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The efficiency of renewable energy sources like PV and fuel cells is improving with advancements in technology. However, maximum power point (MPP) tracking remains the most important factor for a PV-based fuel cell power system to perform at its best. The MPP of a PV system mainly depends on irradiance and temperature, while the MPP of a fuel cell depends upon factors such as the temperature of a cell, membrane water content, and oxygen and hydrogen partial pressure. With a change in any of these factors, the output is changed, which is highly undesirable in real-life applications. Thus, an efficient tracking method is required to achieve MPP. In this research, an optimal salp swarm algorithm tuned fractional order PID technique is proposed, which tracks the MPP in both steady and dynamic environments. To put that technique to the test, a system was designed comprised of a grid-connected proton exchange membrane fuel cell together with PV system and a DC-DC boost converter along with the resistive load. The output from the controller was further tuned and PWM was generated which was fed to the switch of the converter. MATLAB/SIMULINK was used to simulate this model to study the results. The response of the system under different steady and dynamic conditions was compared with those of the conventionally used techniques to validate the competency of the proposed approach in terms of fast response with minimum oscillation.

This paper proposes a multi-objective planning framework for electric vehicle (EV) charging stations in emerging power networks that move towards green transportation electrification. Four cases are investigated to study the impacts of EV integration on environmental and economic requirements. In order to facilitate the installation of EV charging stations, the proposed model is formulated to combine the planning models of renewable energy systems, energy storage systems (ESSs), thyristor-controlled series compensators, and transmission lines into the EV-based planning problem. The first objective function aims to maximize EVs’ penetration by increasing the networks’ capacity to supply charging stations throughout the day, whereas the second objective, on the other hand, emphasizes lowering the carbon dioxide emissions from fossil fuel-based generation units in order to benefit the environment. The third objective is to meet the financial requirements by lowering the initial investment and operating costs of the installed devices. The proposed model is written as a multi-objective optimization problem that is solved using the multi-objective version of the Gazelle optimization algorithm (MGOA). The efficiency of the MGOA was tested by solving a set of four benchmark test functions and the proposed problem. The obtained results demonstrated the MGOA’s superiority in solving multi-objective optimization problems when compared to some well-known optimization algorithms in terms of robustness and solution quality. The MGOA’s robustness was between 20% and 30% and outperformed other algorithms by 5%. The MGO was successful in outperforming the other algorithms in providing a better solution. The Egyptian West Delta Network simulations revealed a 250 MWh increase in the energy supplied to EVs when energy storage was not used. However, storage systems were necessary for shifting EV charging periods away from high solar radiation scenarios. The use of ESS increased greenhouse gas emissions. When ESS was installed with a capacity of 1116.4 MWh, the carbon emissions increased by approximately 208.29 million metric tons. ESS’s role in improving the EV’s hosting capacity grows as more renewables are added to the network. ESS’s role in improving the EV’s hosting capacity rises as more renewables are added to the network.

To remedy the widespread chromium (Cr) pollution in the environment, this study mainly used the ultrasonic-assisted co-precipitation and precipitation methods to prepare FeS-modified Fe-Al-layered double hydroxide (FeS/LDH) composite material. The experimental results showed that FeS/LDH has higher removal efficiency of Cr in aqueous solution and stronger anti-interference ability than unmodified LDH. Under the same reaction conditions, the removal efficiency of total Cr(Cr(T)) using LDH was 34.85%, and the removal efficiency of Cr(VI) was 46.76%. For FeS/LDH, the removal efficiency of Cr(T) and Cr(VI) reached 99.57% and 100%, respectively. The restoration of Cr(T) and Cr(VI) by FeS/LDH satisfied the Langmuir adsorption isotherm. The maximum adsorption capacity of Cr(T) and Cr(VI) achieved 102.9 mg/g and 147.7 mg/g. The efficient removal of Cr by FeS/LDH was mainly based on the triple synergistic effect of anion exchange between Cr(VI) and interlayer anions, redox of Cr(VI) with Fe2+ and S2−, and co-precipitation of Fe3+ and Cr3+.

This quantitative investigation aims to test the model of responsible consumption behavior (RCB). The specific purpose is to examine the relationship of pro-environmental behavior, attitudes, norms, intention, and awareness using the theory of planned behavior as an underlying theoretical framework. A multistage sampling technique was used to select people (n = 665). Data were collected using a self-administered questionnaire from sample respondents. The data were analyzed using structural equation modeling (SEM)–partial least square (PLS). The findings revealed that attitudes, norms, and awareness all have a role in predicting the intention to engage in post-consumer plastic packaging activity. This finding supports the theory of planned behavior, and it can be extended to explain environmental behavior by adding a reasonable variable.

Post-disaster reconstruction (PDR) is a dynamic, complex system that is chaotic in nature, and represents many challenges and issues. Recently, building information modelling (BIM) has been commonly utilized in the construction industry to solve complex and dynamic challenges. However, BIM has not been thoroughly considered for managing PDR, and there is a lack of comprehensive scientometric analyses that objectively examine the trends in BIM applications in PDR. A literature search was performed considering studies published from 2010 to March 2021 using the Scopus database. A total of 75 relevant studies were found to meet the inclusion criteria. The collected literature was analyzed using VOSviewer through scientific journals, authors, keywords, citations, and countries. This is the first study in its vital significance and originality that aims to investigate the current states of research on BIM applications in PDR and provide suggestions for potential research directions. The findings showed that “Reconstruction” and “Safety Management” have emerged as mainstream research themes in this field and recently attracted scholars’ interest, which could represent the directions of future research. Five major research domains associated with BIM were identified based on the most frequently used keywords, namely “Disasters”, “Earthquakes”, “HBIM”, “Damage Detection”, and “Life Cycle”. Moreover, a proposed conceptual framework of BIM adoption for PDR is provided. Accordingly, the outcomes of this study will help scholars and practitioners gain clear ideas of the present status and identify the directions of future research.

Swedish municipalities use negotiable developer obligations and public land development in sustainability-profiled districts to achieve various public sustainability objectives. They initiate and govern these districts, which act as models for sustainable urban development and testbeds for new sustainability-related policies, using municipally owned land. Public land development in Sweden enables municipalities to include sustainability-oriented negotiable developer obligations in development agreements. The aim of the study is to investigate how Swedish municipalities use sustainability-oriented negotiable developer obligations together with public land development, and to identify what public value outcomes they currently seek to create by using these public value capture instruments. Sustainability-oriented negotiable developer obligations are investigated in relation to municipalities’ desired public value outcomes in five sustainability-profiled district developments in different Swedish municipalities. Findings illustrate that Swedish municipalities use negotiable developer obligations to create ecological, social and cultural, political, and economic public value outcomes. This calls for more research investigating different forms of value and value creation in relation to public value capture instruments.

