decisions, the requirements may be modest if one alternative has much lower impacts than the others. These initial requirements are to be revised once the results of the first inventory and impact assessment calculation are available.

In comparative LCA, the **required overall data quality** depends mainly on:

- the **goal of the study** and intended use,
- the **magnitude of the differences** between the alternatives,
- the **importance of the processes/flows** driving those differences,
- and the **consequences of the decision** being supported.

For **ecodesign decisions**, the requirement can be **relaxed** when one alternative has **clearly and substantially lower impacts** than the others. In that case, very high precision may not be necessary, because the conclusion is unlikely to change even with moderate data uncertainty. If the alternatives are close in performance, however, **higher data quality** is needed to distinguish them reliably.

In comparative LCA studies, the overall data quality requirement depends on the relative difference in the overall environmental impact between the compared systems. For ecodesign decisions, if one alternative has much lower impacts than the others, the data quality requirements may be modest; the initial requirements should then be revised once first inventory and impact assessment results are available.
(Source: ILCD Handbook, ch. 6.10.5, p. 144)

In comparative LCA, the **overall data quality requirements depend on the relative difference of the overall environmental impact between the compared systems**. For **ecodesign decisions** comparing alternative designs, the requirements **may be modest if one alternative has much lower impacts than the others**; moreover, the **initial overall data quality requirements should be revised once the first inventory and impact assessment results are available**.
(Source: European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), p. 144)


Question: In an LCI model where no decision support is involved, how should the analysed system be described?

It should describe the analysed system as it is, without including any market consequences in the model, since no decision consequences are related to it.

If no decision support is involved, the analysed system should be described as a **retrospective, attributional system**.

In practice, that means you describe:

- the **actual system as it exists or existed**
- the **average physical flows** of materials, energy, emissions, and waste
- the **supply-chain relationships** without modelling market-mediated consequences of decisions

So the system is framed to answer: **“What share of environmental burdens is associated with this product/system?”** rather than **“What consequences would result from a decision or change?”**

If no decision support is involved, the LCI model should describe the analysed system “as it is, without including any market consequences in the model.”
(Source 1: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.37)

If no decision support is involved, “the LCI model should describe the analysed system as it is, without including any market consequences in the model.” (European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.37)


Question: When normalisation is applied in LCIA, how are normalised LCIA results calculated, and for what level is the calculation performed separately?

Normalised LCIA results are calculated by dividing the LCIA results by the normalisation basis, done separately for each impact category (for midpoint level approaches) or each area of protection (for endpoint level approaches).

Normalised LCIA results are calculated by dividing the LCIA result for each impact category by a corresponding normalisation reference value, typically representing the total or per-capita impact in a reference region and time period.

Formally:

**Normalised result = LCIA category result / normalisation reference**

This calculation is performed **separately for each impact category indicator result**.

So, normalisation is not done on the total LCIA score at once, but **category by category**.

Normalised LCIA results are calculated by dividing the LCIA results by the normalisation basis. This is done separately for each impact category at midpoint level, or for each area of protection at endpoint level.
(Source 1: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.281)

Normalised LCIA results are calculated by dividing the LCIA results by the normalisation basis. This is done separately for each impact category for midpoint-level approaches, or for each area of protection for endpoint-level approaches. (European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), Chapter 8, p.281)


Question: What requirement must a study apply to protect non-technical audiences when product comparisons are disclosed to the public?

It must apply the same ISO requirements that apply to 'comparative assertions disclosed to the public', including the same review and other requirements, and at least state that the study does not support drawing conclusions or recommendations on the superiority or equality of any of the analysed systems.

When an LCA study is used for **publicly disclosed product comparisons**, it must undergo a **critical review by an independent interested parties panel**.

This requirement is intended to protect **non-technical audiences** from misleading comparative claims. Under ISO 14044, comparative assertions disclosed to the public require this higher level of review.

To protect non-technical audiences, a study must apply the ISO requirements for “comparative assertions disclosed to the public” also to “product comparisons disclosed to the public.”
Cited source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.141.

When product comparisons are disclosed to the public, the study must apply the ISO requirements for “comparative assertions disclosed to the public” also to “product comparisons disclosed to the public,” in order to avoid bypassing protection for audiences such as consumers and other non-technical external audiences. The ILCD states this explicitly: “the ISO requirements on ‘comparative assertions disclosed to the public’ shall also be applied to ‘product comparisons disclosed to the public’” (European Commission – JRC, ILCD Handbook: General Guide for LCA, p.141). It also notes that such disclosure entails “additional mandatory requirements under ISO 14040 and 14044:2006 on the execution, documentation, review and reporting” because results may affect “external companies, institutions, consumers, etc.” (p.34).


Question: In the outdoor wall paints comparison example, which type of product properties are quantified in the functional unit, and which type are merely documented?

Obligatory properties are quantified in the functional unit, while positioning properties are documented.

In that outdoor wall paints comparison, the **functional unit quantifies the performance-related properties** needed to deliver the service of the paint.

- **Quantified in the functional unit:** properties tied to the paint’s function, such as **covering/protecting a given wall area for a defined lifetime/quality level**.
- **Merely documented:** **additional descriptive or aesthetic properties** that are not part of the quantified service, such as aspects of appearance or other product characteristics that are reported for transparency but not built into the FU.

So, in short: **service/performance properties are quantified; non-service/descriptive properties are documented only.**

In the outdoor wall paints comparison, obligatory properties are quantified in the functional unit, while positioning properties are merely documented.
Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), Chapter 6, p.64.

In the outdoor wall paints comparison, **obligatory properties are quantified in the functional unit**, while **positioning properties are merely documented**.
Source: **European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.64**.


Question: When comparing systems in an LCA to draw conclusions or recommendations, what three data quality attributes must be sufficiently similar across the compared systems?

The achieved completeness, accuracy, and precision of the data must be sufficiently similar for the compared systems.

When comparing systems in an LCA to support **conclusions or comparative assertions**, three data quality attributes need to be sufficiently comparable between the systems:

1. **Time-related coverage**
   - Data should represent a similar time period / level of temporal representativeness.

2. **Geographical coverage**
   - Data should reflect comparable geographic regions or conditions.

3. **Technological coverage**
   - Data should represent comparable technologies, processes, or technical performance levels.

These are the key comparability requirements highlighted for making fair LCA comparisons.

When comparing systems in an LCA, the inventory data should be of comparable quality in terms of:

- accuracy
- completeness
- precision

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.305, chapter/provision I.d.iii.

When comparing systems, the inventory data should be of comparable quality across the alternatives, specifically in terms of **accuracy, completeness, and precision**.

Cited source: **European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.305**.


Question: Why does LCA not account for the direct health impacts that products such as food, healthcare, or tobacco products exert on humans during their use stage?

Because these impacts occur within the technosphere and are not subject to any environmental fate and exposure chain.

Because standard **Life Cycle Assessment (LCA)** is designed to assess **environmental burdens caused by the product system**, not the **intended or intrinsic effects of using the product on the user**.

In other words, LCA asks:

- what emissions and resource uses occur over the life cycle,
- how those emissions affect human health, ecosystems, and resources,

but **not**:

- whether eating the food improves or worsens nutrition,
- whether a medicine cures disease or causes side effects as a treatment outcome,
- whether tobacco harms the smoker through its intended consumption.

### Why this boundary exists
1. **Methodological scope**
   LCA focuses on impacts mediated through environmental interventions: emissions, extraction, land use, energy use, etc. Direct product effects on the user are usually considered **outside the environmental mechanism chain**.

2. **Functional unit comparability**
   LCA compares systems delivering the same function. Direct health outcomes from products like food or drugs depend heavily on dose, behavior, physiology, and context, making them difficult to represent consistently within standard LCA.

3. **Avoiding double counting / scope confusion**
   Direct health performance is often treated in other assessment frameworks:
   - nutrition assessment for food,
   - clinical evaluation / health technology assessment for healthcare products,
   - toxicology, epidemiology, or risk assessment for harmful consumer products.

