Sustainable Development Goal 13: Climate Action (32389)

Efforts to decarbonize the world have shown a quick increase in electric vehicles (EVs), limiting increasing pollution. During this electric transportation revolution, lithium-ion batteries (LIBs) play a vital role in storing energy. To determine the range of an electric vehicle (EV), the state of charge and the state of health (SOH) of the battery pack is essential. Access to high-quality data on battery parameters is a crucial challenge for researchers working in the energy storage domain due primarily to confidentiality constraints on manufacturers of batteries and EVs. This paper proposes a hybrid framework for predicting the state of a lithium-ion battery for electric vehicles (EV). Electric vehicles are growing worldwide because of their environmental and sustainability advantages. Batteries are replacing fossil fuels in electric vehicles. In order to prevent failure, Li-ion batteries in electric vehicles should be operated and controlled in a controlled and progressive manner to ensure increased efficiency and safety. An extreme gradient boosting (XGBoost) algorithm is used in this paper to estimate the state of health (SOH) of lithium-ion batteries used in electric vehicles. The model is subjected to error analysis to optimize the battery’s performance parameter. The model undergoes an error analysis to optimize its performance parameters. Furthermore, a state of health (SOH) estimation method based on the extreme gradient boosting algorithm with accuracy correction is proposed here to improve the accuracy of state of health (SOH) estimation for lithium-ion batteries. To describe the aging process of batteries, we extract several features such as average voltages, voltage differences, current differences, and temperature differences. The extreme gradient boosting (XGBoost) model for estimating the state of health (SOH) of lithium-ion batteries is based on the ensemble learning algorithm’s higher prediction accuracy and generalization ability. Experimental results suggest that the boundary gradient lifting algorithm model is capable of more accurate prediction. Full article

The United Nations (UN) has identified the promotion of cleaner energy and improving women’s health as two important elements in achieving the global sustainable development goals. However, the impact of household clean energy consumption on women’s health needs to be further analyzed and improved based on new methods, new data, and new perspectives. This paper used the data from the 2018 China Health and Retirement Longitudinal Study as the sample, and the Ordered Probit model, the instrumental variable (IV) approach, the conditional mixed process (CMP) method, and the mechanism analysis model were applied to empirically investigate the impact of cleaner household energy consumption on women’s health. The findings are the following: (1) It is found that cleaner household energy consumption improved women’s health, and after selecting “respondent’s regions of residence” as an IV to overcome endogenous issues, the estimated results remained significant. (2) The mechanistic estimation showed that air quality, social contact, and well-being play a mediating role in the effects of cleaner household energy consumption on women’s health, while digital ability plays a moderating role in the cleaner household energy consumption impact on women’s health. (3) This study further explored that cleaner household energy consumption significantly reduced the likelihood of women being diagnosed with hypertension, hyperlipidemia, cancer, lung disease, asthma, and depression. The conclusion of this paper that “cleaner household energy can enhance the level of women’s health” supports the viewpoints of some present literature. At the same time, this paper puts forward four policy recommendations based on the research conclusions. Full article

In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs. In experimental studies, simplified results for three SA types and 100 devices for each type were presented. The obtained results confirm that, thanks to the use of SAs and the appropriate algorithm for their control, it is possible to change the load profile of the power grid. The efficacious operation of SAs will be possible thanks to the change of habits of electricity users, which is briefly described in the article. Full article

Aviation is responsible for nearly 2.5% of the world’s anthropogenic carbon emissions. Despite a commitment to reduce these emissions, it is a challenging industry to decarbonise. Very little is known about the attitudes of those working in aviation towards climate change and whether they are motivated to support decarbonisation initiatives. This uncertainty highlights several threats to the industry, with cascading impact on the economy and inequality. To deal with these challenges, this study explores long-term strategies to support compatibility between the evolution of the aviation industry and climate constraints. Using surveys, in-depth interviews, and thematic analysis, this research investigates the views of professionals towards climate change, and the role that they perceive aviation plays. The results of the interviews allow the development of a system map composed of ten self-reinforcing and three balancing loops, highlighting ten leverage points to inform strategies for the industry to respond to threats. This research concludes that the aviation industry should encourage a new generation of sustainability-aware innovators to decarbonise aviation. It also concludes that collaboration both internationally and within the industry is essential, as is the need to encourage an open-minded approach to solution development. It also presents the modelling results in terms of the multilevel perspective technological transition framework and suggests ways forward for modelling using the risk–opportunity analysis. Full article

Natural gas plays a vital role in the economically and environmentally sustainable future of energy. Its reliable deliveries are required, especially nowadays, when the energy market is so volatile and unstable. The conversion of natural gas to its liquefied form (LNG) allows its transport in greater quantities. Affordability and reliability of clean energy is a key issue even for developed markets. Therefore, natural gas usage enables to implement green solutions into countries’ economies. However, the LNG-production process consumes a considerable amount of energy. This energy is stored in LNG as cold energy. After LNG unloading into storage tanks at receiving terminals, it is vaporised and compressed for transmission to a natural gas pipeline system. During the regasification process, the large part of the energy stored in LNG may be recovered and used for electricity generation, seawater desalination, cryogenic air separation, hydrogen liquefaction, material freezing, carbon dioxide capture, as well as for combined LNG cold energy utilization systems. Moreover, increased efficiency of LNG terminals may attract potential clients. In the presented paper, a mathematical model is performed to determine the influence of LNG composition and regasification process parameters on the quantity of released LNG cold energy in a large-scale floating storage and regasification units (FSRU)-type terminal “Independence” (Lithuania). Flow rate of LNG regasification, pressure, and boil-off gas recondensation have been considered. Possibilities to reduce the energy losses were investigated to find the ways to improve the regasification process efficiency for real FSRU. The results analysis revealed that potential of LNG cold energy at FSRU could vary from 20 to 25 MW. A utilisation of industrial and urban waste heat for the heat sink FSRU is recommended to increase the energy efficiency of the whole regasification process. Full article

A general rise in environmental and anthropogenically induced greenhouse gas emissions has resulted from worldwide population growth and a growing appetite for clean energy, industrial outputs, and consumer utilization. Furthermore, well-established, advanced, and emerging countries are seeking fossil fuel and petroleum resources to support their aviation, electric utilities, industrial sectors, and consumer processing essentials. There is an increasing tendency to overcome these challenging concerns and achieve the Paris Agreement’s priorities as emerging technological advances in clean energy technologies progress. Hydrogen is expected to be implemented in various production applications as a fundamental fuel in future energy carrier materials development and manufacturing processes. This paper summarizes recent developments and hydrogen technologies in fuel refining, hydrocarbon processing, materials manufacturing, pharmaceuticals, aircraft construction, electronics, and other hydrogen applications. It also highlights the existing industrialization scenario and describes prospective innovations, including theoretical scientific advancements, green raw materials production, potential exploration, and renewable resource integration. Moreover, this article further discusses some socioeconomic implications of hydrogen as a green resource. Full article

