Next Article in Journal
Review of MVDC Applications, Technologies, and Future Prospects
Next Article in Special Issue
Challenges in the EU Banking Sector as Exemplified by Poland in View of Legislative Changes Related to Climate Crisis Prevention
Previous Article in Journal
Analytical Study of Nonlinear Vibration in a Rub-Impact Jeffcott Rotor
Previous Article in Special Issue
The Leading Traits of the Modern Corporate Leader: Comparing Survey Results from 2008 and 2018
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Energies
Volume 14
Issue 24
10.3390/en14248292
energies-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Blockchain Technology in Life Cycle Assessment—New Research Trends

by
Robert Karaszewski
1,
Paweł Modrzyński
2,*,
Gözde Türkmen Müldür
3 and
Jacek Wójcik
4
1
College of Business Administration, American University in the Emirates, Dubai P.O. Box 503000, United Arab Emirates
2
Faculty of Management Poland, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland
3
Business Administration Department, Adana Alparslan Türkeş Science and Technology University, Adana 01250, Turkey
4
Faculty of Finance and Management, WSB University in Torun, 87-100 Toruń, Poland
*
Author to whom correspondence should be addressed.
Energies 2021, 14(24), 8292; https://doi.org/10.3390/en14248292
Submission received: 30 October 2021 / Revised: 3 December 2021 / Accepted: 6 December 2021 / Published: 9 December 2021
(This article belongs to the Special Issue Strategic Planning and Management in Energy)
Browse Figures
Review Reports Versions Notes

Abstract

:
Environmental protection is currently one of the key priority areas of the European Union (EU). The search for precise tools to assess the impact of the economy, industry, or the production of individual products or services is crucial for an effective and efficient policy in environmental protection. Blockchain technology, originally related to the financial sector and cryptocurrencies, is an innovative solution that is increasingly being implemented by other areas of the economy and industry sectors. The authors reviewed the literature and based on it presented the possibilities and effects of using blockchain technology in Life Cycle Assessment (LCA), which is in line with the current development trends of this method. The analysis of the research conducted in this area also allowed to present not only the advantages of blockchain in LCA, but also the limitations of this technology and the potential directions of further research.

1. Introduction

Environmental protection, rational management of natural resources, and inclusion of the ecological account in the economic account are among the contemporary priorities of the European Union in implementing the sustainable development policy. On 14 July 2021, the European Commission (EC) adopted a set of proposals to make the EU’s climate, energy, transport, and taxation policies fit for reducing net greenhouse gas emissions by at least 55% by 2030, compared to 1990 levels. Achieving these emission reductions in the next decade is crucial to Europe becoming the world’s first climate-neutral continent by 2050 and making the European Green Deal a reality [1]. One of the answers to the priorities of environmental protection contained in the EU documents is the remodelling of the rules for determining the actual cost of production or services, including calculations of all costs related to the production of goods and services along with their disposal—which corresponds to the ISO 14001: 2015 standard [2]. The guidelines of ISO 14001: 2015 are the basis for a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service, known as Life Cycle Assessment (LCA) [3]. Estimating the costs of production and use of a product based on the LCA method means taking into account the impact on the environment, society, and economy throughout the entire life cycle of the product. The LCA method considers the costs of using raw materials, the costs of material processing, maintenance, use, and final disposal or recycling [4]. Linking the LCA assessment with the ISO 14,040 series standards allows for the recognition of the cost of item production according to the following methods: (1) cradle-to-gate: from the extraction of raw materials and transporting them to the factory, (2) cradle-to-grave: from raw material extraction, through use and disposal of the product and (3) gate to gate: from one defined point to another on the product life cycle axis [5]. Growing awareness of business responsibility, the need to implement environmental standards, or rationally managing resources are just some of the “motivators” to look for solutions that, on the one hand, meet environmental protection requirements, and, on the other hand, reduce consumption costs and increase the economic efficiency of production or service processes. In this area, blockchain technology is becoming more and more commonly and more widely used and supports the implemented business processes [6,7,8,9,10,11,12]. The question, therefore, arises whether blockchain technology can be used in LCA? Should the further direction of scientific research focus on linking these two research areas—blockchain and LCA? The aim of the authors was, based on the conducted analysis of the literature, to determine the current research trends in the area of potential blockchain use in LCA, but also to draw attention to its potential limitations.

2. Blockchain

Blockchain is a technology that is increasingly used in the modern world. Its creator is Satoshi Nakamoto, who in 2008 used this technology in cryptocurrencies [13]. The idea of blockchain assumes creating data chains between any two pages and storing them in a distributed cloud environment [14]. This technology is most often associated with cryptocurrencies, financial markets, or transactions, still, it is more and more widely used in other areas of industry or economy—health care, smart energy, copyright protection [15,16,17,18,19,20]. Originally blockchain technology was used to create a peer-to peer network and focused on cryptography and smart contracts [21,22,23]. Illustrating the current, extensive range of blockchain technology use, one can use the visualization (Figure 1) developed by Casino et al. [24].
By reviewing the literature in blockchain and the possibilities of its use, Xu et al. [24] pointed to, emphasized by many researchers [11,25,26,27,28,29,30], a feature that enables the collection and processing of vast amounts of data in real-time. It is the fundamental advantage of this technology, which implies such extensive use. Hence, the financial area has become a natural sector for using this technology [31]. Two branches of blockchain use out of the possibilities of using this technology indicated in Figure 1 [24] relate to: economy and industry, as well as data management. The organization of production processes, supply chains, and warehouse management requires processing considerable information. This is another area that is within the scope of the possibility of adopting blockchain technology [32,33]. Other areas of blockchain application are: medical sector [34,35,36,37,38,39,40,41], education [42] or management and logistics [43,44]. Since, as many researchers emphasize, blockchain is primarily a kind of database [21,45,46], which supports the reading and transmission of data (information). It is based on a decentralized structure that allows direct contact of users without the participation of an intermediary and at the same time ensures the security of event logs with the help of the use of a time stamp [47,48]. The existing areas of blockchain technology use have focused on financial applications or the processing of large amounts of data, e.g., personal data in medical or insurance services. Bui et al. [49] by reviewing the literature in the blockchain area, they systematized and classified the research areas presented in the literature. Bui et al. divided the publications of research results by category into: inherent characteriscs of a blockchain and add-ons to a blockchain. The first category includes publications that described blockchain features such as decentralization, immutability and transparency. In the second category, however, publications were grouped according to such features of blockchain technology as: authencity, privacy, smart contracts, incenvies and deployment.
Zhang, Y et al. [50] and Tang et al. [51] indicate a great potential in the integration of blockchain platforms with IoT, and thus the processing of a huge amount of data, which consequently fits into the assumptions of smart city and sustainable development. The main advantages of blockchain technology are: (1) the data that is stored on the blockchain network is a rich source of information in itself, (2) blockchains can enable trusted data analytics environments to share data between multiple entities, adding an element of certainty to data and derived analytical models [51]. Bui et al. claims that the advantages of blockchain are based on a consensus mechanism. The authenticity of information in the chain is determined and verified by most nodes before it is encrypted in blocks. However, most of the existing research takes into account information from objective sources, and very little takes into account information from subjective sources. Researchers who consider such information do not propose an approach to verify its authenticity, and this remains a research gap.
Therefore, is it indicated by Xu et al. [24] the use of blockchain in the areas of IoT and Data Management can be linked and used in the LCA method? The authors point out that the existing literature lacks a guiding framework integrating Blockchain and other relevant technologies for carrying out LCA.

