A Review of Current Substitution Estimates for Buildings with Regard to the Impact on Their GHG Balance and Correlated Effects—A Systematic Comparison

Abstract

The construction sector accounts for one-third of Europe’s total greenhouse gas (GHG) emissions, offering significant potential for emission reduction. Emission reduction can be achieved by substituting conventional building materials with wood- or bio-based alternatives; the difference in GHG emissions is referred to as the substitution potential (SP). In this study, a literature review was conducted to identify studies in which SPs had been determined. The calculation methods used for these SPs were then analysed in detail. The analysis considered the general conditions, outcomes, and scaling effects, revealing that differing initial conditions lead to inconsistent results. Therefore, transparent allocation of SPs and comparable product life cycle assessments (LCAs) based on functional equivalence are essential. To reliably extrapolate the benefits of wood use to the entire construction sector, scaling effects must be justified by consistent functional equivalence. For policy relevance, it is crucial that SPs are determined using the standardised rules and that the building level, as the actual place of material use, is not overlooked. This is particularly important when scaling up the effects of increased wood use to the landscape level. Only with these measures SPs at the product level can provide reliable results in a broader context. Additionally, the studies reviewed indicate that changes in forest management have not yet been considered.

1. Introduction

1.1. General

The pressure to act is growing due to the constantly increasing demand to protect the climate and the need to meet greenhouse gas (GHG) reduction targets. In its Special Report on Global Warming of 1.5 °C, the Intergovernmental Panel on Climate Change (IPCC) [1] determined that the remaining GHG emission quotas required to achieve the 1.5 °C and 2 °C targets are 570 and 800 GtCO₂e, respectively.

The construction and housing sector has a major responsibility, as it accounts for 37% of global energy-related CO₂ emissions [2] and approximately 40% of European primary energy demand [3]. At the building level in Europe, embodied emissions account for around 21% of total GHG emissions over the entire life cycles of buildings [4].

To strengthen the contribution of the construction and housing sector with regard to the GHG reduction targets, different policies, instruments and initiatives exist in the European Union (EU), such as the ‘European Green Deal’ [5], the EU regulation 2024/3012 on a ‘certification framework for permanent carbon removals, carbon farming and carbon storage in products’ (CRFC) [6], the EU directive 2023/1791 on ‘energy efficiency’ [7], and the ‘New European Bauhaus Initiative’ [8]. Likewise, in Germany, the Federal Climate Change Act [9] and the Federal Action Plan on Nature-based Solutions for Climate and Biodiversity [10], as well as the Wood Construction Initiative [11], exist. Regulations such as the CRFC, for example, refer to a standard-compliant calculation method for building life cycle assessment (LCA) according to EN 15978 and EN 15804. Consequently, the construction sector can reduce its GHG emissions by constructing and renovating buildings using two strategies: reducing the operational energy of buildings and reducing the GHG emissions associated with the life cycles of the building materials contained within those buildings. These emissions are also known as ‘embodied emissions’ [1]. The operational energy of a building can be reduced through a combination of the thermal optimisation of the building envelope, selection of efficient heating systems, integration of renewable energies, implementation of energy-efficient lighting and ventilation strategies, adoption of high-efficiency cooling systems, optimisation of equipment load, utilisation of a sustainable energy mix, and promotion of energy-conscious user behaviour. A reduction in embodied GHG emissions can be achieved by selecting construction materials with a lower environmental impact. When comparing the emissions of different construction materials, wood in particular is often associated with lower emissions [12]. This paper examines the second approach, the reduction in embodied emissions, through using wood- and bio-based products.

1.2. GHG Relevance of Wood

As shown in Figure 1, there are three GHG relevant mechanisms of action to be considered in the GHG balance of wood products: (1) biogenic CO₂ emissions and removals from forests, (2) biogenic CO₂ emissions and removals arising from harvested wood products (HWP), and (3) the non-biogenic GHG emissions of manufacturing industries.

Through harvesting timber, some of the biogenic carbon that was previously sequestered by living biomass in the forest ecosystem is transferred to the product system. Here, the material use of wood in a consumer product merely delays the release of that material’s inherent biogenic carbon until the end of the lifespan of this product.

According to the United Nations Framework Convention on Climate Change (UNFCCC) [14] and the associated calculation rules of the IPCC [1], national GHG inventories estimate and report GHG emissions by sources and their removals by sinks. These inventories specifically address biogenic CO₂ emissions and removals from the forest-based sector. The calculations are based on annual changes in defined biogenic carbon pools at both the landscape and national levels. Besides the five forest carbon pools, namely above- and below-ground living tree biomass, dead wood, litter, and soils, this also includes HWPs. The results of the calculated changes in those carbon pools (i.e., carbon storage effects) are reported under the category ‘land use, land use change and forestry’ (LULUCF) as part of countries’ GHG inventories. Therefore, HWPs can also serve as both a source of biogenic CO₂ emissions and a sink if this pool increases over time at the national level [14,15,16]. This is why HWPs often play a vital role in countries’ policies to achieve national GHG reduction targets [1,14].

At the product level, carbon balance is neutral because the biogenic carbon that has been transferred from the ecosystem is released again at the end of the product’s life. Individual products do not sequester CO₂ from the atmosphere, and their carbon content does not increase during their service life—they therefore do not represent a sink. This is also a mandatory requirement in all relevant international standards on the LCA, especially relevant for the construction sector [17,18]. The method of LCA that is standardised in ISO 14040:2006 [19] and ISO 14044:2006 [20] is intended to quantify and assesses all environmentally relevant material and energy flows, as well as all environmentally relevant impacts of the defined product system. This also includes the impact category ‘climate change’ with its indicator global warming potential (GWP), in which, as required by standards for the construction sector, the environmental impact is also subdivided into life cycle stages (modules).

Unlike biogenic CO₂ emissions from renewable biomass, which can only be classified within a larger framework (see (1) and (2) of Figure 1), the remaining non-biogenic GHG emissions of a product system can be very well quantified using LCAs.

1.3. GHG Substitution Potential

At the building level, processing timber and the manufacturing of wood products often requires fewer fossil fuels than producing conventional construction materials such as brick stones, steel or concrete, as shown in [21,22]. So, when comparing functional equivalent buildings made with different construction materials (e.g., wood versus concrete or brick stone), the wood-based construction works often generate lower fossil GHG emissions. Those resulting emission reductions, in terms of lower embodied GHG emissions (not to be mixed with the term ‘embodied carbon’), are often referred to as the substitution potential (SP) [13,21,23,24].

The SP indicates how much GHG emissions are reduced by using more low-emission construction materials (e.g., wood products) compared to the more emission-intensive construction materials (non-wood product) in the defined product systems or buildings. It is calculated as the difference in the results for the LCA indicator GWPs of the assessed product systems or buildings [15].

