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.

## Why Toxicity Impact Categories Have Much Higher Uncertainty

### Core Reasons

**1. Extremely Long and Complex Cause-Effect Chains**
Toxicity characterization requires modeling multiple sequential steps:
- Emissions → environmental fate & transport → exposure → toxicokinetics → toxicodynamics → effect

Each step multiplies uncertainty, whereas acidification or global warming involve shorter, better-constrained pathways.

**2. Fate & Exposure Modeling Complexity**
- Chemicals partition across many compartments (soil, water, sediment, air, biota) in ways that depend heavily on substance-specific physicochemical properties (Kow, Koc, Henry's law constant, etc.)
- Many of these properties are **measured with high uncertainty or estimated** from QSARs
- Bioaccumulation and bioavailability are difficult to characterize generically

**3. Enormous Diversity of Substances and Mechanisms**
- Tens of thousands of chemicals with different modes of action, target organisms, and dose-response relationships
- No single universal metric exists (compare: CO₂-equivalents work well for GWP because the mechanism is uniform)
- Different endpoints (carcinogenicity, neurotoxicity, endocrine disruption) are difficult to aggregate meaningfully

**4. Dose-Response Relationship Uncertainty**
- Extrapolation across species, from high to low doses, and across exposure routes introduces large uncertainty
- Threshold vs. non-threshold debate for many substances
- Use of **HC50/HC5** (hazardous concentration for species sensitivity distributions) involves significant statistical uncertainty

**5. Lack of Empirical Validation**
- Acidification, ozone formation, and GWP characterization factors can be compared against well-established atmospheric chemistry and monitoring data
- Toxicity characterization factors are rarely validated against real ecosystem or human health outcomes at the systems level

**6. Data Gaps**
- Most chemicals lack complete ecotoxicological or human toxicological datasets
- Missing data forces reliance on read-across, QSARs, or omission — all sources of uncertainty

---

### Contrast with "Better-Constrained" Categories

| Feature | GWP / Acidification / PCOP | Human Tox / Ecotox |
|---|---|---|
| Cause-effect chain length | Short–medium | Very long |
| Mechanistic understanding | Well-established | Incomplete |
| Number of substances | Few key drivers | Thousands |
| Empirical validation | Good | Poor |
| Spatial/temporal variability | Moderate | Very high |

---

### Quantitative Implication
Uncertainties in toxicity characterization factors commonly span **2–4 orders of magnitude**, compared to factors of ~2–5× for GWP or acidification factors. This makes toxicity results in LCA particularly sensitive to methodological choices and data quality.

Human toxicity and ecotoxicity midpoint impact categories are associated with considerably larger uncertainties than categories like acidification, photochemical ozone formation, or global warming for several interconnected reasons:

**1. Sheer number of substances and range of characterisation factors**
These toxicity categories cover an enormous number of elementary flows — there is "a factor of >1000 between other impact categories and the toxicity categories," with characterisation factors spanning many orders of magnitude. For freshwater ecotoxicity alone, 90% of characterisation factors fall within five to six orders of magnitude, while the full range spans 16–19 orders of magnitude. By contrast, categories like eutrophication, acidification, or global warming cover only a handful of elementary flows with impact potentials ranging only three to four orders of magnitude. *(Hauschild et al., Chapter 10, p.187; Chapter 11, p.312)*

**2. Complexity of fate and intermedia transport modelling**
Toxic substances do not remain in the compartment into which they are emitted but spread to other compartments, making accurate modelling considerably more difficult and uncertain. *(Guinée et al., p.589)*

**3. Precision vs. accuracy trade-off**
While indicators like GWP are precise (input data are straightforward to measure and reproducible), toxicity indicators statistically quantify disease cases or affected species per mass emitted — a more complex and less precise, though more environmentally relevant, calculation. *(Hauschild et al., Chapter 11, p.278–279)*

These factors are explicitly acknowledged in the ILCD Handbook, which states that "chemical-related midpoint level impact categories addressing human toxicity and ecotoxicity are thus accompanied by considerably larger uncertainties than the often energy-conversion related midpoint level categories." *(European Commission – JRC, ILCD Handbook, p.297)*

Midpoint impact categories for human toxicity and ecotoxicity are associated with considerably larger uncertainties than categories such as acidification, photochemical ozone formation, or global warming for several interconnected reasons:

**1. Sheer number and variability of substances involved**
The toxicity categories cover an extraordinarily large number of elementary flows, with characterisation factors ranging over many orders of magnitude. As noted, there is "a factor of >1000 between other impact categories and the toxicity categories (human health and ecotoxicity)" in terms of the number of elementary flows assigned. By contrast, categories like eutrophication, acidification, or global warming cover only a handful of elementary flows with impact potentials ranging only three to four orders of magnitude (Hauschild et al., *10 Life Cycle Impact Assessment*, p.187).

**2. Enormous spread of characterisation factors**
For freshwater ecotoxicity alone, 90% of characterisation factors fall within five to six orders of magnitude, while the full range spans 16–19 orders of magnitude across 2,499 organic chemicals (Hauschild et al., *11 Uncertainty Management and Sensitivity Analysis*, p.312).

**3. State of the art in modelling and data quality**
The ILCD Handbook explicitly states: *"The chemical-related midpoint level impact categories addressing human toxicity and ecotoxicity are thus accompanied by considerably larger uncertainties than the often energy-conversion related midpoint level categories addressing e.g. acidification, photochemical ozone formation or global warming impacts"*, reflecting limitations in the underlying impact pathway modelling and the availability and quality of substance data (ILCD Handbook, p.297).

**4. Precision vs. accuracy trade-off**
While GWP is a precise indicator (based on well-reproducible laboratory measurements of radiative forcing), it is less accurate regarding actual environmental impacts. Toxicity indicators, though less precise, quantify statistically how many disease cases or affected species may occur per mass emitted — making them more environmentally relevant but inherently more uncertain (Hauschild et al., *11 Uncertainty Management and Sensitivity Analysis*, p.279).


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 three data quality attributes that must be sufficiently similar across the compared systems are:

1. **Time-related coverage** (temporal representativeness) – the data should refer to the same or equivalent time periods
2. **Geographical coverage** (spatial representativeness) – the data should reflect the same or equivalent geographic regions/contexts
3. **Technology coverage** (technological representativeness) – the data should represent the same or equivalent technology levels or mixes

These requirements are specified in ISO 14044 to ensure that comparisons between systems are valid and that differences in results reflect actual differences in the systems rather than artifacts of inconsistent data quality.

Based on Source 8 (European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.300), the consistency check provisions state that differences in **data quality per se** must be checked across compared systems.

More specifically, from Source 4 (ILCD Handbook, p.305), the three data quality attributes that must be of comparable quality across all compared alternatives are:

1. **Accuracy**
2. **Completeness**
3. **Precision** (along with methodological consistency)

As stated in provision I.d.iii): *"The inventory data should be of comparable quality (i.e. accuracy, completeness, precision, methodological consistency) for all compared alternatives."*

— ILCD Handbook: General Guide for LCA (2010), p.305

Based on the ILCD Handbook, when comparing systems in an LCA, the inventory data should be of comparable quality across all compared alternatives in terms of three data quality attributes:

1. **Accuracy**
2. **Completeness**
3. **Precision** (and methodological consistency)

As stated in the ILCD Handbook: "The inventory data should be of comparable quality (i.e. accuracy, completeness, precision, methodological consistency) for all compared alternatives." (European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.305)


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, the key differentiation required to support established practice in resource-depletion impact assessment is:

**Differentiation by energy carrier type (fuel type) and by whether the resource is from an in-ground (virgin/fossil) source versus other sources.**

More specifically:

1. **Differentiation by fuel/energy carrier** (e.g., hard coal, lignite, crude oil, natural gas, uranium, etc.) — because different energy carriers have different energy content, scarcity, and characterization factors in resource depletion methods.

2. **Differentiation between the energetic content basis** — many resource depletion characterization methods (such as CML, ReCiPe, or methods based on thermodynamic approaches like Exergy/Cumulative Exergy Demand) rely on knowing the **upper (gross) calorific value (UCV/HHV)** or **lower calorific value** of the specific fuel, requiring the elementary flow to be linked to a specific energy carrier.

3. **Differentiation between "in ground" resources** (primary, fossil/mineral) versus renewable or secondary sources — because most abiotic resource depletion impact categories only apply characterization factors to virgin, in-ground fossil resources.

In practice, this means that energetic resource elementary flows must be specified by **individual fuel type** (not aggregated as generic "energy") and identified as **in-ground** resources, so that methods like **Abiotic Resource Depletion (fossil)** (e.g., in CML) or **Cumulative Energy Demand** can apply appropriate characterization factors based on calorific value or scarcity.

