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Smart homes are at the forefront of sustainable living, utilizing advanced monitoring systems to optimize energy consumption. However, these systems frequently encounter issues with anomalous data such as missing data, redundant data, and outliers data which can undermine their effectiveness. In this paper, an artificial neural network (ANN)-based approach for data imputation is specifically designed to deal with the anomalies in smart home energy consumption datasets. Our research harnesses the power of ANNs to model intricate patterns within energy consumption data, enabling the accurate imputation of missing values while detecting and rectifying anomalous data. This approach not only enhances the completeness of the data but also augments its overall quality, ensuring more reliable results. To evaluate the effectiveness of our ANN-based imputation method, comprehensive experiments were conducted using real-world smart home energy consumption datasets. Our findings demonstrate that this approach outperforms traditional imputation techniques like mean imputation and median imputation in terms of accuracy. Furthermore, it showcases adaptability to diverse smart home scenarios and datasets, making it a versatile solution for improving data quality. In conclusion, this study introduces an advanced data imputation technique based on ANNs, tailor-made for addressing anomalies in smart home energy consumption data. Beyond merely filling data gaps, this approach elevates the dataset's reliability and completeness, thereby facilitating a more precise analysis of energy consumption and supporting informed decision-making in the context of smart homes and sustainable energy management. Ultimately, the proposed method has the potential to contribute considerably to the ongoing evolution of smart home technologies and energy conservation efforts. [ABSTRACT FROM AUTHOR]

In this paper, we have investigated the implications of the threshold effect of changes in FDI inflows for the nexus between energy consumption and economic growth in eight under-researched sub-Saharan African countries for the period 1971--2016. The countries are Benin, Congo, Kenya, Nigeria, Senegal, South Africa, Sudan, and Zambia. Using the lag-augmented VAR (LAVAR) model (corrected for cross-sectional dependence), we develop an empirical framework tightly linked to the endogenous growth model that allows for a threshold effect of changes (strength and weakness) in FDI inflows on the nexus. Our findings show that the FDI inflows matter for the causal link between energy consumption and economic growth in some countries, although, for the cross-section as a whole, our bootstrap simulation supports the neutrality hypothesis. The overall results suggest that an energy demand policy, such as an energy conservation policy, should not cause any significant adverse side-effects to economic growth in those sub-Saharan African countries. Policy implications of the threshold effect for the nexus for individual sub-Saharan African countries are also provided. [ABSTRACT FROM AUTHOR]

Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th-50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces. [ABSTRACT FROM AUTHOR]

This paper uses data from the 2015 Residential Energy Consumption Survey to explore the extent to which renters' electricity use in the United States exceeds that of otherwise similar non-renters. Renting households are found to use approximately 9% more electricity than non-renters when controlling for location, socioeconomic, and many appliance-quantity controls. There are multiple factors that explain this extra electricity use, including inferior energy efficiency of appliances, behavioral factors, differences in bill payment responsibilities, and additional reliance by renters on electric space and water heaters. The paper finds that none of these factors are dominant. The phenomenon of renters' (conditionally) higher electricity use is thus best understood as one that emerges from multiple sources. [ABSTRACT FROM AUTHOR]

This paper examines the determinants of inequality in the distribution of CO2 emissions across U.S. regions. We implement a factorial decomposition of CO2 per capita based on extended Kaya factors, that is, carbon intensity of fossil fuel consumption, energy mix, energy intensity of GDP, economic growth in terms of labor productivity and employment rate. Results reveal that U.S. states display marked differences in most factors. We identify energy intensity as the main source of emissions inequality. Based on the within and between group inequality components we also explore the effect of geographical, geological, climatic and human development partitions of U.S. states' groups. Findings indicate that the within-group inequality had been the main contributor to the whole inequality. Finally, some economic policy implications are also discussed; explaining the unequal distribution of emissions is vital to establish differentiated targets and work towards successful mitigation proposals. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of women's intra-household bargaining power on household cooking fuel choice. It further analyzes the determinants of household energy spending after the decision to use a given fuel has been made. The results reinforce the important role women play in the household cooking fuel choice and energy transition from traditional to modern fuel. In addition, income and education are found to be crucial factors that influence both household cooking fuel choice and energy expenditure. These findings imply that energy transition policies need to consider gender dimension and women's intra-household bargaining power. [ABSTRACT FROM AUTHOR]

