Journal Description
Sustainability
Sustainability
is an international, peer-reviewed, open-access journal on environmental, cultural, economic, and social sustainability of human beings, published semimonthly online by MDPI. The Canadian Urban Transit Research & Innovation Consortium (CUTRIC), International Council for Research and Innovation in Building and Construction (CIB) and Urban Land Institute (ULI) are affiliated with Sustainability and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE and SSCI (Web of Science), GEOBASE, GeoRef, Inspec, AGRIS, RePEc, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q1 (Geography, Planning and Development)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.8 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Sustainability.
- Companion journals for Sustainability include: World, Sustainable Chemistry, Conservation, Future Transportation, Architecture, Standards, Merits and Wind.
Impact Factor:
3.9 (2022);
5-Year Impact Factor:
4.0 (2022)
Latest Articles
Study of the Effect of Seepage–Cyclic Load Coupling Disturbance on the Physical Field in Old Urban Underground Spaces
Sustainability 2024, 16(9), 3588; https://doi.org/10.3390/su16093588 (registering DOI) - 24 Apr 2024
Abstract
The safety and sustainability of urban underground spaces have become crucial considerations in development projects. Seepage and cyclic loads are the principal reasons for the instability and failure of old underground space structures. This study investigates the variations in physical fields of underground
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The safety and sustainability of urban underground spaces have become crucial considerations in development projects. Seepage and cyclic loads are the principal reasons for the instability and failure of old underground space structures. This study investigates the variations in physical fields of underground spaces in cities under the coupling disturbance of seepage and cyclic loads, focusing on underground civil air defense engineering in Beijing as a case study. Different seepage conditions and the effects of seepage–cyclic load coupling were simulated using the numerical calculation software Plaxis 3D V20. The results show that change in groundwater can affect the deformation of underground space, and the severity is related to the quantity and intersection state of tunnels, the location of rivers above, and the strength of materials. The coupling effect of seepage–cyclic load on urban underground space structures is more serious than that of a single percolation. Decrease in material strength and high traffic loads are the principal reasons for the failure of underground structures. A 30% decrease in material strength causes the displacement to increase almost 1.5 times, and maximum displacement under different traffic loads can vary by 3 times. This study holds significant implications for the design, maintenance, and engineering management of underground spaces, emphasizing the importance of sustainable practices in urban development and infrastructure.
Full article
(This article belongs to the Special Issue Advancing Sustainability in Rock Mechanics and Underground Engineering)
Open AccessArticle
Sustainable Creative Practice with Older People: A Collaborative Approach between Arts and Care Sectors
by
Anna Dadswell, Ceri Wilson and Hilary Bungay
Sustainability 2024, 16(9), 3587; https://doi.org/10.3390/su16093587 (registering DOI) - 24 Apr 2024
Abstract
Interprofessional working is common practice within the health and care sector and particularly within care homes to support the diverse needs of their residents. However, this is less common between the arts and care sectors despite the established impact of the arts on
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Interprofessional working is common practice within the health and care sector and particularly within care homes to support the diverse needs of their residents. However, this is less common between the arts and care sectors despite the established impact of the arts on older people’s health, wellbeing, and quality of life. Arts activities that do take place in care homes tend to be time-bound, with artists utilising short-term funding to deliver a defined project often with limited engagement from care home staff due to their competing priorities. This article reflects on qualitative findings from the Artists’ Residencies in Care Homes (ARCH) programme led by Magic Me, which paired four leading arts organisations with four care homes in Essex who worked together over four years to deliver creative arts for the residents. Building trusted relationships and collaborative working between the artists and care home staff was essential for the success of the residencies and for generating and embedding sustainable creative practice in the homes. This article argues that for creative practice to become sustainably embedded in care homes, arts organisations and the arts and culture sector need to embrace interprofessional collaborative practice in health and social care.
Full article
(This article belongs to the Section Health, Well-Being and Sustainability)
Open AccessArticle
Enhancing Disaster Resilience for Sustainable Urban Development: Public–Private Partnerships in Japan
by
Mikio Ishiwatari, Haruki Kawakami, Daisuke Sasaki, Akiko Sakamoto and Mikiyasu Nakayama
Sustainability 2024, 16(9), 3586; https://doi.org/10.3390/su16093586 (registering DOI) - 24 Apr 2024
Abstract
A resilient building environment is crucial for securing sustainable development in urban areas, as the 2030 Agenda for Sustainable Development Goal 11 stresses. In developing countries in particular, the risk of disasters is increasing due to the poorly built environment caused by urbanization.