According to the ILCD Handbook, for energetic resource elementary flows, **exclusively a differentiation by type of deposit/source** is required to support established practice in resource-depletion impact assessment. Specifically:

- **Primary, secondary, and tertiary crude oil**
- **Open pit or underground mining of hard coal**

Other fossil fuel resource elementary flows (natural gas, oil shale, tar sand, lignite, peat) **do not currently need a differentiation**.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 220)*

According to the ILCD Handbook, for energetic resource elementary flows, **exclusively a differentiation by type of deposit/source** is required to support established practice in resource-depletion impact assessment. This means only **primary, secondary, and tertiary crude oil** and **open pit or underground mining of hard coal** need differentiation. Other fossil fuel resource elementary flows (natural gas, oil shale, tar sand, lignite, peat) **do not currently need a differentiation**.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 220)*


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.

## Functional Unit in Outdoor Wall Paints LCA

In the classic outdoor wall paints comparison example (commonly used in LCA methodology textbooks and ISO 14044 guidance):

### Quantified in the Functional Unit:
**Technical/performance properties** are quantified, specifically:
- The **coverage area** (e.g., m² of wall surface covered)
- The **durability/service life** (e.g., protection over a defined number of years, such as 10–15 years)
- The **hiding power/spreading rate** (m²/L)

These are expressed together so the functional unit delivers equivalent protective and decorative function over time (e.g., "covering 1 m² of wall surface for 15 years").

### Merely Documented (not quantified in the FU):
**Aesthetic properties** (such as color, gloss level, appearance) are typically only **documented as background information** — they are noted to ensure the compared products are equivalent in these respects, but they are not mathematically incorporated into the functional unit calculation.

### Key Principle:
This distinction reflects the general LCA rule that the functional unit must capture the **primary function** in measurable terms, while secondary or qualitative characteristics that define the comparison scope are recorded as **reference flow qualifiers** or product specifications rather than being quantified in the FU itself.

Based on Source 2 (European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.64):

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

As stated in the ILCD Handbook: "The quantitative definition of the function of the product and some key qualitative aspects will typically be based on the **obligatory properties** of the product" (which are quantified in the functional unit), while "other qualitative aspects that typically relate to the user perception may be identified among the **positioning properties**" (which are only documented).

This is explicitly illustrated in Table 4 of that page for the outdoor wall paints comparison, where obligatory properties (such as covering the wall with uniform colour, protecting against rain/sun/microalgae, providing an easy-to-clean surface, and meeting health requirements) feed into the functional unit quantification, whereas positioning properties are simply documented.

Based on the ILCD Handbook, in the outdoor wall paints comparison example:

- **Obligatory properties** are quantified in the functional unit
- **Positioning properties** are merely documented

As stated in the ILCD Handbook: "The quantitative definition of the function of the product and some key qualitative aspects will typically be based on the **obligatory properties** of the product, while other qualitative aspects that typically relate to the user perception may be identified among the **positioning properties**." The table explicitly shows: "Obligatory properties → quantify in functional unit" and "Positioning properties → document."

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.64)*


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

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

When a study that includes product comparisons is disclosed to the public (i.e., made available to non-technical audiences), it must conform to the **full critical review requirements** — specifically, it must undergo a **critical review by a panel of interested parties** (a third-party panel review), as required by **ISO 14044** (and ISO 14040).

In practical terms, the key requirement is:

**A critical review by a panel including at least one independent expert and representation from interested parties (including public interest groups)** must be conducted before comparative assertions are disclosed to the public.

This is intended to protect non-technical audiences from potentially misleading or incomplete comparative claims by ensuring the study's methodology, data, and conclusions have been independently validated before public release.

Based on the context provided, when product comparisons are disclosed to the public, the study **shall apply the ISO requirements on "comparative assertions disclosed to the public"** — even when the study does not explicitly make an assertion of superiority or equality, but merely shows comparative environmental performance (e.g., through numbers or graphics).

This requirement exists to prevent bypassing ISO standards by publishing comparative results without formally asserting superiority, thereby protecting external audiences — including non-technical audiences such as consumers — from potentially misleading or incomplete comparative information.

> *"To avoid a by-passing of this ISO requirement by publishing product comparisons that show e.g. along the numbers or graphics the environmental performance of the compared products but without explicitly making an assertion as to superiority or equality, also comparative but not assertive LCA studies shall meet these requirements"*
> — **ILCD Handbook, p. 34**

Additionally, the goal definition shall explicitly state whether the study includes a comparative assertion intended to be disclosed to the public, and the target audience must be classified as "internal," "restricted external," or "public," and differentiated between "technical" and "non-technical."

> — **ILCD Handbook, p. 36 (Requirements III, IV, V, VI)**

Based on the context, when product comparisons are disclosed to the public, the study **shall apply the ISO requirements on "comparative assertions disclosed to the public"** — even when the study is comparative but not explicitly assertive (i.e., not explicitly claiming superiority or equality between products).

This requirement exists specifically to prevent bypassing ISO standards by publishing product comparisons that show environmental performance data (e.g., through numbers or graphics) without formally making an assertion of superiority or equality — which could nonetheless mislead non-technical audiences such as consumers.

As stated in the ILCD Handbook:

> "To avoid a by-passing of this ISO requirement by publishing product comparisons that show e.g. along the numbers or graphics the environmental performance of the compared products but without explicitly making an assertion as to superiority or equality, also comparative but not assertive LCA studies shall meet these requirements."

*(ILCD Handbook, p. 34)*

Additionally, the goal definition **shall explicitly state** whether the study includes a comparative assertion intended to be disclosed to the public, and the target audience must be identified and classified (including distinguishing "technical" vs. "non-technical" audiences), as this classification drives additional mandatory requirements on execution, documentation, review, and reporting.

*(ILCD Handbook, pp. 34 and 36)*


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 as an allocation criterion for multifunctional processes, the price should refer to:

- **The point of substitution/diversion** – i.e., the price at the point where the co-products leave the process (gate price or ex-works price), not at the final consumer market. This avoids distortions introduced by downstream processing, transport, or marketing costs that differ between co-products.

- **Marginal or long-run market prices** rather than short-term fluctuating spot prices, to ensure stability and representativeness.

- **The same market conditions and location** for all co-products being allocated – meaning prices should be compared at the same point in the supply chain (same geographic market, same stage of processing) to ensure consistency and comparability.

- **The relevant geographic market** where the products are actually traded, reflecting the conditions applicable to the system under study.

In practice, this means using **prices at the factory gate** (ex-works) for all co-products simultaneously produced, so that differences in downstream value chains do not inappropriately skew the allocation factors. The ISO 14044 standard and related guidance (e.g., ILCD Handbook) stress that prices used must be **consistent, simultaneous, and at the same system boundary point** to be a valid allocation basis.

Based on Source 1 (ILCD Handbook, p.268), when market price is used as an allocation criterion for multifunctional processes, the price shall refer to:

**Specific conditions and location**: The price must relate to **the specific point where the co-functions leave or enter the multifunctional unit process or are provided**.

More specifically, the known, calculated, or approximated market price shall relate to:
- The **specific technical characteristics** in quantity and quality (such as purity, compressed or not, packaged or not, etc.)
- **Bulk or small amounts**
- All measured **at the point it leaves the process**

If these conditions cannot be met, the resulting lack of accuracy and potential distortion of the results shall be documented and considered in the results interpretation.

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

Based on the ILCD Handbook, when market price is used as an allocation criterion for multifunctional processes, the price **shall refer to the specific condition and at the point the co-functions leave or enter the multifunctional unit process or are provided**.

More specifically, the known, calculated or approximated market price shall relate to:
- The **specific technical characteristics** in quantity and quality (such as purity, compressed or not, packaged or not, etc.)
- **Bulk or small amounts**, etc.
- **At the point it leaves the process**

If this cannot be done, the resulting lack in accuracy and potential distortion of the results shall be documented and considered in the results interpretation.

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


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

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

Under the **flexibility principle** in LCA (as outlined in ISO 14044), when deviations from the standard provisions or requirements are made, the following is required:

1. **Transparency** – The deviations must be clearly described and documented in the study report.
2. **Justification** – The reasons for the deviation must be explicitly stated and justified, explaining why the deviation was necessary or appropriate for the specific study.
3. **The deviation must not compromise the overall integrity** of the study or the validity of the results.

In essence, the flexibility principle allows practitioners to adapt the methodology to specific situations, but any such deviation must be **transparently reported and scientifically justified**, so that the study remains credible and the results are not misleading. This ensures that even with methodological flexibility, the study maintains its reliability and the results can be properly interpreted by the intended audience.

