Insight from Review Articles of Life Cycle Assessment for Buildings
Abstract
1. Introduction
Acronym | Concept | Definition |
---|---|---|
LCI | Life cycle inventory analysis | Phase of life cycle assessment involving the compilation and quantification of inputs and outputs for a product/process throughout its life cycle. |
LCA | Life cycle assessment | Compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product/process throughout its life cycle. |
LCCA | Life cycle cost analysis | Analysis of financial costs for a product/process throughout its life cycle. |
LCEA | Life cycle energy analysis | Analysis of energy performance for a product/process throughout its life cycle. |
LC(CO2)A | Life cycle CO2 emissions analysis | Analysis of CO2 emissions for a product/process throughout its life cycle. |
2. Methodology
3. Results
3.1. Scientometric Analysis
3.1.1. Publication Trend
3.1.2. Analysis of Article Sources
Journal | Total Link Strength | Article Number | Citation Number | Norm. Citations 1 | Avg. Citations | Avg. Norm. Citations 2 | Avg. Pub. Year 3 |
---|---|---|---|---|---|---|---|
Environmental Chemistry Letters | 8 | 4 | 1106 | 35.5 | 276.5 | 8.9 | 2023 |
Applied Energy | 37 | 2 | 710 | 5.0 | 355.0 | 2.5 | 2016 |
Environmental Research Letters | 16 | 3 | 365 | 4.2 | 121.7 | 1.4 | 2019 |
Building and Environment | 192 | 18 | 1329 | 22.6 | 73.8 | 1.3 | 2020 |
Renewable & Sustainable Energy Reviews | 328 | 78 | 10,162 | 85.8 | 130.3 | 1.1 | 2016 |
Journal of Cleaner Production | 122 | 27 | 2417 | 28.9 | 89.5 | 1.1 | 2019 |
Sustainable Cities and Society | 26 | 3 | 252 | 3.0 | 84.0 | 1.0 | 2020 |
Science of the Total Environment | 13 | 3 | 236 | 3.0 | 78.7 | 1.0 | 2019 |
Energy and Buildings | 153 | 17 | 2389 | 16.6 | 140.5 | 1.0 | 2019 |
Journal of Environmental Management | 22 | 7 | 631 | 6.6 | 90.1 | 0.9 | 2019 |
Construction and Building Materials | 3 | 4 | 223 | 3.8 | 55.8 | 0.9 | 2021 |
Journal of Building Engineering | 33 | 4 | 283 | 3.7 | 70.8 | 0.9 | 2019 |
International Journal of Life Cycle Assessment | 32 | 20 | 1125 | 16.8 | 56.3 | 0.8 | 2020 |
Sustainability | 141 | 35 | 1316 | 27.9 | 37.6 | 0.8 | 2020 |
Waste Management | 14 | 2 | 160 | 1.5 | 80.0 | 0.8 | 2019 |
Sustainable Production and Consumption | 10 | 8 | 127 | 5.7 | 15.9 | 0.7 | 2023 |
Buildings | 55 | 14 | 211 | 9.2 | 15.1 | 0.7 | 2022 |
Engineering Structures | 3 | 2 | 100 | 1.1 | 50.0 | 0.6 | 2015 |
Heliyon | 6 | 2 | 28 | 1.1 | 14.0 | 0.6 | 2023 |
Renewable Energy | 5 | 2 | 112 | 1.1 | 56.0 | 0.5 | 2017 |
Environmental Science and Pollution Research | 15 | 3 | 86 | 1.4 | 28.7 | 0.5 | 2019 |
Environment Development and Sustainability | 6 | 2 | 20 | 0.8 | 10.0 | 0.4 | 2023 |
Energies | 31 | 13 | 189 | 4.9 | 14.5 | 0.4 | 2022 |
Canadian Journal of Civil Engineering | 5 | 2 | 17 | 0.7 | 8.5 | 0.4 | 2023 |
Ecological Indicators | 7 | 2 | 16 | 0.6 | 8.0 | 0.3 | 2023 |
Applied Sciences-Basel | 6 | 3 | 30 | 0.6 | 10.0 | 0.2 | 2022 |
Bioresources | 1 | 2 | 10 | 0.1 | 5.0 | 0.0 | 2019 |
3.1.3. Analysis of Article Regions
3.1.4. Analysis of Co-Authorship
3.1.5. Analysis of Keywords
- Review studies on LCA-B encompasses dual dimensions: building classifications and internal components within buildings including structural components and energy systems. (1) Building classifications, such as residential units, commercial buildings, office buildings, refurbished buildings, nearly/net-zero energy buildings (nZEBs/ZEBs), green buildings, and passive houses. The aim is to understand their operational mechanisms and provide directions to establish performance benchmarks for different types of buildings and accelerate their implementation. (2) Building materials or structures, such as cement, concrete, building envelope, roof, and window, are investigated to explore appropriate strategies for reducing both energy consumption and GHG emissions. (3) Energy systems, such as heat pump, HVAC, and solar thermal systems, are examined to optimize sustainability practices.
