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In the effort to limit global warming to 1.5°C above the pre-industrial level, decarbonization of supply chains is crucial. Companies will need to reduce not only their direct and indirect emissions (scope 1 and 2) but also their indirect emissions (scope 3). In some sectors, the upstream scope 3 emissions can actually be larger than the companies' direct emissions. Therefore, a systematic literature review was carried out to understand how previous research in the field of supply chain management (SCM) approached energy efficiency and energy management in the upstream supply chain. The results indicate that only a few studies have addressed energy efficiency within SCM, and the majority assess energy solely as total energy use, without exploring opportunities to reduce final energy use among upstream suppliers. Moreover, results show that there is a lack of standards and methods to assess suppliers' energy use, making it difficult for suppliers, particularly small and medium-sized enterprises, to overcome barriers to implementing energy management. In conclusion, even though energy efficiency is a cost-effective means to reduce CO2 emissions, only a limited number of studies in the field of SCM have integrated energy efficiency, revealing a vast knowledge gap in this field. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development. [ABSTRACT FROM AUTHOR]

In response to the challenges of global warming and the development of A low-carbon economy, the integrated electricity and natural gas energy system (IEGES) is known as an important structure for future energy supply; thus, its planning and design must take low-carbon and environmental protection factors into account. Regarding carbon emissions as an optimization criterion, this paper built life-cycle carbon emission models of IEGES components. Then, taking the capacities of the energy resources, storage and conversion units of IEGES as the optimization variables, a multi-objective optimization configuration model was established considering the annual investment operation cost and the life-cycle carbon emissions. The multi-objective model was transformed into a single-objective one by an ε-constraint approach and the polynomial fitting method was employed to obtain the value of ε for obtaining uniformly distributed Pareto sets. Based on the fuzzy entropy weight method and the fuzzy affiliation degree approach, the obtained Pareto sets were ranked and the solution with the highest ranking value was selected as the optimal solution for the original problem. Finally, the configuration schemes were analyzed from the perspectives of economy, carbon emission and renewable energy utilization, and the effectiveness and rationality of the proposed optimization method were verified through MATLAB simulation. [ABSTRACT FROM AUTHOR]

With the acceleration of the global warming process, the clean energy crisis is becoming serious; conventional energy is unlikely to solve the current crisis, so people pay attention to new energy. As wave energy is widely distributed, renewable, and clean, hundreds of wave energy converters emerge. In order to understand the research progress of wave energy converters better, this paper divides wave energy converters into overtopping type, oscillating water column type, and oscillating body type according to the working principle and divides the oscillating body type into oscillating float type and oscillating pendulum type by different ways of energy capture. Based on the classification, various types of engineering cases, physical tests and digital simulation, and other academic research results are summarized, especially the generation power and energy conversion efficiency of various devices, and some shortcomings and suggestions are put forward, hoping to provide help for readers to study wave energy generation converters. [ABSTRACT FROM AUTHOR]

Overheating in school buildings can negatively affect the cognitive learning performance of particularly young students whose thermoregulation systems are still developing. However, currently, in schools, issues related to overheating have been addressed by limiting the exposure time to thermal discomfort. In this paper, the development of a general procedure that combines building and bioheat simulations to evaluate overheating risk in schools and generate health-based overheating limit criteria that may be applied in Canadian schools is described. General school building models, having either old or new constructions, were created based on a primary school building and successfully calibrated using field measurements of indoor temperature and humidity and published building energy use intensity data. Three sets of two limit criteria (exposure duration and severity of overheating) that account for the personal exposure conditions of students in primary, middle, and secondary schools were developed by limiting the body dehydration of students during extreme overheating events. Comparing the proposed limit criteria with the hour of exceedance criterion revealed interesting relationships between them, suggesting the proposed limit criteria as a benchmark for the comfort-based criteria, particularly for the more vulnerable primary and middle schools. The proposed procedure with the obtained overheating limit criteria is intended to be applied in any field or simulation study to assess the risk of overheating in similar school buildings under any local prevailing climate. [ABSTRACT FROM AUTHOR]

Despite the serious threat of global warming caused by carbon emissions, commercial refrigeration systems that generate cooling are unable to adjust their usage time. Therefore, it is essential to enhance the energy efficiency of refrigeration systems themselves. Recently developed refrigeration systems offer improved energy consumption efficiency as they utilize inverter-type outdoor units that can communicate with indoor units. However, traditional legacy refrigeration systems still suffer from poor energy efficiency because the existing indoor units cannot communicate with inverter-type outdoor units. Hence, this paper introduces a heuristic energy efficiency improvement algorithm for commercial refrigeration systems using legacy indoor units when an inverter-type outdoor unit is installed. In particular, to reduce the computational complexity of the process of selecting the optimal temperature difference and target low-pressure variables that can enhance energy efficiency, the algorithm employs the Monte Carlo method. Finally, the performance of the proposed heuristic energy efficiency improvement algorithm was evaluated in a laboratory environment to confirm its applicability. [ABSTRACT FROM AUTHOR]

EV development is being prioritized in order to attain the target of net zero emissions by 2050. Electric vehicles have the potential to decrease greenhouse gas (GHG) emissions, which contribute to global warming. The driving range of electric vehicles is a significant limitation that prevents people from using them generally. This paper proposes a comprehensive model for calculating the amount of energy needed to charge EVs for a scheduled trip. The model contains anticipated consumption energy for the whole trip as well as contingency energy to account for unpredictable conditions. The model is simple to apply to various types of electric vehicles and produces results with sufficient precision. A number of driving tests with different road characteristics and weather conditions were implemented to evaluate the success of the proposed method. The findings could help the users feel more confidence when driving EVs, promote the usage of EVs, and advocate for the increased use of green and renewable energy sources. [ABSTRACT FROM AUTHOR]

The greenhouse effect was focused by more learners with the global warming. It has become a very serious issue the relationship between foreign direct investment (FDI) and carbon emissions in the process of sustainable economic development in Shandong. This paper studied the relationship trend in middle of FDI, carbon emissions, and greenhouse effect impact mechanism in Shandong Province based on the data from 2000 to 2016 in Shandong Province by simultaneous equation model from qualitative and quantitative analysis. There is an inverted environmental Kuznets curve correlation between FDI and carbon emissions. The mechanism of FDI's impact on Shandong's ecological environment in three aspects: scale effect, structure effect, and technology effect. The results show that FDI has negative scale effect, structure effect and positive technology effect on carbon emissions in Shandong Province, and the overall effect is negative. Accordingly, taking the transformation of new and old kinetic energy in Shandong Province as the goal, this paper puts forward the optimization strategy, provides policy suggestions for the government in the implementation of the transformation of new and old kinetic energy, in order to better promote economic development, industrial restructuring and upgrading, and realize the construction of regional ecological civilization. [ABSTRACT FROM AUTHOR]