When deviations from the guidelines are made, practitioners **must clearly justify their decision accordingly**. Additionally, it is advisable to introduce such deviations in the form of a **sensitivity analysis of detailed LCA**, in order to retain reference to a more or less standardised type of LCA. The implementation of such deviations is **entirely the responsibility of the LCA practitioner**.

*(Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.452)*

When deviations from the guidelines/provisions are made under the flexibility principle in LCA, practitioners must **clearly justify their decision** accordingly. Furthermore, it is advisable to introduce such deviations **in the form of a sensitivity analysis** of detailed LCA, in order to retain reference to a more or less standardised type of LCA. The implementation of such deviations is **entirely the responsibility of the LCA practitioner**.

*(Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p. 452)*


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 in LCA Context

In the framework developed by the **Swedish Environmental Research Institute (IVL)** and used in discussions around consequential vs. attributional LCA (particularly in waste and recycling contexts), the "Situation" classification describes how a system handles **co-products and recycling**.

---

### Situation C1 Characteristics

**Situation C1** describes a case where:
- A product system **produces a recyclable material** (or co-product) that **displaces virgin material production** in another system
- The **recycled material substitutes** for a primary/virgin material on the market
- The **credit for recycling** is given to the **producing system** (the system that generates the recyclable output)
- This is often associated with **open-loop recycling** where material crosses system boundaries

The key feature is the **direction of the credit**: the system delivering the recyclable material receives the environmental benefit.

---

### Relationship to Other Situations

| Situation | Description |
|-----------|-------------|
| **A/B** | Closed-loop recycling or co-products handled within the same system; substitution or allocation within a single product system |
| **C1** | Open-loop recycling — **credit goes to the first (producing) system** |
| **C2** | Open-loop recycling — **credit goes to the second (using/recycling) system** |

---

### Key Distinction: C1 vs. C2

- **C1**: The system that **produces** the recyclable waste/material takes the recycling credit
- **C2**: The system that **uses** the recycled material takes the credit

This distinction significantly affects **which product system** appears more environmentally favorable and is particularly relevant in **waste management LCA** and **end-of-life modeling**.

---

This framework is closely linked to ISO 14044 guidance on system expansion and is frequently discussed in the context of the **European Commission's Product Environmental Footprint (PEF)** methodology and circular economy assessments.

## Characterization of Situation C1 and Its Relationship to Other Situations

### Definition of Situation C1

Situation C1 is defined as **"Accounting, with system-external interactions"** — a purely descriptive accounting or documentation of an analysed system (past, present, or forecasted future) that **includes existing interactions with other systems** in the LCI model, such as recycling benefits or avoided production for co-products. Critically, this occurs **without implying a decision-context** that would account for potential additional consequences on other systems.
*(ILCD Handbook, p.43)*

### Relationship to Situations A/B

While Situations A and B involve **additional/future consequences assumed to be caused by the analysed decision**, Situation C1 only accounts for **existing/past interactions** between systems. As stated:

> *"Situation C1 lies hence between A/B and C2, being retrospective but accounting for benefits on other systems e.g. via co-products and recycling."*
*(ILCD Handbook, p.46)*

### Relationship to Situation C2

The key difference between C1 and C2 is:
- **C1** includes existing benefits outside the analysed system (e.g., recycling benefits)
- **C2** accounts for the analysed system **in isolation**, excluding any such interactions

C1 is the **default choice** unless C2 is specifically prescribed by the commissioner's goal.
*(Hauschild et al., p.71)*

### Typical Applications of C1
- Monitoring environmental impacts of nations or industry sectors
- Policy information studies (basket-of-products)
- Corporate/site environmental reporting under EMS
- Development of average or generic LCI datasets

*(ILCD Handbook, p.43)*

## Situation C1: Characteristics and Relationships

### Definition and Core Character

Situation C1 is defined as **"Accounting, with system-external interactions"** — a purely descriptive accounting/documentation of the analysed system (past, present, or forecasted future) **without implying a decision-context** that would account for potential additional consequences on other systems (ILCD Handbook, p.43).

### Key Characteristics

- **Retrospective documentation** that includes existing interactions with other systems (e.g., recycling benefits or avoided production for co-products) (ILCD Handbook, p.43)
- Uses **average processes** and is **attributional** in nature (Hauschild, *8 Scope Definition*, p.98)
- **No decision to be taken** from the LCA results (Hauschild, *7 Goal Definition*, p.71)

### Typical Applications

- Monitoring environmental impacts of a nation, industry sector, or product group
- Corporate/site environmental reporting including indirect effects under EMS
- Development of specific, average, or generic unit process or LCI results data sets
(ILCD Handbook, p.43)

### Relationship to Situations A/B

Situation C1 is **retrospective** but, unlike A and B, does **not account for additional/future consequences** caused by an analysed decision. The "interactions" in C1 refer only to *existing* interactions with other systems, contrasted with the *additional consequences assumed to be caused by the analysed decision* in Situations A and B. Notably, **"Situation C1 lies between A/B and C2"** (ILCD Handbook, p.46).

### Relationship to Situation C2

The key difference between C1 and C2 is whether **existing benefits outside the analysed system are considered**:
- **C1 includes** these existing interactions (e.g., co-products, recycling benefits)
- **C2 accounts for the analysed system in isolation**, i.e., without such interactions

C1 is used **by default** unless C2 is specifically prescribed by the commissioner's goal (Hauschild, *7 Goal Definition*, p.71).


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.

# Geographical Representativeness in LCA

When ensuring geographical representativeness, the practitioner must identify and confirm proper representation of the following location-varying elements:

## Background System Elements

- **Electricity grid mix** (generation sources, transmission losses, marginal vs. average supply)
- **Water availability and stress** (scarcity characterization factors vary significantly by watershed)
- **Transport infrastructure** (distances, modes, fuel mixes)
- **Waste management systems** (treatment technologies, landfill gas capture rates)

## Foreground/Process Elements

- **Emission factors** (combustion conditions, technology standards, regulatory context)
- **Energy efficiency** of industrial processes (varies by regional technology vintage)
- **Agricultural practices** (yield factors, fertilizer application rates, soil conditions)
- **Raw material extraction impacts** (ore grades, land use context)

## Impact Assessment Elements

- **Characterization factors** that are spatially differentiated:
  - Ecotoxicity and human toxicity (fate & exposure modeling)
  - Land use impacts (biodiversity context)
  - Water scarcity (AWARE or similar regionalized factors)
  - Eutrophication (sensitivity of receiving water bodies)

## Practical Confirmation Steps

1. Match **inventory data** to the actual geographic scope (site-specific, regional, national, continental)
2. Verify **background database** geography aligns with actual supply chains
3. Apply **regionalized LCIA methods** where spatial variability is significant
4. Document **any mismatches** between data geography and actual geography as limitations

The core principle is aligning **where processes actually occur** with **where data and characterization factors assume they occur**.

Based on the sources provided, when ensuring geographical representativeness in an LCA, the practitioner must identify and confirm proper representation of the following location-varying elements:

**1. Technology level and operating conditions** — including the type and level of technology applied, and the conditions under which it runs (e.g., surrounding climate or national legal requirements on emission limits) (ILCD Handbook, p.128).

**2. Elementary flows, energy flows, material flows, and waste to treatment** — two processes delivering the same product output but located in different places can differ considerably in these flows (Hauschild et al., Ch. 8, p.106).

**3. Geographical differences** — such as local climate and proximity to natural resources (Hauschild et al., Ch. 8, p.106).

**4. Regulatory differences** — such as energy taxes and emission thresholds, which typically follow national borders (Hauschild et al., Ch. 8, p.106).

**5. Market mixes or marginal process mixes** — the location of the mix used in the model versus the actual location must be confirmed to match, for both attributional and consequential LCA (Hauschild et al., Ch. 8, p.106).

**6. Spatial scope resolution** — the appropriate resolution (city, region, nation, continent) must reflect spatial coverage of regulation, geographical variations, and the spatial extent of markets (Hauschild et al., Ch. 8, p.106).