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A resilient building environment is crucial for securing sustainable development in urban areas, as the 2030 Agenda for Sustainable Development Goal 11 stresses. In developing countries in particular, the risk of disasters is increasing due to the poorly built environment caused by urbanization. However, building disaster resilience in vulnerable urban environments characterized by aging houses, limited public spaces, and complex land rights and tenancy issues poses a major challenge. This study aims to identify critical factors influencing effective disaster-resilient urban development by examining Japan’s experience, with a focus on approaches facilitating public–private partnerships. Driven by disasters like the 1995 Kobe Earthquake, Japan has promoted innovative strategies to improve urban resilience and mitigate disaster impacts. The Disaster Mitigation Zone Implementation Program represents a novel program designed to revitalize densely populated areas with aging wooden structures highly vulnerable to disasters. Through semi-structured interviews, a literature review, and an in-depth case study in Tokyo, this research analyzes the development and effectiveness of this targeted redevelopment approach. Findings underscore the pivotal role of policies promoting public–private collaboration, consensus-building mechanisms among stakeholders, flexibility in project formulation, and financial incentives via government subsidies. Engaging the private sector ensures project feasibility through urban development expertise, while simpler, smaller-scale projects attract greater private investment. Japan’s experience offers valuable insights into collaborative, context-sensitive strategies for enhancing urban disaster resilience through targeted redevelopment of high-risk areas.
Full article
(This article belongs to the Special Issue Improving Community Well-Being through Sustainable Interventions)
Open AccessArticle
The Impact of Data Elements on Enterprises’ Capital Market Performance: Insights from Stock Liquidity in China and Implications for Global Markets
by
Rong Cui, Yuda Wang and Yujing Wang
Sustainability 2024, 16(9), 3585; https://doi.org/10.3390/su16093585 (registering DOI) - 24 Apr 2024
Abstract
Amidst a backdrop of global economic challenges and shifting market dynamics, this study highlights the transformative role of data elements in enhancing enterprise performance within capital markets, particularly focusing on China’s leading position in the digital economy as a model with implications for
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Amidst a backdrop of global economic challenges and shifting market dynamics, this study highlights the transformative role of data elements in enhancing enterprise performance within capital markets, particularly focusing on China’s leading position in the digital economy as a model with implications for global markets. This study utilized a panel data set consisting of 10,493 observations from 2687 listed enterprises in Shanghai and Shenzhen A-shares from 2015 to 2023. An econometric analysis was conducted using a two-way fixed effects model to explore the impact of enterprise data elements on capital market performance in the digital economy and its underlying mechanisms. The research reveals that the digitization of enterprise production factors can significantly enhance performance in the capital market. The study further suggests that enterprise innovation and enterprise value play a crucial role in mediating this effect. This paper introduces a new concept called “data elements”, which expands the definition and assessment methods of enterprise data capabilities. It goes beyond just digital transformation at the application level and includes data governance at the basic ability level. This approach provides a more accurate and comprehensive understanding of the different elements of data. Moreover, the research expands the research scope of microeconomic entities’ economic benefits, thereby extending the value contributed by enterprise data elements to their performance in the capital market. Additionally, this study reveals the relationship between enterprise data elementization and capital market performance through intermediary analysis of enterprise innovation performance and enterprise value, which unveils the “black box” and clarifies the transmission pathway. The findings of this research hold considerable theoretical value and have far-reaching practical implications for government policies concerning data elements and the development of high-quality enterprises, suggesting pathways for global markets to leverage data for enhanced enterprise performance and economic resilience. The results are particularly useful for policymakers, enterprise managers, and scholars in understanding and implementing data-driven strategies in capital markets.
Full article
(This article belongs to the Special Issue Global Economies and Markets)
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Open AccessArticle
How Review Valence Shapes Visit Intention: Affective Commitment and Destination Reputation
by
Yagang Zhao, Binli Tang, Xiaojie Yang and Jeroen Nawijn
Sustainability 2024, 16(9), 3584; https://doi.org/10.3390/su16093584 (registering DOI) - 24 Apr 2024
Abstract
In the era of social media, online reviews have become a crucial factor influencing the exposure of tourist destinations and the decision-making of potential tourists, exerting a profound impact on the sustainable development of these destinations. However, the influence of review valence on
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In the era of social media, online reviews have become a crucial factor influencing the exposure of tourist destinations and the decision-making of potential tourists, exerting a profound impact on the sustainable development of these destinations. However, the influence of review valence on visit intention, especially the role of affective commitment and reputation (ability vs. responsibility), remains unclear. Drawing on emotion as a social information theory, this paper aims to elucidate the direct impact of different review valences on tourists’ visit intentions, as well as mediating mechanisms and boundary conditions. Three experiments indicate that positive (vs. negative) reviews can activate stronger affective commitment and visit intention, with affective commitment also playing a mediating role. Additionally, destination reputation significantly moderates the after-effects of review valences. More specifically, a responsibility reputation (compared with an ability reputation) weakens the effect of negative valence on affective commitment and visit intention. This study provides valuable theoretical insights into how emotional elements in online reviews influence the emotions and attitudes of potential tourists. Particularly for tourism managers, review valence and responsibility reputation hold practical significance in destination marketing.