In temperate climates, such as in most parts of Italy, it is necessary to limit both winter heat losses of buildings and their overheating in other periods. Moreover, in warmer Mediterranean climates the convenience of insulation against the building's thermal inertia must also be evaluated. Therefore, when the energy renovation of an old building with heavy masonry is performed the problem is to optimize the position and the thickness of the additional insulation. In presence of extended glazed surfaces, the most appropriate solar control strategy should be defined too. Both issues are present in many old Italian public buildings. This paper deals with a computerized methodology for optimizing these choices by taking into account the interactions between thermal mass, additional insulation as well as internal and solar gains. The case study consists in a typical school building from the early 1900s. Building's thermal behavior was simulated in different Italian climates: Bologna, Roma and Palermo. The effects of various solutions on energy demand and comfort were compared. The possible effects of different types of masonry, different building's orientations and various intended uses were also explored. Simulation results show that the optimal intervention strategy, for the considered type of building, depends not only on the climate but also on the building's intended use, which determines the internal gains and the time profile of use. [ABSTRACT FROM AUTHOR]

This paper analyses, as a case study, various balcony glazing arrangements in a typical tourist apartment building on the Mediterranean coast of south-eastern Spain, and their effects on the energy performance. The glazing of terraces has been very common in this type of flat over the last 40 years. The objective is to determine qualitatively and quantitatively how the glazing of terraces in such buildings influences their energy efficiency and indoor thermal comfort, considering the specific characteristics of the dry Mediterranean climate (BShs) within a warm semi-arid climate (BSh). The scientific novelty of the work consists of demonstrating that the installation of glazed enclosures on terraces allows the houses to be heated for free in winter, taking advantage of the greenhouse effect, and allows excess heat to be dissipated in summer by using natural ventilation. The results of the work enable the determination of appropriate terrace glazing solutions to improve the energy efficiency and thermal comfort of the dwelling, obtaining a reduction of more than 58% in annual energy demand and annual energy consumption. The work demonstrates the advantages that glazing systems for terraces can have in improving the energy efficiency of houses by using systems like glass curtains. [ABSTRACT FROM AUTHOR]

Blockchain technology is being looked at to solve numerous real-world problems that demand transparency by meeting sustainable goals. Do we ponder whether this technology is a boon or a bane for the environment? This paper analyses blockchain's dominant consensus method, Proof-of-Work (PoW), which consumes more energy than Malaysia and Sweden and further deteriorates the environment through carbon emissions. This study is the first systematic evaluation of PoW consensus-based blockchain applications' environmental consequences. We found 11 significant Theories, 6 Contexts, and 26 Methodologies (TCM) in 60 reviewed articles. We propose an Antecedents, Drivers, and Outcomes (ADO) model, which depicts that marginal profits drive high energy consumption and carbon emissions, with non-renewable energy proportionally responsible for carbon emissions. The article distinctively uses an integrated TCM-ADO framework for literature synthesis and the PESTLE framework for reporting future research areas. This is the first study to use the following four frameworks: PRISMA; TCM; ADO; and PESTLE for systematic literature review. Profit is identified as one of the most significant drivers of energy consumption and further carbon emissions. The article proposes 65 future research areas and makes theoretical contributions to the literature that may interest academicians, practitioners, and social stakeholders. [ABSTRACT FROM AUTHOR]

Why do neurons communicate through spikes? By definition, spikes are all-or-none neural events which occur at continuous times. In other words, spikes are on one side binary, existing or not without further details, and on the other, can occur at any asynchronous time, without the need for a centralized clock. This stands in stark contrast to the analog representation of values and the discretized timing classically used in digital processing and at the base of modern-day neural networks. As neural systems almost systematically use this so-called event-based representation in the living world, a better understanding of this phenomenon remains a fundamental challenge in neurobiology in order to better interpret the profusion of recorded data. With the growing need for intelligent embedded systems, it also emerges as a new computing paradigm to enable the efficient operation of a new class of sensors and event-based computers, called neuromorphic, which could enable significant gains in computation time and energy consumption—a major societal issue in the era of the digital economy and global warming. In this review paper, we provide evidence from biology, theory and engineering that the precise timing of spikes plays a crucial role in our understanding of the efficiency of neural networks. [ABSTRACT FROM AUTHOR]

In response to global warming, China has formulated the "double carbon" strategic goals of peaking carbon dioxide emissions before 2030 and reaching carbon neutrality before 2060. The problem of rural carbon emissions is often ignored due to underdeveloped industries and services. In this paper, the carbon emission pathways in the rural areas of Guangdong Province are investigated. Since energy consumption is the main source of carbon emissions, the factor analysis was used to analyze the main factors affecting rural household energy consumption and agricultural production energy consumption. Multiple linear regression was conducted to predict the rural energy consumption demand in Guangdong. Furthermore, the current situation and development trend of rural energy supply, demand and consumption structure, and the potential of renewable energy development were considered to predict carbon emissions in the rural areas of Guangdong. Moreover, the carbon emission pathways in the rural areas of Guangdong were discussed under two scenarios: the base scenario and the radical model. [ABSTRACT FROM AUTHOR]

The paper presents a comparison of the fuel oil (FO) consumption and carbon dioxide (CO2) emissions of a container ship's 8000 twenty-foot equivalent unit (TEU) during oceanographic navigation. The evaluation has two types of FOs: a 3.4% heavy fuel oil with desulfurization (HFOWD) and a 0.5% very-low-sulfur fuel oil (VLSFO), based on the sulfur cap policy of the International Maritime Organization (IMO). The results show the average FO consumption at 130 tons/day of HFOWD and 141 tons/day of VLSFO, which means shifting to VLSFO increases fuel consumption 8.4% more than the HFOWD. The average CO2 emissions are 429 tons/day of the HFOWD and 471 tons/day of the VLSFO, indicating an 9.5% increase in CO2 emissions when the IMO adopts the low-sulfur fuel policy. Moreover, the VLSFO blending of various chemicals further deteriorates and wears out the main engine of the ship. IMO's low-sulfur fuel policy significantly reduced the emission of sulfur oxides (SOX) and particulate matter emissions. Still, we should not ignore the fact that adopting VLSFO may cause more CO2 emissions. Therefore, while switching to low-sulfur fuels, the maritime industry should improve the related energy efficiency to reduce fuel consumption and CO2 emissions. [ABSTRACT FROM AUTHOR]