3. Life-Cycle Assessment

Dong et al. [52] (p. 4), while reviewing the literature, indicated the need to compare the environmental performance of buildings. The existing criteria have been developed based on: (1) the level of greenhouse gas emissions, (2) stages of the life cycle of a building, (3) absolute or relative value, (4) analysis of the entire building or its elements, and (5) top-down or bottom-up approaches (Hollbeerg et al. [53]) (see Table 1).
The literature analysis in question shows that the LCA method is increasingly used primarily in manufacturing industries. M. Buyle [54] and A.F. Abd Rashid and S. Yusoff [55] indicate difficulties in the direct use of LCA in construction due to the variety and mass use of materials, long product life cycle, and their enormous technological and urban diversity. S. Hellweg, L.M. Canals [56] and C.K. Anand, B. Amor [57] also emphasize the difficulty of using the LCA method in construction due to the huge amount of data and the inability to compare the tested objects, which is a significant problem when using the LCA method, especially when comparing buildings. This is a significant drawback of the LCA method, which in some cases may undermine the credibility of the obtained results. In order to carry out a systematic assessment of the impact of buildings, the emission levels should be analyzed quantitatively based on the impact analysis of each of the facilities tested. Therefore, each of the tested objects will be assessed separately, and its features will be taken into account, which is necessary for the interpretation of the environmental performance of buildings. Anand and Amor [57] indicate that there is still a research gap in this area, which makes it challenging to conduct a comparative analysis of buildings using the LCA method. Many researchers focused on reviewing the literature in the area of life-cycle assessment and its impact on the environmental assessment of buildings, which undoubtedly allowed to enrich and systematize knowledge in this area, which is an important step towards the elimination of the aforementioned barriers or problems with the use of this method. Khasreen et al. 2009 highlighted the importance of LCA as a decision support tool in the construction sector [58]. Ramesh et al. [59] performed a detailed analysis of the effectiveness of applying the LCA method in the environmental assessment of buildings on a large group of 73 cases from 13 countries. A similar research area was adopted by Sharma et al. [60], who also studied the performance of the LCA in assessing buildings located in different areas, but focused in particular on energy consumption by building types and greenhouse gas emissions. Rashid and Yusoff [55], Chau et al. [25] and Islam et al. [61] reviewed the LCA, Life Cycle Energy Analysis (LCEA) and Life-cycle cost analysis (LCCA) methods to distinguish building materials that have a significant impact on the environment. The problems with using the LCA method to compare the impact of individual buildings on the environment indicated by Anand and Amor [57] were analyzed by Soust-Verdaguer et al. [27], who identified possible simplifications for each study to develop LCA. A similar research area—verifications of the application nature of the LCA method for assessing the construction sector were carried out by Saynajoki et al. [26]. The applicative nature of LCA can be found in work by Vilches et al. [62], who investigated the impact on the environmental assessment of renovations and renovations of buildings carried out using the LCA method. Further possibilities of using LCA in Building Information Modeling (BIM) were investigated by: Lu et al. [63], Llatas et al. [64] and Potrc Obrecht et al. [65]. Lu et al. [63] performed a critical analysis of BIM integrated with LCA and life-cycle costing (LCC). Llatas et al. [64] focused on the possibility of integrating the Life Cycle Sustainability Assessment (LCSA) with the process of building design and BIM. Potrc Obrecht et al. [65] analyzed the advantages and disadvantages of various methods of the BIM integration process with LCA. The construction area is extensive, hence attempts to use the LCA method also for individual construction products. Yurong Zhang et al. [66] undertook a literature review on applying the LCA method in the concrete production process with the use of ore waste recycling. Concrete is the most widely used construction product. Its annual consumption is estimated at between 13 and 21 trillion tonnes [67]. Sustainable development requirements and the considerable production needs of concrete promote the use of waste materials in its production. The use of recycled aggregate concrete (RAC) is becoming more and more common, and the LCA method allows to compare the environmental impact of concrete production using the traditional natural aggregate concrete (NAC) and RAC methods [2,68,69]. Dong et al. [52] (p. 4), while reviewing the literature, indicated the need to compare the environmental performance of buildings. The existing criteria have been developed based on: (1) the level of greenhouse gas emissions, (2) stages of the life cycle of a building, (3) absolute or relative value, (4) analysis of the entire building or its elements, and (5) top-down or bottom-up approaches (Hollbeerg et al. [53]) (see Table 1).
To answer the research question—what emission levels should a building have throughout its life cycle, for different impact categories, respectively, Dong et al. [52] applied two research methods: (1) case study selection and (2) comparative analysis using CML 2001 [70] and IMPACT 2002+ [61]. As a result of the research, the factors influencing the environment of the building’s life cycle (including three stages: (1) production, (2) use and (3) end-of-life) were identified and grouped by categories (Table 2).
Dong et al. [52] indicated a correlation between the suggested categories, but two of them deserve special attention: climate change and energy depletion. Comparing types based on different units of measurement requires their prior normalization (Figure 2).
A literature review by Dong et al. [52] deserves special attention, as it touched upon the problems of comparing buildings using the LCA method, previously highlighted by Anand and Amor [57], or by Soust-Verdaguer et al. [27]. The conducted analysis of as many as 105 cases allowed to observe significant discrepancies for all the indicated impact categories. Dong et al. [52] reported comparative analysis of LCA results not always mentioned climate change, and depletion of energy sources are essential impact categories. In general, LCA is a method that allows to estimate the cumulative environmental and social effects associated with the production of a product or the provision of a service. [72,73]. An important element of the use of LCA in the implementation of sustainable development is the identification of key areas of the production process that have the most important impact on the environment [74]. Currently, a significant burden on LCA is access to information within the entire life cycle of a product, which is crucial for its effectiveness and the ability to estimate its environmental impact [75,76]. The effectiveness of using LCA to assess the impact on the environment and its barriers can be analyzed on a wide level—systemic, organizational and the enterprise itself. The systemic barrier is the geographical complexity of supply chains and production processes, the use of outsourcing significantly reduces the possibility of obtaining data necessary to assess the impact of a manufactured product or service using the LCA method. On an organizational level, individual suppliers often do not keep the necessary production process data, and consumers still have a limited understanding of environmental issues. Barriers at the enterprise level result from limited financial resources or limited human resources [77]. In addition, the problem of the possibility of testing the impact on the environment with the dispersed organization of production processes also arises from the legal framework [78]. Taking into account the specificity of production processes, the LCA method must therefore be based on assumptions and simplifications, which is its significant limitation [79,80,81,82].
There are two LCA methodologies in the literature: retrospective and prospective. The retrospective LCA describes environmentally significant flows related to the life of the product and its subsystems. The goal of a prospective LCA is to describe how environmentally relevant flows will change in response to possible decisions [83,84]. Both retrospective and prospective LCA analyzes have methodological limitations that result from access to data and their standardization [81].

