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 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 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?”**


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.

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)

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.


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 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 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.


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 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 **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**.


Question: Under what circumstance may a chosen weighting set be changed during the course of an LCA study?

It may be changed only if an extension is required because a non-default impact category has been additionally included during the study; otherwise the weighting set should not be changed later.

If normalisation and weighting are used to support results interpretation, the weighting set may not be changed during the study; “the same normalisation and weighting set shall be used as for the cut-off rules.”
— Hauschild et al., *LCA: Theory and Practice*, “37 LCA Cookbook,” p. 994.

In an LCA, a chosen weighting set should generally **not be changed once selected**, because that would undermine consistency and comparability of results.

It may only be changed **if there is a justified methodological reason**, and then only with **full transparency and documentation**. Typical acceptable cases are:

- **The goal and scope of the study are revised**
- **The original weighting set is found to be inappropriate** for the decision context, region, or stakeholders
- **A sensitivity or scenario analysis** is being performed to test how results depend on weighting choices

If changed, the study should clearly report:

- **why** the weighting set was changed
- **what** the new weighting set is
- **how** the change affects the conclusions

Also note: under **ISO 14044**, weighting is **optional** and should be treated carefully, especially in studies intended for **public comparative assertions**.


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 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 **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.**


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 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 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**.


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.

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)

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.


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 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 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**.


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.

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 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.


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, 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 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.


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 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 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.**


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.

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)

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.**


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 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 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.


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.

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)

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.**


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.

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 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**.


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 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 **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**.


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.

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.

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**.


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.

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** 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.


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.

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.

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.**


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 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 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.**


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, 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 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.


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 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.”

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.


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.

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).

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.


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 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 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**.


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.

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**.

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**.


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.

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.

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**.


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.

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)

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.


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).

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.

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**.


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 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** 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.


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**.


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.

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)

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.


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 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 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**.


Question: What unit is used to express the indicator result for abiotic resource depletion based on exergy content?

The indicator result is expressed in MJ exergy content.

MJ exergy content. (Guinée et al., Handbook on LCA, 2002, p.172)

Abiotic resource depletion based on exergy content is typically expressed in **MJ exergy** (megajoules of exergy).

Sometimes it may also be reported in **PJ exergy** or **GJ exergy**, depending on scale.


Question: What is the molar weight of zinc oxide?

The molar weight of zinc oxide is 81.369 g/mol.

Zinc oxide: 81.369 g/mol. Source 1, p.21.

The molar mass of **zinc oxide (ZnO)** is:

- **Zn**: 65.38 g/mol
- **O**: 16.00 g/mol

**Total = 81.38 g/mol**


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.

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.

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.


Question: What does the characterisation factor in the abiotic depletion equation represent?

The characterisation factor represents abiotic depletion of resource i based on the exergy content.

In the abiotic depletion equation based on exergy, the characterisation factor represents the **abiotic depletion factor of resource i based on its exergy content**.
Cited: **Guinée et al. (2002), p.172**.

In LCA, the **characterisation factor** in the **abiotic depletion** equation represents the **relative contribution of extracting a given resource to resource depletion**, compared to a reference substance.

For abiotic depletion, it usually reflects:

- the **scarcity of the resource**
- the **rate at which it is extracted**
- sometimes the **size of known reserves**

So it converts the amount of a specific mineral or fossil resource used into a common depletion unit, such as:

- **kg Sb-eq** for elements/minerals
- **MJ** or **kg oil-eq** for fossil resources, depending on the method

In simple terms:
**the characterisation factor tells you how “depletion-intensive” 1 kg of a resource is relative to the reference resource.**


Question: What are the two most important macronutrients associated with eutrophication?

The two most important macronutrients associated with eutrophication are nitrogen (N) and phosphorus (P). (Guinée et al., Handbook on LCA, 2002, §4.3.11, p.606)

The two most important macronutrients associated with eutrophication are:

- **Nitrogen (N)**
- **Phosphorus (P)**

Excess inputs of these nutrients into water bodies stimulate algal and plant growth, which can lead to oxygen depletion and ecosystem damage.


Question: In what type of compartment are substances such as lead, mercury, and nickel classified in this life cycle assessment annex?

They are classified in the industrial soil (indus. soil) compartment.

They are classified as interventions/substances in the classification table, with emission compartments specified separately as air, water, and soil, with sub-divisions for fresh water/seawater and agricultural/industrial soil where relevant. This applies to substances including lead (Pb), mercury (Hg), and nickel (Ni).
Chapter 4.4 Classification, p.360; see also p.53.

In this LCA annex, substances like lead, mercury, and nickel are typically classified in the **natural resources / minerals compartment**, more specifically as **metal resources in the ground** (sometimes called the **in-ground** compartment).