Full article
(This article belongs to the Special Issue Designing Scenarios as Interpretive Measurement of Human–Environment-Social Sustainable Interaction)
Open AccessArticle
Expansion of Next-Generation Sustainable Clean Hydrogen Energy in South Korea: Domino Explosion Risk Analysis and Preventive Measures Due to Hydrogen Leakage from Hydrogen Re-Fueling Stations Using Monte Carlo Simulation
by
Kwanwoo Lee and Chankyu Kang
Sustainability 2024, 16(9), 3583; https://doi.org/10.3390/su16093583 (registering DOI) - 24 Apr 2024
Abstract
Hydrogen, an advanced energy source, is growing quickly in its infrastructure and technological development. Urban areas are constructing convergence-type hydrogen refilling stations utilizing existing gas stations to ensure economic viability. However, it is essential to conduct a risk analysis as hydrogen has a
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Hydrogen, an advanced energy source, is growing quickly in its infrastructure and technological development. Urban areas are constructing convergence-type hydrogen refilling stations utilizing existing gas stations to ensure economic viability. However, it is essential to conduct a risk analysis as hydrogen has a broad range for combustion and possesses significant explosive capabilities, potentially leading to a domino explosion in the most severe circumstances. This study employed quantitative risk assessment to evaluate the range of damage effects of single and domino explosions. The PHAST program was utilized to generate quantitative data on the impacts of fires and explosions in the event of a single explosion, with notable effects from explosions. Monte Carlo simulations were utilized to forecast a domino explosion, aiming to predict uncertain events by reflecting the outcome of a single explosion. Monte Carlo simulations indicate a 69% chance of a domino explosion happening at a hydrogen refueling station if multi-layer safety devices fail, resulting in damage estimated to be three times greater than a single explosion.
Full article
(This article belongs to the Special Issue Green Energy and Sustainable Development)
Open AccessArticle
Detailed Land Use Classification in a Rare Earth Mining Area Using Hyperspectral Remote Sensing Data for Sustainable Agricultural Development
by
Chige Li, Hengkai Li, Yanbing Zhou and Xiuli Wang
Sustainability 2024, 16(9), 3582; https://doi.org/10.3390/su16093582 (registering DOI) - 24 Apr 2024
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In China, ion-adsorbing rare earth minerals are mainly located in the southern hilly areas and are important strategic resources. Extensive long-term mining has severely damaged the land cover in mining areas, caused soil pollution and terrain fragmentation, disrupted the balance between mining and
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In China, ion-adsorbing rare earth minerals are mainly located in the southern hilly areas and are important strategic resources. Extensive long-term mining has severely damaged the land cover in mining areas, caused soil pollution and terrain fragmentation, disrupted the balance between mining and agriculture, severely restricted agricultural development, and affected ecological development. Precise and detailed classification of land use within mining areas is crucial for monitoring the sustainable development of agricultural ecology in these areas. In this study, we leverage the high spatial and high spectral resolution characteristics of the Zhuhai-1 (OHS) hyperspectral image datasets. We create four types of datasets based on spectral, vegetation, red edge, and texture characteristics. These datasets are optimized for multifaceted features, considering the complex land use scenario in rare earth mining areas. Additionally, we design seven optimal combination schemes for features. This is performed to examine the impact of different schemes on land use classification in rare earth mining areas and the accuracy of identifying agricultural land classes from broken blocks. The results show that (1) the inclusion of texture features has the most obvious effect on the overall classification accuracy; (2) the red edge feature has the worst effect on improving the overall accuracy of the surface classification; however, it has a prominent effect on the identification of agricultural lands such as farmland, orchards, and reclaimed vegetation; and (3), following the combination of various optimization features, the land use classification yielded the highest overall accuracy, at 88.16%. Furthermore, the comprehensive identification of various agricultural land classes, including farmland, orchards, and greenhouse vegetables, yielded the most desirable outcomes. The research results not only highlight the advantages of hyperspectral images for complex terrain classification and recognition but also address the previous limitations in the application of hyperspectral datasets over wide mining areas. Additionally, the results underscore the reliability of feature selection methods in reducing information redundancy and improving classification accuracy. The proposed feature selection combination, based on OHS hyperspectral datasets, offers technical support and guidance for the detailed classification of complex land use in mining areas and the accurate monitoring of agroecological environments.
