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  • AJET Bibliometrics

    Heinrich, Eva; Henderson, Michael; Redmond, Petrea (ASCILITE, 2020-03-20)
    The bibliometric data in this editorial provide readers with information about the journal’s publication, review and article access statistics, the articles attracting the most interest over the past year and the citation performance of the journal.
  • Does Administrative Approval Impede Low-Quality Innovation? Evidence from Chinese Manufacturing Firms

    Haiwei Jiang; Shiyuan Pan; Xiaomeng Ren (MDPI AG, 2020-03-01)
    Sustainable economic development is tightly connected to substantial innovation which can be improved by reducing low-quality innovation. This paper constructs a theoretical framework to present the ultimate relationship between administrative approval and sustainability. In order to verify the research hypotheses, we define the dormant patents whose patent rights are terminated due to non-payment of renewal fees to measure the low-quality innovation of Chinese manufacturing firms. By using the merged firm-level data between 1998 and 2007 and collected information on whether a city establishes the administrative approval center (AAC), and employing a difference-in-difference (DID) approach, we identify the impacts of administrative approval and firms’ low-quality innovation. First, the results reveal that administrative approval reduces the firms’ low-quality innovation. Second, administrative approval has a smaller impact on the low-quality innovation for state-owned enterprises (SOE). Third, three mechanisms are uncovered through which administrative approval impedes low-quality innovation: enhancing market competition, changing the direction of innovation, and optimizing research and development (R&D) investment strategy.
  • Analyzing Driver Drowsiness: From Causes to Effects

    Sónia Soares; Tiago Monteiro; António Lobo; António Couto; Liliana Cunha; Sara Ferreira (MDPI AG, 2020-03-01)
    Drowsiness and fatigue are major safety issues that cannot be measured directly. Their measurements are sustained on indirect parameters such as the effects on driving performance, changes in physiological states, and subjective measures. We divided this study into two distinct lines. First, we wanted to find if any driver’s physiological characteristic, habit, or recent event could interfere with the results. Second, we aimed to analyze the effects of subjective sleepiness on driving behavior. On driving simulator experiments, the driver information and driving performance were collected, and responses to the Karolinska Sleepiness Scale (KSS) were compared with these parameters. The results showed that drowsiness increases when the driver has suffered a recent stress situation, has taken medication, or has slept fewer hours. An increasing driving time is also a strong factor in drowsiness development. On the other hand, robustness, smoking habits, being older, and being a man were revealed to be factors that make the participant less prone to getting drowsy. From another point of view, the speed and lane departures increased with the sleepiness feeling. Subjective drowsiness has a great correlation to drivers’ personal aspects and the driving behavior. In addition, the KSS shows a great potential to be used as a predictor of drowsiness.
  • Seismic Vulnerability Assessment of Existing Reinforced Concrete Buildings in Urban Centers

    Tiago Miguel Ferreira; Hugo Rodrigues; Romeu Vicente (MDPI AG, 2020-03-01)
    Despite the recent advances in the analysis of the seismic performance of reinforced concrete structures, the assessment of large building inventories aimed at defining and prioritizing structural retrofitting strategies is still a technically challenging task. This paper aims to contribute to bridging this gap by presenting a simplified methodology for assessing the seismic vulnerability of reinforced concrete buildings, which is then applied to a group of 91 buildings affected by recent earthquakes with different macroseismic intensities. The presented methodology is based on the evaluation of eight parameters associated with different factors that affect the seismic response of the building, namely its structural features, foundation conditions, and position within the urban mesh. The formulation of each parameter and the relative weight attributed to each one of them were defined on the basis of post-earthquake damage observation and expert opinion. After defined, the proposed methodology is applied to Faro city center. Based on the results obtained, a cost benefit analysis is made considering a strengthening solution to the buildings with soft-story irregularity.
  • Decision Simulation of Construction Project Delivery System under the Sustainable Construction Project Management