Energy need is predicted to increase by 48% in the next 30 years. Global warming resulting from the continuously increasing atmospheric CO2 concentration is becoming a serious and pressing issue that needs to be controlled. CO2 capture and storage/use (CCS/CCU) provide a promising route to mitigate the environmental consequences of CO2 emission from fossil fuel combustion. In recent years, hollow fiber membrane contactors are regarded as an advanced technique with several competitive advantages over conventional technologies such as easy scale-up, independent control of flow rates, more operational flexibility, absence of flooding and foaming as well as high interfacial area per unit volume. However, many factors such as the membrane material selection, proper choice of solvent, and membrane module design are critical to success. In this regard, this paper aims at covering all areas related to hollow fiber membranes, including membrane material, membrane modification, membrane surface modification, shape, solvent characterization, operating parameters and costs, hybrid process, membrane lifetime, and energy consumption as well as commercially available systems. Current progress, future potential, and development of pilot-scale applications of this strategy are also assessed carefully. Furthermore, pore wetting as the main technical challenge in membrane contactor industrial implementation for post- and pre-combustion CO2 capture processes is investigated in detail. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and Russia's war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlighting the need for greater energy diversification and reliance on local, renewable energy sources. However, the early evidence suggests that policymaking worldwide is focused on short-term, seemingly quicker solutions, such as supporting the incumbent energy industry in the post-pandemic era to save the economy and looking for new fossil fuel supply routes for enhancing energy security following the war. As such, the fossil fuel industry may emerge even stronger after these energy crises creating new lock-ins. This implies that the public sentiment against dependency on fossil fuels may end as a lost opportunity to translate into actions toward climate-friendly energy transitions, without ambitious plans for phasing out such fuels altogether. We propose policy recommendations to overcome these challenges toward achieving resilient and sustainable energy systems, mostly driven by energy services. [ABSTRACT FROM AUTHOR]

Cities, as production and consumption hubs, cause significant amount of global CO2 emissions and energy consumption. Climate change challenges world's welfare due to the global warming. Cities' environmental footprint can be reduced with the help of energy efficient and sustainable built environment which can further contribute to the wellbeing and welfare of the urban population contributing to the solution of the fuel poverty. Straw is a traditional and contemporary material having outstanding technical characteristics (e.g. thermal insulation). Straw is a traditional material as it has been used in sheltering starting from the ancient times. Straw is a contemporary material as it is used even in small buildings with the help of innovations. Furthermore, it is a cost effective material from initial investment as well as maintenance and repair aspects. Straw houses can reduce energy consumption. This can reduce countries' trade deficit due to the reduced demand for energy import, contributing to the solution of the fuel poverty. Straw is environmental friendly natural material. Constructing straw houses is important for sustainable living. Giving importance to the straw house construction can help reduction in the CO2 emission and in the energy consumption. Based on an in-depth literature review, this paper investigates political economy of straw houses and straw houses' contribution to the sustainability performance of the built environment. This paper introduces to the literature political economy of the straw houses and provides recommendations on how to widespread the use of straw houses. [ABSTRACT FROM AUTHOR]

The TeMA Journal of Land Use Mobility and Environment focuses on the integration of urban transformation studies and mobility governance for environmental sustainability. The 2024 volume addresses various challenges faced by cities in the 21st century, including global warming, an aging population, energy consumption reduction, immigration flows, land use optimization, and technological innovation. The articles cover topics such as land use changes in coastal wetlands in Sri Lanka, gender analysis of urban mobility behaviors in Tunisia, sustainable development and the role of new public spaces, spatial attractiveness for industrial placement, planning the transition of cities, and the cost of shopping in physical and virtual spaces. The journal also includes review notes on energy transition policies, strategies for active mobility, climate change adaptation, and urban safety for women. [Extracted from the article]

The exponential increase in the number of daily traveling vehicles has exacerbated global warming and environmental pollution issues. These problems directly threaten the continuity and quality of life on the planet. Several techniques and technologies have been used and developed to reduce fuel consumption and gas emissions of traveling vehicles over the road network. Here, we investigate some solutions that assist drivers to follow efficient driving tips during their trips. Advanced technologies of communications or vehicle manufacturing have enhanced traffic efficiency over road networks. In addition, several advisory systems have been proposed to recommend to drivers the most efficient speed, route, or other decisions to follow towards their targeted destinations. These recommendations are selected according to the real-time traffic distribution and the context of the road network. In this paper, different high fuel consumption scenarios are investigated over the road networks. Next, the details of efficient driving techniques that were proposed to tackle each case accordingly are reviewed and categorized for downtown and highway driving. Finally, a set of remarks and existing gaps are reported to researchers in this field. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with innovative approaches to renewable energy sources computation methodologies, which provide more refined results than the classical alternatives. Such refinements provide additional improvements especially for replacement of fossil energy usages that emit greenhouse gas (GHG) into the atmosphere leading to climate change impact. Current knowledge gap among each renewable energy source calculation is rather missing fundamentals of plausible, rational, and logical explanations for the interpretation of results. In the literature, there are rather complicated and mechanically applicable methodologies, which require input and output measurement data match with missing physical explanations. The view taken in this review paper is to concentrate on quite plausible, logical, rational, and effectively applicable innovative energy calculation methodologies with simplistic fundamentals. For this purpose, a set of renewable energy methodological approaches is revisited with their innovative structures concerning solar, wind, hydro, current, and geothermal energy resources. With the increase in the renewable energy utilizations to combat the undesirable impacts of global warming and climate change, there is a need for better models that will include physical environmental conditions and data properties in the probabilistic, statistical, stochastic, logical, and rational senses leading to refined and more reliable estimations with application examples in the text. Finally, new research directions are also recommended for more refined innovative energy system calculations. [ABSTRACT FROM AUTHOR]