Following the international standard on LCA for buildings, a comparison always requires the functional equivalence of the analysed product systems [19] to fulfil the same minimum technical and functional requirements [25,26], including aspects such as the structural safety and load carrying capacity of the construction, as well as fire protection requirements according to building regulations and noise protection. The term substitution is often illustrated by means of a GHG displacement factor, as introduced for the first time by Sathre and O’Connor [27]. This metastudy compared various LCA studies in the literature and generated an average displacement factor. To compare all the different product systems described in those studies, the authors decided to relate the observed GHG differences from the analysed studies to the particular amount of biogenic carbon contained in the relevant wood-based product system (tC/tC). However, not only did all the analysed studies originate from different years, regions, or countries, but they also assessed various product systems based on different functional requirements (products, construction elements, buildings), and the studies were based on different system boundaries (spatial and temporal).

1.4. Objectives of This Study

While the reference to carbon content appears to permit mathematical generalisation with regard to the utilisation of wood, it does so by disregarding the normatively required basic principle of functional equivalence. The reverse conclusion derived from this, according to which the use of wood as a raw material is always associated with a substitution effect, is also too simplified.

Therefore, this study defines criteria to be used for analysing the comparability of studies assessing substitution. This paper analyses the literature where SP through using wood-based construction materials is presented. The following aspects were considered: the general conditions of studies, results at the product level, and scaling effects. Additionally, the studies were analysed to see how they arrive at their SPs and where they derive possible upscaling effects.

The objective of this study is to provide an overview of the current research on substitution estimates. At the same time, this paper contextualises the literature found to create a common understanding of the results and to give clear advice on what needs to be addressed.

2. Materials and Methods

A literature search was conducted to identify relevant papers on the topic of SP. The following keywords were entered in ResearchGate and Google Scholar: ‘displacement factor’, ‘substitution factor’, ‘substitution potential’, ‘substitution’, ‘carbon sequestration’, ‘carbon storage’ AND ‘building’, ‘built environment’, ‘timber’, ‘wood’, ‘timber construction’. The list of identified studies was reviewed for relevance. In addition to the proposed studies themselves, the sources of these studies were examined for further relevant studies, and the search was expanded accordingly. International peer-reviewed papers published between 2017 and 2022 were considered because a significant increase in the literature was found from 2017 onwards, as the topic has only recently come on the public agenda. The resulting literature was filtered by excluding duplicates, studies outside the period under review, thematic references to the construction sector, and inaccessible papers. The remaining papers were reviewed and any papers that did not represent SP or emission reductions were eliminated. This resulted the inclusion of 25 papers in this study.

To analyse the identified SPs, the studies were first divided into two categories: product level (1) and building level (2). This division was based on the different functionalities of each level. Studies focusing on the product level consider individual construction materials. The SP is determined by comparing wood-based and non-wood-based products (which are used for the same functional purpose). Based on the assessed SP at the product level, conclusions are drawn as to which products should be preferred for making an environmentally friendly choice. At the building level, the entire building is assessed. The GHG emissions of timber buildings and their non-wood equivalents, consisting of steel, masonry and reinforced concrete constructions, are compared and all building components are considered. This approach allows for determining the potential for GHG substitution in the context of the entire residential and non-residential building stock.

Both categories were analysed using the indicators shown in

Table 1. Indicators for analysing the studies investigated.

General Conditions	Outcome	Scaling Effects
Sector Background of Authors	Definition of Substitution Potential	Scaling Level
Scope of Application	GHG Substitution Potential	Period/Date
Region	Comparative Values of Substitution	Reference Scenario
Standards	GHG Emission Reductions	Scenarios
System Boundaries	Biogenic Carbon Storage	Calculation Rules
Reference Study Period		GHG Emission Reductions
LCA Background Data and Database		Biogenic Carbon Storage
Functional Units and der Equivalence

. These indicators directly influence the determination of the SP and include general conditions, outcome, and scaling effects. The general conditions represent the foundation for determining the SP. The outcome includes the results of the calculations, the calculation method, and the comparative values. The scaling effects summarise the underlying assumptions for extrapolation and result values.

The definitions of the applied indicators are provided in Section 2.1 for the general conditions, Section 2.2. for the studies’ outcomes, and Section 2.3 for the scaling effects. This includes an explanation of the relevance and context of each indicator.

2.1. Describtion of Indicators: General Conditions

Sector Background of Authors: The sector background of the authors is distinguished as either construction or forestry, depending on the place of publication and the academic background of the authors. This approach allows for a clearer understanding of the context and perspective from which the research has been conducted.

Scope of Application: At the building level, the scope of application provides a more detailed definition of the building type. The classification includes residential and non-residential buildings, as well as the exact type of use.

Region: The region has a significant influence on the standards and technical requirements applied to construction material, products and buildings. The energy mix is also country-specific, meaning that the associated datasets differ.

Standards: The standards considered in the LCA study specify the method for determining emissions at building and product levels. Among other things, this includes specifications on the system boundaries and applies at the national, European or international level.

System Boundaries: According to current standards, the environmental assessment of the entire life cycle of a product and a building must be carried out within defined system boundaries. EN 15804 [18] and EN 15978 [25] define the system boundary according to the ‘modularity principle’, which comprises the manufacturing and construction phase (Module A), the use phase (Module B), and the disposal phase (Module C). Benefits and burdens that lie beyond the system boundary are assigned to Module D and have to be shown separately (see [18,25,26]).

Reference Study Period: The calculation of LCAs is conducted over a defined time period. At the building level, this period is referred to as the reference study period in accordance with EN 15978. At the product level, this period corresponds to the assumed service life.

LCA Background Data and Database: The calculation of LCAs is based on material-specific values. These values are taken both from LCA background databases as they are contained in corresponding LCA software systems (e.g., by Ecoinvent or Sphera Solutions) and publicly available LCA-databases that provide LCA results for specified product systems, e.g., associated with the building sector (e.g., ECO Platform). While the former are especially intended for analysing the life cycle inventory (LCI) in the course of modelling and conducting LCA in corresponding LCA software and contain data on material flows and background data for individual process steps. The latter already offer corresponding LCA results that have been calculated under certain assumptions. However, the differences in the level of detail of the data contained in these two different types of databases are fluid.

Functional Units and their Equivalence: To determine the SP, the functional unit is determined in the first phase of an LCA (the definition of the objective and the scope of the study). The functional unit is defined in EN ISO 14044 as the ‘quantified performance of a product system for use as a reference unit’ [20]. Functional equivalence is defined in EN 15804 (product level) and EN 15978 (building level) as the ‘basis for comparisons of quantified functional requirements and/or technical requirements for a building or a composite building element’ [25].

The papers were examined with regard to their functional unit at the product level and their functional equivalence at the building level.