4. Life-Cycle Assessment Based on Blockchain Technology

The research question posed in this article regarding the possibility of supporting the use of blockchain technology in the LCA method requires illustrating its impact on the traditional structure of the LCA model [68] (Figure 3). It is worth recalling that blockchain technology allows: (1) to ensure traceability and transparency of the goal and scope definition, (2) at the inventory analysis level—by using the Internet of Things (IoT) concept, collecting and integrating data collected in real-time, and (3) at the level of impact assessment—create analytical forms [85] (Figure 4).
The four phases (levels) of the LCA method defined by the ISO standard are supported by blockchain allowing operational excellence at all levels. The problem of the analysis and comparability of a large number of data in the LCA method, indicated in the literature on the subject, appears at its first stage. According to the assumption, LCA should comprehensively examine the product life cycle, from obtaining raw materials, production, use of the product, its reuse, maintenance, recycling, and finally its disposal [86]. The time constraints mentioned by the researchers, data availability, and financial resources will have the final impact on the effectiveness of the LCA method [33]. Genovese et al. [87] indicate that the use of blockchain solves other LCA problems of quantitative data regarding material and energy consumption in production processes, which are diagnosed by Rebitzer et al. [88] on the second level. The use of blockchain and IoT technologies at the third level of the LCA—impact assessment allows for much more detailed analyzes. The IoT technology is supported by sensors and devices that generate a huge amount of data in real-time, which allows for a more precise determination of the potential influence of the discussed impact categories, e.g., energy consumption or climate change [71,89,90]. The use of blockchain in the three phases of the LCA method allows, in the last, fourth—interpretative stage, to properly assess the product life cycle based only on relevant data. Moreover, the mentioned collection of vast amounts of data in real-time significantly increases the possibilities and functionalities of the LCA method: better use of production resources [91,92], more efficient management of supply chains [93], reduction of production time [94], and consequently gaining a competitive advantage by enterprises [95].
The aforementioned advantage of blockchain technology—the ability to collect, process and analyze huge amounts of data in real time, which is the basic element of correct LCA estimation, may also be its greatest threat. Sameri at al. indicate the problem of access to data and competitive advantage. Blockchain technology would facilitate the sharing of information through LCA activities, and some stakeholders, e.g., the company’s management or shareholders, may consider access to such information as an element of a competitive advantage, and therefore may consequently consider it confidential [96]. Hence, restricting access to information would significantly hamper LCA implementations with blockchain technology [97]. Another factor determining the possibility of using blockchain in LCA is the participation of many stakeholders involved in the process of collecting and processing data (e.g., an extensive production process involving several entities), which is a significant challenge in the organization and management of this process [98,99].
Teh et al. studied the possibilities of using blockchain in the implementation of LCA as part of a sustainable development policy and strategy on the example of the materials industry, in particular, they examined how the use of blockchain in LCA can meet the challenges of integrity, traceability and data transparency [100]. The implementation of new technologies allows to achieve new possibilities, but a frequent problem in life cycle assessment is still low availability of life cycle inventory (LCI) [101,102,103]. Certainly, new technologies such as blockchain, IoT will allow to collect, combine and analyze large amounts of data, which will revolutionize the data inventory process necessary for the effective use of LCA [104]. Still, a significant limitation is the relatively low dissemination of these technologies. A successful example of blockchain implementation is the Dutch dairy sector, where the data inventory process (LCI) lasted up to several months, and the use of the application programming interface (API) made it possible to shorten this period to zero and ensure almost immediate access to this data, and thus increased the effectiveness of the method LCA. [105]. The energy sector is another example where blockchain technology successfully increases the economic and environmental efficiency of the energy production process. The benefits of using blockchain include, among others: reducing transaction costs by eliminating or reducing the need for intermediaries in operating the system, increasing the consistency of energy standards, collecting data on energy production and CO2 emissions in real time [106].

5. Conclusions

Supporting the LCA method with blockchain technology is undoubtedly the right direction of increasing the effectiveness and eliminating the limitations of this method for calculating the environmental impact assessment. In addition, the ability to process data in real-time thanks to the use of IoT allows for broader use of LCA in every branch of the economy or industry. In this article, the authors focus on using the LCA method in sectors with the most significant impact on the environment. Still, a more common measurement of individual elements of production chains in all economic areas is advisable. It will allow for the collection of data and their ongoing analysis, optimization of production processes, reduction of production costs, rational management of natural resources, and ultimately increasing competitiveness. The use of blockchain technology will allow for a more precise determination of the impact of the economy or a particular product on the environment and has a measurable economic feature. This trend is not only in line with the EU strategy and priorities [1], but is also of interest to Corporate Social Responsibility (CSR) [107,108]. The literature review indicates the need for further research in the field of analysis of potential areas of use of LCA based on blockchian technology [45,49,50,100,109,110,111].
However, the authors point to the existence of a research gap in the study of the effectiveness of collecting and analyzing data using blockchain technology when conducting LCA. Conducting further research in this direction will allow us to better verify the usefulness of blockchain in eliminating the current burdens of the LCA method.

Author Contributions

Conceptualization, R.K. and P.M.; Methodology, R.K., P.M., G.T.M. and J.W.; Project administration, P.M. and J.W.; Resources, P.M.; Supervision, R.K.; Writing—original draft, R.K., P.M. and G.T.M.; Writing—review & editing, R.K., P.M., G.T.M. and J.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was not supported by any external source. The authors take all responsibility to prepare and conduct research.