Germany carried out a nationwide “Alert Day” in 2020 to test its civil alarm systems. The test revealed some problems. Heterogeneous development structures and topography can be limiting factors for sound propagation. In consequence, sirens could be heard inadequately, depending on their location. Furthermore, the reason of warning remains unknown to the public. In terms of civil protection, warnings with the code of behavior by general available media is desired. Smart sirens can transmit additional spoken information and be installed on already-existing streetlights. In this study, we analyze how smart sirens could lead to an improved civil protection. Exemplarily, a detailed analysis is made for a different structured rural area, Dansenberg in Germany, whereas the influence of local conditions on the sound propagation is considered. We analyzed with the software CadnaA—a software for calculation, assessment and prediction of environmental sound—how the location and number of smart sirens can be optimized in order to produce a full coverage of the study area. We modeled the coverage in different scenarios and compared four scenarios: (a) current situation with two E57 type sirens; (b) replacing the existing sirens with two high-performance sirens; (c) one high-performance siren at the more central point; and (d) optimized network of smart sirens of the type Telegrafia Bono. The aim was to achieve a full coverage with a minimum of warning sirens. We could show that the current situation with two E57 type sirens fails to reach out to the whole population whereas the optimized network of smart sirens results in a better coverage. Therefore, a reconsideration of the existing warning system of civil protection with smart sirens could result in a better coverage and improved information of warning.

This paper describes the construction of a model to explore the effectiveness of environmental protection taxes on haze emission reduction in China. The model is based on panel data from 30 provinces and cities in China, from 2003–2019. It is found that the current environmental protection tax has a significant inhibitory effect on haze. In addition, an upfront pollutant discharge fee can guide enterprises to significantly reduce the emission of haze-causing pollutants. A robustness test is conducted, using the variable substitution method of taking sulfur dioxide (SO2) as haze, and the research conclusions are consistent. We then put forward three specific suggestions: (1) Expand the scope of the environmental protection tax, gradually increase the tax rate, or adopt an excessive progressive tax rate. For example, China could consider including mobile pollution sources into the scope of taxation. (2) Increase the supervision and collection of the environmental protection tax. (3) Strengthen the multiple linkages between regional taxation departments and environmental protection departments, in order to form a collaboration between the departments in an effort to control haze and promote the sustainable development of the Chinese economy and the environment.

Conservation of traditional olive groves through effective monitoring of their health state is crucial both at a tree and at a population level. In this study, we introduce a comprehensive methodological framework for estimating the traditional olive grove health state, by considering the fundamental phenotypic, spectral, and thermal traits of the olive trees. We obtained phenotypic information from olive trees on the Greek island of Lesvos by combining this with in situ measurement of spectral reflectance and thermal indices to investigate the effect of the olive tree traits on productivity, the presence of the olive leaf spot disease (OLS), and olive tree classification based on their health state. In this context, we identified a suite of important features, derived from linear and logistic regression models, which can explain productivity and accurately evaluate infected and noninfected trees. The results indicated that either specific traits or combinations of them are statistically significant predictors of productivity, while the occurrence of OLS symptoms can be identified by both the olives’ vitality traits and by the thermal variables. Finally, the classification of olive trees into different health states possibly offers significant information to explain traditional olive grove dynamics for their sustainable management.

A heavily degraded hardé area in the community of Gawel (Extreme Nord) was rehabilitated with a ReviTec approach. To evaluate the efficiency of introduced plants for rehabilitation, the site was monitored with the BioSoilPlot experiment over two years during the dry and rainy seasons (January 2018/2019, June 2018/2019, respectively). ReviTec was applied to accelerate ecological succession and improve the establishment of vegetation on these degradation-prone sites (Gawel 1 and Gawel 2). Growth volume, height and percentage cover of the herbaceous plants and soil physical and chemical parameters were assessed. Growth volume increased in both sites between 2018 and 2019 with Pennisetum pedicellatum exhibiting the highest values (Gawel 1: 3.41 dm3/m2 and 3.50 dm3/m2; Gawel 2: 3.47 dm3/m2 and 3.62 dm3/m2). Bunds were suitable for herbaceous growth, Sesbania sesban having the highest growth height (Gawel 1: 1.91 cm and 1.95 cm; Gawel 2: 1.95 cm and 1.97 cm) and Pennisetum pedicellatum the best percentage cover (Gawel 1: 53% and 58.33%; Gawel 2: 40.67% and 56.67%). Soil changed from sandy and strongly acid to clay-loam and slightly acid at Gawel 1, and from sandy and strongly acid to clay-loam and alkaline at Gawel 2. Soil water content and soil nutrient had increased within the ReviTec site compared to the outside with the application of compost-biochar-mycorrhiza treatment as the most promising over the two years of monitoring. Such results suggest that ReviTec approach can be used in sustainable restoration of soil hardé.

Cost and performance-effective materials used in advanced oxidation processes such as photocatalysis have obtained widespread attention in recent years. In this study, thermal spraying was used as a one-step method to obtain thick visible-light-active photocatalyst coatings on two types of substrates, namely, plain carbon steel and copper. A mixed metallic titanium–silicon powder bearing 10% wt. Si was used as feedstock. The optical bandgaps of the coatings were close to 1.000 eV, allowing good photodecoloration efficiencies (>89%) and mineralization efficiencies (>67%) for methylene blue dye from aqueous solutions under visible light irradiation. The photodegradation process could be successfully modelled by the Langmuir–Hinshelwood pseudo-first-order kinetic model, with reaction rate constants k between 0.16 and 1.06 h−1.

Basic Chinese medical insurance has achieved full coverage, but the inequality between urban and rural areas is still outstanding. Under this background, the government proposed the urban-rural Integrated Medical Insurance System which proposes two kinds of financing modes. Based on the decision-making theory of medical insurance and the logit regression model, this paper studies the influence of two kinds of financing modes on middle-aged and elderly people’s decisions to participate in integrated medical insurance in China. The two financing modes are “single-standard” and “multi-standard”. The results show that the two kinds of financing methods have positive and significant effects, and the incentive effect of “multi-standard” on the integrated medical insurance is greater than that of “single-standard”. Having an urban household registration promotes the development of the “multi-standard”. However, there are some central provinces are not eable to improve the integrated medical insurance participation rate through “multi-standard”. Improving the participation rate of integrated medical insurance can promote the balanced allocation of resources between urban and rural areas, as well as different income groups and regions. Moreover, it can ensure a smooth transition of medical insurance policies. We should hold and boost the financing method of “multi-standard” to guarantee medical insurance integration’s rapid and steady progress in China.

