Embodied impacts of residential stocks; multi-level assessment of materials, buildings, typologies and functional units to support policymaking towards sustainable housing

The rapid urbanization of the last centuries increased the rate of infrastructure development all around the world, thus making the construction industry one of the fastest developing sectors globally (Govindan et al., 2016). The most widely used material of the sector, concrete, is, after water, the second most consumed product by mankind (Regúlez et al., 2023). Consequently, the construction sector is one of the largest emitters of greenhouse gases (GHGs), accounting for approximately 37% of global GHG emissions (United Nations Environment Programme, 2023), as well as for 16.7% of the world’s freshwater withdrawals and one-quarter of harvested wood (Sandanayake, 2022). Amongst the several subsectors of the construction sector, the building sector is responsible for approximately 16% of the global GHG emissions, while residential buildings (housing sector) are responsible for 64% of those (Shobhakar et al., 2023). It is therefore essential to optimize the way the future housing stock is designed and developed to ensure alignment with environmental and social goals.

The environmental impacts of buildings are typically divided into two primary categories: embodied impacts and operational impacts. Operational impacts involve the energy and water used during a building’s lifetime, gradually accumulating throughout its use phase. In contrast, embodied impacts encompass the environmental effects associated with the infrastructure requirements and the processes of manufacturing, transporting, assembling, maintaining and eventually disposing of building components. Historically, research has mainly concentrated on minimizing operational impacts by promoting energy-efficient designs and improving insulation materials (Zhou et al., 2023). Recently, there has been growing focus on reducing embodied impacts, driven by concerns over resource scarcity and the ongoing shift toward decarbonizing electricity. As operational impacts decline due to cleaner energy sources, embodied impacts are expected to become the dominant contributor to a building’s total life cycle impacts (Fnais et al., 2022; Goldstein and Rasmussen, 2018; Rodrigues et al., 2024).

The assessment and optimization of buildings towards a more sustainable sector is currently happening at several different levels. Life cycle assessment (LCA) is the most popular methodology, described in ISO 14040 and ISO 14044 (International Standards Organization, 2006a, b), and widely used in academia and industry. Most of the LCA studies are performed at the component level (e.g. insulation material, wall curtain component, etc.), while building design assessments towards both energy efficiency and embodied impact reduction are also areas of current research focus (Hu, 2019). The component-level studies usually evaluate and compare the environmental performance of different building components, suggesting or discouraging their use. At the building level, integrated building information modelling (BIM)-LCA frameworks are popular, assisting designers in achieving embodied impact reductions from the early-design stages (Röck et al., 2018), while integrated energy modelling-LCA frameworks pursue operational impact reductions (Tushar et al., 2021).

While both approaches (component and building level) provide useful insights regarding which materials, systems, or design characteristics contribute the most to a building’s impacts, their results cannot be directly utilized by those seeking to reduce the impacts of housing in general at a broader scale. This is due to the goal of these studies being the increased relative performance of the under-study subject itself, rather than the performance of the wider system that includes it. This being the urban environment, studies have been exploring ways to quantify, assess and limit the environmental impacts of the built environment at the urban scale (Papageorgiou et al., 2024). Such LCAs are less popular and poorly standardized (Albertí et al., 2019) and aim at mapping impacts and identifying ways to reduce them at the urban level, where a (more) sustainable built environment at the city, region or country is the objective rather than a building or a building component. The LCA results of such studies are characterized by methodological non-homogeneity, with various functional units, system boundaries and assumptions being adapted accordingly. This is mainly due to the far more complicated and wide scopes needed for such studies, while recent literature supports that a standardized framework should be introduced, and propositions have been made with regards to defining assessment aspects (Albertí et al., 2019).

