LCA and energy efficiency in buildings: mapping more than twenty years of research

• URL: http://arxiv.org/abs/2409.00065v1
• Date: Fri, 23 Aug 2024 08:43:25 GMT
• Title: LCA and energy efficiency in buildings: mapping more than twenty years of research
• Authors: F. Asdrubali, A. Fronzetti Colladon, L. Segneri, D. M. Gandola,
• Abstract summary: This article reviews more than twenty years of research on Life Cycle Assessment (LCA) The authors identify seven key thematic groups, building and sustainability clusters (BSCs) The major research topics mainly relate to building materials and energy efficiency. The article also provides insights into emerging and underdeveloped themes, outlining crucial future research directions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Research on Life Cycle Assessment (LCA) is being conducted in various sectors, from analyzing building materials and components to comprehensive evaluations of entire structures. However, reviews of the existing literature have been unable to provide a comprehensive overview of research in this field, leaving scholars without a definitive guideline for future investigations. This paper aims to fill this gap, mapping more than twenty years of research. Using an innovative methodology that combines social network analysis and text mining, the paper examined 8024 scientific abstracts. The authors identified seven key thematic groups, building and sustainability clusters (BSCs). To assess their significance in the broader discourse on building and sustainability, the semantic brand score (SBS) indicator was applied. Additionally, building and sustainability trends were tracked, focusing on the LCA concept. The major research topics mainly relate to building materials and energy efficiency. In addition to presenting an innovative approach to reviewing extensive literature domains, the article also provides insights into emerging and underdeveloped themes, outlining crucial future research directions.

Related papers

• Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation [58.064940977804596]
  A plethora of new AI models and tools has been proposed, promising to empower researchers and academics worldwide to conduct their research more effectively and efficiently. Ethical concerns regarding shortcomings of these tools and potential for misuse take a particularly prominent place in our discussion.
  arXiv  Detail & Related papers  (2025-02-07T18:26:45Z)
• A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning [51.7818820745221]
  Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic review is still absent.
  arXiv  Detail & Related papers  (2024-05-30T04:46:40Z)
• KG-EmpiRE: A Community-Maintainable Knowledge Graph for a Sustainable Literature Review on the State and Evolution of Empirical Research in Requirements Engineering [0.43512163406552]
  KG-EmpiRE is a Knowledge Graph (KG) of empirical research in requirements engineering (RE) based on scientific data extracted from 680 papers published in the IEEE International Requirements Engineering Conference (1994-2022) KG-EmpiRE is maintained in the Open Research Knowledge Graph (ORKG), making all data openly and long-term available according to the FAIR data principles. Since its first release based on 199 papers (2014-2022), KG-EmpiRE and its analysis have been updated twice, currently covering over 650 papers.
  arXiv  Detail & Related papers  (2024-05-14T06:42:47Z)
• A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence [55.33653554387953]
  Pattern Analysis and Machine Intelligence (PAMI) has led to numerous literature reviews aimed at collecting and fragmented information. This paper presents a thorough analysis of these literature reviews within the PAMI field. We try to address three core research questions: (1) What are the prevalent structural and statistical characteristics of PAMI literature reviews; (2) What strategies can researchers employ to efficiently navigate the growing corpus of reviews; and (3) What are the advantages and limitations of AI-generated reviews compared to human-authored ones.
  arXiv  Detail & Related papers  (2024-02-20T11:28:50Z)
• Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering [0.3277163122167433]
  Empirical research in requirements engineering (RE) is constantly evolving. The underlying problem is the unavailability of data from earlier works. We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE.
  arXiv  Detail & Related papers  (2023-06-29T08:55:35Z)
• A Decade of Knowledge Graphs in Natural Language Processing: A Survey [3.3358633215849927]
  Knowledge graphs (KGs) have attracted a surge of interest from both academia and industry. As a representation of semantic relations between entities, KGs have proven to be particularly relevant for natural language processing.
  arXiv  Detail & Related papers  (2022-09-30T21:53:57Z)
• Artificial Intelligence in Concrete Materials: A Scientometric View [77.34726150561087]
  This chapter aims to uncover the main research interests and knowledge structure of the existing literature on AI for concrete materials. To begin with, a total of 389 journal articles published from 1990 to 2020 were retrieved from the Web of Science. Scientometric tools such as keyword co-occurrence analysis and documentation co-citation analysis were adopted to quantify features and characteristics of the research field.
  arXiv  Detail & Related papers  (2022-09-17T18:24:56Z)
• Vision-Centric BEV Perception: A Survey [92.98068828762833]
  Vision-centric Bird's Eye View (BEV) perception has garnered significant interest from both industry and academia. The rapid advancements in deep learning have led to the proposal of numerous methods for addressing vision-centric BEV perception challenges. This paper compiles and organizes up-to-date knowledge, offering a systematic review and summary of prevalent algorithms.
  arXiv  Detail & Related papers  (2022-08-04T17:53:17Z)
• An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics [33.655334920298856]
  We provide a comprehensive overview of the research on long document summarization. We conduct an empirical analysis to broaden the perspective on current research progress.
  arXiv  Detail & Related papers  (2022-07-03T02:57:22Z)
• Characterising Research Areas in the field of AI [68.8204255655161]
  We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics. The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.
  arXiv  Detail & Related papers  (2022-05-26T16:30:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.