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Sustainability, Volume 14, Issue 20 (October-2 2022) – 745 articles

Cover Story (view full-size image): Despite the growing consensus surrounding the need to decarbonise power, the share of low-carbon electricity sources in the overall energy mix has varied significantly across countries and over time. We evaluate the influence of democracy on clean energy transition by studying national solar, wind, hydro, and nuclear energy shares of total energy use for electricity generation from 1980 to 2020. Using data from the Varieties of Democracy, International Energy Agency, and World Bank databases, we conduct a large-N hierarchical study of the emission levels of 135 countries. Our findings provide strong evidence that democracy significantly influences low-carbon electricity use and that the effect of democracy within individual countries is highly contingent on national economic conditions. View this paper
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17 pages, 8862 KiB  
Article
Monitoring Marine Oil Spills in Hyperspectral and Multispectral Remote Sensing Data by the Spectral Gene Extraction (SGE) Method
Sustainability 2022, 14(20), 13696; https://doi.org/10.3390/su142013696 - 21 Oct 2022
Cited by 3 | Viewed by 2062
Abstract
Oil spill incidents threaten the marine ecological environment. Detecting sea surface oil slicks by remote sensing images provides support for the efficient treatment of oil spills. This is important for sustainable marine development. However, traditional methods based on field analysis are time-consuming. Spectral [...] Read more.
Oil spill incidents threaten the marine ecological environment. Detecting sea surface oil slicks by remote sensing images provides support for the efficient treatment of oil spills. This is important for sustainable marine development. However, traditional methods based on field analysis are time-consuming. Spectral indices lack applicability. In addition, traditional machine learning methods strictly rely on training and testing samples which are in short supply in oil spill images. Inspired by the spectral DNA encoding method, a spectral gene extraction (SGE) method was proposed to detect oil spills in hyperspectral images (HSI) and multispectral images (MSI). The SGE method contained a parameter and two strategies. The parameter of elimination was designed based on the population genetic frequency. It was used to control the number of spectral genes. The spectral gene extraction strategies, named largest in-class similarity (LIS) strategy and largest inter-class difference (LID) strategy, were proposed to mine the spectral genes by oil spill samples. The oil spills would be determined by calculating the similarity of the extracted spectral genes to the DNA encoded images. In this research, the SGE method was validated by two AVIRIS images of the Gulf of Mexico oil spill, one MODIS image of the Gulf of Mexico oil spill, and one Landsat 8 image of a Persian Gulf oil spill. The oil spills in different remote sensing images could be detected accurately by the proposed method in a small set of samples. Experimental results indicated that the proposed method was suitable for detecting marine oil spills in AVIRIS, MODIS, and Landsat 8 images. In addition, the SGE method with the LIS strategy was more suitable for detecting oil spills in HSI. Its proper elimination rates were 0.8~1.0. The SGE method with the LID strategy was more suitable for detecting oil spills in MSI. Its proper elimination rates were 0.5~0.7. Full article
(This article belongs to the Special Issue Innovation and Sustainable Development of Remote Sensing Technology)
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20 pages, 3248 KiB  
Article
Manure Effect on Soil–Plant Interactions in Capia Pepper Crops under Semiarid Climate Conditions
Sustainability 2022, 14(20), 13695; https://doi.org/10.3390/su142013695 - 21 Oct 2022
Cited by 1 | Viewed by 1495
Abstract
One of the biggest threats to agro-ecosystems, especially in arid and semiarid areas, is the deterioration of soil quality, which is associated with low soil organic matter levels. Despite the elevated volume of publications related to soil quality and crops, information about specific [...] Read more.
One of the biggest threats to agro-ecosystems, especially in arid and semiarid areas, is the deterioration of soil quality, which is associated with low soil organic matter levels. Despite the elevated volume of publications related to soil quality and crops, information about specific plants such as the Capia pepper (Capsicum annuum L. cv.) with clear economic relevance in semiarid environments is missing. The aim of present study is to investigate the effects of different doses of manure on Capia pepper focusing on soil–plant interaction, soil quality, and plant yield in an experimental area located in Turkey. Key soil properties were monitored and relationships between plant and soil properties were evaluated using the principal component analysis (PCA). At the end of the first and second growing season, the effects of manure application on some plant and soil characteristics were statistically significant at different levels. According to the PCA result, 15 plant characteristics and 7 soil characteristics were grouped into five factors and defined 85.4% and 90.9% of the total variability in the population in the first and second growing seasons, respectively. Our research concluded that sustainable soil management such as the use of specific dose of manure improves soil quality and plant productivity. Full article
(This article belongs to the Section Sustainable Agriculture)
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16 pages, 2786 KiB  
Article
The Optimal Urban Scale from Different Perspectives and under Different Development Goals Based on the CES Utility Function
Sustainability 2022, 14(20), 13694; https://doi.org/10.3390/su142013694 - 21 Oct 2022
Viewed by 909
Abstract
To analyze the differences in the optimal urban scale of a country, a government, and residents under different urban development goals and to provide a reference for urban development, an urban development model is constructed based on the constant elasticity of substitution (CES) [...] Read more.
To analyze the differences in the optimal urban scale of a country, a government, and residents under different urban development goals and to provide a reference for urban development, an urban development model is constructed based on the constant elasticity of substitution (CES) utility function. The objective function includes four indicators: the economic level, the traffic level, environmental quality, and living conditions. The urban development model is constructed by integrating an urban road planning model, bus route planning model, land use model, and four-stage traffic sharing and traffic allocation model. Based on the setting of different development goals, this model is used to calculate the urban utility value perceived by each stakeholder at different urban scales. Through comparative analysis, we determine the following: (1) When the urban development goals are different, the optimal urban scale of residents and the government differs greatly, and the optimal scale of the country differs very little. (2) When facing the same development goal, the optimal urban scales of the three stakeholders are not the same. However, the three stakeholders are closely related to urban development. Therefore, the selection of the optimal urban scale should comprehensively consider the interests of the three stakeholders. Full article
(This article belongs to the Section Sustainable Urban and Rural Development)
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20 pages, 3066 KiB  
Article
Consumption-Driven Carbon Emission Reduction Path and Simulation Research in Steel Industry: A Case Study of China
Sustainability 2022, 14(20), 13693; https://doi.org/10.3390/su142013693 - 21 Oct 2022
Cited by 5 | Viewed by 1680
Abstract
China’s steel industry’s carbon emissions accounted for more than 60% of global carbon emissions, approximately 15% in China in 2020. China’s steel industry accounted for approximately 16% of China’s total carbon emissions in 2021. The ability to reduce the carbon dioxide emissions generated [...] Read more.