- Review studies address comprehensive evaluation perspectives of LCA-B: LCA, LCCA, LCEA, LC(CO2)A, and dynamic LCA are the most popular assessment viewpoints. LCA prioritizes comprehensive analysis of energy consumption and ecological impacts throughout product/system lifespans. LCCA adopts an economic lens to evaluate cost viability of energy usage and environmental impact. LCEA emphasizes quantifying total energy demands across building life cycles, encompassing material production, construction, operation, and deconstruction phases.
- Research methods involved in LCA-B studies and review papers: In terms of LCA-B studies, building simulation and energy simulation are the basic and traditional approaches to derive building energy consumption during operation stage. Assessment tools, such as SimaPro, One Click LCA, Pleiades Equer, and Athena Impact Estimator, are the most used software to evaluate the potential environmental impacts [102]. In addition, the integration of digital technologies is assuming growing significance in low-carbon building practices, as evidenced by Building Information Modeling (BIM). This tool has demonstrated transformative potential in architectural planning, structural implementation, and data-driven lifecycle governance. In terms of LCA-B review articles: bibliometric analysis, machine learning, and science mapping are used in a high frequency recently. Bibliometric analysis focuses on external characteristics of the literature (such as author regions, article sources, keywords, and citation numbers) and aims to reveal the development disciplines and trends through quantitative indicators. Science mapping is commonly applied in bibliometric analysis to provide information visualization and network analysis through software (such as VOSviewer, CiteSpace) and machine learning.
- Cost performance: Life cycle costing provides a comprehensive economic viewpoint for different stakeholders, which is more reasonable compared with the traditional cost analysis method that focuses on a certain stage.
- Energy performance: Previous literature encompasses diverse energy classifications throughout the whole building life cycle, prioritizing operational energy (OE) and embodied energy (EE), while additionally detailing specific energy subtypes including primary energy, transportation-associated energy, and recurrent embodied energy. The tailored energy-saving strategies can be designed based on energy consumption and energy utilization efficiency analysis.
- Environmental performance: Within the context of sustainable development, environmental consequences of buildings have garnered substantial interest and are extensively investigated by scholars. Contemporary examinations of environmental burdens in LCA-B predominantly focus on quantifying greenhouse gas discharges from the building sector, employing methodologies such as carbon footprint tracing and CO2 emission inventories to rigorously evaluate the environmental impact of construction-related activities.
