Sustainable Development Goal 13: Climate Action (32389)

This present research examined the association among carbon emissions, financial development, economic growth, natural resources, and energy usage in GCC nations within the environmental Kuznets curve framework by applying the datasets between 1995 and 2019. It used some empirical approaches, including second-generation unit roots and cointegration methods and method of moments quantile regression (MMQR). We detected a cointegrating interconnection between carbon emissions and financial development, energy usage, economic growth, natural resources, and squared of economic growth in the long term. Furthermore, the findings of the MMQR reveal that economic growth, financial development, energy usage, and natural resources degrade the environment, as well as proving the presence of the EKC hypothesis. Moreover, the results also demonstrated that financial development greatly moderates energy usage in order to attain environmental sustainability. Furthermore, the fixed-effect ordinary least squares, fully modified ordinary least squares, and dynamic ordinary least squares were also used in the study as a soundness check of the MMQR approach. The path of causality moves from financial development, economic growth, and squared of economic growth to CO₂ emissions. Lastly, the causality direction runs from carbon emissions to energy usage. Based on these findings, the energy mix of the region must be revised by ensuring the promotion of sustainable energy sources and other energy-efficient technology in order to attain the quality of the environment. Full article

With the increasing influence of climate change, green development has become an important trend. Since manufacturing represents approximately one-half of total energy consumption, reducing the amount of energy consumed within this industry is imperative. This study provides a hybrid flow shop scheduling issue under a time-of-use and ladder electricity price system to reduce total energy consumption without compromising maximum completion time. An improved non-dominated sorting genetic algorithm II with some optimization strategies is proposed to solve the problem. First, an enhanced constructive heuristic algorithm is used to improve the quantity of initial solution in the initialization. Besides, an adaptive genetic operation is introduced, aiming to avoid the emergence of locally optimal solutions. In addition, the right-shift approach is developed to reduce the total energy consumption without affecting completion time. By maintaining the production efficiency and reducing the energy consumption cost by 4.33%. A trade-off proposal is made between productivity and sustainability in view of the calculation results. Full article

The article concerns the assessment of the energy consumption of inland waterway freight transport on river sections in the context of environmental management. The research question was: Does the choice of the route determine the total energy consumption of inland waterway transport and therefore affect the potential of cargo transport of this mode? The article aims to indicate the directions of energy consumption by inland waterway freight transport depending on the route selection, the volume of transport, and the length of the route. The study was carried out on nine sections of the Odra River in Poland during the years 2015–2020. Statistical and econometric techniques were used, i.e., ANOVA, generalized linear models, Eta coefficients, Lasso and Ridge regularization, and X-average control charts (Six Sigma tool). Based on early warning models, river sections were identified that favor the rationalization of energy consumption in terms of the network. The sensitivity of the energy consumption of inland waterway transport to changes in the average distance and in the volume of transport was examined. With the use of Six Sigma tools, the instability of the energy consumption processes of inland waterway transport was identified, paying attention to the source of the mismatch, which was the increase in the average transport distance in the sections, where energy consumption increased due to the operational and navigation conditions of these sections. Full article

Since its birth, nuclear power has been a hot topic of academic research while being subject to much controversy. As a new green energy source with zero greenhouse gas (GHG) emissions, nuclear power plays a vital role in combatting global climate change. Based on global databases and various empirical analysis methods, this study aimed to explore the changes in the global nuclear power product trade (GNT) network and its impact on GHG emissions from 2001 to 2018. The main findings are summarized as follows. (1) Global trade in nuclear power products and GHG emissions showed a non-linear and fluctuating growth during the research period. The geographical pattern of GNT not only has prominent spatial heterogeneity, but it also has some spatial reverse coupled with the spatial distribution of global GHG emissions. (2) The overall regression analysis finds that nuclear power product trade had a significant suppressive effect on global GHG emissions and had the greatest influence among all the selected variables. (3) As for the impact of the GNT network on GHG emissions, nuclear power product trade was better able to curb GHG emissions in countries with the dominate positions compared to those with affiliated positions, which reflects the heterogeneous effect of nuclear power product trade on GHG emissions. These results provide further evidence for the dialectical debate on whether nuclear power products contribute to GHG emissions reductions. This paper also provides corresponding recommendations for policymakers. Full article

Due to the increasing concern about climate change and environmental sustainability, the investigation of energy consumption represents a very intriguing and undeniable subject. This study was directed to investigate energy footprints, greenhouse gas (GHG) emissions and life cycle assessment (LCA) of the main vegetable crops cultivated under open field conditions in southern Egypt. Potato production required the maximum energy amount (112.3 GJ/ha) compared to 76 GJ and 96 GJ for onion and tomato, respectively. Based on energy indices, potato gave (energy ratio > 1; energy productivity > 1; energy profitability > 1; net energy > 0), while onion and tomato production shared the same indicators (energy ratio < 1; energy productivity > 1; energy profitability < 0; net energy < 0). However, GHG emissions generated for producing one ton of potato tubers registered the least amount by 76.0 kg CO₂ eq. The same GHG amount was produced by 834 kg of onion bulbs and 940.6 kg of tomato fruits. The emission rates were more a consequence of diesel, followed by inorganic fertilizer and manure. In addition to carbon emissions, every production process causes several other environmental problems, thus a comprehensive analysis of environmental impact categories is required. The openLCA program performed LCA and ten impact categories were considered to transform the inventory data into several indicators. Producing one ton of potato tubers has the least footprint on the environment and the ecosystem, such as global warming (GW)—238.8 kg CO₂ eq. t⁻¹; human toxicity (HT)—288.3 kg 1,4-DB eq. t⁻¹; fresh water aquatic ecotoxicity (FAEF)—160.44 kg 1,4-DB eq. t⁻¹; marine aquatic ecotoxicity (MAET)—365,636 kg 1,4-DB eq. t⁻¹; and terrestrial ecotoxicity (TE)—1.18 kg 1,4-DB eq. t⁻¹. The analyses indicated that machinery and diesel fuel had the highest impact on all the studied categories. Full article

In recent years, urban communities in China have been continuously affected by extreme weather and emergencies, among which the rainstorm and waterlogging disasters pose a great threat to infrastructure and personnel safety. Chinese governments issue a series of waterlogging prevention and control policies, but the waterlogging prevention and mitigation of urban communities still needs to be optimized. The concept of “resilience” has unique advantages in the field of community disaster management, and building resilient communities can effectively make up for the limitations of the traditional top-down disaster management. Therefore, this paper focuses on the pre-disaster prevention and control of waterlogging in urban communities of China, following the idea of “concept analysis–influencing factor identification–evaluation indicators selection–impact mechanism analysis–resilience simulation prediction–empirical research–disaster adaptation strategy formulation”. The structural equation model and BP neural network are used by investigating the existing anti-waterlogging capitals of the target community to predict the future waterlogging resilience. Based on this simulation prediction model, and combined with the incentive and restraint mechanisms, suggestions on corrective measures can be put forward before the occurrence of waterlogging. Full article