China’s steel industry’s carbon emissions accounted for more than 60% of global carbon emissions, approximately 15% in China in 2020. China’s steel industry accounted for approximately 16% of China’s total carbon emissions in 2021. The ability to reduce the carbon dioxide emissions generated by the steel industry and protect the living environment for humans and nature has become a realistic issue for China. This paper constructs a steel consumption–carbon emission system. Research shows that by adjusting the GDP growth rate and CO2 emissions per unit of steel production, the carbon peak in the steel industry will advance to 2030 and the carbon emissions after the peak will be significantly reduced. The reduction in steel consumption in the construction and machinery sectors does not have a significant impact on carbon emissions from the steel industry, whereas the reduction in steel consumption in the transportation and infrastructure sectors has contributed to carbon reduction activities in the steel industry. When all four sectors are regulated simultaneously, it is found that the predicted carbon peaking time for the steel sector advances to 2029, fulfilling the goal of achieving carbon peaking by 2030. Carbon emissions should decrease after that point. Full article
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21 pages, 4649 KiB  
Article
The Possibility of Providing Acoustic Comfort in Hotel Rooms as an Element of Sustainable Development
Sustainability 2022, 14(20), 13692; https://doi.org/10.3390/su142013692 - 21 Oct 2022
Cited by 2 | Viewed by 1372
Abstract
The noise problem in hotel rooms is strictly connected to noise generated by heating, ventilating, and air conditioning (HVAC) devices. Hospitality industry companies in many countries have specific requirements and monitor the noise level with technical equipment inside the hotel room. To ensure [...] Read more.
The noise problem in hotel rooms is strictly connected to noise generated by heating, ventilating, and air conditioning (HVAC) devices. Hospitality industry companies in many countries have specific requirements and monitor the noise level with technical equipment inside the hotel room. To ensure an adequately low level of noise from the HVAC system, proper calculations and tests are performed before the final application of the system in the hotel room. One of the best methods for assessing the noise level from HVAC devices in hotel rooms is to create a testing room (mock-up) in a certain available space, e.g., in a warehouse, and to perform appropriate standard measurements for the noise level. This method is a popular choice in the hotel industry because the noise level can not only be verified, but also, the installation and operation of the HVAC system inside the room can be checked. The main factors in choosing the space in which the mock-up will be made are availability and appropriate volume. It is not always possible to provide a hall space with a very low background level of noise. This article shows that the selection of a mock-up space is also determined by the noise level in the selected space. The background noise level—thus, the noise level in the mock-up room—must be low enough to be able to reliably measure the noise level from the HVAC equipment to avoid the phenomenon of acoustic masking by other noise sources (background noise) not related to the measurement. Background noise at too high a level will lead to invalidation of the measurement results or overestimation of the actual noise level in the room from the tested HVAC devices. In this study, background noise level measurements made in the testing rooms are described. The results are discussed, and a conclusion is drawn. Full article
(This article belongs to the Special Issue Technology, Organisation and Management in Sustainable Construction)
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19 pages, 1579 KiB  
Article
Eastern Poland Consumer Awareness of Innovative Active and Intelligent Packaging in the Food Industry: Exploratory Studies
Sustainability 2022, 14(20), 13691; https://doi.org/10.3390/su142013691 - 21 Oct 2022
Cited by 4 | Viewed by 1824
Abstract
For some time, traditional food packaging has not been able to meet the current market demand in some segments. This is mainly due to the advancing market globalization, increasing product complexity, the changing and increasingly high expectations and needs of customers, increasing requirements [...] Read more.
For some time, traditional food packaging has not been able to meet the current market demand in some segments. This is mainly due to the advancing market globalization, increasing product complexity, the changing and increasingly high expectations and needs of customers, increasing requirements for monitoring packaging materials and, consequently, food safety, as well as the revival of national and international initiatives to support the circular economy and minimize the carbon footprint of manufactured products. Therefore, smart packaging with increased functionality has become indispensable. On the one hand, this solution allows for the offering or adaptation of products that meet the stricter national and international regulatory requirements (in particular for food safety) and allows a tracking from the cradle to the grave; on the other hand, it can serve as a way to expand markets in the context of globalization. Moreover attention should be paid to the development of knowledge on environmental protection and the increasing environmental awareness of consumers. In connection with the above, in recent years there has been an increase in interest in the design and production of new packaging for food products based on the latest technical and technological solutions. It is primarily intelligent and active packaging that should be mentioned here. Hence, the aim of the article, as well as that of our own conducted research, was to analyze consumer attitudes and behaviors in the field of modern food packaging, as well as to check the level of awareness of consumers from Eastern Poland in relation to innovative active and intelligent packaging in the food industry. In addition, the intermediate aim was also to identify other factors influencing the attractiveness of food packaging and, consequently, increasing the willingness to buy them. To achieve these aims, a literature study was carried out, as well as empirical research using the diagnostic survey method, conducted among the inhabitants of South-Eastern Poland. Based on our own research, it can be concluded that the level of knowledge of the essence of intelligent and active packaging in Eastern Poland is still at a low level. Among the other factors increasing the attractiveness of packaging for food products, contemporary consumers from the analyzed region of Poland indicated primarily their environmental friendliness, the possibility of recycling, as well as the readability and transparency of the information contained on the packaging. Full article
(This article belongs to the Section Sustainable Materials)
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26 pages, 2619 KiB  
Article
Evaluation of Green Manufacturing Level in China’s Provincial Administrative Regions Based on Combination Weighting Method and TOPSIS
Sustainability 2022, 14(20), 13690; https://doi.org/10.3390/su142013690 - 21 Oct 2022
Cited by 3 | Viewed by 1336
Abstract
Green manufacturing is becoming an important emerging field in the new round of global industrial revolution and scientific and technological competition. Scientific evaluation of China’s regional green manufacturing level has far-reaching significance for promoting the transformation and upgrading of the manufacturing industry and [...] Read more.
Green manufacturing is becoming an important emerging field in the new round of global industrial revolution and scientific and technological competition. Scientific evaluation of China’s regional green manufacturing level has far-reaching significance for promoting the transformation and upgrading of the manufacturing industry and enhancing international competitiveness. This paper defines the connotation of green manufacturing in China in the new era, proposes four dimensions of green production, green emission, green technology, and green benefit as the framework of the evaluation system, and constructs the evaluation index system. By taking 30 provincial administrative regions as research samples, based on the data from 2017 to 2020, the combination weighting method and TOPSIS are used for evaluation from the perspective of “static” and “dynamic” to identify the current situation and development of green manufacturing level in each region. It was found that the important factors affecting the green manufacturing level in each region are green products, green invention patents, sulfur dioxide, green factories, and coal consumption. The “static” evaluation results show that the green manufacturing level varies significantly among regions. The eastern area is generally better than the central and western areas, and only six regions are at high-level and medium to high-level. In addition, the four dimensions in most regions are imbalanced, with an obvious Matthew effect. The “dynamic” evaluation results show that the green manufacturing level in 30 regions appears to have six different types of dynamic trends. There is a small change in the ranking of most regions, indicating that the dynamic development of green manufacturing level has clear regional dependence, which is difficult to change in the short term. The research results show that the index system and model can effectively evaluate the regional green manufacturing level. Finally, combined with the important influencing factors, some suggestions are proposed to enhance the regional green manufacturing level. Full article
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22 pages, 5991 KiB  
Article
Long-Term Effects of COVID-19, and Its Impact on Business, Employees, and CO2 Emissions, a Study Using Arc-GIS Survey 123 and Arc-GIS Mapping
Sustainability 2022, 14(20), 13689; https://doi.org/10.3390/su142013689 - 21 Oct 2022
Cited by 3 | Viewed by 1702
Abstract
Further investigation is needed to study the impacts of the COVID-19 lockdown and subsequent lifestyle changes. The global pandemic caused a high degree of uncertainty, leading to extreme anxiety. These feelings were also compounded by the sudden changes in lifestyle at home, within [...] Read more.