With regard to functional unit selection, the component-level studies adopt functional units that reflect the product’s functionality (per surface, mass, volume or item), while building-level studies usually use gross floor area (GFA) (de Simone Souza et al., 2021). On the other hand, urban-level studies adopt occupancy-centric and population-equivalent metrics (González-García et al., 2021; Mirabella et al., 2019). The different functional unit selections across levels of assessment highlight the distinct functions that these assessment approaches prioritize, as well as their significantly diverse scopes and goals. Component-level studies seek comparative results with similar-functionality products (e.g. cladding materials) and therefore adopt functional units that allow such comparisons. At the building level, the buildings’ ability to provide space is prioritized, and therefore buildings are being compared according to this (per m²). Finally, at the urban level, residential stocks are being assessed for their function to efficiently provide shelter to the city’s population, and therefore occupancy-oriented metrics are adopted. The aforementioned variation in scope and functional unit selection across studies has several negative implications for addressing the environmental impacts of housing. First, the transferability and comparability of results between studies is limited, reducing their value for effective policymaking. While component- and building-level LCAs have already been standardized to improve sector integration and comparability, discussions on standardizing urban-level LCAs have only begun recently (Albertí et al., 2019). Second, the variation in functional unit selection can lead to contradictory results. For instance, evaluating buildings solely on their environmental performance per GFA can be misleading, as it overlooks their shelter-provision function. This may encourage designs with larger floor areas, which, over the long term, translate into higher cumulative impacts per occupant through increased space and resource consumption (Christoforatos et al., 2025).

Sustainability and regionality are interchangeably linked, as the effectiveness of sustainable strategies generally depends on the specific socio-ecological, cultural and economic context of the region (Mishra et al., 2021). For instance, literature on regional products and sustainability has demonstrated that local production systems—by emphasizing shorter supply chains and supporting regional economies—can significantly reduce environmental footprints while fostering cultural and economic resilience (Haid et al., 2024), while it is suggested that locally tailored measures are critical to ensure that policy interventions are not only technically feasible but also socially acceptable and economically viable (Foroudi et al., 2024). In the context of buildings, regionality is crucial because large-scale construction projects can hide significant environmental burdens in unexpected life cycle stages. While designers often focus on the material selection and energy efficiency to lower buildings’ impacts, secondary and often overlooked life cycle modules, such as module A4 (transport of building materials to the construction site), can contribute substantially to a building’s overall environmental footprint. Research (Greer and Horvath, 2025) has shown that for some under-study materials, A4 was responsible for up to 80% of the upfront embodied impacts (A1-A5), underscoring the potential intensity of transportation impacts in some instances and their underestimated importance. A study in Iceland (Emami et al., 2016) performed LCA at a school building and examined how domestically produced building materials compare with imported ones. Due to the remoteness of the country, some imported materials were characterized with up to 31% more impacts in some impact categories, thus highlighting that in some contexts, importing materials and their transportation impacts can be of great importance.

Recently, prospective LCA (pLCA) has been emerging as a necessary methodology to support decision-making towards environmental impact mitigation by allowing impact evaluations at future points, according to different socioeconomic and technological projections (Bruhn et al., 2023). The significance of pLCA, and generally time-dependent environmental analysis, is considered paramount for informed decision-making and policymaking—particularly for long-lifespan, impact-intensive systems like buildings—ensuring that choices made today are guided by the best available projections about future conditions, technologies and environmental constraints (Fnais et al., 2022). A study, for example, examined different retrofit scenarios for existing buildings according to projected climate data and found that roof and window parameters become less significant in future climate scenarios (Rodrigues et al., 2024), while others compared construction materials to identify their future potential according to technological advancement scenarios (Horup et al., 2025). Another study performed a temporally dynamic analysis of a building stock and found that while decarbonization of electricity is expected to deliver notable impact reductions, the demand for more buildings and renovations post-2040 is expected to result in large upcoming impacts (Ohms et al., 2024). The study suggested that decision-making should not rely on technological development solely while supporting that time-dependent insights can support effective policymaking.