The vulnerability of the rare earth element (REE) supply in a global context of increasing demands entails important economic and political issues, and has encouraged several countries to develop their own REE production projects. This study comparatively evaluated the production of REEs from primary and secondary resources in terms of their sustainability and contribution to the achievement of the Geoethics concept as responsibility towards oneself, colleagues, society, and the Earth system. Twelve categories of potential environmental and social impacts were selected: human health toxicity, global warming or climate change, terrestrial and aquatic eutrophication, acidification potential, particulate matter, resource depletion, water consumption, fresh water ecotoxicity, ionizing radiation, fossil fuel consumption, and ozone depletion. The results showed that the environmental impact of REE production from secondary sources is much lower relative to primary sources. A comparison of conventional and non-conventional REE resources showed that significant impact categories were related to particulate matter formation, abiotic resource depletion, and fossil fuel depletion, which could result from avoiding the tailings disposal before reuse. Based on these findings, governments and stakeholders should be encouraged to increase the recycling of secondary REE sources with Geoethics in mind, in order to balance the high demand of REEs while minimizing the overexploitation of non-renewable resources. Full article

The urbanization process in Peninsular Malaysia has resulted in an increase in temperature. Large cities such as Kuala Lumpur, Johor Bharu, and George Town are experiencing rapid urbanization processes, resulting in unpredictable changes in temperature and weather, which consequently impact community livelihoods. Many believe that the recent flooding in urban residential areas in Peninsular Malaysia has been worsened by climate change. Hence, this paper explores and discusses recent community perceptions of the climate change issue in Peninsular Malaysia. A group of 350 community members from different states in Peninsular Malaysia gave their views and opinions related to climate change via an online quantitative survey questionnaire. Their perception of the urbanization process and its impact on the increase in temperature was descriptively analyzed using the frequency analysis technique and mean score, while their suggestions in verbatim form on reducing the effects of climate change were analyzed thematically. The respondents perceived the climate change issue as attributable to the factors of urbanization, namely the manufacturing industry, population density, and private motor vehicles. Respondents provided suggestions for reducing the effects of climate change, ranging from government policies to community actions. Full article

South African indigenous breeds’ population is decreasing at a time when their genetic material is mandatory due to the rising climate change and global warming. South African indigenous sheep breeds include Namaqua Afrikaner, Zulu, BaPedi, and Damara sheep. These breeds are the most preferred breeds by rural farmers in South Africa due to their adaptability, low feed, and veterinary requirements. However, since they are characterized by small body sizes, farmers tend to crossbreed them with exotic breeds. An early survey conducted in Kwa-Zulu Natal revealed a 7.5% decline in Zulu sheep between 2008–2011. It has recently been observed that the population left is genotypically mixed with exotic genetic material due to uncontrolled breeding techniques that rural farmers apply. Therefore, the aim of this review is to address the present status, difficulties, and conservation approaches applied to save these breeds. However, this review will be limited to the current extinction status as it appears in the Food and Agriculture Organization (FAO) system, data from recent studies, difficulties limiting the conservation success of these breeds, and the current conservation approaches in use to conserve these breeds. Full article

Maize (Zea mays L.) is one of the most consumed grains in the world. Within the context of continuous climate change and the reduced availability of arable land, it is urgent to breed new maize varieties and screen for the desired traits, e.g., high yield and strong stress tolerance. Traditional phenotyping methods relying on manual assessment are time-consuming and prone to human errors. Recently, the application of uncrewed aerial vehicles (UAVs) has gained increasing attention in plant phenotyping due to their efficiency in data collection. Moreover, hyperspectral sensors integrated with UAVs can offer data streams with high spectral and spatial resolutions, which are valuable for estimating plant traits. In this study, we collected UAV hyperspectral imagery over a maize breeding field biweekly across the growing season, resulting in 11 data collections in total. Multiple machine learning models were developed to estimate the grain yield and flowering time of the maize breeding lines using the hyperspectral imagery. The performance of the machine learning models and the efficacy of different hyperspectral features were evaluated. The results showed that the models with the multi-temporal imagery outperformed those with imagery from single data collections, and the ridge regression using the full band reflectance achieved the best estimation accuracies, with the correlation coefficients (r) between the estimates and ground truth of 0.54 for grain yield, 0.91 for days to silking, and 0.92 for days to anthesis. In addition, we assessed the estimation performance with data acquired at different growth stages to identify the good periods for the UAV survey. The best estimation results were achieved using the data collected around the tasseling stage (VT) for the grain yield estimation and around the reproductive stages (R1 or R4) for the flowering time estimation. Our results showed that the robust phenotyping framework proposed in this study has great potential to help breeders efficiently estimate key agronomic traits at early growth stages. Full article

Precipitation elasticity provides a basic estimate of the sensitivity of long-term streamflow to changes in long-term precipitation, and it is especially useful as the first assessment of climate change impact in land and water resource projects. This study estimated and compared the precipitation elasticity (ε_p) of streamflow in 86 catchments within Pakistan over 50 major rivers using three widely used analytical models: bivariate nonparametric (NP) estimator, multivariate NP analysis, and multivariate double logarithm (DL) model. All the three models gave similar values of elasticity in the range of 0.1–3.5 for over 70–75% of the catchments. This signifies that a 1% change in the annual mean precipitation compared to the long-term historic mean annual precipitation will amplify the streamflow by 0.1–3.5%. In addition, the results suggested that elasticity estimation of streamflow sensitivity using the multivariate DL model is more reliable and realistic. Precipitation elasticity of streamflow is observed high at altitudes ranging between 250 m and 1000 m while the longitudinal and latitudinal pattern of ε_p shows higher values in the range of 70–75 and 32–36 decimal degrees, respectively. The ε_p values were found to have a direct relationship with the mean annual precipitation and an inverse relationship with the catchment areas. Likewise, high ε_p values were noticed in areas where the mean annual temperature ranges between 15 and 24 °C. Full article