2.2. Describtion of Indicators: Outcome

Definition of Substitution Potential: There is currently no universally accepted definition for the determination of SP. Consequently, both the magnitude of the calculated SP and the interpretations or conclusions that can be derived from this value may differ depending on the underlying methodological approach.

GHG Substitution Potential: The SP is determined according to the underlying definition. The SP indicates the reduction in emissions achieved by substituting construction materials associated with higher emissions for those with lower emissions (see Section 1.3). The SP is material-specific and results from the difference in emissions between the comparative values of substitution.

Comparative Values of Substitution: In calculating the SP, the pivotal factor is the basis upon which the SP is derived. In this context, construction materials are substituted by low-emission construction materials both at the product and building levels.

GHG Emission Reductions: The GHG emissions associated with construction materials differ for various construction materials. A comparison of the emission budgets of wood-based materials with those of non-wood-based materials showed that the GHG emissions of wood-based materials were often lower than those of the non-wood-based materials [28,29,30,31,32,33]. The difference in GHG emissions is used to determine the GHG emission reduction potential. This value is used for the studies that did not contain SP as a factor. Emission reductions were often given as a percentage of various reference values.

Biogenic Carbon Storage: Over the life cycle of wood-based construction materials, the stored amount of carbon is booked in and out. An input is made during tree growth, since, at this time, carbon is bound in the wood via photosynthesis. This amount of stored carbon is entered in Module A of the LCA and is accounted for as negative CO₂ emissions or, according to EN 15804, as biogenic GWP. It remains there until the disposal of the HWP (Module C). At this point, the amount of stored carbon is booked out as positive emissions in an −1/+1 approach, so there are no emission reductions from carbon storage over the entire life cycle according to the construction-related standards ISO 21930 and EN 15978/EN 15804 and the general product-related standard ISO 14067 [34]. If the HWPs are recycled, the carbon quantity is first booked in as credit and finally booked out as emissions during the disposal of the recycled material. Biogenic carbon storage therefore serves as a material-inherent property of the wooden material.

2.3. Describtion of Indicators: Scaling Effects

Scaling Level: The scaling level summarises two levels, the base level and the upscaling level, between which scaling effects occur. At the baseline level, data on emission reductions and biogenic carbon storage are collected at the material, product, or building level. These values are then scaled up to the upscaling level using information from the harvest, consumption, production, building, or market level.

Period/Date: The scaling effects refer to a defined reference date or period of time. This date or period is either in the future, so that a forecast of development at the product or building level is required, or in the present/past, so that statistical values can be used.

Reference Scenario: The reference scenario serves as a reference for determining the reduction potential of upscaling scenarios compared to a defined baseline scenario. The reference scenario should be clearly defined and represents the state of the art.

Scenarios: Scaling effects are determined for defined scenarios. Scenarios may be based on past or present statistics, or they may be projections of future developments. The upscaling of different scenarios is used to calculate past, present, or future GHG emission reductions and biogenic carbon storage.

Calculation Rules: Calculation rules are the set of clearly defined methods, assumptions, formulas, and parameters that determine how emissions are scaled from one level (e.g., product or building) to another (e.g., harvest or consumption level). These rules ensure consistency, transparency, and reproducibility in the calculation process, enabling meaningful comparison and interpretation of results across different studies or contexts.

GHG Emission Reductions and Biogenic Carbon Storage: Upscaling allows statements to be made about actual and potential GHG emission reductions and biogenic carbon storage. These values are expressed as reductions or additional storage compared to the reference level.

3. Results

The papers were examined with regard to the indicators described in Section 2. In

Table 2. Studies with reference product level (1).

GENERAL CONDITIONS
Year	Sector Background of Authors	Region	Standards	System Boundaries (Modules)				Reference Study Period	LCA Background Data and Database	Functional Units and Their Equivalence		Reference
				A	B	C	D
2017	Forestry	Canada	-	✓ (A1–A3)	-	-	-	-	Literature	End-use product (SFH, MFH, multiuse building, flooring, furniture, decking)		[35]
2021	Forestry	Ireland, Northern Ireland	-	✓	-	✓	-	-	Literature	-		[36]
2021	Forestry	Finland	-	s. [23]	s. [23]	s. [23]	s. [23]	-	Literature	Functional unit groups (structural element, non-structural element, short-lived use)		[37]
2018	Forestry	var.	var.	var.	var.	var.	var.	var.	var.	var.		[23]
2018	Forestry and Construction	Japan	-	✓	-	-	-	100 years	Literature	Functional equivalence for different products (equivalent soil improvement conditions, volume of sediment runoff, paving thickness, class for roadside earth-embedded guardrails or levels of sound transmission loss and wind load)		[38]
2020	Construction	Global	-	✓	✓	✓	-	-	-	Function: ceiling		[39]
2022	Forestry	Global	-	✓ (A1–A3)	-	-	-	80 years	-	-		[40]
2018	Construction	Quebec City, Canada	EN ISO 14067 EN ISO 14040 EN ISO 14044	✓	-	-	-	-	Ecoinvent Database	Functional unit: 1 m2 of floor area for residential purposes		[41]
OUTCOME
Definition SP		SP		Substitution —Comparative Values					GHG Emission Reductions	Biogenic Carbon Storage		Reference
(ΣNfD * Kfp)/Dp		0.54 tC/tC 0.45 tC/tC		Sawnwood —less wood-intensive products Panels —less wood-intensive products					-	-		[35]
(GHGnon-wood-GHGwood)/ (WUwood)		1.85 tCO2e/tCO2e		Wood-based—alternative products					-	0.9175 tCO2/m3		[36]
(GHGnon-wood-GHGwood) /(WUwood-WUnon-wood)		Pine: 1.28 Mg C/Mg C Spruce: 1.16 Mg C/Mg C Birch: 1.43 Mg C/Mg C		Wood—non-wood					-	s. [37], Table 2		[37]
(GHGnon-wood-GHGwood)/ (WUwood-WUnon-wood)		Ø 1.3 kgC/kgC (Structural construction); Ø 1.6 kgC/kgC (Non-structural construction)		Wood—non-wood					-	var.		[23]
-		1.41 tCO2e/m3		Wood—non-wood					s. [38], Table 1	1.04 tCO2e/m3 (incl. in SP)		[38]
-		-		CLT—RC					-	-		[39]
-		-		Engineered wood—conventional construction material					-	✓		[40]
-		-		EPS—cellulose Conventional floor materials —hardwood flooring system					2.19 kg CO2e/m2 8.4 kg CO2e/m2	✓		[41]
SCALING EFFECTS
Scaling Level		Period/Date	Reference Scenario	Scenarios					Calculation Rules	GHG Emission Reductions	Biogenic Carbon Storage	Reference
From the product level to the production level		2019	(0) Estimated production 2019	-					Production volume [m3] * Carbon content [tCO2e/m3] * SP [tCO2/tCO2]	1.09 Mt CO2e/year	-	[36]
From the material level to the production and consumption levels		(0) 2015–2018 (a) - (b) 2030 (c) 2050 (d) 2003 (e) 2009	(0) BAU	(a) Potential (b) WEM 2030 (c) WEM 2050 (d) Historical production 2003 (e) Historical production 2009					Not evident *	(a) 1% (b) 9% (c) 32% (d) 20% (e) −30%	(0) 10.0 Tg CO2/year	[37]
From the product/building level to the market level		By 2030	(0) BAU	(a) Increase in sawnwood production by 1.8%/year (b) Increase in multi-storey residential wood buildings by 1%					Not evident *	(a) 88.7 Mt CO2e (b) 4.4 Mt CO2e	-	[23]
From the product level to the production level		(1) By 2030 (2) By 2050	(0) Zero scenario in 2017	(a) Likely potential (b) Maximum potential					Production volume [m3] * SP [tCO2/m3]	(2a) 4.82 mio. tCO2e/year (2b) 9.63 mio. tCO2e/year	(1a) 1.09 mio. tCO2e/year (1b) 2.17 mio. tCO2e/year (2a) 2.18 mio. tCO2e/year (2b) 4.36 mio. tCO2e/year	[38]
From the product (ceiling) level to the building market		2020–2050	(0) Baseline (S50)	Urban density scenarios: (a) Low (S25) (b) High (S75) Levels of uptake for hybrid systems: (A) u = 0 (no uptake) (B) u = 1 (full uptake)					s. [39], Equation (1)	(0A) 171–303 Mt CO2e (0B) 142–229 Mt CO2e (aA-B) and (bA-B) s. [39], Figure 5 (B) 22–82.8 Mt CO2e (GHG)	-	[39]
From the product level to the building market		2020–2100	(0) BAU	Proportion of new urban population living in wooden buildings (a) 10% (b) 50% (c) 90%					Not evident *	(0) 138 Gt CO2 (a) 14 Gt CO2 lower, 10% lower (b) 71 Gt CO2 lower, 51% lower (c) 106 Gt CO2 lower, 77% lower	(a) 7 Gt CO2 (b) 33 Gt CO2 (c) 53 Gt CO2	[40]
From the product level to the building level		-	(0) Baseline	(a) EPS—cellulose (b) Conventional floor materials —hardwood flooring system					(emission reduction on product level)/(emission of the baseline building)	(a) 0.8% (b) 3.1%	-	[41]