Reducing energy consumption and Greenhouse Gas (GHG) emissions is an essential part of the clean growth and climate change framework recently developed by the Canadian government, which emphasizes the importance of energy-efficient building constructions. In this paper, the effects of thermal mass and placement of the thermally massive layer within wall assemblies on the transient thermal performance of walls and energy performance of a case study office building were studied. Three climate conditions representative of the heating-dominated, temperate, and cooling-dominated climates were considered. As for the assessment of energy demands, two cases for the indoor air temperature were taken into account: (i) indoor temperature was maintained at 20°C throughout the year, and (ii) during summertime, there was a set-point of 24°C and a setback of 35°C during the rest of the day while during wintertime, the set-point and setback values were 22°C and 18°C, respectively. The cases were compared according to the resulting decrement factor, the time required to reach quasi-steady state conditions, amplitudes of changes of heat fluxes and indoor surface temperatures, and the energy demands. The results showed that, for the cases studied, the wall, for which the thermally massive layer is not directly exposed to the indoor and outdoor climate conditions, resulted in the lowest decrement factor, the minimum amplitude of changes of heat fluxes and indoor surface temperatures, and maximum time required to reach quasi steady-state conditions. As for the energy performance, on the other hand, the wall, for which the thermally massive layer is exposed to the interior and exterior climate conditions, performed best amongst the cases investigated. [ABSTRACT FROM AUTHOR]

Imperfect information on future energy costs can lower the demand for more energy efficient technologies, with clear implications for energy supply, emissions and climate change. These hypotheses are explored using a randomised discrete choice experiment for property rental decisions. Results show that when energy consumption is expressed in physical units (as per the current EU labels) the willingness- to-pay for energy efficiency improvements is small and marginally significant. While bimonthly energy cost information displayed in monetary terms has no effect on the valuation of energy efficiency, annual monetary energy cost information led to a significant increase. This is the first paper to compare short and long-term point of sale energy cost information for household property decisions. There are clear implications for labelling policy for properties--framing energy consumption according to long-term monetary cost increases the demand for energy efficiency. [ABSTRACT FROM AUTHOR]

Evolutionary Algorithms (EAs) are routinely applied to solve a large set of optimization problems. Traditionally, their performance in solving those problems is analyzed using the fitness quality and computing time, and the effect of evolutionary operators on both metrics is routinely used to compare different versions of EAs. Nevertheless, scientists face nowadays the challenge of considering the energy efficiency in addition to computational time, which requires studying the energy consumption of algorithms. This paper discusses the interest of introducing power consumption as a new metric to analyze the performance of standard genetic programming (GP). Two well-studied benchmark problems are addressed on three different computing platforms, and two different approaches to measure the power consumption have been tested. Analyzing the population size, the results demonstrates its influence on the energy consumed: a non-linear relationship was found between size and energy required to complete an experiment. This analysis was extended to the cache memory and results show an exponential growth in the number of cache misses as the population size increases, which affects the energy consumed. This study shows that not only computing time or solution quality must be analyzed, but also the energy required to find a solution. Summarizing, this paper shows that when GP is applied, specific considerations on how to select parameter values must be taken into account if the goal is to obtain solutions while searching for energy efficiency. Although the study has been performed using GP, we foresee that it could be similarly extended to EAs. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate bi-directional spillovers into residential and industrial sectors induced by energy efficiency improvement (EEI) in both the short- and long-term, and the impact of nesting structure as well as the size of elasticities of substitution of production and utility functions on the magnitude and the transitional dynamic of rebound effect. Developing a dynamic general equilibrium model, we demonstrate that residential EEIs spillover into the industrial sector through the labor supply channel and industrial EEIs spillover into the residential sector through the conventional income channel. Numerical simulations calibrated on the U.S. suggest that not taking into account these spillover effects could lead to misestimating the rebound effect notably of residential sector EEIs. We also demonstrate how the size and the duration of the rebound effect depend on the elasticities of substitution’s values. Numerical simulations suggest that alternative sets of value for the elasticities of substitution may give different sizable patterns of rebound effects in both the short- and long-term. In policy terms, our results support the idea that energy efficiency policies should be implemented simultaneously with rebound effect offsetting policies by considering short- and long-term economy feedbacks. As a consequence, they require considering debates about what type of policy pathways are more effective in mitigating the rebound effect. [ABSTRACT FROM AUTHOR]

Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top- 1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers. [ABSTRACT FROM AUTHOR]

This paper analyzes the nexus between energy consumption, financial development, and economic growth in twenty-one (21) sub-Saharan African (SSA) nations by using the nonlinear autoregressive distributed lag (NARDL) framework from 1990Q1 to 2014Q4. First, the study reveals that energy consumption and financial development have asymmetrical impacts on economic growth in most countries in the short and long term. Second, positive shocks to financial development favor economic growth in only a few nations compared to the negative shocks in the short term, whereas they have mixed effects in the long term. Third, we found that adverse shocks to energy consumption boost economic growth in several nations in the short term, unlike the positive shocks, but the scenario has reversed in the long term. We also found that gross fixed capital formation and labor force remain key factors promoting economic growth in many SSA countries, in contrast to the mixed effects of trade openness over time. Accordingly, our study recommends implementing energy-saving policies in specific SSA countries to stimulate sustainable development. Policymakers must embrace an effective credit allocation to the private sector supporting productive investments. Governments should also optimize domestic investments in physical capital, upgrade the labor force, and implement efficient strategies in international trade. These policy recommendations need to be implemented according to the unique socio-economic characteristics of each SSA country. [ABSTRACT FROM AUTHOR]

Following the European Union's implementation of Energy Performance Certificates (EPCs) for buildings, the capitalization of energy efficiency in transaction prices and rents has been subject to much research. This paper uses different identification strategies for the Norwegian residential sales (N = 750,000) and rental (N = 670,000) markets to highlight the endogeneity and methodological limitations associated with assessing the price effects of energy efficiency and the signaling effect of label adoption. We find that the valuation of energy efficiency is subject to unobserved location and quality bias, that labeling has immediate, short-run, and long-run price effects and that different effects are observed in different submarkets. We provide evidence that sample selection issues related to location and time, with methodological and data limitations, are essential factors that must be considered when assessing the effects of the EPC implementation. [ABSTRACT FROM AUTHOR]

The optimal control of a system governed by an elliptic equation has been widely applied in engineering, and it requires twice differentiability. Furthermore, the optimal control cannot effectively deal with unsmooth boundaries. Now, the condition will not be maintained for a long time because this paper suggests a fractal optimal control of a system governed by a fractal variational principle to deal with unsmooth boundaries. The new optimal theory has obvious advantages in low differentiability for an unsmooth boundary problem. The air conditioning in a room is used as an example to show how to maintain maximum comfortableness of the workplace and maximum efficiency of energy saving. [ABSTRACT FROM AUTHOR]

This paper is the first to investigate the relationship between the energy efficiency of dwellings, measured by the energy performance certificate (EPC), and utility cost inclusion in rental prices. First, we investigate potential drivers behind the decision to include utility costs in rents. We find that labeled dwellings are more likely to include utility costs and that this likelihood is higher among energy-effi- cient dwellings than among inefficient dwellings. Next, we surprisingly find that utility costs seem to be under-capitalized in energy-inefficient dwellings. These results are confirmed with the counterfactual decomposition approach. Overall, the findings indicate that the EPC labeling policy may be important for both landlord and tenant decision-making and may enhance market efficiency. [ABSTRACT FROM AUTHOR]

Robot swarm networking systems (RSNS) exhibit complex emergent behavior by using local control laws based on spatial information from nearby environment and adjacent robot agents. The consensus behavior of the RSNS depends on a set of parameters of robot agent algorithms or system parameters for their operation, issued mainly by the operator. The challenge in the RSNS is developing techniques for the operator to interact with the RSNS in order to make system behavior adaptive to changes in system configuration and for operator commands without having to handle them individually. Another challenge is saving energy consumption over the robot agents in the RSNS by reducing the number of information exchange between robot agents when the system configuration is spread out the network from the operator. To address these issues, this paper presents an energy-efficient control approach for system configuration propagation with self-triggering control. The proposed method controls the RSNS operation by indirectly propagating the system configuration within the framework of local rules. Moreover, a self-triggered propagation model is designed according to the convergence rate of configuration propagation in order to save and to balance energy consumption among robot agents in the RSNS. This model is then extended to an optimal timing control, where the operator determines its next input time without having to keep track of all the states of robot agents. Theoretical analysis and simulation results are performed to demonstrate the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Existing tariff schemes often fail to achieve basic economic objectives. They set prices per unit that either exceed or fall short the social marginal cost and produce unfair distributional outcomes. In many cases, electricity rates also contribute to unsustainable fiscal deficits due to the (almost) generalized electricity subsidies. Moreover, inefficient residential tariffs do not favor the adoption of green technologies and the investment in energy efficiency improvements. We argue that the efficient deployment of green technologies, and more generally, the clean energy transition, will require electricity tariff reforms. In this paper, we use household level data and hourly industry data from Mexico to show how more efficient pricing mechanisms (such as a two-part tariff scheme in the context of efficient nodal pricing), combined with well-design environmental regulations (e.g., net-metering schemes) and correctly targeted transfer programs (e.g., means testing mechanisms) can improve economic, social, and environmental outcomes significantly, all at once. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important policy in the current global response to climate change and has been widely recognized by various industries. In the process of promoting carbon neutrality, new energy plays a pivotal role. In this study, the definition and connotation of new energy and its role and specific operation in the energy transition of carbon neutrality are firstly explained. Promoting new energy development requires significant green and low-carbon investments. Taking China as an example, this paper analyzes the opportunities brought by the carbon neutral process to the field of green finance and analyzes the main features and development trends of green finance in China at present. Then this paper proposes policy recommendations to strengthen the development of green finance in China in terms of improving the green financial policy system, enhancing the supply capacity of green financial services, and optimizing the supporting environment for green financial development. Finally, this paper analyzes the measures and experiences of the United States in promoting low-carbon development and proposes countermeasures for China's low-carbon development on the basis of the five major relationships that need attention in China's carbon-neutral process. That is, strengthen the top-level design and improve the regulatory policy system; optimize the energy structure and increase the proportion of clean energy; optimize the industrial structure and reduce energy consumption in key industries; build a complete low-carbon technology system and promote low-carbon technology research and development and demonstration applications, and encourage local conditions to explore low-carbon development paths. The development of green finance can contribute to the advancement of new energy technologies, thus contributing to the achievement of carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Wool fabrics are preferred over synthetic and cellulosic fibers by consumers because of their good elasticity, warmth, and high moisture sorption. How to use new materials and new methods to break the bottleneck of high pollution and high energy consumption in wool dyeing and finishing, and develop new functional wool materials has become an urgent need of wool development. In this paper, wool is colored and functionalized with antistatic properties using one-step ecofriendly process by superfine graphene oxide (GO). The results of the assembly mechanism show that the adsorption thermodynamic behavior of GO on wool is more consistent with Langmuir model and the process is exothermic similar to the adsorption of conventional acid dyes on wool fibers. The kinetic behavior results indicated that adsorption behavior of GO on wool was identified, and the phenomenon was more in line with the quasi-secondary dynamics model. The antistatic test results showed that the antistatic performance of the wool fabric that was colored by GO was obviously improved and the half-life of the GO colored wool fabric could be as low as 0.17. The strategy of colored fabrics with GO and imparting additional functionality can provide a basis for the ecological processing and formation of wool fabrics with designed functions. [ABSTRACT FROM AUTHOR]

This paper studies the green single-machine scheduling problem that considers the delay cost and the energy consumption of manufacturing equipment and builds its integrated optimization model. The improved ant colony scheduling algorithm based on the Pareto solution set is used to solve this problem. By setting the heuristic information, state transition rules, and other core parameters reasonably, the performance of the algorithm is improved effectively. Finally, the model and the improved algorithm are verified by the simulation experiment of 10 benchmark cases. [ABSTRACT FROM AUTHOR]

The plug-in hybrid electric vehicle not only has the advantages of low emissions from electric vehicles, but also takes advantage of the high specific energy and high specific power of petroleum fuels, which can significantly improve the emissions and fuel economy of traditional vehicles. Studying its comprehensive energy consumption evaluation method is an important part of analyzing the economics of plug-in hybrid electric vehicles. This paper first puts forward the concept of statistical energy consumption and then proposes an innovative calculation method of plug-in hybrid electric vehicle energy consumption based on statistical energy consumption by referring to and analyzing the energy consumption test regulations of the United States, the European Union, and China. Given the two use case assumptions of charge depleting mode priority and charge sustaining mode only, considering the fuel consumption and the energy consumption that converts electrical energy consumption to fuel consumption, the probability density function of travel mileage distribution and energy consumption is derived. Finally, the interpretation and analysis of statistical energy consumption evaluation results are carried out. [ABSTRACT FROM AUTHOR]

The distributional impact of the low-carbon transition is an increasingly important topic both for academics and policymakers. Quantifying where the costs and benefits fall can provide greater insight into the equity and cost-effectiveness of government policies, and improve our understanding of household investment decisions. This paper provides new evidence on the distribution of returns from energy efficiency measures both over time and across household-type. A range of econometric techniques are applied to a database of over four million households over an eight year period to quantify heterogeneity, persistence and how these factors impact the relative cost-effectiveness of measures. Results suggest that more deprived households experience lower energy savings, the difference persists over time, and that significantly heterogeneity may be present across levels of deprivation and income deciles that can not be explained by differences in baseline consumption. Measures have been largely cost-effective but savings are much lower than previous policy evaluations using ex-ante estimates would suggest. [ABSTRACT FROM AUTHOR]

Under the dual goals of achieving carbon peak and carbon neutralization, it is of great practical significance to explore the impact of product information labeling on technological innovation. As an essential element in improving energy performance in consumer products, energy-efficiency labels (EEL) have played a vital role in the government's portfolio of energy-efficiency improvement, technological progress, and carbon emission mitigation. We estimate the extent of the inductive effects of varying patent types on the relationship between the EEL system and technological innovation in a panel differences-indifferences framework based on the panel data of energy-saving patents and electricity-saving patents from 1998 to 2013 in China. Results indicate that the EEL system helps firms improve the ratio of energy-saving and electricity-saving patents to water-saving patents, and the rate of energy-saving and electricity-saving patents to all patents in the region. In another word, the EEL has a significant directed technological inducing effect. As for the role of the heterogeneity of patent types, the positive effects of the EEL system on invention patents are significantly suppressed in patent-for-utility models. Thus, it is suggested to improve the existing EEL system, gradually expand the product coverage of the EEL system, and increase the protection scope of utility model patents for achieving technological progress and sustainable development of society. [ABSTRACT FROM AUTHOR]