Further investigation is needed to study the impacts of the COVID-19 lockdown and subsequent lifestyle changes. The global pandemic caused a high degree of uncertainty, leading to extreme anxiety. These feelings were also compounded by the sudden changes in lifestyle at home, within families, work, studies, and recreation. With the end of the lockdown approaching in most regions of the world, many of these lifestyle changes, including work-from-home, might remain for a good percentage of the workforce. The primary objective of this research is to explore employees’ work-from-home model and its impact on commute time, job satisfaction, and carbon footprint. Quantitative variables include data from North America and Global country-specific carbon dioxide (CO2) emissions, and quantitative data, including employee satisfaction, commute time, miles traveled, and more, was collected using ArcGIS Survey123. This research focus on CO2 emissions data, comparing 2019 data (March to May) as a baseline to 2020, 2021, and 2022 (March to May) as the target year. The hypothesis is that the work-from-home order had a significant impact on short-term CO2 reductions and could have potential long-term impacts due to many corporations’ adoption of the “work-from-home” model. The data collected regarding CO2 were analyzed using ArcGIS Pro and Geostatistical Interpolation. This study also explored the potential impacts of this adoption on employee job satisfaction and CO2 emissions reductions based on surveyed employees. Another objective of this research is to look at the relationship between the COVID-19 lockdown with the work-from-home model and the reduction in air emissions, namely CO2. Full article
(This article belongs to the Collection Impact of COVID-19 on the Environment, Energy and Economics)
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16 pages, 17629 KiB  
Article
Analysis of Wind Turbine Distances Using a Novel Techno-Spatial Approach in Complex Wind Farm Terrains
Sustainability 2022, 14(20), 13688; https://doi.org/10.3390/su142013688 - 21 Oct 2022
Cited by 3 | Viewed by 1199
Abstract
Among the current challenges facing the energy sector is finding environmentally friendly and high-performance forms of energy generation. One such form of energy generation is from the wind. In addition to the fluctuations that cause changes in the generated energy, another factor that [...] Read more.
Among the current challenges facing the energy sector is finding environmentally friendly and high-performance forms of energy generation. One such form of energy generation is from the wind. In addition to the fluctuations that cause changes in the generated energy, another factor that significantly affects the overall efficiency of wind farms is the distance between the turbines. In that context, a distance of at least three diameters (3D) onwards is necessary to enable a stable operation. This is more difficult to implement for mountainous terrain due to the terrain configuration’s influence, the turbine units’ positioning, and the mutual influence resulting from their position in the area under consideration. This work investigates the interdependence of the terrain features, the placement of ten turbines in different scenarios, and the impact on the overall efficiency of the wind farm. The place where the wind farm is considered is in Koznica, a mountainous area near Prishtina. An analysis has been carried out for two-diameter (2D), three-diameter (3D), and five-diameter (5D) turbine blade spacing for turbines with a rated power of 3.4 MW. The study considers placement in the following forms: Arc, I, L, M, and V. The results show that for 2D distance layout, the capacity factors for Arc, I, L, M, and V placements have the values: 32.9%, 29.8%, 31.1%, 30.6%, and 37.1%. For the 3D distance, according to these scenarios, the capacity factor values are: 29.9%, 30.8%, 30.4%, 29.3%, and 35.6%. For the longest distance, 5D, the capacity factor values are: 28.9%, 29.9%, 29.4%, 27.6%, and 30.6%. The value of the capacity factor for an optimal layout; is achieved at 39.3%. Full article
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20 pages, 1558 KiB  
Article
Internet, Green Innovation and Industrial Upgrading
Sustainability 2022, 14(20), 13687; https://doi.org/10.3390/su142013687 - 21 Oct 2022
Cited by 3 | Viewed by 1508
Abstract
The internet and green innovation are important driving forces to promote industrial high-quality and sustainable development at present. Studying their independent and interactive effects on industrial upgrading is of great practical and theoretical significance. Based on the panel data of 30 provinces in [...] Read more.
The internet and green innovation are important driving forces to promote industrial high-quality and sustainable development at present. Studying their independent and interactive effects on industrial upgrading is of great practical and theoretical significance. Based on the panel data of 30 provinces in China from 2006 to 2019, this paper constructs a spatial error model based on four weight matrices to study independent and interactive effects of the internet and green innovation on industrial upgrading. The results show that the internet, green innovation, and industrial upgrading have significant spatial correlation, with all showing high–high and low–high agglomeration trends. Both the internet and green innovation contribute to industrial upgrading, and their interaction effect is more significant for enhancing industrial upgrading. The heterogeneity analysis finds that green innovation has a greater impact on industrial upgrading in eastern China, and the internet in the central and western regions has a greater impact on industrial upgrading. Few previous studies put the internet, green innovation, and industrial upgrading into the unified framework. This paper expands and enriches the research on the relationship among the three to analyze the independent and interactive effects of the internet and green innovation on industrial upgrading by spatial metrology. We also promote the construction, promotion, and application of the internet and optimization of the green innovation environment, taking the “Internet plus green innovation” strategy as the foothold and implementing differentiation and a dynamic strategy that provides a reference for how to realize the transformation and upgrading of China’s industrial structure through the internet and green-innovation strategy. Full article
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15 pages, 2688 KiB  
Article
Techno-Economic Analysis of Integrated Solar Photovoltaic Winnower-Cum Dryer for Drying Date Palm Fruit
Sustainability 2022, 14(20), 13686; https://doi.org/10.3390/su142013686 - 21 Oct 2022
Cited by 3 | Viewed by 1460
Abstract
Date palm (Phoenix dactylifera L.) fruits are widely grown in rural areas of arid Rajasthan of India. The grown date palm fruits are generally dried in forced convection mode. However, given the socio-economic status of farmers, dryer facility affordability has become crucial. [...] Read more.