Cooling systems can effectively enable information and communication technology (ICT) equipment to utilize power more efficiently in data centers (DCs). Two-phase cooling provides a potential method to cool CPUs and other electronics and involves submerging them in a thermal conductive dielectric liquid or coolant. In this study, an innovative cooling structure and a two-phase immersion cooling system procedure are presented. The CPU is directly submerged in an engineered fluid, and an experimental test is conducted to obtain the boiling heat transfer and energy consumption data. A prediction equation for saturated boiling HTC in the pool, based on the influence of the characteristics of the heat transfer surface of the CPU and the physical parameters, is proposed. The average partial power usage effectiveness (pPUE) value of the proposed system is 1.036, indicating a significantly improved energy conservation effect compared to conventional air cooling systems. Studies have shown that direct-touch heat dissipation is suitable for supercomputer server CPU heat dissipation with low heat flux density, while for high-density CPU heat dissipation, it is easy to reach the maximum temperature limit of the CPU, thereby reducing the CPU frequency. Full article

In recent years, special attention has been paid to climate change assessment and research into our changing environment. The greatest economic losses worldwide are due to the negative effects of drought stress and extreme temperature on the plants’ morphological, physiological, and biochemical properties which limit crop growth and productivity. Sweet basil (Ocimum basilicum L.) is one of the most popular plants widely grown around the world as a spice, as well a medicinal, aromatic plant. The seedlings with 5–6 true leaves were divided into two groups, and one group of seedlings was sprayed with 10 mM potassium bicarbonate (KHCO₃). Three days after potassium bicarbonate treatment, half of the plants from each group were subjected to a water deficit (drought stress), and the other half were grown under stress-free conditions (well-watered). The present study aimed to evaluate the effect of potassium bicarbonate (KHCO₃) on morphophysiological parameters, phenolics content and the antioxidant activity of basil under drought conditions. The application of potassium bicarbonate to drought stressed plants significantly increased the chlorophyll content, fresh and dry weight, phenolics content in the two of tested cultivars, and antioxidant activity, determined by DPPH and ABTS methods. Principal component analysis showed that the first factor was highly and positively related to all the investigated parameters. Hierarchical clustering analysis showed that the first cluster was formed by being well-watered, well-watered and sprayed with potassium bicarbonate, and grown under drought conditions and sprayed with potassium bicarbonate basil cultivars, while the second cluster was formed by all the tested cultivars grown under drought conditions. Full article

Rice cultivation consumes more than half of the planet’s 70% freshwater supply used in agricultural production. Competing water uses and climate change globally are putting more pressure on the limited water resources. Therefore, water-saving irrigation (WSI) is recommended for rice production in water scares areas. The impact of WSI techniques on direct-seeding rice production and greenhouse gas emissions in North China is becoming increasingly important in the era of climate change. Therefore, we conducted a two-year field experiment on directly seeded rice to assess the impact of traditional flooding irrigation (CK) and three water saving irrigation (WSI) methods, including drip irrigation with an irrigation amount of 50 mm (DI₁) and 35 mm (DI₂) at each watering time and furrow wetting irrigation (FWI), on rice yield and greenhouse emissions. Generally, the WSI techniques decreased the number of rice panicles per m⁻², spikelet per panicle, 1000-grain weight and rice yield compared to CK. Rice yield and yield components of (DI₁) were significantly higher than (DI₂). The adoption of either (DI₁) or (FWI) showed insignificant variation in terms of rice yield and its yield components measured except for 1000-grain weight. The water productivity was 88.9, 16.4 and 11.4% higher in the FWI plot than the CK, DI₁ and DI₂ plots, respectively. The WSI decreased cumulative CH₄ emission significantly by 73.0, 84.7 and 64.4% in DI₁, DI₂ and FWI, respectively, in comparison with CK. The usage of DI₂ triggered 1.4 and 2.0-fold more cumulative N₂O emission compared to DI₁ and FWI, respectively. Area-scaled emission among the water-saving irrigation methods showed no significance. The yield-scaled emission in DI₁ and DI₂ and FWI were 101, 67.5 and 102%, respectively, significantly lower than CK. The adoption of FWI produced an acceptable rice yield with the lowest yield-scaled emission and highest water productivity among the irrigation practices. Our experiment demonstrates that dry direct-seeding with furrow irrigation can impact triple-wins of sustainable rice yield, high water-use efficiency and low GHG emissions in North China. Full article

Air/soil temperatures play important roles in land–atmosphere interactions. The three-dimensional (temporal, spatial, and vertical) variations of maximum, mean, and minimum ground soil temperature at 0 cm (GSTx, GSTm, and GSTn, respectively), surface air temperature at 2 m (SATx, SATm, and SATn, respectively), and soil–air temperature difference (SATDx, SATDm, and SATDn, respectively) and their potential linkages with large-scale indexes in Southwest China during 1980–2019 were analyzed. Variations of GST and SAT at the majority of stations (pixels) exhibited significant (p ≤ 0.05) warming, albeit at different rates; consequently, SATD exhibited different variation. Moreover, the period of GST, SAT, and SATD was similar in intra-annual and interannual oscillation but was different in interdecadal oscillation. The variation rate of GST, SAT, and SATD exhibited significant (p ≤ 0.05) correlation with elevation, but with different variation gradient. Notably, asymmetric variation of SATDx (downward trend) and of SATDn (upward trend) with elevation was found at elevations >3 km. Wavelet coherence showed that the Atlantic Multidecadal Oscillation is the dominant factor affecting GST and SAT, whereas the Pacific Decadal Oscillation and the North Atlantic Oscillation make the greatest contributions to SATD. It was found that GST, SAT, and SATD exhibit different variations under the effects of global warming, the driving mechanism of which requires further study. Full article

The emergence of new information technologies, market globalization, climate change, labor shortages, and changing consumer habits have led to dynamic demand and the need for customized mass production systems. This has forced companies, especially small- and medium-sized enterprises (SME), to rethink their product design, production, and marketing models to remain competitive by increasing their agility in the face of growing and changing demand. It becomes relevant to investigate how to move efficiently towards customized mass production in an Industry 4.0 (I4.0) environment. The objective of this research is to develop a strategy for implementing I4.0 in manufacturing SME, based on lean, agility, and intelligent modular product design. A literature review made it possible to target the following performance measures: reducing inventory, minimizing makespan, and reducing time to consumer (reaction time). A case study was conducted in an SME in the agri-food sector to validate the proposed strategy. Inventory levels were reduced by more than 70% and time was cut by almost 65%. Full article

The Internet of Things (IoT) brings internet connectivity to everyday devices. These devices generate a large volume of information that needs to be transmitted to the nodes running the IoT applications, where they are processed and used to make some output decisions. On the one hand, the quality of these decisions is typically affected by the freshness of the received information, thus requesting frequent updates from the IoT devices. On the other hand, the severe energy, memory, processing, and communication constraints of IoT devices and networks pose limitations in the frequency of sensing and reporting. So, it is crucial to minimize the energy consumed by the device for sensing the environment and for transmitting the update messages, while taking into account the requirements for information freshness. Edge-caching can be effective in reducing the sensing and the transmission frequency; however, it requires a proper refreshing scheme to avoid staleness of information, as IoT applications need timeliness of status updates. Recently, the Age of Information (AoI) metric has been introduced: it is the time elapsed since the generation of the last received update, hence it can describe the timeliness of the IoT application’s knowledge of the process sampled by the IoT device. In this work, we propose a model-driven and AoI-aware optimization scheme for information caching at the network edge. To configure the cache parameters, we formulate an optimization problem that minimizes the energy consumption, considering both the sampling frequency and the average frequency of the requests sent to the device for refreshing the cache, while satisfying an AoI requirement expressed by the IoT application. We apply our caching scheme in an emulated IoT network, and we show that it minimizes the energy cost while satisfying the AoI requirement. We also compare the case in which the proposed caching scheme is implemented at the network edge against the case in which there is not a cache at the network edge. We show that the optimized cache can significantly lower the energy cost of devices that have a high transmission cost because it can reduce the number of transmissions. Moreover, the cache makes the system less sensitive to higher application-request rates, as the number of messages forwarded to the devices depends on the cache parameters. Full article