Based on the retrieved passages, when ensuring geographical representativeness in an LCA, the practitioner must identify and confirm proper representation of the following location-varying elements:

**1. Technology level and operating conditions** — "The level and type of technology that is applied, and the conditions under which it runs (e.g. in terms of surrounding climate or national legal requirements on emission limits), are influenced by the geographical location of the process" *(ILCD Handbook, p.128)*

**2. Elementary flows, energy flows, material flows, and waste to treatment** — "two processes delivering the same product output, but taking place in two different locations...can be quite different in terms of the other flows (elementary flows, energy flows, material flows and waste to treatment)" *(Hauschild et al., 8 Scope Definition, p.106)*

**3. Geographical differences such as local climate and proximity to natural resources**, as well as **regulatory differences such as energy taxes and emission thresholds** *(Hauschild et al., 8 Scope Definition, p.106)*

**4. The location of market mixes** (attributional LCA) or **marginal process mixes** (consequential LCA) used in background system modelling versus the actual location *(Hauschild et al., 8 Scope Definition, p.106)*

**5. The appropriate geographical resolution** (city, region, nation, continent), depending on spatial coverage of regulation, geographical variations, and the spatial extent of markets *(Hauschild et al., 8 Scope Definition, p.106)*


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.

## Why Elementary Flows Should Be Inventoried as Individual Substances

### Core Principle
Elementary flows should represent **discrete physical/chemical entities** rather than aggregated measurements or categories. Here's why:

---

### 1. **Characterization Flexibility Across Impact Categories**
Individual substances can be characterized differently depending on the impact category:
- A heavy metal like **cadmium** contributes to human toxicity, ecotoxicity, AND possibly soil quality
- If inventoried as "heavy metals (grouped)," you cannot apply substance-specific characterization factors
- Different LCIA methods (USEtox, ReCiPe, CML) use **different factors for each substance**

---

### 2. **AOX/COD Are Measurement Artifacts, Not Substances**
- **AOX** (Adsorbable Organic Halogens) is an analytical proxy measuring a mixture — the actual toxicological behavior depends on *which* halogenated compounds are present
- **COD** (Chemical Oxygen Demand) lumps together substances with vastly different environmental fates and toxicities
- These indicators **cannot be linked to characterization factors** in any meaningful, scientifically defensible way

---

### 3. **Avoids Double-Counting**
- If a substance is both listed individually and included in a grouped flow, it would be counted twice in impact assessment

---

### 4. **Reproducibility and Transparency**
- Individual substance data allows independent verification
- Aggregated indicators depend on the analytical method used, making results non-comparable across studies

---

### 5. **Future-Proofing**
- As new LCIA methods develop characterization factors for additional substances, an inventory of individual flows remains usable
- Aggregated flows become stranded data if characterization methodology changes

---

### Practical Implication
> If only aggregate data (AOX, COD) is available from a process, this represents an **inventory quality limitation** that should be documented — it is preferable to decompose these into constituent substances wherever possible.

Elementary flows should be inventoried as individual substances rather than as measured indicators (such as AOX or COD) or grouped flows (such as "heavy metals" or "hydrocarbons") because **such measured and grouped elementary flows are generally not suitable for subsequent impact assessment and can cause large bias in the results, either exaggerating or underestimating the real impact potential**.

Additionally, sum-indicators and measured indicators "cannot be usefully addressed in impact assessment and which typically have no impact factor at all and that shall not remain in the inventory."

*(ILCD Handbook: General Guide for LCA, p. 215 and p. 278)*

According to the ILCD Handbook, elementary flows should be inventoried as individual substances rather than as measured indicators (such as AOX or COD) or grouped flows (such as "heavy metals" or "hydrocarbons") for the following key reasons:

1. **Unsuitability for impact assessment**: Such measured and grouped elementary flows "are in general not suitable for a subsequent impact assessment" (ILCD Handbook, p.215).

2. **Risk of biased results**: They "can cause large bias in the results, either exaggerating or underestimating the real impact potential" (ILCD Handbook, p.215).

3. **Lack of impact factors**: Sum-indicators such as "Metals" and measured indicators "cannot be usefully addressed in impact assessment and which typically have no impact factor at all" (ILCD Handbook, p.278).

4. **No double-counting**: When grouped or indicator flows are used alongside individual substances, there is a risk of double-counting across indicators and their contained individual substances (e.g., inventorying both "BOD" and "COD" simultaneously), which must be avoided (ILCD Handbook, p.217).

Additionally, the LCA Cookbook reinforces this, stating that "individually measured substances shall not be integrated/combined into measurement indicators and elementary flow groups but be inventoried individually" (Hauschild et al., LCA Cookbook, p.1028).


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.

# Options for Dealing with Data Gaps in LCI/LCA Studies

When missing inventory data is encountered, practitioners have several principal options:

## 1. **Measured/Primary Data Collection**
- Conduct direct measurements or request data from suppliers/operators
- Most accurate but time-consuming and costly

## 2. **Estimated Data**
- **Stoichiometric/mass balance calculations** – derive flows from known chemical/physical relationships
- **Engineering estimates** – based on process knowledge and expert judgment
- **Extrapolation** from similar processes or conditions

## 3. **Proxy/Surrogate Data**
- Use data from a **similar process, material, or technology**
- Geographically or temporally adjusted data from analogous systems

## 4. **Secondary/Background Database Data**
- Draw from established LCI databases (ecoinvent, GaBi, US LCI, etc.)
- May introduce representativeness issues

## 5. **Literature Values**
- Published studies, emission factors, industry reports

## 6. **Cut-off / Neglect**
- Exclude the flow if it is demonstrably **below a defined cut-off threshold** (mass, energy, or environmental significance)
- Must be justified and documented

## 7. **Sensitivity/Uncertainty Analysis**
- Use **scenario analysis or Monte Carlo simulation** to test the influence of assumed values on results

---

## Key Principle
ISO 14044 requires that **all assumptions, sources, and limitations be transparently documented**, and a **data quality assessment** should evaluate the impact of any gaps on the overall conclusions.

Based on the ILCD Handbook, the principle options for dealing with missing information in an LCI/LCA study are:

1. **Calculation from other, known information**
2. **Using information from similar processes or regions** with similar process operation (and background processes in case of LCI results) or older data
3. **Estimating the value based on specific expertise**
4. **Using methodologically not fully but sufficiently consistent data** (mainly referring to LCI data sets for background use)
5. **Accepting and documenting the gap**

The handbook notes that the best solution depends on the specific case: "qualified estimates may be very accurate while using data from not sufficiently similar processes or regions may result in relevant errors." It also emphasizes that "a good technical understanding of the process is indispensible to correctly deal with missing data" and that all measures taken must be documented.

Additionally, the first step should always be to **attempt to measure/obtain the data at the process operator**, and if that fails, data can be sought from a **third-party LCI data provider**.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 207)*

Based on the ILCD Handbook, when facing missing information in an LCI/LCA study, the following principle options exist for dealing with data gaps:

1. **Calculation from other, known information**
2. **Using information from similar processes or regions** with similar process operation (and background processes in case of LCI results) or older data
3. **Estimating the value based on specific expertise**
4. **Using methodologically not fully but sufficiently consistent data** (mainly referring to LCI data sets for background use)
5. **Accepting and documenting the gap**

The handbook notes that "which is the best solution, depends on the specific case: qualified estimates may be very accurate while using data from not sufficiently similar processes or regions may result in relevant errors. A good technical understanding of the process is indispensable to correctly deal with missing data. Measures taken are to be documented."

It also emphasizes that the first step should be to attempt to **measure/obtain the data at the process operator**, and if that fails, data can be obtained from a **third-party LCI data provider**.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 207)*


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.

## Importance of Consistent Naming Conventions in LCA

Using consistent naming conventions for common objects in LCA is critical for several interconnected reasons:

### 1. **Data Interoperability and Exchange**
- Different LCA databases (ecoinvent, GaBi, ELCD, etc.) and software tools need to communicate and share data
- Consistent names allow datasets from different sources to be **linked, merged, or compared** without manual reconciliation
- Enables the use of **background databases** alongside foreground data seamlessly

### 2. **Correct Impact Assessment Calculations**
- Characterization factors in Life Cycle Impact Assessment (LCIA) methods are mapped to **specific elementary flow names**
- If "Carbon dioxide" in one dataset is named "CO₂" or "carbon-dioxide" in another, the **characterization factor may not be applied**, leading to incorrect or incomplete results (e.g., missing GWP contributions)

### 3. **Avoiding Double-Counting or Omissions**
- Inconsistent naming can cause the same substance to be treated as **multiple different flows** or missed entirely during aggregation

### 4. **Reproducibility and Transparency**
- Standardized nomenclature ensures studies can be **replicated and verified** by third parties
- Supports **critical review** processes

### 5. **Efficiency and Error Reduction**
- Reduces time spent on **data cleaning and mapping**
- Minimizes human error in interpreting what a flow or unit represents

### Key Standards Addressing This
- **ILCD nomenclature**, **ecospold formats**, and **openLCA** reference flows all attempt to standardize elementary flow naming across the LCA community.