Data Availability Statement

The graphs presented in the publication were taken from publicly available scientific articles. Detailed information about the source of the publication is attached to each graph.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. European Commission Website. A European Green Deal. Available online: https://ec.europa.eu/info/strategy/priorities-2019-2024/european-green-deal_en (accessed on 8 October 2020).
  2. International Organization for Standardization Website. ISO 14001:2015. Environmental Management Systems—Requirements with Guidance for Use. Available online: https://www.iso.org/standard/60857.html (accessed on 8 October 2021).
  3. Hauschild, M.Z.; Rosenbaum, R.K.; Olsen, S.I. Life Cycle Assessment. In Theory and Practice; Springer International Publishing: Cham, Switzerland, 2018. [Google Scholar] [CrossRef]
  4. Guinée, J.B.; Gorrée, M.; Heijungs, R.; Huppes, G.; Kleijn, R.; de Haes, H.A.; Van der Voet, E.; Wrisberg, M.N. Life Cycle Assessment, an Operational Guide to ISO Standards. Available online: https://www.nikkakyo.org/sites/default/files/ICCA_LCA_Executive_Guide_en_0.pdf (accessed on 10 October 2021).
  5. Guinée, J.B.; Heijungs, R.; Huppes, G.; Zamagni, A.; Masoni, P.; Buonamici, R.; Ekvall, T.; Rydberg, T. Life Cycle Assessment: Past, Present, and Future. Environ. Sci. Technol. 2011, 45, 90–96. [Google Scholar] [CrossRef]
  6. Karaszewski, R.; Modrzyński, P.; Modrzyńska, J. The Use of Blockchain Technology in Public Sector Entities Management: An Example of Security and Energy Efficiency in Cloud Computing Data Processing. Energies 2021, 14, 1873. [Google Scholar] [CrossRef]
  7. Kumar, V.D. How Blockchain Impact Energy Sector. Available online: https://www.blockchain-council.org/blockchain/how-blockchain-impact-energy-sector/ (accessed on 22 February 2021).
  8. Lakshmi, N.; Sricharan, S. Blockchain: Single Source of truth in Shared Services? An Empirical Paper on the Relevance of Blockchain for Shared Services. Int. J. Recent Technol. Eng. 2019, 7, 6. [Google Scholar]
  9. Lin, Y.-P.; Petway, J.R.; Lien, W.-Y.; Settele, J. Blockchain with Artificial Intelligence to Efficiently Manage Water Use under Climate Change. Environment 2018, 5, 34. [Google Scholar] [CrossRef] [Green Version]
  10. Paech, P. The Governance of Blockchain Financial Networks. Mod. Law Rev. 2017, 80, 1073–1110. [Google Scholar] [CrossRef]
  11. World Energy Council. The Developing Role of Blockchain White Paper; World Energy Council: London, UK, 2017. [Google Scholar]
  12. Zikratov, I.; Kuzmin, A.; Akimenko, V.; Niculichev, V.; Yalansky, L. Ensuring data integrity using blockchain technology. In Proceedings of the 2017 20th Conference of Open Innovations Association (FRUCT), Saint Petersburg, Russia, 3–7 April 2017. [Google Scholar]
  13. Nakamoto, S. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008. Available online: https://bitcoin.org/bitcoin.pdf (accessed on 17 October 2021).
  14. Iansiti, M.; Lakhani, K.R. The truth about blockchain. Harv. Bus. Rev. 2017, 95, 118–127. [Google Scholar]
  15. Engelhardt, M.A. Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector. Technol. Innov. Manag. Rev. 2017, 7, 22–34. [Google Scholar] [CrossRef]
  16. Hyvarinen, H.; Risius, M.; Friis, G. A Blockchain-based approach towards overcoming financial fraud in public sector services. Bus. Inf. Syst. Eng. 2017, 59, 441–456. [Google Scholar] [CrossRef] [Green Version]
  17. Kim, H.M.; Laskowski, M. Toward an ontology-driven blockchain design for supply-chain provenance. Intell. Syst. Account. Financ. Manag. 2018, 25, 18–27. [Google Scholar] [CrossRef]
  18. O’Dair, M.; Beaven, Z. The networked record industry: How blockchain technology could transform the record industry. Strateg. Chang. 2017, 26, 471–480. [Google Scholar] [CrossRef]
  19. Radanovic, I.; Likić, R. Opportunities for Use of Blockchain Technology in Medicine. Appl. Health Econ. Health Policy 2018, 16, 583–590. [Google Scholar] [CrossRef] [PubMed]
  20. Savelyev, A. Copyright in the blockchain era: Promises and challenges. Comput. Law Secur. Rev. 2018, 34, 550–561. [Google Scholar] [CrossRef] [Green Version]
  21. Christidis, K.; Devetsikiotis, M. Blockchains and smart contracts for the internet of things. IEEE Access 2016, 4, 2292–2303. Available online: https://people.cs.pitt.edu/~mosse/courses/cs3720/blockchain-iot.pdf (accessed on 12 October 2021). [CrossRef]
  22. Cruz, J.P.; Kaji, Y.; Yanai, N. RBAC-SC: Role-based access control using smart contract. IEEE Access 2016, 6, 12240–12251. Available online: https://ieeexplore.ieee.org/document/8307397 (accessed on 14 October 2021). [CrossRef]
  23. Kraft, D. Difficulty control for blockchain-based consensus systems. Peer-Peer Netw. Appl. 2015, 9, 397–413. [Google Scholar] [CrossRef]
  24. Xu, M.; Chen, X.; Kou, G. A systematic review of blockchain. Financ. Innov. 2019, 5, 27. [Google Scholar] [CrossRef] [Green Version]
  25. Chau, C.K.; Leung, T.M.; Ng, W.Y. A review on life cycle assessment, life cycle energy assessment and life cycle carbon emis-sions assessment on buildings. Appl. Energy 2015, 143, 395–413. [Google Scholar] [CrossRef]
  26. Säynäjoki, A.; Heinonen, J.; Junnila, S.; Horvath, A. Can life-cycle assessment produce reliable policy guidelines in the building sector? Environ. Res. Lett. 2017, 12, 13001. [Google Scholar] [CrossRef] [Green Version]
  27. Soust-Verdaguer, B.; Llatas, C.; García-Martínez, A. Simplification in life cycle assessment of single-family houses: A review of recent developments. Build. Environ. 2016, 103, 215–227. [Google Scholar] [CrossRef] [Green Version]
  28. Swan, M. Anticipating the Economic Benefits of Blockchain. Technol. Innov. Manag. Rev. 2017, 7, 6–13. [Google Scholar] [CrossRef]