* The calculation rules are not evident. Although the studies often describe the parameters used for upscaling, it is unclear how these values are balanced against each other.

, papers are summarised with reference to the product level.

Table 3. Studies with reference building level (2).

GENERAL CONDITIONS
Year	Sector Background of Authors	Scope of Application	Region	Standards	System Boundaries (Modules)				Reference Study Period	LCA Background Data and Database	Functional Units and Their Equivalence	Reference
					A	B	C	D
2017	Construction	Residential buildings	Germany; Austria	EN 15978, EN 15804, EN ISO 14040, EN ISO 14044, ISO/TS 14071, (EN 16485)	✓ (A1–A3)	✓ (B2 + B4)	✓ (C3-C4)	-	50 years	Ökobaudat	✓	[22]
2020	Forestry	Mixed-use buildings	Portland, USA	EN 15978, PAS 2050, ISO 14067	✓	✓ (B2, B4, (B6))	✓	✓	60 years	Athena LCI Database, U.S. LCI Database	✓	[42]
2020	Forestry	Mixed-use buildings and parking garages	var.	var.	✓ (var.)	-	-	-	-	var.	-	[43]
2022	Construction	Non-residential buildings (office and administrative, agricultural, non-agricultural, other non-residential buildings)	Germany	EN 15978, EN 15804, EN ISO 14040, EN ISO 14044, ISO/TS 14071, (EN 16485)	✓	✓ (B2 + B4)	✓	-	50 years	Ökobaudat	✓	[21]
2018	Forestry	Mixed-use buildings	Ontario, Canada	-	-	-	-	-	-	-	-	[44]
2021	Construction	Building superstructures	UK	EN 15978	✓	✓ (B1)	✓	✓	50 years	Ecoinvent Database, Literature	✓	[45]
2020	Forestry	Residential buildings	South Africa	-	✓	-	-	-	-	Literature	-	[46]
2021	Construction	Building	Kronoberg County, Sweden	-	✓	-	✓	✓ (incl. in SP)	80 years	-	- *	[47]
2020	Construction	Mixed-use buildings	Europe	-	✓	-	-	-	-	-	-	[48]
2019	Construction	Residential buildings	Oslo, Norway	-	✓	✓	✓	✓ **	50 years	Literature	✓	[49]
2018	Construction	Residential and commercial buildings	Melbourne, Australia; London, UK	-	✓	-	-	-	-	Literature	-	[50]
2017	Construction	Residential buildings	Harbin City, China	-	✓	✓ (B6)	✓	✓ **	50 years	-	- *	[51]
2018	Construction	Residential buildings	Sydney, Australia	-	✓ (w/o A4)	✓ (w/o B1, B6, B7)	✓ (w/o C2)	-	50 years	ICE Database GaBi Database, eTool	✓	[52]
2019	Construction	Parking garages	USA	-	✓ (A1–A3)	-	-	-	-	ICE Database	-	[53]
2018	Construction and Forestry	Residential buildings	Germany	EN 15978, EN 15804, EN ISO 14040, EN ISO 14044, ISO/TS 14071, (EN 16485)	✓	✓	✓	✓ **	50 years	Ökobaudat	✓	[54]
2019	Construction (Forestry)	Residential buildings	UK	BS EN 15804	✓ (A1–A3)	-	-	-	100 years	EPDs	✓	[55]
2019	Forestry	Residential and non-residential buildings	China	-	✓ (A1–A3)	-	-	-	-	Literature	✓	[56]
OUTCOME
Definition of SP		SP		Substitution —Comparative Values		GHG Emission Reductions					Biogenic Carbon Storage	Reference
(GHGbuilding,mineral − GHGbuilding,timber) /(|GHGbuilding,minerals|) [kgCO2e/kgCO2e]		SFH/TFH 0.35–0.56 kgCO2e/m2 GEA MFH 0.09–0.48 kgCO2e/m2 GEA		Timber—mineral		SFH/TFH 77–207 kg CO2e/m2 35–56% MFH 18–178 kg CO2e/m2 9–48%					✓ (considered in an −1/+1 approach according to EN 15978 and EN 15804)	[22]
(GHGnon-wood − GHGwood) /(WUwood)		−1.68 tCO2e/tCO2e		CLT—mineral		3.51 × 106 kg CO2e (GHG emission) 70% (Embodied GHG emissions)					1.84 × 106 kgCO2e (stored in CLT building)	[42]
-		-		CLT—RC		216 kg CO2e/m2 of floor area 69%					var.	[43]
(GHGbuilding,mineral-GHGbuilding,timber) /(|GHGbuilding,minerals|) [kgCO2e/kgCO2e]		office and administrative buildings 0.06–0.48 kgCO2e/kgCO2e agricultural buildings 0.05–0.37 kgCO2e/kgCO2e non-agricultural buildings 0.14–0.44 kgCO2e/kgCO2e other non-residential buildings 0.13–0.46 kgCO2e/kgCO2e		Timber—mineral		Non-residential buildings 5–48% office and administrative buildings 17–177 kg CO2e/GEA 6–48% agricultural buildings 10–70 kg CO2e/GEA 5–37% non-agricultural buildings 10–170 kg CO2e/GEA 14–44% other non-residential buildings 37–133 kg CO2e/GEA 13–46%					✓ (considered in an −1/+1 approach according to EN 15978 and EN 15804)	[21]
(GHGnon-wood-GHGwood) /(WUwood-WUnon-wood)		ø 8.91 tCO2e/tC in HWP		HWP —non-wood construction materials		-					-	[44]
(GHGnon-wood-GHGwood) /(WUwood-WUnon-wood)		0.51 tC/tC 0.85 tC/tC		Timber—RC Timber—steel		Calculable from: timber 119 kgCO2e/m2; RC 185 kgCO2e/m2; steel 228 kgCO2e/m2					35.2 kg/m2	[45]
-		-		-		-					-	[46]
-		-		Timber or CLT—RC		-					-	[47]
-		-		-		-					1.84 kg CO2/kg wood; 23–310 CO2kg/m2	[48]
-		-		Timber-based —RC		Calculable from [49], Table 4 (Production), 6 (Operation), 7 (End-of-Life)					-	[49]
-		-		Timber —concrete		Calculable from 523.6 kgCO2e/m2 (concrete building) and 508.8 kgCO2e/m2 (timber building)					-	[50]