In essence, consistent naming is the **foundation of data quality and comparability** in LCA.

Using consistent naming conventions to identify and define commonly required objects is important in LCA for two key reasons:

1. **Integration of inventory data**: Consistent nomenclature 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 to the inventory data (ILCD Handbook, p.244).

2. **Enabling consistent practitioner work and correct LCIA linkage**: Consistent naming ensures that **different practitioners can consistently work with the data** (e.g., that the elementary flow "Carbon dioxide" is clearly identified by name, CAS number, and measured always in the same unit), and that **LCI data can be correctly linked with the LCIA characterization factors** (ILCD Handbook, p.334).

In essence, without such conventions, data from multiple sources could not be reliably aggregated or compared, and the connection between inventory flows and their associated impact assessment factors would break down.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), pp. 244 and 334)*

Using consistent naming conventions to identify and define commonly required objects is important in LCA for two key reasons:

1. **Combining and integrating inventory data**: Consistent nomenclature is "a pre-requisite for being able to combine and integrate inventory data sets from different data developers to systems and LCA studies" (ILCD Handbook, p.244).

2. **Correctly linking LCI data with LCIA methods**: It ensures "that the LCI data can be correctly linked with the LCIA factors" — for example, that "the elementary flow Carbon dioxide is clearly identified by name, CAS number, measured always in the same unit etc." (ILCD Handbook, p.334).

Additionally, consistent use of LCA terminology under "Nomenclature" ensures "that different practitioners can at all consistently work with the data" (ILCD Handbook, p.334).


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.

## Why LCA Doesn't Account for Direct Health Impacts During Use

LCA traditionally excludes direct health impacts on users during the use stage for several interconnected reasons:

### 1. **Methodological Boundary: Functional vs. Causal System**
LCA assesses **environmental burdens** flowing through a product system to the environment, then models how those environmental stressors affect human health *indirectly* (e.g., emissions → air quality → health). Direct physiological effects on users are considered **outside the environmental pathway**.

### 2. **The "Human as Beneficiary" Convention**
LCA's functional unit framework assumes the product delivers its **intended function** to the user. The health effect *is* the intended outcome (e.g., a drug curing disease) or is treated as a separate societal/regulatory matter, not an environmental externality.

### 3. **Characterization Factor Limitations**
Human health impact categories (e.g., DALYs in ReCiPe) are built around **environmental exposure pathways** (inhalation, ingestion of pollutants). There are no standardized characterization factors for direct pharmacological, nutritional, or toxic effects on the *consumer* themselves.

### 4. **Attribution Complexity**
Direct health impacts depend heavily on:
- Individual behavior and dosage
- Pre-existing conditions
- Voluntary vs. involuntary exposure

This makes them **highly context-specific** and difficult to generalize.

### 5. **Scope Definition (ISO 14040/14044)**
The ISO standards define LCA as covering **environmental** aspects; social and direct health consequences fall under **Social LCA (S-LCA)** or health risk assessment — separate, complementary tools.

---

**In essence**, LCA draws the system boundary around environmental flows, not physiological ones — direct user health impacts require different methodologies (epidemiology, risk assessment, S-LCA) to capture properly.

LCA does 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**. Since LCA is fundamentally designed to assess impacts that flow through the ecosphere (i.e., emissions to and interactions with the natural environment), direct human health effects that remain entirely within the technosphere fall outside its scope.

However, use-phase impacts that these products exert *via* an emission to the ecosphere (e.g., smoke emissions to the environment, wastewater discharge) are still to be included in the LCA.

*(ILCD Handbook: General Guide for LCA, 2010, p. 95)*

LCA does 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**. Since LCA is designed to assess impacts that move through the ecosphere (via emissions to the environment), direct effects on humans that remain entirely within the technosphere fall outside the scope of the LCA methodology.

However, use-phase impacts that these products exert *via* an emission to the ecosphere (e.g., smoke emissions to the environment, wastewater discharge) are still to be included in the LCA.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.95)*


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.

## Handling Net Accumulation or Depletion in LCA Inventory

Regardless of the substance type (agrochemicals, nutrients, heavy metals, carbon, etc.), the principle is consistent:

### Core Principle

**Net accumulation or depletion in the field should be treated as an inventory flow** — either as an emission to soil or as an uptake/sequestration from the environment.

### Specifically:

| Situation | Inventory Treatment |
|-----------|-------------------|
| **Net accumulation** (more enters than leaves the field) | Recorded as an **emission to soil** (output from the technosphere to the ecosphere) |
| **Net depletion** (more leaves than enters the field) | Recorded as a **resource extraction** or negative emission / avoided emission from soil |

### Rationale

- The field is not a "black box" — mass balance must be maintained
- Substances left behind in soil represent a **delayed environmental burden** (or benefit, in the case of carbon sequestration)
- This approach ensures **temporal consistency** and avoids underreporting environmental impacts

### Examples

- **Heavy metals**: Net accumulation in soil → emission to soil
- **Carbon (SOC)**: Net sequestration → negative CO₂ emission (or resource uptake); net depletion → CO₂ emission
- **Nutrients (N, P)**: Net surplus → emission to soil (with potential leaching implications)
- **Pesticides**: Residual persistence → emission to soil

This approach aligns with **mass balance principles** fundamental to LCI methodology (e.g., per ISO 14044 and guidance from ecoinvent/ILCD).

Net accumulation or depletion of a substance in the field shall be recorded in the inventory, disregarding the nature of the substance (whether it is an agrochemical, nutrient, heavy metal, carbon, etc.), and must be correctly considered in the system model or the impact assessment, as applicable. This applies because nutrients or other substances remaining in the field after harvest that serve as input to the next crop cross the system boundary within the technosphere over time, making the preceding crop's process multi-functional, and the general provisions for solving multifunctionality apply.

*(ILCD Handbook: General Guide for LCA, European Commission – JRC, 2010, p. 234)*

According to the ILCD Handbook, net accumulation or depletion of a substance in the field **shall be recorded in the inventory**, regardless of the nature of the substance (whether it is an agrochemical, nutrient, heavy metal, carbon, etc.), and must be correctly considered in the system model or the impact assessment, as applicable.

This provision also addresses the case where nutrients from fertilisation remain in the field after harvest and serve as input to the next crop — crossing the system boundary within the technosphere over time — making that process multi-functional, and requiring that the general provisions for solving multifunctionality apply.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 234)*


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.

When a plantation has a 30-year plantation cycle, the duration used for assigning land-use impacts should be **30 years** — corresponding to the rotation/cycle length of the plantation.

This is consistent with the approach in life cycle assessment (LCA) land use impact assessment methodology (e.g., as outlined in the UNEP/SETAC guidelines and the EC JRC method), where the relevant time period for land occupation impacts is the actual duration of land use, which equals the length of the production/rotation cycle.

Based on the ILCD Handbook guidelines, when a plantation has a 30-year plantation cycle, **that 30-year duration should be used** for assigning land-use impacts, rather than the default 20-year period.

As stated in the ILCD Handbook: "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."

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.100)*

This is further confirmed in Hauschild et al., which notes that "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."

*(Hauschild et al., LCA: Theory and Practice — 30 LCA of Biofuels and Biomaterials, p.774)*

Based on the ILCD Handbook guidance, when a plantation has a 30-year plantation cycle, that duration of **one plantation/use cycle (30 years)** shall be used for assigning land-use impacts.

As stated in the ILCD Handbook: "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."

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.100)*

This is corroborated by Hauschild et al., which recommends that LUC emissions for tree/palm plantations "are allocated to the first cycle of trees/palms, i.e. 20–30 years."

*(Hauschild et al., LCA: Theory and Practice — 30 LCA of Biofuels and Biomaterials, p.774)*


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.

## Elementary Flows for Lead-Zinc Ore Extraction

When extracting 1 kg of lead-zinc ore with 1.2% Pb and 2.3% Zn, the elementary flows inventoried in the **resource extraction** category are:

### Elementary Flows (Inputs from Nature)

| Elementary Flow | Calculation | Amount |
|----------------|-------------|--------|
| Lead (Pb), in ground | 1 kg × 1.2% | **0.012 kg** |
| Zinc (Zn), in ground | 1 kg × 2.3% | **0.023 kg** |

### Key LCA Principles Applied

- The elementary flows represent the **resources extracted from nature** (inputs from the ecosphere)
- These are recorded as **"X, in ground"** flows — the actual metal content removed from the natural stock
- The **gangue/waste rock** (the remaining ~96.5%) is generally not inventoried as an elementary flow since it is not a resource being utilized
- The ore itself (1 kg) is a **product flow** (economic flow), not an elementary flow

### Context

These elementary flows feed into **resource depletion impact categories** such as:
- Abiotic Resource Depletion (ADP) in CML methodology
- Mineral Resource Scarcity in ReCiPe

This approach follows standard LCA practice (ISO 14040/44) where elementary flows are defined as material drawn from the environment without prior human transformation.