  29. Tapscott, D.; Tapscott, A. Blockchain Revolution: How the Technology behind Bitcoin Is Changing Money, Business, and the World; Portfolio: New York, NY, USA, 2016; 368p. [Google Scholar]
  30. Zadorozhnyi, Z.-M.V.; Muravskyi, V.; Shevchuk, O.A. Management accounting of electronic transactions with the use of cryptocurrencies. Financ. Credit Act. Probl. Theory Pract. 2018, 3, 169–177. [Google Scholar] [CrossRef] [Green Version]
  31. Gomber, P.; Kauffman, R.J.; Parker, C.; Weber, B.W. On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. J. Manag. Inf. Syst. 2018, 35, 220–265. [Google Scholar] [CrossRef]
  32. Ashta, A.; Biot-Paquerot, G. FinTech evolution: Strategic value management issues in a fast changing industry. Strateg. Chang. 2018, 27, 301–311. [Google Scholar] [CrossRef]
  33. Matos, S.; Hall, J. Integrating sustainable development in the supply chain: The case of life cycle assessment in oil and gas and agricultural biotechnology. J. Oper. Manag. 2007, 25, 1083–1102. [Google Scholar] [CrossRef]
  34. Brogan, J.; Baskaran, I.; Ramachandran, N. Authenticating Health Activity Data Using Distributed Ledger Technologies. Comput. Struct. Biotechnol. J. 2018, 16, 257–266. [Google Scholar] [CrossRef] [PubMed]
  35. Manion, S.T.; Bizouati-Kennedy, Y. Blockchain for Medical Research: Accelerating Trust in Healthcare; Taylor & Francis: Boca Raton, FL, USA, 2020; p. 150. [Google Scholar]
  36. Ramzi Abujamra, D. Blockchain Applications in Healthcare and the Opportunities and the Advancements due to the New Information Technology Framework, in Advance in Computers. In Role of Blockchain Technology in IoT Applications; Shiho-Kim, G.C.D., Zhang, P., Eds.; Academic Press: Cambridge, MA, USA, 2019; Volume 115, Chapter 5; pp. 141–154. [Google Scholar]
  37. Randall, D.; Goel, P.; Abujamra, R. Blockchain Applications and Use Cases in Health Information Technology. J. Health Med. Inform. 2017, 8, 1–4. [Google Scholar] [CrossRef]
  38. Shae, Z.; Tsai, J.J. On the Design of a Blockchain Platform for Clinical Trial and Precision Medicine. In Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, USA, 5–8 June 2017; pp. 1972–1980. [Google Scholar]
  39. Shetty, S.; Liang, X.; Bowden, D.; Zhao, J.; Zhang, L. Blockchain-Based Decentralized Accountability and Self-Sovereignty in Healthcare Systems. In Business Transformation through Blockchain; Treiblmaier, H., Beck, R., Eds.; Springer International Publishing: Cham, Switzerland, 2019; Volume 2, pp. 119–149. [Google Scholar]
  40. Wang, X.; Shi, H. Research on Container Transportation Application Based on Blockchain Technology. In Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering, Beijing, China, 21–23 December 2018; pp. 277–281. [Google Scholar]
  41. Wutthikarn, R.; Hui, Y.G. Prototype of blockchain in dental care service application based on hyperledger composer in hyperledger fabric framework. In Proceedings of the 2018 22nd International Computer Science and Engineering Conference (ICSEC), Chiang Mai, Thailand, 21–24 November 2018; pp. 1–4. [Google Scholar]
  42. Mehendale, M.S.; Kamble, A. Trust the system–blockchain technology and its application in education. J. Xian Univ. Archit. Technol. 2019. Available online: http://www.xajzkjdx.cn/gallery/128-dec2019.pdf (accessed on 21 November 2021).
  43. Álvarez-Díaz, N.; Herrera-Joancomartí, J.; Caballero-Gil, P. Smart contracts based on blockchain for logistics management. In Proceedings of the 1st International Conference on Medical and Health Informatics, Taichung, Taiwan, 20–22 May 2017; pp. 1–8. [Google Scholar]
  44. Polishchuk, A.I.Y.; Dyba, O. SMART-contracts via blockchain as the innovation tool for SMEs development. Econ. Stud. J. 2019, 39–53. Available online: https://www.ceeol.com/search/article-detail?id=831391 (accessed on 29 October 2021).
  45. Catalini, C.S.; Gans, J.S. Some Simple Economics of the Blockchain. 2016. Available online: https://ssrn.com/abstract=2887234 (accessed on 28 October 2021).
  46. Hofmann, A. Building Scalable Blockchain Applications—A Decision Process. In Designing for Digital Transformation. Co-Creating Services with Citizens and Industry; Springer International Publishing: Cham, Switzerland, 2020; pp. 309–320. [Google Scholar] [CrossRef]
  47. Gipp, B.; Meuschke, N.; Gernandt, A. Decentralized Trusted Timestamping using the Crypto Currency Bitcoin. In Proceedings of the iConference 2015 (to Appear), Newport Beach, CA, USA, 24–27 March 2015; Available online: http://ischools.org/the-iconference/ (accessed on 15 September 2021).
  48. Zyskind, G.; Nathan, O.; Pentland, A. Decentralizing Privacy: Using Blockchain to Protect Personal Data. In Proceedings of the 2015 IEEE Security and Privacy Workshops, San Jose, CA, USA, 21–22 May 2015; pp. 180–184. [Google Scholar] [CrossRef]
  49. Bui, H.T.; Hussain, O.K.; Saberi, M.; Hussain, F. Assessing the authenticity of subjective information in the blockchain: A survey and open issues. World Wide Web 2021, 24, 483–509. [Google Scholar] [CrossRef]
  50. Zhang, Y.; Xu, X.; Liu, A.; Lu, Q.; Xu, L.; Tao, F. Blockchain-based trust mechanism for IoT-based smart manufacturing system. IEEE Trans. Comput. Soc. Syst. 2019, 6, 1386–1394. [Google Scholar] [CrossRef]
  51. Tang, B.; Kang, H.; Fan, J.; Li, Q.; Sandhu, R. IoT Passport. In Proceedings of the 24th ACM Symposium on Access Control Models and Technologies, Toronto, ON, Canada, 3–6 June 2019; pp. 83–92. [Google Scholar]
  52. Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Build. Environ. 2021, 204, 108162. [Google Scholar] [CrossRef]
  53. Hollberg, A.; Lützkendorf, T.; Habert, G. Top-down or bottom-up?—How environmental benchmarks can support the design process. Build. Environ. 2019, 153, 148–157. [Google Scholar] [CrossRef]
  54. Buyle, M.; Braet, J.; Audenaert, A. Life cycle assessment in the construction sector: A review. Renew. Sustain. Energy Rev. 2013, 26, 379–388. [Google Scholar] [CrossRef]