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Open AccessArticle
Prediction of Losses Due to Dust in PV Using Hybrid LSTM-KNN Algorithm: The Case of Saruhanlı
by
Tuba Tanyıldızı Ağır
Sustainability 2024, 16(9), 3581; https://doi.org/10.3390/su16093581 (registering DOI) - 24 Apr 2024
Abstract
Sustainable and renewable energy sources are of great importance in today’s world. In this respect, renewable energy sources are used in many fields of technology. In order to minimize dust on PV panels and ensure their sustainability, power losses due to dust must
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Sustainable and renewable energy sources are of great importance in today’s world. In this respect, renewable energy sources are used in many fields of technology. In order to minimize dust on PV panels and ensure their sustainability, power losses due to dust must be estimated accurately. In this way, the efficiency of a sustainable energy source will increase and serious economic savings can be achieved. In this study, a hybrid deep learning model was designed to predict losses caused by dust in PV panels installed in the Manisa Saruhanlı district. The hybrid deep learning model consists of Long Short-Term Memory (LSTM) and K-Nearest-Neighbors (KNN) algorithms. The performance of the proposed hybrid deep learning model was compared with LSTM and KNN algorithms. Sensitivity analysis was performed to statistically evaluate the prediction results. The input variables of the models were time, sunshine duration, humidity, ambient temperature and solar radiation. The output variable was the losses caused by dust in the PV panels. Hybrid LSTM-KNN, LSTM and KNN models predicted losses caused by dust in PV panels with 98.22%, 95.51% and 61.49% accuracy. The hybrid LSTM-KNN model predicted losses caused by dust in PV panels with higher accuracy than other models. Using LSTM and KNN algorithms together improved the performance of the hybrid deep learning model. With sensitivity analysis, it was found that solar radiation is the most important variable affecting the losses caused by dust in PV panels.
Full article
Open AccessArticle
Socioeconomic Determinants of Poverty Reduction among Irrigating Farmers in Mberengwa District, Zimbabwe
by
Norman Mupaso, Godswill Makombe, Raymond Mugandani and Paramu L. Mafongoya
Sustainability 2024, 16(9), 3580; https://doi.org/10.3390/su16093580 (registering DOI) - 24 Apr 2024
Abstract
Sustainable Development Goal 1 aims to end extreme poverty everywhere by the year 2030. Smallholder irrigation development is arguably a vital strategy to reduce rural poverty. The authors assessed the socioeconomic determinants of poverty reduction in Mberengwa district, Zimbabwe. Data were collected from
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Sustainable Development Goal 1 aims to end extreme poverty everywhere by the year 2030. Smallholder irrigation development is arguably a vital strategy to reduce rural poverty. The authors assessed the socioeconomic determinants of poverty reduction in Mberengwa district, Zimbabwe. Data were collected from 444 randomly selected households. Data were analyzed using SPSS version 27 and Microsoft Excel 2019 software packages. Chi-square tests, t-tests, and Foster–Greer–Thorbecke (FGT) poverty index and binary logistic regression model tests were performed. The chi-square test results show an association between access to irrigation and farmer’s level of education (p < 0.01). The t-test results show significant differences between irrigators and non-irrigators for household size (p < 0.01), household labor (p < 0.05), and rainfed plot size (p < 0.05). FGT indices show that the poverty incidence, depth, and severity were lesser for irrigators than non-irrigators. The binary logistic regression model results show that age, household size, access to irrigation and household income significantly influence household poverty status. In conclusion, access to irrigation reduces poverty in rural areas. However, access to irrigation is not a panacea for poverty reduction in rural areas. Smallholder irrigation development policies should consider socioeconomic determinants of poverty reduction to properly target and tailor interventions, and increase the relevance and effectiveness of poverty reduction efforts.
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Open AccessArticle
Prediction and Feed-In Tariffs of Municipal Solid Waste Generation in Beijing: Based on a GRA-BiLSTM Model
by
Xia Zhang and Bingchun Liu
Sustainability 2024, 16(9), 3579; https://doi.org/10.3390/su16093579 (registering DOI) - 24 Apr 2024
Abstract
To cope with the increasing energy demand of people and solve the problem of a “Garbage Siege”, most cities have begun to adopt waste power generation (WTE). Compared to other WTE technologies, incineration has proven to be the most efficient technology for municipal
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To cope with the increasing energy demand of people and solve the problem of a “Garbage Siege”, most cities have begun to adopt waste power generation (WTE). Compared to other WTE technologies, incineration has proven to be the most efficient technology for municipal solid waste (MSW) treatment. Therefore, to further explore the economic feasibility of MSW incineration plant construction, this study established a multi-factor prediction of MSW generation based on the GRA-BiLSTM model. By fully considering the relationship between the change in feed-in tariff (FIT) and the building of an incineration plant in Beijing, the economic feasibility of building an incineration plant is discussed based on the three scenarios set. The experimental results showed that (1) the combined model based on the GRA-BiLSTM showed good applicability for predicting MSW generation in Beijing, with MAE, MAPE, RMSE, and R2 values of 12.47, 5.97%, 18.5580, and 0.8950, respectively. (2) Based on the three scenarios set, the incineration power generation of Beijing MSW will show varying degrees of growth in 2022–2035. In order to meet future development, Beijing needs to build seven new incinerators, and the incineration rate should reach 100%. (3) According to setting different feed-in tariffs, based on the economic feasibility analysis, it is found that the feed-in tariff of MSW incineration for power generation in Beijing should be no less than $0.522/kWh. The government should encourage the construction of incineration plants and give policy support to enterprises that build incineration plants.