4. **Standards practice**
   ISO-based LCA generally includes **human toxicity from environmental exposures**, but not the **consumer’s direct use-phase health effect as a product benefit or harm** unless the goal and scope explicitly extend beyond conventional LCA.

### Example
- For **cigarettes**, LCA includes impacts from tobacco farming, manufacturing, transport, and emissions to the environment.
- It typically does **not** include lung cancer in the smoker as a use-stage impact, because that is a **direct consumption effect**, not an environmentally mediated life-cycle emission impact in the standard sense.

### If you want those effects included
You usually need a broader framework, such as:
- **LCA combined with health risk assessment**
- **Life cycle sustainability assessment**
- **Health technology assessment**
- **Nutrition- or welfare-adjusted functional assessment**

So the short answer is: **standard LCA excludes direct user health effects because it is an environmental assessment method, not a full assessment of product-induced human health outcomes.**

LCA does not account for these direct health impacts because they occur within the technosphere and not through an environmental fate and exposure chain. Therefore, they are not treated as environmental interventions in LCA; only use-phase impacts that occur via emissions to the ecosphere are included.
(Source: European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.95; see also p.63)

LCA does not account for those direct health effects because they occur **within the technosphere**, not **via emissions to the environment**, and therefore they do **not pass through an environmental fate and exposure chain** that LCA models. The ILCD Handbook states that “the health impact (or improvement) that products may directly exert on humans is equally not covered by LCA” for this reason; only use-phase impacts that occur **through emissions to the ecosphere** are included (e.g. smoke emissions, wastewater discharge) (European Commission – JRC, *ILCD Handbook: General Guide for LCA*, 2010, p.95).

Related guidance adds that such direct human impacts “shall not be combined with interventions with the ecosphere” in the life cycle inventory and should instead be documented separately or assessed with complementary tools such as risk assessment (European Commission – JRC, *ILCD Handbook: General Guide for LCA*, 2010, p.63).


Question: For energetic resource elementary flows, what differentiation is required to support established practice in resource-depletion impact assessment?

Exclusively a differentiation by type of deposit/source, i.e. primary, secondary, and tertiary crude oil, and open pit or underground mining of hard coal.

To support established practice in **resource-depletion impact assessment**, energetic resource elementary flows should be **differentiated by the type of energy resource** rather than treated as one generic “energy” flow.

In practice, this means distinguishing flows such as:

- **Crude oil / petroleum**
- **Natural gas**
- **Coal** (and often lignite, hard coal, etc.)
- **Uranium** and other nuclear energy resources
- Sometimes also other primary energetic resources if relevant

The reason is that depletion assessment methods are based on the **scarcity and extraction of specific natural resources**, and each energetic resource has different reserve bases, renewability characteristics, and characterization factors.

So the required differentiation is essentially:
**one elementary flow per relevant energetic resource type, ideally at the level used by depletion LCIA methods.**

For energetic resource elementary flows, only differentiation by type of deposit/source is required to support established practice in resource-depletion impact assessment: specifically primary, secondary, and tertiary crude oil, and for hard coal, open pit or underground mining. Other fossil fuel resource elementary flows do not currently need differentiation. (European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.220; see also p.223)

For energetic resource elementary flows, the required differentiation is **exclusively by type of deposit/source**. Specifically:

- for **crude oil**: distinguish **primary, secondary, and tertiary** crude oil
- for **hard coal**: distinguish **open pit** and **underground mining**
- for other fossil fuels such as **natural gas, oil shale, tar sand, lignite, and peat**, **no differentiation is currently needed**

Citations:
- **ILCD Handbook, p.220**: “exclusively a differentiation by type of deposit/source is required, i.e. primary, secondary, tertiary crude oil and open pit or underground mining of hard coal. Other fossil fuel resource elementary flows … do currently not need a differentiation.”
- **ILCD Handbook, p.223**: non-renewable energy resources “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”.


Question: What is required when deviations from the provisions are made under the flexibility principle in LCA?

Deviations need to be documented and explicitly considered in the results interpretation.

Under the **flexibility principle** in LCA, any **deviations from the standard provisions must be clearly justified, documented, and transparently reported**.

Typically, this means you should provide:

- **A rationale for the deviation**
- **An explanation of why it is appropriate for the goal and scope of the study**
- **A description of the potential effects on results, interpretation, and comparability**
- **Sufficient documentation so reviewers and users can understand and assess the choice**

In short: deviations are allowed only if they are **well-founded and fully transparent**.

When deviations from the Guide’s provisions are made under the flexibility principle, they must be clearly justified; it is also advisable to introduce such deviations as a sensitivity analysis to retain reference to a more or less standardised LCA.
Chapter/page: Guinée et al. (2002), p.452.

When deviations from the provisions are made under the flexibility principle, they must be clearly justified, and it is advisable to introduce them as a sensitivity analysis to retain reference to a more or less standardized type of LCA. Practitioners may deviate, but implementation is entirely their responsibility. (Guinée et al., *Handbook on LCA*, p.452)


Question: When the market price is used as an allocation criterion for multifunctional processes, to what conditions and location should the price refer?

The price should refer to the specific condition and the point at which the co-functions leave or enter the multifunctional unit process or are provided, relating to specific technical characteristics such as quantity and quality (e.g., purity, compressed or not, packaged or not, bulk or small amounts) at the point it leaves the process.

When **market price** is used for **economic allocation** in a multifunctional process, the price should refer to the products:

- **at the same point in the value chain / same processing stage**, and
- **under the same market conditions**, especially **same place and time**.

So, prices should ideally be taken for all co-products:

- **at the factory gate** or other common reference point,
- **for the same period** (to avoid distortion from price fluctuations),
- **in the same geographic market/location**,
- and **excluding/including transport, taxes, margins, etc. consistently**.

In short: use **comparable prices for each output at the same location and under the same conditions at the moment they leave the multifunctional process**.

When market price is used for allocation, the price should refer to the specific condition of the co-functions and to the point where they leave or enter the multifunctional unit process, or are provided. This includes matching the specific technical characteristics such as quantity, quality, purity, compressed or not, packaged or not, and bulk or small amounts.

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.268.

When market price is used for allocation of multifunctional processes, “the price shall refer to the specific condition and at the point the co-functions leave or enter the multifunctional unit process or are provided.” It should reflect the specific technical characteristics and quality/quantity conditions, such as “purity, compressed or not, packaged or not, etc. as well as bulk or small amounts, etc. at the point it leaves the process.” If that cannot be done, the inaccuracy and possible distortion should be documented and considered in interpretation.
(Source: European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.268)


Question: What is the consequence of using data that is not sufficiently representative in an LCI/LCA study?

It renders the whole LCI/LCA study invalid and misleading.

Using data that is not sufficiently representative in an LCI/LCA study can lead to **misleading or biased results**.

Main consequences include:
- **Wrong impact estimates** because the data may not reflect the actual technology, geography, time period, or operating conditions of the system studied.
- **Poor comparability** between alternatives, which can cause incorrect conclusions about which option is better.
- **Reduced credibility and robustness** of the study, especially for decision-making or external communication.
- **Higher uncertainty**, making the results less reliable.
- In severe cases, it can lead to **wrong decisions or burden shifting**, where impacts appear lower or higher than they truly are.

In short: non-representative data weakens the validity of the LCA and can distort the conclusions.

Using data that is not sufficiently representative can make the LCI/LCA study “unreliable and distorted,” often leading to “wrong conclusion and recommendations drawn” (European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.247).

For comparative studies, lower representativeness must not affect the conclusions or recommendations, and especially must not “relatively disfavour any competitors’ products in a relevant degree”; otherwise this limitation must be explicitly considered when drawing conclusions and recommendations (Hauschild et al., LCA: Theory and Practice, ch. 37, p.988).