  55. Rashid, A.F.A.; Yusoff, S. A review of life cycle assessment method for building industry. Renew. Sustain. Energy Rev. 2015, 45, 244–248. [Google Scholar] [CrossRef] [Green Version]
  56. Hellweg, S.; Canals, L.M. Emerging approaches, challenges and opportunities in life cycle assessment. Science 2014, 344, 1109–1113. [Google Scholar] [CrossRef] [PubMed]
  57. Anand, C.K.; Amor, B. Recent developments, future challenges and new research directions in LCA of buildings: A critical review. Renew. Sustain. Energy Rev. 2017, 67, 408–416. [Google Scholar] [CrossRef]
  58. Khasreen, M.M.; Banfill, P.F.G.; Menzies, G.F. Life-Cycle Assessment and the Environmental Impact of Buildings: A Review. Sustainability 2009, 1, 674–701. [Google Scholar] [CrossRef]
  59. Ramesh, T.; Prakash, R.; Shukla, K.K. Life cycle energy analysis of buildings: An overview. Energy Build. 2010, 42, 1592–1600. [Google Scholar] [CrossRef]
  60. Sharma, A.; Saxena, A.; Sethi, M.; Shree, V. Varun Life cycle assessment of buildings: A review. Renew. Sustain. Energy Rev. 2011, 15, 871–875. [Google Scholar] [CrossRef]
  61. Islam, H.; Jollands, M.; Setunge, S. Life cycle assessment and life cycle cost implication of residential buildings—A review. Renew. Sustain. Energy Rev. 2015, 42, 129–140. [Google Scholar] [CrossRef]
  62. Vilches, A.; Garcia-Martinez, A.; Sanchez-Montanes, B. Life cycle assessment (LCA) of building refurbishment: A literature review. Energy Build. 2017, 135, 286–301. [Google Scholar] [CrossRef]
  63. Lu, K.; Jiang, X.; Yu, J.; Tam, V.W.; Skitmore, M. Integration of life cycle assessment and life cycle cost using building information modeling: A critical review. J. Clean. Prod. 2021, 285, 125438. [Google Scholar] [CrossRef]
  64. Llatas, C.; Soust-Verdaguer, B.; Passer, A. Implementing Life Cycle Sustainability Assessment during design stages in Building Information Modelling: From systematic literature review to a methodological approach. Build. Environ. 2020, 182, 107164. [Google Scholar] [CrossRef]
  65. Obrecht, T.P.; Röck, M.; Hoxha, E.; Passer, A. BIM and LCA Integration: A Systematic Literature Review. Sustainability 2020, 12, 5534. [Google Scholar] [CrossRef]
  66. Zhang, Y.; Luo, W.; Wang, J.; Wang, Y.; Xu, Y.; Xiao, J. A review of life cycle assessment of recycled aggregate concrete. Constr. Build. Mater. 2019, 209, 115–125. [Google Scholar] [CrossRef]
  67. World Business Council for Sustainable Development (WBCSD). The Cement Sustainability Initiative; World Business Council for Sustainable Development: Geneva, Switzerland, 2009. [Google Scholar]
  68. Singh, R.K.; Murty, H.; Gupta, S.; Dikshit, A.K. An overview of sustainability assessment methodologies. Ecol. Indic. 2012, 15, 281–299. [Google Scholar] [CrossRef]
  69. Yang, J.; Du, Q.; Bao, Y. Concrete with recycled concrete aggregate and crushed clay bricks. Constr. Build. Mater. 2011, 25, 1935–1945. [Google Scholar] [CrossRef]
  70. Guinée, J.B.; Gorrée, M.; Heijungs, R.; Huppes, G.; Kleijn, R.; de Koning, A.; van Oers, L.; Sleeswijk, A.W.; Suh, S.; de Haes, H.A.; et al. Handbook on Life Cycle Assessment. Operational Guide to the ISO Standards. I: LCA in Perspective. IIa: Guide. IIb: Operational Annex. III: Scientific Background; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2002; p. 692. ISBN 1-4020-0228-9. [Google Scholar]
  71. Kouhizadeh, M.; Sarkis, J. Blockchain Practices, Potentials, and Perspectives in Greening Supply Chains. Sustainability 2018, 10, 3652. [Google Scholar] [CrossRef] [Green Version]
  72. Gonzales, C.J. Life Cycle Assessment. In Green Metrics; Anastas, P.T., Constable, D.J., Gonzales, C.J., Eds.; Wiley: Hoboken, NJ, USA, 2018; pp. 95–118. [Google Scholar]
  73. Paik, H.-Y.; Xu, X.; Bandara, H.M.N.D.; Lee, S.U.; Lo, S.K. Analysis of Data Management in Blockchain-Based Systems: From Architecture to Governance. IEEE Access 2019, 7, 186091–186107. [Google Scholar] [CrossRef]
  74. Linkov, I.; Trump, B.D.; Wender, B.A.; Seager, T.P.; Kennedy, A.J.; Keisler, J.M. Integrate life-cycle assessment and risk analysis results, not methods. Nat. Nanotechnol. 2017, 12, 740–743. [Google Scholar] [CrossRef]
  75. Ortiz, O.; Castells, F.; Sonnemann, G. Sustainability in the construction industry: A review of recent developments based on LCA. Constr. Build. Mater. 2009, 23, 28–39. [Google Scholar] [CrossRef]
  76. Sinistore, J. Driving Sustainability through Life Cycle Assessment, Renewable Energy and Blockchain. 2018. Available online: https://www.wsp.com/en-AU/insights/blockchain-driving-sustainability (accessed on 28 November 2021).
  77. van der Meer, Y. Life Cycle Assessment: Benefts and Limitations. 2018. Available online: https://fibrenet.eu/index.php?id=blog-post-eleven (accessed on 21 November 2021).
  78. Mortimer, C. Enablers and Barriers to Adoption of Life Cycle Management. NZLCM Centre Working Paper Series: Paper 01/11. 2011. Available online: https://www.lcm.org.nz/sites/default/files/files/Mortimer%20FINAL.pdf (accessed on 27 November 2021).
  79. Curran, M. Strengths and Limitations of Life Cycle Assessment. In Background and Future Prospects in Life Cycle Assessment. LCA Compendium—The Complete World of Life Cycle Assessment; Klöpffer, W., Ed.; Springer: Dordrecht, The Netherlands. [CrossRef]
  80. Seth, S. Blockchain Solutions to Grow 75% through 2022: IDC. 2019. Available online: https://www.investopedia.com/news/blockchain-solutions-grow75-through-2022-idc/ (accessed on 28 November 2021).
  81. Weidema, B.P.; Ekvall, T.; Heijungs, R. Guidelines for application of deepened and broadened LCA. Deliv. D18 Work Package 2009, 5, 17. [Google Scholar]
  82. Zamagni, A. Critical Review of the Current Research Needs and Limitations Related to ISO-LCA Practice; ENEA: Bologna, Italy, 2008. [Google Scholar]