Despite significant advancements in the application of LCA across different scales in the built environment, a major gap persists in the literature regarding the development of an integrated framework capable of guiding policymaking towards achieving impact reductions. Existing studies focus on either materials, components, individual buildings, or broader urban environments, which are dealt as black boxes, without adequately linking these levels within a cohesive, region-specific assessment framework. Moreover, there is a notable absence of comparative analysis between building typologies themselves. Considering those as urban residential development options and mapping their comparative impacts is essential for strategically designing future residential stocks towards sustainable housing. Furthermore, the main materials used in the sector (e.g. timber, concrete, etc.) and their impact contribution, as well as their comparative performance with alternatives, have been examined thoroughly in literature, while the contribution of secondary materials remains limited. These observations indicate that current sustainability research in the built environment does not orient itself towards optimizing the way we inhabit buildings but rather optimizing the building products (building materials, building designs, etc.) that are already available or traditionally established.

This study aims at addressing this gap by introducing a comprehensive, multi-level assessment approach that simultaneously considers materials, buildings, typologies and functional units within a specific regional context. By examining how these aspects contribute to the embodied environmental performance of the residential stock—using New Zealand as a case study—this research is expected to provide deeper, actionable insights that can be directly translated into robust policymaking recommendations.

The proposed framework is illustrated in Figure 1. It begins with the selection of a representative building stock within the under-study context. The stock’s BIM models are collected and assessed through a multi-level LCA, which evaluates different aspects of the stock across multiple functional units. Finally, the results are analysed, and the generated insights are translated into guidance for policymakers to support the optimization of the stock’s overall performance.

The presented work follows a bottom-up approach, examining 16 case-study buildings designed for the context of Auckland, New Zealand. The BIM models for 14 of those were collected from Building Research Association of New Zealand as well as a study (Ganda, 2019) (licensed under CC BY-NC 4.0) which explored different townhouse designs for the context of New Zealand, while for the remaining two, only the bills of quantities were obtained (more information in supplementary material SM1). The buildings are named according to their type (A for apartment, T for townhouses, double-storey detached building (DD) for double-storey detached and single-storey detached (SD)) and numbered according to their occupational load factor (OLF) in a descending manner for each typology (Figure 2a). OLF is a building design characteristic that is mainly used in building risk assessment (De Sanctis et al., 2014; Wong, 2003) and derives from Equation (1). Finally, Figure 2b shows the percentage share of consented residential GFA, across typologies, in New Zealand for the 2018Q2–2024Q2 period (Interest.co.nz, 2024), alongside the percentage share of the representative stock examined in the study. The close alignment between the GFA of the representative stock and the national consented stock strengthens the reliability of the study’s findings while ensuring that the insights derived are applicable to the regional context under examination. Each building’s characteristics can be found in Table 1.

Data preprocessing took place before the LCA to make sure that each building is characterized by the same level of accuracy; materials that were present only in specific buildings, such as landscaping materials (e.g. granular fill) were excluded from the BoQs. Typology-specific materials and elements (e.g. elevators for apartment buildings) were included in the assessment due to them being essential for each typology. Finally, material tags were assigned to each BoQ element. More information about the assigned material tags can be found in supplementary material SM2.

The LCA methodology was carried out in this study according to ISO 14040 and ISO 14044 (International Standards Organization, 2006a, b). These describe the methodology’s four main steps: the goal and scope definition, the life cycle inventory (LCI) analysis, the life cycle impact assessment (LCIA) and the interpretation of the results. LCAQuickv3.6 (Building Research Association of New Zealand, 2016) was used for the impact assessment.