Air-source heat pumps are strongly influenced by outdoor conditions, it is expected that ongoing climate changes may impact their operation. This paper presents a predictive analysis of the behaviour of air-source heat pumps in two cities with extremely cold and warm climates in the short, medium, and long term. The seasonal coefficient of performance and heat pump seasonal energy efficiency index are evaluated over the years, considering climate change for both locations. Climate change will shorten the winter period and prolong the summer. In winter, this results in a slight softening of the seasonal coefficient of performance and a reduction in operating hours. In summer, there is a slight increase in seasonal energy efficiency ratio values and hours of operation. The work highlights how the performance of the air-source heat pump, on average, will improve in winter due to an average increase in temperature. Heat pumps are expected to be used in the future and in geographical areas where they are not currently used due to the extreme winter temperatures. [ABSTRACT FROM AUTHOR]

Global warming is resulting in higher summer indoor temperatures in the severe cold region and cold region of China, and this is affecting thermal comfort. Local building design codes consider these regions as cool in summer, and do not consider the phenomenon of overheating or propose countermeasures. This paper studied the possibility of overheating in residential buildings in these areas. It suggested alleviating this phenomenon using external horizontal shading, and discussed how to integrate thermal comfort into the building design and save energy consumption. The IESVE software was used to simulate 18-storey residential buildings with natural ventilation in Yichun, Harbin, Shenyang, Dalian, and Beijing, and to calculate the change in indoor operative temperature. Horizontal shading was designed for case study building to attempt to alleviate the overheating phenomenon in summer. The results showed that the case study building in the five cities experienced different degrees of overheating. External horizontal shading was successful in reducing indoor overheating, especially in the severe cold B and C zones and the cold A and B zones. The relevant building codes should be modified to take this into account. Reasonable design of horizontal shading can effectively reduce energy consumption, particularly when compared with air-conditioned buildings. [ABSTRACT FROM AUTHOR]

Energy consumption is steadily increasing with the ever-growing population, leading to a rise in global warming. Building energy consumption is one of the major sources of global warming, which can be controlled with renewable energy installations. This paper deals with an advanced evacuated hybrid solar photovoltaic–thermal collector (PVT) for simultaneous production of electricity and domestic hot water (DHW) with lower carbon emissions. Most PVT projects focus on increasing electricity production by cooling the photovoltaic (PV). However, in this research, increasing thermal efficiency is investigated through vacuum glass tube encapsulation. The required area for conventional unglazed PVT systems varies between 1.6–2 times of solar thermal collectors for similar thermal output. In the case of encapsulation, the required area can decrease by minimizing convective losses from the system. Surprisingly, the electrical efficiency was not decreased by encapsulating the PVT system. The performance of evacuated PVT is compared to glazed and unglazed PVTs, and the result shows a 40% increase in thermal performance with the proposed system. All three systems are simulated in ANSYS 18.1 (Canonsburg, PA, USA) at different mass flow rates and solar irradiance. [ABSTRACT FROM AUTHOR]

The rising concerns about global warming have motivated the international community to take remedial actions to lower greenhouse gas emissions. The transportation sector is believed to be one of the largest air polluters. The quantity of greenhouse gas emissions is directly linked to the fuel consumption of vehicles. Eco-driving is an emergent driving style that aims at improving gas mileage. Real-time fuel estimation is a critical feature of eco-driving and eco-routing. There are numerous approaches to fuel estimation. The first approach uses instantaneous values of speed and acceleration. This can be accomplished using either GPS data or direct reading through the OBDII interface. The second approach uses the average value of the speed and acceleration that can be measured using historical data or through web mapping. The former cannot be used for route planning. The latter can be used for eco-routing. This paper elaborates on a highly pipelined VLSI architecture for the fuel estimation algorithm. Several high-level transformation techniques have been exercised to reduce the complexity of the algorithm. Three competing architectures have been implemented on FPGA and compared. The first one uses a binary search algorithm, the second architecture employs a direct address table, and the last one uses approximation techniques. The complexity of the algorithm is further reduced by combining both approximated computing and precalculation. This approach helped reduce the floating-point operations by 30% compared with the state-of-the-art implementation. [ABSTRACT FROM AUTHOR]

Smart technology has potential in tracking the key challenges based on population based on the sustainable future. In today's cultures, a smart approach enables for the integration of information needed to address crucial concerns. The critical challenge is to limit the effects of global warming while maintaining a balanced economic growth. The impact of global warming mitigates the fundamental problem while ensuring the balance economic development. Intense research efforts should be directed toward balanced resource utilization, renewable energy system integration, efficient energy conversion technologies, effective process integration, effective techniques to enable a circular economy framework, and other issues that are important to the population. This paper finds the latest technology in the field of smart grid technologies which focused on the effective enhancement and efficient utilization of resource. The issues and challenges in using sustainable future are discussed and bring new ideas towards the sustainable future base on the application of smart technologies. [ABSTRACT FROM AUTHOR]

With the growing concerns on global warming, much research attention has been focused on industrial activities which largely consume energy and emit carbon to the atmosphere. Low-carbon manufacturing, aiming to reduce carbon intensity and enhance resource utilization, is then emerging as a timely topic and spurs much research into a low carbon scenario. This paper proposes an analytical method of quantifying carbon emissions of a computer numerical control (CNC)-based machining system. In particular, the paper discusses the breakdown of the processes that contribute to the overall carbon emissions of a CNC-based machining system, such as electricity, cutting fluid, wear and tear of cutting tools, material consumption and disposal of chips, etc. The way of quantifying the amount of carbon emissions from individual processes are then analyzed. Finally, the proposed methodology is applied into two different machining cases, in which the impact of different machining parameters and different machining methods on carbon emissions in the CNC machining process are analyzed, respectively. [ABSTRACT FROM AUTHOR]

HVAC and refrigeration system fault detection and diagnostics (FDD) has attracted extensive studies for decades; however, FDD of supermarket refrigeration systems has not gained significant attention. Supermarkets consume around 50 kWh/ft2 of electricity annually. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40%–60% of its total electricity usage and is equivalent to about 2%–3% of the total energy consumed by commercial buildings in the United States. Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Reducing refrigerant usage or using environmentally friendly alternatives can result in significant climate benefits. A challenge is the lack of publicly available data sets to benchmark the system performance and record the faulted performance. This paper identifies common faults of supermarket refrigeration systems and conducts an experimental study to collect the faulted performance data and analyze these faults. This work provides a foundation for future research on the development of FDD methods and field automated FDD implementation. Measurement(s) fault detection and diagnostics • temperature • pressure • mass flow rate • power Technology Type(s) fault imposition • measurement device Factor Type(s) fault type • fault scenario Sample Characteristic - Environment refrigeration system Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14384321 [ABSTRACT FROM AUTHOR]