    Ji-Wei Zhu; Li-Nan Zhou; Liang Li; Wajhat Ali (MDPI AG, 2020-03-01)
    Choosing an appropriate project delivery system (PDS) directly affects the achievement of performance goals, and at the same time it is of great significance for sustainable construction project management (SCPM). This paper took the PDS of construction engineering as the research object, took the Design-Build (DB) and the Design-Bid-Build (DBB) as examples, and established the indicator system for determinants of the PDS decision. Based on Multi-Agent Systems (MAS), a decision-making simulation model of the PDS decision was constructed, and this paper analyzed the influence of the project attribute characteristics, policy and market environment, owner ability and preference, and contractor technology and capabilities of the PDS decision. While analyzing the circumstances under which the owners tend to choose DB or DBB, the following conclusions were reached: (1) the contractor technology and capabilities increase faster in DB than in DBB. (2) The PDS with policy and market environment preferences has an advantage in the PDS decision, and the owners are more willing to choose the PDS which was selected previously. (3) The competition mechanism in the construction market will eliminate contractors whose growth rate is too low to meet the needs of projects in the market. The research provides theoretical references for the scientific decision-making of construction enterprises.
  • Modeling the Socioeconomic Metabolism of End-of-Life Tires Using Structural Equations: A Brazilian Case Study

    Euclides Santos Bittencourt; Cristiano Hora de Oliveira Fontes; Jorge Laureano Moya Rodriguez; Salvador Ávila Filho; Adonias Magdiel Silva Ferreira (MDPI AG, 2020-03-01)
    Socioeconomic metabolism (SEM) is the exchange of materials and energy between society and the environment involving the social, economic and environmental sectors. In this paper, a boundary was defined between the economic (consumption) and environmental (waste recovery) limits in a city of 300,000 inhabitants in relation to the circulation (generation, reuse and disposal) of end-of-life tires (ELTs). The objective was to elaborate a theoretical structural model to evaluate the socioeconomic metabolism of waste (SEMw) by means of technical constructs (direct material flows (DMF), reverse material flows (RMF), socioeconomic environment (SEF) and sociodemographic factors (SDF)). Structural Equation Modeling (SEMm) was performed using Partial Least Squares Structural Equation Modeling (SmartPLS) software. The results obtained from the hypotheses show the causal relationships between the technical and social constructs and suggest guidelines for supporting the planning and management of urban solid waste in the collection and final disposal of ELTs. The processed information also contributes to the analysis of the city’s socioeconomic scenarios in relation to the disposal of ELTs. One of the hypotheses tested (RMF have a direct effect on SEMw) shows the importance of managing ELTs through the correct final disposal of waste and recycling. SEMw was evaluated from the perception of the local society and it is concluded that it is possible to plan public policies to avoid the formation of waste inventory in the city.
  • Estimating Soil Available Phosphorus Content through Coupled Wavelet–Data-Driven Models

    Jalal Shiri; Ali Keshavarzi; Ozgur Kisi; Sahar Mohsenzadeh Karimi; Sepideh Karimi; Amir Hossein Nazemi; Jesús Rodrigo-Comino (MDPI AG, 2020-03-01)
    Soil phosphorus (P) is a vital but limited element which is usually leached from the soil via the drainage process. Soil phosphorus as a soluble substance can be delivered through agricultural fields by runoff or soil loss. It is one of the most essential nutrients that affect the sustainability of crops as well as the energy transfer for living organisms. Therefore, an accurate simulation of soil phosphorus, which is considered as a point source pollutant in elevated contents, must be performed. Considering a crucial issue for a sustainable soil and water management, an effective soil phosphorus assessment in the current research was conducted with the aim of examining the capability of five different wavelet-based data-driven models: gene expression programming (GEP), neural networks (NN), random forest (RF), multivariate adaptive regression spline (MARS), and support vector machine (SVM) in modeling soil phosphorus (P). In order to achieve this goal, several parameters, including soil pH, organic carbon (OC), clay content, and soil P data, were collected from different regions of the Neyshabur plain, Khorasan-e-Razavi Province (Northeast Iran). First, a discrete wavelet transform (DWT) was applied to the pH, OC, and clay as the inputs and their subcomponents were utilized in the applied data-driven techniques. Statistical Gamma test was also used for identifying which effective soil parameter is able to influence soil P. The applied methods were assessed through 10-fold cross-validation scenarios. Our results demonstrated that the wavelet−GEP (WGEP) model outperformed the other models with respect to various validations, such as correlation coefficient (R), scatter index (SI), and Nash−Sutcliffe coefficient (NS) criteria. The GEP model improved the accuracy of the MARS, RF, SVM, and NN models with respect to SI-NS (By comparing the SI values of the GEP model with other models namely MARS, RF, SVM, and NN, the outputs of GEP showed more accuracy by 35%, 30%, 40%, 50%, respectively. Similarly, the results of the GEP outperformed the other models by 3.1%, 2.3%, 4.3%, and 7.6%, comparing their NS values.) by 35%-3.1%, 30%-2.3%, 40%-4.3%, and 50%-7.6%, respectively.
  • Tillage Intensity Effects on Soil Structure Indicators—A US Meta-Analysis