3.1.6. Analysis of Article Citations
Article | Title | Source | Citation Numbers | Norm. Citations |
Chen (2022) [103] | Strategies to achieve a carbon neutral society: a review | Environmental Chemistry Letters | 633 | 11.59 |
Yang (2023) [83] | Circular economy strategies for combating climate change and other environmental issues | Environmental Chemistry Letters | 286 | 11.37 |
Rahman (2020) [104] | Assessment of energy storage technologies: A review | Energy Conversion and Management | 479 | 6.33 |
Manso (2021) [105] | Green roof and green wall benefits and costs: A review of the quantitative evidence | Renewable & Sustainable Energy Reviews | 272 | 5.88 |
Chen (2023) [106] | Green construction for low-carbon cities: a review | Environmental Chemistry Letters | 125 | 4.97 |
Schiavoni (2016) [107] | Insulation materials for the building sector: A review and comparative analysis | Renewable & Sustainable Energy Reviews | 666 | 4.30 |
Chau (2015) [108] | A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings | Applied Energy | 638 | 4.21 |
Ghisellini (2018) [109] | Exploring environmental and economic costs and benefits of a circular economy approach to the construction and demolition sector. A literature review | Journal of Cleaner Production | 367 | 3.99 |
Wu (2016) [110] | A critical review of the use of 3-D printing in the construction industry | Automation in Construction | 589 | 3.80 |
Dixit (2012) [97] | Need for an embodied energy measurement protocol for buildings: a review paper | Renewable & Sustainable Energy Reviews | 324 | 3.75 |
Cabeza (2014) [5] | Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: A review | Renewable & Sustainable Energy Reviews | 898 | 3.65 |
Aditya (2017) [111] | A review on insulation materials for energy conservation in buildings | Renewable & Sustainable Energy Reviews | 521 | 3.52 |
Hertwich (2019) [112] | Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics-a review | Environmental Research Letters | 259 | 3.20 |
Ramesh (2010) [113] | Life cycle energy analysis of buildings: an overview | Energy and Buildings | 930 | 2.97 |
Mukherjee (2020) [114] | A review on municipal solid waste-to-energy trends in the USA | Renewable & Sustainable Energy Reviews | 218 | 2.88 |
D’oca (2018) [115] | The human dimensions of energy use in buildings: A review | Renewable & Sustainable Energy Reviews | 261 | 2.84 |
Kamali (2016) [116] | Life cycle performance of modular buildings: A critical review | Renewable & Sustainable Energy Reviews | 403 | 2.60 |
Anand (2017) [117] | Recent developments, future challenges and new research directions in LCA of buildings: A critical review | Renewable & Sustainable Energy Reviews | 353 | 2.38 |
Khan (2021) [118] | Sustainability assessment, potentials and challenges of 3d printed concrete structures: a systematic review for built environmental applications | Journal of Cleaner Production | 105 | 2.27 |
Nwodo (2019) [119] | A review of life cycle assessment of buildings using a systematic approach | Buildings and Environment | 183 | 2.26 |
Soust-verdaguer (2017) [120] | Critical review of bim-based LCA method to buildings | Energy and Buildings | 332 | 2.24 |
Buyle (2013) [121] | Life cycle assessment in the construction sector: a review | Renewable & Sustainable Energy Reviews | 366 | 2.12 |
Vilches (2017) [122] | Life cycle assessment (LCA) of building refurbishment: A literature review | Energy and Buildings | 311 | 2.10 |
Shukla (2017) [123] | Recent advancement in BIPV product technologies: A review | Energy and Buildings | 295 | 1.99 |
Obrecht (2020) [96] | Bim and lca integration: a systematic literature review | Sustainability | 147 | 1.94 |
Fenner (2018) [124] | The carbon footprint of buildings: a review of methodologies and applications | Renewable & Sustainable Energy Reviews | 178 | 1.94 |
Panteli (2020) [125] | Building information modeling applications in smart buildings: from design to commissioning and beyond a critical review | Journal of Cleaner Production | 124 | 1.64 |
Ingrao (2018) [126] | How can life cycle thinking support sustainability of buildings? investigating life cycle assessment applications for energy efficiency and environmental performance | Journal of Cleaner Production | 147 | 1.60 |
Abd rashid (2015) [81] | A review of life cycle assessment method for building industry | Renewable & Sustainable Energy Reviews | 239 | 1.58 |
Hong (2018) [127] | Building simulation: ten challenges | Building Simulation | 141 | 1.53 |
3.2. Findings of Qualitative Analysis
3.2.1. Analysis of LCA Software