The management of the global energy resources has stimulated the emergence of various agreements in favor of the environment. Among the most famous are the Conference of Parties (COP) and Route 2030, which aim to limit global warming to 1.5 °C by reducing the energy consumption and global emission levels. In order to comply with the international standards for energy consumption and pollutant emissions, the Brazilian government has been promoting the expansion of biofuels in the national energy matrix. Considering this scenario, the development of a novel internal combustion engine for the exclusive use of ethanol as a fuel, equipped with state-of-the-art technologies and employing modern design concepts, consists of an innovative and promising pathway for future Brazilian mobility, from both environmental and technological outlooks. In this sense, this work presents a method to determine the main engine dimensions as part of the initial process for a new ethanol prototype engine development. The Brazilian biofuel was selected due to its physicochemical properties, which allow the engine to achieve higher loads, and also due to its large availability as a renewable energy source in the country. Furthermore, a port water injection system was fitted to the engine in order to assist the combustion process by mitigating the knock tendency. The predicted overall engine performance was obtained by carrying out a GT-Power^TM 1D-CFD simulation, whose results pointed to a maximum torque of 279 Nm from 2000 to 4000 rpm and an indicated peak power of 135 kW at 5500 rpm. With a maximum water-to-fuel ratio of 19.2%, the engine was able to perform its entire full load curve at the MBT condition, a fact that makes the WI approach along with the ethanol fuel a very attractive solution. As a result of the specific design and optimization of each geometric parameter for this unique ethanol engine, a maximum indicated fuel conversion efficiency of 45.3% was achieved. Moreover, the engine was capable of achieving over 40% of the indicated fuel conversion efficiency in almost its entire full load curve. Full article

Biochar (BC) is often proposed as a tool for climate change mitigation, due to the expected long lifetime in the environment. However, BC’s stability can vary depending on feedstock type and the presence of labile carbon fractions. In this study, we verify the recent methods with new possible tools for biochar stability assessment on six different biochars derived from commonly available Europe biomass sources. Elemental composition (CHNO), dissolved organic carbon (DOC) and water-soluble carbonates content (WSC), volatile organic compounds (VOCs) composition, and mid-infrared spectra (MIR) were performed to estimate the persistence of biochars. Under similar conditions of pyrolysis, biochar properties can vary depending on a feedstock origin. Less aromatic structure and higher contents of labile carbon fractions (DOCs and WSC) in food waste biochars affected the lower stability, while biochars derived from high lignocellulose materials (straw, wood, and grass) were strongly carbonized, with persistent, aromatic structure. Labile carbon pool content (DOC, WSC) and spectral analysis can be useful tools for biochar stability assessment, giving similar information to the standard molar ratio method. Biochars obtained from agriculture and forestry management biomass should be considered as highly stable in soil and are appropriate for long-term carbon sequestration purposes. Full article

Wearable Internet of Things (IoT) devices can be used efficiently for gesture recognition applications. The nature of these applications requires high recognition accuracy with low energy consumption, which is not easy to solve at the same time. In this paper, we design a finger gesture recognition system using a wearable IoT device. The proposed recognition system uses a light-weight multi-layer perceptron (MLP) classifier which can be implemented even on a low-end micro controller unit (MCU), with a 2-axes flex sensor. To achieve high recognition accuracy with low energy consumption, we first design a framework for the finger gesture recognition system including its components, followed by system-level performance and energy models. Then, we analyze system-level accuracy and energy optimization issues, and explore the numerous design choices to finally achieve energy–accuracy aware finger gesture recognition, targeting four commonly used low-end MCUs. Our extensive simulation and measurements using prototypes demonstrate that the proposed design achieves up to 95.5% recognition accuracy with energy consumption under 2.74 mJ per gesture on a low-end embedded wearable IoT device. We also provide the Pareto-optimal designs among a total of 159 design choices to achieve energy–accuracy aware design points under given energy or accuracy constraints. Full article

Carbon tax is an important carbon emission mitigation tool and has been widely recognized as an efficient mechanism for slowing down global warming. The imposition of a carbon tax will, however, inevitably affect income distribution, as a household’s income level influences its priorities regarding consuming the affected goods. This will have important implications for the government, which will have to formulate policies that can achieve efficiency as well as equity. In this study, we apply the input–output price model to estimate the distribution effects of a carbon tax for urban as well as rural areas in China. Our results show that the price increases due to carbon taxes affect rural areas more than urban areas. The Suits index in rural areas is −0.1928, while the value in urban areas is −0.0588. This indicates carbon tax is regressive in all areas, especially the rural ones, and there is a need to formulate suitable policy measures to alleviate a possible widening income gap among income groups and between urban and rural areas. Full article

The formation of algal and cyanobacterial blooms caused by the eutrophication of water bodies is a growing global concern. To examine the impact of extreme weather events on blooms, eutrophication-related parameters (e.g., water temperature, nitrate, ammonium, nitrite, and soluble reactive phosphate (SRP)) were quantitatively assessed monthly over three years (2017–2019) at Lake Seeburg (Central Germany), a shallow eutrophic lake with regular cyanobacterial blooms. In addition, SRP concentrations in sediment pore water were assessed monthly for one year (2018). The monitoring period included a three-day extremely heavy rain event in 2017 as well as a severe drought in summer 2018. No such extreme weather conditions occurred in 2019. After the heavy rain event in 2017, anoxic water containing high levels of ammonium and SRP entered the lake from flooded upstream wetlands. This external nutrient spike resulted in a heavy but short (3 weeks) and monospecific cyanobacterial bloom. A different situation occurred during the exceptionally hot and dry summer of 2018. Especially favored by high water temperatures, SRP concentrations in sediment pore waters gradually increased to extreme levels (34.4 mg/L). This resulted in a strong and sustained internal SRP delivery into the water column (69 mg/m²·d⁻¹), which supported the longest-lasting cyanobacterial bloom (3 months) within the three-year monitoring period. Subsequent biomass decay led to oxygen-depleted conditions in the bottom waters, elevated ammonium, and, later, nitrate concentrations. Our observations demonstrate the particular effects of extreme weather events on nutrient dynamics and the phytoplankton composition in the lake. As the frequency and intensity of such events will likely increase due to climate change, their impacts need to be increasingly considered, e.g., in future remediation strategies. Full article

It is common in the numerical simulations for drying of food to suppose that the food does not experience a change of volume. The few numerical studies that include volume changes assume that the shrinkage occurs symmetrically in all directions. Therefore, this effect has not been fully studied, and it is known that not considering it can be detrimental for the accuracy of these simulations. The present study aims to develop a three-dimensional model for the simulation of fruits that includes the volume changes but also takes into consideration the asymmetry of the shrinkage. Physalis peruviana is taken as the subject of study to conduct experiments and imaging analyses that provided data about the drying kinetics and asymmetric shrinkage mode. The effective diffusion coefficient is found to be between 10⁻¹² m² s⁻¹ and 1.75 × 10⁻⁹ m² s⁻¹. The shrinkage occurs essentially in only one direction, with an average velocity of 8.3 × 10⁻⁵ m/min. A numerical modelling scheme is developed that allows including the shrinkage effect in computer simulations. The performance of the model is evaluated by comparison with experimental data, showing that the proposed model decreases more than 4 times the relative error with respect to simulations that do not include volume changes. The proposed model proves to be a useful method that can contribute to more accurate modeling of drying processes. Full article