Summary: The consumption of fossil fuel has resulted in global warming, environmental pollution, and many other crucial problems. Replacing fossil fuel with renewable energy has become an important issue over the recent decades. As a renewable clean energy, wind power is a relatively well‐developed and promising energy method for current technology development in China. Under the background of growing demand for electricity and enhancing awareness for environmental, the “Internet+ wind power” concept has emerged based on both the wind power's characteristics that renewable and non‐polluting, and the rapid development of the Internet in China. Through querying an amount of literature and information, this paper reveals the resource endowment and policy environment about wind power and energy Internet at first. Then, the PEST‐SWOT strategy analysis model is used to analyze the internalities (strengths and weaknesses) and the externalities (opportunities and threats) of “Internet+ wind power”. According to these results, the paper puts forward some measures (development and utilization, business mode) for wind power accommodation. Then some policy recommendations have been proposed. The government should provide favorable conditions for wind power grid with the “Internet+” technology innovation. [ABSTRACT FROM AUTHOR]

• This paper proposes a concept that utilizes historical time-series data from transmission system operators (TSOs) to estimate the optimal day-ahead energy-mix proportion for a power system dominated by converters. • This paper employs a long short-term memory (LSTM) network as a data-driven model to forecast the day-ahead values of key parameters. • To ensure secure system functioning, an energy-mix operation and reserve scheduling model is developed. • This paper emphasizes the importance of power system security in incorporating inverter based resources (IBRs). Advancements in various scientific fields have encouraged the development of novel tools, techniques, components, methodologies, and innovations aimed at addressing the challenges encountered in modern power systems dominated by inverter-based resources (IBRs). This paper focuses on a concept that leverages historical time-series data obtained from transmission system operators (TSOs) to enhance the secure management and operation of power systems. By employing a data-driven model, the day-ahead values of power generation and load consumption are estimated and integrated with a dynamic model of the power system for further analysis. To optimize energy generation and ensure grid stability, an energy-mix operation and reserve scheduling model is utilized. This model optimally combines different power-generating technologies, including synchronous generators (SGs), grid-following converters (GFLs), and grid-forming converters (GFMs), to meet the energy demands of the day while enhancing the overall system strength. The findings are supported by quantitative analysis utilizing variables such as frequency, power production, terminal voltages, and system non-synchronous penetration (SNSP). Simulation results demonstrate that implementing the proposed concept enables the power system under consideration to operate securely, even in the face of a 38% increase in immediate load, with a maximum SNSP ratio of 59%. These findings highlight the effectiveness of the proposed approach in addressing the reliability, system dynamics, stability, control efficiency, and security challenges posed by IBR-dominated power systems. Furthermore, it is believed that this research contributes to the ongoing efforts in decarbonization, renewable energy integration, and combating global warming by facilitating the secure and optimized operation of renewable energy-dominated power systems. [ABSTRACT FROM AUTHOR]

The implications of global warming on energy uses for heating and cooling in buildings are analysed in the paper. The research methodology is based on monitoring data on average daily temperature variation during a certain period and expected future temperature variation of existing mean daily temperatures according to a certain climate model. Developed model also uses the current real energy consumption of public buildings at a location and envisaged variation of cooling and heating degree day influenced by global warming. Based on the model, authors examine the influence of global warming on primary energy consumption for heating and cooling in public buildings in a city of Kragujevac, Serbia. The results show that a consequence of global warming should be a significant reduction of total primary energy consumption for heating and cooling in the public buildings. Possible increase in mean annual temperature of 3.8 °C till the end of the century has an impact to the reduction of primary energy use for heating for 35.7% in public buildings in Kragujevac, while predicted consumption of primary energy for cooling will be almost five times higher than nowadays. [ABSTRACT FROM AUTHOR]

It's generally known that ocean stores abundant energy resources for the development and growth of human beings. Nowadays, the sustainable development of marine economy calls for precisely speculation of marine energy prices and efficiency. However, the traditional methods of measuring energy price and efficiency, for instance, the EROI (energy return on investment) model unable to define system boundaries and to calculate labor and physical costs, be it tidal energy or marine biomass energy. Thus, these methods may ignore as much as 50% of input energy consumption. Energy efficiency could be calculated by the ratio of average energy input cost to the average useable energy output cost while energy price could be measured by the ratio of the monetary input to the output. The principle above could be viewed as a check for energy return on investment as well as an elimination for a redundant process analysis. The results give us a chance to innovate traditional energy efficiency model by social and environmental factors which could be depicted through monetary terms. The precise estimation of marine energy efficiency could also help us make appropriate policies to combat global warming. [ABSTRACT FROM AUTHOR]

The energy demand is increasing due to population growth and economic development. To satisfy this energy demand, the use of renewable energy is essential to face global warming and the depletion of fossil fuels. Photovoltaic energy is one of the renewable energy sources, widely used by several countries over the world. The integration of PV energy into the grid brings significant benefits to the economy and environment, however, high penetration of this energy also brings some challenges to the stability of the electrical grid, due to the intermittency of solar energy. To overcome this issue, the use of a forecasting system is one of the solutions to guarantee an effective integration of PV plants in the electrical grid. In this paper, a PV power ultra short term forecasting has been done by using univariate and multivariate LSTM models. Different combinations of input variables of the models and different timesteps forecasting were tested and compared. The main aim of this work is to study the influence of the different combinations of variables on the accuracy of the LSTM models for one-step forecasting and multistep forecasting and comparing the univariate and multivariate LSTM models with MLP and CNN models. The results show that for one step forecasting, the use of a univariate model based on historical data of PV output power is sufficient to get accurate forecasting with 28.98W in MAE compared to multivariate models that can reach 35.39W. Meanwhile, for multistep forecasting, it is mandatory to use a multivariate model that has historical data of meteorological variables and PV output power in the input of LSTM model. Moreover, The LSTM model shows great accuracy compared to MLP and CNN especially in multistep PV power forecasting. [ABSTRACT FROM AUTHOR]