-		-		CLT—RC		13.2% Carbon emissions 9.9% energy consumption					0.08 tCO2/m3	[51]
-		-		Timber—brick		10% LCE					-	[52]
-		-		Timber—precast concrete resp. cellular steel resp. post-tension concrete		Calculable from [53], Tables 7 and 8					-	[53]
0.35–0.56 kgCO2e/m2 GEA (SFH/TFH) 0.09–0.48 kgCO2e/m2 GEA (MFH) (according to [22])		(GHGbuilding,mineral-GHGbuilding,timber)/(|GHGbuilding,minerals|) [kgCO2e/kgCO2e] (according to [22])		Timber—mineral		35–56% (SFH/TFH) 9–48% (MFH) (according to [22])					-	[54]
-		-		Timber frame —masonry CLT—RC		1.7–3.2 t CO2e 20% 12.8–18 t CO2e 60%					2.0–4.2 t CO2e 12.4–17.3 t CO2e	[55]
(GHGnon-wood-GHGwood) /(WUwood-WUnon-wood)		3.48 tC/tC		HWP —non-wood materials		s. [56], Table 1					1.84 kg CO2/kg HWP	[56]
SCALING EFFECTS
Scaling Level		Period/Date	Reference Scenario	Scenarios		Calculation Rules			GHG Emission Reductions		Biogenic Carbon Storage	Reference
From the building level to the building market		2020–2030	-	50% of new constructions are wooden buildings		Total global annual emissions reductions = 50% of annual demand for new buildings *** annual emission reduction			9% of annual emission reductions		-	[43]
From the product level to the harvesting market		100 years	(0) Baseline scenario	(1) Increased harvesting Production scenarios: (a) BAU (b) Lumber (c) Structural panel (d) Non-structural panel (e) Pulp and paper		GHGnet(t0 + t) = GHGHWP−inc(t0 + t) + ∆FC(t0 + t)			(a) 21 Mt CO2e (b) 93 Mt CO2e (c) 112 Mt CO2e (d) 66 Mt CO2e		(0) 1426 Mt C (1) 1373 Mt C	[44]
From the building level to the building market		-	-	Comprehensive switch to engineered timber systems (apartments and commercial buildings); maximum potential		-			1 MtCO2e/year 1.5% of emissions the construction sector can affect		-	[45]
From the building level to the building market		-	-	Percentage of residential wood-based buildings: (a) 10%, (b) 20% (c) 100%		Not evident ***			(a) 2.4% (b) 4.9% (c) 30%		-	[46]
From the building level to the harvesting market		201 years	(0) BAU	(a) Production scenario (b) Set-aside scenario		Not evident ***			s. [47], Figures 8, 10, 12, 14 and 16		-	[47]
From the building level to the buildings market		2020–2040	-	Percentage of wooden buildings: (a) 5%, (b) 10% (c) 45%, (d) 80%		Not evident ***			-		1–55 Mt CO2/year; 0.022–1.067 Gt CO2	[48]
From the building level to the building market		2015–2030	(0) REF	(a) ‘55/15′		s. [15,24]			0.8 Mt CO2e/year		(0) −0.96 Mt CO2/year (a) Δ −0.65 Mt CO2/year	[54]
From the building level to the building market		2050	(0) No growth (2018; refers to the level of timber construction activity)	Rates of house-building activity: (a) Low and (b) high levels of timber construction activity: (A) BAU (B) Moderate growth (C) High growth		Not evident ***			Residential buildings (a) [55], Table E6 (b) [55], Table E7 Non-residential buildings [55], Table E14		Residential buildings (a) [55], Table E6 (b) [55], Table E7 Non-residential buildings [55], Table E14	[55]
(1) From the product level to the consumption level (2) From the building level to the building market		(1) 2014 (2) 2015	(01) National HWP consumption of 2014 (02) Total gross floor area in 2015	(1a) +10% HWP + substitution of non-wood materials in construction and furniture production (1b) +10% HWP + substitution of non-wood construction materials (2a) 10% wood-frame construction of total gross floor area (2b) Additional HWP substitute GHG-intensive construction materials		Not evident ***			(1a) 18.76 Mt C (1b) 22.5 Mt C (2a) 8.11 Mt C (2b) 28.22 Mt C		-	[56]

* The study does not provide sufficient information to determine functional equivalence. ** Module D is calculated separately. *** The calculation rules are not evident. Although the studies often describe the parameters used for upscaling, it is unclear how these values are balanced against each other.

show papers with reference to the building level. Only papers for which a scaling effect has been calculated are included in Table 2 and Table 3.

3.1. General Conditions

The general conditions of each paper distinguish between the product level (Table 2 and Section 3.1.1) and the building level (Table 3 and Section 3.1.2).

3.1.1. Product Level

At the product level, the analysis includes eight studies. Seven papers focus on construction products, and one focuses on materials.

Sector Background of Authors: The analysis shows that five out of eight papers belong to the forestry sector, two to the construction sector, and one to both sectors.

