Increased arthroplasty surgeon energy consumption when performing primary total hip arthroplasty compared to total knee arthroplasty

Introduction

Previously published studies have hypothesized that total hip arthroplasty (THA) requires the surgeon to expend more energy that total knee arthroplasty (TKA). However, techniques for performing these procedures have evolved. Therefore, we sought to compare if primary THA had increased energy expenditure compared to primary TKA.

Methods

We prospectively recorded the heart rate, respiratory rate, minute ventilation, cadence, and energy expenditure of a single fellowship-trained arthroplasty surgeon while performing primary THA and TKA on 372 patients. Patient demographics and operative records were reviewed to evaluate differences in the physical demands of each surgical case. Age (64.3 versus 65.9 years, p = 0.1) and gender (54.8% versus 51.0% female, p = 0.5) were similar between THA and TKA, but TKAs had a higher body mass index (31.1 versus 28.7 kg/m2, p < 0.001). Chi-square and independent-samples t-tests were used to compare cohorts. Significance was set at p < 0.05.

Results

THA tended to have 1.1 times longer operative time than TKA (102.2 versus 88.9 min, p < 0.001). THA had a statistically higher heart rate compared to TKA, although this is unlikely to be clinically significant (82.5 versus 80.7 beats/minute, p < 0.001). Respiratory Rate was 1.1 times higher (15.9 versus 14.9 respirations/minute, p < 0.001) and minute ventilation was 1.2 times higher (19.6 versus 16.9 L/min, p < 0.001) when performing THA. Cadence was 1.5 times higher when performing TKA (4.2 versus 2.8 steps/minute, p < 0.001). THA had a 1.2 times higher energy expenditure/patient (378.8 versus 312.0 Calories/patient, p < 0.001) and a 1.1 times higher energy expenditure/minute (3.7 versus 3.5 Calories/minute, p = 0.01) compared to TKA.

Discussion

THA is associated with longer operative time and increased energy expenditure per compared to TKA. Despite THA and TKA procedures becoming more efficient, arthroplasty surgery continues to have heavy physical burden on the surgeon. Further research is needed to understand ways to decrease surgeon energy expenditure and promote career longevity.

Innovative cropping systems designed to reach both environmental and production targets: Data set of biotic and abiotic variables from a twelve-year French field trial

The data set describes variables collected from a French (N 48.84°, E 1.95°) field trial, over a twelve-year period (2009-2020), in which four innovative cropping systems designed to reach multiple environmental and production goals were assessed. The four cropping systems were designed with new combinations of agricultural practices; they differed in terms of pesticide uses, nitrogen inputs, tillage practices, and crop sequences. Both biotic and abiotic variables were measured. In a previous data paper, we focused on nitrogen fluxes collected from two systems, over eight years (2009-2016). In the present one, we enlarge the scope of the variables, including more crop descriptions and environmental indicators, from all four systems, and over a longer period (2009-2020). The biotic data are: growth stages; aboveground plant nitrogen content and biomass collected at different growth stages, depending on the species; yield components of all the crops; and yield harvested with a combine machine. No weed, crop disease, and pest data are described. The abiotic data are physical and chemical properties of the soil (i.e. texture, calcium carbonate content, pH, organic carbon contents, and nitrogen contents) collected at different assessment periods. All agricultural practices, and climate were regularly recorded, and the treatment frequency indexes and the energy consumptions were computed. These data could be used for benchmarking, to design low-input systems, to improve models for parameterization and validation, and to increase the predictive accuracy of models of crop growth and development, specifically for orphan species such as linseed, faba bean or hemp, and for soil carbon and soil nitrogen fluxes in various conditions.

A review of emerging membrane-based microalgal-bacterial processes for wastewater treatment: Process configurations, biological and membrane performance, and perspectives

Microalgal-bacterial (MB) consortia create an excellent eco-system for simultaneous COD/BOD and nutrients (N and P) removals in a single step with significant reduction in or complete elimination of aeration and carbonation in the biological wastewater treatment processes. The integration of membrane separation technology with the MB processes has created a new paradigm for research and development. This paper focuses on a comprehensive and critical literature review of recent advances in these emerging processes. Novel membrane process configurations and process conditions affecting the biological performance of these novel systems have been systematically reviewed and discussed. Membrane fouling issues and control of MB biofilm formation and thickness associated with these emerging suspended growth or immobilized biofilm processes are addressed and discussed. The research gaps, challenges, outlooks of these emerging processes are identified and discussed in-depth. The findings from the literature suggest that the membrane-based MB processes are advanced biotechnologies with a significant reduction in energy consumption and process simplification and high process efficiency that are not achievable with current technologies in wastewater treatment. There are endless opportunities for research and development of these novel and emerging membrane-based MB processes.

Dynamic resource allocation for energy-efficient downlink NOMA systems in 5G networks

Non-Orthogonal Multiple Access (NOMA) is a promising energy-efficient technology designed to satisfy the demands of future networks by efficiently sharing radio resources. In NOMA, the same radio resource is simultaneously assigned to two users at different power levels based on the NOMA-power domain. Resource allocation in NOMA presents a non-convex challenge, characterized as a non-deterministic polynomial (NP-hard) problem. This involves user and channel assignment and power allocation, making it an extraordinarily complex task to achieve an optimal solution. In this work, Simulated Annealing (SA) is proposed as an optimization technique for resource allocation in an energy-efficient downlink NOMA system. This resource allocation scheme addresses user and channel assignment, as well as power allocation, using SA as an efficient standalone approach to maximize energy efficiency in NOMA. SA is utilized to execute the assignment of users to channels, distribute the necessary power for each channel, and determine the power ratio among users sharing the same channel. The results obtained demonstrate a significant improvement in energy efficiency, outperforming the existing numerical methods by 22 %. The proposed SA scheme not only achieves a close optimal solution but also in less computational time, offering sufficient reliability in terms of energy efficiency enhancement when compared to the existing numerical method.

Calcium-induced upregulation of energy metabolism heats neurons during neural activity

Cellular temperature affects every biochemical reaction, underscoring its critical role in cellular functions. In neurons, temperature not only modulates neurotransmission but is also a key determinant of neurodegenerative diseases. Considering that the brain consumes a disproportionately high amount of energy relative to its weight, neural circuits likely generate a lot of heat, which can increase cytosolic temperature. However, the changes in temperature within neurons and the mechanisms of heat generation during neural excitation remain unclear. In this study, we achieved simultaneous imaging of Ca2+ and temperature using the genetically encoded indicators, B-GECO and B-gTEMP. We then compared the spatiotemporal distributions of Ca2+ responses and temperature. Following neural excitation induced by veratridine, an activator of the voltage-gated Na+ channel, we observed an approximately 2 °C increase in cytosolic temperature occurring 30 s after the Ca2+ response. The temperature elevation was observed in the non-nuclear region, while Ca2+ increased throughout the cell body. Moreover, this temperature increase was suppressed under Ca2+-free conditions and by inhibitors of ATP synthesis. These results indicate that Ca2+-induced upregulation of energy metabolism serves as the heat source during neural excitation.

Low Energy-consumption Oriented Membrane Fouling Control Strategy in Anaerobic Fluidized Membrane Bioreactor

Anaerobic fluidized membrane bioreactors (AFMBR) has attracted growing interest as an emerging wastewater treatment technology towards energy recovery from wastewater. AFMBR combines the advantages of anaerobic digestion and membrane bioreactors and shows great potential in overcoming limiting factors such as membrane fouling and low efficiency in treating low-strength wastewater such as domestic sewage.In AFMBR, the fluidized media performs significant role in reducing the membrane fouling, as well as improving the anaerobic microbial activity of AFMBRs. Despite extensive research aimed at mitigating membrane fouling in AFMBR, there has yet to emerge a comprehensive review focusing on strategies for controlling membrane fouling with an emphasis on low energy consumption.Thus, this work overviews the recent progress of AFMBR by summarizing the factors of membrane fouling and energy consumption in AFMBR, and provides targeted in-depth analysis of energy consumption related to membrane fouling control. Additionally, future development directions for AFMBR are also outlooked, and further promotion of AFMBR engineering application is expected. By shedding light on the relationship between energy consumption and membrane fouling control, this review offers a useful information for developing new AFMBR processes with an improved efficiency, low membrane fouling and low energy consumption, and encourages more research efforts and technological advancements in the domain of AFMBR.

Feasibility of replacing proton exchange membranes with pressure-driven membranes in membrane electrochemical reactors for high salinity organic wastewater treatment

Membrane electrochemical reactor (MER) shows superiority to electrochemical oxidation (EO) in high salinity organic wastewater (HSOW) treatment, but requirement of proton exchange membranes (PEM) increases investment and maintenance cost. In this work, the feasibility of using low-cost pressure-driven membranes as the separation membrane in MER system was systematically investigated. Commonly used pressure-driven membranes, including loose membranes such as microfiltration (MF) and ultrafiltration (UF), as well as dense membranes like nanofiltration (NF) and reverse osmosis (RO), were employed in the study. When tested in a contamination-free solution, MF and UF exhibited superior electrochemical performance compared to PEM, with comparable pH regulation capabilities in the short term. When foulant (humic acid, Ca2+ and Mg2+) presented in the feed, UF saved the most energy (43 %) compared to PEM with similar removal rate of UV254 (∼85 %). In practical applications of MER for treating nanofiltration concentrate (NC) of landfill leachate, UF saved 27 % energy compared to PEM per cycle with the least Ca2+ and Mg2+ retention in membrane and none obvious organics permeation. For fouled RO and PEM with ion transport impediment, water splitting was exacerbated, which decreased the percentage of oxidation for organics. Overall, replacing of PEM with UF significantly reduce the costs associated with both the investment and operation of MER, which is expected to broaden the practical application for treating HSOW.

Green Hospital as a new Standard in Japan: How far can Neurosurgery go in Japan?

BACKGROUND

Climate change is a significant challenge that the medical community must address. Hospitals are large facilities with high water and energy consumption, as well as high levels of waste generation, which makes it important to pursue green hospital initiatives. Neurosurgery requires substantial energy for surgeries and tests.

METHODS

Based on the keywords "Climate change," "green hospital," "neurosurgery," "energy consumption," "environmental impact" listed in this paper, we extracted representative manuscripts, and the practices employed in the authors' hospital were assessed.

RESULTS

The "Guidelines for Environmental Consideration in Hospitals" and "Guidelines for the Sustainability of Hospital Environments" have been developed; however, they are not implemented in most hospitals in Japan. Inhalational anesthetics were found to contribute significantly to greenhouse gas emissions. Educating patients and staff and employing the "8 Rs" (rethink, refuse, reduce, reuse, recycle, research, renovation, and revolution) showed promise in achieving green hospital standards.

CONCLUSIONS

The advent of 'green hospitals' in Japan is imminent. The active participation of neurosurgeons can play a crucial role in diminishing the environmental footprint of health care while simultaneously enhancing medical standards. Given the pressing challenges posed by climate change, there is a critical need for an overhaul of medical practices. It is imperative for neurosurgeons to pioneer the adoption of new, sustainable medical methodologies.

Unveiling energy security in agriculture through vital indicators extraction and insights

Despite advancements in meeting various human needs, energy supply remains a top priority for all countries worldwide. The escalating energy consumption in the agricultural sector underscores the necessity to scrutinize its energy usage. Presently, there exists an absence of a precise tool for accurately measuring this consumption. Hence, this study aims to identify indicators for measuring energy security in agriculture, conducted in three phases: content analysis, indicator validation, and field investigation. In the content analysis phase, energy security indicators were extracted and grouped into four categories: accessibility, availability, utilization, and sustainability. Following this, a two-stage validation process led to the identification of 18 indicators for assessing energy security in agriculture. In the field phase, a tailored questionnaire was distributed to 160 randomly selected farmers. The findings revealed that the availability component held the highest rank in establishing energy security, with an average score of 3.31. However, the current status of the access component indicates a more unfavorable situation compared to other dimensions. Consequently, to achieve energy security in agriculture, particular emphasis should be placed on enhancing energy access. Key areas to address include reducing transportation costs and minimizing the use of chemical pesticides. This indicates a necessity for focused interventions aimed at improving both energy access and sustainability within the agricultural sector. These efforts would contribute to enhancing economic efficiency and promoting environmental conservation.

Analysis of factors influencing the energy efficiency in Chinese wastewater treatment plants through machine learning and SHapley Additive exPlanations

Wastewater treatment plants (WWTPs) contribute significantly to the control of pollution in water. However, they are significant energy consumers. Identifying the factors influencing energy consumption is crucial for enhancing the energy efficiency of WWTPs. To address this, the unit energy consumption (UEC) of WWTPs was predicted using machine learning models. In order to accurately evaluate WWTPs' energy utilization efficiency, a comprehensive energy evaluation indicator, UEC (kWh/kg TODremoved) was utilized in this study. Among the prediction models, the eXtreme Gradient Boosting (XGBoost) achieves the highest prediction accuracy. SHapley Additive exPlanations (SHAP) was adopted as the model explanation system, and the results revealed that UEC was negatively affected by TN concentration, which was the most influential factor. The stoichiometry-based model calculation result indicates that the nitrification consumes average 77 % of the overall oxygen demand. SHAP analysis illustrated that the UEC of main technologies decreases with increasing influential factors. Partial dependence plot (PDP) compared average UEC of these technologies and SBR consumed the least amount of energy. The research also indicated that low influent TN concentration is the main problem in China. Consequently, it is imperative to exert efforts in ensuring the influent TN concentration while simultaneously making appropriate adjustments to the treatment process. This study provides valuable implications and methods for retrofitting and upgrading WWTPs.

Scenario analysis of energy consumption and related emissions in the transportation industry-a case study of Shaanxi Province

In the context of pursuing carbon neutrality and balancing the use of fossil fuels with renewable energy, the transportation industry faces the challenge of accurately predicting energy demand, related emissions, and assessing the effectiveness of energy technologies and policies. This is crucial for formulating energy management plans and reducing carbon dioxide (CO2) and atmospheric pollutant emissions. Currently, research on energy consumption and emission forecasting primarily relies on energy consumption quantities and emission factors, which lack precision. This study employs the low emissions analysis platform (LEAP) model, utilizing a "bottom-up" modeling approach combined with scenario analysis to predict and analyze the energy demand and related emissions in the transportation industry. Compared to previous studies, the methodological framework proposed in this research offers higher precision and can explore energy-saving and emission-reduction pathways for different modes of transport, providing a valuable energy forecasting tool for transport policy formulation in other regions. The forecast results indicate that under the business-as-usual (BAU) scenario, by 2049, the energy consumption and related emissions in Shaanxi Province's transportation industry are expected to increase by 1.15 to 1.85 times compared to the baseline year. In the comprehensive (CP) scenario, the industry is projected to reach a carbon peak around 2033. The study also finds that energy consumption and emissions predominantly originate from private passenger vehicles, highway freight, and civil aviation passenger, which have the greatest potential for emission reduction under the transport structure optimized (TSO) scenario. Therefore, policymakers should consider regional development characteristics, combine different transportation modes, and specifically analyze the emission reduction potential of the transportation industry in various regions, formulating corresponding reduction policies accordingly.

How to improve the energy-saving performance of China's transport sector? An input-output perspective

The transport sector proves a major energy consumer in China, but improving energy-saving performance in China's provincial transport sector from the lifecycle perspective remains unresolved. Thus, this study employs the environmentally extended multi-region input-output (MRIO) method, structural path analysis, and the newest MRIO table of China from 2017, to investigate how to improve the energy-saving performance from final demand structure, supply chain, and pathway perspectives. The relevant results are threefold. (1) Regarding the final demand structure level, the embodied energy consumption of China's transport sector is predominantly driven by investment from the production side, while that of the consumption side is primarily caused by exports. (2) At the supply chain level, production-side embodied energy consumption primarily occurs along a three-echelon supply chain, while that from the consumption side mostly occurs via a two-echelon supply chain. (3) At the pathway level, the production-side energy-saving performance of China's provincial transport sector is dominated by two pathways along the construction sector, including transport sector → construction sector → final demands, and transport sector → intermediate inputs → construction sector → final demands, while that of the consumption side is chiefly determined by three pathways along internal transportation chains.

Microwave pretreatment of wastewater sludge technology-a scientometric-based review

This manuscript presents a scientometric review of recent advances in microwave pretreatment processes for sewage sludge, systematically identifying existing gaps and prospects. For this purpose, 1763 papers on the application of microwave technology to sludge pretreatment were retrieved from the Web of Science (WoS) using relevant keywords. These publications were then analyzed using diverse scientometric indices. The results show that research in this field encompasses applications based on the non-thermal effects of microwaves, enhanced effectiveness of anaerobic digestion (AD), and the energy balance of this pretreatment system. Overcoming existing technical challenges, such as the cleavage of extracellular polymers, reducing microwave energy consumption, understanding the non-thermal effects of microwaves, promoting AD of sludge in combination with other chemical and physical methods, and expanding the application of the technology, are the main scientific focuses. Additionally, this paper thoroughly examines both the constraints and potential of microwave pretreatment technology for wastewater treatment.

Exploring the asymmetric effect of fiscal policy instruments in encountering environmental degradation: proposing an SDG framework for India

Asian countries are facing difficulties in attaining sustainable development goals (SDGs), and India is not an exception to it, with environmental degradation being one of the primary issues. Therefore, a policy-level reorientation may be required to address it. From this standpoint, fiscal policy instruments may come in handy towards fully integrating the SDGs into its agenda. The present investigation designs an SDG framework for India that could serve as an example for other Asian nations. This study introduces a new investigation exploring the relationship between fiscal policy instruments and environmental quality in India by examining the environmental Kuznets curve (EKC) hypothesis from 1990 to 2021. A nonlinear autoregressive distributed lag (NARDL) model is applied for empirical examination. The findings indicate that positive and negative shocks in fiscal policy instruments have significant impact on carbon emissions in both the long and short run. The study has also found evidence of an "inverted U-shape" EKC for India. These results are valuable from a policy perspective for India and other Asian countries to address environmental issues. The study has also outlined potential outcomes that may benefit India's fiscal policy in resolving environmental issues and attaining better economic growth. In the end, the study proposes a policy framework that supports SDG 7, SDG 8, SDG 12, SDG 13, and SDG 17 objectives.

Energy demand forecasting using convolutional neural network and modified war strategy optimization algorithm

Predicting the electricity demand is a key responsibility for the energy industry and governments in order to provide an effective and dependable energy supply. Traditional projection techniques frequently rely on mathematical models, which are limited in their ability to recognize complex patterns and correlations in data. Machine learning has emerged as a viable tool for estimating electricity in the last decade. In this study, the Modified War Strategy Optimization-Based Convolutional Neural Network (MWSO-CNN) has been provided for electricity demand prediction. To increase the precision of electricity demand prediction, the MWSO-CNN approach integrates the benefits of the modified war strategy optimization technique and the convolutional neural network. To improve efficiency, the modified war strategy optimization technique is employed to adjust the hyperparameters of the CNN algorithm. The suggested MWSO-CNN approach is tested on a real-world electricity demand dataset, and the findings show that it outperforms many state-of-the-art machine learning techniques for predicting electricity demand. In general, the suggested MWSO-CNN approach could offer a successful and cost-effective strategy for predicting energy consumption, which will benefit both the energy business and society as a whole.

Deep learning-based forecasting of electricity consumption

Building energy management systems (BEMS) are integrated computerized systems that track and manage the energy use of many pieces of building-related machinery and equipment, including lighting, power systems, and HVAC systems. Modern buildings must have BEMSs in order to reduce energy usage while maintaining comfort. Not only for energy-saving purposes, BEMS is essential in enhancing the quality of the energy supply, which helps to gain a better understanding of how energy is used and the building's energy usage. When the dynamics of a building's energy usage are known, it is possible to determine which changes are most likely to reduce consumption. Numerous connected devices, operating modes, energy usage, and environmental factors can all be monitored and controlled in real-time using BEMS. Changing operating times and setting points to maximize comfort and efficiency is made simple by this. In this paper, we have primarily addressed the two significant issues of model optimization and electricity consumption forecasts. Future forecasting has been done using the LSTM based time series approach. We generated data on the amount of electricity consumed by a hospital facility and tested our suggested methodologies on actual data. The findings gained demonstrated that the strategies were successful with both types of data. On actual data, the trend in electricity consumption can be accurately predicted. Several model optimizers enhanced the suggested methods' performance as well. Our objective function gain accuracy result of 95%.

Data aggregation algorithm for wireless sensor networks with different initial energy of nodes

Data aggregation plays a critical role in sensor networks for efficient data collection. However, the assumption of uniform initial energy levels among sensors in existing algorithms is unrealistic in practical production applications. This discrepancy in initial energy levels significantly impacts data aggregation in sensor networks. To address this issue, we propose Data Aggregation with Different Initial Energy (DADIE), a novel algorithm that aims to enhance energy-saving, privacy-preserving efficiency, and reduce node death rates in sensor networks with varying initial energy nodes. DADIE considers the transmission distance between nodes and their initial energy levels when forming the network topology, while also limiting the number of child nodes. Furthermore, DADIE reconstructs the aggregation tree before each round of data transmission. This allows nodes closer to the receiving end with higher initial energy to undertake more data aggregation and transmission tasks while limiting energy consumption. As a result, DADIE effectively reduces the node death rate and improves the efficiency of data transmission throughout the network. To enhance network security, DADIE establishes secure transmission channels between transmission nodes prior to data transmission, and it employs slice-and-mix technology within the network. Our experimental simulations demonstrate that the proposed DADIE algorithm effectively resolves the data aggregation challenges in sensor networks with varying initial energy nodes. It achieves 5-20% lower communication overhead and energy consumption, 10-20% higher security, and 10-30% lower node mortality than existing algorithms.