Urban-scale Numerical Weather Prediction (NWP) systems will be important tools for decision-making in and around large cities in a changing climate exposed to more extreme weather events. Such a state-of-the-art real-time system down to 250-m grid spacing was implemented in the context of the Toronto 2015 Panamerican games, Canada (PanAm). Combined with the Global Environmental Multiscale (GEM) model, attention was brought to the representation of the detailed urban landscape, and to the inclusion of sub-daily variation of the Great Lakes surface temperature. Results show a refined representation of the urban coastal environment micro-meteorology with a strong anisotropy of the urban heat island reaching about 2 °C on average for the summer season, coastal upwelling, and mesoscale features such as cumulus clouds and lake-breeze flow. Objective evaluation at the surface with a dense observational network reveals an overall good performance of the system and a clear improvement in comparison to reference forecasts at 2.5-km grid spacing in particular for standard deviation errors in urban areas up to 0.3 °C for temperature and dew point temperature, and up to 0.5 m s${}^{-1}$ for the wind speed, as well as for precipitation with an increased Equitable Threat Score (ETS) by up to 0.3 for the evening accumulation. The study provides confidence in the capacity of the new system to improve weather forecasts to be delivered to urban dwellers although further investigation of the initialization methods in urban areas is needed. Full article

Although some exotic tree species, new to the country at the time, had already been introduced at the turn of the 18th and 19th century in the Hungarian landscape gardens, using foreign tree species in the space composition became widely popular only from the second half of the 19th century. This research focused on determining the date of appearance and compositional role of exotic trees in Hungarian landscape gardens. We can still find aged exotic woody taxa which determine the historical spatial structure in numerous landscape gardens nowadays. The nationwide distribution of these species, and their location within the gardens, can be an important addition to the questions of the revitalization of historical gardens, the more so because they may be indicative of the climate adaptability and, therefore, resilience of built heritage environments. An experimental approach to the introduction and use of new exotic tree species in historic gardens where this approach can be proven to have existed is also discussed as an opportunity to use these gardens in search of new foreign taxa to adapt to climate change. Full article

Even though peonies are highly valued as ornamental, medicinal, and edible species and are also considered to be long-lived and relatively disease and pest resistant, they are becoming rare or endangered in their natural habitats. This could be primarily associated with climate change and unsustainable wild collecting practices. So far, in situ conservation efforts have received little attention. In addition, very little is known about the cultivation of herbaceous peonies, particularly their propagation from seeds. What is known is that their seeds possess double dormancy, often accompanied by a low germination rate, which, together, make the cultivation of herbaceous peonies more difficult. Based on a comprehensive analysis of relevant literature, this paper summarizes, analyzes, and discusses all available studies on the seed traits of herbaceous peonies associated with the effect of seed harvest time on dormancy and seed germination, with a strong focus on dormancy breaking procedures. Improving our understanding of dormancy release modalities (impacts of temperature, moisture, light, hormones, various pre-treatments, etc.) will aid the establishment and management of in situ and ex situ collections of valuable species of herbaceous peonies and enable further studies for their successful propagation, breeding, and cultivation. Full article

Hydrogen fuel cells are systems that can be successfully used to partially replace internal combustion propulsion systems. For this reason, the article presents an operational analysis of energy flow along with an analysis of individual energy transmission systems. Two generations of the Toyota Mirai vehicle were used for the tests. The operational analyses were carried out on the same route (compliant with RDE test requirements), assessing the system’s operation in three driving sections (urban, rural and motorway). Both generations of the drive system with fuel cells are quite different, which affects the obtained individual systems operation results as well as the overall energy flow. Research was carried out on the energy flow in the fuel cells, FC converter, battery and electric motor using a dedicated data acquisition system. The analyses were carried out in relation to the energy of fuel cells, battery energy and recovered braking energy. It was found that in the urban drive section of the second-generation system (due to its much larger mass), a slightly higher energy consumption value was obtained (by about 2%). However, in the remaining phases of the test, consumption was lower (the maximum difference was 18% in the rural phase). Total energy consumption in the research test was 19.64 kWh/100 km for the first-generation system compared to 18.53 kWh/100 km for the second-generation system. Taking into account the increased mass of the second-generation vehicle resulted in significantly greater benefits in the second-generation drive (up to 37% in individual drive sections and about 28% in the entire drive test). Full article

Algeria is a wealthy country with natural resources, namely, nuclear, renewable, and non-renewable sources. The non-renewable energy sources are considered the lion’s share for energy production (98%). Algeria’s efforts to ensure and strengthen its energy security will take an important step in the coming decades by commissioning new energy infrastructure based on intensive use of water, coal, nuclear, non-renewable, and renewable sources. The implementation of new power infrastructure is expected to be operational from 2030. The renewable power realization in Algeria is relatively less compared to other African countries, i.e., Morocco, Egypt, South Africa, etc. The total renewable power installed capacity in Algeria reached 686 MW in 2020, as part of its national energy portfolio, although the Algerian government has spent tremendous efforts on introducing new sustainable technologies to enable the transition towards a cleaner and sustainable energy system. Indeed, the country announced its plan to install around 22 GW of renewable energy capacity by 2030. It will include 1 GW bio-power from the waste, 13.5 GW from solar PV, 2 GW from CSP, 15 MW from geothermal, 400 MW cogeneration, and, finally, 5 GW from wind. The scope of the present research provides general information about the usage of energy resources such as fossil, nuclear, and renewable sources in Algeria and also covers the energy supply outlook. The present effort is the first of its kind which discusses the application of the coal and nuclear as clean energy sources as part of renewable energy transition. Additionally, it also includes the description of the existing Algerian energy sector and information about water and water desalination and their usage in other sectors. Full article

Wastewater treatment plants (WWTPs) are important contributors to global greenhouse gas (GHG) emissions, partly due to their huge emission of nitrous oxide (N₂O), which has a global warming potential of 298 CO₂ equivalents. Anaerobic ammonium-oxidizing (anammox) bacteria provide a shortcut in the nitrogen removal pathway by directly transforming ammonium and nitrite to nitrogen gas (N₂). Due to its energy efficiency, the anammox-driven treatment has been applied worldwide for the removal of inorganic nitrogen from ammonium-rich wastewater. Although direct evidence of the metabolic production of N₂O by anammox bacteria is lacking, the microorganisms coexisting in anammox-driven WWTPs could produce a considerable amount of N₂O and hence affect the sustainability of wastewater treatment. Thus, N₂O emission is still one of the downsides of anammox-driven wastewater treatment, and efforts are required to understand the mechanisms of N₂O emission from anammox-driven WWTPs using different nitrogen removal strategies and develop effective mitigation strategies. Here, three main N₂O production processes, namely, hydroxylamine oxidation, nitrifier denitrification, and heterotrophic denitrification, and the unique N₂O consumption process termed nosZ-dominated N₂O degradation, occurring in anammox-driven wastewater treatment systems, are summarized and discussed. The key factors influencing N₂O emission and mitigation strategies are discussed in detail, and areas in which further research is urgently required are identified. Full article