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

- **0.012 kg "Lead"**
- **0.023 kg "Zinc"**

The ore body is differentiated into single elements' elementary flows rather than inventoried as a single combined ore flow.

*(Source 2: ILCD Handbook, p.221)*

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

- **0.012 kg "Lead"**
- **0.023 kg "Zinc"**

These individual element elementary flows are recorded on the input side, while the product flow "Lead-zinc ore; 1.2% Pb, 2.3% Zn" appears on the output side. This approach of splitting the ore into its constituent element elementary flows reduces the number of elementary flows in the final inventory, as only the relevant elementary resource flows "Lead" and "Zinc" remain when calculating LCI results.

*(ILCD Handbook: General Guide for LCA (2010), p. 221)*


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.

The incorrect way of combining attributional and consequential modelling within the same system model is described as **"hybrid" LCA** when it involves inconsistently mixing the two approaches — specifically, using **attributional (average/allocated) data for background systems while applying consequential logic (marginal/system expansion) for foreground systems** (or vice versa) without a coherent, consistent methodological framework.

More precisely, the practice often criticized is **inserting marginal/consequential data into an otherwise attributional framework** (or vice versa) in an ad hoc manner. This is considered incorrect because:

- Attributional LCA uses average data and allocation to model the actual physical flows of a system as it is.
- Consequential LCA uses marginal data and system expansion to model the effects of a decision/change.

Mixing these within the **same system boundary and calculation** violates the internal consistency of either approach — the background database assumptions (e.g., average electricity mix vs. marginal electricity supplier) are incompatible with each other, leading to results that are neither properly attributional nor properly consequential, and thus methodologically incoherent.

This is sometimes referred to in LCA literature (e.g., by Weidema, Finnveden, and others) as an **"inconsistent hybrid"** — contrasted with deliberate, methodologically justified hybrid approaches.

Combining attributional and consequential modelling on an **ad hoc, unsystematic basis** is described as incorrect — for example, allocating among the co-products of one multifunctional process while simultaneously substituting the co-products of another, without following a systematic approach.

*(Source 1: ILCD Handbook: General Guide for LCA (2010), p. 70)*

According to the ILCD Handbook, 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 while substituting the co-products of another. Instead, a systematic approach must be followed.

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p. 70)*


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 (recycled/recovered) material are unknown, the **system expansion by substitution** approach may not be straightforwardly applicable, so practitioners apply the **cut-off method** (also called the **recycled content method** or **cut-off allocation**).

However, the specific method you are referring to — where a **reduced amount of primary material** is credited based on a ratio — is the **"value-corrected substitution"** or, more precisely, the approach described in ISO 14044 and commonly known as the **50/50 method** (or more broadly, **allocation based on a quality/value ratio**).

More specifically, when the end-of-life fate or quality of a secondary material is uncertain, the **"recycling rate" or "recyclability" factor approach** credits the primary material inventory with a reduced credit based on the **ratio of the quality (or market value) of the secondary material to that of the primary material** — sometimes expressed as:

> **Credit = (Quality of secondary / Quality of primary) × inventory of primary material**

In many LCA frameworks (notably the **PEF — Product Environmental Footprint** methodology of the European Commission), this is formalized as the **"Circular Footprint Formula (CFF)"**, which uses a **quality ratio (Q_secondary/Q_primary)** to scale the substitution credit when the secondary material does not fully replace the primary.

In short: the method is **substitution with a quality-correction factor**, and it is based on the **ratio of the quality (or value) of the secondary material to that of the primary material**.

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

For example, if recycled polymer granulate has a market price of 0.9 US$/kg and the primary material granulate costs 1.2 US$/kg, then only 0.9/1.2 = 0.75 (75%) of the primary material inventory would be credited.

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

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

For example, if a recycled polymer granulate has a market price of 0.9 US$/kg and the primary material granulate costs 1.2 US$/kg, then only 0.9/1.2 = 0.75 (i.e., 75%) of the primary material inventory would be credited.

*(ILCD Handbook: General Guide for LCA (2010), p. 360; see also p. 182 and Hauschild et al., LCA: Theory and Practice, p. 1011, §13:2:6)*


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

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

In life-cycle assessment, weighting is applied for two main purposes:

1. **Aggregation across impact categories** – to combine the results of different impact categories (e.g., climate change, acidification, resource depletion) into a single overall score by assigning relative importance (weights) to each category, enabling a simplified comparison or ranking of product systems.

2. **Decision support / communicating priorities** – to reflect societal, political, or stakeholder value choices about the relative importance of different environmental issues, thereby supporting decision-making by highlighting which impacts matter most according to a given value perspective.

Based on the ILCD Handbook, weighting is mainly applied for two purposes:

1. **Weighting to support interpretation** (MAY): As an additional, optional element in support of the interpretation of results, one may perform a "weighting" or other valuation of the normalised or non-normalised indicator results.

2. **Weighting use in cut-off quantification** (MAY): For quantification of the achieved completeness/cut-off, the normalised indicator results for different impact categories may be weighted across the indicators.

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

Based on the ILCD Handbook, weighting is mainly applied for two purposes:

1. **Weighting to support interpretation**: As an additional, optional element in support of the interpretation of the results of the study, one may perform a "weighting" or other valuation of the normalised or not normalised indicator results.

2. **Weighting use in cut-off quantification**: For quantification of the achieved completeness/cut-off, the normalised indicator results for the different impact categories may be weighted across the indicators.

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


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.

## Why Exhaustive Listing of Functional Unit Aspects Is Not Useful

It is not considered useful to attempt listing **all potentially relevant aspects** of a functional unit and its specification because:

### 1. **Infinite Regress Problem**
There is theoretically no limit to the level of detail or number of characteristics that could be described for any product or service — the process becomes practically endless without adding meaningful value to the study.

### 2. **Context Dependency**
Which aspects are *actually relevant* depends entirely on the **specific goal and scope** of the study. Aspects that matter in one comparative study may be completely irrelevant in another, making a universal exhaustive list impossible and misleading.

### 3. **Risk of Obscuring Key Comparisons**
In comparative studies especially, listing excessive characteristics can **obscure the functionally equivalent aspects** that truly matter for ensuring a fair comparison between systems.

### 4. **Practical Resource Constraints**
LCA is inherently an iterative and resource-limited process. Spending effort documenting irrelevant aspects diverts attention from **aspects that genuinely drive the study's conclusions**.

### 5. **Clarity and Communication**
A functional unit specification should be **clear and communicable**; exhaustive listings reduce clarity rather than improving it.

---

**In summary:** Only the aspects that are **relevant to the study's goal**, particularly those needed to ensure functional equivalence in comparisons, need to be specified — completeness for its own sake adds no analytical value.

Based on the provided context, there is no information that directly addresses why it is not considered useful to attempt listing all potentially relevant aspects of a product's functional unit and specification. The sources discuss how to define functional units, what aspects to include, and common mistakes, but none of them explicitly explain why comprehensively listing all potentially relevant aspects would not be useful.

Based on the provided context, there is no passage that explicitly states why it is **not** considered useful to attempt listing **all** potentially relevant aspects of a product's functional unit and specification. The sources discuss *how* to define functional units, common mistakes, and what qualitative and quantitative aspects to include, but none of them directly address or explain why comprehensively listing all potentially relevant aspects would be considered not useful.

The answer to this specific question is not found in the provided context.


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

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

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

1. **Proxy data** – Data from similar processes, materials, or technologies that can serve as reasonable substitutes for missing data.

2. **Generic/average data** – Industry-average or sector-wide data sets from established LCA databases (e.g., ecoinvent, GaBi, ELCD).

3. **Scaled or extrapolated data** – Data from related processes that are mathematically scaled or extrapolated based on known parameters (e.g., mass, energy, capacity).

4. **Literature-based estimates** – Data sourced from published scientific literature, technical reports, or industry studies.

5. **Engineering estimates** – Estimates derived from engineering calculations, mass/energy balances, or process knowledge.

6. **Supplier/manufacturer data** – Data obtained from supply chain partners, even if not fully verified or site-specific.

7. **Stoichiometric/theoretical estimates** – Data derived from chemical or physical relationships (e.g., stoichiometry, thermodynamics).

8. **Older or geographically different data** – Temporally or geographically mismatched data used as a best available approximation.