The preparation of clean energy is an effective way to solve the global energy crisis and reduce environmental pollution. The decomposition of water can produce hydrogen and oxygen, which is one of the effective ways to prepare clean energy. However, water oxidation is a bottleneck for water decomposition, thus, developing a water oxidation catalyst can accelerate the process of water decomposition to generate clean energy. Nickel-substituted polyoxometalate [Ni₂₅(H₂O)₂(OH)₁₈(CO₃)₂(PO₄)₆(SiW₉O₃₄)₆]⁵⁰⁻ (Ni25) is proven as an excellent water oxidation photocatalyst. To develop the effective photoelectrocatalyst for water oxidation, in this work, we constructed two composite films containing Ni25 on ITO, [PDDA/Ni25]_n, and PDDA/[Ni25/(PDDA–rGO)]_n, by layer-by-layer self-assembly, which is the first combination of nickel-substituted polyoxometalates and reduced graphene oxide (rGO). The study on the photoelectrocatalytic performance of the two films indicates that the water oxidation current of the film PDDA/[Ni25/(PDDA–rGO)]_n-modified electrode is increased by 33.7% after light irradiation, which is 1.71 times that of the film [PDDA/Ni25]_n-modified electrode. Moreover, the transient photocurrent response of the film PDDA/[Ni25/(PDDA–rGO)]_n-modified electrode demonstrates that there is a synergistic effect between rGO and Ni25, and rGO-accelerated electron transport and inhibited charge recombination. In addition, the film PDDA/[Ni25/(PDDA–rGO)]_n-modified electrode exhibits good stability, indicating its great potential as an effective photoelectrocatalyst for water oxidation in practical application. Full article

The transport sector generates a considerable amount of greenhouse gas (GHG) emissions worldwide, especially road transport, which accounts for 95% of the total GHGs. It is commonly known that Electric vehicles (EVs) can significantly reduce GHG emissions. However, with a fossil-fuel-based power generation system, EVs can produce more GHGs and therefore cannot be regarded as purely environmentally friendly. As a result, renewable energy sources (RES) such as photovoltaic (PV) can be integrated into the EV charging infrastructure to improve the sustainability of the transportation system. This paper reviews the state-of-the-art literature on power electronics converter systems, which interface with the utility grid, PV systems, and EVs. Comparisons are made in terms of their topologies, isolation, power and voltage ranges, efficiency, and bi-directional power capability for V2G operation. Specific attention is devoted to bidirectional isolated and non-isolated EV-interfaced converters in non-integrated architectures. A brief description of EV charger types, their power levels, and standards is provided. It is anticipated that the studies and comparisons in this paper would be advantageous as an all-in-one source of information for researchers seeking information related to EV charging infrastructures. Full article

The aerodynamics of an aerofoil with surface heating was numerically studied with the objective to build an effective anti-icing strategy and balance the aerodynamics performance and energy consumption. NACA0012, RAE2822 and ONERA M6 aerofoils were adopted as the test cases and the simulations were performed in the subsonic flight condition of commercial passenger aircraft. In the first session, the numerical scheme was firstly validated with the experimental data. A parametric study with different heating temperatures and heating areas was carried out. The lift and drag coefficients both drop with surface heating, especially at a larger angle of attack. It was found that the separation point on the upper surface of the aerofoil is sensitive to heating. Higher heating temperature or larger heating area pushes the shock wave and hence flow separation point moving towards the leading edge, which reduces the low-pressure region of the upper surface and decreases the lift. In the second session, the conclusions obtained are applied to inform the design of the heating scheme for NACA0012. Further guidelines for different flight conditions were proposed to shed light on the optimisation of the heating strategy. Full article

The cost of silver separation is lowered when ammonia and hydrazine hydrate are replaced with sodium thiosulfate and sodium dithionite in the process of extracting of metallic silver from copper anode slime. The overall environmental impact of two types of copper silver separation processes from anode slime has been analyzed\using the LCA method. Through the subdivision analysis, we found the raw materials or emission items that should be improved first. The following conclusions are drawn: (1) The life cycle environmental impact of the sodium thiosulfate process is much lower than the existing process; (2) The resource and environmental impacts of the sodium thiosulfate method are mainly in the fields of climate change, photochemical smog, and ionizing radiation, exceeding two-thirds of the impact on all of the resources and environment; (3) In terms of input and output items, the main impact of the new process on the resources and the environment is concentrated on the use of sodium hydroxide, accounting for 33.98% of the total equivalent, followed by sodium thiosulfate and sodium carbonate, respectively. These input–output items are the key fields that need attention in future technology improvement. Full article

Despite the unbounded and undeniable advantages of manufacturing, affiliated negative externalities, such as environmental pollution, cannot be overlooked. Our article aims to focus on the current interdependence between the selected economic and environmental aspects in related manufacturing enterprises in Slovakia. We focused on analysing the relationship between carbon monoxide emissions from the largest polluters of the Slovak Republic and relevant sales. The data were taken from 83 enterprises from the Slovak Republic. Environmental and economic data were comprehensive during 2014–2019; therefore, this paper focuses on this period. Among the substantial results, we identified that carbon monoxide production from Slovak production companies was almost unchanged from 2014 to 2019, with only minimal deviations. Based on the results, we created an environmental ratio indicator as an appropriate tool for managers for their decision-making process to achieve the enterprise’s sustainability goals. Full article

A virtual tour of the onshore wind farm near Gaomei Wetland, Taichung City, Taiwan, was produced by producing panoramic images of the site by stitching images captured with a full-frame digital single-lens reflex camera and a multi-row panorama instrument, which automatically and precisely divided each scene into several images. Subsequently, the image stitching quality was improved by calculating the root mean square error (RMSE) of tie point matching and adjusting the tie points. Errors due to eccentricity attributed to the camera’s relative position to the rotational axis of the multi-row panorama instrument were examined and solved; the effect of the overlap rate on image stitching quality was also investigated. According to the study results, the overlap rate between the original images was inversely proportional to the RMSE and directly proportional to the time required for photography and image processing. The stitching quality was improved by resolving eccentricity and by increasing the number of tie points. The RMSEs of the panoramas of all stations were all less than 5 pixels. Subsequently, multimedia materials providing information on wind turbine attributes were combined with the panorama platform to establish a virtual reality tour platform. The content of the platform could be accessed with a smartphone and viewed with a virtual reality device and could promote both tourist attractions and wind energy. Full article