Electricity, heating and cooling usage at the same time constitute an important part of primary energy consumption. Currently, intense efforts are being devoted to the improvement and development of new technologies to promote energy savings and to mitigate the global warming. Among these technologies, tri-generation and poly-generation systems come into prominence due to their high efficiencies, as well as low operating costs and low greenhouse gas emissions. Nevertheless, modelling and sizing these systems is a large-sized problem itself, and the higher the number of inputs, the higher the computational complexity. This paper aims to give a comprehensive review of the optimisation techniques used in tri-generation and poly-generation systems modelling and optimisation. After having reviewed more than a hundred papers, taxonomy is constructed. Self-organising map is used to cluster the reviewed studies based on the optimisation techniques. Variations of the energy resources and the outputs of implemented systems are summarised. The crowd of clusters demonstrated the widely used optimisation techniques and the gaps in research. This study will certainly pioneer the optimisation studies in the field of tri-generation/poly-generation applications. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The battery electric vehicle (BEV) industry, commanding over half of the global market share in China, has garnered significant attention in response to escalating concerns about climate change. NCM (LiNi x Co y Mn z O 2) batteries, prized for their high energy density, are pivotal in this industry. However, their production relies on critical metals, posing environmental challenges. Recycling processes aim to address this issue by recovering critical metals from end-of-life batteries. The industry is updating from NCM 111 to NCM 811 batteries to enhance energy density and reduce costs, but the key factors influencing the material flows and environmental impacts remain uncertain. This paper aims to identify the key factors contributing to the potential differences in material flows and environmental impacts introduced by the NCM battery upgrading in China. Following the new energy vehicle sales projections in China until 2035, a dynamic material flow analysis was employed to calculate material demands, recovered amounts, and substitution rates for various upgrading scenarios. The study reveals that the majority of retired batteries until 2035 were sold between 2022 and 2029. Material substitution rates prove to be more sensitive to the upgrading scenario than the lifetime and growth rate of BEVs. Faster NCM 811 penetration results in over 2.5 times more saved cobalt demand compared to additional nickel demand. A life cycle assessment of NCM batteries reveals a 39% lower global warming impact for NCM 811 compared to NCM 111, highlighting environmental benefits from increased energy density and reduced cobalt consumption. The energy density improvement contributed 85%, while the alteration in material composition contributed 15% to the global warming reduction in NCM 811. Recycling emerges as a crucial strategy in mitigating environmental impacts across all categories, particularly addressing eutrophication, previously deemed challenging due to the difficulty in recovering Li 2 CO 3. [ABSTRACT FROM AUTHOR]

Based on recent interest and on the importance of the ongoing climate change catastrophe, this article provides the basics of global carbon cycle modelling as required for the assessment of the degree of carbon neutrality of biomass energy, and its underlying dynamics. It is aimed at clarifying the question "Are biomass fuels carbon neutral?". The "Combined Energy and Biosphere Model" (CEBM) computes annual carbon flows including growth and decay of plants on 2.5 × 2.5° grid elements of the continents' surface and offers detailed results on the changes of after implementation of large-scale biomass energy strategies worldwide. The main (and possibly unexpected) effect is the long-term depletion of the soil organic compartment after extraction of biomass fuels. When comparing CEBM model runs using (i) biomass energy sources and (ii) carbon-free energy sources (such as solar or wind), it becomes quantitatively clear already on the theoretical level (i.e., even without taking into account efficiency losses) that biomass is only "half as carbon neutral" as ideally assumed, to express a rule of thumb—mainly because of soil carbon depletion. Still, biomass energy will play an important role when fighting global warming, even if efforts to lower energy demand are preferable as a fundamental strategy. [ABSTRACT FROM AUTHOR]

Thermal comfort is a complex issue in the built environment due to the physiological and psychological differences of each individual in a building. There is a growing worry over the environmental implications of energy use as a result of the warming of the global climate and the growth in the number of instances of extreme weather events. Many review articles have been written, but these reviews have focused on a specific aspect of occupant behavior and thermal comfort. To research the trends of thermal comfort and energy, this research adopted mixed reviews, i.e., quantitative and qualitative, to understand the state-of-the-art factors affecting the thermal comfort of occupants concerning energy, different occupant modeling approaches, functions, and limitations. The in-depth qualitative discussion provides deeper insights into the impacts of occupant behaviors, factors affecting thermal comfort, and occupant behavior modeling approaches. This study classified occupant behaviors into five categories: occupant characteristics, perceptions of the occupant, realistic behaviors, heat gain, and occupant interactions with the system. It also went further to classify the factors affecting the thermal comfort of users based on past works of literature. These include structural, environmental, and human factors. It was concluded that factors that have the most significant impact on energy are human, structural, and environmental factors, respectively. In addition, most of the occupant behavior modeling approaches that have been used in past studies have pros and cons and cannot accurately predict human behaviors because they are stochastic. Future research should be conducted on thermal comfort for different building functions by examining the varied activity intensity levels of users, especially in educational or commercial buildings. Additionally, a proper investigation should be carried out on how thermal insulation of structural members influences thermal comfort. These should be compared in two similar buildings to understand occupant behavioral actions and energy consumption. [ABSTRACT FROM AUTHOR]

International shipping currently accounts for about 3% of total global greenhouse gas (GHG) emissions, but would continue to rise as transport capacity expands. If the shipping industry aims at delivering its proportionate contribution to curbing global warming under the Paris agreement, the sector has to, inevitably, promote energy conservation and emission reduction. A rapidly growing oceangoing fleet size and correspondingly rising GHG emissions on a global scale raise an interesting research question: could a certain relationship between the two be characterized as a function so that further emissions can be forecast based on the model? The paper adopts an allometric approach based on biological scaling laws to explore the potential relationship between the fleet size and corresponding GHG emissions from shipping. The results show that both the slowdown of the navigation speed and the current implementation of the Energy Efficiency Design Index (EEDI) and Energy Efficiency Operation Index (EEOI) are effective on the whole. By employing the model, the development trends of GHG emissions from shipping in the future can be better understood. Through model applications and result analysis, numerical results validate the effectiveness of this method. The paper not only studies the development of GHG emissions from shipping in the past, but aslo evaluates its specific emission quantities in the future which is in line with the GHG emission reduction targets proposed by IMO on the 72nd IMO meeting, which will be helpful for policy decisions on the quota of GHG emissions to the International Maritime Organization (IMO) and port administrators. • Governance of GHG emissions from shipping is very important. • The relationship between fleet size and GHG emissions is explored. • The effects of different existing GHG emission reduction measures are analyzed. • Future tasks and pressures of GHG emission reduction are assessed. [ABSTRACT FROM AUTHOR]