Region: The SP as determined in the studies refers to different regions, which are listed below:

• Regional [41]
• National [35,36,37,38]
• Global [39,40]
• Not specified [23]

Standards: Of the studies, only [34] provides information on the standards (EN ISO 14040, EN ISO 14044, and EN ISO 14067). These standards refer to life cycle assessments (LCA) in general. Standards relevant to building products are not mentioned.

System Boundaries: The studies consider different modules of the life cycle for the system boundaries, as listed below:

• Module A [35,38,40,41]
• Modules A + C [36]
• Modules A + B + C [39]
• Variable [23]
• Reference to other literature [37]

Note that, in some of the studies, only selected modules of the life cycle are considered (see Table 2).

Reference Study Period: The SPs refer to different reference study periods. In [38], the reference study period is set at 100 years; in [40], it is at 80 years; and in all the other studies, this period is not specified [23,35,36,37,39,41].

LCA Background Data and Database: Most of the studies are based on data from the literature. In addition, [41] uses data from the LCA database Ecoinvent (LCA background database).

Functional Units and their Equivalence: The functional unit is different in all the studies. In addition, three studies [23,36,40] do not specify the functional unit at all.

3.1.2. Building Level

A total of 17 studies address the building level in their analysis.

Sector Background of Authors: At the building level, 11 out of 17 studies belong to the construction sector.

Scope of Application: At the reference building level, the scope of application includes residential and non-residential buildings. The buildings cover different numbers of storeys and types of use, including the following:

• Residential buildings [22,46,49,51,52,54,55]
• Parking garages [43,53]
• Office and administrative buildings [21]
• Agricultural buildings [21]
• Non-agricultural buildings [21]
• Other non-residential buildings [21]
• Mixed-use buildings [23,42,43,44,48,50]
• Others [45,47]

Region: The SP determined in the studies refer to different regions, as listed below:

• Regional [42,44,47,49,50,51,52]
• National [21,22,45,46,53,54,55,56]
• European [48]
• Global [43]

Standards: The standards considered in all the studies examined at the building level are listed below:

• EN ISO 14040 and EN ISO 14044 [21,22,54]
• EN ISO 14067 [42]
• CEN ISO/TS 14071 [21,22,54]
• BA PAS 2050 [42]
• EN 15978 [21,22,42,44,45]
• EN 15804 [21,22,54,55]
• EN 16485 [21,22,54]
• Not Specified [43,44,46,47,48,49,50,51,52,53,56]

The standards EN ISO 14040, EN ISO 14044, EN ISO 14067, CEN ISO/TS 14071, and BA PAS 2050 refer to LCA in general. The standards EN 15978 and EN 15804 refer specifically to environmental impacts in the construction sector and are only referenced together in three studies. Ten studies did not provide any information on the standards that were applied.

System Boundaries: The studies consider different modules of the life cycle according to ISO 21930 and EN 15978 for the system boundaries, which are listed below:

• Module A [43,46,48,50,53,55,56]
• Modules A + B + C [21,22,52]
• Modules A + C + D [47]
• Modules A + B + C + D [42,45,49,51,54]

It should be noted that some of the studies only consider selected modules of the life cycle stages (see Table 3). Ref. [44] does not provide information on the system boundaries.

Reference Study Period: At the building level (Table 3), the reference study period is between 50 [21,22,45,49,51,52,54], 60 [42], 80 [47], and 100 years [55]. Refs. [43,44,46,48,50,53,56] do not specify the reference study period.

LCA Background Data and Database: The sources of the data used for all the studies are listed below:

LCA-background database

• Ecoinvent Database
• (different versions) [45]
• GaBi Database [52]

LCA-inventory database

• EPD [55]
• eTool [52]
• Ökobaudat
• (different versions) [21,22,54]
• Athena LCI Database [42]
• U.S. LCI Database [42]

Others

• ICE Database [52,53]
• Literature [45,46,49,50]
• Not specified [43,44,47,48,51,56]

The main databases used were Ökobaudat (for Germany), the ICE (the Inventory of Carbon and Energy) Database (for the USA and Australia), and the literature data. In addition, data from Ecoinvent, the GaBi Database, Environmental Product Declarations (EPDs), eTool, the Athena LCI Database, and the US LCI Database were used. In some cases, several databases were used within one study (see [45,52]). Some studies do not provide information on the data used at all.

Functional Units and their Equivalence: At the building level, nine studies consider the functional equivalence and the remaining eight studies do not specify the functional equivalence.

3.2. Outcome

The analysis of the outcome indicators distinguishes between the product level (Table 2 (outcome) and Section 3.2.1) and the building level (Table 3 (outcome) and Section 3.2.2).

3.2.1. Product Level

Definition of Substitution Potential: The studies refer to different definitions of SP, and therefore the emission reductions refer to different quantities. The reference quantity is either mass or volume:

• tC/tC [23,35,37]
• Equal tCO₂/tCO₂ [36]
• tCO₂e/m³ wood [38]
• Not specified [39,40,41]

GHG Substitution Potential: SPs at the product level range from 0.46 tC/tC [35] to 1.85 tCO₂e/tCO₂e [36]. In addition, some studies do not determine SP or emission reductions at the product level but provide information on the scaling effects of emission reduction potential (cf. Scaling Effects).

Comparative Values of Substitution: The studies compare different materials used to determine the SP. At the product level, specific wood-based products were used to substitute alternative (non-wood-based) products, e.g., expanded polystyrene (EPS) for cellulose [41].

GHG Emission Reductions: Most of the studies do not provide information on GHG emission reductions at the product level. Only [41] indicates emission reductions of 2.19 kg CO₂e/m² and 8.4 kg CO₂e/m² of floor area.

Biogenic Carbon Storage: Information on biogenic carbon storage differs, both in terms of the reference unit and the level of the biogenic carbon storage. At the product level, [38,40,41] consider biogenic carbon storage, but only [36] and [38] provide a specific value, namely 0.9175 tCO₂/m³ and 1.04 tCO₂e/m³.

3.2.2. Building Level

Definition of Substitution Potential: The studies refer to different definitions of SP, and therefore the emission reductions refer to different quantities. The reference quantity is either mass or area:

• tC/tC [45,56]
• Equal tCO₂/tCO₂ [21,42]
• tCO₂e/tC [44]
• kgCO₂/m² GEA [21,22]
• Not specified [43,46,47,48,49,50,51,52,53,54,55]

GHG Substitution Potential: At the building level, the SP ranges from 0.05 kgCO₂e/kgCO₂e [21] to 8.91 tCO₂e/tC [44].