The goal of the LCA study is to quantify the environmental impacts of New Zealand’s representative residential stock and identify areas where impact reductions can be achieved. The scope of the study is limited to the context of New Zealand and specifically to the city of Auckland. The study’s scope considers the impact categories of Global Warming Potential (GWP with a unit of kgCO₂eq), Eutrophication Potential (EP with a unit of kgPO₄^3-eq), Ozone Depletion Potential (ODP with a unit of kgCFC-11eq) and Acidification Potential (AP with a unit of kgSO₂eq). Multiple impact categories were considered to ensure that the study’s output is not prone to potential trade-offs among the impact categories (Petit-Boix et al., 2017; Seyedabadi and Eicker, 2023). GWP is the most examined impact category in sustainability literature (Anand and Amor, 2017), while the rest are among those included in EN15804+A2 (European Committee for Standardization (CEN), 2019). Modules A1–A5 (upfront impacts), B2, B4 and C1–C4 (end-of-life impacts) are included in the scope of the study (Figure 3). Two separate functional units were employed: GFA and number of occupants. Finally, the lifespan of the buildings was considered the same (50 years according to New Zealand’s building code regulations (New Zealand Government, 1992)).

For the second step of the LCA, the LCI development, the BoQs of the case-study buildings were obtained from the BIM models and inserted as inputs into LCAQuickv3.6. The impact assessment was performed next by calculating each module with the corresponding environmental product declaration (EPD) from LCAQuick’s database. Modules A1–A2–A3 are provided directly by the EPDs, while modules A4, A5, B2, B4 and C1–C4 were calculated according to BRANZ’s standards (Building Research Association of New Zealand, n.d.).

To assess each material’s contribution across all impact categories, a CIS is used. Scores such as the one presented in this study are popular in literature, aiming at evaluating a system’s performance across several criteria. Literature applications with regard to composite scores for LCA results can currently be found mostly in the research field of agricultural systems (Gómez-Limón et al., 2020; Sabiha et al., 2016), probably due to the complexity of those systems and their diverse effects across several impact categories. In the building research field, there was not a study found that introduced or used such indicator; this may be due to most studies reporting environmental impacts of buildings with regard to GWP and excluding secondary impact categories (Seyedabadi and Eicker, 2023), as mentioned in 2.2.

In this study, the weighted sum method (WSM) is applied (Marler and Arora, 2010). For each material the relative contribution according to the rest of the materials’ contribution was calculated using min-max normalization (Gómez-Limón et al., 2020) (Equation (3)), where i are the several materials (alternatives) and j the several impact categories (criteria). The method of min-max normalization assigns a dimensionless value (between 0 and 1) across the alternatives for each criterion. Then, Equation (4) is used to calculate the CIS, where w_j is the assigned weight for each criterion (equal weighting was used).

Figure 4 shows the LCA results for the 16 buildings across the 4 impact categories. Each column represents the impact contribution (per GFA) per material for each building, while the red scattered points represent the corresponding total impacts per occupant on the secondary axis. Buildings A1 and A2 had almost identical impacts per GFA (Figure 4a, b, c, and d) due to the building’s BIM model being identical (same materials and design as in SM1), with the only difference being that A1 is more compact (same number of occupants but less GFA as in Table 1). Apartment buildings (A1 and A2) had generally the largest emissions across all impact categories, with percentage differences ranging from 291.14% (comparing A2 to SD2 for AP, Figure 4d) to 16.59% (comparing A2 to DD1 in EP, Figure 4b). On the other hand, SD2 had by far the best performance across all impact categories and the two functional units. This is due to SD2 being characterized by low emissions per GFA while also having a high OLF (5th higher OLF after A1, A2, T1 and DD1 as in Table 1). While a detailed analysis of design contributions is beyond the scope of this study, it is evident that the low impacts per GFA observed in SD2 can be largely attributed to the minimal concrete used in its construction, mainly due to the use of a pile foundation system. However, not all buildings with pile foundations showed similarly low impacts—DD1, for example, performed worse due to other impact-intensive material choices, such as extensive use of plastics. With regard to material contribution, it can be observed that steel, concrete (with and without reinforcement) and timber were the most dominant across all impact categories, while plastics had a significant contribution in EP. Plastics’ contribution to EP is mainly due to high end-of-life impacts (C1-C4 in Figure 3) of plastics such as membranes (used mainly in foundation systems) and PVC-U window frames (used in DD1). Furthermore, T1, T2 and T3 were characterized by relatively high aluminium impacts, probably due to the high window-to-wall ratio that these buildings adopted. Additionally, T1, T2, T3 and DD1 had high timber impacts across the several impact categories due to extensive use of engineered timber products (such as laminated veneer lumber and cross-laminated timber, see SM1). The structural requirements for the rest of the complex buildings that did not use timber (A1, A2 and T4) were satisfied by using steel and reinforced concrete, which also resulted in high impacts per GFA. Finally, the material category Others had relatively high impacts, especially for apartment buildings, mainly due to the high embodied impacts associated with the elevator systems that these buildings were equipped with (see SM1).