LCA Software | Key Application Characteristics | Strengths | Limitations |
---|---|---|---|
Athena Impact Estimator (Canada) | Specialized for North American building materials. | Free to use; Detailed structural analysis. | Limited global coverage; Outdated interface. |
BIM3LCA (Denmark) | BIM-integrated early design LCA. | Revit/ArchiCAD compatibility; User-friendly. | Europe-focused databases; Requires BIM skills. |
HBERT (China) | Open-source building energy and material LCA. | Free; Links to energy simulation tools. | Basic UI; Small user community. |
LCAbyg (Denmark) | Simplified LCA for Danish regulations. | Fast compliance checks; Free for research. | Nordic-region only; Limited complexity. |
LCA-Quick (USA) | Rapid early-stage carbon assessment. | Excel-based simplicity; Fast results. | Only CO2 analysis; No BIM integration. |
OneClick LCA (Finland) | Cloud-based certification support LEED/BREEAM. | Compliance; Good BIM links. | Subscription model; Advanced features limited. |
Tally (USA) | Revit-embedded material analysis. | Real-time BIM-LCA feedback; US data strong. | Revit-dependent; Global data lacking. |
GaBi (Germany) | Comprehensive industrial LCA. | Dynamic modeling; Excellent databases. | Expensive; Steep learning curve. |
SimaPro (Netherlands) | Advanced academic/professional LCA. | Best database support; Customizable. | Complex interface; High cost. |
Pleiades + Equer (France) | French energy-LCA integration. | HQE certification ready. | France-specific; Needs energy modeling expertise. |
3.2.2. Analysis of Highly Cited Review Articles
3.2.3. Findings from Highly Cited Papers
- Passive and active features are generally advocated for buildings while excessive use of these technologies may be counterproductive in the life cycle context [113]. This is mainly because the embodied carbon of high-performance materials and equipment is relatively high, and the cost of these materials and equipment are also high, low energy buildings are actually performing better from the perspective of LCA although the concept of self-sufficient buildings (e.g., net zero energy buildings) are widespread and promoted in many countries. Meanwhile, energy consumption reduction through many efficiency improvements is usually overestimated since building-users’ behavior can greatly affect the building energy consumption during use phase of buildings and thus is difficult to predict. Therefore, further investigation is required to identify their differences.
- Many studies concluded that the LCA results of different cases lack comparability, mainly due to the complexity and diversity of building LCA [117,122,124]. (1) Differences in system boundaries definitions, i.e., the coverage of life cycle stages and inconsistency of functional units. For example, some studies focused on “Cradle to Gate” and others focused on “Cradle to Grave”. (2) Differences in data sources and assumptions, i.e., background databases, geographical and climatic conditions, technical parameters, and scenario assumptions. For example, material production, transportation, and energy consumption data may come from different databases, such as Ecoinvent, GaBi, China’s local database, etc., which cause the difference in results. (3) Differences in methodological and model selection, i.e., process-based LCA (PLCA) and input–output LCA (IO-LCA) and hybrid LCA, impact assessment model, and software tool selection. For example, the data sources, coverage and modeling are different for PLCA, IO-LCA, and hybrid LCA. (4) Differences in building characteristics and design, i.e., building function and types, material and technology selection, and regional adaptive design. For example, the energy usage patterns and intensities of buildings may vary significantly for buildings with different functions, such as office buildings, residential buildings, and hospital buildings. (5) Differences in the time span and data timeliness, i.e., the assumptions of buildings service life, parameter update due to technology upgradation. For example, the building lifespan used in most cases ranges from 50 years to 120 years. In addition, a large amount of data (i.e., material production, transportation, energy consumption, etc.) is required for building LCA, while the data is usually scattered and difficult to collect precisely in actual projects, especially the embodied carbon data in the supply chain. To overcome this challenge, much effort should be made to develop a set of standardized guidelines and methodology on the boundary scoping, methodology choices, and data inventories so as to establish benchmarks for building LCA.