Using data that is not sufficiently representative can make the study results **unreliable and distorted**, and may lead to **wrong conclusions and recommendations**. Specifically:

- For inconsistent or insufficiently appropriate secondary data, “the whole LCI/LCA study [becomes] unreliable and distorted, often with wrong conclusion and recommendations drawn” (European Commission – JRC, *ILCD Handbook: General Guide for LCA*, p.247).
- If less representative data are used, this is only acceptable when it does **not relevantly change the overall LCIA results**; otherwise, the lower representativeness must be documented in the dataset/report (Hauschild et al., *LCA: Theory and Practice*, Ch. 37 “LCA Cookbook”, p.988; European Commission – JRC, *ILCD Handbook*, p.127).
- In **comparative LCA studies**, insufficient representativeness must not affect the study’s conclusions or recommendations, and must not unfairly disfavour competitors’ products (Hauschild et al., *LCA: Theory and Practice*, Ch. 37, p.988).
- Poor representativeness is also a **source of uncertainty**, and practitioners can reduce this by improving data quality and representativeness (Hauschild et al., *LCA: Theory and Practice*, Ch. 11 “Uncertainty Management and Sensitivity Analysis”, p.287).


Question: What characterizes a Situation C1 study, and how does it relate to Situations A/B and C2?

Situation C1 is an accounting-type study that is retrospective but accounts for benefits on other systems (e.g., via co-products and recycling), placing it between Situations A/B and C2. It applies when providing accounting-type life cycle information without including existing interactions with other systems; its accounting character must be stated explicitly in the study's goal, and its restrictions for decision support and comparisons must be clarified in the reporting.

A **Situation C1** study is an LCA situation where:

- the **decision is highly constrained**, and
- the study focuses on **small-scale, short-term consequences** of a change.

### What characterizes C1
Typical features are:

- **Limited freedom to change suppliers, technology, or market structure**
- **Short time horizon**
- **Small change in demand or production**
- Effects are mainly in the **immediate foreground system** or among directly affected processes
- Often uses **specific/average data for the constrained system**, rather than broad market-wide marginal modeling

### Relation to Situations A/B
Situations **A and B** generally deal with decisions that have broader freedom and/or market consequences:

- **A**: often non-decision or accounting-type descriptions of a product system
- **B**: decisions with consequences that can affect marginal suppliers and broader markets

Compared with A/B, **C1 is more constrained and narrower in scope**, with less emphasis on large-scale market responses.

### Relation to C2
Situation **C2** is similar in being a **consequential-type constrained situation**, but:

- **C1** = **small/short-term constrained consequences**
- **C2** = **larger-scale and/or longer-term constrained consequences**

So **C1 can be seen as the constrained analogue of a short-run marginal analysis**, while **C2 extends to broader or longer-term constrained consequences**.

Situation C1 is a descriptive “accounting” study that models the analysed system while including existing interactions with other systems, such as recycling benefits, avoided production for co-products, or other existing benefits outside the system. It does not imply a decision context and therefore does not include additional consequences caused by a decision, unlike Situations A and B. Relative to C2, the key difference is that C1 includes these existing system-external interactions, whereas C2 accounts for the system in isolation. The ILCD Handbook describes C1 as lying “between A/B and C2,” because it is retrospective/accounting-based like C2, but still accounts for benefits on other systems via co-products and recycling.
Sources: ILCD Handbook, ch. 5.3.7, p.43; p.46; p.86.

A Situation C1 study is an **accounting / descriptive** study: it documents the analysed system “of the past, present or forecasted future” **without implying a decision-context** that would include **additional consequences on other systems**. What distinguishes **C1** is that **existing interactions with other systems are included in the LCI model**, such as “recycling benefits or avoided production for co-products.” These are **existing interactions only**, not decision-caused consequences.
— **ILCD Handbook, p.43**

The ILCD further summarizes the key difference between the two accounting sub-types as follows: for **Situation C1**, “existing benefits outside the analysed system are considered,” whereas **Situation C2** accounts for the analysed system **in isolation**.
— **ILCD Handbook, p.86** and **p.43**

In relation to **Situations A/B**, C1 is explicitly contrasted with them because A and B address **additional consequences** on other systems that are **assumed to be caused by the analysed decision**, while C1 remains **retrospective / accounting**. The ILCD states that “Situation C1 lies hence between A/B and C2, being retrospective but accounting for benefits on other systems e.g. via co-products and recycling.”
— **ILCD Handbook, p.43** and **p.46**

Typical applications of Situation C1 include:
- monitoring environmental impacts of a **nation, industry sector, product group, or product**,
- **corporate or site environmental reporting** including indirect effects under EMS, and
- development of **average or generic unit process / LCI results data sets** for use in C1.
— **ILCD Handbook, p.43**

Hauschild et al. add that in the decision tree, **“C1 is used unless C2 is specifically prescribed by the commissioner’s goal of the study.”**
— **Hauschild et al., Goal Definition, p.71**


Question: When facing missing information in an LCI/LCA study, what are the principle options for dealing with the data gaps?

Calculating from other known information; using information from similar processes or regions or older data; estimating the value based on specific expertise; using methodologically not fully but sufficiently consistent data; or accepting and documenting the gap.

When you have missing information in an LCI/LCA, the main principle options are:

1. **Collect better primary data**
   - Go back to suppliers, operators, measurements, invoices, logs, etc.
   - Best option when feasible.

2. **Use secondary/proxy data**
   - Substitute with data from databases, literature, similar processes, similar materials, or analogous technologies.
   - Adjust for geography, time, scale, and technology where possible.

3. **Estimate/model the missing data**
   - Engineering calculations, stoichiometry, mass/energy balances, emission factors, economic correlations, expert judgment.
   - Clearly document assumptions.

4. **Apply cut-off/exclusion**
   - Omit the flow or process if it is demonstrably insignificant and consistent with the study’s cut-off rules and goal/scope.
   - Must be justified transparently.

5. **Use scenarios or ranges**
   - Create best-case/worst-case or alternative assumptions when the value is uncertain.
   - Helpful when no single reliable estimate exists.

6. **Assess uncertainty and sensitivity**
   - Test how much the data gap affects results.
   - If conclusions do not change, the gap may be acceptable; if they do, more data collection is needed.

7. **Revise scope or system boundary**
   - Simplify or redefine the study if the missing data cannot be resolved and are critical to the intended use.

8. **Report the limitation transparently**
   - Document what is missing, how it was handled, data quality implications, and effects on interpretation.

In practice, the usual hierarchy is: **get primary data if possible; otherwise use proxy/estimated data; exclude only if justified; then test sensitivity and report clearly.**

Principle options for dealing with missing information in an LCI/LCA study are:

- calculation from other, known information
- using information from similar processes or regions with similar process operation (and background processes in case of LCI results) or older data
- estimating the value based on specific expertise
- using methodologically not fully but sufficiently consistent data
- accepting and documenting the gap

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), Chapter 7 “Life Cycle Inventory analysis - collecting data, modelling the system, calculating results,” p.207.

Principle options for dealing with missing information in an LCI/LCA study are:

- calculate it from other known information,
- use information from similar processes or regions with similar process operation, or older data,
- estimate the value based on specific expertise,
- use methodologically not fully but sufficiently consistent data,
- accept and document the gap.

The ILCD also notes that the first step is to try to measure/obtain the data from the process operator; if that fails, data can be obtained from a third-party LCI data provider. (European Commission – JRC, ILCD Handbook: General Guide for LCA, Chapter 7, p.207)


Question: Why should elementary flows be inventoried as individual substances rather than as measured indicators such as AOX or COD, or as grouped flows like heavy metals?

Because such measured and grouped elementary flows are generally not suitable for a subsequent impact assessment and can cause large bias in the results, either exaggerating or underestimating the real impact potential.

Elementary flows should be inventoried as individual substances because LCIA works by linking each emitted or extracted substance to specific environmental mechanisms and characterization factors. Measured indicators and grouped flows lose that substance-level meaning.

Main reasons:

- Different substances have different impacts
  Even within a group like “heavy metals,” lead, mercury, cadmium, and chromium behave very differently in toxicity, persistence, bioavailability, and fate.

- LCIA needs substance-specific characterization
  Impact assessment methods assign factors to individual flows, not usually to aggregate indicators like COD, AOX, or “metals to water.”

- Aggregates can hide composition
  Two emissions with the same COD or AOX value may consist of very different chemicals and therefore cause very different impacts.

- Avoids double counting or misallocation
  Grouped indicators can overlap with individual emissions and make it unclear how impacts should be assigned.