Phuket is well-known around the world as a popular tourist destination. Tourism-related population growth depends more on groundwater as the only available source of potable water in Phuket. The proper precautions must be taken to reduce the risk of spending large sums of money in sinking abortive boreholes, and a groundwater potential map would enhance the success rate of future groundwater exploration and exploitation in the study area. Geoelectrical surveys were carried out in this study to collect electrical properties of the subsurface, and the Dar-Zarrouk parameters (DZP) were calculated using the geoelectrical data. The first thematic groundwater potential map was constructed using the interpretation of DZP, while the second thematic groundwater potential map was created using the basis maps of the depth-of-basement and aquifer thickness parameters. Finally, two thematic maps based on geographic information system (GIS) environments were overlaid on a groundwater potential map of Phuket. However, in order to provide a reliable assessment of groundwater potential, time-lapse electrical resistivity imaging was used to confirm the area of the high-potential zone indicated on the map. The map created by this study is aimed to act as a reference for future groundwater exploration and exploitation, preventing water supplies from becoming unsustainable through botched borehole drilling for groundwater production.

Online professional communities based on sharing under open licenses have become a new way of building knowledge, learning and professional development of the participants who build and expand their professional identity in the new global space. These new dynamics of cyberculture are not being sufficiently explored in the training of vocational students. However, open pedagogy models can foster pre-professional identity, influence academic success and self-perception, as well as contribute to the commons. In this study, we have investigated from the anthropological perspective, the impact of a training program based on an open pedagogy model. Specifically, we have investigated the effect on the pre-professional identity and the academic results of vocational students, as well as on the development of the commons of their profession. Methodologically, we have combined the bibliographic review with the empirical, quantitative, and qualitative data, collected in the ethnographic fieldwork carried out during two academic years on 77 students of “Microcomputer Systems and Networks”, in a vocational center located in the Community of Valencia (Spain). The results indicate that this methodology promotes, among students, the development of pre-professional identity, a better understanding of copyright and open licenses, appreciation of the documentation processes of their tasks, and the value of their works for society.

With regard to the scientific debate which highlights the potential of joint climate planning, there are few concrete experiences in Europe where this approach has been applied. This contribution focuses on critical methodological and application aspects of the processes underlying the development of Joint Plans for Sustainable Energy and Climate in the supra-municipal area as emerged from the direct participation of the authors in the Joint_SECAP project funded by the Interreg Italia-Croatia programme. This paper presents a comparative analysis of nine case studies in Italy and Croatia with a focus on fundamental aspects of the planning process: the governance model, shared knowledge framework, risk and vulnerability assessment, and participatory process. The analysis and comparison of the Joint_SECAP experiences confirm that joint climate planning, developed in the framework of the European Covenant of Mayors (CoM) initiative, is effective for creating synergy between local authorities and for defining and implementing strategies and actions for adaptation to the territorial scale. Finally, the research indicates some recommendations to overcome the barriers that impede the spread and effectiveness of this approach to climate planning. In particular, it highlights the need to enhance collaboration between local authorities, regions, and CoM coordinators.

This Special Issue aims to explore current challenges and trends, as well as opportunities for sustainability and innovation, in the fields of agricultural and industrial water management [...]

Contemporary cities are complex systems in which there are many interactions and dependencies in relation to the environment. Currently, the development of cities and their safety are among the most important international socio-economic processes. The movement of people to larger agglomerations from smaller towns creates a variety of relationships between actors and often leads to very complicated lives in urban space. Features of contemporary cities include urbanization, personal development opportunities, labor markets, and infrastructure, as well as technological and cybernetic networks that optimize all the processes taking place in agglomerations. It should be emphasized that the main goal of public management in urban space is to create various solutions in the field of safety and thus to improve the quality of. In this respect, the role and influence of stakeholders on the processes of smart and safe city development are important. At each stage of activity, the City Council, local communities, economic entities, scientific institutions, and municipal enterprises are important for a city’s safety. This article emphasizes the importance of stakeholders in the process of managing a safe city. The article presents a literature review, as well as research results based on the example of Polish cities, presenting the importance of stakeholders in managing safe cities.

The objective of our investigation was to verify a questionnaire’s suitability in identifying managerial competencies concerning managers’ personality characteristics. Methods: For the content validity of the questionnaire assessment of managerial competencies (AMC23), we investigated its coherence with the appraisal of the management style methodology, i.e., managerial grid (MG), with correlation analysis. The existence of statistically significant relationships between the assessment of managerial competencies and managers’ personality characteristics was determined using Pearson’s correlation coefficient concerning the BIG-5 model. Results: In total, 573 managers participated in this study. Our examination concludes that motivational competencies correlated positively with the compromise and cooperative style; performance competencies with the competitive and cooperative style; and social competencies with the cooperative, adaptive, and compromise style. Not least, target competencies positively correlated with the competitive and cooperative style. Further, neuroticism negatively correlated with social managerial competence, extraversion, and openness to experience, which positively correlated with motivational and target competence. Friendliness was positively associated with social competence, and diligentness positively correlated with motivational, performance, and target competence. Conclusion: We determined significant correlations between managerial competencies (AMC23) and managerial style (MG). Our findings might have implications for further investigation and the development of more comprehensive instruments to assess managerial competencies in connection with managers’ personalities. We point out the need for further research to verify, improve, and constitute a model that further elucidates and explains managerial competencies.

Used cooking oils (UCOs) have a high potential as renewable fuels for the maritime shipping industry. However, their corrosiveness during storage and usage are some of the concerns yet to be investigated for addressing compatibility issues. Thus, the corrosion of steels and copper exposed to the UCOs was studied through the immersion of metal rods for different periods. The changes on the rod surfaces were analyzed with a scanning electron microscope (SEM). After the immersion, the copper concentration dissolved in the bio-oils was measured using inductively coupled plasma-optical emission spectrometry (ICP-OES). The free fatty acids and glycerides were analyzed using gas chromatography with flame ionization detection (GC-FID). The acid number (AN), water concentration, as well as density and kinematic viscosity of the bio-oils were determined with standard methods. The UCOs with the highest water content were corrosive, while the oils with lower water concentrations but higher ANs induced lower corrosion. After mixing two different UCOs, the metal corrosion decreased with an increasing concentration of the oil with lower corrosive properties. The lower corrosion properties were most likely due to the monounsaturated fatty acids, e.g., oleic acid in oils. These acids formed a barrier layer on the rod surfaces, thereby inhibiting the permeation of oxygen and water to the surface. Even adding 0.025 wt% of tert-butylamine decreased the corrosivity of UCO against polished steel rod. The results suggested that mixing several oil batches and adding a suitable inhibitor reduces the potential corrosive properties of UCOs.