Revisiting the relationships between energy consumption, economic development and urban size: A global perspective using remote sensing data

Existing methods of measuring energy consumption require complex statistics and computing. A real-time and globally applicable approach for comparing energy consumption across different cities is still lacking. Additionally, the nonlinear relationships and varying thresholds of energy consumption in relation to economic activities and urbanization remain unconfirmed. This study aims to fill these gaps by utilizing Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data in 2015 and a top-down approach based on a multiple regression model to examine energy consumption in global cities employing a redefined urban boundary. It also explores the accurate relationship between energy consumption, population density (as a proxy of urbanization), and per capita gross domestic product (GDP) across different regions and urban sizes using generalized additive models and regression models. High-resolution gridded population and GDP datasets covering the entire planet are utilized for this purpose. The study also estimates the development potentiality. The study yields followings outcomes: Firstly, the top 30 cities with the highest per capita energy consumption account for over 0.66% of the total per capita energy consumption of all cities. Secondly, in East Asia (EA) and Southeast Asia (SEA), the per capita energy consumption decreases when per capita GDP reaches $40,000 and $75,000, respectively, while it remains stable in cities located in Western Europe (WE) and North America (NA) as per capita GDP increases. Thirdly, the per capita energy consumption declines with increasing urban population density until reaching 10,000 person/km2, 22,000 person/km2, and 4000 person/km2 in EA, SEA, and NA, respectively. Fourthly, in Central Asia (CA), megacities can save over 100 Mbtu/population when per capita GDP increases by $1000 compared to big cities. This pioneering study provides a comparable investigation of energy consumption at the global city level, exploring its relationship with urbanization and economy by employing a unified calculation standard. It will facilitate long-term energy-saving policies and urban planning strategies.

Simultaneous ammonia and organics degradation from municipal landfill leachate by electrochemical oxidation

The two primary issues for wide implementation of the electrochemical oxidation of wastewater are the significant cost of electrode and high energy consumption. On the other side, conventional biological processes and membrane technology have several drawbacks for recalcitrant landfill leachate (LL) treatment. To address these issues, graphite/PbO2 anode was used to treat medium to mature age (biodegradability index, 5-day biochemical oxygen demand/chemical oxygen demand: 0.25) LL. To reduce the cost of the oxidation process and maximize the efficiency, operating conditions were optimized. The optimum parameter values were obtained as 24.7 mA cm-2, 180 ± 3 rpm, and 1.9 cm of current density, stirring rate, and electrode gap, respectively. Dissolved organic carbon (DOC), chemical oxygen demand (COD), and ammonia-N removal efficiencies of 55 ± 1.4%, 81 ± 1.9%, and 56 ± 3% were obtained after 8 h of degradation at optimum conditions. The decrease in aromatic substances and ultraviolet (UV) quenching materials were evaluated by UV-Visible spectroscopy and Specific UV absorbance. The conversion of aromatic compounds into simpler molecule compounds was also verified by Fourier-transform infrared spectroscopy analysis. The lab-scale anode synthesis cost was evaluated as 0.42 USD.

Asymmetric impact of patents on green technologies on Algeria's Ecological Future

This study examines how patents on green technologies impact Algeria's ecological footprint from 1990 to 2022 while controlling for economic growth and energy consumption. The objectives are to analyze the asymmetric effects of positive and negative shocks in these drivers on ecological footprint and provide policy insights on leveraging innovations and growth while minimizing environmental harm. Given recent major structural shifts in Algeria's economy, time series data exhibits nonlinear dynamics. To accommodate this nonlinearity, the study employs an innovative nonlinear autoregressive distributed lag approach. The findings indicate that an upsurge in green technologies (termed as a positive shock) significantly reduces the ecological footprint, thereby enhancing ecological sustainability. Interestingly, a decline in green technologies (termed as a negative shock) also contributes to reducing the ecological footprint. This highlights the crucial role of clean technologies in mitigating ecological damage in both scenarios. Conversely, a positive shock in economic growth increases ecological footprint, underscoring the imperative for environmentally friendly policies in tandem with economic expansion. Negative shocks, however, have minimal impact. In a similar vein, positive shock in energy consumption increases ecological footprint, underlining the importance of transitioning towards cleaner energy sources. Negative shock has a smaller but still noticeable effect. The results confirm asymmetric impacts, with positive and negative changes in the drivers affecting Algeria's ecological footprint differently. To ensure long-term economic and ecological stability, Algeria should prioritize eco-innovation and green technology development. This will reduce dependence on fossil fuels and create new, sustainable industries.

Decomposition of the site-level energy consumption and carbon dioxide emissions of the iron and steel industry

Identifying the key factors influencing energy consumption and CO2 emissions is necessary for developing effective energy conservation and emission mitigation policies. Previous studies have focused mainly on decomposing changes in energy consumption and CO2 emissions at the national, regional, or sectoral levels, while the perspective of site-level decomposition has been neglected. To narrow this gap in research, a site-level decomposition of energy- and carbon-intensive iron and steel sites is discussed. In this work, the logarithmic mean Divisia index (LMDI) method is used to decompose the changes in the energy consumption and CO2 emissions of iron and steel sites. The results show that the production scale significantly contributes to the increase in both energy consumption and CO2 emissions, with cumulative contributions of 229.63 and 255.36%, respectively. Energy recovery and credit emissions are two key factors decreasing site-level energy consumption and CO2 emissions, with cumulative contributions to the changes in energy consumption and CO2 emissions of -158.30 and -160.45%, respectively. A decrease in energy, flux, and carbon-containing material consumption per ton of steel promotes direct emission reduction, and purchased electricity savings greatly contribute to indirect emission reduction. In addition, site products and byproducts promote an increase in credit emissions and ultimately inhibit an increase in the total CO2 emissions of iron and steel sites.

Investigating the energy-saving potential of using thermochromic coatings on opaque and transparent elements of educational buildings

Buildings consume about 40% of global energy. It is essential to use various measures to reduce the energy consumption of the buildings as much as possible. This research investigates the impact of using a new combination of thermochromic (TC) materials in the building envelope of educational buildings. A case study building at Razi University was selected, and a 3D model was created in DesignBuilder software. Firstly, TC coating for external walls was entered into the base model, and several simulations were performed to find the effect of this coating on the energy consumption of the building. Then, a low-emissivity thermochromic (LETC) window was defined using energy management system (EMS) scripting and was entered into the base model. Finally, these two measures were combined, and the cumulative effect of using both TC coating on the external walls and LETC window was identified. Results indicated that the simultaneous application of these two measures reduced the heating demand of the building more in Tabriz, with the least cooling degree days (CDD). Also, simulation results revealed that the simultaneous use of these measures decreased the cooling demand of the building more in Bandar Abbas, with the highest CDD. Using TC coating on the external walls and LETC windows together reduced the energy consumption of the building more in Bandar Abbas. Consequently, integrating these measures can reduce the heating demand of educational buildings more in heating-dominated climates. Also, the simultaneous use of these measures can reduce cooling demand more in cooling-dominated climates.

Novel coiled hollow fiber module for high-performance membrane distillation

Membrane distillation (MD) scale-up is challenged by ineffective heat recovery and the temperature polarization effect. Direct contact membrane distillation (DCMD) modules suffer high thermal conduction losses due to feed flow direction along the length of the membrane, resulting in low thermal efficiency. We propose a novel module design named coiled hollow fiber (CHF) to decouple the flow direction from the membrane surface in hollow fiber (HF) DCMD. Experimental and computational analyses were employed to compare the performance of CHF and the conventional design. The CHF module design successfully mitigates the TP effect in HF DCMD, increasing the flux by 148 % and 163 % in cross-flow and localized heating (LH) modes, respectively. Moreover, CHF operated in LH mode exhibits the lowest energy consumption of all configurations (81 % decrease) compared to the conventional design. This novel module design represents a new pathway for efficient and highly performing DCMD module.

Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness

The purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specific contributions of each country to the study variables and their impact on carbon emissions. The findings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly significant impact (p < 0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development, and international cooperation within Asia to reach the goal of being carbon neutral by 2050.

Energy saving effects of digital technologies from a life-cycle-analytical perspective: evidence from China

Digital technology has become a key driver of industrial transformation and resource utilization. However, no consensus has been reached on the exact relationship between digital technology and energy utilization. This study adopted a comprehensive index system to investigate the impact of digital technologies on energy utilization across 30 provinces in China. The results reveal a non-linear relationship between digital technologies and energy efficiency in China (represented by an N-curve), which is validated by robustness tests. This indicates digital technology exerts a fast-slow-rapid impact on improving energy efficiency throughout its initial-rapid-stable developmental stages. Geographically, this effect is more pronounced in eastern and central China, as well as in areas with lower energy efficiency. Furthermore, the impact of digital technology on total energy consumption can be characterized by an inverted N-shaped curve. As regional energy efficiency improves, the energy consumption associated with the development of digital technologies gradually decreases. These findings can contribute valuable insights for enhancing energy efficiency and provide practical guidance for the formulation of energy and digital technology policies.

Does foreign direct investment influence carbon emission-related environmental problems? Contextual evidence from developing countries across Sub-Saharan Africa

Sub-Saharan African nations face multifaceted environmental problems, especially those associated with carbon discharges. Hence, this study calculates a composite carbon index in the context of 39 developing nations from this region and uses it as a proxy for the carbon emission-related environmental problems they have faced during the 2000-2020 period. This index is estimated by utilizing data regarding annual carbon dioxide discharges, output-based carbon productivity rates, and energy consumption-based carbon intensity levels in the concerned countries. Hence, policy takeaways from this study have critical relevance for the selected sub-Saharan African nations to help them achieve the objectives related to the Sustainable Development Goals agenda and the Paris Accord. Overall, the findings from the econometric analyses verify that more receipt of foreign direct investment initially raises but later on reduces environmental problems. Thus, the nexus concerning these variables depicts an inverse U-shape. Besides, the results endorse that greening the energy consumption structures of the sampled sub-Saharan African countries helps to abate their environmental problems in the long run while financial development aggravates the extent of environmental adversities that take place. Lastly, improving the quality of regulatory agencies enables the Sub-Saharan African nations to further mitigate their environmental problems. Moreover, these aforementioned findings are observed to be heterogeneous across low- and middle-income categories of the selected Sub-Saharan African countries. Furthermore, the heterogeneity of the findings is also confirmed by the outcomes derived from the country-specific analyses. Nevertheless, these nations should attract clean energy-embodying foreign direct investment, make their energy consumption structures greener by amplifying renewable energy adoption rates, introduce green funds to develop their financial sectors, and make their environmental regulatory agencies more transparent with their activities.

Stationarity and cycles in the energy consumption in the United States

The purpose of this paper is twofold: analyzing stationarity of energy consumption by source in the United States and studying their cycles and pairwise synchronization. We study a panel of nine time series of monthly energy consumption for the period 1973-2022. Four of the series (namely coal, natural gas, petroleum, and nuclear electric power consumption) are non-renewables, whereas the remaining ones (hydroelectric power, geothermal, biomass, solar, and wind energy consumption) are renewable energy sources. We employ a nonparametric, panel stationarity testing approach. The results indicate that most of the series may be trend-stationarity, with nuclear and geothermal energy consumption being the only exceptions. Additionally, a study on potential cycles in the series of energy consumption by source is carried out, and subsequently we analyze pairwise concordance between states of different energy sources and between states of energy sources and the business cycle. Significant correlations are detected in the latter analysis, which are positive in the case of fossil fuel sources and negative for two renewable sources, namely geothermal and biomass energy consumption.

Assessing the effect of energy consumption and food production from agriculture on environmental degradation in Pakistan: Does institutional quality matter?

The nexus between food production (FP), energy consumption (EC), institutional quality (IQ), and ecological degradation (ED) has important implications for environmental sustainability. Nevertheless, environmental degradation caused by FP is widely ignored, especially in Pakistan. To fill this void, we investigated the impact of energy use, FP, and IQ on Pakistan's environmental degradation between 1990 and 2021. We also explore the moderating influence of IQ on ED. To evaluate this influence, we use the autoregressive distributed lag (ARDL) method for cointegration and the fully modified ordinary least-squares method for robustness estimation. Our empirical results demonstrate that, whereas FP and EC contribute to pollution, IQ reduces the pace of environmental degradation. Furthermore, the presence of a strong IQ mitigates the harmful ecological effects of FP and EC. Moreover, the results revealed that unbiased domestic IQ is crucial to boosting energy and agricultural efficiency while reducing CO2 emissions. Our findings might be considered while public policies to reduce carbon emissions and increase FP in a healthy environment are being developed. Integr Environ Assess Manag 2024;20:518-532. © 2023 (SETAC).

An energy-efficient solution to sludge drying and combustion process through Camellia oleifera shells amended foaming

Foaming pretreatment has been proven effective in promoting sludge drying, however, the variation in sludge properties significantly influences the foaming efficiency. Inspired by foam stabilizer of solid particles, Camellia oleifera shells (COS) was screened out from various biomasses as an additive incorporated with the CaO for promoting the sludge foaming. For the introduction of COS, this study analyzed the drying behaviors of foamed sludge, quantified the surface cracks information, characterized the combustion performance, and evaluated the energy consumption. The results indicated that 46.72-50.10% of time could be saved in foaming the sludge to 0.70 g/mL by addition of 3.0 wt% COS. Compared with the original sludge (OS), the 0.70 g/mL foamed sludge saved 47.43% of time for sludge drying at 80 °C, and this value further increased to 53.14% with 3.0 wt% COS addition. Combining the multifractal spectra and drying kinetics analysis, the foaming promoted the formation of complex surface cracks in the warm-up period, while COS further improved the complexity of cracks in the constant rate period, and the shrinkage of isolated sludge blocks in the falling rate period, thus enhanced the moisture diffusion and heat transfer. Furthermore, the appropriate porous structure and additional volatile matters promoted the combustion performance. The 0.90 g/mL foamed sludge with COS presented the lowest activation energy of 180.362 kJ/mol in combustion. Overall, compared with OS, the 0.70 g/mL foamed sludge with COS saved 40.65% energy consumption during the foaming, drying and combustion processes, providing an energy-efficient solution for the sludge treatment and disposal.

Energy consumption in MRI: Determinants and management options

BACKGROUND

Energy consumption awareness is a known concern, and radiology departments have energy-intensive consuming machines. The means of energy consumption management in MRI scanners have yet to be evaluated.

PURPOSE

To measure the MRI energy consumption and to evaluate the means to reduce it.

MATERIALS AND METHODS

Data was retrieved for two MRI scanners through the hospital's automated energy consumption measurement software. After correlation with picture archiving and communication system (PACS) files, they were segmented by machine and mode (as follows: stand-by, idle and active) and analyzed. Active mode data for a specific brain MRI protocol have been isolated, and equivalent low energy consuming protocol was made. Both were performed on phantom and compared. Same protocol was performed on a phantom using 3.0T 16 and 32 head channels coils. Multiples sequences were acquired on phantom to evaluate power consumption.

RESULTS

Stand-by mode accounted for 60 % of machine time and 40 % of energy consumption, active mode accounted for 20 % machine time and 40 % energy consumption, idle mode for 20 % imachine time and 20 % consumption. DWI and TOF sequences were the most consuming in our brain-MRI protocol. The low energy consuming protocol allowed a saving of approximately 10 % of energy consumption, which amounted for 0.20€ for each examination. This difference was mainly due to an energy consumption reduction of the DWI sequence. There were no difference in consumption between a 3.0T 16 and 32 channels head coils. Sequence's active power and duration (especially considering slice thickness) have to be taken into account when trying to optimize energy consumption.

CONCLUSION

There are two key factors to consider when trying to reduce MRI scan energy consumption. Stand-by mode energy consumption has to be taken into account when choosing an MRI scan, as it can't be changed further on. Active mode energy consumption is dependent of the MRI protocols used, and can be reduced with sequences adaptation, which must take into account sequence's active power and duration, on top of image quality.

Industrialization and environmental sustainability in Africa: The moderating effects of renewable and non-renewable energy consumption

African countries have become interested in economic transformation through revamping their manufacturing sectors. However, the environmental effect of industrialization is an issue of great concern, with the need to maintain a sustainable environment in line with sustainable development goals. This study investigates the effect of industrialization on environmental sustainability in Africa, taking in to consideration the moderation effect of renewable energy and non-renewable energy consumption. Data was collected for 46 African countries from the Global Footprint Network, World Development Indicators of the World Bank and the Food and Agricultural Organization from 2000 to 2022. Robust panel fixed effects regression and generalized least squares methods were used to analyze the data. The empirical results showed that value added in manufacturing has a negative and significant effect on environmental sustainability. However, when interacted with renewable energy consumption, manufacturing exerted a positive effect on load capacity factor, indicating that the environment will be sustainable if manufacturing sector activities are powered by renewable energies. This suggests that renewable energy has the ability to propel industrial growth in Africa while sustaining the environment. The moderating effect of non-renewable energy and manufacturing is positive in the fixed effects regression and negative for the generalized least squares estimates. This suggest that fossil fuel consumption, particularly clean fossil fuels or natural gas can still drive African manufacturing without considerably harming the environment but continual use of it in to the long run will make the environment unsustainable. From the above results, this study recommends that for sustainable industrialization to take place, Africa should grow her manufacturing sector by extending the range of manufactured products from light to heavy manufactures while ensuring that renewable energy remains the major source of industrial energy supply.

Recent advances and new insights on the construction of photocatalytic systems for environmental disinfection

Photocatalysis, as a sustainable and environmentally friendly green technology, has garnered widespread recognition and application across various fields. Especially its potential in environmental disinfection has been highly valued by researchers. This study commences with foundational research on photocatalytic disinfection technology and provides a comprehensive overview of its current developmental status. It elucidates the complexity of the interface reaction mechanism between photocatalysts and microorganisms, providing valuable insights from the perspectives of materials and microorganisms. This study reviews the latest design and modification strategies (Build heterojunction, defect engineering, and heteroatom doping) for photocatalysts in environmental disinfection. Moreover, this study investigates the research focuses and links in constructing photocatalytic disinfection systems, including photochemical reactors, light sources, and material immobilization technologies. It studies the complex challenges and influencing factors generated by different environmental media during the disinfection process. Simultaneously, a comprehensive review extensively covers the research status of photocatalytic disinfection concerning bacteria, fungi, and viruses. It reveals the observable efficiency differences caused by the microstructure of microorganisms during photocatalytic reactions. Based on these influencing factors, the economy and effectiveness of photocatalytic disinfection systems are analyzed and discussed. Finally, this study summarizes the current application status of photocatalytic disinfection products. The challenges faced by the synthesis and application of future photocatalysts are proposed, and the future development in this field is discussed. The potential for research and innovation has been further emphasized, with the core on improving efficiency, reducing costs, and strengthening the practical application of photocatalysis in environmental disinfection.

Technological progress and coupling renewables enable substantial environmental and economic benefits from coal-to-olefins

China's growing demand for bulk chemicals and concerns regarding energy security are scaling up coal-to-olefins (CTO) production. Three generations of independent dimethyl ether/methanol-to-olefins technologies have been successively launched with greatly improved production efficiencies. However, to date, widespread concerns regarding the intensive environmental impacts and potential economic risks have not been addressed in the context of this industrialization. Here we show that, through the technological progress from the first to the third generation, life cycle energy consumption, water consumption, and carbon emissions can be reduced to 119.5 GJ/t, 27.6 t/t, and 9.1 t CO2-eq/t, respectively, and human health damage, ecosystem quality damage, and resource scarcity impacts can be decreased by 40.5 %, 50.1 %, and 16.4 %, respectively. This is accompanied by an excellent performance in terms of production cost, net present value, and internal return rate at 792.5 USD/t, 173.4 USD/t, and 19.4 %, respectively. Substantial environmental and economic benefits can be gained by coupling renewables in the form of using green hydrogen from solar and wind power to synthesize methanol. Particularly, life cycle carbon emissions and resource scarcity impacts are reduced by 23.4 % and 22.4 %, respectively, exceeding the reduction in technological progress. However, coupling renewables increases the life cycle energy consumption to 154.5 GJ/t, counteracting the benefits of technological progress. Our results highlight the importance of technological progress and coupled renewables for enhancing the sustainability of the CTO industry.

An environmental perspective of energy consumption, overpopulation, and human capital barriers in South Asia

Prior literature is substantive in highlighting the nexus between pollutant and socio-economic predictors; however, the role of human interaction has not been sufficiently explored. Thus, the present study examines the validity of the environmental Kuznets Curve (EKC) hypothesis in the presence of energy consumption, overpopulation, and human capital index in five South Asian countries. It employs fixed effects, random effects, and dynamic panel causality techniques with a set of panel data from 1972 to 2021. The baseline results validate the existence of the EKC hypothesis in the recipient panel. Nevertheless, the findings reveal that energy consumption and population density have positive effects, while human capital has negative impacts on CO2 emissions. Furthermore, the study observes that energy consumption and per capita GDP have a significant causal link with CO2 emissions, whereas CO2 emissions are evident to have causality with population density and human capital index. The results are robust and suggest that the consolidation of an effective regulatory framework and technological improvements are substantial measures to improve environmental quality in South Asia. Moreover, allocating sufficient resources to uplift contemporary educational and health status would be imperative to improving environmental quality as aspired to by the Paris Agreement.

Impacts of workplace automation on energy poverty: The new challenge of achieving SDG 7 in the context of technological revolution

This paper systematically examines how workplace automation impacts energy poverty from a demand-side perspective, revealing a new challenge for Sustainable Development Goal 7 (SDG 7) in the context of technological revolution. Our research demonstrates that workplace automation significantly increases household energy poverty. This finding is robust when using the instrumental variable approach to tackle endogeneity, as well as employing different automation and energy poverty measures, placebo tests, and machine learning methods for robustness checks. Automation's impact mechanism is that it reduces people's income and work-related social capital, thus exposing households to higher risks of energy poverty. Moreover, its consequences are more prominent for rural households, less educated people, non-migrants, those without labor contracts, non trade-union members, and out-of-system workers. Thus enhancing human capital, promoting free movement of workers, and providing better labor protection contribute to weakening the adverse impact of the technological shock. Meanwhile, we find that improving the price reasonability, stability, security and accessibility of energy supply can also mitigate the negative effects of workplace automation on household energy consumption. In the dual context of the fourth technological revolution promoting industrial automation as well as the increasing urgency to achieve SDG 7, findings of this paper have important policy implications.

Electricity demand analysis and forecasting: The case of GADA special economic zone

Ethiopia is a country in East Africa experiencing significant economic growth in recent years, with an increasing electricity demand. Ensuring sustainable and efficient energy for newly developed industries and economic zones is crucial. In this study, a 15-year electric power demand forecast for the new economic zone under construction is conducted. The electrical power demand forecast is done for the year 2025-2040 by using bottom-up forecasting approach for three different scenarios. Long-range Energy Alternatives Planning (LEAP) system software is used to analyze residential, industrial, and general business sector electric power demand. The analysis of the assessed scenario shows that the economic zone's electric power demand increases by 52.2 % from the base year 2025-2040 for the baseline scenario, due to anticipated rapid urbanization, growth in population, economic expansion, and anticipated political stability. Compared to the baseline scenario, the total power demand shows a growth of 68 % from the forecast year (2025) to 2040 for the aggressive scenario, which ensures sustainable and efficient energy options that can draw businesses from both domestic and international baselines. In contrast, the total power demand in the conservative scenario shows a growth of 30.3 % from the base year (2025) to 2040. This reduction in demand compared to the two scenarios indicates a reflection of how much electricity power demand could be if certain development conditions failed to be realized in the economy. In general, both results show a rapid increase in power demand compared to the base year. To address this increasing demand, a supply-side demand analysis can be done for reference and aggressive scenarios. The analysis result indicated that by 2040, supply-side demand from the national grid will increase by 93.5 % and 175.9 % for reference and aggressive scenarios, respectively, compared to the base year 2025 demand. Due to the huge gap between the supply and demand in the country, onsite off-grid generation can be considered to cover 25 % of the demand in the economic zone. Hence, with the support of off-grid generation, the demand from the national grid was reduced to 45 % and 107 % for reference and aggressive scenarios with the support of onsite generation. Hence, this research clearly shows that there is a serious need for large scale electricity generation and distribution planning and preparation to meet the continually increasing electric power demand in a sustainable manner to accommodate the growth and change required to develop the modern economic zones in the country.

An integrated economic, energy, and environmental analysis to optimize evaluation of carbon reduction strategies at the regional level: A case study in Zhejiang, China

China plays a crucial role in responding to global climate change. Provinces are the main sources of energy consumption and greenhouse gas emissions in China's economic and social development. However, it is still unclear how to achieve dual-carbon goals by formulating and implementing local policies to adapt to climate change. In this study, we take Zhejiang Province in China as the research object, based on the LEAP (Low Emissions Analysis Platform) model to construct four social scenarios under different policies, comprehensively considering regional economic characteristics, population, and energy consumption patterns. The results show that to achieve Zhejiang Province's goal of carbon peaking by 2030 while maintaining steady economic growth, additional measures are required to reduce energy consumption intensity or improve the power generation structure. Otherwise, energy demand will increase to 228.06 million tonnes of coal equivalent and carbon emissions will be 487.76 million tonnes in 2050. Moreover, developing clean energy and promoting CCUS technology can continuously reduce carbon emissions to 293.59 and 210.76 million tonnes respectively. The economic viability of CCUS power generation is contingent upon the development of carbon taxes in the future. Once the growth rate reaches 7.2%, power cost will be 167.77 billion RMB and CCUS will become economically advantageous in 2050.

Integrating wet stirred-bead milling for Tetraselmis suecica biorefinery: Operating parameters influence and specific energy efficiency

Stirred bead milling proved to be an efficient cell destruction technique in a biorefinery unit for the extraction of over 95 % of proteins and 60 % of carbohydrates from the green marine microalga Tetraselmis suecica. Optimum conditions, expressed in terms of metabolite yield and energy consumption, were found for average values of bead size and agitator rotation speed. The higher the microalgae concentration, up to 100 g.L-1, which is adequate for biofilm algae growth in an industrial unit, the more efficient the cell destruction process. Cell destruction rates and metabolite extraction yields are similar in pendular and recycling modes, but the pendular configuration reduces the residence time of the suspension in the grinding chamber, which is less costly. With regard to the cell destruction mechanism, it was concluded that bead shocks first damage cells by permeabilizing them, and that after a longer period, all cells are shredded and destroyed, forming elongated debris.

Electrochemically enhanced activation of Co3O4/TiO2 nanotube array anode for persulfate toward high catalytic activity, low energy consumption, and long lifespan performance

Advanced oxidation processes (AOPs) can directly degrade and mineralize organic pollutants (OPs) in water by generating reactive oxygen species with strong oxidizing ability. The development of advanced electrode materials with high catalytic performance, low energy consumption, no secondary pollution, and long lifespan has become a challenge that must be addressed in this field. A heterojunction catalyst loaded with Co3O4 on TDNAs (Co3O4/RTDNAs) was designed and constructed by a simple and efficient pyrolysis (Co3O4/TDNAs) and electrochemical reduction. Co3O4 can be uniformly distributed on the inner wall and surface of the TiO2 nanotubes, enhancing the specific surface area while forming a tight conductive interface with TiO2. This facilitates rapid transmission of electrons, thereby assisting Co3O4 in quickly activating PS to form reactive oxygen species. The Ti3+ and Ov generated in Co3O4/RTDNAs can significantly improve the electrocatalytic degradation of OPs. Also, the interface formed by Co3O4 and RTDNAs will effectively suppress Co2+ leakage, thereby reducing the risk of secondary pollution. When the reaction conditions were 1 mM PMS (PDS) and a current density of 5 mA/cm2 in the EA-PMS (PDS)/Co3O4/RTDNA system, 30 mg/L TC can achieve 83.24 % (81.89 %) removal in 120 min, with very low cobalt ion leaching, while the energy consumption was reduced significantly. Therefore, EA-PS/Co3O4/RTDNA system has strong stability and a high potential for treating the OPs in AOPs.

Unraveling the environmental Kuznets curve: interplay between [Formula: see text] emissions, economic development, and energy consumption

The study investigates the complex interplay among [Formula: see text] emissions, energy consumption, and economic growth in China, employing the Environmental Kuznets Curve (EKC) framework to analyze the dynamics from 1990 to 2022. The research contributes to the urgent need for sustainable development by filling important gaps in comprehending China's specific challenges and potential and considering the relationship between economic advancement and environmental quality. This study utilizes advanced econometric tools, including the AutoRegressive Distributed Lag model, Vector Error Correction Model, and AutoRegressive Integrated Moving Average, to comprehensively examine the complicated relationship between variables, considering both short-run and long-run dynamics. The study supports the EKC concept, suggesting that targeted measures can reduce environmental degradation as China's economy advances. Strategic policy recommendations include emission reduction targets, investments in green technologies, and promoting sustainable consumption patterns. Furthermore, transitioning from fossil fuels to cleaner energy aligns with global climate objectives. This research provides valuable insights for policymakers, emphasizing the interconnected nature of energy consumption, [Formula: see text] emissions, and economic growth in shaping China's sustainable future.

Exploring asymmetric influence of R&D expenditures on CO2 emissions in China: evidence from nonlinear ARDL model

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China.