Date palm (Phoenix dactylifera L.) fruits are widely grown in rural areas of arid Rajasthan of India. The grown date palm fruits are generally dried in forced convection mode. However, given the socio-economic status of farmers, dryer facility affordability has become crucial. Additionally, there is a critical need for a simple winnower, especially with its operation. To address the highlighted issues with the dryer and winnower and given a location already receiving abundant solar radiation, a solar photovoltaic (PV) winnower cum-dryer was designed and developed. The developed winnower cum-dryer was tested in actual conditions to realize the performance. First, the drying experiment for dehydrating date palm fruits and, second, the winnower experiment for separating grains from straw were carried out. The date palm fruits used for experimentation have a moisture content of 65% on a wet basis. During the drying trial, the dryer reduced this moisture content by 39% in 6 days. In contrast, in the open sun drying, it took 8 days. The drying chamber’s temperature gradient was reduced to 2–3 °C from 6–8 °C in the system provided with a preheater, resulting in uniform drying. The observed effective moisture diffusivity and the dryer’s efficiency are 4.34 × 10−9 m2·s−1 and 16.1%, respectively. A high IRR of 57.4% and a shorter payback period of 2.10 years were found in the economic analysis, indicating that the dryer is cost-effective. The winnower operation results suggest that about 200–300 kg grains could be separated daily when used as a winnower without natural wind. Overall, the developed winnower cum-dryer produced better-quality dried date palms in a shorter time than open drying by efficiently using solar energy and separating the grains from straw to enhance the utility throughout the year. Full article
(This article belongs to the Special Issue Sustainable Circular Bioeconomy)
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17 pages, 1769 KiB  
Article
Classification of Cotton Genotypes with Mixed Continuous and Categorical Variables: Application of Machine Learning Models
Sustainability 2022, 14(20), 13685; https://doi.org/10.3390/su142013685 - 21 Oct 2022
Cited by 2 | Viewed by 1266
Abstract
Mixed data is a combination of continuous and categorical variables and occurs frequently in fields such as agriculture, remote sensing, biology, medical science, marketing, etc., but only limited work has been done with this type of data. In this study, data on continuous [...] Read more.
Mixed data is a combination of continuous and categorical variables and occurs frequently in fields such as agriculture, remote sensing, biology, medical science, marketing, etc., but only limited work has been done with this type of data. In this study, data on continuous and categorical characters of 452 genotypes of cotton (Gossypium hirsutum) were obtained from an experiment conducted by the Central Institute of Cotton Research (CICR), Sirsa, Haryana (India) during the Kharif season of the year 2018–2019. The machine learning (ML) classifiers/models, namely k-nearest neighbor (KNN), Classification and Regression Tree (CART), C4.5, Naïve Bayes, random forest (RF), bagging, and boosting were considered for cotton genotypes classification. The performance of these ML classifiers was compared to each other along with the linear discriminant analysis (LDA) and logistic regression. The holdout method was used for cross-validation with an 80:20 ratio of training and testing data. The results of the appraisal based on hold-out cross-validation showed that the RF and AdaBoost performed very well, having only two misclassifications with the same accuracy of 97.26% and the error rate of 2.74%. The LDA classifier performed the worst in terms of accuracy, with nine misclassifications. The other performance measures, namely sensitivity, specificity, precision, F1 score, and G-mean, were all together used to find out the best ML classifier among all those considered. Moreover, the RF and AdaBoost algorithms had the highest value of all the performance measures, with 96.97% sensitivity and 97.50% specificity. Thus, these models were found to be the best in classifying the low- and high-yielding cotton genotypes. Full article
(This article belongs to the Special Issue Sustainable Management of Water Resource and Environmental Monitoring)
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24 pages, 4499 KiB  
Article
An Analysis of Renewable Energy Technology Integration Investments in Malaysia Using HOMER Pro
Sustainability 2022, 14(20), 13684; https://doi.org/10.3390/su142013684 - 21 Oct 2022
Cited by 19 | Viewed by 2930
Abstract
Renewable energy systems are technologies that can generate electricity from solar, wind, hydroelectric, biomass, and other renewable energy resources. This research project aims to find the best renewable energy technology combinations for several scenarios in Malaysia. The strategies are analysed by evaluating the [...] Read more.
Renewable energy systems are technologies that can generate electricity from solar, wind, hydroelectric, biomass, and other renewable energy resources. This research project aims to find the best renewable energy technology combinations for several scenarios in Malaysia. The strategies are analysed by evaluating the investments in the renewable energy systems in each of the decided scenarios in Malaysia, Pekan, Pahang and Mersing, Johor, using HOMER Pro software. The finding shows that the PV–wind hybrid system has a better net present cost (NPC) than the other systems for both scenarios, which are USD −299,762.16 for Scenario 1 and USD −642,247.46 for Scenario 2. The PV–wind hybrid system has 4.86-year and 2.98-year payback periods in Scenarios 1 and 2. A combination of RE technologies yielded fewer emissions than one kind alone. The PV–wind hybrid system provides a quicker payback period, higher money savings, and reduced pollutants. The sensitivity results show that resource availability and capital cost impact NPC and system emissions. This finding reveals that integrated solar and wind technologies can improve the economic performance (e.g., NPC, payback period, present worth) and environmental performance (e.g., carbon dioxide emissions) of a renewable energy system. Full article
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15 pages, 2371 KiB  
Article
Study on the Spatio-Temporal Evolution of Land Use in Resource-Based Cities in Three Northeastern Provinces of China—An Analysis Based on Long-Term Series
Sustainability 2022, 14(20), 13683; https://doi.org/10.3390/su142013683 - 21 Oct 2022
Cited by 1 | Viewed by 1201
Abstract
Land is the basis of development, and the unique patterns of the spatio-temporal evolution of land use in resource-based cities can reflect regional development, help land resources to be used efficiently and rationally, promote scientific regulation, and achieve high-quality development. Based on the [...] Read more.