Nowadays, the aviation industry pays more attention to emission reduction toward the net-zero carbon goals. However, the volume of global passengers and baggage is exponentially increasing, which leads to challenges for sustainable airports. A baggage-free airport terminal is considered a potential solution in solving this issue. Removing the baggage operation away from the passenger terminals will reduce workload for airport operators and promote passengers to use public transport to airport terminals. As a result, it will bring a significant impact on energy and the environment, leading to a reduction of fuel consumption and mitigation of carbon emission. This paper studies a baggage collection network design problem using vehicle routing strategies and augmented reality for baggage-free airport terminals. We use a spreadsheet solver tool, based on the integration of the modified Clark and Wright savings heuristic and density-based clustering algorithm, for optimizing the location of logistic hubs and planning the vehicle routes for baggage collection. This tool is applied for the case study at London City Airport to analyze the impacts of the strategies on carbon emission quantitatively. The result indicates that the proposed baggage collection network can significantly reduce 290.10 tonnes of carbon emissions annually.

In a world with a growing human population, resources are becoming increasingly scarce. To ensure food supply, fertilizers are often used to accelerate growth when planting agricultural products. Sewage sludge (SS), containing as high as 10–15 wt% Phosphorus (P), can be synthesized into liquid fertilizer. P species in SS can generally be classified into four types: inorganic phosphorus (IP), organic phosphorus (OP), nonapatite inorganic phosphorus (NAIP), and apatite phosphorus (AP). However, OP is not leached out by wet chemical methods and NAIP is not bioavailable. This study investigated the P-form conversion (OP and NAIP to AP) in SS by adding 8 wt% CaO at 300 °C. SS through pretreatment can easily leach out P when combined with organic acid. The content of heavy metals is in accordance with fertilizer regulations in a leaching solution. The solution was mixed with potassium and ammonia compounds to synthesize a liquid fertilizer. To ensure the safe and efficient use of liquid fertilizer and undertake an analysis of heavy metals, an aquatic organisms (D. magna) toxicity test, and the growth of plants test were both used. The liquid fertilizer can be demonstrated to accelerate the growth of plants while not causing the death of D. magna in short time, as the liquid fertilizer has enough nutrients to help the D. magna to survive.

Walkability has become a research topic of great concern for preserving public health, especially in the era of the COVID-19 outbreak. Today more than ever, urban and transport policies, constrained by social distancing measures and travel restrictions, must be conceptualized and implemented with a particular emphasis on sustainable walkability. Most of the walkability models apply observation and subjective methods to measure walkability, whereas few studies address walkability based on sense perception. To fill this gap, we aim at investigating the perceived neighbourhood walkability (PNW) based on sense perception in a neighbourhood of Brussels. We designed a survey that integrates 22 items grouped into 5 dimensions (cleanness, visual aesthetics, landscape and nature, feeling of pressure, feeling of safety), as well as the socio-demographic attributes of the participants. Using various statistical methods, we show that socio-demographics have almost no effects on perceived neighbourhood walkability. Nonetheless, we found significant differences between groups of different educational backgrounds. Furthermore, using a binomial regression model, we found strong associations between PNW and at least one item from each grouping dimension. Finally, we show that based on a deep neural network for classification, the items have good predictive capabilities (78% of classification accuracy). These findings can help integrate sense perception into objective measurement methods of walkable environments. Additionally, policy recommendations should be targeted based on differences of perception across socio-demographic groups. This work was supported by the National Fund for Scientific Research F.R.S.-FNRS (grant no 32730312).

Computational decision-making in “real world” environmental and sustainability contexts frequently requires the need to contrast numerous uncertain factors and difficult-to-capture dimensions. Monte Carlo simulation modelling has frequently been employed to integrate the uncertain inputs and to construct probability distributions of the resulting outputs. Visual analytics and data visualization can be used to support the processing, analyzing, and communicating of the influence of multi-variable uncertainties on the decision-making process. In this paper, the novel Simulation Decomposition (SimDec) analytical technique is used to quantitatively examine carbon emission impacts resulting from a transformation of the aviation industry toward a state of greater airline electrification. SimDec is used to decompose a Monte Carlo model of the flying range of all-electric aircraft based upon improvements to batteries and motor efficiencies. Since SimDec can be run concurrently with any Monte Carlo model with only negligible additional overhead, it can easily be extended into the analysis of any environmental application that employs simulation. This generalizability in conjunction with its straightforward visualizations of complex stochastic uncertainties makes the practical contributions of SimDec very powerful in environmental decision-making.

Contrary to energy, exergy may be destroyed due to irreversibility. Exergy analysis can be used to reveal the location, and amount of energy losses of engines. Despite the importance of the exergy analysis, there is a lack of information in this area, especially when the engine is fueled with biodiesel–diesel fuel blends under various injection operating parameters. Thus, in this research, the exergy analysis of a direct-injection diesel engine using biodiesel–diesel fuel blends was performed. The fuel blends (B0, B20, B40, and B100) were injected into cylinders at pressures of 200 and 215 bars. Moreover, the simulation of exergy and energy analyses was done by homemade code. The simulation model was verified by compression of experimental and simulation in-cylinder pressure data. The results showed there was good agreement between simulation data and experimental ones. Results indicated that the highest level of in-cylinder pressure at injection pressure of 215 bars is more than that of 200 bars. Moreover, by increasing the percentage of biodiesel, the heat transfer exergy, irreversibility, burnt fuel, and exergy indicator decreased, but the ratio of these exergy parameters (except for heat transfer exergy) to fuel exergy increased. These ratios increased from 46 to 50.54% for work transfer exergy, 16.57 to 17.97% for irreversibility, and decreased from 16 to 15.49% for heat transfer exergy. In addition, these ratios at 215 bars are higher than at 200 bars for all fuels. However, with increasing the injection pressure and biodiesel concentration in fuel blends, the exergy and energy efficiencies increased.

The relationship between income and pollution is contested, yet wealth alone is insufficient to regulate emissions, which necessitates environmental regulations. Even if inadequate environmental laws may overcome market failures produced by pollution’s negative externality, a thorough examination of their function in pollution management is critical. This research takes a step forward in offering a fresh viewpoint on the function of environmental laws in pollution reduction for BRICS (Brazil, Russia, India, China, and South Africa) nations to better understand the role of environmental regulations in CO2 emission mitigation. The research presented here uses panel data econometric methodologies to achieve this goal, using data from 1995 to 2018. In addition, to provide country-specific findings, the research employs a completely modified ordinary least squares estimator. Environmental laws provide a beneficial influence in reducing carbon emissions. According to the empirical findings, the present environmental regulation positively meets pollution reduction objectives in chosen nations. The environment Kuznets curve (EKC) between pollution and income is controlled by environmental restrictions. Climate change mitigation in BRICS nations is driven by strong environmental policies and economic growth.