If you want, I can also explain how LCA annexes usually distinguish this from **emissions to air, water, or soil**.


Question: What is the exergy value of sodium oxide?

The exergy value of sodium oxide is 413.1 kJ/mol.

Sodium oxide: 413.1 kJ/mol.
Source: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.21.

For **sodium oxide (Na₂O)**, the commonly cited **standard chemical exergy** is approximately:

**375–380 kJ/mol Na₂O**

A representative value often used is:

**≈ 377 kJ/mol Na₂O**

If you want it in mass-specific terms:

- Molar mass of Na₂O = **61.98 g/mol**
- So the exergy is about **6.1 MJ/kg**

If needed, I can also give:
- the **reference/source conventions** behind this value,
- the value for **aqueous sodium species** instead,
- or explain how this differs from **Gibbs free energy of formation**.


Question: What long-term research goal is recommended regarding fate and regional differences in life cycle assessment?

It is recommended to develop a standard method to account for fate and regional differences for all impact categories, supported by a research programme focusing on all impact categories for which fate and regionalisation may be important, including acidification.

A recommended long-term research goal is to investigate “the scope for fully integrating fate in the characterisation factor for each impact category” and to develop regionally differentiated assessment, as reflected in work on “spatial differentiation” and “site-dependent characterisation” in LCA.

Citations:
- Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.541
- Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.654

A commonly recommended **long-term research goal** in LCA is to **better account for spatial and temporal variation in environmental fate and impacts**—that is, to develop **regionalized fate/exposure/effect models** instead of relying on generic average assumptions.

In practice, this means research should aim to:
- capture **regional differences** in climate, soils, hydrology, ecosystems, and population exposure,
- improve **fate modeling** for emissions and resource use across locations,
- link inventory data to **site-dependent characterization factors**, and
- ultimately support **more location-specific impact assessment**.

So, in short: **the long-term goal is to develop robust regionalized LCA methods that reflect differences in fate and impacts across regions.**


Question: Which polycyclic aromatic hydrocarbon (PAH) substances are listed in this LCA operational annex?

The PAH substances listed are indeno[1,2,3cd]pyrene, phenanthrene, and naphthalene.

The PAH substances listed in the operational annex are:

- Anthracene — p. 240, p. 265, p. 381
- Benzo[a]anthracene — p. 240, p. 265, p. 381
- Benzo[a]pyrene — p. 233, p. 240, p. 265, p. 381
- Benzo[ghi]perylene — p. 233, p. 240, p. 265, p. 381
- Benzo[k]fluoranthrene — p. 233, p. 240, p. 265, p. 381
- Carcinogenic PAHs / Polycyclic Aromatic Hydrocarbons Carcinogenic-(carcinogenic-PAH) — p. 265, p. 368, p. 380, p. 383
- Chrysene — p. 233, p. 381
- Indeno[1,2,3-cd]pyrene — p. 203, p. 267
- Naphthalene — p. 267, p. 383
- Phenanthrene — p. 203, p. 212, p. 267, p. 368, p. 380, p. 383

All are from Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), Part 2b: Operational annex.

I don’t have the annex text itself in this chat, so I can’t identify the exact PAH substances listed there.

If you paste the relevant section, I can extract them directly.
Common PAHs that appear in LCA/operational annex substance lists include:

- Naphthalene
- Acenaphthylene
- Acenaphthene
- Fluorene
- Phenanthrene
- Anthracene
- Fluoranthene
- Pyrene
- Benzo[a]anthracene
- Chrysene
- Benzo[b]fluoranthene
- Benzo[k]fluoranthene
- Benzo[a]pyrene
- Indeno[1,2,3-cd]pyrene
- Dibenzo[a,h]anthracene
- Benzo[g,h,i]perylene

Send the annex excerpt and I’ll tell you exactly which PAH substances it lists.


Question: In the context of life cycle assessment, what is an incremental change?

An incremental change is a shift from the reference value of a product's output (x) to the value of that output implied in the choice for an alternative, resulting from a change in demand for that product.

In change-oriented LCA, an incremental change is a change the analysis treats as an increment rather than an average; it is concerned with “incremental changes rather than averages.” Under certain assumptions, incremental changes may coincide with marginal effects, and in simple linear models they may also coincide with average effects.
— Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.424

In life cycle assessment, an **incremental change** is a **small, marginal change in demand, production, or system conditions** that is large enough to affect the system but **not large enough to fundamentally alter its structure**.

In practice, this means:
- you increase or decrease output by a small amount,
- the existing market and production technologies still basically remain the same,
- the response is usually provided by the **marginal supplier** or marginal technology.

This concept is especially important in **consequential LCA**, where the goal is to assess the environmental consequences of a change in demand.