Nature-based solutions (NbS) present an opportunity to reduce rising temperatures and the urban heat island effect. A multi-scale study in Toronto, Ontario, Canada, evaluates the effect of NbS on air and land surface temperature through two field campaigns at the micro and meso scales, using in situ measurements and LANDSAT imagery. This research demonstrates that the application of NbS in the form of green infrastructure has a beneficial impact on urban climate regimes with measurable reductions in air and land surface temperatures. Broad implementation of green infrastructure is a sustainable solution to improve the urban climate, enhance heat and greenspace equity, and increase resilience. Full article

With the rise of a new generation of low Earth orbit (LEO) satellite constellations and the advancement of the 6G network, satellite–terrestrial integrated Internet of Things (IoT) in the future will achieve global coverage through the integration of LEO constellation, and extend computing to the edge of the network through the deployment of edge computing services in LEO constellation so as to meet the demand of mass connection and low latency data processing. The LEO constellation network of the future will be an edge cloud network combining network and computing. In this paper, we propose a computation offloading strategy for the combined optimization of energy and computational load in a LEO constellation edge cloud network (hereinafter referred to as LEO-ECN). First, we establish the LEO-ECN system model, in which the user task can be offloaded to the satellite through the multi-hop path. Then, a cost model considering energy consumption and load calculation is proposed. Finally, a joint optimization problem to minimize energy consumption and balance the LEO-ECN load is established, which is a convex optimization problem. The simulation result demonstrates that, compared with the benchmark strategy, our proposed strategy has better performance and can improve the computing resource utilization of LEO-ECN. Full article

In numerous locations of bulk water supply/distribution systems, energy is dissipated by pressure-reducing devices, whereas it could be recovered by means of turbines or pumps as turbines. These pipe systems, owned and operated by municipalities, water utilities, large water-consuming industries, and mines, could be used as a source of renewable sustainable energy. However, the exploitation of these systems presents several issues related to the complexity of the operational optimization of the hydropower generation facilities and to the potential negative impact on the reliability of the system itself. We have developed a novel procedure to optimize the energy generation in such a conduit system by assessing the interrelationship of storage volumes, demand patterns, operating cycles, and electricity tariff structures. The procedure is a multi-objective genetic algorithm designed to provide a solution to maximize electricity generation and thus revenue and to minimize the risk involved in supplying the demand. A Pareto-optimal trade-off curve is set up, indicating the potential benefit (revenue) versus the reliability index (supply security). The results indicate that a Pareto-optimal trade-off curve was generated from which a solution could be selected which would improve the weekly revenue by up to 7.5%, while still providing a reliable water supply system. Full article

The popularity of electric vehicles (EVs) is increasing day by day due to their environmentally friendly operation and high milage as compared to conventional fossil fuel vehicles. Almost all leading manufacturers are working on the development of EVs. The main problem associated with EVs is that charging many of these vehicles from the grid supply system imposes an extra burden on them, especially during peak hours, which results in high per-unit costs. As a solution, EV charging stations integrated with hybrid renewable energy resources (HREs) are being preferred, which utilize multi-energy systems to produce electricity. These charging stations can either be grid-tied or isolated. Isolated EV charging stations are operated without any interconnection to the main grid. These stations are also termed standalone or remote EV charging stations, and due to the absence of a grid supply, storage becomes compulsory for these systems. To attain maximum benefits from a storage system, it must be configured properly with the EV charging station. In this paper, different types of the latest energy storage systems (ESS) are discussed with a comprehensive review of configurations of these systems for multi-energy standalone EV charging stations. ESS in these charging stations is applied mainly in three different configurations, named single storage systems, multi-storage systems, and swappable storage systems. These configurations are discussed in detail with their pros and cons. Some important expectations from future energy storage systems are also highlighted. Full article

Oleaginous yeasts have attracted increasing scientific interest as single cell oil (SCO) producers. SCO can be used as a fossil-free fuel substitute, but also as a source of rarely found odd-chain fatty acids (OCFAs), such as C15, C17, and C25 fatty acids which have a wide range of nutritional and biological applications. Volatile fatty acids (VFAs) have gained interest as sustainable carbon source for yeasts. This study aims to improve current knowledge on yeast species that yield high amounts of SCO using VFAs as a carbon source. Specifically, the growth of the promising yeasts Cryptococcus curvatus and Rhodotorula toruloides was evaluated on individual VFAs, such as acetic, propionic, and butyric acid. C. curvatus proved to be more tolerant in higher concentrations of VFAs (up to 60 g/L), while butyric acid favored biomass and lipid conversion (0.65 and 0.23 g/g_substrate, respectively). For R. toruloides, butyric acid favored biomass conversion (0.48 g/g_substrate), but lipid conversion was favored using acetic acid, instead (0.14 g/g_substrate). Propionic acid induced the formation of OCFAs, which yielded higher amounts for C. curvatus (up to 2.17 g/L). VFAs derived from the anaerobic digestion of brewer’s spent grain were tested as a cost-competitive carbon source and illustrated the significance of the combination of different VFAs in the quality of the produced SCO, by improving the biodiesel properties and OCFAs production. Full article

Salinity is becoming a serious threat to global food security, as it can significantly reduce crop yields and irreversibly damage soil fertility. Moreover, this problem is currently exacerbated by the impact of climate change, especially in drylands. Hence, introducing and adapting salinity-tolerant species, such as quinoa (Chenopodium quinoa, Willd.), could be among the ways to enhance the value of saline land, increasing its productivity and improving small farmers’ income in rural areas. Quinoa, originally cultivated in the Andean region, has gained more attention throughout the Mediterranean region because it yields well even in marginal soils. It is also considered one of the world’s healthiest foods, as its grains contain a balanced composition of minerals, vitamins, dietary fiber, fats, and high-quality, gluten-free proteins, with a balanced profile of all amino acids. In Morocco, quinoa was introduced in 2000, but its expansion is still limited to certain regions. In Eastern Morocco, for the first time, an experiment was carried out in 2019–2020 aiming to assess the response of five quinoa cultivars (INIA-420 Negra, Titicaca, Puno, ICBA-Q4 and ICBA-Q5) to saline irrigation. For this, we used two levels of water irrigation salinity: 1.50 dS.m⁻¹ as a no-salt control from Tagma’s source in Tafoghalt village and 10.5 dS.m⁻¹ as salt treatment from local water drilling. Agronomic parameters, mainly dry matter, leaf area, grain yield and 1000-kernel weight, were measured to assess quinoa cultivars’ responses to saline irrigation. Statistical analysis revealed that all investigated parameters were significantly affected by salinity, quinoa variety and their interaction (p < 0.05). Furthermore, significant differences in terms of salinity tolerance among the five quinoa cultivars were observed, with the highest (2.17 t.ha⁻¹) and lowest (0.33 t.ha⁻¹) yields recorded for ICBA-Q5 and INIA-420 Negra, respectively. However, the same varieties tested previously in Southern Morocco tolerated a higher level of salinity (12 dS.m⁻¹). We assume that other factors interfered with salinity and variety, such as the sowing date, which was relatively late and exposed the flowering and grain filling stages to high heat in May and June. Full article