    Márcio R. Nunes; Douglas L. Karlen; Thomas B. Moorman (MDPI AG, 2020-03-01)
    Tillage intensity affects soil structure in many ways but the magnitude and type (+/−) of change depends on site-specific (e.g., soil type) and experimental details (crop rotation, study length, sampling depth, etc.). This meta-analysis examines published effects of chisel plowing (CP), no-tillage (NT) and perennial cropping systems (PER) relative to moldboard plowing (MP) on three soil structure indicators: wet aggregate stability (AS), bulk density (BD) and soil penetration resistance (PR). The data represents four depth increments (from 0 to >40-cm) in 295 studies from throughout the continental U.S. Overall, converting from MP to CP did not affect those soil structure indicators but reducing tillage intensity from MP to NT increased AS in the surface (<15-cm) and slightly decreased BD and PR below 25-cm. The largest positive effect of NT on AS was observed within Inceptisols and Entisols after a minimum of three years. Compared to MP, NT had a minimal effect on soil compaction indicators (BD and PR) but as expected, converting from MP to PER systems improved soil structure at all soil depths (0 to >40-cm). Among those three soil structure indicators, AS was the most sensitive to management practices; thus, it should be used as a physical indicator for overall soil health assessment. In addition, based on this national meta-analysis, we conclude that reducing tillage intensity improves soil structure, thus offering producers assurance those practices are feasible for crop production and that they will also help sustain soil resources.
  • Why People Participate in Collaborative Consumption: An Exploratory Study of Motivating Factors in a Latin American Economy

    Jessica Alzamora-Ruiz; Carlos Guerrero-Medina; Myriam Martínez-Fiestas; Jaime Serida-Nishimura (MDPI AG, 2020-03-01)
    In recent decades, collaborative initiatives have become relevant in Latin America, however, the owners of these businesses still face great challenges to mobilize consumers interest. In the research field, many collaborative consumption (CC) researchers have focused on the identification of their predictors; but studies that have explored this phenomenon via motivations perspective are very limited, especially those that focus on the Latin American context. Furthermore, these studies have analyzed on particular consumption activities and consumers with previous experience, restricting the scope of its results. To close this gap, the research has as its purpose the exploration of the motivating factors that best predict the intention to participate in CC activities into one of the three countries with the greatest number of collaborative businesses in the region. The ANOVA and CHAID are applied to a sample of 2080 people. The results reveal that, although enjoyment, sustainability, reputation and economic benefits are significant factors for CC, not all are equally effective in promoting high levels of participation in Latin American context. These findings allow to achieve a better understanding of the collaborative phenomenon, and also they contribute to the development of value proposals and more focused recruitment strategies for potential consumers in the region.
  • Saline and Alkaline Tolerance of Wetland Plants—What are the Most Representative Evaluation Indicators?

    Rui Cheng; Hui Zhu; Xianwei Cheng; Brian Shutes; Baixing Yan (MDPI AG, 2020-03-01)
    The increasing discharge of wastewater containing inorganic salts, sometimes accompanied by high pH, has been a worldwide environmental problem. Constructed wetlands (CWs) are considered a viable technology for treating saline and/or alkaline wastewater provided that saline-alkaline tolerant plant species are selected and applied. The influence of both saline and alkaline stress on four wetland plant species during their seed germination, early growth, vegetative propagation and continued growth stages was evaluated by three experiments. Principal component analysis (PCA) was conducted for selecting representative indicators for evaluating the saline and alkaline tolerance of plants during vegetative propagation and plant growth stages. The saline and alkaline stress inhibited the vegetative propagation and plant growth of all tested plant species to varying degrees, therein the influences of saline-alkaline stress on plants were more marked than saline stress. The length of new roots, Na<sup>+</sup> accumulation in plant tissue, Na<sup>+</sup>/K<sup>+</sup> ratios in aerial tissue and the total dry biomass were selected as most representative indicators for evaluating the saline and alkaline tolerance of plants. <i>Iris sibirica</i> and <i>Lythrum salicaria</i> showed better saline and alkaline tolerance ability among tested species and could be grown in CWs for treating saline and/or alkaline wastewater.
  • Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm

    Bo Peng; Lifan Wu; Yuxin Yi; Xiding Chen (MDPI AG, 2020-03-01)
    The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.
  • An Experimental Approach to Understanding the Impacts of Monitoring Methods on Use Intentions for Autonomous Vehicle Services: Survey Evidence from Japan

    Ryosuke Abe; Yusuke Kita; Daisuke Fukuda (MDPI AG, 2020-03-01)
    Safety guidelines for autonomous vehicles (AVs) in many regions or countries require AV service providers to have the means to communicate with vehicles and the ability to stop them safely in case of emergencies. The transition to full deployment of AV services is dependent on more advanced monitoring methods. This study uses a survey of approximately 2000 residents of Japanese cities to investigate how monitoring methods affect their intentions to use these services. In particular, the survey is designed to understand how individuals react to unattended operations and remote monitoring in road passenger services including buses and taxis; the survey includes direct questions about intentions to use autonomous buses and taxis and a stated choice experiment based on the respondents’ preferences over their current mode of transportation and autonomous taxis. The results show that monitoring methods have mixed impacts. On one hand, monitoring could affect the general acceptance of AV services. The difference in the overall resistance to using these services is particularly large between the onboard human and remote monitoring options. Individuals tend to express stronger resistance to more advanced remote monitoring. On the other hand, the stated choice results show that the effects of these monitoring factors could be less significant in the actual settings of transportation mode choices; the effects of travel cost and time factors are likely to be more significant. These results suggest that when individuals consider AVs in the context of real-world decisions, their resistance to new technologies is diminished in comparison to their responses to abstract questions.
  • Sustainability Research on Promoting the Inheritance of Lacquer Art Based on the E-learning Mode—Case Study of the Popularization of Lacquer Art Education in Primary Schools in Guangzhou Area

    Kuo-Kuang Fan; Xue-Hui Li; Meng-Jia Lu (MDPI AG, 2020-03-01)
    This paper investigates the sustainable inheritance of contemporary lacquer art in the Guangzhou area. Based on the traditional teaching mode dominated by folk inheritance and university education, this paper develops the advantage of contemporary information technology and proposes the application of the e-learning mode to assist the popularization of lacquer art education in society, which plays a positive role in promoting the sustainable development of the lacquer art culture in Guangzhou. This study adopts literature analysis and the questionnaire survey method, and then integrates this learning mode into the lacquer art learning curriculum in primary schools. Finally, this paper summarizes and reflects on the teaching results, and presents the effective role of this model in promoting the teaching of lacquer art culture, which is of important practical significance for consolidating the sustainable development of contemporary lacquer art culture.
  • Disaster and Climate Change Issues in Japan’s Society 5.0—A Discussion

    Aleksandrina V. Mavrodieva; Rajib Shaw (MDPI AG, 2020-03-01)
    Faced with a number of socio-economic challenges and a continuously rising risk of more frequent and higher-impact disasters, the Japanese government, in cooperation with the private sector, has formulated a new comprehensive strategy, under the name of “Society 5.0”, which is to utilize a number of various technological innovative solutions in an attempt to provide a secure future for its citizens, centering around several important sectors. The current paper aims to discuss disaster risk and climate change policies in Society 5.0 in particular, with some special focus on adaptation and inclusiveness. We start with giving details on the Society 5.0 concept and its goals, after which we focus more specifically on how disaster and climate change policies are integrated into the new strategy and proceed to discuss several contentious issues which represent both opportunities and risks or challenges for implementing the concept in a truly sustainable way. The paper tries to present various points of view and hopes to provide some food for future thought and research, rather than solutions or specific suggestions.
  • Tariff Reduction and Environment: Evidence from CAFTA and Chinese Manufacturing Firms