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Open AccessArticle
EDAR 4.0: Machine Learning and Visual Analytics for Wastewater Management
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David Velásquez, Paola Vallejo, Mauricio Toro, Juan Odriozola, Aitor Moreno, Gorka Naveran, Michael Giraldo, Mikel Maiza and Basilio Sierra
Sustainability 2024, 16(9), 3578; https://doi.org/10.3390/su16093578 (registering DOI) - 24 Apr 2024
Abstract
Wastewater treatment plant (WWTP) operations manage massive amounts of data that can be gathered with new Industry 4.0 technologies such as the Internet of Things and Big Data. These data are critical to allow the wastewater treatment industry to improve its operation, control,
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Wastewater treatment plant (WWTP) operations manage massive amounts of data that can be gathered with new Industry 4.0 technologies such as the Internet of Things and Big Data. These data are critical to allow the wastewater treatment industry to improve its operation, control, and maintenance. However, the data available need to be improved and enriched, partly due to their high dimensionality and low reliability, and the lack of appropriate data analysis and processing tools for such systems. This paper presents a visual analytics-based platform for WWTP that allows users to identify relationships among data through data inspection. The results show that the tool developed and implemented for a full-scale WWTP allows operators to construct machine learning (ML) models for water quality and other water treatment process variables. Consequently, analyzing and optimizing plant operation scenarios can enhance key variables, including energy, reagent consumption, and water quality. This improvement facilitates the development of a more sustainable WWTP, contributing to a beneficial environmental impact. Domain experts validated the variables influencing the created ML models and proved their appropriateness.
Full article
(This article belongs to the Special Issue Novel Decision Technology Analytics for Evaluating Sustainable Strategies and Environmental Operations)
Open AccessArticle
How to Reduce College Students’ Food Waste Behavior: From the Perspective of College Canteen Catering Modes
by
Amin Wang, Xi Luo, Xiaojun Liu and Yongkai Sun
Sustainability 2024, 16(9), 3577; https://doi.org/10.3390/su16093577 - 24 Apr 2024
Abstract
Reducing consumer food waste plays an important role in achieving the Sustainable Development Goals. Considering the large number of colleges in China, with the largest enrollment in the world, it is especially important to address the issue of food waste among college students.
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Reducing consumer food waste plays an important role in achieving the Sustainable Development Goals. Considering the large number of colleges in China, with the largest enrollment in the world, it is especially important to address the issue of food waste among college students. However, the mechanisms underlying the effects that the college canteen catering modes have on the food-saving behavior of college students remain unclear. To fill this gap, an integrated theoretical framework model was constructed from the perspective of “psychological factors–behavioral intention–external environment–actual behavior” based on the theory of planned behavior, the norm activation model, and the attitude–context–behavior theory. Then, 422 valid questionnaires were empirically analyzed by structural equation modeling and hierarchical regression. The main conclusions of this study are as follows: (1) Food-saving intention and herd mentality are the major drivers of college students’ food-saving behavior. Personal norms, attitudes, subjective norms, perceived behavior control, and health risk perception are influencing factors on food-saving intention, among which personal norms have the greatest effect. (2) The standard-quantity catering mode has an inhibitory moderating effect, while the large-/small-portion-size and buffet catering modes have promoting moderating effects in the transformation of food-saving intention into actual behavior. Notably, the moderating effects of the buffet catering mode are more pronounced than those of the large-/small-portion-size catering mode. (3) The standard-quantity catering mode has a promoting moderating effect, while the large-/small-portion-size and buffet catering modes have inhibitory moderating effects in the path of the negative impact of herd mentality on food-saving behavior. These conclusions can help colleges recommend strategies to avoid food waste on their campuses from the perspectives of both the individual student and the food provider.