Precision agriculture is a concept that encompasses various technologies aimed at optimizing the management of agricultural activities. The main aim of this investigation is to evaluate the environmental and economic performance of precision agriculture practices on the production of a stone fruit crop (nectarine) using a life cycle approach and to consider a cradle-to-farm gate scope. The results have been compared against the traditional uniform application (UA). The analysis considers five impact categories, including climate change, photochemical ozone formation, acidification, eutrophication, and water use. The foreground inventory data was provided by a local producer in Southern Spain, and the background information was sourced from commercial Life Cycle Inventory (LCI) databases. The results show that the manufacturing of crop inputs (mainly fertilizers, but also crop management inputs) is responsible for most of the damage generated in all the impact categories, except for water use. The reduced input requirements associated with the application of VA techniques resulted in significantly lower economic costs and environmental savings throughout the life cycle of the production system, which ranged on average between 12–26%. Full article

Fresh waters are among the most imperiled ecosystems in the world. Not surprisingly, freshwater and diadromous fishes, which show remarkably high levels of endemism, are declining dramatically worldwide. In Portugal, more than 60% of the native fishes are already threatened and risk further population declines due to the intensification of multiple threats such as habitat loss and degradation, non-native species, and climate change. However, there is a lack of a comprehensive information about this vertebrate group in Portugal, and also in Spain. A Guide to Freshwater and Migratory Fishes in Portugal is the first book with dedicated information about the 62 fishes listed for freshwater ecosystems in the region, including data on their morphological characteristics, distribution, ecology, conservation, and economic value, and original scientific drawings by Claudia Baeta and Pedro Salgado. The guide is directed to the general public, scholars and fishermen, constitutes a groundbreaking mark for the Portuguese and Iberian ichthyology, and hopes to attract more research and public engagement to the conservation of the freshwater ecosystems. Full article

Electric Technology Vehicles (ETVs: hybrid, electric, and plug-in hybrid) may reach price parity with incumbent internal combustion vehicles (ICEVs) in the near future. Climate policy for transportation will depend on the degree to which consumers prefer ETVs, and price parity is a key factor. In this study, we explore the interaction between future cost reductions and the economically motivated adoption of ETVs. We construct a model of the U.S. personal vehicle market accounting for heterogenous use and vehicle preferences, in which adoption induces cost reductions that increase future market share. Model results indicate that price parity is reached for most consumers in a number of cost scenarios, but not with constant ICEV costs and modest ETV cost declines. A price parity future suggests that government support could be temporary and phased out after a successful market transition. However, if ETVs continue to be more expensive than ICEVs, then lasting government support is needed. Heterogeneity is essential to understanding the market transition: treating consumers as heterogeneous results in an ETV market share 23% higher than assuming average consumers. Future work can clarify ETV support policy by resolving uncertainty in cost trajectories and modeling dynamic and heterogenous consumer markets. Full article

One of the main problems faced by the Belém Metropolitan Region (BMR) inhabitants is flash floods caused by precarious infrastructure and extreme rainfall events. The objective of this article is to investigate whether and how the local urban characteristics may influence the development of thunderstorms. The Weather Research and Forecasting (WRF) model was used with three distinct configurations of land use/cover to represent urbanization scenarios in 2017 and 1986 and the forest-only scenario. The WRF model simulated reasonably well the event. The results showed that the urban characteristics of the BMR may have an impact on storm systems in the urban areas close to the Northern Coast of South America. In particular, for the urban characteristics in the BMR in 2017, the intensification of the storm may be linked to a higher value of energy available for convection (over 1000 J kg⁻¹) and favorable wind convergence and vertical shear in the urban area (where the wind speed at the surface was more than 3 m s⁻¹ slower than in the forest-only scenario). Meanwhile, the other land cover scenarios could not produce a similar storm due to lack of moisture, wind convergence/shear, or convective energy. Full article

The Qinghai–Tibet Plateau (QTP) is a sensor of global climate change and regional human activities, and drought monitoring will help to achieve its ecological protection and sustainable development. In order to effectively control the geospatial scale effect, we divided the study area into eight geomorphological sub-regions, and calculated the Temperature-Vegetation Drought Index (TVDI) of each geomorphological sub-region based on MODIS Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) data, and synthesized the TVDI of the whole region. We employed partial and multiple correlation analyses to identify the relationship between TVDI and temperature and precipitation. The random forest model was further used to study the driving mechanism of TVDI in each geomorphological division. The results of the study were as follows: (1) From 2000 to 2019, the QTP showed a drought trend, with the most significant drought trend in the central region. The spatial pattern of TVDI changes of QTP was consistent with the gradient changes of precipitation and temperature, both showing a gradual trend from southeast to northwest. (2) There was a risk of drought in the four seasons of the QTP, and the seasonal variation of TVDI was significant, which was characterized by being relatively dry in spring and summer and relatively humid in autumn and winter. (3) Drought in the QTP was mainly driven by natural factors, supplemented by human factors. The driving effect of temperature and precipitation factors on TVDI was stable and significant, which mainly determined the spatial distribution and variation of TVDI of the QTP. Geomorphological factors led to regional intensification and local differentiation effects of drought, especially in high mountains, flat slopes, sunny slopes and other places, which had a more significant impact on TVDI. Human activities had local point-like and linear impacts, and grass-land and cultivated land that were closely related to the relatively high impacts on TVDI of human grazing and farming activities. In view of the spatial-temporal patterns of change in TVDI in the study area, it is important to strengthen the monitoring and early warning of changes in natural factors, optimize the spatial distribution of human activities, and scientifically promote ecological protection and restoration. Full article

In economies, cleaner technology, increased demand for renewable energy, and more efficient use of natural resources contribute to meeting environmental sustainability targets. The Chinese economy is no exception in its attempts to conserve economic and natural resources via collaborative efforts to embrace cleaner technology, green energy sources, and resource conservation management to preserve resources for future generations. This research examines the influence of cleaner technologies, green energy sources, and natural resource management on reducing greenhouse gas emissions using quarterly data for the Chinese economy from 2000Q1 to 2020Q4. The findings demonstrate that increasing demand for green energy reduces greenhouse gas emissions, hence substantiating the premise of ‘green is clean’ energy development. Additionally, optimum resource usage enhances environmental quality, corroborating the ‘resource cleaner blessing’ hypothesis. The positive link between inward foreign direct investment and greenhouse gas emissions substantiates the ‘pollution haven’ concept, according to which inward foreign direct investment uses unsustainable technology in manufacturing processes, hence degrading air quality indicators. Inadequate access to clean cooking technology and increased population density has a detrimental effect on the country’s environmental sustainability agenda, which must be corrected via sustainable regulations. The causality estimates show the feedback relationship between renewable energy demand (and economic growth) and cleaner technology, between economic growth and green energy (and inbound foreign direct investment), and between population density and economic growth (and green energy). The Impulse Response function estimates suggested that economic growth and population density would likely increase GHG emissions. In contrast, cleaner technology, green energy demand, natural resource management, and inbound foreign direct investment would likely decrease greenhouse gas emissions for the next ten-year time period. The sustainability of the environment and natural resources in China is bolstered by developing cleaner technologies, a greater reliance on renewable energy sources, and better management of natural resources. Full article