    Ling-Yun He; Geng Huang (MDPI AG, 2020-03-01)
    In the context of anti-globalization and trade wars (especially between the US and China), China-ASEAN Free Trade Area (CAFTA) now plays a prominent role in many aspects. In this paper, we investigate how import tariff reduction in CAFTA affects the importers’ pollution emissions, using the firm-level data of Chinese manufacturing from 2002 to 2007. The mechanisms of import tariff reduction in CAFTA on pollution emissions are divided into technique, composition and scale effects. Our results indicate that import tariff reduction in CAFTA on final goods is conductive to importers’ pollution reduction, whereas that on intermediates significantly aggravates importers’ pollution emissions. Moreover, import tariff reduction has heterogeneous impacts on different types of enterprises in terms of industries, ownership, and region. Our results also find that the state-owned importers’ emissions can hardly be affected through technique, composition and scale effects.
  • Genotoxic and Anatomical Deteriorations Associated with Potentially Toxic Elements Accumulation in Water Hyacinth Grown in Drainage Water Resources

    Farahat S. Moghanm; Antar El-Banna; Mohamed A. El-Esawi; Mohamed M. Abdel-DAIM; Ahmed Mosa; Khaled A.A. Abdelaal (MDPI AG, 2020-03-01)
    Potentially toxic elements (PTEs)-induced genotoxicity on aquatic plants is still an open question. Herein, a single clone from a population of water hyacinth covering a large distribution area of Nile River (freshwater) was transplanted in two drainage water resources to explore the hazardous effect of PTEs on molecular, biochemical and anatomical characters of plants compared to those grown in freshwater. Inductivity Coupled Plasma (ICP) analysis indicated that PTEs concentrations in water resources were relatively low in most cases. However, the high tendency of water hyacinth to bio-accumulate and bio-magnify PTEs maximized their concentrations in plant samples (roots in particular). A Random Amplified Polymorphic DNA (RAPD) assay showed the genotoxic effects of PTEs on plants grown in drainage water. PTEs accumulation caused substantial alterations in DNA profiles including the presence or absence of certain bands and even the appearance of new bands. Plants grown in drainage water exhibited several mutations on the electrophoretic profiles and banding pattern of total protein, especially proteins isolated from roots. Several anatomical deteriorations were observed on PTEs-stressed plants including reductions in the thickness of epidermis, cortex and endodermis as well as vascular cylinder diameter. The research findings of this investigation may provide some new insights regarding molecular, biochemical and anatomical responses of water hyacinth grown in drainage water resources.
  • Probabilistic Assessment of Hybrid Wind-PV Hosting Capacity in Distribution Systems

    Dichen Liu; Chenxu Wang; Fei Tang; Yixi Zhou (MDPI AG, 2020-03-01)
    In recent years, hybrid wind-photovoltaic (PV) systems are flourishing due to their advantages in the utilization of renewable energy. However, the accurate assessment of the maximum integration of hybrid renewable generation is problematic because of the complex uncertainties of source and demand. To address this issue, we develop a stochastic framework for the quantification of hybrid energy hosting capacity. In the proposed framework, historical data sets are adopted to represent the stochastic nature of production and demand. Moreover, extreme combinations of production and demand are introduced to avoid multiple load flow calculations. The proposed framework is conducted in the IEEE 33-bus system to evaluate both single and hybrid energy hosting capacity. The results demonstrate that the stochastic framework can provide accurate evaluations of hosting capacity while significantly reducing the computational burden. This study provides a comprehensive understanding of hybrid wind-PV hosting capacity and verifies the excellent performance of the hybrid energy system in facilitating integration and energy utilization.
  • A Study on the Development Trends of the Energy System with Blockchain Technology Using Patent Analysis