Comparative Values of Substitution: The studies determine the SP by comparing different materials. At the building level, the comparative values are as follows:

• Timber and mineral [21,22,42,47,54]
• Timber and brick resp. masonry [52,55]
• Timber and reinforced concrete (RC) [43,45,49,50,51,55]
• HWP and non-wood construction materials [44,56]
• Timber and steel [45]
• Not specified [46,48,53]

GHG Emission Reductions: At the building level, emission reductions are either related to the floor area and range from 10 kgCO₂e/m² gross external area (GEA) [21] to 216 kgCO₂e/m² of floor area [43], or to the whole building and range from 1.7 tCO₂e to 18 tCO₂e [55]. In addition, emission reductions are given as percentages, ranging from 5% [21] to 70% [42].

Biogenic Carbon Storage: At the building level, refs. [42,45,48,51,54,55,56] consider the biogenic carbon storage in different amounts. Refs. [21,22] show the biogenic carbon storage separately following the −1/+1 approach, so there is no influence on the SP.

3.3. Scaling Effects

The scaling effects refer to the product level (Table 2 and Section 3.3.1) and the building level (Table 3 and Section 3.3.2).

3.3.1. Product Level

Ref. [35] does not scale up results, so the paper is not included in the analysis of scaling effects.

Scaling Level: The papers refer to different base levels and upscaling levels:

• Product level to production level [36,38]
• Material level to production and consumption level [37]
• Product/building level to market level [23]
• Product level to building market [39,40]
• Product level to building level [41]

Period/Date: The scaling effects refer to different dates or time periods. Ref. [36] refers to estimated production in 2019, while the other papers refer to a point in time or a period in the future and are based on projections. Ref. [41] is an exception as it does not specify a point in time.

Reference Scenario: All the papers present a baseline or Business-As-Usual (BAU) scenario based on statistics from a given year in the recent past or the present. Only [38] references a zero scenario, where production for the reference year is zero.

Scenarios: The studies analyse different scenarios based on assumptions and projections. More information on the scenarios can be found in the Supplementary Information.

Calculation Rules: Refs. [23,37,40] do not provide sufficient information on the calculation rules. The parameters used for upscaling are described, but it is unclear how these values are offset against each other. Refs. [36,38] give the exact calculation rules.

GHG Emission Reductions: The information on GHG emission reductions is given according to the scenarios as percentage [37,40,41], annual [36,38] or absolute values [23,39,40].

Biogenic Carbon Storage: For biogenic carbon storage, [37] and [38] indicate the annual storage capacity and [40] indicates the absolute storage capacity over the period indicated. The remaining papers do not provide any information on biogenic carbon storage.

3.3.2. Building Level

Refs. [21,22,42,49,50,51,52,53] do not scale up, so they are not included in the following analysis of scaling effects.

Scaling Level: The papers refer to different base levels and upscaling levels:

• Building level to building market [43,45,46,48,54,55,56]
• Product level to harvesting market [44]
• Building level to harvesting market [47]
• Product level to consumption level [56]

Period/Date: The scaling effects refer to different time periods or dates in the future [43,44,47,48,54,55] or past [56]. Ref. [46] refers to the market shares of other countries.

Reference Scenario: The papers present a baseline or BAU scenario based on statistics from a given year in the recent past or the present. A baseline scenario is not provided in [43,45,46,48].

Scenarios: The studies analyse different scenarios based on assumptions and projections regarding the level of scaling. More information on the scenarios can be found in the Supplementary Information.

Calculation Rules: Refs. [43,44] calculate scaling effects according to predefined calculation rules. Refs. [46,47,48,55,56] do not provide sufficient information on the calculation rules. The parameters that are used for upscaling are described, but it is unclear how these values are offset against each other. Ref. [45] does not provide any information about the calculation rules.

GHG Emission Reductions: The information on GHG emission reductions is given according to the scenarios as percentage [43,45,46], annual [45,54] or absolute values [44,56]. Ref. [48] does not provide any information on GHG emission reductions.

Biogenic Carbon Storage: For biogenic carbon storage, [48,54] indicate the annual storage capacity, while [44,48] indicate the absolute storage capacity over the period indicated. Refs. [43,45,46] do not provide any information on biogenic carbon storage.

3.4. Summary of Findings

General Conditions: The studies were carried out in different contexts and therefore differ in terms of the product or building level, and they are created from the point of view of either forestry or the construction. The general conditions also differ in terms of the geographical and temporal context. Moreover, the requirements on which the underlying LCA is based (standards, system boundaries, data, functional units, and functional equivalence) are different. Therefore, conformity between studies is only given for individual indicators but not in general.

Outcome: The outcome-related indicators also differ in their definitions, the comparative values, and the values of GHG emission reductions and biogenic carbon storage so that the SP also varies. So, the results shown in the various studies cannot be compared.

Scaling Effects: Upscaling is performed for different scaling levels, time periods, and scenarios and determined according to different calculation rules. This results in different values for GHG emission reductions and biogenic carbon storage. The results of individual studies are not comparable, as the general conditions and the calculation rules vary broadly.

4. Discussion

Based on the results from Section 3.1, Section 3.2 and Section 3.3, the comparability of the studies is discussed in detail for the main indicators.

4.1. General Conditions

Sector Background of Authors: Studies with forestry background rarely ensure the necessary and normatively prescribed functional equivalence at the building level when making comparisons. Their authors appear to be less familiar with the building-relevant environmental standards EN 15978 and ISO 21931. An understanding of the importance of specific requirements of buildings does not seem to be given. However, this expertise is necessary to assess the use of wooden materials in the construction sector.

Region: The studies examined calculate SPs for 17 different regions. Different databases are used to calculate LCAs depending on the region. The data also vary due to regional differences in electricity generation, production standards, technologies, disposal systems, and transport distances. Likewise, the availability and quality of the data are location-dependent, and different standards (e.g., building codes) are used in different regions. The LCA results and, therefore, the SP are location dependent. This means that they will differ for the same material, depending on the region, as shown in [57].

Standards: Compliance with standardisation when determining SPs is essential. A standard-compliant calculation enables the correct and uniform presentation of results, which allows for comparing the results. The relevant standards at the building level (ISO 21931 and EN 15978), with life cycle and system limits defined within them, were only referenced by five studies. It is not clear whether standard-compliant calculations were performed in the other studies. However, the transparency of such information is necessary to enable comparison of these results. The below aspects of standardisation are particularly relevant.

System Boundaries: The SP value depends on the modules being considered. Considering isolated modules, as conducted in 11 of the studies examined, can lead to misleading statements as the amount of biogenic carbon is included (see indicator biogenic carbon storage in Section 4.2).

Additionally, Module D should be shown separately, as this module is outside the system boundaries according to EN 15978 and EN 15804 (as well as ISO 21930). Including Module D leads to an increased SP, as the biogenic carbon storage is accounted for a second time as a negative emission. This results in double counting, since the carbon benefit was already considered in Module A. Crediting the same carbon again at the end-of-life stage artificially enhances the overall climate performance of the product. For the interdisciplinary acceptance of studies on SP, an LCA, according to the introduced rules of ISO 21930 and EN 15978, should be conducted.