Escalating geopolitical factors are closely related to climate warming, but researchers have not fully considered this. Therefore, the purpose of this study is to explore the interaction between geopolitical risk (GPR) and carbon dioxide (CO₂) in China. This paper uses the recently developed GPR index and a bootstrap Granger rolling-window estimation. Empirical results spanning different subsamples reveal a two-way causal relationship between GPR and CO₂. GPR transforms energy consumption and economic activities through trade disputes, military deployments and energy issues, which have a complex impact on CO₂ emissions. Oppositely, CO₂ emissions affect GPR through changes in international cooperation and shaping of geopolitical systems. In view of these empirical results, we put forward several policy recommendations. The Chinese government can effectively consider GPR to control CO₂ emissions by increasing green investment and signing environmental contracts. Enterprises must focus on research and development (R&D) and investment in new energy innovations. In addition, international organizations can be a useful tool for monitoring decarbonization policies and resolving conflicts between countries. Full article

Light and nutrients are among the most important factors for sustained plant production in agriculture. As one of the goals of the European Green Deal strategy is to reduce energy consumption, greenhouse growers focus on high-value crop cultivation with less-energy-demanding growing systems. This study aimed to evaluate the effect of fertilization at different light intensities on the growth of lettuce and basil and the activity of the antioxidant system. Sweet basil (Ocimum basilicum, ‘Opal’) and lettuce (Lactuca sativa, ‘Nikolaj’) were grown in a greenhouse supplementing natural light (~80 µmol m⁻² s⁻¹) with lighting at two photon flux densities (150 and 250 µmol m⁻² s⁻¹), 16 h photoperiod, and 20/16 °C day/night temperature in May (Lithuania, 55°60′ N, 23°48′ E). In each light regime treatment, half of the plants were grown without additional fertilization; the other half were fertilized twice a week with a complex fertilizer (NPK 3-1-3). The results showed that the antioxidant activity of basil was most affected by 150 µmol m⁻² s⁻¹ PPFD lighting and the absence of fertilization. Altered antioxidant activity in lettuce in the presence of 250 µmol m⁻² s⁻¹ PPFD additional light intensity and fertilization resulted in higher morphological parameters. Full article

Steel double-beam floor systems reinforced with concrete panels can improve the structural and environmental performance of buildings by reducing moment demands and embodied CO₂ emissions. However, for steel double-beam floor systems, a time-consuming iterative analysis is required to derive an optimal design proposal owing to the rotational constraints in the composite joints between the concrete panel and steel beams. In this study, a non-iterative optimal design method using the LM index is proposed to minimize the embodied CO₂ emissions of steel double-beam floor systems. The LM index is a measure that can be used to select the optimal cross-section of the steel beams considering the decreased moment capacity according to the unbraced length. The structural feasibility of the proposed design method was verified by investigating whether safety-related constraints were satisfied by the LM index with respect to the design variables under various gravity loads. The applicability of the proposed optimal design method is verified by comparing the embodied CO₂ emissions derived from the proposed and code-based design methods. Applicable design conditions were presented based on the LM index to aid engineers. The proposed design method can provide environmentally-optimized design proposals to ensure structural safety by directly selecting the LM index of steel beams. Full article

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. Full article

Concrete technology is adopted worldwide in construction due to its effectiveness, performance, and price benefits. Subsequently, it needs to be an eco-friendly, sustainable, and energy-efficient material. This is achieved by replacing or adding energy-efficient concrete materials from industries, such as ground granulated blast furnace slag, steel slag, fly ash, bottom ash, rice husk ash, etc. Likewise, copper slag is a waste material produced as molten slag from the copper industry, which can be used in concrete production. Copper slag can perform roles similar to pozzolans in the hydration process. This paper extends the comparative study of copper slag concrete with polypropylene fiber (PPF) subjected to destructive and non-destructive testing. Under destructive testing, compressive strength of concrete cubes, compressive strength of mortar cubes, splitting tensile tests on cylindrical specimens, and flexural tests on plain cement concrete were conducted and analysed. Ultrasonic pulse velocity and rebound hammer tests were performed on the samples as per IS13311-Part 1-1992 for non-destructive testing. The 100% replacement of copper slag exhibited a very high workability of 105 mm, while the addition of 0.8% PPF decreased the flowability of the concrete. Hence, the workability of concrete decreases as the fiber content increases. The density of the concrete was found to be increased in the range of 5% to 10%. Furthermore, it was found that, for all volume fractions of fiber, there was no reduction in compressive strength of up to 80% of copper slag concrete compared to control concrete. The 40% copper slag concrete was the best mix proportion for increasing compressive strength. However, for cement mortar applications, 80% copper slag is recommended. The findings of non-destructive testing show that, except for 100% copper slag, all mixes were of good quality compared to other mixes. Linear relationships were developed to predict compressive strength from UPV and rebound hammer test values. This relationship shows better prediction among dependent and independent values. It is concluded that copper slag has a pozzolanic composition, and is compatible with PPF, resulting in good mechanical characteristics. Full article

Multi-date remotely sensed SPOT images of 1991, 2000, 2009 and 2017 were used to reconstruct changes in land cover in the Gamtoos River Estuary, Eastern Cape province, South Africa. These images were complemented by near-anniversary aerial photographs and Google Earth images that were used as ancillary sources of ground truth. The long-term trend direction of change was determined by calculating percentage changes and performing linear trend analysis. The magnitude of change was established by calculating Sen Slope estimates (SSE) and the influence of climate change on changes in land cover tested by correlating changes in rainfall and different cover types. The greatest and lowest changes were for noncultivated land and surface water (−7.94%, y = −1.2032x + 21.275, SSE = −0.292, and 0.44%, y = −0.4261x + 9.657, SSE = 0.007, respectively). Correlations between rainfall and all cover types were weak and ranged between 0.453816 and −0.643962. Rainfall exhibited a significant decrease (p = 0.0411, σ 0.05; y = −7.175x + 734.55, SSE = −11.130) that was highly correlated with changes in surface water distribution (0.813709, Critical R = 0.805). Overall, the results of this investigation point to the combined influence of climate change and human agency, with the latter tending to play a more prominent role by exerting increasing pressure on the environment’s natural supporting potentials. We therefore urge the scientific community to continue exploring actionable interventions that can be used to enhance the sustainability of this ecosystem and others elsewhere. Full article

Global agreements mandate the international community, including Indonesia, to commit to reducing the risks and impacts of climate change. Indonesia’s Nationally Determined Contributions (NDCs) will contribute to the achievement of the Convention’s goals by reducing greenhouse gas (GHG) emissions and increasing climate resilience. This commitment must be supported by a wide range of actions, including the use of timber. Despite the fact that wood contains carbon, limited information is currently available on the size of the wood utilisation subsector’s contribution to reducing GHG emissions. More research is needed on the magnitude of wood products’ contribution to climate change mitigation. This study assessed the amount of carbon stored in wood used as a building material. Purposive sampling was used to select the cities with rapid housing development surrounding Jakarta’s capital city, i.e., the Bekasi District, East Jakarta City, Depok City, and Bogor District. The amount of carbon stored in wood was calculated according to EN 16449:2014-06 and energy dispersive X-ray spectroscopy (EDS/EDX) analysis. Results show that wood is currently only used in door frames, door leaves, window frames, shutters, and vents. The carbon stored on the components ranges from 450 to 680 kg (average of 554.50 kg) in each housing unit, according to the EN 16449:2014-06 calculation. The weight range is between 130 and 430 kg (average of 400.42 kg) according to EDX/S carbon analysis. With an increase in housing needs of 800,000 units per year, this amount has the potential to store 0.44 million tons of carbon over the lifespan of the products. Full article