    Lin-Yun Huang; Jian-Feng Cai; Tien-Chen Lee; Min-Hang Weng (MDPI AG, 2020-03-01)
    Recently, the application of blockchain to the setting, management, and trading of the energy system has formed an innovative technology and has attracted a lot of attention from industry, academia, and research. In this study, we use patent analysis technology to explore the development trends of the energy system with blockchain technology. During the patent analysis process, this study makes corresponding analysis charts, such as patent application numbers over time, patent application numbers for main leading countries, applicants, patent citations, international patent classification (IPC), and life cycle. Relative research and design (R&D) capability of the top ten applicants is estimated and the cluster map of the technology is obtained. The technical features of the top five IPC patent applications are related to the cluster map to show the development of energy blockchain technology. Through this paper, first, the basics of the blockchain and patent analysis are illustrated and, moreover, the reason why and how blockchain technology can be combined with the energy system is also briefly described and analyzed. The results of the patent analysis of energy blockchain technology indicate that the United States leads the way, accounting for more than half of the global total. It is also interesting to note that the participants are not from traditional specific fields, but included electric power manufacturers, computer software companies, e-commerce companies, and even many new companies devoted to blockchain technology. Walmart Apollo, LLC and International Business Machines Corporation (IBM) have the highest number of patent applications. However, Walmart Apollo, LLC ranks first with a greater number of inventors of 36, an activity year of 2 years, and a relative R&D capability of 100%. IBM ranks second with an activity year of 3 years and a research and development capability of 91%. Among various applicants, IBM and LO3 energy started earlier in this field, and their patent output is also more prominent. The IPC is mainly concentrated in G06Q 50/06, which belongs to the technical field of the setting and management of the energy system including electricity, gas, or water supply. Currently, most projects are in the early development stages, and research on key areas is still ongoing to improve the required scalability, decentralization, and security. Thus, energy blockchain technology is still in the growth period, and there is still considerable room for development of the patent in the later period. Moreover, it is suggested that the novel communication module such as the combination of the consortium blockchain and the private blockchain cold also provide their own advantages to achieve the purpose of improving system performance and efficiency.
  • Computation of Global and Local Mass Transfer in Hollow Fiber Membrane Modules

    Benjamin Lukitsch; Paul Ecker; Martin Elenkov; Christoph Janeczek; Bahram Haddadi; Christian Jordan; Claus Krenn; Roman Ullrich; Margit Gfoehler; Michael Harasek (MDPI AG, 2020-03-01)
    Computational fluid dynamics (CFD) provides a flexible tool for investigation of separation processes within membrane hollow fiber modules. By enabling a three-dimensional and time dependent description of the corresponding transport phenomena, very detailed information about mass transfer or geometrical influences can be provided. The high level of detail comes with high computational costs, especially since species transport simulations must discretize and resolve steep gradients in the concentration polarization layer at the membrane. In contrast, flow simulations are not required to resolve these gradients. Hence, there is a large gap in the scale and complexity of computationally feasible geometries when comparing flow and species transport simulations. A method, which tries to cover the mentioned gap, is presented in the present article. It allows upscaling of the findings of species transport simulations, conducted for reduced geometries, on the geometrical scales of flow simulations. Consequently, total transmembrane transport of complete modules can be numerically predicted. The upscaling method does not require any empirical correlation to incorporate geometrical characteristics but solely depends on results acquired by CFD flow simulations. In the scope of this research, the proposed method is explained, conducted, and validated. This is done by the example of CO<sub>2</sub> removal in a prototype hollow fiber membrane oxygenator.
  • The “Metal-Energy-Construction Mineral” Nexus in the Island Metabolism: The Case of the Extractive Economy of New Caledonia

    Jean-Baptiste Bahers; Paula Higuera; Anne Ventura; Nicolas Antheaume (MDPI AG, 2020-03-01)
    The concept of island metabolism strives to implement the principles of social ecology at the island scale. It is, therefore, a question of analyzing the flows of materials and energy passing through these territories, as well as the resource base needed to sustain their activities. We propose to develop a nexus approach to the New Caledonian island metabolism to understand the interactions between biophysical structures and societal, as well as economic, activities. Metals, construction minerals, and energy are good symbols of economies based on the extraction of non-renewable resources. This is why, in this article, we sought to investigate how the “metal-energy-construction mineral” nexus can affect the resilience and metabolic sustainability of the extractive island of New Caledonia. We carried out the Material and Energy Flow Analysis (MEFA) of each nexus subsystem for 2016 and of the nodes of interdependence. We also interrogated the role of importing countries because the island’s metabolism is dominated by the nickel extraction industry. Indeed, the metabolic profile of this island corresponds to the one of a supply territory for other consumption territories. The latter outsource the impacts of their own consumption to New Caledonia. Finally, based on interviews with economic stakeholders, we studied the potential building blocks for the emergence of an industrial symbiosis in the nexus.

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