- Improves transparency and comparability
  Listing individual substances allows others to interpret, update, and reuse the inventory with different LCIA methods.

- Better supports fate and exposure modeling
  Environmental fate depends on the exact substance and receiving compartment, which grouped parameters do not capture well.

Indicators like COD, BOD, AOX, or grouped “heavy metals” can still be useful as supplementary reporting parameters, especially when only monitoring data are available, but they are generally not appropriate as the main elementary flows for LCA.

Elementary flows should, wherever possible, be inventoried as individual substances because measured indicators like AOX or COD and grouped flows like “heavy metals” are generally not suitable for subsequent impact assessment and can cause large bias in results, either overestimating or underestimating the real impact potential.

Cited source: ILCD Handbook, chapter 7.4.3.2, p.215.

Elementary flows should, wherever possible, be inventoried as individual substances because measured indicators like “AOX” or “COD” and grouped flows like “heavy metals” or “hydrocarbons” are “in general … not suitable for a subsequent impact assessment” and “can cause large bias in the results, either exaggerating or underestimating the real impact potential” (ILCD Handbook, ch. 7.4.3.2, p.215).

This is reinforced by the guidance that individually measured substances “shall not be integrated/combined into measurement indicators and elementary flow groups but be inventoried individually” (Hauschild et al., *LCA Cookbook*, ch. 37, p.1028). The ILCD also notes that such sum-indicators and measured indicators “cannot be usefully addressed in impact assessment” and “typically have no impact factor at all,” so they “shall not remain in the inventory” (ILCD Handbook, p.278).


Question: When ensuring geographical representativeness in an LCA, which elements must the practitioner identify as varying by location and confirm are properly represented?

The key processes and key assumptions that vary according to the geographical location.

To ensure **geographical representativeness** in an LCA, the practitioner should identify which parts of the system **change with location** and verify that the data reflect those differences. In practice, this includes:

- **Processes and technologies** used in each location
- **Energy supply / electricity mix**
- **Raw material sourcing and availability**
- **Transport modes and distances**
- **Emission factors and environmental conditions** that depend on local geography
- **Waste management and end-of-life treatment**
- **Infrastructure and production efficiencies**
- **Regional regulations or operating practices** that affect emissions or resource use

In short: identify all **location-sensitive inputs, processes, and outputs** and confirm they are represented with data appropriate to the relevant region.

The practitioner must identify and ensure proper representation of location-dependent differences in:

- elementary flows
- energy flows
- material flows
- waste to treatment

These can vary due to local climate, proximity to natural resources, and regulatory differences such as energy taxes and emission thresholds.

Cited: Hauschild et al., LCA: Theory and Practice, Chapter 8, p.106.

To ensure geographical representativeness, the practitioner must identify and properly represent the elements that vary with location, namely:

- the **level and type of technology applied**
- the **conditions under which it runs**, such as **surrounding climate** and **national legal requirements on emission limits**

This is because these are influenced by the geographical location of the process.
(Source 3, *ILCD Handbook*, p.128)

Relatedly, inventory data should represent location-specific differences in:
- **elementary flows**
- **energy flows**
- **material flows**
- **waste to treatment**

since the same product output can involve different flows in different locations due to climate, resource proximity, and regulation.
(Source 1, *Hauschild et al., LCA: Theory and Practice*, Ch. 8, p.106)


Question: Why is using consistent naming conventions to identify and define commonly required objects (such as "Carbon dioxide" as an emission to air or "kg" as a unit for mass) important in LCA?

It is a prerequisite for being able to combine and integrate inventory data sets from different data developers into systems and LCA studies and to correctly link LCIA methods.

Using consistent naming conventions in LCA is important because it enables **clarity, comparability, and interoperability**.

- **Avoids ambiguity:** The same object can be described in different ways (e.g., “CO2,” “Carbon dioxide,” “carbon dioxide to air”). A standard name makes sure everyone means the same thing.
- **Supports correct modeling:** Flows, units, compartments, and processes must be identified precisely so software and practitioners assign them correctly.
- **Enables data exchange:** Databases, tools, and organizations can share and combine datasets reliably only if common objects are named consistently.
- **Improves comparability:** Results from different studies can be compared more confidently when the underlying elementary flows and units are defined in the same way.
- **Reduces errors and duplication:** Standard naming prevents accidental double counting, mismatching, or creating duplicate entries for the same substance or unit.
- **Facilitates automation:** Mapping, linking, aggregation, and impact assessment depend on machine-readable consistency.

In short, consistent naming is essential for making LCA data **unambiguous, reusable, and robust**.

Using consistent naming conventions is important in LCA because it is a prerequisite for combining and integrating inventory datasets from different data developers, building systems and LCA studies, and correctly linking LCI data with LCIA methods/factors. It also ensures that practitioners can consistently identify elementary flows and units (e.g. Carbon dioxide by name, CAS number, and unit), supporting correct data use and interoperability.
(Source 1, ILCD Handbook, p.244; Source 2, ILCD Handbook, p.334)

Using consistent naming conventions is important in LCA because they are a prerequisite for combining and integrating inventory datasets from different developers into product systems and LCA studies, and for correctly linking LCI data with LCIA methods/factors. They also ensure that practitioners can work consistently with the data by clearly identifying flows and units (e.g. carbon dioxide by name, CAS number, and unit).
(Source 1, p.244; Source 2, p.334)


Question: How should net accumulation or depletion of a substance in the field be handled in the inventory, regardless of whether the substance is an agrochemical, nutrient, heavy metal, or carbon?

It is to be recorded in the inventory disregarding the nature of the substance, and correctly considered in the system model or the impact assessment, as applicable.

In LCA inventory, treat **net accumulation or depletion in the field as a stock change in soil/field compartment**.

- **Accumulation**: record it as a **flow from the technosphere/environment into the field/soil stock**; it is **not counted as an emission to the wider environment** in that period.
- **Depletion**: record it as a **flow out of the field/soil stock**.

This applies **regardless of the substance**—agrochemicals, nutrients, heavy metals, or carbon are handled the same way. The key is that the inventory should reflect the **mass balance** and distinguish **temporary storage in the field** from **actual emissions** to air, water, or other compartments.

Net accumulation or depletion of a substance in the field “is to be recorded in the inventory, disregarding the nature of this substance (agrochemical, nutrient, heavy metal, carbon, etc.) and to be correctly considered in the system model or the impact assessment, as applicable.” If part of the substance remains after harvest and serves as input to the next crop, it crosses the system boundary within the technosphere over time, making the preceding crop process multi-functional, so the general provisions for solving multifunctionality apply.

Chapter 7, p.234 (ILCD Handbook: General Guide for LCA, 2010).

Net accumulation or depletion of a substance in the field “is to be recorded in the inventory, disregarding the nature of this substance (agrochemical, nutrient, heavy metal, carbon, etc.) and to be correctly considered in the system model or the impact assessment, as applicable.” If it remains in the field after harvest and serves as input to the next crop, it crosses the system boundary within the technosphere over time and may make the preceding crop process multifunctional.
— ILCD Handbook: General Guide for LCA, Ch. 7 Life Cycle Inventory analysis, p. 234


Question: When 1 kg of lead-zinc ore containing 1.2 % Pb and 2.3 % Zn is extracted, what elementary flows and amounts are inventoried?

0.012 kg of "Lead" and 0.023 kg of "Zinc" elementary flows are inventoried.

For an LCI of **1 kg of lead-zinc ore extracted** with grade **1.2% Pb** and **2.3% Zn**, the inventoried **elementary flow to technosphere/economy** is typically the ore resource removed from nature, represented by its contained metals.

### Elementary flows inventoried
Per **1 kg ore extracted**:

- **Lead in ore, in ground**:
  \(1 \times 0.012 = 0.012\) kg = **12 g**

- **Zinc in ore, in ground**:
  \(1 \times 0.023 = 0.023\) kg = **23 g**

### Optional remainder
If the full ore composition is tracked, the remainder is:

- **Gangue / other minerals**:
  \(1 - 0.012 - 0.023 = 0.965\) kg = **965 g**

### So the main inventoried elementary resource flows are:
- **0.012 kg lead, in ground**
- **0.023 kg zinc, in ground**

If you want, I can also explain how this would be represented in **ecoinvent-style elementary flows** or in an **LCIA resource depletion context**.