The findings on functional unit selection are consistent with concerns raised in the literature (de Simone Souza et al., 2021), as notable variations in results were observed depending on the chosen functional unit. Figure 3 shows that although apartment buildings have by far the highest impacts per GFA across all impact categories, these differences are significantly reduced—and in some cases even reversed—when the impacts are calculated per occupant instead. For example, the difference of 211% between A2 and SD2 in GWP (Figure 4a) is reduced to 124%. Shifts in relative differences can also be found, such as in Figure 4a, where T3, DD4 and SD6 had percentage differences of GWP per GFA of −27.72%, −48.69% and −37.14% compared to A2, which became 12.22%, 12.96 and 20.90% when occupancy was used as a functional unit. The same is observed in the rest of the impact categories (Figure 4b, c, and d), especially for buildings with low OLFs (T3, T4, DD3, DD4, SD5, SD6), where the shifts of impacts according to the two functional units are significant and often surpass the impacts per occupant of A1 and A2. Furthermore, significant differences in performance within the same typology are observed; for example, DD1 is characterized by more impacts per GFA across all impact categories compared to DD4, while DD4 surpasses it in impacts per occupancy across all categories and even in EP (Figure 4b), where DD1 was the 3rd most impact-intensive building per GFA, after A1 and A2.

Figure 5 shows the average impacts per GFA and occupant for each typology. DDs were found to be the less impact intensive across 3 out of 4 impact categories (GWP, ODP, AP), followed by SD. In the impact category of EP (Figure 5b), DD had 39.5% more impacts compared to SD due to heavily using plastics as mentioned in 3.1. Apartment buildings (A) were characterized by 147.3–68.1% more impacts on average when compared to DD. Townhouses (T) were generally the second most impact-intensive typology, only surpassed by DD in the impact category of EP. Timber impact contribution was generally consistent among T, DD and SD, varying from 38.9% of the total GWP impacts for T (Figure 5a) to 13.2% of the total AP for SD (Figure 5d). Steel contributed the most for apartments, with its contribution ranging from 68.7% of the total impacts in EP to 43.2% in ODP. Furthermore, when occupancy was considered as a functional unit, the average percentage differences of impacts per GFA between apartments and the best-performing typologies for each impact category changed from 99.3%, 134.5%, 99.7% and 147.3%–11%, 37.2%, 11% and 38.5% for GWP, EP, ODP and AP, respectively. Finally, DD surpassed apartments in average EP per occupant: apartments had 68.1% more impacts per GFA and 3% less impacts per occupant compared to double-storey detached.

Figure 6 shows the overall impacts for the representative stock and the material contribution. Timber and steel were the most impact-intensive materials across the four impact categories, followed by concrete, due to extensive use. Plastics had a significant contribution in EP, as demonstrated in Figure 5b above. Beyond the main structural materials and plastics, the use of paint contributed 2.52–6.69% across the impact categories, while the use of bricks contributed 2.30–8.96%. Both bricks and paint had their highest percentage share contributions in ODP. Aluminium, structural insulated panels (SIP), glass and concrete also had disproportionally large contributions in ODP with percentage shares of 10.34%, 4.82%, 7.98% and 20.27%, respectively, in comparison to the other impact categories where these materials had significantly less shares. The use of steel had a significantly low contribution in this category (5.80%). This indicates the non-homogeneity of LCA results across impact categories with regard to material contribution and the importance of comprehensive assessments that include several impact categories to identify and limit the potential trade-offs.