Example:
- If demand for 1 more kWh of electricity increases slightly, the incremental change is the extra electricity generated by the power plant(s) that would actually respond at the margin, not the average of all plants on the grid.


Question: Which type of soil appears more frequently as a land use or impact category: agricultural soil or industrial soil?

Agricultural soil (soil agri.) appears far more frequently than industrial soil (soil indus.).

Industrial soil appears more frequently in the provided context.

- Industrial soil is explicitly listed multiple times in **Chapter 39, p.1137**: “Emissions to industrial soil,” “Heavy metals to industrial soil,” and “Inorganic emissions to industrial soil.”
- Agricultural soil is mentioned less directly, e.g. disposal “on agricultural land” in **Chapter 34, p.868** and “use in agriculture” in **Chapter 10, p.248**.

So, based on the provided excerpts, **industrial soil** appears more frequently (**Chapter 39, p.1137**).

Agricultural soil appears far more frequently.

In land use and environmental impact contexts, categories commonly refer to things like:

- agricultural land/soil
- arable land
- pasture
- cropland

By contrast, “industrial soil” is not a commonly used standard land use or impact category. Industrial areas may be counted under urban, built-up, or artificial surfaces, but not usually as a distinct “soil” category.

So the more frequent category is agricultural soil.


Question: What are the two types of soil categories mentioned in life cycle assessment?

The two types of soil categories mentioned are agricultural soil (soil agri.) and industrial soil (soil indus.).

The two soil categories mentioned are:

- **Soil and groundwater remediation** — *Hauschild et al., LCA: Theory and Practice, Chapter 36, p.939*
- **Soil erosion impacts** — *Hauschild et al., LCA: Theory and Practice, Chapter 10, p.268*

In life cycle assessment, the two commonly mentioned soil-related categories are:

1. **Agricultural soil** – soil used for crop production and farming.
2. **Industrial/urban soil** – soil occupied or affected by buildings, infrastructure, or industrial activities.

If you want, I can also explain how soil categories are treated in LCIA methods.


Question: In a simplified unit process producing electricity with fuel as an input, what effect does a change in electricity demand have on the process?

A change in the demand for electricity induces a change in the production volume of the generation process.

A change in electricity demand induces a change in the production volume of the electricity generation process; in the simplified case, this means an incremental change in electricity output leads to an associated change in fuel input demand.

Chapter/page: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), Part 3: Scientific background, p.422.

In a simplified unit process for electricity generation, a change in electricity demand usually changes the process output proportionally.

So, if demand for electricity increases:

- the process produces more electricity,
- it consumes more fuel,
- and emissions and other related flows also increase proportionally.

If demand decreases, the opposite happens.

In other words, in a simplified unit process, electricity is the reference output, and changing its demand scales the whole process up or down, assuming linearity.


Question: What are the three areas of protection in life cycle assessment?

The three areas of protection are the natural environment, natural resources, and the man-made environment.

The three areas of protection in life cycle assessment are:

- Human health
- Natural environment
- Natural resources

(Hauschild et al., *LCA: Theory and Practice*, Ch. 37, p. 991)

In life cycle assessment, the three common **areas of protection** are:

1. **Human health**
2. **Natural environment / ecosystem quality**
3. **Natural resources / resource availability**

These are used at the endpoint level in LCIA to group potential environmental damages into broad protection targets.


Question: What are the categories of substances that can be initially emitted or extracted into sea water as listed in LCA inventory data?

The categories of substances emitted or extracted into sea water include halogenated aromatics, pesticides, metals, PAHs, and radioactive metals.

The listed LCA inventory categories for substances initially emitted or extracted into sea water are:

- Sea water — input side
- Heavy metals to sea water
- Hydrocarbons to sea water
- Inorganic emissions to sea water

Citations:
- Hauschild et al., LCA: Theory and Practice, 37 LCA Cookbook, p.1030
- Hauschild et al., LCA: Theory and Practice, 39 Illustrative Case Study: Life Cycle Assessment of Four Window Alternatives, p.1140

In LCA inventory data, substances that can be initially emitted or extracted into **sea water** are typically grouped into broad inventory categories such as:

- **Inorganic emissions to sea water**
  e.g. metals, nutrients, acids, salts

- **Organic emissions to sea water**
  e.g. hydrocarbons, solvents, pesticides, chlorinated organics

- **Radioactive substances to sea water**

- **Resources extracted from sea water**
  e.g. water itself, salt, magnesium, bromine, fish/biological marine resources depending on the database scope

So, the main categories are usually **inorganic substances**, **organic substances**, **radioactive substances**, and **resources extracted from sea water**.


Question: What is the unit of measurement used for radioactive substances emitted into sea water in life cycle assessment?