When 1 kg of lead-zinc ore containing 1.2% Pb and 2.3% Zn is extracted, the inventoried elementary flows are:

- 0.012 kg “Lead”
- 0.023 kg “Zinc”

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.221.

When 1 kg of lead-zinc ore containing 1.2% Pb and 2.3% Zn is extracted, the inventoried elementary flows are:

- **0.012 kg “Lead”**
- **0.023 kg “Zinc”**

This is because metal ore elementary flows are inventoried by splitting the ore into the single elements’ elementary flows rather than keeping the combined ore as an elementary flow (European Commission – JRC, *ILCD Handbook: General Guide for LCA*, 2010, **p. 221**).


Question: Within an LCA, which two conditions must processes meet to be included in the final system boundary of the analysed system, and how must any relevant deviation or omission be handled?

Processes must (a) be operated within the technosphere, and (b) need to be included according to the provisions for identifying to-be-included processes under attributional or consequential modelling (with the specific provisions and simplifications for the applicable Situation A, B, or C). Any relevant deviation or omission must be clearly documented and, in the case of LCA studies, later considered in the interpretation.

In an LCA, a process should be included in the final system boundary if it meets both of these conditions:

1. **It is expected to contribute significantly** to the overall environmental interventions/impacts of the product system.
2. **Sufficient data can be collected with the required quality** to model it consistently with the goal and scope of the study.

If a relevant process is **excluded, truncated, or treated differently**, that **deviation/omission must be clearly documented and justified**, including its potential significance and implications for the study results.

According to the ILCD Handbook, the final system boundary shall as far as possible include all relevant life cycle stages and processes that:

1. “are operated within the technosphere,” and
2. “need to be included along the provisions of identifying to-be-included processes under attributional or consequential modelling … with the specific provisions and simplifications for the applicable Situation A, B, or C.”

Any relevant deviation or omission “shall be clearly documented and in case of LCA studies later be considered in the interpretation.”
(Source 1, European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.105)

Processes included in the final system boundary shall, as far as possible, be all relevant life cycle stages and processes that:

1. **are operated within the technosphere**, and
2. **need to be included according to the provisions for identifying to-be-included processes under attributional or consequential modelling**, with the applicable simplifications for Situation A, B, or C.

Any **relevant deviation or omission** must be **clearly documented** and, for LCA studies, **later considered in the interpretation**.
**(European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.105)**


Question: What is described as an incorrect way of combining attributional and consequential modelling within the same system model?

Combining them unsystematically on an ad hoc basis, such as allocating among the co-products of one multifunctional process while substituting the co-products of another; a systematic approach should be followed instead.

An incorrect approach is to mix attributional and consequential rules inside one product system model, for example:

- using average/supplier-specific data for some processes, but
- using market-marginal/substitution logic for others

within the same foreground-background chain.

This is generally considered inconsistent because attributional and consequential modelling are based on different decision logics and system boundary rules. If both are needed, they should usually be modeled as separate scenarios, not merged into one single system model.

It is described as incorrect to “unsystematically combine attributional and consequential modelling in the same system model on an ad hoc basis,” for example “allocating among the co-products of one multifunctional process and substituting the co-products of another.”
(Source 1, ILCD Handbook, p.70, with guidance referring to chapter 6.5.4)

It is described as incorrect to **unsystematically combine attributional and consequential modelling in the same system model on an ad hoc basis**, for example **“allocating among the co-products of one multifunctional process and substituting the co-products of another.”** (ILCD Handbook: General Guide for LCA, chapter 6, p.70)


Question: How should waste and waste water treatment be modelled with respect to the boundary between the technosphere and ecosphere, and what must be done if this is not followed?

Waste and waste water treatment shall be modelled consistently to the boundary between technosphere and ecosphere; otherwise it shall be clearly documented and explicitly considered in later interpretation.

Waste and wastewater treatment should be modeled so that the **technosphere–ecosphere boundary is crossed only once**.

## Recommended modeling principle
- **Waste treatment processes** belong to the **technosphere**.
- The **waste** or **wastewater** itself is treated as a **technosphere flow** entering the treatment process.
- Only the **final emissions** from the treatment process to air, water, or soil should cross into the **ecosphere**.

So, for example:
- wastewater from a factory → **technosphere flow** to wastewater treatment
- emissions from the treatment plant (e.g. nitrate to river, CO₂ to air, sludge to soil if released) → **elementary flows** to the ecosphere

## What should not be done
Do **not** model untreated waste or wastewater directly as an **elementary flow to nature** if it is actually sent to a treatment system. That would place the technosphere–ecosphere boundary incorrectly.

## If this rule is not followed
If waste or wastewater is already modeled as crossing into the ecosphere before treatment, then you must **compensate/correct** for this to avoid inconsistency or double counting. In practice, that means:
- **redefine/relink the flow as a technosphere waste flow** to treatment, or
- if that is impossible, **add corrective transfers/subtractions** so that only the **net final releases** remain as elementary flows.

In short: **waste stays in the technosphere until treatment is complete; only the treatment’s final releases enter the ecosphere.**

Waste and wastewater treatment shall be modelled consistently all the way to the boundary between technosphere and ecosphere, including all treatment steps up to and including final disposal of remaining waste deposits or landfills, and the emissions from these sites to/from the ecosphere must be inventoried. If this is not done, it shall be clearly documented and explicitly considered later in the interpretation. Waste flows themselves are not elementary flows but flows within the technosphere, so their further management must be modelled until elementary flows are reached.
(Hauschild et al., *LCA: Theory and Practice*, Ch. 37 “LCA Cookbook”, p.1031; European Commission – JRC, *ILCD Handbook: General Guide for LCA*, p.242)

Waste and wastewater treatment “shall be modelled consistently to the boundary between technosphere and ecosphere.” This 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” (Hauschild et al., *LCA: Theory and Practice*, Ch. 37 “LCA Cookbook”, p.1031).

Similarly, the ILCD states that waste flows “are no elementary flows but are flows inside the technosphere,” so “their further management and treatment needs to be modelled” to elementary flows / the technosphere–ecosphere boundary (European Commission – JRC, *ILCD Handbook: General Guide for LCA (2010)*, p.242).

If this is not followed, “this shall be clearly documented and be explicitly considered in later interpretation” (Hauschild et al., *LCA: Theory and Practice*, Ch. 37, p.1031). Guinée et al. likewise note that if wastewater treatment is omitted in practice, “this should be clearly reported and justified” (Guinée et al., *Handbook on LCA*, p.483).


Question: What are the two main purposes for which weighting is applied in a life-cycle assessment?

Weighting is mainly applied to support the interpretation of the study's results (as an additional, optional element) and to quantify the achieved completeness or cut-off (where normalised indicator results across impact categories may be weighted).

In LCA, **weighting** is mainly applied for two purposes:

1. **To support interpretation and decision-making**
   It assigns relative importance to different impact categories so results can be aggregated or prioritized.

2. **To compare and rank alternatives more easily**
   By converting multiple impact category results into a weighted score, it helps distinguish between products, systems, or scenarios.

In short: **prioritization of impacts** and **simplification of comparisons/choices**.

Weighting is mainly applied for two purposes in LCA:

1. To support interpretation of the study results.
2. To quantify achieved completeness / cut-off by weighting normalised indicator results across impact categories.

Source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), Chapter 8, p.283.

The two main purposes are:

1. **To support interpretation of the study results** — weighting may be used as an additional, optional element in interpreting normalised or non-normalised indicator results.
2. **To quantify achieved completeness / cut-off across impact categories** — normalised indicator results may be weighted across indicators for cut-off quantification.

**Source:** European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), **p. 283**.


Question: When a plantation has a 30-year plantation cycle, what duration should be used for assigning land-use impacts?

The duration of one plantation/use cycle—i.e., 30 years—should be used.

Use the full plantation cycle as the occupation period: **30 years**.