Understanding evacuees’ responses to dynamic environmental changes, during an emergency evacuation, is of great importance in determining which aspects are ideal and which aspects should be eliminated or corrected. Evacuees differ in their ability to continually plan escape routes and adapt the routes chosen when they become unsafe owing to moving sources of threat. This is because they have different views and perspectives. The perspectives of evacuees are stochastic and are characterized by a high degree of uncertainty and complexity. To reduce the complexity and control of uncertainty, a model is proposed that can test for variant stochastic representations of evacuees’ perspectives. Two extremely realistic perspectives—the most ideal and the least ideal—are proposed to reasonably limit the range of variance. The success of achieving optimal evacuation is tested when different tendencies towards extreme perspectives are adopted. It is concluded that data toward the most ideal perspectives are capable of demonstrating safer evacuation by reducing the number of simulated burnt agents. This study enables crowd managers and fire safety researchers to test guidance systems as well as configuration of buildings using different perspectives of evacuees.

The problem of the quality of electric energy in the utilization of petroleum gas is considered. The article presents the results of the development of a mathematical description of power supply systems with gas turbine power stations based on two-shaft gas turbine units. The typical power distribution scheme of a gas turbine power station is given. The joint analysis of the generation modes of the gas turbine power station and the detected deviations of the power quality indicators values was carried out. The influence of the used mode on the power quality indicators is determined. As a result, the factors of operation of a gas turbine power station that affects power quality are identified, and recommendations for their elimination are given.

Temperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has been frequently used to forecast air temperature. However, because of its deprived grid resolution and lack of parameterizations, it has systematic distortions. In this study, a gray wolf optimizer (GWO) and a support vector machine (SVM) are used to ensure accuracy and stability of the next day forecasting for minimum and maximum air temperatures in Seoul, South Korea, depending on local data assimilation and prediction system (LDAPS; a model of local NWP over Korea). A total of 14 LDAPS models forecast data, the daily maximum and minimum air temperatures of in situ observations, and five auxiliary data were used as input variables. The LDAPS model, the multimodal array (MME), the particle swarm optimizer with support vector machine (SVM-PSO), and the conventional SVM were selected as comparison models in this study to illustrate the advantages of the proposed model. When compared to the particle swarm optimizer and traditional SVM, the Gray Wolf Optimizer produced more accurate results, with the average RMSE value of SVM for T max and T min Forecast prediction reduced by roughly 51 percent when combined with GWO and 31 percent when combined with PSO. In addition, the hybrid model (SVM-GWO) improved the performance of the LDAPS model by lowering the RMSE values for T max Forecast and T min Forecast forecasting from 2.09 to 0.95 and 1.43 to 0.82, respectively. The results show that the proposed hybrid (GWO-SVM) models outperform benchmark models in terms of prediction accuracy and stability and that the suggested model has a lot of application potentials.

In this study, we explore the association between the intellectual capital (IC) efficiency of firms and their voluntary disclosure of environmental, social, and governance (ESG) information, using data on Jordanian listed firms and the value-added intellectual coefficient (VAIC) model with its three components of human, structural, and relational capital efficiency (HCE, SCE, and RCE, respectively). We find that disclosing environmental information is unrelated to IC efficiency, that disclosing governance information is associated with raised IC efficiency through the HCE and RCE components, and that disclosing social information is negatively associated with IC efficiency through the SCE and RCE components. We also find that releasing information on one or two of the three ESG dimensions has a positive effect on IC efficiency. This evidence has implications for the management of intangible assets.

The agricultural production in Punjab has increased manifold that aggravated the deficiencies of micronutrients in soils and plants. The availability of soil micronutrients in different soil orders depends upon the soil mineralogy, topography, climatic conditions and cropping sequences. Hence, to study the pedospheric variations of DTPA-extractable micronutrients, viz., zinc (Zn), iron (Fe), manganese (Mn) and copper (Cu), in three prominent soil orders of Punjab, a total of 144 depth-wise soil samples were collected from four major land-use systems (cultivated, horticulture, forest and pasture lands). The DTPA extractable micronutrients varied from 1.74–2.81, 1.83–2.82 and 1.81–2.80 for Zn; 5.3–6.8, 5.6–6.9, 4.3–6.3 for Fe; 5.1–7.8, 5.5–7.9, 5.4–7.5 for Mn; and 0.84–1.40, 0.93–1.68, 0.87–1.65 for Cu in soil orders Aridisol, Entisol and Inceptisol, respectively. The average content of DTPA-extractable micronutrients was highest under soil order Entisol followed by Inceptisol and Aridisol. The content of micronutrients showed a declining trend with increase in soil depth in all orders. Among different soil properties, the pH and EC showed significantly negative correlation, however, OC had non-significant correlation with DTPA-extractable micronutrients in soils. Therefore, it is concluded that parent material, land use systems and soil depth affected the distribution of DTPA extractable micronutrients in different soil orders.

The objective of this paper is to model and study the impact of high temperature on mortality in Pakistan. For this purpose, we have used mortality and climate data consisting of maximum temperature, variation in monthly temperature, average rainfall, humidity, dewpoint, as well as average air pressure in the country over the period from 2000 to 2019. We have used the Generalized Linear Model with Quasi-Poisson link function to model the number of deaths in the country and to assess the impact of maximum temperature on mortality. We have found that the maximum temperature in the country has a significant impact on mortality. The number of deaths in Pakistan increases as the maximum temperature increases. We found that, as the maximum temperature increase beyond 30 °C, mortality increases significantly. Our results indicate that mortality increases by 27% when the maximum temperature in the country increases from medium category to a very high level. Similarly, the number of deaths in the country increases by 11% when the temperature increases from medium temperature to high level. Furthermore, our study found that when the maximum temperature in the country decreases from a medium level to a low level, the number of deaths in the country decreases by 23%. This study does not consider the impact of other factors on mortality, such as age, medical conditions, gender, geographical location, as well as variability of temperature across the country.