Radioactive substances emitted into sea water are measured in kilobecquerels (KBq).

The unit used for radioactive substances emitted into sea water is **kBq (kilobecquerel)**.

Cited sources:
- **Guinée et al., Handbook on LCA (2002), p.375** — radioactive emissions to sea water are listed with unit **KBq**.
- **ILCD Handbook: General Guide for LCA (2010), p.245** — emitted radioactive isotopes are reported as **ionising radiation activity** in **kBq**.

In life cycle assessment, radioactive substances emitted to sea water are typically measured in **becquerels (Bq)**.

- **Bq** = one radioactive disintegration per second
- In LCI databases, emissions to water are often reported as **Bq to seawater**

If you want, I can also explain how this differs from impact assessment units, where characterization results may use other units.


Question: What characterisation model is used for the eutrophication impact category, and what does it identify?

The stoichiometric procedure is used, which identifies the equivalence between N and P for both terrestrial and aquatic systems.

The eutrophication impact category uses the eutrophication potentials of Heijungs et al. (1992) as the characterisation factor in the baseline characterisation method. The category indicator is described as being close to the intervention, i.e. it identifies nutrient emissions contributing to eutrophication rather than endpoint damage. (Guinée et al., Handbook on LCA, 2002, p.609)

For **eutrophication**, LCIA commonly uses a **characterisation model based on nutrient enrichment potential**, typically expressed as:

- **kg PO₄³⁻-eq** for general eutrophication, or
- sometimes split into **freshwater, marine, and terrestrial eutrophication** with different reference substances.

It identifies **emissions of nutrients**—mainly **nitrogen compounds** (e.g. nitrate, ammonia, NOx) and **phosphorus compounds** (e.g. phosphate)—that can cause **over-fertilisation of ecosystems**, leading to effects like algal blooms and oxygen depletion.


Question: What is identified as both the major strength and limitation of LCA?

The 'holistic' nature of LCA is both its major strength and its limitation, as the broad scope of analysing the complete life cycle of a product can only be achieved at the expense of simplifying other aspects.

The major strength and also a limitation of LCA is its comprehensiveness—specifically its life cycle perspective and broad coverage of environmental issues. This is identified as both a strength and a limitation because such comprehensiveness requires simplifications and generalisations that prevent LCA from calculating actual environmental impacts, instead yielding impact potentials.

(Hauschild et al., LCA: Theory and Practice, Ch. 2.3 “Strengths and Limitations of LCA,” p.14)

Its **major strength** is the **holistic, life-cycle perspective**—it considers impacts across all stages from raw material extraction to end-of-life, helping avoid burden shifting.

Its **major limitation** is essentially the same thing: that **full life-cycle coverage makes LCA complex and data-intensive**, requiring many assumptions, large amounts of data, and often introducing uncertainty.


Question: Who developed the capital good approach that includes a drafted working procedure for each level of sophistication?

The capital good approach was developed by Lindeijer (1998).

The capital good approach was developed by **Lindeijer (1998)**.
**Citation:** Guinée et al., *Handbook on LCA: Operational Guide to the ISO Standards* (2002), **Part 2b: Operational annex, p. 3**.

The **capital good approach with a drafted working procedure for each level of sophistication** was developed by **Frischknecht et al. (2007)**.

If you want, I can also summarize the different sophistication levels in that approach.


Question: How can LCA be used as a management tool on a continuous basis?

Criteria are derived from a more extensive LCA study and then used for the ongoing monitoring of the management process, with a specific example being the benchmarking of business and governmental activities.

LCA can be used as a management tool on a continuous basis by deriving criteria from a more extensive LCA study and then using those criteria for ongoing monitoring of the management process; a specific example given is benchmarking of business and governmental activities. (Guinée et al., Handbook on LCA, 2002, p.8)

LCA can be used as a continuous management tool by integrating it into regular decision-making rather than treating it as a one-off study. Key ways include:

- **Track environmental performance over time**
  Use repeat LCAs or simplified LCAs to monitor products, processes, or sites and see whether impacts are improving or worsening.

- **Support continuous improvement**
  Identify “hotspots” in materials, energy, transport, use, or end-of-life, then prioritize actions and reassess after changes are made.

- **Guide product and process design**
  Embed LCA in eco-design, procurement, and process development so environmental impacts are considered alongside cost, quality, and risk.

- **Set KPIs and targets**
  Translate LCA results into management indicators such as carbon footprint, energy demand, water use, or toxicity-related metrics, and use them in dashboards.

- **Compare alternatives routinely**
  Apply LCA when selecting suppliers, materials, packaging, technologies, logistics options, or waste treatment routes.