Climate change is one of the most important problems facing society in the 21st century. Despite the uncertainty about the behaviour of rainfall due to climate change, what is clear is that average rainfall has been reduced in the inland areas and headwaters of Spain’s river basins. The Tagus basin is one of the most affected, with implications for the Jucar and Segura basins. The working hypothesis is to corroborate with the data collected on the effects of climate change on the TTS. To this end, the following methodology has been applied: (a) analysis in the headwaters of the Tagus, using data on precipitation, surface runoff and reservoir water; (b) analysis of the resources of the Segura basin (supply and demand), based on the basin organisation’s own data; (c) construction of a water balance adjusted to the Bajo Segura district (Alicante), a user of the water transferred for agricultural use. Likewise, the data provided by the basin organisation have made it possible to corroborate the data on consumption and allocation of the corresponding volumes of water. The results obtained make it possible to put forward a novel proposal in the scientific field related to hydrological planning based on the principles of sustainability. Full article

The random nature of wind energy is an important reason for the low energy utilization rate of wind farms. The use of a compressed air energy storage system (CAES) can help reduce the random characteristics of wind power generation while also increasing the utilization rate of wind energy. However, the unreasonable capacity allocation of the CAES system results in high capital investment and a long payback period. In order to improve the economic benefits of energy storage, this paper studies the capacity configuration of compressed air energy storage systems under the condition of wind energy uncertainty. First, the typical hourly power distribution of wind power generation was obtained using historical data. Factors such as user load demand, time-of-use price of the power grid, system investment cost, power shortage cost, and power sales revenue were considered. Then, a model was built with the charging and discharging power and gas storage capacity of the CAES system as constraints, and the maximum return on investment and the minimum volume of the gas storage tank as targets. NSGA-II and TOPSIS optimal selection methods were used to solve the problem. Finally, the model was used to optimize a power operation case. The results show that in the case of an hourly load power demand of a factory using 3.2 MW, a wind farm would need to keep four wind turbines running every day, and a compressed air energy storage system with a rated power of 1 MW and a rated capacity of 7 MW would ensure the best project benefit. In this mode, 1.24 × 10³ MWh of wind abandoning power could be reduced annually, 2.6 × 10⁴ kg of carbon emissions could be reduced by increasing energy storage within the operation cycle, and the payback period of investment would only be 4.8 years. Full article

Dealing with the environmental and climate risks caused by global warming has become a global consensus. As a sensitive area with particularly fragile ecological environment, the Nordic countries took the lead in making the commitment of “carbon neutrality” by the middle of this century. The green industry will play an important role during this process. Based on the patent data related to the green industry in Nordic countries, this paper studies the evolution characteristics and dynamic changes of influencing factors of patent citation network from 1980 to 2019 by using the social network analysis method and exponential random graph model. The research results show that: Nordic green technologies have gradually changed from passive development to active innovation from the source, and gradually diversified and subdivided in the development process; the connectivity and transitivity of the patent citation network are good and relatively stable in the evolution process; the connections of Nordic countries with non-Nordic countries are strong and gradually spread to distant regions; the awareness of patent property rights protection has gradually increased, and industry and academia are increasingly integrated, which all promote the formation of patent citation relationship. Full article

Canadian high-frequency temperature time series exhibit physical heterogeneity in the coexistence of radiative and advective populations in the total air temperature sample. This work examines forty-five Canadian hourly air temperature records to study seasonal characteristics and variability of radiative and advective population counts and their corresponding temperature biases and trends. The Linear Pattern Discrimination algorithm, conceptualized in a previous study, was adjusted to seasonal analysis on the equinox-to-equinox time scale. Count analysis of radiative and advective days supports the existence of two distinct thermal regimes, Spring–Summer and Fall–Winter. Further, seasonal advective counts for the majority of examined stations typically decrease in numbers. The consistently warmer winter radiative temperature extrema points to the critical role of the advective population in control of the overall temperature magnitude. Canadian northwest warming trends are found to be the highest, indicating the amplifying effect of decreasing advective counts with rapidly increasing temperatures that weaken the advective population’s moderating ability to control the magnitude of the total temperature population. Full article

Combustible carbon-based energy is still prevailing as the world’s leading energy due to its high energy density. However, the oxidation of these hydrocarbons disturbs the natural carbon cycle greatly by increasing greenhouse gases. As emission legislation becomes more rigorous, lean premixed combustion becomes promising because it can reduce nitrogen oxides (NO_x) and Carbon Monoxide (CO) emissions without compromising efficiency. However, utilising lean premixed flames in industrial combustors is not easy because of its thermo-acoustic instabilities associated with pressure fluctuations and the non-linearity in the mean reaction rate. Therefore, reliable predictive combustion models are required to predict emissions with sensible computational costs to use the mode efficiently in designing environmentally friendly combustion systems. Along with the promising methodologies capable of modelling turbulent premixed flames with low computational costs is the ERN-RANS framework. Thus, this study aims to compute a bluff-body stabilised premixed flames close to blow-Off using the ERN-RANS framework. As a result, a satisfactory agreement is reached between the predicted and measured values. Full article

Food systems are both contributing to and affected by environmental degradation and climate change. The transition towards resilient and sustainable food systems is essential to ensure food security and minimise negative environmental impacts. Innovative technologies can accelerate this transition. Blockchain technology (BCT) is attracting attention as it can deliver transparency to complex global food supply chains and has the potential to guide current food production towards better sustainability and efficiency. This case study investigated the opportunities that BCT can offer to food supply chains. Qualitative interviews with eight main BCT providers were conducted to evaluate the current state of BCT and put it into perspective by mapping out advantages, disadvantages, incentives, motives, and expectations connected to its implementation in global food systems. A thematic analysis showed that, while BCT was considered beneficial by all interviewees, uptake is slow due to high implementation costs and the lack of incentives for companies throughout the food chain from farms to food industry and retail. Results further revealed that the advantages of BCT go beyond communication of trustworthy information and development of closer producer–consumer relationships. In fact, it can provide the opportunity to decrease food waste, enhance working conditions throughout the supply chain, and promote sustainable consumption habits. As BCT may be increasingly used in the food supply chain, the results give a basis for future research that may leverage both qualitative and quantitative methods to examine actors’ behaviours. Also, the importance of improving user experiences through functional applications and software to facilitate the adoption of the technology is stressed. Full article

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO₂ levels may be used as efficient predictors of room occupancy accuracy is needed to help designers better utilize the readings and data collected in order to improve interior design, in an effort to better suit users. It also aims to help in energy efficiency and saving in an ever-increasing energy crisis and dangerous levels of climate change. This paper evaluated the accuracy of room occupancy recognition using a dataset with diverse amounts of light, CO₂, and humidity. As classification algorithms, K-nearest neighbors (KNN), hybrid Adam optimizer–artificial neural network–back-propagation network (AO–ANN (BP)), and decision trees (DT) were used. Furthermore, this research is based on machine learning interpretability methodologies. Shapley additive explanations (SHAP) improve interpretability by estimating the significance values for each feature for classifiers applied. The results indicate that the KNN performs better than the DT and AO-ANN (BP) classification models have 99.5%. Though the two classifiers are designed to evaluate variations in interpretations, we must ensure that they have accurate detection. The results show that SHAP provides successful implementation following these metrics, with differences detected amongst classifier models that support the assumption that model complexity plays a significant role when predictability is taken into account. Full article