Climate change is currently one of agriculture’s main problems in achieving sustainability. It causes drought, increased rainfall, and increased diseases, causing a decrease in food production. In order to combat these problems, Agricultural Big Data contributes with tools that improve the understanding of complex, multivariate, and unpredictable agricultural ecosystems through the collection, storage, processing, and analysis of vast amounts of data from diverse heterogeneous sources. This research aims to discuss the advancement of technologies used in Agricultural Big Data architectures in the context of climate change. The study aims to highlight the tools used to process, analyze, and visualize the data, to discuss the use of the architectures in crop, water, climate, and soil management, and especially to analyze the context, whether it is in Resilience Mitigation or Adaptation. The PRISMA protocol guided the study, finding 33 relevant papers. However, despite advances in this line of research, few papers were found that mention architecture components, in addition to a lack of standards and the use of reference architectures that allow the proper development of Agricultural Big Data in the context of climate change. Full article

In the field of automated technology research and development, trajectory tracking plays a crucial role in the energy consumption of the vehicle’s power battery. Reducing the deviation between the actual trajectory and the reference trajectory is the focus of trajectory tracking research. This paper proposes the use of the model predictive control (MPC) method to reduce the deviation of lateral and longitudinal position between the actual driving trajectory and the reference trajectory. First, the driving conditions of the vehicle are reflected by establishing the vehicle dynamics model. Then, the MPC trajectory tracking controller is built by designing the objective function with constraints; Finally, the feasibility of this approach was verified by a joint Carsim-Simulink simulation. The simulation results show that the MPC controller designed in this paper can track the trajectory better, and reduce the lateral and longitudinal position deviation. To a certain extent, the battery energy consumption is reduced and the accuracy of the tracking trajectory and the safety of vehicle driving are improved. Full article

Mangrove ecosystems sequester and store large amounts of carbon in both biomass and soil. In this study, species diversity, the above and below-ground biomass as well as carbon stock by the mangroves in Kanhlyashay natural mangrove forest were estimated. Six true mangrove species from four families were recorded in the sample plots of the study area. Among them, Avicennia officinalis L. from the Acanthaceae family was the abundance of species with an importance value of 218.69%. Shannon–Wiener’s diversity index value (H′ = 0.71) of the mangrove community was very low compared to other natural mangrove forests since the mangrove stands in the study site possessed a low number of mangrove species and were dominated by a few species. Estimated mean biomass was 335.55 ± 181.41 Mg ha⁻¹ (AGB = 241.37 ± 132.73 Mg ha⁻¹, BGB = 94.17 ± 48.73 Mg ha⁻¹). The mean overall C-stock of the mangrove stand was 150.25 ± 81.35 Mg C ha⁻¹ and is equivalent to 551.10 ± 298.64 Mg CO₂ eq. The role of forests in climate change is two-fold as a cause and a solution for greenhouse gas emissions. The result of the study demonstrated that the mangroves in Letkhutkon village have high carbon storage potential, therefore it is necessary to be sustainably managed to maintain and increase carbon storage. Climate change mitigation may be achieved not only by reducing the carbon emission levels but also by maintaining the mangrove ecosystem services as carbon sinks and sequestration. Full article

Oxygen and hydrogen generated by water electrolysis may be utilized as a clean chemical fuel with high gravimetric energy density and energy conversion efficiency. The hydrogen fuel will be the alternative to traditional fossil fuels in the future, which are near to exhaustion and cause pollution. In the present study, flowery-shaped In₂MnSe₄ nanoelectrocatalyst is fabricated by anion exchange reaction directly grown on nickel foam (NF) in 1.0 M KOH medium for oxygen evolution reaction (OER). The physiochemical and electrical characterization techniques are used to investigate the chemical structure, morphology, and electrical properties of the In₂MnSe₄ material. The electrochemical result indicates that synthesized material exhibits a smaller value of Tafel slope (86 mV/dec), lower overpotential (259 mV), and high stability for 37 h with small deterioration in the current density for a long time. Hence, the fabricated material responds with an extraordinary performance for the OER process and for many other applications in the future. Full article

The rise of artificial intelligence (AI), blockchain (BC), and the internet of things (IoT) has had significant applications in the advancement of sustainability research. This review examines how these digital transformations drive natural and human systems, as well as which industry sectors have been applying them to advance sustainability. We adopted qualitative research methods, including a bibliometric analysis, in which we screened 960 publications to identify the leading sectors that apply AI/BC/IoT, and a content analysis to identify how each sector uses AI/BC/IoT to advance sustainability. We identified “smart city”, “energy system”, and “supply chain” as key leading sectors. Of these technologies, IoT received the most real-world applications in the “smart city” sector under the dimensions of “smart environment” and “smart mobility” and provided applications resolving energy consumption in the “energy system” sector. AI effectively resolved scheduling, prediction, and monitoring for both the “smart city” and “energy system” sectors. BC remained highly theoretical for “supply chain”, with limited applications. The technological integration of AI and IoT is a research trend for the “smart city” and “energy system” sectors, while BC and IoT is proposed for the “supply chain”. We observed a surge in AI/BC/IoT sustainability research since 2016 and a new research trend—technological integration—since 2020. Collectively, six of the United Nation’s seventeen sustainable development goals (i.e., 6, 7, 9, 11, 12, 13) have been the most widely involved with these technologies. Full article

Sweet pepper is susceptible to changes in temperature conditions, especially above 30 °C. In this research study, two cultivars, Melchor and Tamarín, were subjected to three different temperatures. For this, the experiment was run at three specific temperatures (24 °C, 28 °C, and 32 °C), keeping the rest of the parameters the same in all experiments. In fully mature fruits, parameters such as weight, color, TSS, total phenols, mineral content, and amino acid content were analyzed. Our results showed that high temperatures reduced fruit weight and increased color parameters, mainly in Melchor. In addition, a temperature of 28 °C advanced the maturation of the Tamarín fruits by 14 days with respect to 24 °C. At a nutritional level, high temperatures caused a reduction in TSS, total phenols, and cations, and on the contrary, increased the content of anions. In the case of amino acids, a temperature increase to 28 °C caused a general increase in the amino acids measured, except for proline, which was reduced. Thus, the data from this study support the need to study new strategies in crop management to reduce the negative effects that the unstoppable rise in temperatures due to climate change will produce. Full article

Coasts are highly dynamic and geo-morphologically complex systems that are exposed to several factors such as waves, extreme meteorological events and climate change. It is also well-recognized that coastal zones, characterized by an increasing population growth, are vulnerable to climate change. In addition, coastal erosion, resulting from natural environment changes and human activities, acts worldwide. Consequently, it is necessary to quantify coastal hazards vulnerability and develop tools to monitor coastal risks and support making targeted climate adaptation policies. In this paper, a framework to estimate coastal vulnerability to flooding and erosion has been developed for the Ionian Basilicata coast. It is based on two methods: the integrated vulnerability index (flooding and erosion) and the CeD physical vulnerability index (multi-risk assessment). Our results are in agreement with the recent shoreline evolution: the integrated coastal risk of the Ionian Basilicata coast is generally medium to high, while the “physical erosion vulnerability” is generally high to very high. In addition, the results highlight a spatial variability of the vulnerability, probably due to the morphology of the beach, which requires developing a strategic approach to coastal management and defining mitigation measures, considering relevant risk aspects as the vulnerability and exposure degree. Full article