  83. Ekvall, T.; Tillman, A.-M.; Molander, S. Normative ethics and methodology for life cycle assessment. J. Clean. Prod. 2005, 13, 1225–1234. [Google Scholar] [CrossRef] [Green Version]
  84. Tillman, A.-M. Significance of decision-making for LCA methodology. Environ. Impact Assess. Rev. 2000, 20, 113–123. [Google Scholar] [CrossRef] [Green Version]
  85. Zhang, A.; Zhong, R.Y.; Farooque, M.; Kang, K.; Venkatesh, V.G. Blockchain-based life cycle assessment: An implementation framework and system architecture. Resour. Conserv. Recycl. 2020, 152, 104512. [Google Scholar] [CrossRef]
  86. Christensen, T.H.; Bhander, G.; Lindvall, H.; Larsen, A.W.; Fruergaard, T.; Damgaard, A.; Manfredi, S.; Boldrin, A.; Riber, C.; Hauschild, M. Experience with the use of LCA-modelling (EASEWASTE) in waste management. Waste Manag. Res. 2007, 25, 257–262. [Google Scholar] [CrossRef]
  87. Genovese, A.; Acquaye, A.A.; Figueroa, A.; Koh, S.L. Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications. Omega 2017, 66, 344–357. [Google Scholar] [CrossRef]
  88. Rebitzer, G.; Ekvall, T.; Frischknecht, R.; Hunkeler, D.; Norris, G.; Rydberg, T.; Schmidt, W.-P.; Suh, S.; Weidema, B.P.; Pennington, D.W. Life cycle assessment: Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environ. Int. 2004, 30, 701–720. [Google Scholar] [CrossRef] [PubMed]
  89. Jolliet, O.; Dubreuil, A.; Gloria, T.; Hauschild, M.Z. Progresses in Life Cycle Impact Assessment within the UNEP/SETAC Life Cycle Initiative. Int. J. Life Cycle Assess. 2005, 10, 447–448. [Google Scholar] [CrossRef] [Green Version]
  90. Krishna, I.M.; Manickam, V.; Shah, A.; Davergave, N. Chapter Five—Life Cycle Assessment. In Environmental Management: Science and Engineering for Industry; Butterworth Henneman Elsevier: Oxford, UK, 2017; pp. 57–75. [Google Scholar]
  91. Cai, Y.; Zhu, D. Fraud detections for online businesses: A perspective from block chain technology. Financ. Innov. 2016, 2, 20. [Google Scholar] [CrossRef] [Green Version]
  92. Tao, F.; Zuo, Y.; Xu, L.D.; Zhang, L. IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans. Ind. Inform. 2014, 10, 1547–1557. [Google Scholar]
  93. Zhong, R.Y.; Huang, G.Q.; Lan, S.; Dai, Q.Y.; Chen, X.; Zhang, T. A big data ap proach for logistics trajectory discovery from RFID-enabled production data. Int. J. Prod. Econ. 2015, 165, 260–272. [Google Scholar] [CrossRef]
  94. Zhong, R.Y.; Huang, G.Q.; Dai, Q.Y.; Zhang, T. Mining SOTs and dispatching rules from RFID-enabled real-time shopfloor production data. J. Intell. Manuf. 2012, 25, 825–843. [Google Scholar] [CrossRef]
  95. Galletti, A.; Papadimitriou, D.-C. How Big Data Analytics Are Perceived as a Driver for Competitive Advantage: A Qualitative Study on Food Retailers; Uppsala University Department of Business Studies: Uppsala, Sweden, 2013; p. 53. Available online: http://www.diva-portal.org/smash/get/diva2:641706/FULLTEXT01.pdf (accessed on 12 October 2021).
  96. Buyle, M.; Ben, M.; Hernando, D.; Amaryllis, A.; France, C.; Van den Bergh, W. Quantifying the environmental and economic impact of adding RAP and rejuvenators in asphalt pavements using LCA and LCCA. Rejuvebit 2021. [Google Scholar] [CrossRef]
  97. Curran, M.A.; Mann, M.; Norris, G. The international workshop on electricity data for life cycle inventories. J. Clean. Prod. 2005, 13, 853–862. [Google Scholar] [CrossRef]
  98. Beck, R.; Müller-Bloch, C.; King, J.L. Governance in the blockchain economy: A framework and research agenda. J. Assoc. Inf. Syst. 2018, 19, 1020–1034. [Google Scholar] [CrossRef]
  99. Saberi, S.; Kouhizadeh, M.; Sarkis, J.; Shen, L. Blockchain technology and its relationships to sustainable supply chain management. Int. J. Prod. Res. 2019, 57, 2117–2135. [Google Scholar] [CrossRef] [Green Version]
  100. Trump, B.D.; Florin, M.V.; Matthews, H.S.; Sicker, D.; Linkov, I. Governing the use of blockchain and distributed ledger technologies: Not one-size-fts-all. IEEE Eng. Manag. Rev. 2018, 46, 56–62. [Google Scholar] [CrossRef]
  101. Davis, C.; Nikolic, I.; Dijkema, G.P.J. Industrial Ecology 2.0. J. Ind. Ecol. 2010, 14, 707–726. [Google Scholar] [CrossRef]
  102. Teh, D.; Khan, T.; Corbitt, B.; Ong, C.E. Sustainability strategy and blockchain-enabled life cycle assessment: A focus on materials industry. Environ. Syst. Decis. 2020, 40, 605–622. [Google Scholar] [CrossRef]
  103. Testa, F.; Nucci, B.; Tessitore, S.; Iraldo, F.; Daddi, T. Perceptions on LCA implementation: Evidence from a survey on adopters and nonadopters in Italy. Int. J. Life Cycle Assess. 2016, 21, 1501–1513. [Google Scholar] [CrossRef]
  104. Norris, C.B. Data for social LCA. Int. J. Life Cycle Assess. 2014, 19, 261–265. [Google Scholar] [CrossRef] [Green Version]
  105. Miah, J.H.; Griffiths, A.; McNeill, R.; Halvorson, S.; Schenker, U.; Espinoza-Orias, N.; Morse, S.; Yang, A.; Sadhukhan, J. A framework for increasing the availability of life cycle inventory data based on the role of multinational companies. Int. J. Life Cycle Assess. 2018, 23, 1744–1760. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  106. Mieras, E.; Gaasbeek, A.; Kan, D. How to seize the opportunities of new technologies in life cycle analysis data collection: A case study of the Dutch Dairy Farming Sector. Challenges 2019, 10, 8. [Google Scholar] [CrossRef] [Green Version]
  107. Al Halbusia, H.; Tehseenb, S. Corporate Social Responsibility (CSR): A Literature Review. Malays. J. Bus. Econ. 2017, 4, 30–48. [Google Scholar]
  108. Jackson, A. Corporate Social Responsibility: Tracking the Top Trends, Investopedia. Available online: https://www.investopedia.com/ask/answers/011215/what-are-top-trends-corporate-social-responsibility.asp (accessed on 16 October 2021).
  109. Chen, Z.; Li, Y.; Wu, Y.; Luo, J. The transition from traditional banking to mobile internet finance: An organizational innovation perspective—A comparative study of Citibank and ICBC. Financ. Innov. 2017, 3, 12. [Google Scholar] [CrossRef]