Figure 7 presents the overall impact contribution of materials across the four impact categories for the representative building stock. Equation (4) was used with equal weighting to determine the Composite Index Scores (CISs) in order to identify which materials contribute the most for the considered impact categories. Timber, steel and concrete combined contributed more than 50% of the total impacts. When plastics and reinforced concrete are added, the contribution exceeds 70%. The contribution of plastics and paint is also noticeable, especially considering the secondary role that these materials have and the minor amounts of these used (in terms of mass).

Figure 8 shows the life cycle stage contribution for each typology across the four impact categories. Apartment buildings and townhouses had the most upfront impacts (A1-A5), while the overall stock’s life cycle stage impacts were closer to the levels of SD and DD due to them dominating the stock’s GFA (as in Figure 2). The high upfront impacts of the two complex typologies are probably a result of structural stability requirements and the use of steel and reinforced concrete. The stock’s upfront impacts were in the range of 63.27–74.52%, which confirms the concerns in the literature regarding buildings requiring significant upfront impact investments (Reyna and Chester, 2015) and their importance towards climate change mitigation (Röck et al., 2020).

Figure 9 shows the average life cycle stage impact contribution for each material across the four impact categories. The values represent the overall life cycle stage contribution for each material using Equation (5), where i refers to each impact category (GWP, EP, etc.), s to each life cycle stage (A1-A3, etc.) and M to each material. The analytical life cycle stage contribution for each material and each impact category can be found in SM3.

Timber, bricks, fibre cement and plasterboard were characterized with significant A4-A5 impacts which correspond to the transportation of these materials (probably from overseas) alongside the waste generated during construction. Furthermore, the dominant B modules’ contribution for paint, glass, steel, plastic and others refers to numerous replacements during the building’s life cycle. These modules refer to 10.85–18.70% of the stock’s impacts across the four impact categories (Figure 8) and should not be considered negligible. Finally, paint, plastics, plasterboard, concrete and timber had the highest C1-C4 module contributions due to the waste generation and management associated with those materials’ end-of-life.

Based on the analysis of embodied impacts across the representative sample of New Zealand’s residential building stock, several key recommendations emerge. At the building level, specific design choices, such as SD2, demonstrated significantly lower impacts per GFA; SD2 used a pile foundation system which contributed to its lower impacts by minimizing concrete use, while other houses which used the same system (DD1 and SD6) indeed had lower impacts with regard to the particular system (foundation), but overall had average to bad performance due to other material choices (e.g. excessive plastic usage from DD1). Given New Zealand’s established market for pile foundation systems, alongside the emerging market for concrete-free foundation systems, further research is recommended to assess their potential adoption from the sector, as this area remains largely unexplored and could potentially lead to great impact reductions.