- The integration of BIM technology in LCA is widely acknowledged as it can achieve the visualization and dynamic management of the entire life cycle data of buildings, improving design efficiency and data accuracy. Nevertheless, the major issues can be summarized as follows: (1) The lack of a unified standard for data interfaces between different BIM software and LCA tools leads to obstacles in software compatibility and data exchange. (2) It is difficult to synchronize the energy consumption and maintenance data during the building operation stage to the BIM model in real time, which may lead to the deviation of LCA results from the actual situation. Furthermore, the data of the demolition and recycling stages are often ignored due to the lack of coordination of the industrial chain. (3) The integration of BIM-LCA requires professionals to master architectural modeling, LCA methods, and data analysis techniques simultaneously. However, the current talent reserve in the industry is insufficient and thus limits its promotion. The following solution paths are proposed: (1) Adopt unified data standards and long-term archiving formats; establish a digital twin for the entire life cycle and continuously record the changes in the building’s status. (2) Develop automated data synchronization tools to collect operation and maintenance data in real time and update models using the Internet of Things; combine machine learning to predict future trends and generate dynamic LCA input parameters at multiple time nodes; develop an LCA tool integrating uncertainty analysis. (3) Strengthen the construction of BIM-LCA courses in the education sector, improve the training and incentive system in the enterprise sector, promote standard and resource support, and accelerates optimization tools for BIM-LCA, based on these, a virtuous cycle of “talent cultivation-technology application—industry upgrading” will be gradually formed.
- Extensive studies have been conducted to analyze environmental issues of buildings, but the social or cultural aspects were ignored. The main reason for this may be that the influence of social and cultural aspects is difficult to quantify since it faces challenges such as data collection and indicator design, which lead to the lack of standardized methods for social and cultural assessment. To address these issues, a multi-objective assessment including other assessment tools is required to increase the usefulness of building LCA for decision-making, and a multi-dimensional LCA framework of “environment–society–culture” can be constructed.
- Circular economy principles, which focus on reducing waste, reusing materials, and recycling resources, are increasingly seen as critical to addressing climate change, promoting sustainability in the construction sector and achieving carbon neutrality. Therefore, circular economy principles offer a pathway to reduce waste and emissions, and LCA provides the tools to measure and optimize these efforts. In the construction sector, circular practices like modular construction [116] and recycling construction and demolition waste [109] can significantly lower greenhouse gas emissions. However, the implementation of circular economy strategies faces several challenges. One major barrier is the lack of standardized protocols for measuring the environmental and economic benefits of such practices. For example, Dixit [97] pointed out the need for an embodied energy measurement protocol for buildings, which is essential for evaluating the true impact of circular practices. In addition, as mentioned by Wu [110] in their review of 3D printing in construction, significant upfront investment in new technologies and infrastructure is required for transitioning to a circular economy. To address these challenges, approaches such as standardization, data availability, and technological integration will be crucial for their widespread adoption and success in achieving carbon neutrality, and the potential benefits offered by circular economy approaches, such as reducing material costs, lower emissions, and enhancing resource efficiency, make them a promising direction for future research and policy development. The high citation counts of these studies underscore their relevance and the urgent need for continued research and innovation in these areas.
4. Conclusions and Limitations
- The most popular journal is observed to be Renewable & Sustainable Energy Reviews, followed by Sustainability, Journal of Cleaner Production, and International Journal of Life Cycle Assessment. Five main collaboration groups are obtained that contain at least three influential scholars. Rooney DW, Chen L, Yap P, Osman AI, Huang L, Chen Z, and Fawzy S are observed to be the most active recent researchers and are also among the most influential scholars in LCA-B review studies. China, United States, and Italy have the most published LCA-B review papers, and China, Australia, and Spain are most active in this field.