Full article
(This article belongs to the Special Issue Food Waste Management and Sustainability)
Open AccessArticle
Reconsidering the Long-Term Impacts of Digitalization, Industrialization, and Financial Development on Environmental Sustainability in GCC Countries
by
Kamel Touati and Ousama Ben-Salha
Sustainability 2024, 16(9), 3576; https://doi.org/10.3390/su16093576 - 24 Apr 2024
Abstract
Gulf Cooperation Council (GCC) countries have faced environmental challenges in recent decades. This study aims to identify the contribution of digitalization, industrialization, and financial development to the ecological footprint (EF) in GCC countries between 2000 and 2021. The empirical investigation involves estimating the
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Gulf Cooperation Council (GCC) countries have faced environmental challenges in recent decades. This study aims to identify the contribution of digitalization, industrialization, and financial development to the ecological footprint (EF) in GCC countries between 2000 and 2021. The empirical investigation involves estimating the STochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model using the augmented mean group (AMG), common correlated effects mean group (CCEMG) and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimators. The findings reveal the existence of long-term linkages between EF and the factors mentioned above. Furthermore, there is evidence that adopting digitalization and information and communication technologies (ICT) improves long-term environmental quality. In contrast, both industrialization and financial development exert detrimental effects on the environment. Finally, the JKS Granger non-causality test revealed that all variables, except financial development, predict environmental degradation in GCC countries. These findings can assist in formulating efficient strategies to reduce ecological degradation and achieve environmental sustainability in GCC countries.
Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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Application of Internet-of-Things Wireless Communication Technology in Agricultural Irrigation Management: A Review
by
Pan Tang, Qi Liang, Hong Li and Yiyuan Pang
Sustainability 2024, 16(9), 3575; https://doi.org/10.3390/su16093575 - 24 Apr 2024
Abstract
The integration of Internet-of-Things technology with traditional agricultural irrigation is a crucial factor in the advancement of traditional agricultural irrigation towards smart irrigation. Despite the widespread use of conventional irrigation methods in many areas, they lead to the significant wastage of both human
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The integration of Internet-of-Things technology with traditional agricultural irrigation is a crucial factor in the advancement of traditional agricultural irrigation towards smart irrigation. Despite the widespread use of conventional irrigation methods in many areas, they lead to the significant wastage of both human and water resources. Therefore, the development of energy-saving and efficient intelligent irrigation systems through the application of Internet-of-Things technology and wireless communication technology is the way forward. This paper summarizes the common wireless communication technologies in the agricultural Internet of Things: Fifth-generation, WiFi, ZigBee, LoRa, and NB-IoT. The research status of the above wireless communication technology in agricultural irrigation management is discussed, and the agricultural irrigation management example using the above wireless communication technology is also presented. The advantages and limitations of the application of the above wireless communication technology in agricultural irrigation management are sorted out. Finally, this paper analyzes the challenges of data security issues, data fusion problems, intelligent irrigation system costs, power and energy problems, and system equipment failures faced by the use of IoT wireless communication technology in agricultural irrigation management. This review aims to assist researchers and users in choosing the most suitable wireless communication technology for diverse applications.
Full article
(This article belongs to the Special Issue Planning and Sustainable Management of Irrigation in Agricultural Operations)
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Open AccessArticle
Sustainable Development of the Real Economy: Supply Chain Finance and Enterprise Financialization
by
Jingjing Dong and Qiancheng Zhang
Sustainability 2024, 16(9), 3574; https://doi.org/10.3390/su16093574 - 24 Apr 2024
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Supply chain finance, as an important financial instrument supporting the sustainable development of the real economy, has attracted significant attention. In this paper, research is conducted on 3181 non-financial listed enterprises in the A-share market in China from 2012 to 2021. Multiple regression
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Supply chain finance, as an important financial instrument supporting the sustainable development of the real economy, has attracted significant attention. In this paper, research is conducted on 3181 non-financial listed enterprises in the A-share market in China from 2012 to 2021. Multiple regression analysis is adopted to examine the relationship between supply chain finance and enterprise financialization, as well as the impact of the former on the latter and the underlying mechanisms at play. The research findings indicate that the supply chain finance model, led by core enterprises, tends to exacerbate enterprise financialization in China. The significant resource dependence of small- and medium-sized enterprises (SMEs) on core enterprises acts as a moderating variable for supply chain finance and enterprise financialization. This dependence amplifies the stimulus of supply chain finance on the “financialization” of enterprises, demonstrates a pronounced moderating effect within state-owned enterprises, and strengthens over time when the core enterprises possess information advantages. The findings articulated herein contribute to the scholarly discourse, offering insights into the improvement of supply chain finance and the advancement of the real economy’s sustainable development via financial services. A good supply chain finance model should align with the requirements for the development of China’s real economy. It should provide not only financial assistance to enterprises but also foster a virtuous cycle within the industrial chain and encourage industrial production over financial investment.