Furthermore, a critical insight from this study is the substantial variation in results depending on the functional unit used. While current international and national building sustainability certification schemes (e.g. LEED (U.S. Green Building Council, 2023), Homestar (New Zealand Green Building Council, n.d.) and more) focus on energy efficiency and embodied impacts per GFA, this overlooks the sector’s core purpose: accommodating people. Policies should incorporate the OLF to ensure that resource allocation and environmental impacts are also evaluated per occupant, not just per area, thereby avoiding the risk of favouring convenience over sustainability. Considering the essential need for absolute impact reductions (Andersen et al., 2024), which are directly associated with population growth, it is of great significance for those regimes to ensure that future housing will consist of buildings that are not only efficient in a relative basis but also in an absolute sense. The study’s findings suggest that the usage of buildings such as DD4, which may have appropriate efficiency per GFA but much worse efficiency per occupant due to extremely low OLFs, should be regulated by policies to ensure that absolute impacts do not increase, accumulatively, in the long term. This can be achieved by including the OLF as a building design characteristic into the provided guidelines for building LCA (Ministry of Business Innovation and Employment, 2020) and defining OLF limits according to the building’s location. This recommendation aligns with recent research (Hvid Horup et al., 2024) and European guidelines (European Environment Agency, 2022) that mention the necessity for reducing the building sector’s impact by limiting the consented and produced GFA, which can be achieved by controlling the OLF. Importantly, policymaking should include socioeconomic factors in defining OLFs to ensure that higher density is established properly across neighbourhoods to ensure social sustainability, rather than making each neighbourhood equally denser. It is well-known that lower socioeconomic regions are associated with higher density (Dempsey et al., 2012), which already affects the occupants’ wellbeing.

Typology-specific findings require careful consideration. While higher-density housing types—such as apartments and townhouses—are often promoted for their efficiency in terms of energy use (Ahmadian et al., 2021; Trepci et al., 2020), land utilization and transportation benefits (Norman et al., 2006), they also demonstrate significantly higher embodied environmental impacts per GFA, particularly in the form of upfront emissions. Although these impacts often appear more favourable when assessed per occupant (as in Figure 4 and Norman et al. (2006)), this shift is not inherently tied to building typology and should not be interpreted as a definitive environmental advantage of those typologies. Consequently, policymakers and future research must critically assess whether current high-density housing typologies truly align with long-term environmental sustainability goals, or if alternative approaches—such as increasing the density of detached housing or adopting novel typologies—may offer a more effective balance between density and sustainability. Recent literature supports this line of thinking. For instance, Papageorgiou et al. (2024) through prospective LCA, found that reducing the use of materials—especially steel—in construction had a much greater potential to lower environmental impacts than improving recyclability. Similarly, Çimen (2021) highlights that reducing resource consumption could yield meaningful impact reductions, often requiring less effort and lower economic costs than more complex circular strategies. Given these insights, there is a pressing need to re-evaluate the environmental efficiency of apartment buildings, particularly within the specific geographical context of this study. A promising path forward may lie in the densification of simpler, low-rise typologies, which could provide a better trade-off between land use efficiency and embodied impact intensity. This consideration is also crucial given the urgency of climate action. If the current trend of increasing apartment and townhouse consents continues, as recent national data suggest (Interest.co.nz, 2024), many new developments may lock in high levels of embodied carbon before future innovations—such as low-emission structural materials—become widely available. To address this, future research should integrate the proposed multi-level assessment approach with prospective modelling that includes temporally dynamic parameters, as research has suggested (Ohms et al., 2024), to identify optimal housing development scenarios.

Additionally, the material-level analysis revealed that secondary materials—such as paints and plastics—as well as typology-specific systems like elevators in apartment buildings, contributed significantly across all impact categories. These elements are often overlooked in sustainability assessments, likely due to the assumption that their contributions are negligible. However, the findings of this study challenge that assumption, especially as materials like plastics were found to contribute disproportionately to certain categories, notably eutrophication. This underscores several important implications. First, adopting narrow scopes or omitting impact categories in life cycle assessments (LCAs) of complex systems like buildings can result in misleading conclusions (Seyedabadi and Eicker, 2023), as mentioned in 3.3. Second, the results suggest that optimizing the building stock as an integrated whole—rather than focusing exclusively on primary structural systems—may yield greater environmental benefits. For example, reducing the impact of common secondary materials (e.g. developing low-impact paints or plastics) may require significantly less time, investment and technological development compared to innovations like low-carbon concrete and steel, yet offer considerable impact reductions. These low-barrier interventions are also more likely to be adopted quickly by the construction sector. Beyond secondary materials, the results emphasized the importance of identifying and analysing hidden impacts—such as elevator systems in multi-storey buildings—which may otherwise remain undetected in standard assessments.