Reference Study Period: The length of the reference study period impacts the level of emissions, especially emissions from the use phase (Module B). Longer reference study periods result in higher emissions from use, maintenance, repair, replacement, and refurbishment (Modules B1-5), as well as from operational energy and water use (Modules B6-7). Different reference study periods therefore lead to differences in the level of emissions from building products and buildings, as shown in [58]. Therefore, the comparison of SPs with different reference study periods is not correct.

LCA Background Data and Database: The evaluation of the studies showed that the data had been sourced from various databases, EPDs, and the literature, with each utilising different versions of these sources. The values stored in databases can differ between different versions of the same database. In their study, Steubing et al. compared functionally equivalent datasets from two different versions of the same database. The median dataset deviation for GWP was found to be 13% [59]. Moreover, the calculations based on different LCA background data (such as Ecoinvent, Gabi, or no reference at all) yielded divergent results. Building-level differences can amount to around 15%, as demonstrated in [60]. As a result, there is no uniform data foundation, and different values are employed for emissions and carbon storage. These discrepancies in the data and its versions influence the outcomes, leading to varying results for the same building products.

Functional Units and their Equivalence: Functional equivalence is a basic requirement for calculating LCA and SPs according to the relevant standards. However, 11 of the studies examined did not take functional equivalence into account or did not provide sufficient information for verification. If functional equivalence is not given, SP is not comparable, as the equivalent exchange of products in buildings is not feasible.

4.2. Outcome and Scaling Effects

Definition of Substitution Potential: SPs are mostly not comparable due to different units and definitions, as well as the various general conditions. Before applying SP or comparing different SPs, the general conditions should be analysed for conformity. Therefore, an average SP calculated from the SPs of different studies should not be determined without a conformity check, as performed in [23] and [37]. Each SP may be consistent in its context, but the combination of different SPs from different studies requires a comparability check first.

Biogenic Carbon Storage: At the product system level, biogenic carbon storage has no impact on the SP in the full life cycle based on the −1/+1 approach presented in Section 2.2 ‘Biogenic Carbon Storage’. The potential benefits of increased carbon storage can only be calculated at the national level in accordance with the UNFCCC and associated IPCC calculation rules.

The level of the biogenic carbon storage capacity is relevant when only individual life cycle phases are considered to determine the SP. If only Module A is considered, the biogenic carbon storage is booked in as negative emissions without accounting for biogenic carbon storage retirement at the end of life (Module C), which leads to higher SP values, unlike when considering the entire life cycle.

In line with normative requirements, the effects of the carbon storage capacity shall be shown by reporting biogenic and fossil GWPs separately along the defined life cycle stages. In this way, the extent of the influence of the carbon storage capacity can also be seen when looking at individual modules and misinterpretations can be avoided. In Europe, this is taken into account in the current EN 15804 and EN 15978 standards, which separate the GWP indicator into GWP fossil, GWP biogenic, and GWP (LULUCF). Current EPD datasets, as provided for Germany in the database Ökobaudat [61], are already prepared in this way.

Scaling Level: Information on the scaling level should be linked in a transparent, consistent and comprehensible way. The lack of information on the calculation rules means that there is no transparent derivation of the results, and it remains unclear on what assumptions the calculation is based. Consequently, it is impossible to verify the results, including their validity, or to determine whether the calculation was carried out in accordance with the appropriate standards. Therefore, it is also not possible to compare upscaling in cases where information is missing.

Additionally, upscaling should be carried out in relation to a baseline scenario to show the potential emissions reductions compared to a reference scenario. The baseline scenario should be clearly defined and represent the current state, e.g., the building market, etc.

An analysis of different scenarios is performed to assess future market developments. These scenarios should reflect forecasts and be based on scientific statistics. To consistently map the impact of wood use on biogenic CO₂ emissions and their removal in sinks at the landscape level, it is necessary to prepare the information available at the building level accordingly for its consistent use with methods suitable for estimating such biogenic carbon effects.

In general, only if all relevant general conditions of the studies are identical can their outcomes be compared. Furthermore, a transparent and comprehensible allocation of SPs must be ensured to avoid the double counting of SPs. If the advantages of wood use are to be extrapolated onto the whole construction sector, the scaling effects must be justified through reliable functional equivalence.

4.3. Potential Limitations of the Study

A comprehensive literature search was conducted primarily via ResearchGate and Google Scholar. However, these platforms have inherent limitations and may not have captured all relevant studies. Nevertheless, analysing 25 studies provides insight into discrepancies in SP calculation and highlights the challenge of ensuring SP comparability in meta-analytic studies.

5. Conclusions

The evaluation has shown that the studies arrive at different results and subsequent scaling effects because the general conditions in the beginning are not comparable. In many cases, the calculations are not presented transparently. Therefore, a direct comparison of these SPs is not advised. A transparent and comprehensible allocation of SPs has to be ensured. Firstly, the underlying product LCA must be comparable. In Europe, the EN 15978 and EN 15804 series of standards, and globally the ISO 21930 and ISO 21931 standards, provide a clear specification for a comparable life cycle presentation for buildings. In general, scientific studies on this topic should follow the established standards applied in the construction sector (such as the ISO 21930 series or EN 15978) to develop policy relevance.

This means that, to assess possible scaling effects of wood use, which is relevant in a policy context, it is essential that the studies and SPs on which they are based are determined according to standardised rules. Additionally, the building level, as the place of use for these products, is not neglectable. This is especially true when scaling up the effects of increased wood use to the landscape level. To use SP, the indicators described in Section 2 should be clearly defined and implemented. Only in this way does using SP at the product level provide reliable results for a broader context. The studies also show that changes in forest management have not been taken into account.

The LCA method for assessing the environmental impact of buildings was not made for performing an evaluation at the landscape or country level. The method (in accordance with EN 15978 and EN 15804) does not refer to a specific point in time. Although the results refer to a declared lifespan, they do not relate to a particular moment in time. Consequently, no time-specific factors (e.g., forest development) and no changes within the defined period are taken into account. Therefore, using only an LCA cannot plausibly quantify and map the complex inter-relationships of the biogenic carbon cycle along the forestry and timber chain relevant for wooden building products at the landscape or national level. The quantification of these climate relevant effects is carried out via various calculation methods at different scales with mostly different system boundaries and temporally and spatially divergent dimensions. For example, national aspects are covered by methods provided by the IPCC. At the same time, the non-biogenic GHG emissions of the wooden building products, as part of the buildings’ upfront GHG emissions, cannot be determined with methods provided by the IPCC. Here, specific LCA methods designed for the construction sector should be used.

As a consequence, several sources of data, in addition to LCA results, must be consistently combined to allow for a comprehensive assessment of the overall impact of wood use in buildings (including its impact on forests) at various scales [13].