  110. Zhao, J.L.; Fan, S.; Yan, J. Overview of business innovations and research opportunities in blockchain and introduction to the special issue. Financ. Innov. 2016, 2, 28. [Google Scholar] [CrossRef] [Green Version]
  111. Tapscott, D.; Tapscott, A. How blockchain will change organizations. MIT Sloan Manag. Rev. 2017, 58, 10–13. [Google Scholar]
Energies 14 08292 g001 550
Figure 1. Mindmap abstraction of different types of blockchain applications. Source: Casino, F.; Dasaklis, T.K.; Patsakis, C. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics 2019, 36, 62 [24].
Figure 1. Mindmap abstraction of different types of blockchain applications. Source: Casino, F.; Dasaklis, T.K.; Patsakis, C. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics 2019, 36, 62 [24].
Energies 14 08292 g001
Energies 14 08292 g002 550
Figure 2. Normalized medians of impact categories for the entire life cycle of buildings (50-years’ service life). Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [71] p. 12.
Figure 2. Normalized medians of impact categories for the entire life cycle of buildings (50-years’ service life). Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [71] p. 12.
Energies 14 08292 g002
Energies 14 08292 g003 550
Figure 3. Life Cycle Assessment Framework. Source: ISO. Environmental management—Life Cycle Assessment—Principles and Framework. International Organization for Standardization 2011, 3, 20. https://doi.org/10.1016/j.ecolind.2011.01.007 [68].
Figure 3. Life Cycle Assessment Framework. Source: ISO. Environmental management—Life Cycle Assessment—Principles and Framework. International Organization for Standardization 2011, 3, 20. https://doi.org/10.1016/j.ecolind.2011.01.007 [68].
Energies 14 08292 g003
Energies 14 08292 g004 550
Figure 4. Blockchain-based LCA Framework. Source: Zhang, A. et al. Blockchain-based life cycle assessment: An implementation framework and system architecture, Resources, Conservation and Recycling. Volume 152, January 2020, https://doi.org/10.1016/j.resconrec.2019.104512, [85] p. 4.
Figure 4. Blockchain-based LCA Framework. Source: Zhang, A. et al. Blockchain-based life cycle assessment: An implementation framework and system architecture, Resources, Conservation and Recycling. Volume 152, January 2020, https://doi.org/10.1016/j.resconrec.2019.104512, [85] p. 4.
Energies 14 08292 g004
Table
Table 1. Various types of benchmarks of LCA of buildings.
Table 1. Various types of benchmarks of LCA of buildings.
CategoryBenchmarksDescription
LIFE CYCLE STAGESWhole life cycleBenchmark is a value for the whole life cycle of the building.
Life cycle phaseBenchmark is a value for individual life cycle phases.
LEVELS OF VALUESLowest acceptable valueThe limit value is defined as the lowest acceptable value.
Present state of the artThe average or median values of the present state of the art.
Best-practice valueThe best-practice value that has been reached in building projects.
TOP-DOWN OR BOTTOM-UPTop-downBenchmarks are defined based on political targets.
Bottom-upMost of the existing benchmarks are derived from theoretical values.
ABSOLUTE OR RELATIVE VALUESAbsolute valuesBenchmarks are defined as fixed values.
Relative valuesInternal benchmarks are defined according to a reference building.
WHOLE BUILDINGS OR BUILDING ELEMENTSWhole buildingBenchmarks are for the whole building.
Building elementsBenchmarks are for the individual building elements.
Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [52] p. 4.
Table
Table 2. Description of the impact categories and the conversion factors.
Table 2. Description of the impact categories and the conversion factors.
Impact CategoryIndicatorUnitReferecne MethodConversion Factors
CLIMATE CHANGEGlobal warming potential for time horizon 100 yearskg CO2 eqCMLNon Specified: 1
TRACI:1.012
IMPACT
2002+: 1.048
ReCiPe: 0.983
ENERGY DEPLETIONAbiotic depletion of fossil fuel related to the lower heating valueMJCMLNon specified: 1
TRACI:
12.672
IMPACT
2002+: 0.958
ReCiPe:
42.748
EUTROPHICATIONEutrophication potential of emission of nutrientskg PO4 eqCMLNon specified: 1 TRACI: 0.471 IMPACT 2002+: 10.397 ReCiPe: 3.951
ACIDIFICATIONAcidification potentialkg SO2 eqCMLNon specified: 1
TRACI: 1.061
IMPACT
2002+: 1.058
ReCiPe: 1.227
OZONE DEPLETIONOzone depletion
potential of different
gases		kg CFC-11 eqCMLNon specified: 1 TRACI: 0.770 IMPACT 2002+: 1 ReCiPe: 0.159
PARTICULATE MATTERFine particulate matter equivalent for respiratory inorganicskg PM2.5 eqIMPACT 2002+Non specified: 1 TRACI: 0.942 ReCiPe: 0.659
HUMAN TOXICITYHuman toxicity potential describing fate, exposure and effects of toxic substanceskg 1,4-DB eqCMLNon specified: 1 TRACI: N.A. IMPACT 2002+: N.A. ReCiPe: N.A.
Note: N.A.—not available. Source: Dong, Y.; Ng, S.T.; Liu, P. A comprehensive analysis towards benchmarking of life cycle assessment of buildings based on systematic review. Building and Environment 2021, 204, 108162, https://doi.org/10.1016/j.buildenv.2021.108162, [52] p. 6.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Karaszewski, R.; Modrzyński, P.; Müldür, G.T.; Wójcik, J. Blockchain Technology in Life Cycle Assessment—New Research Trends. Energies 2021, 14, 8292. https://doi.org/10.3390/en14248292

AMA Style

Karaszewski R, Modrzyński P, Müldür GT, Wójcik J. Blockchain Technology in Life Cycle Assessment—New Research Trends. Energies. 2021; 14(24):8292. https://doi.org/10.3390/en14248292

Chicago/Turabian Style

Karaszewski, Robert, Paweł Modrzyński, Gözde Türkmen Müldür, and Jacek Wójcik. 2021. "Blockchain Technology in Life Cycle Assessment—New Research Trends" Energies 14, no. 24: 8292. https://doi.org/10.3390/en14248292

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop