Do the effects of aggregate and disaggregate energy consumption on different environmental quality indicators change in the transition to sustainable development? Evidence from wavelet coherence analysis

In the 2030 Agenda for Sustainable Development, adopted by the United Nations (UN) member states in 2015, half of the target period has been exceeded. However, China, whose energy consumption relies heavily on fossil resources, remains at the top of the list of global polluters. Therefore, investigating the environmental impacts of energy types is essential to China's path towards Sustainable Development Goals (SDG)-7 and SDG-13. Based on this motivation, the paper offers new insights into the energy-environment literature for China with wavelet coherence analysis (WCA). This approach can investigate the relationship between variables in a periodic manner based on the frequency behavior of the models. The paper separately analyzes the effects of primary energy consumption (PEC), fossil energy consumption (FEC), renewable energy consumption (REC), nuclear energy consumption (NEC), GDP, and population (POP) on three different environmental indicators in China. Using two environmental pollution indicators (carbon emission (CO2) and ecological footprint (EF)) and one environmental quality indicator (load capacity factor (LCF)), the paper allows for comparison and robustness checks on the environmental impacts of energy indicators. Empirical findings reveal the following: (i) Except for REC and POP in the CO2 model, the variables in all three models largely move together during the period under observation; (ii) variables other than POP have consistent coefficient signs; (iii) PEC, FEC, NEC, and GDP increase CO2 and EF while decreasing LCF; (iv) the effect of NEC on LCF is more obvious until 2000; (v) unlike the others, REC affects CO2 and EF negatively and LCF positively; (vi) there is bidirectional causality between PEC and environmental indicators but not for REC; (vii) the causality relations of other variables with environmental indicators differ in terms of model, time, and direction of causality. In light of the findings, the paper highlights that only the REC improves environmental quality in China. Other energy indicators contribute to environmental degradation. China, whose ecological deficit has increased dramatically in recent years, urgently needs to reduce its dependence on fossil energy sources by accelerating investments in REC. Governments should also review nuclear energy policies, which are expected to help achieve carbon neutrality.

Enhanced thyroxine removal from micro-polluted drinking water resources in a bio-electrochemical reactor amended with TiO2@GAC particles: Efficiency, mechanism and energy consumption

A three-dimensional bioelectrochemical system (3D-BES) with both electrocatalytic and biodegradation functions was designed and developed to enhance iodine-containing hormone removal from micro-polluted oligotrophic drinking water sources and to reduce energy consumption. Thyroxine (T4) removal efficiency was 99.0% in the 3D-BES amendment with TiO2@GAC as the particle electrodes, which was 20.5% higher than the total efficiency of single biodegradation (28.7%) plus electrochemical decomposition (49.8%). The high T4 removal efficiency was a result of biochemical synergistic degradation, enhancement of electron transfer and utilization, enrichment of functional microorganisms, and the expression of dehalogenation functional genes. The electron transfer was increased by 1.63 times in 3D-BES compared to the 2D-BES, which contributed to: (i) ∼17.8% enhancement of dehalogenation, (ii) 2.35 times enhancement of the attenuation rate, and (iii) 60% reduction in energy consumption. Moreover, the aggregation of microorganisms and the hydrophobic T4 onto TiO2@GAC shortened the transfer distance of matter and energy, which induced the degradation steps to be shortened and the toxic decay to be accelerated from T4 and its metabolites. These comprehensive functions also enhanced the 31.8% ATPase activity, 7.3% abundance of the functional reductive dehalogenation genera, and 52.3% dehalogenation genes expression for Pseudomonas, Ancylobacter, and Dehalogenimonas, which contributed to an increase in T4 removal. This work provides an environmental-friendly biochemical synergistic method for the detoxification of T4 polluted water.

Photo-electrochemical oxidation flow system for stormwater herbicides removal: Operational conditions and energy consumption analysis

Photoelectrochemical oxidation (PECO) is a promising advanced technology for treating micropollutants in stormwater. However, it is important to understand its operation prior to practical validation. In this study, we introduced a flow PECO system designed to evaluate its potential for full-scale applications in herbicides degradation, providing valuable insights for future large-scale implementations. The PECO flow reactor demonstrated the ability to treat a larger volume of stormwater (675 mL, approximately 10 times more than previous batch experiments) with effective removal rates of 92 % for diuron and 22 % for atrazine over 6 h of operation at 2 V. To address the large volume issue in stormwater treatment, a multiple module parallel application design is being considered to increase the treatment capacity of the PECO flow reactor. During the flow reactor operations, flow rate was found to have a notable impact on removal performance, particularly for diuron. At a flow rate of 610 mL min-1, approximately 90 % removal of diuron was achieved, while at 29 mL min-1, the removal efficiency decreased to 60 %. While light intensity had minimal effect on diuron degradation (all settings achieved over 90 % removal), it enhanced atrazine degradation from 9 % to 31 % with an increase in intensity from 63 mW cm-2 to 144 mW cm-2. Remarkably, the PECO flow system exhibited excellent removal performance (>90 % removal) for diuron even at extremely high initial pollutant concentrations (240 μg L-1), demonstrating its capacity to handle varying contaminant loads in stormwater. Energy consumption analysis revealed that flow rate as the primary factor influenced the specific energy consumption rate. Higher flow rate (e.g., 610 mL min-1) were preferable in flow reactor due to its well-balanced performance between removal and energy consumption. These findings confirm that the PECO flow system offers an efficient and promising approach for stormwater treatment applications.

Numerical simulation of slug flow in pipelines using drift flux constitutive equations for gas-viscous oil two-phase flow

Transient simulation of multiphase flow in pipes has been performed using Two-Fluid Model and Drift-Flux Model. The main advantage of the Drift-Flux Model is the reduced number of differential equations, which results in a lower computational time. However, the accuracy of the model depends on a suitable constitutive equation for the velocity of the dispersed phase, commonly, the gas phase. The gas velocity constitutive equation includes two important parameters, namely, the distribution coefficient and the void-fraction-weighted drift velocity. A drift-flux-model code was developed, by using the Finite Volume Method (FVM) with staggered grid system, to evaluate the effect of highly viscous liquid and pipe geometry (pipe diameter and pipe inclination) in the prediction of liquid hold-up and pressure drop gradient. The gas phase compressibility was also included in the model. The results show that the energy consumption to pump the fluids through the lift system has been overestimated when highly viscous liquids are produced. For the case of a vertical upward flow, the overestimation can be up to 10 % of energy consumption. We strongly recommend incorporating the effects of pipe inclination and liquid viscosity into the estimation of the Distribution Coefficient of the dispersed phase, encompassing both C 0 and gas drift velocity.

Neural energy computations based on Hodgkin-Huxley models bridge abnormal neuronal activities and energy consumption patterns of major depressive disorder

Limited by the current experimental techniques and neurodynamical models, the dysregulation mechanisms of decision-making related neural circuits in major depressive disorder (MDD) are still not clear. In this paper, we proposed a neural coding methodology using energy to further investigate it, which has been proven to strongly complement the neurodynamical methodology. We augmented the previous neural energy calculation method, and applied it to our VTA-NAc-mPFC neurodynamical H-H models. We particularly focused on the peak power and energy consumption of abnormal ion channel (ionic) currents under different concentrations of dopamine input, and investigated the abnormal energy consumption patterns for the MDD group. The results revealed that the energy consumption of medium spiny neurons (MSNs) in the NAc region were lower in the MDD group than that of the normal control group despite having the same firing frequencies, peak action potentials, and average membrane potentials in both groups. Dopamine concentration was also positively correlated with the energy consumption of the pyramidal neurons, but the patterns of different interneuron types were distinct. Additionally, the ratio of mPFC's energy consumption to total energy consumption of the whole network in MDD group was lower than that in normal control group, revealing that the mPFC region in MDD group encoded less neural information, which matched the energy consumption patterns of BOLD-fMRI results. It was also in line with the behavioral characteristics that MDD patients demonstrated in the form of reward insensitivity during decision-making tasks. In conclusion, the model in this paper was the first neural network energy computational model for MDD, which showed success in explaining its dynamical mechanisms with an energy consumption perspective. To build on this, we demonstrated that energy consumption levels can be used as a potential indicator for MDD, which also showed a promising pipeline to use an energy methodology for studying other neuropsychiatric disorders.

Introducing new green machining technology to enhance process performance and reduce environmental pollution in the metal processing industry

The pursuit of enhanced cooling and lubrication methods for machining processes that are energy-efficient, environmentally friendly, and cost-effective is receiving significant attention from both academia and industry. The reduction of CO2 emissions is closely tied to electrical and embodied energy consumption. This study introduces a novel LN2 oil-on-water (LNOoW) cooling/lubrication (lubricooling) approach for the machining of Ti-6Al-4V alloy. Machinability aspects, energy-related aspects, environmental-related aspects, and economic aspects are measured and compared. More specifically, surface quality, electrical energy, cutting forces, and tool wear were measured in machinability aspects. Similarly, specific total energy and specific cumulative Energy Demand (S_CED), specific carbon emission, and production costs were measured to investigate the energy and environmental and economic aspects, respectively. The LNOoW provided the best machinability results compared with other approaches. Result found that LNOoW produced 37.5% better surface quality, removed 159.17% more material, and reduced 50.56% specific cutting energy and 53.63% specific costs as compared to traditional dry cutting conditions. The 39% increment in specific carbon emissions observed in the LN2 oil-on-water (LNOoW) approach in comparison to the dry-cutting method can be mitigated through the implementation of sustainable practices in the production of liquid nitrogen (LN2). The information provided in this study serves as a valuable resource for the development of environmentally friendly machining processes. The study also helps get the sustainable development goals (SDGs) of the United Nations.

Financial development, energy consumption, and economic growth in the ASEAN countries: evidence from the PVAR approach

The Association of Southeast Asian Nations (ASEAN), a new global economic force, has struggled to achieve a dual objective of enhanced economic growth and improved environmental quality. Financial development is generally considered an important tool in achieving these simultaneous objectives. This paper examines the response mechanism and the inter-relationship between the ASEAN region's financial development, energy consumption, and economic growth. Unlike previous studies, the paper uses a generalized method of moments panel vector autoregression (GMM-panel VAR) framework for the 1981-2021 period. The second-generation Granger causality test is used to identify their causality relationship. Economic growth supports financial development and reduces energy consumption from fossil fuel sources in the ASEAN countries. Financial development also reduces fossil fuel energy consumption. The bi-directional relationship between economic growth and fossil fuel energy consumption exists. Energy consumption and financial development are also bi-directionally linked. However, only the unidirectional Granger causality from economic growth to financial development is found. The variance decomposition analysis results confirm that economic growth accounts for the most significant variance in fossil fuel energy consumption and financial development in the ASEAN countries. Policy implications have emerged based on these findings.

The Impact of Modern Imaging Techniques on Carbon Footprints: Relevance and Outlook

It is estimated that the health care sector accounts for 4.0-8.5% of total global CO2 emissions, with medical imaging representing an energy-intensive contributor. We outline the carbon footprint of the imaging modalities most relevant to urology and list practical recommendations that can have a positive impact on sustainability. PATIENT SUMMARY: Energy use for medical imaging scans is a significant contributor to carbon emissions by the health care sector. Steps to improve sustainability can include choosing the least energy-intensive option among the scan types suitable for each patient and condition, and switching off equipment when it is not in use.

An improved energy-efficient cloud-optimized load-balancing for IoT frameworks

As wireless communication grows, so does the need for smart, simple, affordable solutions. The need prompted academics to develop appropriate network solutions ranging from wireless sensor networks (WSNs) to the Internet of Things (IoT). With the innovations of researchers, the necessity for enhancements in existing researchers has increased. Initially, network protocols were the focus of study and development. Regardless, IoT devices are already being employed in different industries and collecting massive amounts of data through complicated applications. This necessitates IoT load-balancing research. Several studies tried to address the communication overheads produced by significant IoT network traffic. These studies intended to control network loads by evenly spreading them across IoT nodes. Eventually, the practitioners decided to migrate the IoT node data and the apps processing it to the cloud. So, the difficulty is to design a cloud-based load balancer algorithm that meets the criteria of IoT network protocols. Defined as a unique method for controlling loads on cloud-integrated IoT networks. The suggested method analyses actual and virtual host machine needs in cloud computing environments. The purpose of the proposed model is to design a load balancer that improves network response time while reducing energy consumption. The proposed load balancer algorithm may be easily integrated with peer-existing IoT frameworks. Handling the load for cloud-based IoT architectures with the above-described methods. Significantly boosts response time for the IoT network by 60 %. The proposed scheme has less energy consumption (31 %), less execution time (24\%), decreased node shutdown time (45 %), and less infrastructure cost (48\%) in comparison to existing frameworks. Based on the simulation results, it is concluded that the proposed framework offers an improved solution for IoT-based cloud load-balancing issues.

Energy consumption and innovation-environmental degradation nexus in BRICS countries: new evidence from NARDL approach using carbon dioxide and nitrous oxide emissions

The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators-such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)-and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies.

Layered energy-saving speed planning and control method for electric vehicle on continuous signal lights road

Emergency start-stop in front of signal lights is one of the main reasons for additional energy consumption and ride discomfort of Electric Vehicle (EV). Existing research on this issue rarely takes into account both energy consumption and ride comfort. Therefore, the layered energy-saving speed planning and control method is proposed. The upper is the layer of energy-saving speed planning. This layer reduces energy consumption of EV by reducing the number of stops on continuous signal lights road and minimizing the range of speed change. On this basis, the sinusoidal variable speed curve is used to smooth the acceleration process to improve ride comfort. Finally, the energy-saving speed considering ride comfort is obtained. This layer makes up for the issue that existing research rarely takes into account both energy consumption and ride comfort of EV, and is an extension and innovation of existing research. The lower is the layer of Model Predictive Controller (MPC)-based speed control. Based on the longitudinal dynamics model of EV, the MPC-based speed controller is established to control EV to track the energy-saving speed. The controller is easy to understand and implement, and it is also suitable for other research on EV, which has certain application value. The simulation results show that under various working conditions, the maximum energy consumption of EV passing through continuous signal lights road without stopping is 604.29 kJ/km, and the minimum is 244.76 kJ/km. The energy consumption is lower than that of actual road test, and it can be saved by 23.18 % compared with the method in the same field. The maximum Root Mean Square of accelerations (R M S a ) is 0.25 m/s2, and the minimum is 0.10 m/s2. The values of R M S a above are lower than 0.315 m/s2, which indicates that the ride comfort is good. The utilized method can reduce energy consumption of EV, improve its range and ride comfort, which has important reference significance for promoting the development of EV.

Towards low energy-carbon footprint: Current versus potential P recovery paths in domestic wastewater treatment plants

With the unprecedented exhaustion of natural phosphorus (P) resource and the high eutrophication potential of the associated-P discharge, P recovery from the domestic wastewater is a promising way and has been putting on agenda of wastewater industry. To address the concern of P resource recovery in an environmentally sustainable way is indispensable especially in the carbon neutrality-oriented wastewater treatment plants (WWTPs). Therefore, this review aims to offer a critical view and a holistic analysis of different P removal/recovery process in current WWTPs and more P reclaim options with the focus on the energy consumption and greenhouse gas (GHG) emission. Unlike P mostly flowing out in the planned/semi-planned P removal/recovery process in current WWTPs, P could be maximumly sequestered via the A-2B- centered process, direct reuse of P-bearing permeate from anaerobic membrane bioreactor, nano-adsorption combined with anaerobic membrane and electrochemical P recovery process. The A-2B- centered process, in which the anaerobic fixed bed reactor was designated for COD capture for energy efficiency while P was enriched and recovered with further P crystallization treating, exhibited the lowest specific energy consumption and GHG emission on the basis of P mass recovered. P resource management in WWTPs tends to incorporate issues related to environmental protection, energy efficiency, GHG emission and socio-economic benefits. This review offers a holistic view with regard to the paradigm shift from "simple P removal" to "P reuse/recovery" and offers in-depth insights into the possible directions towards the P-recovery in the "water-energy-resource-GHG nexus" plant.

Foam fractionation and electrochemical oxidation for the treatment of per- and polyfluoroalkyl substances (PFAS) in environmental water samples

Treatment of waters contaminated by per- and polyfluoroalkyl substances (PFAS) in large volumes remains a challenge to date. Treatment trains comprising separation and destruction technologies are promising to manage PFAS contamination. Foam fractionation (FF) and electrochemical oxidation (EO) are two cost-effective technologies for PFAS separation and destruction, respectively. This work systematically explored the performance of a treatment train of FF followed by EO (FF-EO) for treating PFAS in environmental water samples. For each treatment step, the dependence of the treatment performance on operational factors and other variables were analyzed statistically. The statistical analysis revealed PFAS enrichment and removal depend significantly on PFAS carbon chain length, solution conductivity, and PFAS concentration. Whether FF-EO treatment costs less energy than direct EO without FF mainly relies upon PFAS carbon chain length and TOC content in the sample. Both correlations were found to be linear. For all environmental water samples in this study, FF-EO is more energy-efficient than EO alone.

How does population aging affect China's energy consumption?

In China, the proportion of elderly population is growing, influencing economic development and energy consumption. Our study investigates the relationship between population aging and energy consumption in China from 1997 to 2020, considering both short and long-term effects. The analysis employs the pooled mean group (PMG) estimation and explores the underlying mechanisms using mediating effects and threshold effects models. The PMG results reveal a negative long-term impact of population aging on energy consumption, indicating that a 1% increase in population aging leads to a 0.348% decrease in energy consumption. Additionally, GDP per capita and capital stock exhibit positive correlations with energy consumption, while the industrial structure shows a negative correlation. Technological progress is found to significantly increase energy consumption. The mechanism analysis suggests that the mediating role of scale and technological effects contributes to the negative effect of population aging on energy consumption. Furthermore, a nonlinear relationship between population aging and energy consumption is observed, influenced by both population size and technological progress. The policy implications call for a comprehensive approach that addresses elderly population growth, enhances energy efficiency, and promotes sustainable technologies to ensure sustainable economic development.

Diazinon and MCPA photo-reduction with sulfite excitation under UV irradiation and reducing agents' generation

Diazinon (DIZ) and 4-Chloro-2-methylphenoxyacetic acid (MCPA) herbicide and widely used in agricultural lands. Present study investigates diazinon and 4-chloro-2-methylphenoxyacetic acid photo-reduction via UV/Sulfite (US) in as Advanced Reduction Processes (ARP). The ideal pH was Molar ratio of sulfite: DIZ or MCPA 1:1 and, 20 min reaction time, and pH 9, in which about 100 % reduction of DIZ and MCPA with a concentration of 10 mg L-1 was achieved and the optimal conditions were considered. Kinetic investigation increasing DIZ and MCPA concentration from 5 to 20 mgL-1, kobs increase about from 0.151 to 0.234 for DIZ and from 0.231 to 0.589 min-1. Also, reaction rate (robs) increases about from 0.755 to 4.68 for DIZ and from 1.155 to 11.78 mg L-1.min. The amount of energy consumption in DIZ solution increased from 5 to 20, respectively, from 0.73 to 2.37, and in the reduction of MCPA from 0.47 to 1.49 kWh per cubic meter. According to experiments performed in 30 min with the US process, COD levels were reduced by about 46 % of both pollutants. It is important to note that the BOD/COD ratio rose from about 0.20 to 0.48 after 30 min. Since the index of biodegradability has grown high, it can be concluded that non-biodegradable COD (NBDCOD) convert to biodegradable COD (BDCOD) and toxicity is lower than of before of treatment. This study has been very suggesting that the UV/sulfite method produces effluent with a non-toxic and ecologically beneficial manner by biological treatment or discharge directly in environment.

Do industrialization and nonrenewable energy affect environmental quality? Evidence from top fossil fuel-consuming countries

The global warming phenomenon has been an issue of considerable discussion and debate among academics and decision-makers over the past few decades. Therefore, a deeper comprehension of the relationships between environmental deterioration and its causes is necessary in nations that rely on fossil fuels. This study examines the relationship between per capita carbon dioxide emissions and total natural resources, nonrenewable energy, industrialization, and ecological footprint from 2001 to 2020 in the case of major fossil fuel-consuming countries. The most recent panel Granger causality and panel-corrected standard error (PCSE) simulation models are used in this study. The findings indicate that natural resources, ecological footprint, and registered companies impede environmental quality. Similarly, the same results were noted by employing the generalized least square method. A feedback effect was noted between carbon dioxide emission and ecological footprint, while unidirectional causality between coal consumption and carbon emission. In light of these findings, it is advised that instead of pursuing policies that encourage the use of coal and petroleum, new energy policies enhance the share of nonfossil fuels in the energy mix for controlling rapid industrialization, extraction of natural resources, and environmental and economic issues.