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Open AccessArticle
A Comprehensive Assessment of the Carbon Footprint of the Coal-to-Methanol Process Coupled with Carbon Capture-, Utilization-, and Storage-Enhanced Oil Recovery Technology
by
Xinyue Li, Bin Zhou, Weiling Jin and Huangwei Deng
Sustainability 2024, 16(9), 3573; https://doi.org/10.3390/su16093573 - 24 Apr 2024
Abstract
The process of coal-to-methanol conversion consumes a large amount of energy, and the use of the co-production method in conjunction with carbon capture, utilization, and storage (CCUS) technology can reduce its carbon footprint. However, little research has been devoted to comprehensively assessing the
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The process of coal-to-methanol conversion consumes a large amount of energy, and the use of the co-production method in conjunction with carbon capture, utilization, and storage (CCUS) technology can reduce its carbon footprint. However, little research has been devoted to comprehensively assessing the carbon footprint of the coal-to-methanol (CTM) co-production system coupled with CCUS-enhanced oil recovery technology (CCUS-EOR), and this hinders the scientific evaluation of its decarbonization-related performance. In this study, we used lifecycle assessment to introduce the coefficient of distribution of methanol and constructed a model to calculate the carbon footprint of the process of CTM co-production of liquefied natural gas (LNG) as well as CTM co-production coupled with CCUS-EOR. We used the proposed model to calculate the carbon footprint of the entire lifecycle of the process by using a case study. The results show that the carbon footprints of CTM co-production and CTM co-production coupled with CCUS-EOR are 2.63 t CO2/tCH3OH and 1.00 t CO2/tCH3OH, respectively, which is lower than that of the traditional CTM process, indicating their ability to achieve environmental sustainability. We also analyzed the composition of the carbon footprint of the coal-to-methanol process to identify the root causes of carbon emissions in it and pathways for reducing them. The work described here provided a reference for decision making and a basis for promoting the development of coal-to-methanol conversion and the CCUS industry in China.
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(This article belongs to the Special Issue Advanced Analysis of Energy Economics and Sustainable Development in China in the Context of Carbon Neutrality)
Open AccessArticle
Public Willingness to Pay for Interstate Cooperation to Preserve the Ecological Integrity of the Han River Estuary in Korea
by
Min-Ki Hyun, Jungho Nam and Seung-Hoon Yoo
Sustainability 2024, 16(9), 3572; https://doi.org/10.3390/su16093572 - 24 Apr 2024
Abstract
The Han River Estuary (HRE), Yellow Sea, forms part of the border between South Korea and North Korea, and these two countries are militarily hostile. Since the HRE has quite excellent ecological integrity, the task of preserving it well is emerging as important.
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The Han River Estuary (HRE), Yellow Sea, forms part of the border between South Korea and North Korea, and these two countries are militarily hostile. Since the HRE has quite excellent ecological integrity, the task of preserving it well is emerging as important. Thus, the South Korean Government is attempting to preserve the ecological integrity of the HRE through interstate cooperation. By employing contingent valuation, this study delves into South Korean households’ willingness to pay (WTP) for this preservation. One thousand households nationwide were sampled and surveyed through face-to-face individual interviews. Annual household income tax was selected as the payment vehicle. Dichotomous choice questioning was chosen as the WTP induction method. A spike model was selected as a method for modelling a WTP of zero. The main results showed statistical significance. Annual WTP per household and national WTP were obtained as KRW 4487 (USD 3.92) and KRW 125.75 billion (USD 109.83 million), respectively. When a 10-year payment period and a 4.5% discount rate were adopted, the value was KRW 766.14 billion (USD 669.12 million). South Korean households placed considerable value on the preservation of the ecological integrity of the HRE through interstate cooperation.
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(This article belongs to the Special Issue Sustainable Coastal and Estuary Management)
Open AccessArticle
Index Insurance for Forage, Pasture, and Rangeland: A Review of Developed (USA and Canada) and Developing (Kenya and Ethiopia) Countries
by
Simon Maina, Maryfrances Miller, Gregory L. Torell, Niall Hanan, Julius Anchang and Njoki Kahiu
Sustainability 2024, 16(9), 3571; https://doi.org/10.3390/su16093571 - 24 Apr 2024
Abstract
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Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable
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Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable ecosystems. Index insurance, which avoids market failures such as moral hazard, adverse selection, and transactional cost, has been piloted and implemented all over the world. To support future development and research on index-based insurance in livestock systems, operational index insurance for forage, pasture, and rangeland systems in developed (USA and Canada) and developing (Kenya and Ethiopia) countries are reviewed and compared. This paper finds some similar characteristics (huge subsidy payments—ranging from 50 to 100 percent, significant government role, low adoption, insufficient payouts, data challenges, etc.), of this product between the two regions. A major difference between the PRF and NDVI is the number of choices available to users of rainfall index insurance who face close to 3000 choice options, while NDVI users have less than 5 choice options available for them. Based on these insights, we highlight opportunities where the two regions can benchmark and improve upon their respective index insurance schemes—index-based livestock insurance (IBLI) in developing and rainfall index insurance for forage in developed regions.