Finally, the life cycle stage analysis highlighted the significant impacts associated with engineered wood, bricks, fibre cement and plasterboard for the life cycle stages A4–A5 (Figure 9), underscoring the potential and importance of localizing processing (or prioritizing locally produced materials) and reducing construction waste. While the development of innovative, sustainable materials is essential for future housing, it is also important to consider where and how these materials are produced, as well as how they are installed. Policymakers should incorporate these factors into strategic guidelines for impact reduction to ensure optimal results in the sector.

The presented work challenges the current orientation of sustainability frameworks, which may be insufficient for achieving absolute impact reductions due to their fragmented approach and ineffective perspective. The findings indicate that treating “housing” as a holistic entity for environmental impact optimization offers a more effective pathway toward sustainability. Several impact hotspots—opportunities for reductions—were identified through the proposed multi-level approach, which would have been overlooked by conventional single-level assessments. As environmental pressures rise from anthropogenic pollution approaching—or already exceeding—the planet’s boundaries, it is crucial for researchers, policymakers and industry stakeholders to prioritize holistic, impactful changes in how we inhabit houses and consume resources. Fundamentally, a shift in perspective is needed: from optimizing relative consumption based on past patterns to optimizing total consumption according to human needs and within the planet’s environmental limits. Therefore, a more macroscopic perspective, coupled with effective policymaking, is essential to ensure that products are strategically designed and developed to minimize absolute impacts.

Future research should explore pathways toward sustainability that go beyond the selection of materials or individual buildings. This requires a broader scope—regional or national—where scenario-based assessments identify the most critical stock parameters (e.g. occupancy density, typology, material choice, building design) and determine the most effective pathways for sustainable housing development. To achieve this, integrating housing demand projections, prospective LCAs and absolute sustainability assessments is crucial. Such an approach would allow policymakers and researchers to anticipate future housing needs, assess the local environmental impact budget and identify optimal housing development scenarios. Ultimately, this could ensure the provision of the highest quality of living for residents while maintaining adherence to essential environmental boundaries. Finally, it is important for future research to address the practical implications of translating results into real-world applications and impacts. The gap between research and policymaking has been a major factor limiting progress toward global environmental goals. Therefore, it is important to develop effective bridges that connect research outcomes with governance adaptability, enabling informed decision-making to shape the future of housing.

A primary limitation of this study refers to sample size and extrapolation. The research was based on 16 case studies representing the residential building stock, following a bottom-up approach. Although bottom-up methods for mapping residential stocks are widely accepted in the literature and often preferred over top-down approaches for their ability to capture material- and building-level details (Seyedabadi and Eicker, 2023), they present challenges regarding the representativeness of the sample (Brøgger and Wittchen, 2018). The same applies for the typology analysis, where results were drawn for each typology based on the samples. Nonetheless, it is essential to highlight that all buildings analysed were developed for the context of Auckland, New Zealand, over the past six years, and therefore their representativeness can be considered sufficient for the study’s findings to be valid. A further limitation is the exclusion of modules B3 (repair), B5 (refurbishment) and D (potential benefits after end-of-life). B3 and B5 were omitted due to data unavailability in LCAquick, while Module D was excluded due to concerns regarding its methodological limitations (Delem and Wastiels, 2019) and its speculative nature. The exclusion of these modules does not alter the study’s main contribution but limits the depth of the results. It is recommended that future studies apply the proposed framework to larger datasets (i.e. more BIM models and/or additional impact categories) to achieve more representative results for the study’s geographical context. Furthermore, including the life cycle modules omitted in the present work—particularly as data availability and quality improve—would further enhance the framework’s accuracy. These expansions would enable more precise assessments that are robust and more trustworthy for policy integration.

The supplementary material for this article can be found online.