In this 21st century, there has been an increase in the usage of renewable products for the economic drifting of vehicle transportations systems. Furthermore, due to recent trends in climate change, researchers have started focusing on statistical optimization techniques for sustainable vehicle routings. However, until now, a major gap has been noticed in the multidomain statistical analysis for optimizing the parametric levels of the vehicle fuel economy. Therefore, in this research work, two widely utilized cars (Toyota and GMC Yukon) are considered on a particular route of Jeddah for the collection of the fuel economy data under the realistic conditions of air conditioner temperature, traffic patterns, and tire pressure. The outcomes of the factorial design of the experiment highlight that the fuel economy is optimal under the low air conditioner temperature, light traffic patterns, and 34 PSI tire pressure. Three replications of the fuel economy have been considered, and the statistical significance of the correlated variables has been justified by implementing the analysis of variance (ANOVA) approach on the various levels of fuel economy. During the analysis, the statistical hypothesis for random exogenous factors has been developed by incorporating a multivariate regression model. The outcomes highlight that both air conditioner temperature and traffic patterns in Jeddah have a significant negative effect on fuel economy. Results also depict that the effect of air conditioner temperature, traffic patterns, and tire pressure is substantially higher for heavy-engine automobiles such as the GMC Yukon compared to light-engine cars (Toyota Corolla). Furthermore, a normality test has also been considered to validate the outcomes of the proposed model. Therefore, it is highly recommended to utilize the proposed methodology in optimizing the trends of fuel economy for sustainable vehicle routings. Based on the findings of multidomain statistical analysis, it is also highly recommended the utilization of the Toyota Corolla car model for investigating the correlation of external undeniable factors (braking frequency, metrological conditions, etc.) with the trends of vehicle fuel economy.

Deep learning models are playing an increasingly important role in time series forecasting with their excellent predictive ability and the convenience of not requiring complex feature engineering. However, the existing deep learning models still have shortcomings in dealing with periodic and long-distance dependent sequences, which lead to unsatisfactory forecasting performance on this type of dataset. To handle these two issues better, this paper proposes a novel periodic time series forecasting model based on DA-RNN, called DA-SKIP. Using the idea of task decomposition, the novel model, based on DA-RNN, GRU-SKIP and autoregressive component, breaks down the prediction of periodic time series into three parts: linear forecasting, nonlinear forecasting and periodic forecasting. The results of the experiments on Solar Energy, Electricity Consumption and Air Quality datasets show that the proposed model outperforms the three comparison models in capturing periodicity and long-distance dependence features of sequences.

The firing parameters in ceramic masses incorporated with 0, 5, and 10 wt% of scheelite tailings were investigated. The ceramic masses were characterized by X-ray fluorescence, granulometric, mineralogical analysis, and Atterberg limits determination. The samples were obtained by uniaxial pressing (20 MPa), sintered at different temperatures (800, 900, and 1000 °C), and heating rates (5, 10, 15, and 20 °C∙min−1). Physical and mechanical tests (water absorption, apparent porosity, and flexural strength) and mineralogical tests were accomplished from the sintered samples. Natural aging tests were also carried out to assess carbonation resistance. For this, some samples were kept in an internal environment (inside the laboratory) for 3 months. The results showed a high content of calcium oxide in the scheelite tailings and a reduction in the plasticity index of the ceramic masses with the tailings addition. The best results were observed for the ceramic mass with 5% tailings. The best results were observed regarding the firing parameters for the temperature equal to 1000 °C, increasing the heating rate to 10 °C∙min−1 without compromising the material properties. The samples kept in an internal environment for 3 months showed a loss of physical and mechanical properties. Such behavior probably occurred due to the onset of the carbonation phenomenon.

Heavy metals play an important role in the homeostasis of living cells. However, these elements induce several adverse environmental effects and toxicities, and therefore seriously affect living cells and organisms. In recent years, some heavy metal pollutants have been reported to cause harmful effects on crop quality, and thus affect both food security and human health. For example, chromium, cadmium, copper, lead, and mercury were detected in natural foods. Evidence suggests that these elements are environmental contaminants in natural foods. Consequently, this review highlights the risks of heavy metal contamination of the soil and food crops, and their impact on human health. The data were retrieved from different databases such as Science Direct, PubMed, Google scholar, and the Directory of Open Access Journals. Results show that vegetable and fruit crops grown in polluted soil accumulate higher levels of heavy metals than crops grown in unpolluted soil. Moreover, heavy metals in water, air, and soil can reduce the benefits of eating fruits and vegetables. A healthy diet requires a rational consumption of foods. Physical, chemical, and biological processes have been developed to reduce heavy metal concentration and bioavailability to reduce heavy metal aggregation in the ecosystem. However, mechanisms by which these heavy metals exhibit their action on human health are not well elucidated. In addition, the positive and negative effects of heavy metals are not very well established, suggesting the need for further investigation.

This study aims to identify the configurational conditions that characterize the establishment of biorefineries in 20 European countries. After determining the conditions which support a bioeconomy transition, secondary data from national sources are used to represent their existing conditions within respective countries. Then, a fuzzy-set qualitative comparative analysis is employed to compare and contrast the effect of varying combinations of the selected conditions on the development of biorefineries. The conditions chosen include coherent bioeconomy strategies, network intensity of regional bioclusters, intellectual capital, and natural resource availability. Our results reveal that the configuration of a coherent bioeconomy strategy, sizable public spending on R&D, abundant biomass supply, and a high level of network intensity is sufficient to explain the pronounced biorefineries development among some European countries. We recommend that countries with fragmented approaches review and redesign the policy and regulatory framework to create a holistic and consistent bioeconomy strategy, taking into account the configurations of conditions as an important prerequisite. In particular, factors such as the lack of best practice examples, the low level of public spending on research and development, the economic capacities for a skilled workforce in addition to the sustainable supply of raw materials should be addressed as focal points.

The contemporary demands for massive reductions in industrial pollution caused by the transport sector, especially in large urban agglomerations, compel local and national authorities to propose, develop, and implement programs and policies that have the ultimate goal of significantly reducing (or eliminating) pollution. The aim of this article is to provide a primary analysis of the effectiveness of Romanian government policies in terms of reducing pollution (CO2 emissions) caused by transportation (due to the “Rabla Plus” (RP) program, through which financial subsidies are granted for the purchase of a new plug-in hybrid electric vehicles (PHEVs) or battery electric vehicle (BEVs)). After analyzing the justification for the use of low-emission and electric vehicles in traffic (as a major solution to eliminate pollution), a comparative analysis of energy-efficient transport for Romania and Europe is presented in order to identify the directions in which it is necessary to develop and implement government policies specifically in Romania, considering a series of indicators chosen and considered by the authors to be important, including CO2 emissions compared with the size of the road infrastructure, the number of registered vehicles, the number of passengers transported, and the quantity of goods transported. With the identification of the ability of government programs to encourage the acquisition and use of low-emission and electric vehicles in traffic, the efficiency achieved is calculated in terms of the net CO2 emissions eliminated (average values of 1949.23 CO2 tons/year and 1.71 CO2 tons/vehicle). Furthermore, this aspect is also beneficial for analyses in terms of the economic costs involved (the associated costs are estimated to be 7034.17 EUR/ton of CO2 eliminated from the transportation sector), identifying new directions of action that are more cost-effective and sustainable and on which government policies should focus in the future.