Energy-saving scheduling has been pointed out as an interesting research issue in the manufacturing field, by which energy consumption can be effectively reduced through production scheduling from the operational management perspective. In recent years, energy-saving scheduling problems in flexible job shops (ESFJSPs) have attracted considerable attention from scholars. However, the majority of existing work on ESFJSPs assumed that the processing of any two consecutive operations in a job cannot be overlapped. In order to be close to real production, the processing overlapping of consecutive operations is allowed in this paper, while the job transportation tasks are also involved between different machines. To formulate the problem, a mathematical model is set up to minimize total energy consumption. Due to the NP-hard nature, a new interior search algorithm (NISA) is elaborately proposed following the feature of the problem. A number of experiments are conducted to verify the effectiveness of the NISA algorithm. The experimental results demonstrate that the NISA provides promising results for the considered problem. In addition, the computational results indicate that the increasing transportation time and sub-lot number will increase the transportation energy consumption, which is largely responsible for the increase in total energy consumption. Full article

Since the Quaternary, the alternate climate of dry and wet, cold and warm, and the emergence of glacial and interglacial periods have led to great changes in the global environment and climate. As an event closely related to cold climate, cryogenic soil has important reference significance for the study of climate change in a certain region and time period. The research on cryogenic soils mainly focuses on the following three aspects: particle size composition, surface morphology and mineral composition. Through the study of the relevant literature, we find that the correlation coefficient of particle size composition before and after freeze-thaw is used to determine the cause of cryogenic weathering. Due to the singleness of judgment conditions, the result is difficult to be convincing; It is difficult to prove the microscopic morphology of the cause of cryogenic weathering from a single mineral of quartz. Therefore, it is necessary to start with more types of primary minerals, and analyze the differences in the particle shape and microscopic surface morphology of different types of primary minerals during the cryogenic weathering process. And on this basis, the typical mineral morphology of the cause of cryogenic weathering is comprehensively judged; Freeze-thaw has little effect on the mineral composition of the soil, but has a greater impact on the size of the mineral particles, and this size change corresponds to the phenomenon of particles silt-fication. The mineral composition also controls the geochemical composition, and the insignificance of the mineral-chemical composition in the process of cryogenic silt-fication increases the difficulty of judging the cause of cryogenic weathering. Full article

Saline soils are a major challenge in agriculture, and salinization is increasing worldwide due to climate change and destructive agricultural practices. Excessive amounts of salt in soils cause imbalances in ion distribution, physiological dehydration, and oxidative stress in plants. Breeding and genetic engineering methods to improve plant salt tolerance and the better use of saline soils are being explored; however, these approaches can take decades to accomplish. A shorter-term approach to improve plant salt tolerance is to be inoculated with bacteria with high salt tolerance or adjusting the balance of bacteria in the rhizosphere, including endosymbiotic bacteria (living in roots or forming a symbiont) and exosymbiotic bacteria (living on roots). Rhizosphere bacteria promote plant growth and alleviate salt stress by providing minerals (such as nitrogen, phosphate, and potassium) and hormones (including auxin, cytokinin, and abscisic acid) or by reducing ethylene production. Plant growth-promoting rhizosphere bacteria are a promising tool to restore agricultural lands and improve plant growth in saline soils. In this review, we summarize the mechanisms of plant growth-promoting bacteria under salt stress and their applications for improving plant salt tolerance to provide a theoretical basis for further use in agricultural systems. Full article

Sustainable development is a major issue confronting society today. Cement, a major constituent of concrete, is a key component of any infrastructure development. The major drawback of cement production is that it involves the emission of CO₂, the predominant greenhouse gas causing global warming. The development of geopolymers has resulted in a decrease in cement production, as well as a reduction in CO₂ emissions. During mass concrete production in the construction of very large structures, interfaces/joints are formed, which are potential failure sites of crack formation. Concrete may interface with other concrete of different strengths, or other construction materials, such as steel. To ensure the monolithic behavior of composite concrete structures, bond strength at the interface should be established. The monolithic behavior can be ensured by the usage of shear ties across the interface. However, an increase in the number of shear ties at the interface may reduce the construction efficiency. The present study aims to determine the interfacial shear strength of geopolymer concrete as a substrate, and high-strength concrete as an overlay, by adding 0.50%, 0.75%, and 1% crimped steel fibers, and two and three shear ties, at the interface of push-off specimens. It was found that three shear ties at the interface can be replaced by two shear ties and 0.75% crimped steel fibers. In addition, a method was proposed to predict the interface shear strength of the concrete composite, which was found to be comparable to the test results. Full article

Spatial and temporal variations in the potential yields of highland barley is important for making policies on adaptation of agriculture to climate change in the Three Rivers Region (TRR), one of the main highland barley growing areas on the Tibetan Plateau. This research tries to explore a suitable strategy for simulating potential yields of highland barley by the WOFOST (WOrld FOod STudies) crop growth model, and further to identify variations in climate conditions and potential yields in TRR from 1961 to 2020 for making policies on adaptation of agricultural production to the climate change impacts on the Tibetan Plateau. Validation results indicated that WOFOST could accurately simulate the potential yields of highland barley with the global radiation estimated by the calibrated Angstrom model. The global radiation during the growth periods decreased at a rate of 0.047 MJ/m²a, while the temperature during the growth periods increased at rates ranging from 0.019 to 0.087 °C/a, which was greater than the average warming rate of the globe. The simulated potential yields ranged from 10,300 to 14,185 kg/ha in TRR, with an average decreasing rate of 28 kg/ha/a. The decrease in the potential yields was mainly attributed to the shortened critical period caused by warming effects, so cultivation of new varieties of highland barley with longer growth periods is suggested as an achievable strategy for the adaptation of highland barley to climate change in TRR. Full article

This paper presents the concept of an expert system supporting the decision-making process of rational energy consumption by an electric car. The driving style and the average speed achieved are very important in terms of the driving range. In addition, the influence of ambient temperature on the efficiency of the electric vehicle and ultimately on energy consumption is very important. The proposed system, based on the method of multi-valued logic trees, allows minimizing the objective function, which is aimed at minimizing the energy consumption of an electric car at different ambient temperatures. The generated decisions, directed to the energy management system, can be processed in a variety of temporal and situational dimensions. The application of the system can also provide prompts to the driver on how to adjust the driving style by operating the accelerator and brake pedal. The expert system is an open system, allowing for further generalizations and modifications. Full article