- Thirty highly cited review articles were selected, based on which the main findings as well as challenges are summarized and synthesized from these influential articles: (1) Low-energy buildings demonstrate superior life cycle assessment outcomes compared to net-zero energy counterparts. (2) Comparability issues persist among LCA studies of various building cases, a set of standardized guidelines and methodology is essential for facilitating consistent benchmarking and cross-case comparison in the field. (3) Interoperability issues and data sharing limitations pose significant challenges for advancing BIM-LCA applications. (4) Developing an inclusive life cycle assessment model that incorporates socio-cultural factors is crucial for achieving complete building performance evaluations. (5) The lack of standardized protocols for measuring the environmental and economic benefits is the major barrier faced with the implementation of circular economy strategies.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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---|---|---|---|---|---|---|---|
North Ireland | 41 | 6 | 1199 | 37.5 | 199.8 | 6.25 | 2022 |
China | 377 | 45 | 4442 | 81.7 | 98.7 | 1.82 | 2020 |
Malaysia | 45 | 6 | 1215 | 10.2 | 202.5 | 1.71 | 2018 |
Portugal | 21 | 10 | 698 | 13.2 | 69.8 | 1.32 | 2019 |
Australia | 251 | 31 | 3160 | 39.4 | 101.9 | 1.27 | 2019 |
India | 56 | 7 | 1632 | 8.9 | 233.1 | 1.27 | 2016 |
England | 216 | 31 | 2079 | 34.5 | 67.1 | 1.11 | 2020 |
Belgium | 125 | 15 | 928 | 16.4 | 61.9 | 1.09 | 2021 |
USA | 245 | 36 | 3874 | 38.7 | 107.6 | 1.08 | 2018 |
Switzerland | 64 | 11 | 1169 | 11.6 | 106.3 | 1.06 | 2016 |
Italy | 166 | 33 | 3036 | 34.8 | 92.0 | 1.05 | 2019 |
Spain | 275 | 30 | 3617 | 31.1 | 120.6 | 1.04 | 2018 |
Denmark | 62 | 13 | 682 | 12.6 | 52.5 | 0.97 | 2021 |
Germany | 61 | 15 | 1114 | 13.7 | 74.3 | 0.91 | 2019 |
Lithuania | 27 | 7 | 256 | 6.0 | 36.6 | 0.85 | 2020 |
Austria | 98 | 10 | 472 | 8.1 | 47.2 | 0.81 | 2021 |
Canada | 247 | 32 | 2297 | 25.8 | 71.8 | 0.81 | 2021 |
Sweden | 45 | 6 | 492 | 4.6 | 82.0 | 0.77 | 2017 |
Norway | 69 | 11 | 543 | 7.8 | 49.4 | 0.71 | 2019 |
France | 97 | 22 | 1271 | 14.6 | 57.8 | 0.66 | 2019 |
Brazil | 27 | 13 | 495 | 7.3 | 38.1 | 0.56 | 2020 |
Finland | 23 | 5 | 193 | 2.6 | 38.6 | 0.51 | 2020 |
Scotland | 32 | 5 | 236 | 2.3 | 47.2 | 0.47 | 2018 |
South Korea | 60 | 12 | 573 | 5.1 | 47.8 | 0.42 | 2014 |
Scholar | Affiliation | Article Numbers | Total Citations | Norm. Citations | Avg. Citations | Avg. Norm. Citations | Avg. Pub. Year |
---|---|---|---|---|---|---|---|
Fawzy S | Queen’s University Belfast | 3 | 1044 | 27.9 | 348.0 | 9.31 | 2022 |
Rooney DW | Queen’s University Belfast | 4 | 1106 | 35.5 | 276.5 | 8.87 | 2023 |
Chen L | Chongqing University | 5 | 1156 | 41.6 | 231.2 | 8.32 | 2023 |