This study established power-related efficiency measures from the perspective of reliability, namely, power system availability, expected power deficiency, accumulated power deficiency, instantaneous power capacity, and accumulated power capacity for a hybrid power system (HPS) in a generic smart grid. Methodologically, a power supply–demand stochastic model that simultaneously considers the inherently stochastic nature of power supply and demand was developed to quantify their interrelationship and characterize the dynamic behavior of an HPS in a continuous-time Markov chain. Preventive maintenance (PM) models were also constructed to determine the optimal PM strategy in alignment with specific scenarios that reflect the power performance requirements and resource limitations. A sensitivity analysis was conducted using the design of experiments (DOE) scheme that simulated climate change and revealed that extreme climate worsens power-related efficiency measures. This analysis provides further insight into the extent to which extreme climate conditions diminish the engineers and designers of smart grid systems’ power-related efficiency measures. The proposed approach will potentially contribute to sustainability and maintainability in the clean energy industry. Full article

Olive tree cultivation is currently a dominant agriculture activity in the Mediterranean basin, where the increasing impact of climate change coupled with the inefficient management of olive groves is negatively affecting olive oil production and quality in some marginal areas. In this context, satellite imagery may help to monitor crop growth under different environmental conditions, thus providing useful information for optimizing olive grove management and final production. However, the spatial resolution of freely-available satellite products is not yet adequate to estimate plant biophysical parameters in complex agroecosystems such as olive groves, where both olive trees and grass cover contribute to the vegetation indices (VIs) signal at pixel scale. The aim of this study is therefore to test a disentangling procedure to partition the VIs signal among the different components of the agroecosystem to use this information for the monitoring of olive growth processes during the season. Specifically, five VIs (GEMI, MCARI2, NDVI, OSAVI, MCARI2/OSAVI) as recorded by Sentinel-2 at a spatial resolution of 10 m over five olive groves in the Montalbano area (Tuscany, Central Italy), were tested as a proxy for olive tree intercepted radiation. The olive tree volume per pixel was initially used to linearly rescale the VIs signal into the relevant value for the grass cover and olive trees. The models, describing the relationship between rescaled VIs and observed fraction of Photosynthetically Active Radiation (fPAR), were fitted and then validated against independent datasets. While in the calibration phase, a greater robustness at predicting fPAR was obtained using NDVI (r = 0.96 and RRMSE = 9.86), the validation results demonstrating that GEMI and MCARI2/OSAVI provided the highest performances (GEMI: r = 0.89 and RRMSE = 21.71; MCARI2/OSAVI: r = 0.87 and RRMSE = 25.50), in contrast to MCARI2 that provided the lowest (r = 0.67 and RRMSE = 36.78). These results may be related to the VIs’ intrinsic features (e.g., lower sensitivity to atmosphere and background effects), which make some of these indices, compared to others, less sensitive to saturation effects by improving fPAR estimation (e.g., GEMI vs. NDVI). On this basis, this study evidenced the need to improve the current methodologies to reduce inter-row effects and select appropriate VIs for fPAR estimation, especially in complex agroecosystems where inter-row grass growth may affect remote sensed-derived VIs signal at an inadequate pixel resolution. Full article

In the context of global warming, relevant studies have shown that China will experience the largest temperature rise in the Qinghai–Tibet Plateau and northwestern regions in the future. Based on MOD10A2 and MYD10A2 snow products and snow depth data, this study analyzes the temporal and spatial evolution characteristics of the snow cover fraction, snow depth, and snow cover days in the three stable snow cover areas in China, and combines 15 modes in CMIP6 snow cover data in four different scenarios with three kinds of variables, predicting the spatiotemporal evolution pattern of snow cover in China’s three stable snow cover areas in the future. The results show that (1) the mean snow cover fraction, snow depth, and snow cover days in the snow cover area of Northern Xinjiang are all the highest. Seasonal changes in the snow cover areas of the Qinghai–Tibet Plateau are the most stable. The snow cover fraction, snow depth, and snow cover days of the three stable snow cover areas are consistent in spatial distribution. The high values are mainly distributed in the southeast and west of the Qinghai–Tibet Plateau, the south and northeast of Northern Xinjiang, and the north of the snow cover area of Northeast China. (2) The future snow changes in the three stable snow cover areas will continue to decline with the increase in development imbalance. Snow cover fraction and snow depth decrease most significantly in the Qinghai–Tibet Plateau and the snow cover days in Northern Xinjiang decrease most significantly under the SSPs585 scenario. In the future, the southeast of the Qinghai–Tibet Plateau, the northwest of Northern Xinjiang, and the north of Northeast China will be the center of snow cover reduction. (3) Under the four different scenarios, the snow cover changes in the Qinghai–Tibet Plateau and Northern Xinjiang are the most significant. Under the SSPs126 and SSPs245 scenarios, the Qinghai–Tibet Plateau snow cover has the most significant change in response. Under the SSPs370 and SSPs585 scenarios, the snow cover in Northern Xinjiang has the most significant change. Full article

The primary objective of this study was to develop a climate-sensitive modular-based structural stand density management model (SSDMM) for red pine (Pinus resinosa Aiton) plantations situated within the western Great Lakes—St. Lawrence and south-central Boreal Forest Regions of Canada. For a given climate change scenario (e.g., representative concentration pathway (RCP)), geographic location (longitude and latitude), site quality (site index) and crop plan (e.g., initial espacement density and subsequent thinning treatments), the resultant hierarchical-based SSDMM consisting of six integrated modules, enabled the prediction of a multitude of management-relevant performance metrics over rotational lengths out to the year 2100. These metrics included productivity measures (e.g., mean annual volume, biomass and carbon increments), volumetric yield estimates (e.g., total and merchantable volumes), pole and log product distributions (e.g., number and size distribution of pulp and saw logs, and utility poles), biomass production and carbon sequestration outcomes (e.g., oven-dried masses of above-ground components and associated carbon mass equivalents), recoverable end-product volumes and associated monetary values (e.g., volumes and economic worth estimates of recovered chip and dimensional lumber products extractable via stud and randomized length mill processing protocols), and crop tree fibre attributes reflective of end-product potential (e.g., wood density, microfibril angle, and modulus of elasticity). The core modules responsible for quantifying stand dynamics and structural change were developed using 491 tree-list measurements and 146 stand-level summaries obtained from 98 remeasured permanent sample plots situated within 21 geographically separated plantation-based initial spacing and thinning experiments distributed throughout southern and north-central Ontario. Computationally, the red pine SSDMM and associated algorithmic analogue (1) produced mathematically compatible stem and end-product volume estimates, (2) accounted for density-dependent as well as density-independent mortality losses, response delay following thinning and genetic worth effects, (3) enabled end-users to specify merchantability standards (log and pole dimensions), product degrade factors and cost profiles, and (4) addressed climate change impacts on rotational yield outcomes by geo-referencing RCP-specific effects on stand dynamical processes via the deployment of a climate-driven biophysical site-based height-age model. In summary, the provision of the red pine SSDMM and its unique ability to account for locale-specific climate change effects on crop planning forecasts inclusive of utility pole production, should be of consequential utility as the complexities of silvicultural decision-making intensify during the Anthropocene. Full article