Analysis of energy-related CO2 emissions in Pakistan: carbon source and carbon damage decomposition analysis

Carbon dioxide emissions (CO2es) are presently a hot topic of worldwide concern. It is of great significance for lessening CO2es to wholly understand the transformation pattern of CO2es among countries, industries, and the main factors (i.e., emission effect, energy intensity, economic development, population size, carbon per unit of land, land per capita, and environmental impact per capita effects) influencing CO2es. Thus, to mitigate the country's CO2es efficiently, it is necessary to determine the driving factors of its emissions and damage variations. For this, we use the logarithmic mean Divisia index method. This research decomposes the major two dimensions, such as carbon sources and carbon damage variations from 1986 to 2020, into eight factors. The results show that Pakistan's CO2es increased continuously during the period, with an average annual growth rate of 4.76%. Growing the country's CO2es over 1986-2020, the key influencing factors are economic development, population, and land, while energy intensity and emission factors are the main forces in mitigating CO2es. The carbon source and carbon damage dimensions reached 68.75 Mt and 208.56 Mt, respectively, which led to a rise in CO2e. The entire set of factors is averagely moving around the major outcomes that provide significant policy measures. Finally, to efficiently reduce CO2e, Pakistan should concentrate on specific industrial paths and implement challenging, comprehensive governance to attain a low-carbon chain throughout the process. Thus, based on empirical results, this research put forward policy suggestions for cleaner production to reduce CO2 emissions further, and environmental policies must be tailored to local conditions.

Development of energy efficient design proposals for air conditioned mosques: Temperate humid climate case

Mosques, which are types of religious buildings, are large buildings where many people pray at the same time. The diversity of the user type and density and the variability of the usage schedule make it difficult to establish the homogeneous thermal comfort of these large-volume public buildings. At the same time, the energy consumption in the buildings should be minimal in nowadays when the conventional energy sources decrease. The aim of this study is to evaluate created design strategies for designers and users in order to minimize energy consumption by determining the passive design criteria and choosing the type of air conditioning equipment while providing an acceptable thermal comfort level in mosques. According to the method created for the aim, the scenarios of mosques were compared in terms of thermal comfort and energy consumption in the temperate humid climate conditions. This method includes the analysis of scenarios created from the change of design parameters of mosques (plan, size, roof type of the mosques) with a simulation software which was validated with actual utility data. The suggestions were presented for the selection and design of the mechanical system as a result of the implementation of the created method. When the design scenarios of mosques are compared, the air conditioning of the indoor with radiant method consumed less energy than HVAC equipment with fan system. In accordance with the plan schemes (square, rectangle, circular), the least energy consumption per unit area was in the circular plan scheme and hemispherical design. Compared to the roof types (single dome, multi dome, pyramidal roof, flat roof), the most energy consumption per unit area was generally in the multi dome design. According to the average energy consumption values of the HVAC systems, there was 23 % less energy consumption in the flat plan type (105.06 kWh/m2) compared to the rectangular plan type (129.2 kWh/m2). In the intermittent use schedule of the HVAC system, 8 % more energy was consumed than in the continuous use schedule. According to the air changes per hour in the mosques, there was 5.93 % more energy consumption in 2 ach conditions compared to 0.5 ach conditions.

How digital finance promotes renewable energy consumption in China?

This study uses a quantitative methodology to investigate how the rise of digital money has affected efforts to increase green energy use in China. This work contributes to the body of knowledge by using a number of empirical methods, such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. This study's results further demonstrate the importance of digital financing in easing the adoption of renewable energy sources throughout China. Financing alternatives for renewable energy projects have increased as a result of digital finance's integration of digital technology with financial services. A wider range of investors has been attracted through crowdfunding, peer-to-peer lending, and other alternative financing models made possible by digital platforms, allowing the development of small and medium-sized renewable energy projects that may have had trouble securing funding through more traditional channels. The impact of digital finance on energy management and optimization is also investigated. As a result, renewable energy sources have been more widely adopted due to increased energy efficiency, better grid integration, and more efficient energy delivery. This study presents substantial evidence of the beneficial benefits of digital finance on renewable energy use in China using rigorous empirical methodologies such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. The results highlight the significance of using digital money to boost the use of renewable energy, lessen reliance on fossil fuels, and help create a greener, more sustainable future.

Analysing driving factors of India's transportation sector CO2 emissions: Based on LMDI decomposition method

India is the world's third-largest carbon dioxide (CO2) emitter, with the transportation sector accounting for most of this emission. Using the logarithmic-mean Divisia index (LMDI) decomposition method and Tapio decoupling, this study examines the driving factors and their relationship with economic growth for the Indian transportation sector. Transportation-related energy consumption is decomposed into six factors. From 2001 to 2020, CO2 emissions from the Indian transportation sector increased from 155.9 Mt to 368.2 Mt. Roadways produce 88% of all CO2 emissions. Energy systems, economic advancement, and population scale increase CO2 emissions, whereas energy performance and transportation form decrease. Transport advancement demonstrates both tendencies intermittently. CO2 emissions from Indian transportation exhibit a weak decoupling. The increasing demand for vehicles, reliance on conventional fuel, and increase in energy consumption indicate a positive correlation with the increase in the nation's CO2 emissions, while the transition from coal to electric locomotives and the increased use of electric vehicles offset the increase in emissions. In short, the government should update strategic sustainable transport policy measures and emphasize renewable energy. This study will assist policymakers in formulating robust sustainable transportation policies.

Activation of the growth-IGF-1 axis, but not appetite, is related to high growth performance in juveniles of the Malabar grouper, Epinephelus malabaricus, under isosmotic condition

Salinity, a determining factor in aquatic environments, influences fish growth. Here, we evaluated the effect of salinity on osmoregulation and growth performance in juveniles of the Malabar grouper, Epinephelus malabaricus, a species of high commercial value in Asian markets; we also identified the salinity that maximized this species' growth rate. Fish were reared at 26 °C and under a 14:10 h photoperiod with a salinity of 5 psu, 11 psu, 22 psu, or 34 psu for 8 weeks. Change in salinity had minimal impact on the plasma Na+ and glucose concentrations, although the Na+/K+-ATPase (nkaα and nkaβ) transcript levels in the gills were significantly lower among fish reared at 11 psu salinity. Concomitantly, oxygen consumption was low in fish reared at 11 psu salinity. The feed conversion ratio (FCR) was lower in fish reared at 5 psu and 11 psu salinities than at 22 psu and 34 psu salinities. However, the specific growth rate (SGR) was higher in fish reared at 11 psu salinity. These results suggest that rearing fish at 11 psu salinity would decrease energy consumption for respiration and improve food-conversion efficiency. Among fish reared at 11 psu salinity, the transcript levels of growth hormone (gh) in the pituitary, as well as its receptor (ghr) and insulin-like growth factor I (igf-1) in the liver, were upregulated; these findings suggested stimulation of the growth axis at low salinity. In contrast, there were minimal differences in the transcript levels of neuropeptide Y (npy) and pro-opiomelanocortin (pomc) in the brains of fish reared at any salinity, suggesting that salinity does not affect appetite. Therefore, growth performance is higher in fish reared at 11 psu salinity because of activation of the GH-IGF system, but not appetite, in Malabar grouper juveniles.

Investigating the impact of building materials on energy efficiency and indoor cooling in Nigerian homes

Urbanization, technological advancements, and lifestyle changes result in varying use of energy consumption throughout a building's life cycle. Building materials play a significant role in determining the energy efficiency of a structure, making it crucial to assess its energy consumption. The goal of the study is to investigate the relationship between building materials and energy efficiency and to assess their impact on interior cooling in Nigerian residential buildings, to provide insights and recommendations for optimizing energy performance and enhancing thermal comfort. The study relied on literature reviews, a case study, simulation and energy performance analysis of a typical three-bedroom apartment in three main distinct climatic zones of Nigeria to investigate the impact of building materials on energy efficiency and indoor cooling. The psychometric chart emphasised the importance of sun shading, dehumidification, and cooling (with potential humidification) for achieving thermal comfort while the advanced simulation capabilities of the DesignBuilder software provided valuable insights revealing that in Maiduguri, Minna and Lagos, the use of insulations on the building fabric and shaders resulted in a remarkable 37.9%, 33.4%, 27.6% reduction in the annual cooling load, and leading to a decrease of 4549 kWh, 4122 kWh, 3280 kWh, electricity consumption annually respectively. The study findings emphasize the importance of selecting energy-efficient building materials and implementing effective design strategies to enhance thermal comfort and reduce energy consumption. By implementing the recommended strategies, substantial energy savings can be achieved, resulting in reduced electricity consumption, cost savings, improved comfort and contributing to the advancement of sustainable building practices in Nigeria and beyond.

Green road transportation management and environmental sustainability: The impact of population density

The objective of the study is to examine the moderating role of population density in the relation between road transportation and environment sustainability of South Asian countries from 1990 to 2014. The study uses environment sustainability (population density) as the outcome (moderator), whereas road infrastructure, road density, energy intensity and transportation energy consumption are explanatory variables. The selection of these variables is motivated by their significance in understanding the relationship between road transportation and environmental sustainability. Road infrastructure and road density capture the physical aspects of transportation systems, while energy intensity and road transportation energy consumption provide insights into the energy efficiency and environmental impact of road transport, respectively. The findings show that a positive impact of road infrastructure and road density exists on environmental sustainability. There is contrarily a negative effect of road transportation energy consumption and energy intensity on environmental sustainability. Population density also harms environmental sustainability. When population density is used as a moderator between road transportation energy consumption, energy intensity and environment sustainability, it increases the coefficients of both energy intensity and road transportation energy consumption, which shows that population density plays an enhancing role between road transportation energy consumption, energy intensity and environment sustainability. The coefficients of road density and road infrastructure changed into a negative from a positive in the presence of population density as a moderator, which states that population density plays an antagonistic role between road density and environmental sustainability. We recommend prioritizing sustainable transportation solutions and policies in densely populated areas. Implementing measures such as promoting public transportation and electric vehicles, and investing in infrastructure that supports active transportation modes like cycling and walking can help mitigate the negative environmental effects of transportation while addressing the challenges posed by population density.

Assessing environmental sustainability in top Middle East travel destinations: insights on the multifaceted roles of air transport amidst other energy indicators

The Middle Eastern region is well-known for its flourishing tourism industry as the aviation sector contributes over US$213 billion to the regional GDP while air transport-related activities account for over 3.3 million jobs. Howbeit, the environmental impacts of this flourishing industry remain questionable. Hence, this study examines the tourism-emissions nexus in the Middle Eastern region from the perspective of air transportation while underscoring the multifaceted roles of major indicators like globalization, income, and energy use in the region. The empirical analysis of data spanning from 1975 to 2018 was conducted with advanced panel data analytical approach using the CS-ARDL technique. The sample selection was guided by available statistics on international tourist arrivals from the United Nations World Tourism Organization (UNWTO 2020), with a focus on the case of the five leading travel destinations in the region including Saudi Arabia, the United Arab Emirates (UAE), Egypt, Oman, and Qatar. The robustness of the evaluated outputs was checked after which result-based policy suggestions were enunciated for authorities and other regional stakeholders. The analysis indicated that air transportation although boosting tourism has constituted significant detrimental environmental impacts on the reviewed destinations with an estimated long-run elasticity of ∼1.03. Additionally, while the trio of globalization, energy utilization, and income expansion exacerbate environmental degradation, the lowest carbon-triggering magnitude was observed from the regional income expansion. Thus, while the aviation sector facilitates the growing quest to diversify from a primary sector-based economy (mainly resources exploitation) to other prospective service industries like tourism, the study posits the need for authorities to put measures in place to address the environmental side effect of air transportation.

Exploring the energy-economy-environment paradox through Yin-Yang harmony cognition

Adopting a symbiotic perspective, this study aimed to examine the paradoxical interrelationship of the energy-economy-environment nexus through the novel lens of Yin-Yang cognitive harmony. With a broad sample of countries (6 African lions, 5 Asian tigers, 3 NAFTA countries, and 10 top European Union economies), we applied the cointegration and fully modified ordinary least squares techniques to evaluate the short- and long-term relationships between energy consumption, economic growth and carbon dioxide (CO2) emissions for the period 1980-2012. The results were heterogeneous across countries, but a curvilinear (inverted U-shaped) relationship between total economic growth and CO2 emissions in conformity with the environmental Kuznets curve was confirmed in many cases. However, there was no evidence that economic growth resulting from energy consumption has been responsible for CO2 reduction, which suggests a 'trilemma' - that is, a challenge in balancing energy production, economic growth and environmental degradation. From a behavioural economic perspective, this paper draws on the Kuznets hypothesis and Jevon's paradox by adopting a paradoxical frame to characterise the complex energy-growth-environment interaction as a balanced, symbiotic coexistence. It thus provides novel insights into the energy-growth-environment trilemma through an unconventional perspective based on Yin-Yang cognitive harmony (Fig. 1, see the Appendix).