Land is the basis of development, and the unique patterns of the spatio-temporal evolution of land use in resource-based cities can reflect regional development, help land resources to be used efficiently and rationally, promote scientific regulation, and achieve high-quality development. Based on the land use data of resource-based cities in three northeastern provinces from 1980 to 2020, the spatio-temporal evolution characteristics and driving factors of land use in the sample study area were studied by the Markov transfer matrix and a parametric optimal geographic detector model. The results showed that: (1) From the perspective of time, the land use changes in the sample study area were active, mainly reflected in the continuous conversion of forest land transfer-out (11.66%) and arable land transfer-in (11.28%), and the dynamic attitude of forest land showed a trend of decreasing, then increasing and then decreasing, while the dynamic attitude of arable land showed a trend of increasing, then decreasing and then increasing. (2) Spatially, the areas where land conversion occurred were mainly concentrated in the northern part of the study area and the border area in the east, which is also the area where forest land was converted to arable land and grassland was converted to arable land, and the expansion of construction land was more common; (3) In terms of influencing factors, land conversion before 2000 was mainly influenced by socio-economic factors, and population quantity and urbanization rate had stronger explanatory power. The spatial and temporal evolution of forest land conversion to arable land was realized by the interaction of various factors, and the driver interactions were all non-linearly enhanced and bi-factor enhanced. (4) In terms of influencing factors, land conversion before 2000 was mainly influenced by socio-economics, with population quantity and urbanization rate having a stronger explanatory power; after 2000, land conversion was mainly influenced by physical geography, with precipitation and temperature having a stronger explanatory power. (5) The spatio-temporal evolution of forest land conversion to cropland was realized by the interaction between various factors, and the driving factor interactions all showed non-linear enhancement and bifactor enhancement. Full article
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16 pages, 2608 KiB  
Article
Three-Party Evolutionary Game of Shared Manufacturing under the Leadership of Core Manufacturing Company
Sustainability 2022, 14(20), 13682; https://doi.org/10.3390/su142013682 - 21 Oct 2022
Cited by 3 | Viewed by 1124
Abstract
Shared manufacturing provides a new development direction for the transformation and upgrading of the manufacturing industry. This paper took a manufacturing company that masters core technology and has strong knowledge creation and spillover capabilities as the core manufacturing company. The core manufacturing company [...] Read more.
Shared manufacturing provides a new development direction for the transformation and upgrading of the manufacturing industry. This paper took a manufacturing company that masters core technology and has strong knowledge creation and spillover capabilities as the core manufacturing company. The core manufacturing company led two resource-complementary manufacturing companies in participating in shared manufacturing, and the additional benefits of each company participating in shared manufacturing were realized. Due to the bounded rational behavior of the participating companies and the difficulty in maximizing each’s own interests, this paper used the evolutionary game method and MATLAB to analyze the influencing factors of shared manufacturing among manufacturing companies. The goal of this study is to understand the decision-making behavior of manufacturing companies in a shared manufacturing context. The research results show that: The initial willingness to share, default losses, and excess income realized by the core manufacturing company as a result of delivering high service levels all contributed to the companies’ willingness to engage in shared production. The companies’ ability to participate in shared manufacturing was negatively impacted by cost-to-income ratio and speculative income. The allocation of additional income had a significant influence on the non-core enterprises’ decision-making: when the distribution ratio of additional income from non-core companies was low, non-core companies would be less willing to share. Although the additional income distribution ratio of core companies were high at the time, the service level of core companies would also decrease due to the reduction of non-core companies’ willingness to share. Full article
(This article belongs to the Section Sustainable Management)
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12 pages, 519 KiB  
Article
Psychometric Parameters of the Intrinsic Motivation Inventory Adapted to Physical Education in a Sample of Active Adults from Austria
Sustainability 2022, 14(20), 13681; https://doi.org/10.3390/su142013681 - 21 Oct 2022
Viewed by 1947
Abstract
Introduction. Intrinsic motivation is essential for establishing life-long positive behaviors. In Physical Education (PE), this variable may have a significant impact on students’ choice of adhering to an active lifestyle both in the short and long term. Many tools have been developed for [...] Read more.
Introduction. Intrinsic motivation is essential for establishing life-long positive behaviors. In Physical Education (PE), this variable may have a significant impact on students’ choice of adhering to an active lifestyle both in the short and long term. Many tools have been developed for the assessment of intrinsic motivation, among which the Intrinsic Motivation Inventory (IMI) was built based on the Self-Determination Theory. The aim of this study is to examine a version of the IMI adapted to PE (IMI-PE). Methods. A total of 660 customers of a Sports Service Center responded to the IMI-PE and 39 individuals carried out a test–retest of the tool within two weeks. Results. The initial model including the original pool of items showed low indexes of goodness of fit. However, the removal of item 6, 8, 13, and 14 led to excellent parameters for the four-factor model (CFI = 0.96, and SRMR = 0.0420). Internal consistency and reliability analyses confirmed the robustness of such model. The final IMI-PE, comprising 14 items distributed into four factors, represents a robust assessment tool for the analysis of intrinsic motivation in PE. Full article
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13 pages, 4644 KiB  
Article
Buffer Capacity of Steel Shed with Two Layer Absorbing System against the Impact of Rockfall Based on Coupled SPH-FEM Method
Sustainability 2022, 14(20), 13680; https://doi.org/10.3390/su142013680 - 21 Oct 2022
Cited by 1 | Viewed by 1542
Abstract
This study aimed to find the optimal thickness combination of the two-layered absorbing system combinated with an expanded polystyrene (EPS) cushion and a soil layer in a steel shed under dynamic loadings. The coupled Smooth Particle Hydrodynamic method (SPH) and Finite Element Method [...] Read more.
This study aimed to find the optimal thickness combination of the two-layered absorbing system combinated with an expanded polystyrene (EPS) cushion and a soil layer in a steel shed under dynamic loadings. The coupled Smooth Particle Hydrodynamic method (SPH) and Finite Element Method (FEM) were introduced to simulate the impact of the rockfall against the steel shed with a two-layer absorbing system. By comparing the numerical results with test data, the coupled numerical model was well validated. Through the verified numerical model, a series of numerical experiments were carried out to find the optimal combination for the two-layered absorbing system. The values of the EPS layer thickness as a percentage of the total thickness were set as 0% (P1), 20% (P2), 40% (P3), 60% (P4), 80% (P5), and 100% (P6). The results show that the coupled FEM–SPH method was an effective method to simulate rockfall impacting the steel rock shed; P4 (0.6 m thickness EPS cushion and 0.9 m thickness soil layer) was the most efficient combination, which can significantly reduce the structural displacement response by 43%. A two-layered absorbing system can effectively absorb about 90% of the total energy. The obtained results yield scientifically sound guidelines for further research on the design of steel sheds against rockfall. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction)
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19 pages, 3321 KiB  
Article
Agronomic Evaluation of Recycled Polyurethane Foam-Based Growing Media for Green Roofs
Sustainability 2022, 14(20), 13679; https://doi.org/10.3390/su142013679 - 21 Oct 2022
Cited by 1 | Viewed by 1055
Abstract
Green roofs are very popular and their individual surface area is constantly growing. Considering that the organo-mineral materials used in planting growing media (GM) are often non-renewable resources, the search for alternative materials from waste recycling is a challenge. Among these, recycled polyurethane [...] Read more.