In LCA land-use accounting, land occupation impacts are generally assigned over the **actual duration the land is occupied by the crop/system**. So for a plantation with a **30-year rotation/cycle**, you would typically use:

- **Land occupation duration:** **30 years**
- often expressed as **hectare-years (ha·yr)** over that cycle

If you are allocating impacts to annual production, you would then **annualize** over the 30 years.

Use the duration of one plantation/use cycle: **30 years**.

Cited:
- **ILCD Handbook, p.100**: “Or the foreseeable minimum use is longer (e.g. plantations with 30 years plantation cycle). In that case, that duration of one plantation / use cycle shall be used.”
- **Hauschild et al., p.774**: “For a plantation with trees or palms, it is recommended that the emissions are allocated to the first cycle of trees/palms, i.e. 20–30 years.”

For plantations, if the foreseeable minimum use is longer than 20 years, “that duration of one plantation / use cycle shall be used,” e.g. “plantations with 30 years plantation cycle” use 30 years for sharing the land transformation inventory (European Commission – JRC, ILCD Handbook: General Guide for LCA, 2010, p.100).

Hauschild et al. also states that for tree or palm plantations, LUC emissions should be allocated to the first cycle, “i.e. 20–30 years” (Hauschild et al., LCA: Theory and Practice, ch. 30, p.774).


Question: When filling initial data gaps of included processes and systems, what types of estimate data sets may be considered for use?

Generic or average data sets for missing specific processes/systems, and average data sets of a group of similar processes or systems.

When filling **initial data gaps** for included processes/systems in an LCA, you may use **estimate datasets** such as:

- **Proxy / analogous datasets** from similar processes, products, or technologies
- **Scaled or adapted datasets** based on known relationships (e.g., mass, energy, capacity, output)
- **Stoichiometric / engineering calculation-based estimates**
- **Modelled datasets** from process simulation or technical literature
- **Generic secondary database datasets** representing average market or industry conditions
- **Expert judgement-based estimates**, where documented and justified

Good practice is to use the **most representative available estimate**, clearly **document assumptions**, and later **replace estimates with specific primary data** where feasible.

When filling initial data gaps of included processes and systems, the following estimate data sets may be considered for use:

- generic or average data sets for missing specific processes / systems
- average data sets of a group of similar processes or systems

Cited source: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), chapter 7.4.3, p.253.

When filling initial data gaps of included processes and systems, estimate data sets that may be considered include:

- “generic or average data sets for missing specific processes / systems”
- “average data sets of a group of similar processes or systems”
(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.253, ch. 9.3.3, item IV.a–b)

Related guidance for estimate data sets also includes:
- generic or average data for missing specific data
- average data of a group of similar products
- correlation with other, more complete and high quality data
- justified judgements of technical experts / process operators
(ILCD Handbook, p.251; see also p.212)


Question: When the uses or amounts of a secondary good are unknown, what method is applied to credit a reduced amount of primary material inventory, and on what ratio is it based?

Value correction is applied, based on the market-price ratio of the secondary good to the superseded primary produced good.

Apply the **cut-off / recycled-content approach**: you **credit a reduced amount of the primary material inventory** to the secondary good.

The reduction is based on a **ratio of the secondary good’s amount or use relative to the corresponding primary material/product**—i.e., a **secondary-to-primary use/amount ratio**.

When the uses or amounts of a secondary good are unknown, **“value correction”** is applied. This credits a reduced amount of primary material inventory based on **the market-price ratio of the secondary good to the superseded primary produced good**.

**Citation:** European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), **Annex C, p.360**.

When the uses or amounts of a secondary good are unknown, the **“value correction”** method is applied. It credits a reduced amount of primary material inventory based on the **market-price ratio of the secondary good to the superseded primary produced good** (e.g. 0.9/1.2 = 0.75).
**Source:** European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), **Annex C, p.360**.


Question: Which chapter of the ILCD Handbook addresses the appropriate coverage of what is reported or documented?

The ILCD Handbook addresses the appropriate coverage of what is reported or documented in **Chapter 10**, which focuses on **Reporting and Review**.

The ILCD Handbook states that “Appropriateness of documentation extent” — i.e. appropriate coverage of what is reported / documented — is addressed in **Chapter 10**.
**Citation:** European Commission – JRC, *ILCD Handbook: General Guide for LCA (2010)*, **p.336**.


Question: Which ISO standard governs Life Cycle Impact Assessment?

ISO 14042 governs Life Cycle Impact Assessment.

Life Cycle Impact Assessment is governed by **ISO 14044**.

- **ISO 14040**: principles and framework for LCA
- **ISO 14044**: requirements and guidelines, including **LCIA**

So if you’re asking specifically about LCIA, the relevant standard is **ISO 14044: Environmental management — Life cycle assessment — Requirements and guidelines**.

Life Cycle Impact Assessment is governed by ISO 14042, “Environmental management - Life cycle assessment - Life cycle Impact assessment” (Guinée et al., Handbook on LCA, p.651, Source 3).

Life Cycle Impact Assessment is governed by **ISO 14042:2000E, Environmental management – Life cycle assessment – Life cycle Impact assessment**.
**Citation:** Guinée et al., *Handbook on LCA: Operational Guide to the ISO Standards* (2002), **p.651**.


Question: Why is it not considered useful to attempt listing all potentially relevant aspects of a product's functional unit and specification?

Because all quantitative and qualitative aspects of the functional unit and specification can matter for a given case, so any list would be incomplete.

Because in LCA, trying to enumerate *every* potentially relevant aspect of a product’s function and specification is usually impractical and not very helpful.

Key reasons:

- **Infinite or very large set of aspects**: A product can be described by many technical, performance, aesthetic, and contextual attributes. Listing all of them is impossible in practice.
- **Not all aspects matter for the study goal**: Only those characteristics that influence the compared function, system design, or environmental results are important.
- **Relevance depends on context**: What matters in one comparison may be irrelevant in another. For example, durability, strength, speed, appearance, or user comfort may or may not affect the LCA depending on the decision context.
- **Creates unnecessary complexity**: Over-specifying the functional unit can make the study cumbersome without improving decision relevance.
- **Can obscure the main function**: The purpose of the functional unit is to provide a clear basis for comparison, not to become a complete product description.

So, instead of listing everything, the useful approach is to identify and specify **only the relevant function-related and performance-related characteristics needed to ensure a fair and meaningful comparison**.

Because many relevant aspects are qualitative, user-dependent, and sometimes not even clear-cut—especially subjective perception elements such as aesthetics, image, fashion, shape, or touch. Which aspects matter depends on the product users and central stakeholders, so trying to make an exhaustive list of all potentially relevant aspects is not useful; instead, the key qualitative and quantitative aspects relevant for fair comparability should be documented.

Cited:
- Hauschild et al., LCA: Theory and Practice, Chapter 8 “Scope Definition,” p.86
- European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.62

Because many relevant aspects are qualitative, user-dependent, and sometimes not even clear-cut, so a complete universal list would not be practical or useful. The importance of properties “will to a large extent depend on the product user,” and subjective or perception-related elements may also need to be included to ensure comparability. Non-technical aspects that differ between compared products should therefore be either included in the functional unit or handled separately in interpretation, rather than trying to exhaustively pre-list everything.

Citations:
- Hauschild et al., *LCA: Theory and Practice*, Ch. 8, p.86
- Hauschild et al., *LCA: Theory and Practice*, Ch. 9, p.132


Question: What was the focus of the 2004 Life Cycle Assessment study co-authored by Schmidt, Dahlqvist, and Finkbeiner?

The 2004 study focused on Life Cycle Assessment of lightweight and end-of-life scenarios for generic compact class passenger vehicles.

The 2004 LCA study co-authored by **Schmidt, Dahlqvist, and Finkbeiner** focused on **developing and discussing a practical approach for applying Life Cycle Assessment to complex industrial systems, particularly in support of environmental decision-making and product-oriented analysis**.

More specifically, their work is commonly associated with **methodological issues in LCA**, such as:

- handling **multi-output processes and allocation**
- improving **consistency and transparency** in industrial LCAs
- supporting **product chain/environmental management decisions**

If you want, I can also help identify the exact paper title and summarize its main findings.

The 2004 study focused on “Life Cycle Assessment of Lightweight and End-of-Life Scenarios for Generic Compact Class Passenger Vehicles.” (Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, p.4)

The 2004 study by Schmidt, Dahlqvist, and Finkbeiner focused on the **life cycle assessment of lightweight and end-of-life scenarios for generic compact class passenger vehicles** (Finkbeiner et al., *The New International Standards for LCA: ISO 14040 & 14044*, p. 4).


Question: What problem arises when trying to sum a lead emission to air of unknown quantity with a known emission of 0.00026 kg from another process?

The sum cannot be determined, because adding an unknown amount of kg to 0.00026 kg yields an undefined result.

You can’t produce a valid total, because one of the values is unknown.

So if you have:

- Process A: lead emission to air = unknown
- Process B: lead emission to air = 0.00026 kg

then the sum is still **unknown**, not 0.00026 kg.

In LCA, the problem is a **data gap / missing inventory value**:
- the total lead emission cannot be quantified reliably,
- any impact assessment using that flow may be incomplete or biased,
- treating the unknown as zero would likely underestimate emissions.

So the core issue is **uncertainty due to missing data**, which prevents proper aggregation.

The problem is that you cannot meaningfully add an unknown amount of lead emission to a known value like 0.00026 kg (“unknown kg + 0.00026 kg = ?”). The ILCD notes this as an issue of combining unclear or unknown quantities with known data and aims to avoid combining highly uncertain information with more certain data.

Chapter/page: European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.209.

The problem is that the sum is indeterminate: you cannot meaningfully add an unknown lead emission to a known 0.00026 kg value (“Unknown kg plus 0.00026 kg = ?”). The ILCD text highlights this as a difficulty of combining unclear or unknown emission amounts with known process emissions, and it also states a principle “to avoid combining highly uncertain information / data with more certain data.” (European Commission – JRC, ILCD Handbook: General Guide for LCA, p.209)


Question: Into how many parts is ISO 14064 divided, and what is the focus of Part 3?

ISO 14064 is divided into three parts, and Part 3 focuses on the specification and guidance for validation, verification, and certification of greenhouse gases.

ISO 14064 is divided into **3 parts**.

- **Part 1**: Organization-level quantification and reporting of GHG emissions and removals
- **Part 2**: Project-level quantification, monitoring, and reporting of GHG emission reductions or removal enhancements
- **Part 3**: **Validation and verification of greenhouse gas assertions** — it focuses on how GHG statements/claims are independently assessed for reliability and conformity.

The provided context only mentions ISO 14064-3, which focuses on “validation, verification and certification” of greenhouse gases; it does not state into how many parts ISO 14064 is divided. (Source 5, p.4)

ISO 14064 is divided into three parts. Part 3 focuses on “specification and guidance for validation, verification and certification” of greenhouse gases. (Finkbeiner et al., 2006, p.4)


Question: Where and when was the Fifth International Conference on Ecobalances held?

The Fifth International Conference on Ecobalances was held in Tsukuba, Japan, from November 6–8, 2002.

The **Fifth International Conference on Ecobalance** was held in **Tsukuba, Japan**, in **November 2002**.

I do not have that information in the provided context. The context mentions the “Third International Conference on EcoBalance – Progress in LCA for a Sustainable Society” held in Tsukuba in November 1998, but not the fifth conference. (Guinée et al., Handbook on LCA, 2002, p.645)

I don’t see the location and date of the **Fifth International Conference on EcoBalance** in the provided context.

What is present is a reference to **“EcoBalance—Pract. tools thoughtful Princ. Sustain., 6–8 Nov 2002, Tsukuba, Japan (2002)”**, but that does not identify it as the **Fifth International Conference on EcoBalance**.
**Citation:** Hauschild et al., *LCA: Theory and Practice*, Ch. 11, p. 319.


Question: Why is transparency considered an important guiding principle in Life Cycle Assessment?

Due to the inherent complexity in LCA, transparency is an important guiding principle in order to ensure a proper interpretation of the results.

Transparency is important in Life Cycle Assessment because LCA involves many choices, assumptions, data sources, and methodological decisions that can strongly affect the results.

Key reasons:

- **Makes results understandable**: Users can see how the study was done, what system boundaries were chosen, what data were used, and what assumptions were made.
- **Supports credibility and trust**: Transparent reporting helps decision-makers, reviewers, and stakeholders trust the findings.
- **Enables reproducibility**: Others can repeat or verify the assessment if methods and data are clearly documented.
- **Allows critical review**: Reviewers can identify weaknesses, uncertainties, value choices, and potential bias.
- **Improves comparability**: When studies clearly report methods, it is easier to compare results across products or systems.
- **Prevents misleading conclusions**: Since LCA results can change depending on allocation rules, functional unit, impact methods, and data quality, transparency helps avoid misuse or overinterpretation.

In short, transparency is essential because LCA is not just about numbers—it is about clearly showing how those numbers were produced.

Transparency is considered important in LCA because, due to the inherent complexity of LCA, it ensures proper interpretation of the results and supports comprehensiveness and consistency in the study and reported results (Finkbeiner et al., 2006, p.83). It is also essential for reproducibility and comparability across studies, since poor documentation of assumptions and methodological choices makes results difficult to interpret and compare (Hauschild et al., p.651). Clear and explicit reporting of all issues is therefore needed to guarantee the baseline quality of an LCA (Guinée et al., 2002, p.27).

Transparency is considered an important guiding principle in LCA because LCA is inherently complex, and transparency is needed “to ensure a proper interpretation of the results” (Finkbeiner et al., *The New International Standards for LCA: ISO 14040 & 14044*, p. 83).

It is also essential for reproducibility, interpretation, and comparison across studies: insufficient documentation of methodological aspects and assumptions “compromis[es] the reproducibility principle,” and makes results difficult to interpret and compare (Hauschild et al., *LCA: Theory and Practice*, Chap. 26, p. 651). More generally, the baseline quality of an LCA “can only be guaranteed if all steps undertaken are clearly reported,” with issues reported transparently and explicitly (Guinée et al., *Handbook on LCA*, p. 27).


Question: How many copies of ISO 14040 were sold in Sweden and the Czech Republic respectively?

1200 copies were sold in Sweden and 909 copies were sold in the Czech Republic.

I’m not aware of any public, authoritative source that reports country-by-country sales figures for ISO 14040, including Sweden and the Czech Republic specifically.

A few reasons:
- ISO standards are sold through multiple channels, including ISO directly and national standards bodies.
- Sales data is typically treated as proprietary by ISO and national distributors.
- Public ISO materials usually discuss adoption or publication, not unit sales by country.

If you want, I can help identify the likely distributors involved:
- Sweden: SIS, Swedish Institute for Standards
- Czech Republic: Czech Office for Standards, Metrology and Testing / national standards distributor

You’d likely need to contact those organizations directly for exact sales figures.

ISO 14040 sold 1200 copies in Sweden and 909 copies in the Czech Republic (Finkbeiner et al., 2006, p.11).

ISO 14040 sold **1200 copies in Sweden** and **909 copies in the Czech Republic** (Finkbeiner et al., 2006, **p.11**).


Question: What was the first key objective agreed upon by the task force formed in July 2001 regarding LCA standards?

The first key objective was to increase readability by compiling only two documents, merging different documents, or reorganising the current standards.

The first key objective was **to develop a strategic plan for standardizing life cycle assessment (LCA), with a particular focus on life cycle inventory (LCI) data and methods**.

The first key objective was to “Increase readability by compiling only two documents / merging different documents / reorganising the current standards.” (Finkbeiner et al., 2006, p.11)

The first key objective was to **increase readability by compiling only two documents, merging different documents, and reorganising the current standards** (Finkbeiner et al., *The New International Standards for LCA: ISO 14040 & 14044*, 2006, p. 11).


Question: What was the primary objective of revising the ISO 14040, 14041, 14042, and 14043 standards?

The primary objective was to improve readability while leaving the requirements and technical content unaffected, except for corrections of errors and inconsistencies.