These estimates should be clearly documented, their uncertainty acknowledged, and sensitivity analyses conducted to assess the influence of data gaps on the overall LCA results — consistent with requirements under **ISO 14044** and good LCA practice.

Based on the ILCD Handbook, when filling initial data gaps of included processes and systems, the following types of 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**
- **Generic or average data** for missing specific data
- **Average data of a group of similar products** for missing inventory data for other, not yet analysed products of that group
- **Correlation with other, more complete and high quality data** for the same or similar process but from other data sources (e.g., industry average data for improving a producer-specific process)
- **Justified judgements of technical experts / process operators**

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), pp. 212, 251, 253)*

Based on the ILCD Handbook, when filling initial data gaps of included processes and systems, the following types of 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**
- **Generic or average data** for missing specific data
- **Average data of a group of similar products** for missing inventory data for other, not yet analysed products of that group
- **Correlation with other, more complete and high quality data** for the same or similar process but from other data sources (e.g. industry average data for improving a producer-specific process)
- **Justified judgements of technical experts / process operators**

*(European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), pp. 251, 253, and 212)*


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: Technosphere/Ecosphere Boundary

### The Standard Approach

Waste and wastewater treatment processes should be modelled such that **emissions to the ecosphere are only reported at the point where substances actually cross the boundary into the natural environment** (i.e., after treatment).

Specifically:
- The **input to a treatment system** (e.g., raw wastewater, solid waste) is a flow **within the technosphere**
- Only the **treated effluent/residues released to air, water, or soil** constitute ecosphere emissions
- Intermediate flows between treatment stages remain technosphere flows

### The Correct Boundary Placement

```
Technosphere:
[Waste generated] → [Treatment process] → [Residual emissions] → Ecosphere
```

Emissions should be modelled **after** the treatment step, not before it, assuming the treatment will occur.

### If This Convention Is Not Followed

If emissions are reported **before treatment** (i.e., as if untreated), or if the treatment process is **outside the system boundary**, then:

1. **A correction must be applied** — the practitioner must manually account for the treatment efficiency and model the actual releases to nature
2. **Avoided burdens or credits** may need to be calculated
3. The **treatment process must be added** to the system as a linked unit process, ensuring the full chain is captured before emissions cross into the ecosphere
4. **Double counting must be avoided** — the untreated emission should not be reported alongside a treated emission

### Key Principle

The ecosphere boundary marks where human control ends. Waste within a pipe, tank, or facility is still in the technosphere — only what is discharged/released to nature counts as an ecosphere emission.

Waste and wastewater treatment shall be modelled **completely and consistently to the boundary between the technosphere and ecosphere**. This modelling includes all treatment steps up to and including disposal of any remaining waste-to-waste deposits or landfills, and inventorying the emissions from these sites to/from the ecosphere. Waste flows are not elementary flows but flows inside the technosphere, and therefore their further management and treatment needs to be modelled until they cross that boundary as elementary flows.

**If this is not followed**, it shall be **clearly documented** and **explicitly considered in later interpretation**.

Two exceptions apply:
- **Radioactive wastes** and
- **Wastes in underground deposits** (e.g. mine filling)

These should be kept as specific waste flows in the inventory, unless detailed, long-term management and related interventions have been entirely modelled for these as well.

*(Hauschild et al., LCA: Theory and Practice — 37 LCA Cookbook, p.1031; European Commission – JRC, ILCD Handbook: General Guide for LCA (2010), p.242)*

Based on the retrieved sources, waste and wastewater treatment should be modelled **consistently to the boundary between the technosphere and ecosphere**. This means modelling must include all treatment steps up to and including disposal of any remaining waste-to-waste deposits or landfills, and inventorying the emissions from these sites to/from the ecosphere.

Waste flows (such as household waste, end-of-life products, wastewater, and tailings) are **not elementary flows** — they are flows inside the technosphere — and therefore their further management and treatment must be modelled until they result in elementary flows crossing into the ecosphere (ILCD Handbook, p.242).

**If this complete modelling is not followed**, it shall be:
- **Clearly documented**, and
- **Explicitly considered in later interpretation**

Two exceptions exist: **radioactive wastes** and **wastes in underground deposits** (e.g. mine filling), which should be kept as specific waste flows in the inventory unless detailed, long-term management and related interventions have been entirely modelled for these.

Additionally, for **unmanaged landfilling, discharge, and littering** (discarding goods individually into nature), the related individual interventions that enter the ecosphere shall be modelled as part of the LCI model.

*(Hauschild et al., LCA: Theory and Practice — 37 LCA Cookbook, p.1031; ILCD Handbook, p.242)*


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

The chapter of the ILCD Handbook that addresses the appropriate coverage of what is reported or documented is **Chapter 5** (or the section dealing with **"Reporting"** / completeness of reporting).

More specifically, in the ILCD Handbook on General Guide for Life Cycle Assessment, the topic of appropriate coverage of what is reported or documented falls under the guidance on **completeness**, which is addressed in the context of **Chapter/Section on "Reporting and documentation"** — this is covered under the quality criteria and specifically relates to **"completeness"** as a data quality indicator.

In the ILCD Handbook structure, this is addressed in **Chapter 5** on **"Documentation and reporting"**, where completeness of the documented/reported scope and results is discussed as a key requirement.

If you are referring to a specific ILCD Handbook volume, could you clarify which one? The most commonly referenced is the *General Guide for LCA - Detailed Guidance*, where reporting guidance appears in the later chapters dealing with documentation requirements.

Based on Source 1, the appropriate coverage of what is reported/documented (referred to as "Appropriateness of documentation extent") is addressed in **Chapter 10** of the ILCD Handbook.

Based on Source 1, the **appropriate coverage of what is reported/documented** (referred to as "Appropriateness of documentation extent") is addressed in **Chapter 10** of the ILCD Handbook.


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

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

ISO 14064 is divided into **three parts**:

- **Part 1**: Specification with guidance at the organization level for quantification and reporting of greenhouse gas emissions and removals.
- **Part 2**: Specification with guidance at the project level for quantification, monitoring, and reporting of greenhouse gas emission reductions or removal enhancements.
- **Part 3**: Specification with guidance for the **validation and verification of greenhouse gas statements** — i.e., it focuses on the processes and requirements for those who validate or verify GHG assertions/claims made by organizations or projects.

Based on the available context, ISO 14064 is divided into at least **3 parts**, and **Part 3** focuses on the **"Specification and guidance for validation, verification and certification"** of greenhouse gases.

*(Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.4)*

Note: The context only explicitly mentions Part 3 of ISO 14064; the total number of parts is not fully detailed in the provided sources beyond confirming at least three parts exist.

Based on the available context, ISO 14064 is divided into at least **3 parts**. **Part 3** is titled *"Greenhouse gases – Part 3 – Specification and guidance for validation, verification and certification"* and focuses on the **validation, verification, and certification** of greenhouse gas statements.

(Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.4)


Question: Which ISO standard governs Life Cycle Impact Assessment?

ISO 14042 governs Life Cycle Impact Assessment.

The ISO standard that governs Life Cycle Impact Assessment (LCIA) is **ISO 14044:2006** (which covers requirements and guidelines for life cycle assessment, including the LCIA phase), as part of the broader LCA framework that also includes **ISO 14040:2006** (principles and framework).

Specifically, ISO 14044 provides the detailed requirements for conducting LCIA, including the mandatory elements (selection of impact categories, classification, and characterization) and optional elements (normalization, grouping, and weighting).

Based on the context provided, **ISO 14042** governs Life Cycle Impact Assessment.

As stated in Source 3 (Guinée et al., Handbook on LCA, p.651):

> "ISO International Standard 14042, 2000E. Environmental management – Life cycle assessment - **Life cycle Impact assessment**."

Additionally, Source 6 (Finkbeiner et al., p.11) confirms that ISO 14042:2000 was later technically revised, cancelled, and replaced by the new **ISO 14044**, which now consolidates the requirements and guidelines for LCA including impact assessment.

Based on the context, **ISO 14042** governs Life Cycle Impact Assessment.

This is referenced in Source 3 (Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002), p.651):

> "ISO International Standard 14042, 2000E. Environmental management – Life cycle assessment - **Life cycle Impact assessment**."

Additionally, Source 6 (Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, p.11) notes that with the publication of the new **ISO 14040 and ISO 14044**, the existing standards including ISO 14042:2000 were "technically revised, cancelled and replaced." Thus, **ISO 14044** now encompasses Life Cycle Impact Assessment requirements in the current standards framework.