Economic development needs energy support, but it is unsustainable to rely too much on high energy consumption and high pollution. At present, China is in the environment of global warming and deepening energy crisis. Its blueprint for development will be based on the theme of "low-carbon economy" and "ecological civilization construction". It will continuously develop existing new energy sources and explore unknown new energy sources as the source of new power for current and future economic development. In recent years, with the increasing R&D investment and policy support, the new energy industry has entered a period of rapid growth, and related listed companies have been able to expand rapidly. However, due to the blind investment and low-level expansion of some new energy enterprises, the excess capacity and low production efficiency of China's new energy industry have slowed down the pace of development of new energy industry, and limited the development space of new energy enterprises. As a result, inefficiency has become one of the bottlenecks restricting the further development of China's new energy industry and its listed companies. Solar tracking is one of the important ways to improve the utilization of solar energy, and there are many ways to achieve it. This paper is based on image processing to improve the design, around this idea, completed the new system simulation analysis, system development, experimental testing and other work. This paper focuses on the evaluation of distribution efficiency of new energy industry based on image processing. Natural images have their unique statistical properties, and interference will make them deviate from the original "natural statistical state". According to the characteristics of the image itself and human visual system, adjusting the image expression is more conducive to the transmission, storage and understanding of information. Therefore, this paper proposes a new energy industry distribution efficiency evaluation method based on image processing from three aspects: the nature of natural images, the expression of image information and the characteristics of human visual system. The research shows that this method can objectively and effectively evaluate the distribution efficiency of new energy industry, has certain practicability, and can effectively alleviate the bottleneck problems faced above. [ABSTRACT FROM AUTHOR]

The rapid development of public buildings has greatly increased the country's energy consumption and carbon emissions. Excessive carbon emissions contribute to global warming. This paper aims to measure the carbon emissions in the operation of public buildings, and to identify the multiple influencing factors of carbon emissions in operational public buildings. First, the spatial and temporal variation characteristics of carbon emissions from public buildings in 30 provinces of China from 2008–2019 are analyzed. Second, a green building index is constructed, and the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model is utilized to explore the relationship between each influencing factor and carbon emissions, using spatial and temporal geographically weighted regression analysis. The results show that the effects of population, urbanization rate, GDP per capita, green building index, and industrial structure on carbon emissions from public buildings all show spatial correlation and differences. There are east-west differences in the operational carbon emissions of public buildings in China's provinces. Cluster evolution shows a spatially increasing trend from west to east. To some extent, policymakers can develop appropriate policies for different provinces through the findings. [ABSTRACT FROM AUTHOR]

A Net Zero Community (NZC) concept and its energy characteristics are presented in this paper. NZC is an emerging topic with multiple variations in terms of scope and calculated methods, which complicates quantifying its performance. This paper covers three key barriers in achieving NZC targets: (1) the main focus of current definitions on buildings, disregarding community power systems and energy use in transportation; (2) different requirements (source, supply, metrics, etc.) in the existing definitions; and (3) lack of updated published reports to track the progress of committed NZC targets. The importance of this research is summarized as due to increased savings in primary energy and greenhouse gas emissions related to the three main energy sectors, namely power systems, buildings, and transportation (PBT). To clarify the current NZC, this paper reviews: (1) variations in the existing definitions and criteria from peer-reviewed publications; (2) the latest climate projection models by policymakers to achieve net zero by 2050; (3) the literature on renewable-based power systems; and (4) three planned NZC cases in international locations, in order to study their NZC targets, energy performance, and challenges. The outcome highlights NZC design guidelines, including energy efficiency measures, electrification, and renewables in PBT sectors that help stakeholders including policymakers, developers, designers, and engineers speed up achievement of NZC targets. [ABSTRACT FROM AUTHOR]

Two economic activities have been integrated in southern Brazil: olive cultivation and sheep farming. The favorable edaphoclimatic conditions in the southern region for cultivating olive trees and cultural preferences for the consumption of sheep meat make this integration a valuable strategy. Considering that every activity causes environmental impact and the exploitation of natural resources, new systems that promote sustainable development and the efficient use of these resources become necessary. This paper presents the first study of the carbon footprint of the life cycle of integrating of sheep and olive farming, with the objective to build an inventory based on primary data collected on olive and sheep farms in Brazil, determine the carbon footprint of the conventional and integrated system and estimate the potential for mitigating GHG emissions. The evaluation was performed using the life cycle assessment (LCA) methodology. The study focuses on the detailed analysis of the processes and activities that are responsible for GHG emissions, including enteric methane emissions, methane emissions from manure management, emissions from nitrogen fertilizer use and limestone application and energy consumption. For this, two major scenarios were considered, the first centered around on the traditional olive cultivation and sheep farming systems individually, and the second involved their synergistic integration. The findings indicate that the conventional system is associated with a global warming impact of 6.8 kg CO 2 eq per liter olive oil and kg live weight. In contrast, the integrated system demonstrates a significant mitigation potential of 27.7%, resulting in a reduced global warming impact of 4.92 kg CO 2 eq. This advantage is a consequence of the synergy between the systems, as they now occupy the same area, which allows the sharing of agricultural activities and agrochemical inputs, in addition to optimizing nutrient recycling and complementing each other. Additionally, the results of a sensitivity analysis showed that enteric methane from sheep and the application of limestone to the soil are the most influential parameters on the carbon footprint, indicating that they are key parameters for the development of GHG mitigation strategies, some of which were discussed in the article. • First life cycle assessment of integration between olive and sheep farming in Brazil. • The inventory was constructed with primary data collected in situ. • The study assesses the carbon footprint of the olive and sheep farming system. • The results show environmental advantages of the integration of olive and sheep farming systems. [ABSTRACT FROM AUTHOR]

Residential sector has been one key sector for reducing its greenhouse gas emissions due to its significant contribution to global warming. Researchers in different countries have studied household energy consumption patterns and greenhouse gas emissions in order to promote low-carbon lifestyles. However, few review papers have been published in this regard, leading to a lack of systematic understanding on the related research achievements. Hence, by using a bibliometric approach, this paper aims to review the existing literature and examine the evolution of such a field so that the research trends can be uncovered, including popular research methods. Citation analysis is performed to assess the influence of most productive journals, countries/territories, and authors. Network analysis is also conducted to evaluate the relationship among different countries/territories, authors, and keywords. Research outcomes of this paper present a comprehensive research picture on residential energy consumption and corresponding greenhouse gas emissions (REE) related papers published from 1997 to 2016. The most productive journals, countries/territories, authors are also analyzed based on citation analysis and network analysis. In addition, results also revealed that behavioral analysis, input-output analysis, life cycle assessment, and cost-benefit analysis are the most commonly used methods in this field. Results obtained from this study can provide valuable information for researchers interested in the REE-related field. [ABSTRACT FROM AUTHOR]