Green roofs are very popular and their individual surface area is constantly growing. Considering that the organo-mineral materials used in planting growing media (GM) are often non-renewable resources, the search for alternative materials from waste recycling is a challenge. Among these, recycled polyurethane (PU) foams are light and porous. The objective of this study was to evaluate the potential agronomic valorisation of PU foams for extensive green roofs. Three GM based on compost, PU foam and topsoil were developed and tested in situ for 18 months along with four plant species in containers containing 15 cm of GM. The agronomic properties of the GM and their contaminant contents were evaluated, as well as the plant aerial and root biomasses and trace element levels. The main results of this work are that GM are suitable for plant growth. Compost ratio effect resulted in a lower pH and higher exchangeable cations in GM1, whereas topsoil proportion effect mainly decreased macroporosity and increased nutrient contents. Furthermore, due to the high trace element load in the compost, hyperaccumulator plants such as Hypericum calycinum and Stipa tenuissima should be preferred. Ecotoxicological analyses will be carried out to validate the absence of risk of PU foam contaminants being released in the environment before proposing these types of GM to green roof developers. Full article
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12 pages, 2817 KiB  
Article
Efficient Degradation of Carbendazim by Ferrate(VI) Oxidation under Near-Neutral Conditions
by and
Sustainability 2022, 14(20), 13678; https://doi.org/10.3390/su142013678 - 21 Oct 2022
Cited by 1 | Viewed by 1072
Abstract
Carbendazim (CBZ), a widely used fungicide in agriculture, is frequently detected in aquatic environment and causes significant concerns because of its endocrine-disrupting activity. This study investigated the degradation kinetics of CBZ in ferrate (Fe(VI)) oxidation, the influence of water matrices, and the transformation [...] Read more.
Carbendazim (CBZ), a widely used fungicide in agriculture, is frequently detected in aquatic environment and causes significant concerns because of its endocrine-disrupting activity. This study investigated the degradation kinetics of CBZ in ferrate (Fe(VI)) oxidation, the influence of water matrices, and the transformation pathways of CBZ. The second-order rate constant for the reaction between CBZ and Fe(VI) decreased from 88.0 M−1·s−1 to 1.6 M−1·s−1 as the solution pH increased from 6.2 to 10.0. The optimum reaction conditions were obtained through response surface methodology, which were pH = 7.8 and [Fe(VI)]/[CBZ] = 14.2 (in molarity), and 96.9% of CBZ could be removed under such conditions. Cu2+ and Fe3+ accelerated the degradation of CBZ by Fe(VI) oxidation; common cations and anions found in natural water had no significant effect, while the presence of humic acid also accelerated the degradation of CBZ. Based on the degradation products identified, degradation of CBZ in Fe(VI) oxidation proceeded via three pathways: namely, hydroxylation, removal of the methoxyl group, and cleavage of the C–N/C=N bond. The initial reaction site of CBZ oxidation by Fe(VI) was also supported by the atomic partial charge distribution on the CBZ molecule obtained from density functional theory (DFT) calculations. CBZ in natural water matrices was efficiently removed by Fe(VI) oxidation under near-neutral conditions, indicating that Fe(VI) oxidation could be a promising treatment option for benzimidazole fungicides. Full article
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20 pages, 2119 KiB  
Article
Evaluation and Empirical Research on Eco-Efficiency of Financial Industry Based on Carbon Footprint in China
Sustainability 2022, 14(20), 13677; https://doi.org/10.3390/su142013677 - 21 Oct 2022
Cited by 4 | Viewed by 1144
Abstract
Since finance is the core of economic development, the green development of the financial industry is an essential driving force not only for achieving the dual “carbon” goal of China but also for economic and social sustainable development. An accurate understanding of the [...] Read more.
Since finance is the core of economic development, the green development of the financial industry is an essential driving force not only for achieving the dual “carbon” goal of China but also for economic and social sustainable development. An accurate understanding of the ecological efficiency of the financial industry is of great importance for guiding sustainable economic development. In this paper, we first calculate the carbon footprint of China’s financial industry in 2012 and 2017 based on the life cycle theory and the input–output analysis method. Second, we analyze the primary sources and final flows of the carbon footprint of the financial industry in each province from the perspectives of the industrial chain and final demand. Finally, we estimate the ecological efficiency, emission reduction, and value-added potential of the financial industry by using the radially adjusted slack variable DEA model (SRAM-DEA) under two assumptions, natural disposability and managerial disposability. The results show that (1) the ecological efficiency of the financial industry in most provinces is low, and the regional differences are significant; (2) the overall ecological efficiency of the financial industry in 2017 was better than that in 2012; (3) technological innovation of financial products and the upgrading of capital supervision play an essential role in promoting the improvement of ecological efficiency. Especially, under managerial disposability, the ecological efficiency of the financial industry in each province has a greater potential for emission reduction and added value. Full article
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19 pages, 1452 KiB  
Article
The Watershed Communal Land Management and Livelihood of Rural Households in Kilte Awlaelo Woreda, Tigray Region, Ethiopia
Sustainability 2022, 14(20), 13676; https://doi.org/10.3390/su142013676 - 21 Oct 2022
Cited by 1 | Viewed by 1132
Abstract
While the degradation of natural resources has a substantial impact on the livelihood of farmers in rural areas, there is scant empirical evidence about livelihood status and benefits from communal resources, especially whether the benefits are equally distributed among local farmers. This study [...] Read more.
While the degradation of natural resources has a substantial impact on the livelihood of farmers in rural areas, there is scant empirical evidence about livelihood status and benefits from communal resources, especially whether the benefits are equally distributed among local farmers. This study examines how the conservation of communal lands affects the food security status and the livelihood of the poor people in the Tigray region of Ethiopia. This paper employed both descriptive statistics and econometric analyses using the ordinary least square regression and quantile regression models. The food security status of rural households was found to be negatively associated with the direct use of natural resources generated on conserved communal lands. The study further affirms that households in the lower quantile harness more of the direct use of common property resources. However, households in the median and the upper quantiles tend to engage in the indirect use of resources generated on communal lands. These findings pose a critical policy implication regarding how to reconcile the trade-offs between the consequence of heavy dependence of the poor on the direct use of communal land-based resources and ensuring sustainable livelihood by allowing the poor to collect benefits from the conserved lands. Full article
(This article belongs to the Special Issue Economics Perspectives on Sustainable Food Security)
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16 pages, 2964 KiB  
Article
A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions
Sustainability 2022, 14(20), 13675; https://doi.org/10.3390/su142013675 - 21 Oct 2022
Cited by 7 | Viewed by 1196
Abstract
In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is [...] Read more.
In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model. Full article
(This article belongs to the Section Resources and Sustainable Utilization)
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20 pages, 1654 KiB  
Article
Green Loans and Green Innovations: Evidence from China’s Equator Principles Banks
Sustainability 2022, 14(20), 13674; https://doi.org/10.3390/su142013674 - 21 Oct 2022
Cited by 3 | Viewed by 1966
Abstract
Green innovation is critical for promoting environmental protection but largely relies on the support of bank financing. How the participation of banks facilitates green innovation remains largely unexplored. Using a sample of A-share listed firms in China, this study examines the impact of [...] Read more.
