Research articleStrategies for enhancing the accuracy of evaluation and sustainability performance of building
Introduction
The building industry is responsible for a substantial amount of resources consumption and consequently inducing enormous pressures on environment (de Klijn-Chevalerias and Javed, 2017). For example, the construction and use of building are associated with 40% and 36% of the total energy consumption and GHG emissions worldwide, respectively (Pal et al., 2017; Marique and Rossi, 2018), and building-related emissions is expected to be double by 2050 (Pomponi and Moncaster, 2016). Owing to an increase in building construction globally, much attention is attributed to this industry to minimize resource consumption by means of design optimization in order to reduce its environmental impacts (Hossain et al., 2016a; Zhang and Wang, 2017), and this is realized by many governments as one of the means to address sustainability concerns (Chau et al., 2015).
As an early-stage decision support tool (Tettey et al., 2014; Anand and Amor, 2017; Panteli et al., 2018), life cycle assessment (LCA) technique is commonly used for assessing the associated environmental impacts of buildings so that the environmental consequences brought by resource consumption of building construction can be unveiled. In previous studies, LCA was adopted to evaluate the environmental implications of building construction, different building components/units and materials used including insulating materials due to their relevance in the construction and operational phases of the building (Sierra-Pérez et al., 2018; Sierra-Perez et al., 2016a,2016b), systems deployed (e.g. construction process), retrofitting, and utilization of building including the end-of-life (EoL) scenario to reduce the environmental impacts (Chau et al., 2015). On the other hand, several studies highlighted the environmental assessment of various types of buildings globally (e.g. Kim et al., 2015; Passer et al., 2012; Onat et al., 2014; Atmaca, 2016; Heinonen et al., 2016; Lasvaux et al., 2017), and more specifically on energy consumption and carbon emissions (Roh and Tae, 2017; Kneifel et al., 2018; Pomponi and Moncaster, 2018; Teng and Pan, 2019) in respect to the principal raw materials of building, such as steel, reinforced concrete and wood (Cho et al., 2012; Guo et al., 2017; Balasbaneh et al., 2018; Sandanayake et al., 2018).
Using LCA for building assessment is unique and complex due to the intrinsic diversity of data, and the complexity is compounded when LCA is carried out with a limited dataset (Escamilla and Habert, 2017). Many LCA studies have used the upstream data from secondary sources, especially from diverse geographical locations of various materials for building-related LCA research, due to a lack of relevant local or regional data sources. The selection of different sources of upstream data, however, can significantly influence the outcomes of LCA studies. The data obtained from reports or measurements and deficient modeling assumptions including missing data could lead to significant uncertainties on the results. Thus, uncertainties associated with the use of different life cycle inventory (LCI) data should be properly addressed (Wei et al., 2015). In addition, the selection of generic and product specific database exhibits significant deviations depending on the impact categories and building materials (Takano et al., 2014; Lasvaux et al., 2015).
The selection of a set of representative data is crucial in LCA, as it requires accurate technological data to warrant a reliable result. Representativeness is a data quality indicator that appropriately represent the technological, temporal and geographical scope of a study (Henriksen et al., 2017; Moncaster et al., 2018). Meanwhile, unifying and harmonizing the LCI databases are equally important (Frischknecht et al., 2015), despite they require a high level of expertise (Silvestre et al., 2015; Kuczenski et al., 2016). Data representativeness is also an important factor affecting the results of building assessment, especially when there is a lack of temporal representation and the data is outdated (Dixit, 2017). While LCI data quality may affect the reliability, accuracy and validity of LCA, data availability is another concern in building-related LCA studies (Dixit, 2017). As buildings are considered as more complicated than a single system/product with a long lifespan and are used to cater for multiple functions, not to mention about the possibility of subsequent renovations and alterations during the operation phase (Chau et al., 2015). Consequently, further efforts are essential to develop case-specific regional or sector-specific LCA databases for the building sector under the unique national context (Silvestre et al., 2015).
As LCA is a tool commonly used to establish what design alternatives and materials would “make sense” (Baitz et al., 2013), a reliable result obtained from the use of accurate and representative LCI data is inevitable. However, LCA results sometimes could render it difficult for decision making and benchmarking so as to facilitate future improvement when significant variations inherit in a process. For example, more than 20% variation on the total carbon was observed due to the selection of different databases (i.e. predominantly generic databases) in the previous studies in Hong Kong (Dong and Ng, 2015; Gan et al., 2017; Teng and Pan, 2019). This aspect is essentially important for many parts of the world, including Hong Kong, where there is a severe lack of upstream recognized databases/data for various materials in conducting LCA for such a complex system. In addition, the EoL of building phase is rarely considered in existing building research (Pomponi and Moncaster, 2016; Hossain and Ng, 2018), despite significant efforts have been put forward in recent years to address the multifaceted challenges, especially in terms of methodology of evaluation, design of (green/low carbon) building, selection of low carbon materials, and sustainable management of building waste. For reducing the carbon emissions of building, strategies to use alternative materials is common in LCA studies. However, the influence of data representativeness and different end-of-life building waste management strategies to the total carbon emissions is currently lacking in the existing studies. This is particularly important for ensuring the accuracy of assessment, comparing and establishing benchmark for future reduction from the building, and supporting sustainable management of building waste. Therefore, an integrated framework is needed to cover these aspects comprehensively in building LCA study.
To address these important aspects in building LCA comprehensively, this study aims to: (i) evaluate the deviations of environmental impacts of building construction between the adoption of a case-specific localize/regionalize upstream and the generic data based on a case study of high-rise residential building construction in Hong Kong (i.e. by considering the principal building materials); (ii) adopt strategies to reduce the carbon emissions using alternative materials for concrete production; and (iii) evaluate the influence of the EoL stage waste materials into the total carbon emissions for adopting materials cycling and resources recovery principle by proposing an integrated LCA framework. The adopted integrated method can add valuable insights in existing building LCA for obtaining the representative results for the decision making process, as well as promoting sustainability performance of building. The results and frameworks could serve to improve fundamental methodological aspects in future LCAs of buildings.
Section snippets
General methodology
The proposed integrated methodological framework is shown in Fig. 1. The framework consists of some novel approaches such as the selection of local data/databases for enhancing the accuracy of the evaluation, strategies for carbon reduction for promoting the sustainability performance of building, and the adoption of materials recovery principle for ensuring the sustainable end-of-life waste management. Based on the global concern and particular importance to building environmental research (
Aspect 1 (influence of data representativeness)
Within the scope of the study, carbon emissions for the case residential building with due consideration of different data sources of construction materials are shown in Fig. 4, Fig. 5. The results indicate the deviations of different magnitudes depending on the building materials employed, especially with concrete and timber. As shown in Figs. 4 and 691 kgCO2e GHG emissions was associated with per unit (m2) of building construction for the base case scenario (M1), as compared to 593 kgCO2e for
Conclusions
Buildings are responsible for considerable amount of resources depletion and associated emissions due to the extensive consumption of diverse construction materials. With a view to reducing carbon emissions from building construction, the selection of representative data is crucial in the decision-making process, as it requires accurate, consistent, representativeness and reliable results. Therefore, this study has comparatively evaluated the carbon emissions of building due to the choice of
CRediT authorship contribution statement
Md. Uzzal Hossain: Formal analysis, Validation, Writing - original draft, Conceptualization. S. Thomas Ng: Supervision, Writing - review & editing, Validation, Methodology.
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