In the last decades, some global events such as the economic crisis of 2008 and the COVID-19 emergency of 2020, have generated more attention towards the housing rental market and its capacity to meet several social needs. In order to study the existent demand for houses, then define the interventions on the residential assets to make them more affordable for the most fragile population groups, adequate evaluation tools are required. With reference to the residential property segment of five metropolitan cities located in the Italian territory, the present research is aimed at analyzing the contribution of the most influencing factors on rental prices. In particular, this research refers to the rented properties of the second half of 2019, with a set of variables that represent the intrinsic and extrinsic factors of the local market. The implementation of an automated valuation model allows the determination of the most significant factors and the functional relationships that they have with housing rental fees. The outputs obtained could support the improvement of equitable public housing policies or could guide private investment decisions, such as refurbishment interventions of certain significant factors that could increase the market rental value. This study is the first step in wider research that is currently in progress, which aims to investigate the effects of the existing COVID-19 pandemic on the residential rental market.

With the rise in online purchases, returns polices have become more lenient to maximise sales, leading to increased product returns. This results in considerable costs to businesses due to complex returns systems, and environmental costs due to unnecessary transportation and waste. Unsustainable consumption poses a threat to our environment, and access-based business models whereby products are borrowed/rented rather than purchased have been proposed as a way to align customer needs, business success, and sustainability. Product returns often constitute a form of informal or illegitimate borrowing, as goods are bought with the intention of being returned. In this discussion paper we propose that, instead of being viewed as a threat to business, issues with high product returns could be seen as an opportunity to switch to an access-based model. As product returns escalate, businesses will need to invest substantially in their reverse supply chains. We propose that a more strategic approach might be to leapfrog the costly stage of developing more efficient returns systems, and move straight to formalising product returns as the new normal for those goods that would best suit an access-based model, so that processes are streamlined around borrowing and returning rather than around sales.

Technological innovation and high-quality economic development are inevitable requirements of sustainable development, and the digital economy has gradually become a new engine to enhance technological innovation and the high-quality development of China’s economy. Deeply discussing the effect of digital economy on high-quality economic development and clarifying the mechanism behind it can effectively grant the boosting power of digital economy to China’s high-quality development, which is of great practical significance to China’s sustainable economic development. In this study, the mechanism, effect, and regional heterogeneity of the impact of the digital economy on the level of high-quality economic development in 30 Chinese provinces from 2011–2019 were measured and empirically tested using a mediating effects model and a spatial Durbin model, among others. The results showed that the overall level of digital economy and high-quality development is not high, and there were both high agglomeration and low agglomeration, with obvious spatial path dependence and spatial lock-in. Digital economy could promote the high-quality development level of the economy, and the spatial spillover effect was remarkable. In addition, the function of digital economy in promoting high-quality economic development in the eastern, central, and western regions was gradually weakened. Besides, the technological innovation was an important transmission path of digital economy to high-quality economic development. Based on these findings, it is proposed that decision-makers should strengthen digitalization efforts so that the digital economy can become a powerful tool to narrow the digital divide. Further, the dynamic and differentiated digital economy development strategy should be implemented to reduce regional development imbalances in an effective manner.

It is difficult for enterprises to adapt to the rapidly developing market demand and increasingly intense competition by relying only on internal resources to carry out innovation activities. We identify three new issues for the Cross-Functional Consortium Families (CFCFs, CF2s) open innovation model based on a cooperating network: participation of large-scale high-tech enterprises (LHEs), impact from open source, and motivation of keeping resource independence. By studying the series cases of Tesla, Inc. (Austin, TX, USA) cooperating with small and medium enterprises (SMEs) through an open source CF2 model, we examined and discussed these three issues and gave new connotations to both open innovation and the CF2 model from perspectives of open source and resources. This paper also provides strategic reference for other LHEs to mitigate the dependency on key resources and generate new key resources accepted by the environment.

With rapid globalization, firm internationalization has become an important corporate strategy as well as the necessity for the survival and growth of the business. In the last decade, there has been a growth in literature that studies this field, especially in emerging countries. However, there exists a gap in the literature in CEE countries. This study aims to fill that gap by conducting an analysis and providing insight regarding the factors that lead to an increase in firm internationalization in this region. This research paper studies the main determinants that have an impact on the firm internationalization of large companies in CEE countries using panel data empirical methods, such as the random effect model and generalized method of moments (GMM) model for a panel of 50 firms from 11 CEE countries and a time duration of 14 years. This study determines the main factors that positively influence firm internationalization in selected countries. These countries have experienced a radical transition from centrally planned economies to market economies, and although they have experienced economic growth and a rise in productivity, they are still facing several challenges. Therefore, it is important to know what facilitates and helps firms to expand in international markets. The main findings derived from this study show that firm characteristics, such as age, size and corporate performance, have a positive effect on the internationalization process. An increase in age, size and firm performance leads to higher levels of internationalization. Larger and relatively older firms have access to more resources and are more experienced in dealing with the environmental difficulties characteristic of these countries.

The hospitality and tourism industry has struggled to deal with the challenges faced after the COVID-19 pandemic began in 2020 [...]

Companies are confronted with increasingly demanding environments, including globalization, technologization, intergenerationality, and crises such as the coronavirus pandemic. To accept uncertainties as a challenge and to recognize opportunities for development, well-educated and resilient founders are needed who can foster innovation and sustainable development within society and the economy. The majority of today’s entrepreneurs have an academic background. Hence, institutions for higher education need to provide comprehensive educational offerings and support initiatives to train and sensitize future entrepreneurs. Therefore, since 2013, agile teaching formats have been developed in our project at a Bavarian university of applied sciences. In two stages, we founded a limited company for hands-on experimentation with entrepreneurship and also conceptualized an elective course and an annual founders’ night. Based on a theoretical model and continuous teaching evaluations, we adjusted the individual modules to suit the target group. The objective is to promote the acquisition of key competencies and exert a positive influence on the startup quotient in the region. There are six startups by students who can be traced back to our project. This indicates that a target-group-oriented educational program encourages motivation and awareness of entrepreneurial thinking and action among students.

