Exploring the impact of economic growth and energy consumption on SO_(2) emissions in China based on the Environmental Kuznets Curve hypothesis

This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.

Smart Building Design to Improve the Energy Consumption at an Office Room

Buildings are becoming smarter as a result of a variety of advanced technologies that enable energy management, optimal space utilization, and smart surveillance for safety, among other things. Energy-efficient smart building ideas and execution are of great interest and top priority due to the building’s occupants’ misused and high-power consumption. This paper addresses the design and execution of an energy management system that includes a solar power system for generating power for the building’s needs and a PIR-based automation system for efficient power use. This project was carried out at the Military Technological College (MTC) in Muscat, in the system engineering department’s offices. This project seeks to generate power for the building’s energy needs using solar photovoltaic panels and reduce energy consumption within the office using a PIR-based automation system. The results demonstrate that after the breakeven point (the time it takes to recoup the initial investment), it can provide power to the building for another 17 years. The calculations and practical results presented in this study approve that the system is extremely helpful.

Thermal comfort assessment and energy consumption analysis of ground-source heat pump system combined with radiant heating/cooling

A new ground source heat pump system combined with radiant heating/cooling is proposed, and the principles and the advantages of the system are analyzed. A demonstration of the system is applied to a rebuilt building： Xijindu exhibition hall, which is located in Zhenjiang city in China. Numerical studies on the thermal comfort and energy consumption of the system are carded out by using TRNSYS software. The results indicate that the system with the radiant floor method or the radiant ceiling method shows good thermal comfort without mechanical ventilation in winter. However, the system with either of the methods should add mechanical ventilation to ensure good comfort in summer. At the same level of thermal comfort, it can also be found that the annual energy consumption of the radiant ceiling system is less than that of the radiant floor system.

Comparison of Energy Consumption of the 12 Classroom Typical School Buildings in Selected 4 City in Turkey

School is a special place where students come together to become productive individuals of society,acquire basic skills and acquire citizenship knowledge.With the introduction of the new education system(4+4+4)in Turkey in 2012-2013,some difficulties occurred in the spatial structure of the schools.After the new system,increasing number of students and decreasing student requirements have been tried to be solved with temporary solutions.At the same time that millions of students studying in primary schools all over Turkey have the same architectural feature as one type of architectural school project,regardless of the geographical and social situation began to be implemented in all parts of the city.Therefore,the increase in consumption varies depending on the geographical reasons where the type projects are implemented.Selected regions of the four thermal zones in Turkey for this research are provided below:1^st Thermal district in Antalya;2^nd Thermal district in Bursa;3^rd Thermal district in Elaz??;4^th Thermal district in Kars.The calculation of the energy consumption created by the above cities by means of BEP-TR program and comparing classes.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Room Temperature Synthesis of Vertically Aligned Amorphous Ultrathin NiCo-LDH Nanosheets Bifunctional Flexible Supercapacitor Electrodes

Developing a simple scalable method to fabricate electrodes with high capacity and wide voltage range is desired for the real use of electrochemical supercapacitors.Herein,we synthesized amorphous NiCo-LDH nanosheets vertically aligned on activated carbon cloth substrate,which was in situ transformed from Co-metal-organic framework materials nano-columns by a simple ion exchange process at room temperature.Due to the amorphous and vertically aligned ultrathin structure of NiCo-LDH,the NiCo-LDH/activated carbon cloth composites present high areal capacities of 3770 and 1480 mF cm^(-2)as cathode and anode at 2 mA cm^(-2),and 79.5%and 80%capacity have been preserved at 50 mA cm^(-2).In the meantime,they all showed excellent cycling performance with negligible change after>10000 cycles.By fabricating them into an asymmetric supercapacitor,the device achieves high energy densities(5.61 mWh cm^(-2)and 0.352 mW cm^(-3)).This work provides an innovative strategy for simplifying the design of supercapacitors as well as providing a new understanding of improving the rate capabilities/cycling stability of NiCo-LDH materials.

Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

NeTrainSim:a network-level simulator for modeling freight train longitudinal motion and energy consumption

Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the Ne Train Sim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator's performance. The first case study validates the model by comparing Ne Train Sim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safefollowing distances between successive trains. The next study highlights the simulator's ability to resolve train conflicts for different scenarios. Finally, the suitability of the Ne Train Sim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Analysis of the Energy and Environmental Sustainability of a Built Space System: The Case of Patte d’Oie University Campus in Ouagadougou

The aim of this study was to carry out a dynamic simulation of the energy and environmental performance of a built space system, with a view to assessing its energy and environmental class. The use of a simulation and modeling tool, supported by various methodological references, formed the basis of our approach. Adopting a systemic perspective, we described the structural and functional aspects of the systems making up built spaces, as well as the associated energy flows. Our approach was also based on a typology, taking into account typical days, structural and functional configurations at different scales and angles of observation. The analysis tool we developed in Java was applied to the built space system of the Patte d’Oie university campus in Ouagadougou. Annual electricity consumption was measured at 124387.34 kWh, closely aligned with the average annual electricity bill (125224.31 kWh), with a maximum relative deviation of 1%, followed by a carbon emission balance of 58337.66 kg eq CO2 per year. This validation confirmed the effectiveness of our tool. In addition, following the analysis of electricity consumption using our tool, the university campus was classified in energy class B and environmental class C. These results will be based on the emission factors of the energy mix of the West African Economic and Monetary Union (WAEMU) territory, with particular emphasis on Burkina Faso.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Optimising Energy Consumption in SD-DCN Networks (Software Defined-Data Center Network)

Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has emerged, Software-Defined Networking (SDN), which is an emerging technique that separates the control plane and the data plane of the deployed network, enabling centralized control of the network, while offering flexibility in data center network management. Some research work is moving in the direction of optimizing the energy consumption of SD-DCN, but still does not guarantee good performance and quality of service for SDN networks. To solve this problem, we propose a new mathematical model based on the principle of combinatorial optimization to dynamically solve the problem of activating and deactivating switches and unused links that consume energy in SDN networks while guaranteeing quality of service (QoS) and ensuring load balancing in the network.

Scenario-Based Assessment of the Water-Energy-Food Nexus in Kuwait: Insights for Effective Resource Management

The interdependency among water, food, and energy (WEF) in the GCC countries is strongly and closely interlinked, and is intensifying as demand for resources increases with population growth and changing consumption patterns, and are expected to be further compounded by the impacts of climate change. Therefore, integrated management of the three sectors is crucial to reduce trade-offs and build synergies among them. This paper presents a comprehensive framework to assess the WEF nexus in Kuwait as a representative case for the GCC countries. The framework consists of three main steps: 1) evaluating the influence of socio-economic development and climate change on water, energy, and food resources;2) generating scenario-based projections;and 3) conducting an extensive quantitative nexus analysis. The WEF interlinkages in Kuwait are modelled quantitatively using the Q-Nexus model, and current critical interdependencies are evaluated. Then, various WEF-Nexus scenarios were conducted for the year 2035 to explore the effects of management interventions in one sector on the other two sectors. The main findings are that per capita municipal water consumption is a major influencer on the WEF-nexus due to the heavy reliance on thermal desalination in municipal water supply in Kuwait, which is attributed to its energy intensity, financial cost, GHGs emissions, and environmental impacts on the marine and air environments. To reduce WEF trade-offs, mitigate risks, and build synergies among the three sectors, it is important to shift the current policy focus on supply-side management approach to the demand-side management and efficiency approaches.

Energy-efficient Approach to Minimizing the Energy Consumption in An Extended Job-shop Scheduling Problem

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production plarming and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed small- and large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

The relationship between energy consumption and economic growth and the development strategy of a low-carbon economy in Kazakhstan

Fossil energy is the material basis of human survival, economic development and social progress. The relationship between energy consumption and economic growth is becoming increasingly close. However, energy consumption is the major source of greenhouse gases, which can significantly affect the balance of the global ecosystem. It has become the common goal of countries worldwide to address climate change, reduce carbon dioxide emissions, and implement sustainable development strategies. In this study, we applied an approximate relationship analysis, a decoupling relationship analysis, and a trend analysis to explore the relationship between energy consumption and economic growth using data from Kazakhstan for the period of 1993-2010. The results demonstrated： （1） the total energy consumption and GDP in Kazakhstan showed a ＂U＂-type curve from 1993 to 2010. This curve was observed because 1993-1999 was a period during which Kazakhstan transitioned from a republic to an independent country and experienced a difficult transition from a planned to a market economy. Then, the economic system became more stable and the industrial production increased rapidly because of the effective financial, monetary and industrial policy support from 2000 to 2010. （2） The relationships between energy con- sumption and carbon emissions, economic growth and energy exports were linked; the carbon emissions were mainly derived from energy consumption, and the dependence of economic growth on energy exports gradually increased from 1993 to 2010. Before 2000, the relationship between energy consumption and economic growth was in a recessional decoupling state because of the economic recession. After 2000, this relationship was in strong and weak decoupling states because the international crude oil prices rose and energy exports increased greatly year by year. （3） It is forecasted that Kazakhstan cannot achieve its goal of energy consumption by 2020. Therefore, a low-carbon economy is the best strategic choice to address climate change from a global perspective in Kazakhstan. Thus, we proposed strategies including the improvement of the energy consumption structure, the development of new energy and renewable energy, the use of cleaner production technologies, the adjustment and optimization of the industrial structure, and the expansion of forest areas.

Impact of summer office set air-conditioning temperature on energy consumption and thermal comfort

To explore the relationship between summer office set air-conditioning temperature and energy consumption related to air conditioning use to provide human thermal comfort,a comparison experiment was conducted in three similar offices at temperatures of 24,26 and 28 ℃ respectively. A thermal comfort questionnaire survey was conducted. It is demonstrated that air-conditioner energy consumption at the set temperature of 28 ℃ is 113% and 271% lower than at 26 ℃ and 24 ℃,respectively. A linear relationship exists between air-conditioner energy consumption and the indoor and outdoor temperature difference. When comfortably dressed,over 80% of research participants accept the set temperature of 28 ℃. The regression analysis leads to a neutral temperature of 26.2 ℃ and an acceptable temperature of 28.2 ℃ for over 80% of the research participants subjects,indicating that the current 26 ℃ set temperature for offices in summer,required by Chinese General Office of the State Council,can be increased to 28 ℃. Moreover,analysis of predicted mean vote(PMV) index shows that a set temperature of 27 ℃,not 26 ℃,is sufficiently comfortable for office staff wearing long-sleeve shirts,long pants and leather shoes.

Energy consumption of electrooxidation systems with boron-doped diamond electrodes in the pulse current mode

A pulse current technique was conducted in a boron-doped diamond （BDD） anode system for electrochemical waste- water treatment. Due to the strong generation and weak absorption of hydroxyl radicals on the diamond surface, the BDD elec- trode possesses a powerful capability of electrochemical oxidation of organic compounds, especially in the pulse current mode. The influences of pulse current parameters such as current density, pulse duty cycle, and frequency were investigated in terms of chemical oxygen demand （COD） removal, average current efficiency, and specific energy consumption. The results demon- strated that the relatively high COD removal and low specific energy consumption were obtained simultaneously only if the current density or pulse duty cycle was adjusted to a reasonable value. Increasing the frequency slightly enhanced the COD re- moval and average current efficiency. A pulse-BDD anode system showed a stronger energy saving ability than a constant-BDD anode system when the electrochemical oxidation of phenol of the two systems was compared. The results prove that the pulse current technique is more cost-effective and more suitable for a BDD anode system for real wastewater treatment. A kinetic analysis was presented to explain the above results.

Impact of the green credit policy on external financing,economic growth and energy consumption of the manufacturing industry

China attempts to achieve energy conservation,emission reduction and environmental protection through the implementation of the green credit policy,but its implementation impact is still controversial.An important content of the green credit policy is to require banking and financial institutions to tighten the credit exposure of industries of‘high pollution and high energy consumption’and industries with overcapacity,so as to use economic leverage to curb their blind expansion and reduce energy consumption by controlling external financing.This paper examined the impact and the lingering effects of the green credit policy on external financing,economic growth and energy consumption in the manufacturing industry,which was most influenced by the green credit policy,from 2003 to 2016 by using the DID method.Furthermore,this paper estimated the dynamic endogenous relationships among external financing,economic growth and energy consumption with two-step system GMM model to investigate the influential path of the green credit policy.The results showed that:the green credit policy had a significant negative impact on the external financing of manufacturing industry,but its negative impact on the economic growth and energy consumption of manufacturing industry was not statistically significant,and the effect of the green credit policy had a dynamic feature of weakening with time.Additionally,in the manufacturing industry,there was a bilateral causal relationship between the energy consumption and economic growth of the control group industry and the processing group industry.There was a bilateral causal relationship between the economic growth and external financing of the control group industries in the manufacturing industry.There was a unilateral causal relationship between the economic growth and external financing of the processing group industries in the manufacturing industry,while the external causality existed between the control group industries and the processing group industries in the manufacturing industry.The causal relationship between the financing and energy consumption was not statistically significant.At present,the transmission path of the green credit policy is that the green credit policy controls external financing,then affects economic growth and ultimately inhibits energy consumption,but the effectiveness of the path is not statistically significant.The conclusion of this paper provides policy reference and scientific basis for the adjustment and improvement of green credit.

Energy Consumption by Rural Households in Northern Hunan

This study was conducted to investigate the household energy consumption in rural districts in northern Hunan and to help explore the sustainable and ecological energy policy.Questionnaires were used to acquire the details of energy consumption,and the electricity equivalent calculation was used in the energy statistics in four villages.The energy consumption in these four villages is influenced by the economic condition,geographic position and landform and the local custom.The traditional biomass energy and coal briquette are the primary energy source for cooking and heating,but they are used in a very low efficiency and result in poor IAQ.For sustainability,further measures should be taken to optimize the energy consumption with the efficient use of biomass energy,coal and electricity.