The primary objective was to **consolidate and harmonize** the original four Life Cycle Assessment standards into a clearer, more consistent framework.

Specifically, the revision aimed to:

- **Integrate** ISO 14041, 14042, and 14043 into a smaller set of standards
- **Clarify requirements, principles, and terminology**
- **Improve consistency and practical usability** of LCA guidance
- **Reduce overlap and ambiguities** among the original documents

This led to the current structure:
- **ISO 14040**: Principles and framework
- **ISO 14044**: Requirements and guidelines

So, in short, the revision’s main goal was to make the ISO LCA standards **more coherent, streamlined, and easier to apply**.

The primary objective was “improving readability, while leaving the requirements and technical content unaffected, except for errors and inconsistencies.” (Finkbeiner et al., 2006, p.1)

The primary objective was **to improve the readability of the standards while leaving the requirements and technical content unchanged, except for correcting errors and inconsistencies**. This included gathering all requirements (“shalls”) into a new standard while keeping ISO 14040 as the framework document.
**Source:** Finkbeiner et al., *The New International Standards for LCA: ISO 14040 & 14044*, **p.1**.


Question: What aspects are considered beyond the scope of TC207 in the context of LCA standardization?

The inclusion of economic and social aspects are beyond the scope of TC207, though links to them should be addressed.

In the context of LCA standardization under ISO/TC 207, some topics are explicitly considered **beyond its scope**, especially where they move from **assessment methodology** into **policy, value choices, or broader sustainability judgments**. These typically include:

- **Weighting of impact categories based on social or political values**
  TC 207 supports characterization and reporting, but not prescribing value-based weighting factors as universally valid.

- **Setting environmental priorities or policy decisions**
  LCA can inform decisions, but deciding what should matter most is outside the standardization scope.

- **Establishing absolute sustainability thresholds**
  TC 207 does not define what level of impact is “sustainable” or “acceptable” in a societal sense.

- **Broader social, ethical, or economic judgments not covered by environmental LCA methodology**
  These may belong to other frameworks, such as social LCA, life cycle costing, or broader sustainability assessment.

- **Product approval, ecolabel criteria, or regulatory pass/fail rules**
  ISO LCA standards provide methods, not specific compliance criteria or certification thresholds.

So, in short, **TC 207 standardizes the LCA framework and methodological principles, but not the normative judgments or policy choices made using LCA results**.

According to Guinée et al., the ISO standards under TC207 “specify only the general structure of LCA,” while “true operationalisation involves so many choices” that full agreement on them cannot be expected in an ISO standard. Thus, detailed operational choices for conducting LCA are considered beyond the scope of TC207 standardization. (Guinée et al., Handbook on LCA, 2002, p.452)

The provided context does not explicitly state what is “beyond the scope of TC207” in LCA standardization.

What it does say is that:
- the ISO standards “specify only the general structure of LCA,” while fuller “operationalisation involves so many choices” beyond that general standardisation framework (Guinée et al., Handbook on LCA, p.452, chapter context).
- the “development of LCIA methods and factors is outside ISO 14044 and outside this document” (European Commission – JRC, ILCD Handbook, p.108, Scope chapter).

Citations:
- Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.452
- European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.108


Question: What is the preferred basis for decisions made within an LCA, and what alternatives exist when that is not possible?

Decisions within an LCA are preferably based on natural science. If that is not possible, other scientific approaches (e.g., from social and economic sciences) can be used, or international conventions can be referred to.

In LCA, decisions should **preferably be based on physical relationships**—that is, on how inputs, emissions, or functions are actually causally related to the product system.

If that **cannot be established or used**, the usual alternatives are:

1. **System expansion / substitution** to avoid allocation where possible.
2. If allocation is still needed, use **other relationships**, typically **economic allocation** (based on value) or other relevant non-physical proxies.

So, in short: **physical causation first; if not possible, use system expansion or a justified alternative such as economic allocation.**

The context states that “comparison of LCA predictions with reality is unattainable” in practice, so decisions within an LCA cannot be based on direct verification against reality. Instead, decisions are made by choosing among “a number of possible and probable future settings” and among methodological options such as modelling principles, system boundaries, datasets, impact categories, and other assumptions.

Citations:
- Guinée et al., Handbook on LCA, Part 3: Scientific background, p.410
- European Commission – JRC, ILCD Handbook: General Guide for LCA, p.378

A preferred basis is to make LCA decisions in accordance with the **goal of the study and its decision context**, rather than by fixed or ad hoc rules. This applies to later methodological choices such as inventory data collection and modelling framework selection, which should be derived individually for each study, considering also criteria like reproducibility, robustness, practical feasibility, and stakeholder acceptance (European Commission – JRC, *ILCD Handbook: General Guide for LCA* (2010), p.70).

When this is not possible, there are still **alternative ways to perform the study**, for example:
- doing a **life cycle screening instead of a full formal LCA**, and
- carrying out the assessment with **own staff or consultants**,

with implications for time, cost, and potentially result quality (Hauschild et al., *LCA: Theory and Practice*, Ch. 22, p.522).


Question: What did the unanimous vote on the Draft International Standard versions indicate about the consensus behind the new ISO standards?

It proved that the standards were achieved on the basis of the broadest possible international consensus.

The unanimous vote indicated there was very strong, broad international consensus behind the new ISO standards.

In other words, the participating countries agreed without opposition that the standards were ready to move forward, showing strong support and legitimacy.

The unanimous vote indicated that the new ISO standards were achieved “on the basis of the broadest possible international consensus.” (Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, p.11)

It indicated that the new ISO standards were achieved “on the basis of the broadest possible international consensus.” (Finkbeiner et al., *The New International Standards for LCA: ISO 14040 & 14044*, p.11)


Question: What requirement was added in the new standards regarding the life cycle interpretation phase when drawing conclusions and making recommendations?

The new standards added a requirement to identify limitations when drawing conclusions and making recommendations.

The newer LCA standards added the requirement that, in the life cycle interpretation phase, **conclusions and recommendations must reflect the limitations identified in the study**.

In other words, when drawing conclusions or making recommendations, you must explicitly take into account issues such as data quality, assumptions, methodological choices, and the intended application of the results.

A clarification added in the new standards is the requirement to identify limitations when drawing conclusions and making recommendations.

Cited: Finkbeiner et al. (2006), “The New International Standards for LCA: ISO 14040 & 14044,” section 3.5 Life cycle interpretation, p.11.

The new standards added the requirement to **identify limitations when drawing conclusions and making recommendations** in the life cycle interpretation phase. They also clarify that recommendations must be based on the study’s final conclusions and be a logical and reasonable consequence of them.
**(Finkbeiner et al. 2006, p. 11)**


Question: What were the two main improvements made to the new ISO 14040 and ISO 14044 standards compared to the previous standards?

Errors and inconsistencies were removed, and the readability was improved.

The two main improvements in the revised **ISO 14040 and ISO 14044** standards were:

1. **Simplification and consolidation of the standards**
   The older LCA standards were reorganized and streamlined. Instead of multiple separate standards, the framework and requirements were clarified and made easier to use:
   - **ISO 14040** now gives the **principles and framework**
   - **ISO 14044** now contains the **requirements and guidelines**

2. **Greater clarity and consistency in requirements**
   The new standards improved definitions, methodological guidance, and reporting/review requirements, making LCA studies more consistent, transparent, and easier to interpret and compare.

If you want, I can also explain exactly how they replaced the older ISO 14041, 14042, and 14043 standards.

The two main improvements were:
1. Improved readability
2. Removal of errors and inconsistencies

This is stated in Finkbeiner et al. (2006), p.11: “Errors and inconsistencies were removed and the readability was improved.”
Also confirmed on p.11: “Improved readability and the removal of errors and inconsistencies was the focus of the revision.”

The two main improvements were:

1. **Improved readability** of the standards
2. **Removal of errors and inconsistencies**

This is stated explicitly for the 2006 revision: “the core part of the technical contents remains unchanged. **Improved readability and the removal of errors and inconsistencies was the focus of the revision**” (Finkbeiner et al., 2006, **p.11**; also **p.1**).