Green innovation is critical for promoting environmental protection but largely relies on the support of bank financing. How the participation of banks facilitates green innovation remains largely unexplored. Using a sample of A-share listed firms in China, this study examines the impact of new loans from Equator Principles banks on green innovations. Consistent with the framework of the stakeholder theory, we find that new loans from Equator Principles banks significantly foster green innovations of borrowing firms. Several robustness tests are conducted, and the conclusion remains valid. Further analysis shows that the relief of financial constraints of borrowing firms and the scrutiny of corporate financing projects by Equator Principles banks jointly contribute to the promotion of corporate green innovation. Heterogeneity tests indicate that new loans from Equator Principles banks are more effective in heavily polluting and more competitive industries and among firms with higher levels of executive education. Overall, our findings suggest that stakeholder engagement in environmental governance is an important means of improving corporate green innovations in emerging markets. Full article
(This article belongs to the Special Issue Accounting, Corporate Policies and Sustainability)
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16 pages, 4455 KiB  
Article
Good Agricultural Practices Related to Water and Soil as a Means of Adaptation of Mediterranean Olive Growing to Extreme Climate-Water Conditions
Sustainability 2022, 14(20), 13673; https://doi.org/10.3390/su142013673 - 21 Oct 2022
Cited by 3 | Viewed by 1509
Abstract
Despite the fact that the olive tree is one of the best-adapted species in Mediterranean hydroclimate conditions, climate extremes impose negative effects on olive fruit set and development and subsequently on crop yield. Considering that the frequency of climate extremes is increasing in [...] Read more.
Despite the fact that the olive tree is one of the best-adapted species in Mediterranean hydroclimate conditions, climate extremes impose negative effects on olive fruit set and development and subsequently on crop yield. Considering that the frequency of climate extremes is increasing in the last years due to climate change, Good Agricultural Practices (GAPs) have to be applied in order to mitigate their impact on olive trees. In this context, 18 experimental olive groves (irrigated and rainfed) were established, located on the island of Crete (south Greece). A set of 13 GAPs were applied in different combinations, mainly targeting to reduce water losses and erosion, alleviate heat stress and increase water use efficiency. Each experimental orchard was divided into two parts, the control (business-as-usual) and experimental (GAPs implementation). Four indicators were used for the assessment of GAPs performance, namely, Water Productivity (WP), Economic Water Productivity (EWP), Runoff (RF), and Yield (Y). WP and EWP were found to be up to 2.02 and 2.20 times higher, respectively, in the demonstration part of the orchards compared to the control, while Y was found to be up to 119% higher. RF was higher up to 190% in the control compared to the demonstration part of the experimental orchards. The above results clearly demonstrate that the implementation of the proposed GAPs can significantly support the adaptation of olive crops to extreme conditions. Full article
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15 pages, 1082 KiB  
Review
Review of Publications on the Water-Energy-Food Nexus and Climate Change Adaptation Using Bibliometric Analysis: A Case Study of Africa
Sustainability 2022, 14(20), 13672; https://doi.org/10.3390/su142013672 - 21 Oct 2022
Cited by 4 | Viewed by 1750
Abstract
Access to clean water, reliable energy services and adequate food supply are basic needs for life and contribute to the reduction of national and global levels of human poverty and forced migration. This study concentrated on reviewing progress made in understanding the relationship [...] Read more.
Access to clean water, reliable energy services and adequate food supply are basic needs for life and contribute to the reduction of national and global levels of human poverty and forced migration. This study concentrated on reviewing progress made in understanding the relationship between the Water-Energy-Food (WEF) nexus and climate change adaptation, using Africa as a case study. The method used to achieve this objective was the bibliometric analysis, covering the period from 1980–2021. Data used for this study were acquired from the Web of Science (WoS) and Scopus databases. Initially, 95 documents were retrieved from the WoS and Scopus core collection databases, but 30 duplicates were removed, and 65 documents were used. The outputs were further analysed using the bibliometric R package and VOS viewer. Analysis of the top 100 keywords in the 65 publications that link WEF nexus with climate change adaptation for Africa showed that 46 keywords fall under the application of WEF nexus, 31 keywords under the implementation of WEF nexus and 23 keywords under the implication of WEF nexus. Researchers from countries around the world have published the WEF nexus work undertaken on the African continent. Countries with the highest number of publications were South Africa, the United Kingdom, the United States of America, Germany, Kenya and Zimbabwe. Thematic analysis was used to explore the conceptual structure of WEF publications, and it produced four themes: (i) well-established concepts appropriate for structuring the conceptual framework of the field of WEF nexus in Africa; (ii) strongly developed concepts but still marginal for the field of WEF nexus in Africa; (iii) not fully developed or marginally interesting concepts for the field of WEF nexus in Africa, and (iv) significant cross-cutting concepts in the field of WEF nexus in Africa in relation to climate change adaptation. This study contributes to the growing body of literature on the WEF nexus by pointing out dominant themes from those that are still emerging in the scholarly work done in Africa. Full article
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10 pages, 280 KiB  
Article
Perception of Healthy Organizational Practices of Workers in the Chilean Educational Sector and Impact on Their Levels of Engagement and Burnout
Sustainability 2022, 14(20), 13671; https://doi.org/10.3390/su142013671 - 21 Oct 2022
Cited by 2 | Viewed by 1235
Abstract
Even before the COVID-19 pandemic, teaching was considered one of the most stressful occupations, one that could provoke burnout in workers. Continuing to provide educational services despite the pandemic and the new methodologies was a challenge for teachers that demonstrated their engagement in [...] Read more.
Even before the COVID-19 pandemic, teaching was considered one of the most stressful occupations, one that could provoke burnout in workers. Continuing to provide educational services despite the pandemic and the new methodologies was a challenge for teachers that demonstrated their engagement in their work. This research, from the model of healthy and resilient organizations (HERO), aimed to assess the perception of healthy organizational practices (HOP) of teachers of an educational institution during the years 2020 and 2021 and the impact they have on their levels of engagement and burnout. Through the application of three instruments, 154 responses were obtained. The data were analyzed through correlations and mean comparisons. The main results show that in 2020, the correlations between HOP with engagement and burnout were positive and negative, respectively, as expected. In 2021, the perception of HOP decreased, as did teacher engagement, while burnout increased. In conclusion, the findings suggest that HOP can become a sustainable human resource management tool that promotes teachers’ mental health, even in challenging times. Full article
19 pages, 3712 KiB  
Article
An Effective Secured Dynamic Network-Aware Multi-Objective Cuckoo Search Optimization for Live VM Migration in Sustainable Data Centers
Sustainability 2022, 14(20), 13670; https://doi.org/10.3390/su142013670 - 21 Oct 2022
Cited by 2 | Viewed by 1104
Abstract
With the increasing use of cloud computing by organizations, cloud data centers are proliferating to meet customers’ demands and host various applications using virtual machines installed in physical servers. Through Live Virtual Machine Migration (LVMM) methods, cloud service providers can provide improved computing [...] Read more.