Sea-surface petroleum pollution is observed as “oil slicks” (i.e., “oil spills” or “oil seeps”) and can be confused with “look-alike slicks” (i.e., environmental phenomena, such as low-wind speed, upwelling conditions, chlorophyll, etc.) in synthetic aperture radar (SAR) measurements, the most proficient satellite sensor to detect mineral oil on the sea surface. Even though machine learning (ML) has become widely used to classify remotely-sensed petroleum signatures, few papers have been published comparing various ML methods to distinguish spills from look-alikes. Our research fills this gap by comparing and evaluating six traditional techniques: simple (naive Bayes (NB), K-nearest neighbor (KNN), decision trees (DT)) and advanced (random forest (RF), support vector machine (SVM), artificial neural network (ANN)) applied to different combinations of satellite-retrieved attributes. 36 ML algorithms were used to discriminate “ocean-slick signatures” (spills versus look-alikes) with ten-times repeated random subsampling cross validation (70-30 train-test partition). Our results found that the best algorithm (ANN: 90%) was >20% more effective than the least accurate one (DT: ~68%). Our empirical ML observations contribute to both scientific ocean remote-sensing research and to oil and gas industry activities, in that: (i) most techniques were superior when morphological information and Meteorological and Oceanographic (MetOc) parameters were included together, and less accurate when these variables were used separately; (ii) the algorithms with the better performance used more variables (without feature selection), while lower accuracy algorithms were those that used fewer variables (with feature selection); (iii) we created algorithms more effective than those of benchmark-past studies that used linear discriminant analysis (LDA: ~85%) on the same dataset; and (iv) accurate algorithms can assist in finding new offshore fossil fuel discoveries (i.e., misclassification reduction). Full article

Accurate prediction of air-conditioning energy consumption in buildings is of great help in reducing building energy consumption. Nowadays, most research efforts on predictive models are based on large samples, while short-term prediction with one-month or less-than-one-month training sets receives less attention due to data uncertainty and unavailability for application in practice. This paper takes a government office building in Ningbo as a case study. The hourly HVAC system energy consumption is obtained through the Ningbo Building Energy Consumption Monitoring Platform, and the meteorological data are obtained from the meteorological station of Ningbo city. This study utilizes a Gaussian process regression with the help of a 12 × 12 grid search and prediction processing to predict short-term hourly building HVAC system energy consumption by using meteorological variables and short-term building HVAC energy consumption data. The accuracy R² of the optimal Gaussian process regression model obtained is 0.9917 and 0.9863, and the CV-RMSE is 0.1035 and 0.1278, respectively, for model testing and short-term HVAC system energy consumption prediction. For short-term HVAC system energy consumption, the NMBE is 0.0575, which is more accurate than the standard of ASHRAE, indicating that it can be applied in practical energy predictions. Full article

Xinjiang, an arid region of China, has experienced a substantial warming–wetting trend over the past five decades. However, climate change has affected vegetation growth/greening in arid Central Asia in unexpected ways due to complex ecological effects. We found a significant greening trend (consistent increase in the normalized difference vegetation index or NDVI) from 1982 to 1996, during the growing season; however, the NDVI consequently decreased and plateaued from 1997 to 2015, especially in naturally vegetated regions. Atmospheric vapor pressure deficit (VPD) is a critical driver of vegetation growth, is a direct measure of atmospheric aridity, and has increased sharply in recent decades. A partial correlation analysis indicated a significant relationship between growing season NDVI and VPD from 1997 to 2015. This implies that decreased VPD corresponds to increasing NDVI, and increasing VPD corresponds to a decrease and plateauing in the NDVI trend. Using the partial derivative equation method, our results suggest that the trend in growing season NDVI was affected primarily by increasing VPD (contributing 87.57%) from 1997 to 2015, especially in the grassland and desert biomes. Rising temperatures lead to a greater VPD, resulting in exacerbated evaporative water loss. Soil drought and atmospheric aridity limit plant stomatal conductance and could effectively lead to a decrease in the greening trend and increased vegetation mortality in arid Xinjiang. Our results emphasize the importance of VPD as a limiting factor of greening trends in arid regions. The influence of VPD on vegetation growth should be considered when evaluating arid ecosystem functioning under global warming. Full article

Landslide is a devastating natural disaster, causing loss of life and property. It is likely to occur more frequently due to increasing urbanization, deforestation, and climate change. Landslide susceptibility mapping is vital to safeguard life and property. This article surveys machine learning (ML) models used for landslide susceptibility mapping to understand the current trend by analyzing published articles based on the ML models, landslide causative factors (LCFs), study location, datasets, evaluation methods, and model performance. Existing literature considered in this comprehensive survey is systematically selected using the ROSES protocol. The trend indicates a growing interest in the field. The choice of LCFs depends on data availability and case study location; China is the most studied location, and area under the receiver operating characteristic curve (AUC) is considered the best evaluation metric. Many ML models have achieved an AUC value > 0.90, indicating high reliability of the susceptibility map generated. This paper also discusses the recently developed hybrid, ensemble, and deep learning (DL) models in landslide susceptibility mapping. Generally, hybrid, ensemble, and DL models outperform conventional ML models. Based on the survey, a few recommendations and future works which may help the new researchers in the field are also presented. Full article

Climate change is now evident on a global scale. In some regions, the phenomenon is especially amplified, generating different consequences for man and the environment. Sicily is one of the Mediterranean regions, the biggest in terms of area, where climatic variations produce significant effects. In this study, temperature trends on monthly time scales are examined in the time frame 1925–2015. The cluster analysis technique (Ward’s method) was used to homogenize the temperature series. The results show four statistically significant clusters, confirming the presence of climatic variability in the region. The non-parametric Mann–Kendall test was used to determine temperature trends. The non-parametric estimator Sen’s slope was used to quantify the variation of trends. The results showed the presence of statistically significant trends. A worrying and unexpected increase in temperatures was found during the winter period. This scenario was presented in three clusters, highlighting a mutation in the winter season, attributable to the climatic changes in progress rather than to territorial factors. If the trends maintain an increasing monotone character, in the coming decades there will be, in many areas of Sicily, a constant loss of fertile soil for the agricultural sector and the advancement of phenomena such as drought and desertification, to which the island is already predisposed. All of this will have serious socio-economic repercussions. Considering that a large part of the region’s economy is based on the agricultural sector, these repercussions will be followed by serious environmental implications that will negatively affect the ecological sustainability of the region. Full article

Large and complex ring forgings are key structural parts of the aerospace field, and their quality is closely related to the reliability of aerospace vehicles. However, high-quality production of aerospace ring forgings faces many problems, such as the long process design cycle and impoverished consistency, the difficulties of real-time detection under the severe time-varying state of the deformation process, the complexity of high-quality non-destructive testing under multitudinous defects, and the cumbersome management control of the multi-source and multi-dimensional heterogeneous data. Considering the current situation of multi-variety and multi-batch production for aerospace ring forgings, establishing an intelligent production line is a crucial means to solving the above problems and realizing the standardization and premiumization of key aerospace components. Therefore, management control and integration technology of the intelligent production line play a crucial role. An analysis, including the research progress of the intelligent computer-aided process planning (CAPP) system, the real-time detection and control system, the product quality testing system, and the intelligent management control and integration system, is systematically reviewed in this work. Through intelligently managing and controlling the integrated systems of the production line, the production efficiency of ring forgings can be effectively improved, and the production energy consumption can be remarkably reduced, which is of great significance for enhancing the manufacturing technology level of aerospace products. Full article

As the most important driving force for ensuring the effective supply of grain in the country, the production stability of the major grain-producing areas directly concerns the national security of China. In this paper, considering the “water–soil–energy–carbon” correlation, water, soil and energy resource factors, and carbon emission constraints were included in an index system, and the global common frontier boundary three-stage super-efficient EBM–GML model was used to measure the grain production resource utilization efficiency of the major grain-producing areas in China from 2000 to 2019. This paper also analyzed the static and dynamic spatiotemporal characteristics and the restrictions of utilization efficiency. The results showed that, under the measurement of the traditional data envelopment analysis model, the grain production resource utilization efficiency in the major producing areas is relatively high, but there is still room to improve by more than 20%, and grain production still has enormous growth potential. After excluding external environmental and random factors, it was found that the utilization efficiency of grain production resources in the major producing areas decreased, and the efficiency and ranking of provinces changed significantly. External factors inhibit pure technical efficiency and expand the scale efficiency. The utilization efficiency of Northeast China was much higher than that of the Huang-Huai-Hai region and the middle and upper reaches of the Yangtze River region, and its grain production resource allocation management had obvious advantages. The total factor productivity index of food production resources showed an upward trend as a whole, and its change was affected by both technological efficiency and technological progress, of which technological progress had the greater impact. Therefore, reducing the differences in the external environment of different regions while making adjustments in accordance with their own potential is an effective way to further improve the utilization efficiency of food production resources. Full article

With the current transitioning and increasing complexity of power systems owing to the continuous integration of distributed generators (DGs) and Flexible AC Transmission Systems (FACTS), power system quality and security studies have extended to incorporate the impacts of these technologies. This paper presents a review of the operation and reliability impacts of FACTS technologies in improving power quality and security in modern Cyber-Physical Power Systems (CPPS). While introducing DG to the power system helps to decentralize the network for easy accessibility and enhances clean energy system, it creates new challenges such as harmonics, voltage instability, and frequency distortion. These challenges can be tackled with FACTS devices which are flexible and dynamic smart electronic controllers used to stabilize power system parameters to improve power quality and reliability. This paper examines the current state-of-the-art optimization techniques and artificial intelligence and/or computational techniques for optimal placement and operation of FACTS devices. This review highlights the generational advancement of FACTS technologies and the different objectives of optimal placement and operation of these devices. Moreover, the concept of CPPS is discussed with the potential utilization of distribution-FACTS (D-FACTS) devices for network security. Furthermore, a bibliometric analysis was carried out to show research trend of FACTS utilization. The result presents future trajectories for power utility industries and researchers interested in power system optimization and the application of FACTS technologies in smart power system networks. Some of the significant findings leads to proposed demand-side management for placement of DGs and FACTS technologies as a more strategic optimal system sizing to minimize cost. It was also concluded that future design of FACTS/D-FACTS devices must consider and appreciate interactions with the automated systems of CPPS to enhance effective integration. To this end, design modification of the operational configuration of these devices with sensors for real-time synchronized control and interaction with other CPPS technologies is an area that requires more research attention in the future. Full article

The building sector represents approximately 40% of the global energy consumption, of which 18 to 73% is represented by heating and ventilation. One focus of research for reducing energy consumption is to study the interaction between the heating system, the occupant’s behaviour, and the building’s thermal mass. For this purpose, a new experimental facility was developed. It consists of a real accommodation in which the thermal performance of the envelope, the heating system, the room’s layout, the weather conditions, and the occupant’s activity are variable parameters. A simulation model of the experimental facility, built in TRNSYS, was used to characterise the experimental facility. This article details the development of the experimental facility and then compares results for two different types of building inertia (low and high thermal masses). Results show the accuracy of the thermal inertia reproduction in the experimental facility and highlight the possibilities of improvements in the interaction between heating systems and building envelope efficiency. Full article

Ventilation plays a key role in underground mining. It is essential due to the natural hazards and technological processes that come with the nature of mining. However, it is highly energy consuming and generates significant operating expenditures. Fan station parameters are selected based on the needs of a particular mine but mainly consider the requirements for the period of developed mining activities. When the period of mine decommissioning begins, the parameters of the main fan station often exceed its needs. In Poland, many mines have been closed in recent years. However, sometimes, due to the necessity of pumping underground water, it cannot be done thoroughly. In such a situation, it usually turns out that the parameters of the existing fan station significantly exceed the mine’s needs. The main fan stations are devoid of control systems, and even if they have them, they do not allow for a significant reduction of their volume flow rate. Modernising of the station to meet new requirements of the mine is expensive and time consuming. Solving the presented problem is possible by developing a fan station to replace main fans that are too big. The idea is easy to implement and consists of connecting it to an existing upcast shaft or downcast shaft, which will then be changed to upcast. The solution presented in the article has been implemented in two Polish coal mines and is in progress in a third mine. The examples presented in the article clearly show the energy benefits of replacing main fans that are too large. Full article

The tobacco industry is an important contributor to realizing the carbon reduction goal. Less attention is paid to the carbon emissions of the tobacco industry. The tobacco production system is generally a carbon sink, where carbon sequestration by photosynthesis in tobacco planting and by soil are sufficient to offset the carbon emissions of the tobacco production system. This work proposed an integrated framework of life-cycle assessment (LCA) and Source-Sink Model to determine the optimal allocation of carbon sources to sinks with the objective of maximizing the profitable external benefits. From an economic perspective, internal carbon sources could be offset by the internal carbon sink of the tobacco production system. The additional internal carbon sinks can be transferred in the form of carbon trading, increasing external revenue. A case-study tobacco manufacturing plant in Sichuan, China, was chosen to demonstrate the feasibility of the proposed work. This study assesses the carbon footprint and economic benefits of a tobacco industry supply chain case (from tobacco cultivation to finished product) and analyzes the energy restructuring of different percentages of renewable energy to replace thermal power. The objective of the study is to maximise the offsetting of carbon emissions from the tobacco production system, while achieving optimal internal costs and profitable external benefits. Full article