- **Integrate with management systems**
  Link LCA with ISO 14001, ESG reporting, carbon management, and sustainability strategies to inform planning, auditing, and review cycles.

- **Engage the supply chain**
  Use LCA data to work with suppliers on reducing upstream impacts and improving data quality over time.

- **Avoid burden shifting**
  Continuous LCA helps ensure that solving one problem, like reducing energy use, does not create another, like higher toxicity or waste.

In practice, this often means using a **screening or streamlined LCA** regularly, and doing a **full LCA** periodically for major decisions or strategic reviews.


Question: What metric did Hofstetter (1998) use as the basis for developing characterisation factors related to air pollution?

Hofstetter (1998) used Disability Adjusted Life Years (DALYs) for respiratory diseases due to air pollution as the basis for developing characterisation factors.

Hofstetter (1998) based these characterisation factors on DALY (Disability-Adjusted Life Years), specifically for ozone-induced respiratory disease; he also developed factors for respiratory diseases from winter smog pollutants. (Guinée et al., Handbook on LCA, 2002, p.598)

Hofstetter (1998) based the characterisation factors for air pollution on **DALYs** — **Disability-Adjusted Life Years** — as the damage metric for human health.


Question: What three data inputs are needed to estimate the environmental profile of capital goods at the most basic level of sophistication?

At the most basic level, the environmental profile is estimated based on an average environmental profile per building volume, the ground surface and height of the facility (or the total building volume), and the annual production of the company.

At the most basic level, the environmental profile of capital goods is estimated using:
1. the building volume (or ground surface and height / total building volume),
2. the annual production of the company,
3. an average environmental profile per building volume.

Cited in:
- Guinée et al. (2002), p.3
- Guinée et al. (2002), p.3, Part 2b Operational annex

At the most basic level, you typically need these three inputs:

1. **What the capital good is made of**
   - Main materials and approximate quantities (e.g., steel, aluminum, concrete, plastics).

2. **How much capital good is used or purchased**
   - The mass, number of units, or total cost/value of the equipment/infrastructure.

3. **How long it lasts / how it is allocated over time**
   - Its service life or depreciation period, so the embodied impacts can be assigned to the product system or reporting period.

In a very simple screening approach, these are combined with generic emission factors for the materials, product type, or spend category.


Question: Under what condition does including substitution processes in inventory modeling fully avoid the multifunctionality problem?

The multifunctionality problem is fully avoided when the additional function(s) delivered by a combined production process can be substituted, fully, by one or more single cradle-to-gate systems.

Including substitution processes in inventory modeling fully avoids the multifunctionality problem when “the additional function(s) delivered by a combined production process can be substituted, fully, by (a) single cradle-to-gate system(s).”
— Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.517

Including substitution processes fully avoids the multifunctionality problem only when the substituted co-product or service can be identified unambiguously and there is a clear, one-to-one displacement of an equivalent external product or function.

In practice, this means:

- the co-product actually replaces another specific product on the market,
- the substituted product provides the same function and quality,
- the amount displaced is known,
- and the displacement is complete and certain.

If these conditions are not met, multifunctionality is not truly eliminated—it is just handled through assumptions about substitution.


Question: What are the two background concentration scenarios used to calculate POCPs, and which research groups are associated with each?

The two scenarios are: a relatively high background concentration scenario (with a surplus of NOx and VOC as the limiting factor for ozone formation), yielding POCPs developed by Derwent et al. (1998); and a relatively low background concentration scenario (with a surplus of VOC and NOx as the limiting factor for ozone formation), yielding POCPs developed by Andersson-Sköld et al. (1992).

Two POCP background concentration scenarios are described:

- High background concentration scenario: relatively high background concentration, with a surplus of NOx and VOC as the limiting factor for ozone formation; associated with Derwent et al. (1998). (Guinée et al., 2002, p.598)
- Low background concentration scenario: relatively low background concentration, with a surplus of VOC and NOx as the limiting factor for ozone formation; associated with Andersson-Sköld et al. (1992). (Guinée et al., 2002, p.598)

The two background concentration scenarios commonly used for calculating **POCPs (Photochemical Ozone Creation Potentials)** are:

1. **Low-NOx / rural background scenario**
   - Associated with the **Derwent and Jenkin** research group.

2. **High-NOx / urban background scenario**
   - Associated with the **Jenkin and Hayman** research group.

These reflect different atmospheric chemical regimes, since ozone formation depends strongly on background **NOx** levels.


Question: What is a key limitation of large models such as MATTER/MARKAL that restricts their use in LCA?

Their complexity limits their general applicability to major studies on complex issues.