With the increasing use of cloud computing by organizations, cloud data centers are proliferating to meet customers’ demands and host various applications using virtual machines installed in physical servers. Through Live Virtual Machine Migration (LVMM) methods, cloud service providers can provide improved computing capabilities for server consolidation maintenance of systems and potential power savings through a reduction in the distribution process to customers. However, Live Virtual Machine Migration has its challenges when choosing the best network path for maximizing the efficiency of resources, reducing consumption, and providing security. Most research has focused on the load balancing of resources and the reduction in energy consumption; however, they could not provide secure and optimal resource utilization. A framework has been created for sustainable data centers that pick the most secure and optimal dynamic network path using an intelligent metaheuristic algorithm, namely, the Network-aware Dynamic multi-objective Cuckoo Search algorithm (NDCS). The developed hybrid movement strategy enhances the search capability by expanding the search space and adopting a combined risk score estimation of each physical machine (PM) as a fitness criterion for ensuring security with rapid convergence compared to the existing strategies. The proposed method was assessed using the Google cluster dataset to ascertain its worthiness. The experimental results show the supremacy of the proposed method over existing methods by ensuring services with a lower total migration time, lower energy consumption, less makespan time, and secure optimum resource utilization. Full article
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21 pages, 8426 KiB  
Article
Mechanical Strength of Saline Sandy Soils Stabilized with Alkali-Activated Cements
Sustainability 2022, 14(20), 13669; https://doi.org/10.3390/su142013669 - 21 Oct 2022
Cited by 12 | Viewed by 1632
Abstract
Saline soils usually cannot satisfy the requirements of engineering projects because of their inappropriate geotechnical properties. For this reason, they have always been known as one of the problematic soils worldwide. Moreover, the lack of access to normal water has intensified the use [...] Read more.
Saline soils usually cannot satisfy the requirements of engineering projects because of their inappropriate geotechnical properties. For this reason, they have always been known as one of the problematic soils worldwide. Moreover, the lack of access to normal water has intensified the use of saline water resources such as seawater in many construction and mining projects. Although cement stabilization is frequently used to improve the engineering properties of saline soils, Portland cement’s usage as a binder is constrained by its negative consequences, particularly on the environment. In this line, the effects of NaCl on the microstructural and mechanical properties of alkali-activated volcanic ash/slag-stabilized sandy soil were investigated in this study. Moreover, the effects of binder type, slag replacement, curing time, curing condition, and NaCl content on the mechanical strength of stabilized soils were examined. In addition, microstructural analyses, including XRD, FTIR, and SEM–EDS mapping tests, were performed to understand the physical and chemical interaction of chloride ions and alkali-activated cements. The results show that alkali-activated slag can be a sustainable alternative to Portland cement for soil stabilization projects in saline environments. The increase in sodium chloride (NaCl) content up to 1 wt.% caused the strength development up to 244% in specimens with 50 and 100 wt.% slag, and adding more NaCl had no significant effect on the strength in all curing conditions. Microstructural investigations showed that the replacement of volcanic ash with slag resulted in the formation of C-S-H and C-A-S-H gels that reduced the porosity of the samples and increased mechanical strength. Furthermore, surface adsorption and chemical encapsulation mechanisms co-occurred in stabilized soil samples containing slag and volcanic ash. Full article
(This article belongs to the Special Issue Sustainable Building Materials: An Eco-Approach for Construction)
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12 pages, 4846 KiB  
Article
Assessment of a Fast Proxy of Vs30 (Vs30m)
Sustainability 2022, 14(20), 13668; https://doi.org/10.3390/su142013668 - 21 Oct 2022
Cited by 1 | Viewed by 1146
Abstract
The most frequent parameter used to quantify seismic site response in ground motion models is time-averaged shear wave velocity in the top 30 m of a site (Vs30), used by many engineering design codes and most recently by published empirical-scaling equations to estimate [...] Read more.
The most frequent parameter used to quantify seismic site response in ground motion models is time-averaged shear wave velocity in the top 30 m of a site (Vs30), used by many engineering design codes and most recently by published empirical-scaling equations to estimate the amplitudes of strong ground motion. The current study explores the potential comparison of the results from the predictive equations and formula recommendations by the international building code. A total of 53 synthetic and real data models with distinct types of vs. profile were used to determine the theoretical dispersion curves and avoid forward and inverse modeling. In the prediction equation, VR36 and VR40 were employed to estimate Vs30. Furthermore, using VR40, based on the 53 different models, shows a good agreement with Vs30. The thickness of the first layer substantially affects the correlation. The findings calculated by the correlation are not in the acceptable zone for layer thicknesses of 10 < H < 20 m and thin layers at shallow depths with lower shear wave velocity. Full article
(This article belongs to the Section Hazards and Sustainability)
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33 pages, 5091 KiB  
Article
Comparison of the Performance of Hybrid Traffic Signal Patterns and Conventional Alternatives When Accounting for Both Pedestrians and Vehicles
Sustainability 2022, 14(20), 13667; https://doi.org/10.3390/su142013667 - 21 Oct 2022
Cited by 1 | Viewed by 1103
Abstract
Traffic control systems are crucial for managing traffic flows. Their main function is to reduce interactions among users for safety reasons, while minimizing the travel times. Researchers often concentrate on the cycle length, whose impact on travel times is directly measurable. However, the [...] Read more.
Traffic control systems are crucial for managing traffic flows. Their main function is to reduce interactions among users for safety reasons, while minimizing the travel times. Researchers often concentrate on the cycle length, whose impact on travel times is directly measurable. However, the choice of the signal pattern may also have a great potential to reduce travel times and unsafe situations. This potential is yet to be thoroughly investigated. In this work, we are interested in comparing different signal patterns in terms of the number of potential conflicts and delay time for both drivers and pedestrians. To this end, we first select three commonly adopted signal patterns, namely the Exclusive Pedestrian Phase (EPP), the Leading Through Interval (LTI) and the Two-Way Crossing (TWC). We then generalize existing methods for measuring user delay and safety for these three signal patterns. Moreover, we investigate a hypothetical hybrid pattern obtained by dynamically adapting the signal pattern to real-time data. The proposed methodology is applied to a case study considering an isolated intersection in Montreal, Canada. We perform computational experiments geared towards determining the best pattern according to ad hoc performance indicators and user flows. Results show that the EPP and LTI patterns generally perform better than TWC. EPP generally outperforms LTI when measuring the number of potential conflicts, while LTI outperforms EPP when considering delay times. Furthermore, the hypothetical hybrid pattern shows a positive but overall limited impact regarding both delay times and number of potential conflicts. Full article
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