Yap P | Xi’an Jiaotong Liverpool University | 5 | 1156 | 41.6 | 231.2 | 8.32 | 2023 |
Osman AI | Queen’s University Belfast | 3 | 820 | 24.1 | 273.3 | 8.04 | 2023 |
Chen Z | Xi’an Jiaotong Liverpool University | 3 | 237 | 18.6 | 79.0 | 6.21 | 2023 |
Huang L | Chongqing University | 3 | 237 | 18.6 | 79.0 | 6.21 | 2023 |
Allen S | University of Bath | 3 | 149 | 7.9 | 49.7 | 2.63 | 2022 |
Dixit MK | Texas A&M University | 4 | 820 | 7.5 | 205.0 | 1.89 | 2015 |
Rock M | Katholieke University Leuven | 3 | 166 | 4.6 | 55.3 | 1.54 | 2022 |
Soust-verdaguer B | University of Seville | 4 | 606 | 5.8 | 151.5 | 1.45 | 2018 |
Llatas C | University of Seville | 3 | 531 | 4.2 | 177.0 | 1.39 | 2017 |
Amor B | University of Sherbrooke | 4 | 593 | 5.4 | 148.3 | 1.34 | 2018 |
Garcia-martinez A | University of Seville | 4 | 761 | 5.3 | 190.3 | 1.32 | 2018 |
Al-ghamdi SG | Hamad Bin Khalifa University | 3 | 165 | 3.5 | 55.0 | 1.16 | 2021 |
Ng ST | City University of Hong Kong | 3 | 205 | 3.5 | 68.3 | 1.16 | 2020 |
Kylili A | Frederick University | 3 | 357 | 3.2 | 119.0 | 1.06 | 2017 |
Sala S | European Commission | 3 | 287 | 3.1 | 95.7 | 1.02 | 2019 |
Roeck M | Graz University of Technology | 4 | 192 | 4.1 | 48.0 | 1.01 | 2021 |
Verones F | Norwegian University of Science & Technology | 3 | 477 | 3.0 | 159.0 | 1.00 | 2015 |
Tam VWY | Western Sydney University | 5 | 219 | 4.7 | 43.8 | 0.94 | 2021 |
Fokaides PA | Kaunas University of Technology | 4 | 399 | 3.7 | 99.8 | 0.94 | 2018 |
Cellura M | University of Palermo | 5 | 595 | 4.7 | 119.0 | 0.93 | 2014 |
Zuo J | University of Adelaide | 4 | 387 | 3.6 | 96.8 | 0.89 | 2018 |
Sonnemann G | University of Bordeaux | 3 | 278 | 2.7 | 92.7 | 0.89 | 2019 |
Mistretta M | University Mediterranea Reggio Calabria | 4 | 483 | 3.4 | 120.8 | 0.86 | 2013 |
Passer A | Graz of University Technology | 7 | 378 | 5.9 | 54.0 | 0.85 | 2020 |
Longo S | University of Palermo | 4 | 420 | 3.3 | 105.0 | 0.82 | 2014 |
Birkved M | University of Southern Denmark | 4 | 184 | 3.2 | 46.0 | 0.80 | 2021 |
Allacker K | Katholieke University Leuven | 4 | 168 | 3.1 | 42.0 | 0.77 | 2020 |
Saade MRM | State University of Campinas (Spain) | 4 | 222 | 2.8 | 55.5 | 0.70 | 2019 |
Shin S | Hanyang University | 4 | 191 | 2.0 | 47.8 | 0.49 | 2011 |
Tae S | Hanyang University | 7 | 332 | 3.2 | 47.4 | 0.45 | 2013 |
Ghisi E | Federal University of Santa Catarina | 3 | 106 | 1.2 | 35.3 | 0.41 | 2020 |
Chemisana D | University of Lleida | 5 | 220 | 1.9 | 44.0 | 0.38 | 2018 |
Roh S | Hanyang University | 4 | 203 | 1.4 | 50.8 | 0.36 | 2015 |
Keyword | Total Link Strength | Occurrences | Avg. Citations | Avg. Norm. Citations | Avg. Pub. Year |
---|---|---|---|---|---|
Climate change | 17 | 10 | 102.4 | 2.72 | 2020 |
Carbon emissions | 11 | 9 | 127.7 | 2.45 | 2021 |
Construction industry | 12 | 6 | 186.3 | 1.52 | 2019 |
Building materials | 9 | 6 | 154.5 | 1.42 | 2020 |