International audience; Nowadays, the sustainability of Greek dairy cattle farms is questionable due to low competitiveness and high GHG emissions. In this context, the BIOCIRCULAR project, funded by the EYDE ETAK, developed a series of alternative practices focusing on precision agriculture principles. However, the adoption of any practice from farmers is not a given, and depends on several determinants. Hence, the objective of this study is to examine farmers’ adoption decisions regarding precision-agricultural practices in Greek dairy production systems, as well as the economic and environmental impacts of this adoption. In order to achieve this, a bio-economic model was developed based on mathematical programming methods. The proposed model simulates a large number of dairy cattle farms with or without crop production, including different management strategies and their relevant costs, and provides an environmental assessment of the adopted practices based on GHG emissions. Moreover, in order to analyze farmers’ adoption decisions, different policy measures, linked to various environmental outcomes, were examined. The results highlighted that the adoption of precision-agricultural practices led to significantly better economic and environmental outcomes. Furthermore, it was found that different levels of incentives can be efficiently targeted to encourage the adoption of new feeds and, more broadly, to secure the sustainability of the sector.

In responding to the COVID-19 pandemic, evidence-based policymaking and risk mitigation have been confronted with limited decision-making mechanisms under conditions of increased uncertainty. Such methods are particularly called for in contexts where reliable data to a large extent are missing and where the chosen policy would impact a variety of sectors. In this paper, we present an application of an integrated decision-making framework under ambiguity on how to contain the COVID-19 virus spread from a national policy point of view. The framework was applied in Jordan and considered both local epidemiologic and socioeconomic estimates in a multistakeholder multicriteria context. In particular, the cocreation process for eliciting attitudes, perceptions, and preferences amongst relevant stakeholder groups has often been missing from policy response to the pandemic, even though the containment measures’ efficiency largely depends on their acceptance by the impacted groups. For this, there exist several methods attempting to elicit criteria weights, values, and probabilities ranging from direct rating and point allocation methods to more elaborated ones. To facilitate the elicitation, some of the approaches utilise elicitation methods whereby prospects are ranked using ordinal importance information, while others use cardinal information. Methods are sometimes assessed in case studies or more formally by utilising systematic simulations. Furthermore, the treatment of corresponding methods for the handling of the alternative’s values has sometimes been neglected. We demonstrate in our paper an approach for cardinal ranking in policy decision making in combination with imprecise or incomplete information concerning probabilities, weights, and consequences or alternative values. The results of our cocreation process are aggregated in the evaluation of alternative mitigation measures for Jordan, showcasing how a multistakeholder multicriteria decision mechanism can be employed in current or future challenges of pandemic situations, to facilitate management and mitigation of similar crises in the future, in any region.

To assess the status of and trends in agricultural nitrogen (N) flows and their wider consequences for Bangladesh, in this study, we analyzed data from national and international bodies. The increased rates of N fertilizer applied for increased food production leaves behind a huge amount of unutilized reactive N (Nr). N fertilizer use is the largest in the crop sector, an important sector, where current annual consumption is 1190 Gg. The present combined annual Nr production from crop, fishery, and livestock sectors is ~600 Gg, while emissions of nitrous oxide (N2O), a potent greenhouse gas, are ~200 Gg. Poor N management results in Nr leaking into the environment, which has increased approximately 16-fold since 1961. One potential consequence is the disruption of ecosystem functioning. The balanced tradeoff between food production and reducing Nr input needs to be achieved. One solution to reducing Nr may be a holistic approach that optimizes N application rates and incorporates waste of one subsector as an input to another applying the principle of the circular economy.

The UN Human Development Report 2020 ranked the United Arab Emirates (UAE) as having achieved ‘very high human development’ and as being at the 31st position among all countries. Despite this, the ever increasing obesity rates among Emirati youth, higher than international standards, is alarming. This research aims at identifying how different perceptions of the built environment by parents and adolescents are likely to affect physical activity (PA) choices among male and female Emirati youth. This can help inform better health and education policies to achieve three of the interconnected UN Sustainable Development Goals (SDGs), namely good quality health and well-being, quality education, and gender equality, that the UAE strives to achieve. Responses from 335 students (aged 14–20) from six schools and 250 parent responses in the Al Ain region of Abu Dhabi Emirate were used to understand the mean variation in perception of five built environment constructs. Further, multinomial logit regression was used to assess the health condition using the perception, behavior, and built environment measures. Results indicate that Emirati males perceive the built environment factors as barriers more than female adolescents. Parents perceive street crossing (p < 0.016) and sidewalk characteristics (p < 0.020) to be more of a hindrance. Traffic exposure, self-reported physical activity, and walkability near homes and schools significantly affect Emirati adolescents’ health conditions. Recommendations are made for various stakeholders including parents, school authorities, Abu Dhabi Municipality and Transportation, and the Urban Planning department on ways to enhance the built environment and encourage PA and well-being of Emirati adolescents.

COVID-19 is spreading out in the world now. Passenger ships such as cruise ships are very critical in this situation. Boats’ hazardous areas need to be identified in advance and managed carefully to prevent the virus. Therefore, this paper proposes for the first time that three technologies are required to support the sustainable management of ships in the post-COVID-19 era. They are ship indoor positioning, close contact identification, and risk area calculation. Ship environment-aware indoor positioning algorithms are proposed for the first time for the moving ship environment, followed by a clustering algorithm for close contact identification. Then, the risk area is calculated using the convex hull algorithm. Finally, a sustainable management approach for ships post COVID-19 is proposed.

Many studies have shown that paint with reflective heat can effectively reduce the temperature of the building envelope and reduce the future energy consumption of the building. This study inspired the next-generation inorganic geopolymer material (IGM) color paint without volatile matter, which could be applied on concrete surfaces to reduce energy consumption in warm seasons. In this study, a total of five insulating IGM paints, white, red, green, blue, and yellow, were applied to a 50 cm × 50 cm × 12 cm concrete slab top surface. The highest average light reflectance of all the paints was 87.5% of white IGM paint, which was higher than plain concrete (36.4%). The heat flux and surface temperature were examined in the laboratory, and those test results were verified outdoor. The results showed that the IGM paints could effectively reduce the surface temperature and heat flux of the upper and lower surfaces of concrete slabs, and the white colored IGM paint was the best performer among all five colors, whereas the heat storage coefficient (Sf) of red, white, yellow, blue, and green IGM painted concrete slabs were 0.57, 0.53, 3.62, 2.95, and 1.91 W·m−2·K−1, respectively, lower than plain concrete (24.40 W·m−2·K−1). This coefficient was presented to externalize the thermal admittance. The overall measurement results showed that the concrete slab with colored IGM paints had better heat insulation ability than the plain concrete slab, especially in white IGM paint.