In most organizations, especially order-oriented ones meeting deadlines are crucial. Job shop environments could be mentioned as an example where decision makers are try to schedule all jobs in such a way that tardy jobs (TJ) are minimized. Indeed, manufacturers are received customers' orders and required to deliver them no later than the determined due dates. Otherwise, penalties should be paid to customers and it can lead to a huge amount of financial loss. Also, regarding global warming and climate changes manufacturers should redesign their processes from an eco-friendly perspective. Motivated by these issues, in this paper, a green bi-objective model has been formulated to solve the problem of scheduling parallel machines considering TJ and job splitting property (JSP). In the proposed model, the first objective function minimizes the total number of TJ while the second objective function is minimization of total energy consumption. An augmented -constraint method has been deployed for solving small-scale problems. However, to solve large-scale problems, an efficient Simulated Annealing (SA) algorithm has been developed while a Harmony Search (HS) algorithm has also been applied to examine the quality of the proposed SA algorithm. Random generated problems have been used to compare the results of three deployed algorithms. Results approved that the proposed SA algorithm outperforms others significantly. In particular, SA solved the problems sooner than others while its solutions were closer to solutions of the augmented -constraint method. [ABSTRACT FROM AUTHOR]

High-tech protected cropping holds great potential to improve global food security, but high cooling energy costs in warm climates pose difficulties in propagating the industry. Emerging technologies, such as diffuse glasses fitted with photoselective thin films, have interactions with crops and other cooling technologies which are not well-characterized for warm-climate glasshouses. A light-blocking film (LBF) was chosen as a high-tech, climate-controlled greenhouse cover permitting transmission of 85% of photosynthetically-active light and blocking heat-generating radiation. Two consecutive 7-month trials of two capsicum crops were grown under warm climate conditions partially impacted by bushfire smoke, with 2 cultivars (Gina and Û06614) in the first trial, and 2 cultivars (Gina and Kathia) in the second trial. Capsicum fruit yield decreased by 3% in Gina and increased by 3% in O06614 for the first trial, and decreased by 13% in Gina, 26% in Kathia for the second trial. Cooling energy use increased by 11% and 12% for both capsicum crops in AE and SE respectively, with small but insignificant decreases in fertigation demand (2%-5%). Cooling potential was significantly different from material specifications, with indications that convection from LBF interfaces was responsible for higher heat loads. LBF and similar absorptive glasses may still be beneficial for reducing nutrient, water, and energy use in warm climate glasshouses. However, yield is cultivar-dependent and may decrease with below-optimal crop lighting, whereas energy savings are more dependent on LBF orientation and building geometry than outside climate. [ABSTRACT FROM AUTHOR]

Due to the intensification of economic globalization and the impact of global warming, the development of methods to reduce shipping costs and reduce carbon emissions has become crucial. In this study, a multi-objective optimization algorithm was designed to plan the optimal ship route for safe cross-ocean navigation under complex sea conditions. Based on the traditional non-dominated sorting genetic algorithm, considering ship stability and complex marine environment interference, a non-dominated sorting genetic algorithm model considering energy consumption was designed with the energy consumption and navigation time of the ship as the optimization objectives. The experimental results show that although the proposed method is 101.23 nautical miles more than the large ring route, and the voyage is increased by 10.1 h, the fuel consumption is reduced by 92.24 tons, saving 6.94%. Compared with the traditional genetic algorithm, the voyage distance and time are reduced by 216.93 nautical miles and 7.5 h, and the fuel consumption is reduced by 58.82 tons, which is almost 4.54%. Through experimental verification, the proposed model can obtain punctual routes, avoid areas with bad sea conditions, reduce fuel consumption, and is of great significance for improving the safety and economy of ship routes. [ABSTRACT FROM AUTHOR]

Tourism serves as a crucial means of funding national development and ensuring the sustainability of local livelihoods in growing countries such as Brazil. Nevertheless, the accelerated growth of tourism in various nations might lead to significant environmental consequences due to heightened energy consumption. This surge in energy usage contributes to the exacerbation of global warming through the amplified release of carbon dioxide (CO2). In light of the increasingly evident impacts of climate change on the natural environment, a multitude of endeavors have been undertaken with the aim of attaining ecological sustainability. The objective of this study is to examine the dynamic effects of economic growth, energy consumption, and tourism on carbon emissions in Brazil by analyzing time series data spanning from 1990 to 2019. The stationarity of data was assessed through the application of unit root tests, while an autoregressive distributed lag (ARDL) approach was employed to analyze the relationship between the components, accounting for both the long-term and short-term dynamics. The empirical results indicate that a 1% rise in economic growth, energy consumption, and tourist arrivals leads to environmental deterioration by causing a respective increase in CO2 emissions of 1.37%, 1.06%, and 0.57% in the near term, and 0.72%, 0.62%, and 0.16% in the long term. This article presents policy ideas aimed at achieving carbon neutrality in Brazil by increasing the utilization of renewable energy sources, while simultaneously fostering sustainable tourism as a means to enhance the country's economy. Highlights •This study investigated the tourism-economy-energy-environment nexus in Brazil. •The econometric analysis revealed that tourism, energy use, and economic growth increase CO2 emissions. •This article offers policy suggestions to achieve sustainable tourism and carbon neutrality. [ABSTRACT FROM AUTHOR]

In the past ten years, rates of forest fires around the world have increased significantly. Forest fires greatly affect the ecosystem by damaging vegetation. Forest fires are caused by several causes, including both human and natural causes. Human causes lie in intentional and irregular burning operations. Global warming is a major natural cause of forest fires. The early detection of forest fires reduces the rate of their spread to larger areas by speeding up their extinguishing with the help of equipment and materials for early detection. In this research, an early detection system for forest fires is proposed called Forest Defender Fusion. This system achieved high accuracy and long-term monitoring of the site by using the Intermediate Fusion VGG16 model and Enhanced Consumed Energy-Leach protocol (ECP-LEACH). The Intermediate Fusion VGG16 model receives RGB (red, green, blue) and IR (infrared) images from drones to detect forest fires. The Forest Defender Fusion System provides regulation of energy consumption in drones and achieves high detection accuracy so that forest fires are detected early. The detection model was trained on the FLAME 2 dataset and obtained an accuracy of 99.86%, superior to the rest of the models that track the input of RGB and IR images together. A simulation using the Python language to demonstrate the system in real time was performed. [ABSTRACT FROM AUTHOR]