Built environment | 22 | 9 | 70.0 | 1.38 | 2021 |
Building life cycle | 15 | 7 | 139.9 | 1.29 | 2018 |
Concrete | 10 | 5 | 102.4 | 1.27 | 2017 |
Buildings | 77 | 38 | 117.2 | 1.20 | 2020 |
Energy | 12 | 10 | 134.1 | 1.16 | 2014 |
Building information modeling | 54 | 27 | 78.1 | 1.16 | 2021 |
Circular economy | 45 | 20 | 65.8 | 1.12 | 2021 |
Life cycle energy | 14 | 7 | 214.0 | 1.08 | 2017 |
Literature review | 19 | 9 | 32.3 | 1.07 | 2021 |
Review | 35 | 18 | 117.6 | 1.06 | 2018 |
Sustainability | 69 | 31 | 71.4 | 1.06 | 2020 |
Embodied carbon | 24 | 13 | 47.7 | 1.05 | 2021 |
Life cycle assessment | 282 | 237 | 83.8 | 1.03 | 2019 |
Environmental impact assessment | 17 | 8 | 75.4 | 1.03 | 2019 |
Life cycle sustainability assessment | 21 | 11 | 43.5 | 0.92 | 2022 |
Environmental performance | 9 | 5 | 51.8 | 0.91 | 2017 |
Life cycle impact assessment | 6 | 5 | 90.8 | 0.89 | 2018 |
Sustainable building | 17 | 7 | 60.4 | 0.86 | 2020 |
Greenhouse gas | 11 | 7 | 75.7 | 0.86 | 2019 |
Embodied energy | 28 | 16 | 123.3 | 0.85 | 2018 |
Global warming potential | 9 | 5 | 48.6 | 0.83 | 2021 |
Energy efficiency | 36 | 16 | 96.9 | 0.82 | 2018 |
Carbon footprint | 13 | 9 | 56.9 | 0.79 | 2020 |
Environmental impacts | 32 | 19 | 43.6 | 0.79 | 2020 |
Energy consumption | 5 | 5 | 85.4 | 0.78 | 2018 |
Life cycle cost | 33 | 22 | 71.4 | 0.76 | 2019 |
Green building | 10 | 5 | 78.4 | 0.74 | 2019 |
Renewable energy | 10 | 6 | 58.7 | 0.69 | 2018 |
Social life cycle assessment | 11 | 6 | 5.2 | 0.59 | 2023 |
Life cycle | 9 | 6 | 49.8 | 0.55 | 2018 |
Construction | 18 | 6 | 38.2 | 0.50 | 2021 |
Bibliometric analysis | 14 | 6 | 39.2 | 0.47 | 2021 |
Key Findings | Challenges/Future Research Directions |
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2009–2015
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2016–2019
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2020–2025
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zhang, Y.; Lu, Y.; Huang, Z.; Chen, D.; Cheng, B.; Wang, D.; Lu, C. Insight from Review Articles of Life Cycle Assessment for Buildings. Appl. Sci. 2025, 15, 7751. https://doi.org/10.3390/app15147751
Zhang Y, Lu Y, Huang Z, Chen D, Cheng B, Wang D, Lu C. Insight from Review Articles of Life Cycle Assessment for Buildings. Applied Sciences. 2025; 15(14):7751. https://doi.org/10.3390/app15147751
Chicago/Turabian StyleZhang, Yang, Yuehong Lu, Zhijia Huang, Demin Chen, Bo Cheng, Dong Wang, and Chengyu Lu. 2025. "Insight from Review Articles of Life Cycle Assessment for Buildings" Applied Sciences 15, no. 14: 7751. https://doi.org/10.3390/app15147751
APA StyleZhang, Y., Lu, Y., Huang, Z., Chen, D., Cheng, B., Wang, D., & Lu, C. (2025). Insight from Review Articles of Life Cycle Assessment for Buildings. Applied Sciences, 15(14), 7751. https://doi.org/10.3390/app15147751