The existence of environmental Kuznets curve: Critical look and future implications for environmental management

Against the backdrop of the great challenge of climate change and growing global environmental concerns, this study deals a systematic literature review of research related to Environmental Kuznets Curve (EKC) from 1991 to 2023, details the background, definition, significance, critiques, theoretical foundations and model specifications of EKC, and summarizes the data, variables, econometric methods and findings used in over 100 EKC studies. This study focuses on EKC studies that examine the relationship between energy consumption, economic growth and environmental degradation, with most of the studies reviewed using global pollutants (carbon emissions) to measure the level of environmental degradation. This study found that EKC still has great research potential, and with the development of energy diversification, energy consumption in EKC studies have been further subdivided into renewable or non-renewable energy consumption; innovative EKC studies in the last few years have favoured the use of novel environmental and economic indicators and econometric method, and have validated the existence of EKC at the sectoral level rather than the national level. Finally, the present study summarizes the development and innovations of EKC and provides suggestions for future research aimed at advancing the development of EKC and environmental management.

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015-2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008-2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

Effects of ohmic heating with different voltages on the quality and microbial diversity of cow milk during thermal treatment and subsequent cold storage

Ohmic heating (OH), an innovative heating technology, presents potential applications in the pasteurization of liquid foods. Therefore, the study was conducted to evaluate the effect of OH at various voltage gradients (10 V/cm, 12.5 V/cm, and 15 V/cm) and water bath (WB) on microbial inactivation, physicochemical and sensory properties and microbial flora of pasteurized milk. Results indicated that OH with higher voltage could effectively inactivate microorganisms in milk, requiring less heating time and energy. Moreover, OH treatment at higher voltages could decelerate lipid oxidation and better maintain the sensory quality and essential amino acids content of milk. Additionally, all treatments significantly altered the microbial community, and during storage, the microbial community in milk treated with 10 V/cm and 12.5 V/cm OH remained relatively stable. OH treatments with voltage gradients exceeding 12.5 V/cm could effectively inactive microorganisms and maintain the quality attributes of milk.

Analysis of the carbon emissions trend in European Union. A decomposition and decoupling approach

This work is aimed to investigate the carbon emissions trend in the European Union. Logarithmic Mean Divisia Index and Tapio's methodology are used for decomposing the carbon emissions and investigating the decoupling factors respectively. Seven indexes are identified, namely carbon intensity of the energy sector, energy consumption structure, energy intensity, climatic factor, Gross Domestic Product per Capita, population distribution, and population evolution. These indexes are then grouped in three macro-categories, specifically technical factors, climatic effect, and socio-economic factors. The study covers the period 1995-2019 and considers EU 27 countries at an aggregate and individual level. Carbon emissions in EU 27 reduced of 689 Mt from 1995 to 2019. Technical factors are responsible for a decrease of 1723 Mt, the climatic effect determines a reduction of 362 Mt, whereas socio-economic factors cause an increase of 1397 Mt. The Strong Decoupling status is achieved in EU 27 in the period 1995-2019 with a decoupling index equal to -0.4. This means that carbon emissions reduced while Gross Domestic Product increased. To provide more precise insights, the paper also presents analyses at individual country level and the splitting in five temporal sub-periods.

Evidence from the energy-technology-growth nexus: A new study based on technology-minerals based complexity index

The increasing trend in sustainable economic growth over the last few decades has elevated the energy demand, technological innovation, and access to minerals resources are contributing well to economic development. This article investigates the nexus among minerals resource complexity, energy consumption, technology, and economic growth by employing autoregressive distributed lag and vector error correction techniques for Pakistan from 1995 to 2021. Following thorough research, the long-term results show that an important 9.73 points of economic growth result from every 1 % increase in the complexity of natural resources. On the other hand, technology and energy use negatively affect economic growth, causing drops of -0.03 and -12.9 points, respectively. One-way causality was noted between mineral resources' complexity and economic growth. Moreover, a one-sided causality effect was also confirmed between energy use, technology, and economic growth. Additionally, it was predicted that there is a neutral causality between mineral resources and technology. Corresponding to this, technology and energy consumption have a bidirectional causal relationship. These results imply that energy consumption, technological advancements, and mineral resources contribute as major economic growth drivers and can improve environmental quality.

The synergistic effects of PM2.5 and CO2 from China's energy consumption

PM2.5 and CO2 emissions are of the same origin. Under the double pressure of PM2.5 and CO2 emissions reduction, PM2.5 and CO2 synergistic emissions reduction is an available way to achieve PM2.5 and carbon reduction. Previous studies had shown that reducing fossil energy consumption could decrease PM2.5 and CO2 emissions. The LEAP-China model and three scenarios namely the baseline scenario (BAS), the carbon peaking scenario (CPS) and the carbon peaking and carbon neutrality goals scenario (CCS) were developed to project energy consumption, PM2.5 and CO2 emissions in China during the period of 2021-2060. Then the synergistic effects of PM2.5 and CO2 were assessed using the synergy effects coordinate system (SECS) and the emissions reduction elasticity coefficient (EREC) method. The consequences demonstrated that: (1) the non-fossil energy consumption would dominate energy use and be the largest PM2.5 and CO2 emissions reduction from energy consumption in the CCS. (2) In the CCS, PM2.5 and CO2 emissions from energy consumption would have a significant synergistic effect on emissions reduction during 2020-2060. The transformation of the energy use mix should be accelerated and the energy use efficiency should be improved. Regular assessments of the synergistic effects of PM2.5 and CO2 should be conducted.

Exploring the impact of public investment on income, energy consumption, and CO2 emissions in ASEAN: new insights from a panel cointegration approach

Policy adjustments can help strike a balance between economic growth and environmental sustainability, which has increasingly been the heart to nations and regions throughout the World. This paper examines how public investment affects economic growth, energy consumption, and CO2 emissions in eight ASEAN countries: Cambodia, Myanmar, Malaysia, Indonesia, the Philippines, Singapore, Thailand, and Vietnam. Extension of a Cobb-Douglas production function and application of panel cointegration techniques reveal bidirectional Granger causation between public investment and both private development and CO2 emissions from 1980 to 2019. Public investment Granger causes energy usage, the opposite does not hold statistically. More findings from pooled mean group estimations show a mean-reversion dynamic that corrects disequilibria by 14% yearly. State investment crowds in private sector growth, energy use, and carbon footprint. It also finds an inverted U-shaped relationship between public investment and energy consumption, and a U-shaped relationship between public investment and CO2 emissions, indicating complex regional interactions. It is suggested the implementation of public investment policies that enrich green infrastructure projects to foster growth while minimizing environmental impacts, and encourage a strategic approach to public investment for prioritizing environmental sustainability and thus, achieving Sustainable Development Goals 7 to 9 and 11 to 13 in this region.

Optimum drying conditions for ginger (Zingiber officinale Roscoe) based on time, energy consumption and physicochemical quality

The effect of ultrasonic pre-treatment on moisture removal characteristics of ginger in a convective dryer was investigated. The slabs were dried by practicing sonication durations of 0, 15 and 30 min at different levels of the air temperature and velocity. Following increasing the sonication duration and air temperature, required time and energy to dehydrate the samples were decreased. The pre-treatment played important role in improving rehydration capability and surface color retention in the dried gingers. Content of the main volatile component (α-Zingiberene) was not influenced by the sonication. Mean values for the phenolic contents and antioxidant activity at sonication duration of 0, 15 and 30 min were determined to be 18.93, 18.15 and 17.49 GAE/g dry matter and 83.57, 78.33 and 74.58 %, respectively. The desired values for the temperature, velocity and sonication duration were revealed to be about 66 °C, 3 m/s and 20 min, respectively.