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

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

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

Based on the provided context, the Fifth International Conference on EcoBalance is mentioned only in Source 1 (Chapter 11, p.319), which references "EcoBalance—Pract. tools thoughtful Princ. Sustain., 6–8 Nov 2002, Tsukuba, Japan (2002)."

The Fifth International Conference on EcoBalance was held in **Tsukuba, Japan, on 6–8 November 2002**. (Source 1: Chapter 11, p.319)

The retrieved context does not contain information about the Fifth International Conference on Ecobalances (its location or date). The only EcoBalance conference mentioned is the one held in **Tsukuba, Japan, on 6–8 November 2002**, which is referenced as "EcoBalance" in Source 1 (Hauschild et al., Chapter 11, p.319), but that does not specify it as the "Fifth" conference.

The answer to where and when the **Fifth** International Conference on Ecobalances was held is not found in the provided context.


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

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

I don't have specific knowledge of a 2004 LCA study co-authored by Schmidt, Dahlqvist, and Finkbeiner. Without reliable details about this particular publication, I'd rather not speculate about its focus and risk providing inaccurate information.

If you could provide additional context — such as the journal it was published in or the product/system studied — I might be able to help further. Alternatively, searching Google Scholar or a database like Scopus with those author names and the year 2004 would quickly identify the study.

Based on Source 1, the 2004 Life Cycle Assessment study co-authored by Schmidt, Dahlqvist, and Finkbeiner (along with Krinke, Lazzari, Oschmann, Pichon, and Thiel) focused on **lightweight and end-of-life scenarios for generic compact class passenger vehicles**.

*(Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.4)*

Based on Source 1 (Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.4), the 2004 Life Cycle Assessment study co-authored by Schmidt, Dahlqvist, and Finkbeiner focused on **lightweight and end-of-life scenarios for generic compact class passenger vehicles**.

The full citation referenced is: Schmidt WP, Dahlqvist E, Finkbeiner M, Krinke S, Lazzari S, Oschmann D, Pichon S, Thiel C (2004): Life Cycle Assessment of Lightweight and End-of-Life Scenarios for Generic Compact Class Passenger Vehicles. Int J LCA 9 (6) 405–414.


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

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

## Preferred Basis for LCA Decisions

### Preferred Basis: **Physical/Technical Relationships**

According to ISO 14044 and general LCA methodology, decisions regarding **system boundary setting, allocation, and other methodological choices** should preferably be based on **physical relationships** (cause-and-effect or technical/physical causality).

Specifically, this means:

- Allocation should **first be avoided** by expanding the system or subdividing processes
- When allocation cannot be avoided, it should be based on **underlying physical relationships** between products and environmental burdens (e.g., mass, energy content, volume)

---

### Alternatives When Physical Relationships Cannot Be Established

When physical relationships alone cannot reflect the underlying reality, alternatives include (in order of preference per ISO 14044):

1. **Other physical parameters** (e.g., mass flow, energy content, stoichiometric relationships)
2. **Economic/market value** – allocating burdens in proportion to the economic value of co-products
3. **Other relationships** as appropriate to the specific context

---

### Key Hierarchy (ISO 14044, Section 4.3.4.2)

| Priority | Approach |
|----------|----------|
| 1st | Avoid allocation (system expansion or subdivision) |
| 2nd | Physical allocation |
| 3rd | Economic allocation |

This hierarchy ensures that allocation choices reflect real-world causality as closely as possible.

Based on the available context, there is no direct answer to this specific question about the "preferred basis for decisions made within an LCA and alternatives when that is not possible."

However, the closest relevant information comes from **Guinée et al., Handbook on LCA (2002), p.410**, which notes that:

> "In practice, therefore, comparison of LCA predictions with reality is unattainable. In addition, when a choice is to be made between several alternatives for a given..."

This passage hints at the challenge of grounding LCA decisions in empirical verification, but the context provided does not complete the argument or enumerate specific alternatives.

Additionally, **ILCD Handbook (2010), p.70** notes that methodological choices in LCA "depend on the decision-context of the LCI/LCA study as well as a number of other criteria such as reproducibility and robustness, practical feasibility, stakeholder acceptance, and others," suggesting these serve as guiding criteria — but this does not directly answer the preferred basis for decisions within an LCA.

**The context provided does not contain a sufficiently complete answer to this question.**

Based on the retrieved context, the question of a preferred basis for decisions within LCA and its alternatives is addressed in the ILCD Handbook:

The preferred basis for decisions made within an LCA is derived individually for each study along the **study's goal and decision-context**, taking into account criteria such as **reproducibility and robustness, practical feasibility, and stakeholder acceptance**. This applies particularly to the choice of LCI modelling framework and approaches, which "is not an independent one but is to be derived individually for each study along the study's goal" (European Commission – JRC, ILCD Handbook, p.70).

When that systematic, goal-derived approach is not followed, errors arise. The ILCD Handbook explicitly identifies as **"frequent and severe errors"** in LCA practice the tendencies to:
- "always perform attributional (or consequential) LCA,"
- "always allocate" (or "do substitution"), or
- "unsystematically combine attributional and consequential modelling in the same system model on an ad hoc basis."

Additionally, the ISO 14040/14044 standards (Finkbeiner et al., p.11) note that "there is no single solution as to how LCA can best be applied within the decision-making context," and that alternatives such as **cradle-to-gate studies, gate-to-gate studies, or specific parts of the life cycle** (e.g., waste management) may be applied with proper justification when a full LCA is not possible.


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

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

In the context of LCA standardization under **ISO TC207** (the technical committee responsible for environmental management standards, including the ISO 14040 series on LCA), certain aspects are explicitly considered **beyond the scope** of the committee's work:

## Aspects Beyond TC207's Scope

### 1. **Setting Pass/Fail Thresholds**
- TC207 does not establish specific numerical limits or benchmarks that products/processes must meet; it provides methodology, not performance standards.

### 2. **Product/Process Performance Requirements**
- Prescribing specific environmental performance levels or eco-design requirements for particular product categories is outside its mandate.

### 3. **Tax or Economic Instruments**
- Determining environmental taxes, subsidies, or economic policy instruments based on LCA results.

### 4. **Accounting and Reporting of Organizational Financial Performance**
- Financial accounting standards are outside scope.

### 5. **Safety, Risk, and Hazard Assessment**
- Human health risk assessment and workplace safety are not covered under LCA standardization.

### 6. **Social and Economic Aspects** *(in traditional LCA context)*
- The original ISO 14040/14044 standards focus on **environmental** aspects; social LCA (S-LCA) and life cycle costing (LCC) were historically outside the core scope (though guidance has since developed separately).

### 7. **Regulatory/Legal Compliance Determinations**
- TC207 standards are not intended to be used as direct legal compliance tools.

---

These boundaries are typically stated in the **"Scope" and "Field of Application"** sections of ISO 14040 and 14044 to clarify what the standards do and do not govern.

Based on the provided context, there is no specific information about what aspects are considered beyond the scope of TC207 (ISO's Technical Committee 207) in the context of LCA standardization.

The sources do reference ISO standards (particularly ISO 14044) and mention that certain developments go beyond ISO standards, but none of the provided excerpts specifically address what falls outside the scope of TC207.

Based on the provided context, the sources do not directly address what aspects are considered beyond the scope of TC207 (the ISO Technical Committee responsible for environmental management standards) in the context of LCA standardization.

The closest relevant information comes from the Guinée et al. Handbook (p.452), which notes that "the [ISO] standards specify only the general structure of LCA" and that "true operationalisation involves so many choices that one can hardly expect the world to agree on all of them and formulate them in an ISO standard." Additionally, the ILCD Handbook (p.108) mentions that "the development of LCIA methods and factors is outside ISO 14044 and outside this document," suggesting that the development of specific LCIA methods falls beyond the standard ISO scope.

However, a specific and direct answer regarding what is considered beyond the scope of TC207 in LCA standardization is not available in the provided context.


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

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

I don't have access to sales data for ISO 14040 copies in Sweden or the Czech Republic. ISO sales figures by country are not publicly available information that I have in my knowledge base.

You would need to contact ISO directly, the Swedish Standards Institute (SIS), or the Czech Office for Standards, Metrology and Testing (ÚNMZ) for that specific sales data.

According to the context, **1,200 copies** of ISO 14040 were sold in **Sweden**, and **909 copies** were sold in the **Czech Republic**.

*(Source 2: Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.11)*

According to the source, **1,200 copies** of ISO 14040 were sold in **Sweden**, and **909 copies** were sold in the **Czech Republic**.

(Finkbeiner et al., The New International Standards for LCA: ISO 14040 & 14044, Int J LCA 11(2):80–85 (2006), p.11)