A key limitation is their complexity: they require specialised modelling knowledge and otherwise “soon become an impenetrable black box,” which restricts their practical use in LCA.
(Guinée et al., Handbook on LCA, 2002, p. 516)

A key limitation is that large energy-system models like **MARKAL/MATTER are highly aggregated and optimization-focused**, so they usually provide **sector- or technology-average results rather than detailed process-level inventories**.

For LCA, this restricts their use because LCA often needs:

- **fine product/process resolution**
- **full life-cycle inventory data**
- **specific technology and supply-chain detail**

In short: **they are too coarse and system-level to directly generate detailed LCA inventories.**


Question: Which three impact categories dominate the weighting result in the impact assessment?

The weighting result is dominated by depletion of abiotic resources, acidification, and climate change.

The weighting result is dominated by three impact categories: depletion of abiotic resources, acidification, and climate change. (Guinée et al., Handbook on LCA, Part 2a: Guide, p.1000)

Without the specific LCA results table, the three impact categories that most commonly dominate the **weighting result** are:

1. **Human health**
2. **Ecosystem quality**
3. **Climate change / fossil energy use**

If you mean a particular LCIA method or a specific study, send the weighting/normalization results and I can identify the exact top three categories.


Question: What is the purpose of procedural organisation in the Inventory Analysis phase of an LCA?

The procedural organisation should ensure identical treatment of all general and specific subjects that the parties involved want to discuss in the Inventory Analysis phase.

The purpose of procedural organisation in the Inventory Analysis phase is to ensure identical treatment of all general and specific subjects that the parties involved want to discuss in that phase, while arranging the supervisory process so as to preserve the authoritativeness of the results.
(Guinée et al., Handbook on LCA, 2002, p.42)

In the **Inventory Analysis (LCI)** phase of an LCA, **procedural organisation** is used to **structure how data are collected, modelled, and connected across the product system**.

Its main purpose is to:

- **Define the sequence of steps and unit processes** in the system
- **Ensure consistent data handling** for inputs, outputs, and allocations
- **Organise responsibilities and methods** for data collection and calculation
- **Make the inventory transparent, reproducible, and traceable**
- **Support completeness and avoid double counting or omissions**

In short, procedural organisation helps turn a complex product system into a **systematic, manageable inventory model** that can be analysed reliably.


Question: What unit is used to express the Freshwater Aquatic Ecotoxicity Potential (FAETP) characterization factors listed in the table?

The FAETP characterization factors are expressed in kg 1,4-DCB equivalents per kg (kg 1,4DCB eq./kg).

Freshwater Aquatic Ecotoxicity Potential (FAETP) characterization factors are expressed in **kg (1,4-dichlorobenzene eq) per kg emission**.
**Source:** Guinée et al., *Handbook on LCA* (2002), **p.77, Section 4.3.3.8.2**.

Freshwater Aquatic Ecotoxicity Potential (FAETP) characterization factors are typically expressed in:

**kg 1,4-dichlorobenzene equivalents (kg 1,4-DCB-eq)**

This means the ecotoxicity impact of a substance is related to the impact of **1,4-dichlorobenzene** as a reference substance.


Question: What should the supervisory process preserve during the main choices stage of the LCA Inventory Analysis phase?

The supervisory process should be arranged so as to preserve the authoritativeness of the results.

During the main choices stage of the LCA Inventory Analysis phase, the supervisory process should preserve **the authoritativeness of the results**.
**Citation:** Guinée et al., *Handbook on LCA: Operational Guide to the ISO Standards* (2002), **p. 42**.

During the **main choices stage** of the **LCA Inventory Analysis**, the supervisory process should preserve:

- **Consistency with the goal and scope definition**
- **Transparency of assumptions, rules, and choices made**
- **Data quality and methodological coherence**
- **Traceability/documentation of decisions**
- **Reproducibility and comparability of results**

In short, it should ensure that key modeling choices remain **consistent, documented, and aligned with the study objectives**.


Question: What are the main results of the Impact Assessment phase that serve as input for the Interpretation phase?

The main results include the environmental profile, the normalised environmental profile, and the weighting profile.

The main results of the Impact Assessment phase that serve as input for the Interpretation phase are:

- The quantitative results of the impact assessment per impact category
- An account of non-quantified but relevant environmental aspects
- Possible preliminary conclusions
- The results of any sensitivity analysis

(Source: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards, 2002, p.64)

In LCA, the main **Life Cycle Impact Assessment (LCIA)** results that feed into the **Interpretation** phase are:

- **Characterized impact results**
  The quantified contributions to each impact category (e.g., climate change, acidification, eutrophication).

- **Optional normalized results**
  Impact results expressed relative to a reference, to show their relative magnitude.

- **Optional grouped results**
  Impact categories sorted or ranked into groups (e.g., local vs global, high vs low priority).

- **Optional weighted results / single-score results**
  Impact categories combined using weighting factors to support comparison or decision-making.

- **Contribution analysis by life cycle stage/process/flow**
  Identification of which processes, materials, or stages are driving the impacts.

These LCIA results are then used in the **Interpretation** phase to identify significant issues, check completeness/consistency/sensitivity, and draw conclusions and recommendations.


Question: What information about the practitioners must be provided in an LCA report?

A presentation of the practitioners, including their background, shall be given in the form of an LCA-oriented C.V.

The report must identify the LCA practitioner(s), including whether they are internal or external.

Cited source: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.426, “general aspects: 1) LCA commissioner, practitioner of LCA (internal or external)”.

In an LCA report, you should identify the people who carried out the study and their qualifications. Typically this includes:

- **Names of the practitioners/authors**
- **Their affiliations/organizations**
- **Their roles in the study** (for example, modeling, data collection, review, interpretation)
- **Their qualifications or competence relevant to LCA** such as education, training, or experience

If the study includes a **critical review**, the report should also identify the **reviewer(s) or review panel** and their qualifications.


Question: What must be included in the report if an external validation or review process has not been carried out?

A statement that an external validation or review process has not been carried out must be included, along with a justification of that decision (e.g., since concerned parties have been involved in the conduct of the study).

A statement that an external validation or review process has not been carried out, including a justification of that decision (e.g. since concerned parties have been involved in the conduct of the study).
Chapter/page cited: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.458.

If no external validation or review has been carried out, the report should explicitly state that fact.

Typically, it should include:
- a clear declaration that no external validation/review was performed
- where relevant, a note that the results have not been independently verified
- any limitations this may imply for interpretation or intended use of the study

If you want, I can also give the exact wording commonly used in LCA/EPD reporting contexts.


Question: Where has the quality analysis been shifted to in the LCA framework described?

The quality analysis has been shifted to the Interpretation.

The quality analysis has been shifted to the interpretation phase of the LCA framework, where overall result quality is assessed through contribution, perturbation, and sensitivity analyses.

Cited source: Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), Part 3, p.495.

In the described LCA framework, the **quality analysis has been shifted to the Life Cycle Inventory (LCI) level**.

That means quality-related aspects are handled earlier in the assessment, during the inventory phase, rather than only later in impact assessment.


Question: What is an intermediate product in the context of a Life Cycle Assessment?

An intermediate product is an input or output from a unit process which undergoes further transformation before consumptive use.

An intermediate product is the output from a unit process that is input to other unit processes and requires further transformation within the system. (Hauschild et al., LCA: Theory and Practice — Glossary, p.1190)

In Life Cycle Assessment, an **intermediate product** is a product or material that is **produced and used within the product system** to make another product, rather than being the final product delivered to the end user.

Examples:
- Steel sheet used to manufacture a car body
- Plastic resin used to make a bottle
- Electricity or steam used in a production step

In LCA terms, intermediate products:
- are exchanged **between unit processes**
- serve as **inputs to downstream processes**
- are not usually the **reference flow/final functional output**

So, they are essentially **in-between products or flows** in the life cycle chain.


Question: In compound terms, how is the term 'unit process' shortened for brevity?

In compound terms, the term 'unit' is omitted, so 'unit process' is simply referred to as 'process' (e.g., process data, foreground process).

The provided context does not state a specific shortened form of “unit process” used in compound terms for brevity. (No citation available in the provided excerpts.)

It’s commonly shortened as **u-process** (or **unit-process** in compound use).


Question: What is the fourth phase of a Life Cycle Assessment (LCA), and what does it involve?

The fourth phase of an LCA is interpretation, in which the results of the Inventory analysis and/or Impact assessment are interpreted in the light of the Goal and scope definition.

The fourth phase of an LCA is **life cycle interpretation**. It involves reviewing inputs from the other phases and, due to the iterative nature of LCA, may lead to changes in earlier phases when errors are found or results are too sensitive to particular data or model choices.
**[Hauschild et al., LCA: Theory and Practice — Glossary, p.1191; Guinée et al., Handbook on LCA, p.450]**

The **fourth phase** of a Life Cycle Assessment (LCA) is **Interpretation**.

It involves:

- **Analyzing the results** from the inventory and impact assessment phases
- **Checking completeness, consistency, and sensitivity**
- **Identifying significant issues** and key contributors
- **Drawing conclusions and recommendations** based on the goal and scope of the study

In short, this phase turns the LCA results into **meaningful findings for decision-making**.


Question: What area of protection does the casualties impact category refer to?

The casualties impact category refers to human health as the area of protection.

The casualties impact category refers to **human health**.
**Citation:** Guinée et al., *Handbook on LCA: Operational Guide to the ISO Standards* (2002), **Part 2b, Section 4.3.16 “Casualties,” p.85**.

The **casualties** impact category generally refers to the **Area of Protection: Human Health**.

It captures impacts related to **injuries and deaths of people**, often from accidents, disasters, or hazardous technologies/processes.


Question: What is the MAETP (inf) characterization factor for selenium (CAS number 7782-49-2)?

The MAETP (inf) characterization factor for selenium (CAS number 7782-49-2) is 1.3E+07 kg 1,4DCB eq./kg.

The MAETP (inf) characterization factor for selenium (CAS 7782-49-2) is 5.9E+04 kg 1,4-DCB eq./kg (Chapter 4, p.330).

The **MAETP (inf)** characterization factor for **selenium** (**CAS 7782-49-2**) is commonly reported as:

**2.1 × 10⁴ kg 1,4-DCB-eq/kg emission**

If you want, I can also tell you the **method/source** this comes from (for example, CML or another LCIA method), since characterization factors can vary by method and compartment.


Question: What unit is used to express both the MSETP and TETP characterization factors listed in the table?

Both MSETP and TETP characterization factors are expressed in kg 1,4-DCB equivalents per kg (kg 1,4DCB eq./kg).

Both MSETP and TETP characterization factors are expressed in **kg 1,4-DCB eq./kg**.
Guinée et al. (2002), **p.323**.

Both the **MSETP** and **TETP** characterization factors are typically expressed in:

**kg 1,4-DCB-eq**

That means **kilograms of 1,4-dichlorobenzene equivalent**.


Question: What does the symbol 'X' represent in the MSETP and TETP data columns of the table?

The symbol 'X' appears in place of a numerical value, indicating that no characterization factor data is available for those particular entries.

The provided context does not explicitly define what the symbol “X” represents in the MSETP and TETP table columns, so I cannot determine it from these excerpts alone. Cite: Guinée et al. (2002), pp. 242, 246, 260, 263–264, 285–286, 291, 306, 312.

In LCA tables, an **“X”** in the **MSETP** and **TETP** columns usually means that the process or material **has a relevant contribution / is included for that impact category**.

Here:
- **MSETP** = **Marine Sediment Ecotoxicity Potential**
- **TETP** = **Terrestrial Ecotoxicity Potential**

So the **“X”** generally indicates that **data is available or the impact category applies** for that entry, rather than giving a numeric value directly. If you want, I can also help interpret the full table if you share it.


Question: What unit is used to express the characterisation factor for ionising radiation damage?

The characterisation factor for ionising radiation damage is expressed in yr/kBq emission (years per kilobecquerel of emission).

The characterisation factor for ionising radiation damage is expressed in **yr/kBq emission**.

Cited source: **Guinée et al. (2002), p.85, Part 2b, section 4.3.15.1**.

In LCA, the characterisation factor for **ionising radiation damage** is typically expressed in:

**DALY per kBq emitted**
or more generally
**DALY per unit emission**

Where:
- **DALY** = Disability-Adjusted Life Years, the damage indicator for human health
- **kBq** = kilobecquerel, a unit of radioactive activity

At the midpoint level, ionising radiation may also be expressed in **kBq U-235 eq** depending on the LCIA method.


Question: What are the three types of impact categories distinguished in the default list elaborated for LCA practitioners?

The three types are 'baseline' impact categories, 'study-specific' impact categories, and 'other' impact categories.

The default list distinguishes three types of impact categories:

1. Baseline impact categories
2. Study-specific impact categories
3. Other impact categories

Cited in:
- Guinée et al., Handbook on LCA, Section 4.3.2, p.67
- Guinée et al., Handbook on LCA, p.533

In the commonly used default lists for LCA practitioners, impact categories are often grouped into three types:

1. **Resource use**
   Covers depletion or use of natural resources such as minerals, fossil fuels, land, and water.

2. **Human health impacts**
   Covers effects on human health from emissions or other interventions, such as toxicity, particulate matter, or climate-change-related health damage.

3. **Ecosystem quality / ecological impacts**
   Covers effects on ecosystems, biodiversity, and species due to emissions, land use, acidification, eutrophication, ecotoxicity, etc.

If you want, I can also give the exact wording used in a specific LCIA method or guideline.


Question: What concept, besides expert-based weighting factors, can serve as the basis for aggregation in human toxicity impact assessment?

Aggregation may also be based on the concept of Disability Adjusted Life Years (DALYs).
— Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), Chapter 4, p.586

A common alternative basis for aggregation in human toxicity impact assessment is **severity (or seriousness) of health effects**.

So, instead of aggregating with **expert-based weighting factors**, impacts can be aggregated using a **severity-based concept**, where different health outcomes are weighted according to how serious they are (for example, mild illness vs. irreversible disease or premature death).