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.

Progress in membrane distillation processes for dye wastewater treatment: A review

Textile and cosmetic industries generate large amounts of dye effluents requiring treatment before discharge. This wastewater contains high levels of reactive dyes, low to none-biodegradable materials and chemical residues. Technically, dye wastewater is characterised by high chemical and biological oxygen demand. Biological, physical and pressure-driven membrane processes have been extensively used in textile wastewater treatment plants. However, these technologies are characterised by process complexity and are often costly. Also, process efficiency is not achieved in cost-effective biochemical and physical treatment processes. Membrane distillation (MD) emerged as a promising technology harnessing challenges faced by pressure-driven membrane processes. To ensure high cost-effectiveness, the MD can be operated by solar energy or low-grade waste heat. Herein, the MD purification of dye wastewater is comprehensively and yet concisely discussed. This involved research advancement in MD processes towards removal of dyes from industrial effluents. Also, challenges faced by this process with a specific focus on fouling are reviewed. Current literature mainly tested MD setups in the laboratory scale suggesting a deep need of further optimization of membrane and module designs in near future, especially for textile wastewater treatment. There is a need to deliver customized high-porosity hydrophobic membrane design with the appropriate thickness and module configuration to reduce concentration and temperature polarization (CP and TP). Also, energy loss should be minimized while increasing dye rejection and permeate flux. Although laboratory experiments remain pivotal in optimizing the MD process for treating dye wastewater, the nature of their time intensity poses a challenge. Given the multitude of parameters involved in MD process optimization, artificial intelligence (AI) methodologies present a promising avenue for assistance. Thus, AI-driven algorithms have the potential to enhance overall process efficiency, cutting down on time, fine-tuning parameters, and driving cost reductions. However, achieving an optimal balance between efficiency enhancements and financial outlays is a complex process. Finally, this paper suggests a research direction for the development of effective synthetic and natural dye removal from industrially discharged wastewater.

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.

The need for scientific-area-related indicators for effective energy planning in higher education institutions

The quest for improving energy efficiency is transversal to all areas of society. Higher education institutions represent an important sector in this quest due to their high demand, but also for the role model that they can play in educating energy-efficient citizens and piloting new approaches and experiences. Thus, decreasing energy consumption in higher education institutions, in addition to reducing the carbon footprint, contributes to ameliorating countries' energy bills, and, most importantly, contributes to a more sustainable society. The purpose of the paper, based on the energy consumption of the University of Minho, Portugal, between 2007 and 2022, is threefold: first, to evaluate how energy consumption and associated carbon footprint indicators have performed under a sustainable strategy program, second to reflect on total energy and specific energy indicators, and lastly to emphasize the need to improve energy metering and planning systems to account for the distinctive needs of the different scientific area buildings. This is not only relevant but also rare to find in scientific literature. Findings suggest that UMinho's energy consumption is in line with the numbers reported in the literature. Moreover, detailed indicators, specified by scientific area building, show diverse patterns in energy use, demonstrating the limitations of an overall analysis of buildings in the university campi. The results show that energy efficiency improved as a result of the implemented action plan, and demonstrate the need for detailed and specific indicators that reflect the different needs of each scientific area. The results provided by this refinement call for the design of tailored initiatives to decrease energy consumption, since they allow the planning of specific measures and programs for different energy use patterns, and therefore improve their efficiency. Finally, the preliminary results of the analysis of building specific energy use point to the need for more detailed data on hourly and daily consumption and academic term given the relative contribution of users' behaviour.

Receive wireless sensor data through IoT gateway using web client based on border gateway protocol

One of the significant topics in the field of the Internet of Things (IoT) pertains to the interaction and information sharing among people. The utilization of the Border Gateway Protocol (BGP) stack enhances the integration of web protocols and sensor networks, leading to greater accessibility. However, the BGP protocol stack introduces substantial overhead to messages transmitted at each layer, resulting in increased data overhead and energy consumption in networks by several orders of magnitude. This paper proposes a method to reduce the overhead on small and medium-sized packets. In multi-temporal networks utilizing BGP, scheduling and aggregating BGP packets at sensor nodes help achieve specific objectives. Various research methodologies and measures are employed to facilitate this, including request classification, BGP response prioritization within the network, determination of maximum acceptable delay, and overall network management. Synchronization and temporal integration of received messages at sensor nodes are performed, considering the maximum allowable delay for each message and the availability of the destination to process the accumulated messages. The evaluation results of the proposed method demonstrate a significant reduction in energy consumption and network traffic, particularly in monitoring applications within multi-stage networks. The protocol stack used is derived from the BGP standard.

Vacuum freeze dryer technology for extending the shelf life of food and protecting the environment: a scenario study of the energy efficiency

This study focused into vacuum freeze dryer technology for increasing food shelf life in a drying food technology. The determinants of energy consumption increase as the energy density of food production and storage increases. Reducing the amount of energy used for drying, freezing, chilling, refrigeration, and air conditioning is becoming more important. The objective of this study was to extend food's shelf life utilizing creative and novel technical approaches, such as vacuum freeze-drying's energy-efficient process. Despite being a part of this investigation, the vacuum freeze drier was created using environmentally benign energy sources. To minimize the carbon footprint of food preservation, it is essential to use eco-friendly energy sources in chilling storage. According to the first law of thermodynamics, the energy efficiency at 1 atm pressure and 25 [°C] temperature (neglecting potential and kinetic energies) in the dead state is calculated under thermal equilibrium conditions. In this study, the energy efficiency was shown according to 5 different scenarios. The results of energy efficiencies are as follows: η1 is from 14.3 to 21.4%, η2 is from 20.7 to 31.0%, η3 is from 27.3 to 40.9%, η4 is from 32.1 to 48.1%, and η5 is from 34.6 to 51.9%, respectively. This analysis demonstrates that the energy efficiency improved from 12 to 18 h. In this study, optimizations with scenarios were employed considering vacuum freeze-drying technology in the plant with sustainable energy sources can considerably improve food shelf life while limiting our environmental impact.

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.

Stability and energy consumption analysis of arctic fleet: modeling and simulation based on future motion of multi-ship

Ensuring the safety of Arctic shipping and preserving the Arctic ecological environment are emerging as key challenges in the shipping sector. Ship collisions and getting trapped in ice are frequently occurring under dynamic ice conditions due to the Arctic environment, making research on ship navigation in Arctic routes significant. Leveraging ship networking technology, we developed an intelligent microscopic model which considered factors such as the future motion trends of multi-ships in front and the influence of pack ice, and carried out a stability analysis of the model utilizing linear and nonlinear methods. Additionally, the accuracy of the theoretical results was further validated through simulation experiments with diverse scenarios. The conclusions manifest that the model can magnify the anti-disturbance ability of traffic flow. Additionally, the problem of energy consumption due to ship speed is explored, and it is determined that the model has a positive intention in reducing speed fluctuations and ship energy consumption. This paper highlights the potential of intelligent microscopic models in studying the safety and sustainability of Arctic shipping routes, providing targeted initiatives to improve safety, efficiency, and sustainability in Arctic shipping.

On energy complexity of fully-connected layers

The massive increase in the size of deep neural networks (DNNs) is accompanied by a significant increase in energy consumption of their hardware implementations which is critical for their widespread deployment in low-power mobile devices. In our previous work, an abstract hardware-independent model of energy complexity for convolutional neural networks (CNNs) has been proposed and experimentally validated. Based on this model, we provide a theoretical analysis of energy complexity related to the computation of a fully-connected layer when its inputs, outputs, and weights are transferred between two kinds of memories (DRAM and Buffer). First, we establish a general lower bound on this energy complexity. Then, we present two dataflows and calculate their energy costs to achieve the corresponding upper bounds. In the case of a partitioned Buffer, we prove by the weak duality theorem from linear programming that the lower and upper bounds coincide up to an additive constant, and therefore establish the optimal energy complexity. Finally, the asymptotically optimal quadratic energy complexity of fully-connected layers is experimentally validated by estimating their energy consumption on the Simba and Eyeriss hardware.

Caffeine: a potential mechanism for anti-obesity

Obesity refers to the excessive accumulation of fat caused by a long-term imbalance between energy intake (EI) and energy expenditure (EE). Over recent years, obesity has become a major public health challenge. Caffeine is a natural product that has been demonstrated to exert anti-obesity effects; however, the mechanisms responsible for the effect of caffeine on weight loss have yet to be fully elucidated. Most obesity-related deaths are due to cardiovascular disease. Recent research has demonstrated that caffeine can reduce the risk of death from cardiovascular disease; thus, it can be hypothesized that caffeine may represent a new therapeutic agent for weight loss. In this review, we synthesize data arising from clinical and animal studies over the last decade and discuss the potential mechanisms by which caffeine may induce weight loss, focusing particularly on increasing energy consumption, suppressing appetite, altering lipid metabolism, and influencing the gut microbiota. Finally, we summarize the major challenges associated with caffeine and anti-obesity research and highlight possible directions for future research and development.

Degradation of reactive red (B-3BF) dye wastewater using UV irradiation (254/185 nm) with sodium persulfate in a pilot UV device

Two low-pressure ultraviolet (UV) lamps at 185/254 nm with sodium persulfate in a pilot UV device were utilized for the degradation of reactive red (B-3BF) dye wastewater compared with two UV lamps at 185/185 nm and two UV lamps at 254/254 nm. The degradation performances of UV irradiation (254/185 nm) with sodium persulfate under different degradation times, flow rates, initial pH, initial Na2S2O8 concentrations and initial dye concentrations were investigated. The experimental results illustrated that the degradation percentage of B-3BF dye could reduce to 90.42% with the energy consumption of 85.1 kWh/kg and the residual dye concentration of 1.92 mg/L by UV irradiation (254/185 nm) with initial Na2S2O8 concentration of 1.5 mmol/L and initial dye concentration of 20 mg/L. In addition, degradation performance of B-3BF dye wastewater by UV irradiation (254/185 nm) with sodium persulfate was more effective than those of UV irradiation (254/254 nm) and UV irradiation (185/185 nm). Therefore UV irradiation (254/185 nm) with sodium persulfate was promising for the degradation of B-3BF dye wastewater.

Characteristic evaluation and environmental validation of self-compacting concrete containing sandstone slurry waste for sustainable usage

This study aims to understand the impact of concrete ingredients on the environment. To analyze the effect of, three significant indexes have been taken into consideration, which are embodied carbon dioxide index (e-CO2), embodied energy consumption (e-energy), and embodied resource consumption (e-resource) index. The life cycle assessment (LCA) methodology has considered veto comprehending the probable application of sandstone waste in the form of a slurry (Sslurry) and powder (Spowder) for the development of self-compacting concrete (SCC). This study can be proven beneficial to evaluate the potential adverse effects from environmental and energy perspectives. One reference mix and eighteen design mixes of SCC have been designed and developed to perform an experimental program. An environmental impact comparison of the "hybrid" SCC was performed using the OpenLCA life cycle analysis software with Ecoinvent LCIA methods. The outcomes of this experimental program reveal that the partial replacement of pozzolana Portland cement (PPC) with Sslurry can reduce e-CO2 emission along with the e-energy and e-resource parameters. When Spowder was used as the partial substitution of fine aggregate (FA), only the e-resource index decreased, and e-CO2 and e-energy increased. Minimalist impact on the environment has been noticed when SCC is prepared with Sslurry and Spowder. A detailed LCA analysis study justifies the utilization of Sslurry and Spowder in SCC, which exhibits encouraging results concerning strength and quality. Hence, it was observed that Sslurry and Spowder in developing green and sustainable SCC with moderate strength characteristics are beneficial from an environmental impact perspective.

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.

Design and simulation of eco-friendly smartphone controlled forklift

The recent revolution in industrial technology increased the demand for unmanned forklifts that can be operated remotely. Unmanned forklifts eliminate the effort needed to train a highly qualified operator and reduce the accident rate due to driver fatigue. Currently, the operation of forklifts depends on either hydraulic systems or gasoline which has a negative impact on the environment. The increased awareness of the environmental threats urged the manufacturers to replace conventional forklifts with electrical ones. Unmanned electrical forklifts have a high cost that is considered a burden for developing countries, especially when being used in small warehouses. Thus, this paper presents an innovative approach for designing a semi-automated eco-friendly forklift suitable for small warehouses operated using a smartphone application. The forklift is designed to lift a maximum load of 200 N using a ball screw feed mechanism, characterized by its light weight and its ability to withstand corrosion. The structural stability of the forklift has been investigated using SolidWorks simulation. The designed model has been imported to MATLAB Simulink to estimate the suitable battery size required for forklifts' operation in addition to calculating the total energy consumed during one complete work cycle. It is found that only 6.7 % of the energy is dissipated which promotes the energy-saving capabilities of the designed forklift.

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.

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.

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.

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.

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.