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Open AccessArticle
Mechanical Properties and Damage Constitutive Model of Thermally Damaged Basalt
by
Wenzhao Chen, Rui Chang, Xiqi Liu, Yan Chang, Fuqing Zhang, Dongwei Li and Zhenhua Wang
Sustainability 2024, 16(9), 3570; https://doi.org/10.3390/su16093570 - 24 Apr 2024
Abstract
Nuclear power is a high-quality clean energy source, but nuclear waste is generated during operation. The waste continuously releases heat during disposal, increasing the adjoining rock temperature and affecting the safety of the disposal site. Basalt is widely considered a commonly used rock
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Nuclear power is a high-quality clean energy source, but nuclear waste is generated during operation. The waste continuously releases heat during disposal, increasing the adjoining rock temperature and affecting the safety of the disposal site. Basalt is widely considered a commonly used rock type in the repository. This study of basalt’s mechanical characteristics and damage evolution after thermal damage, with its far-reaching engineering value, was conducted by combining experimental work and theory. Uniaxial compression tests were conducted on basalt exposed to 25 °C, 500 °C, 700 °C, 900 °C, and 1100 °C conditions, and acoustic emission (AE) equipment was utilized to observe the acoustic emission phenomenon during deformation. This study was carried out to examine the mechanical characteristics, the sound emission features, the progression of damage laws, and the stress–strain framework of basalt after exposure to different types of thermal harm. As the temperature rises, the rock’s maximum strength declines steadily, the peak strain rises in tandem, the rock sample’s ductility is augmented, the failure mode changes from shear to tensile failure, and cracks in the failure area are observed. At room temperature, the acoustic emission signal is more vigorous than in the initial stage of rock sample loading due to thermal damage; however, after the linear elastic stage is entered, its activity is lessened. In cases where the rock approaches collapse, there is a significant surge in acoustic emission activity, leading to the peak frequency of acoustic emission ringing. The cumulative ring count of acoustic emission serves as the basis for the definition of the damage variable. At room temperature, the damage evolution of rock samples can be broken down into four distinct stages. This defined damage variable is more reflective of the entire failure process. After exposure to high temperatures, the initial damage of the rock sample becomes more extensive, and the damage variable tends to be stable with strain evolution. The stress–strain constitutive model of basalt deformation is derived based on the crack axial strain law and acoustic emission parameters. A powerful relationship between theoretical and experimental curves is evident.
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(This article belongs to the Section Hazards and Sustainability)
Open AccessArticle
Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency
by
Indrawan Nugrahanto, Hariyanto Gunawan and Hsing-Yu Chen
Sustainability 2024, 16(9), 3569; https://doi.org/10.3390/su16093569 - 24 Apr 2024
Abstract
Computer Numeric Control (CNC) five-axis milling plays a significant role in the machining of precision molds and dies, aerospace parts, consumer electronics, etc. This research aims to explore the potential of the machine learning (ML) technique in improving energy efficiency during the CNC
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Computer Numeric Control (CNC) five-axis milling plays a significant role in the machining of precision molds and dies, aerospace parts, consumer electronics, etc. This research aims to explore the potential of the machine learning (ML) technique in improving energy efficiency during the CNC five-axis milling process for sustainable manufacturing. The experiments with various machining parameters, forms of toolpath planning, and dry cutting conditions were carried out, and the data regarding energy consumption were collected simultaneously. The relationship between machine parameters and energy consumption was analyzed and built. Subsequently, a machine learning algorithm was developed to classify test methods and identify energy-efficient machining strategies. The developed algorithm was implemented and assessed using different classification methods based on the ML concept to effectively reduce energy consumption. The results show that the Decision Tree and Random Forest algorithms produced lower Root Mean Square Error (RMSE) values of 4.24 and 4.28, respectively, compared to Linear, Lasso, and Ridge Regression algorithms. Verification experiments were conducted to ascertain the real-world applicability and performance of the ML-based energy efficiency approach in an operational CNC five-axis milling machine. The findings not only underscore the potential of ML techniques in optimizing energy efficiency but also offer a compelling pathway towards enhanced sustainability in CNC machining operations. The developed algorithm was implemented within a simulation framework and the algorithm was rigorously assessed using machine learning analysis to effectively reduce energy consumption, all while ensuring the accuracy of the machining results and integrating both conventional and advanced regression algorithms into CNC machining processes. Manufacturers stand to realize substantial energy savings and bolster sustainability initiatives, thus exemplifying the transformative power of ML-driven optimization strategies.
Full article
(This article belongs to the Special Issue Selected Papers on Sustainability from IMETI 2022)
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