Introduction: In the paper, we examine the energy consumption efficiency of specialized container diesel trucks engaged in container transportation at a seaport terminal. Objectives: Using the container terminal at Klaipėda in Lithuania as the background for the research, we produced an improved energy consumption model for measuring the theoretical energy consumption and regeneration of diesel trucks at the terminal and provide a comparative analysis. Methods: We created a mathematical model which describes the instantaneous energy consumption of the diesel trucks, taking into account their dynamic properties and the overall geometry of their routes—"Ship-Truck-Stack-Ship"—using the superposition principle. We investigated other critical parameters relevant to the model and provide a statistical evaluation of the transportation process using data from a case study of Klaipėda port, where we collected measurements of container transportation parameters using georeferenced movement detection and logs from wireless equipment positioned on the diesel-powered container trucks. Results: The modeling results showed that an instantaneous evaluation of energy consumption can reveal areas in the container transportation process which have the highest energy loss and require the introduction of new management and process control initiatives to address the regulations which are designed to decrease harmful industrial emissions and encourage novel technologies and thereby increase the eco-friendliness of existing systems. Conclusion: Based on the research results, the article can provide a reference for the estimation of diesel truck efficiency in seaport terminal operations. [ABSTRACT FROM AUTHOR]

Wireless sensor network is a collection of sensor nodes designed with different routing capabilities to operate on real-world applications. In extreme environments, real-time applications of wireless sensor network ensure exchange of data, a difficult one between the sensor nodes, when less resources are consumed. Therefore, researchers are developing a routing protocol including optimal routing procedures to increase the longevity of the networks. In this paper, an improved route extension architecture is developed in wireless sensor network environment. This Improved Greedy Perimeter Stateless Routing is proposed to offer an improved transmission coverage and reduced power consumption capability. It deploys a periodic broadcast of hello message (or control messages) including the positional information between the sensor nodes. The experimental result concludes that the Improved Greedy Perimeter Stateless Routing method achieves improved routing capabilities than the traditional hybrid protocols like LEACH and Greedy Perimeter Stateless Routing. [ABSTRACT FROM AUTHOR]

In order to reduce the energy consumption of the welding robot and ensure the cooperative movement of the robot joints, a trajectory planning method with optimal energy consumption based on improved sparrow search algorithm is proposed. Firstly, the trajectory planning model with optimal energy consumption is established based on the joint torque and angular velocity of the robot. To make the velocity, acceleration and jerk of each joint of the robot be bounded and continuous, the joint space trajectory is constructed with seventh degree B-spline curve. The total energy consumption of the robot is calculated by combining kinematic and dynamic parameters. On the basis of improved sparrow search algorithm, the time series corresponding to the optimal energy consumption is solved by using elite reverse learning, non-dominated sorting and Gaussian-Cauchy variation strategy, and then the optimal continuous motion trajectory of energy consumption is planned. The simulation results show that the proposed method can not only achieve continuous smooth control objective, but also effectively reduce energy consumption. [ABSTRACT FROM AUTHOR]

This study examines the relationship between financial inclusion, renewable energy, and CO2 emissions using data from 11 Middle East and North Africa (MENA) countries from 2004 to 2019. Evidence from fixed effects-ordinary least squares (FE-OLS), dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical correlation regression (CRR) showed that financial inclusion contributes significantly to decarbonization. Country-specific analysis indicated that financial inclusion is associated with mitigating CO2 emissions in Egypt, Israel, Qatar, and Tunisia while significantly spurring CO2 emissions in Algeria, Lebanon, and Saudi Arabia. In addition, renewable energy contributes significantly to decarbonization in MENA, especially in Algeria, Lebanon, Tunisia, and Turkey. We recommend that policies promoting financial inclusion and renewable energy usage would contribute to the attainment of the carbon-neutrality goal by MENA countries. [ABSTRACT FROM AUTHOR]

Iconic destinations are benchmarks for tourism development, but their effects on the environment are debatable. To highlight the tourism attractiveness factors of sustainability in the world's most visited destinations, we applied clustering and multiple regression to specific indicators for the period 2000–2020. We observed a relatively high heterogeneity in terms of sustainability, with destinations split into four clusters: C1 (France, Spain, Italy, Germany and UK), C2 (Mexico and Thailand), C3 (USA, China) and C4 (Turkey). Unsustainable factors in all destinations include the industry and construction sector, social insecurity, inflation and transport services development. Renewable energy consumption is sustainable, while economic growth, education and tourism indicators have antagonistic effects. The effects of tourism attractiveness factors on the environment have decision-making implications at all levels. The novelty of this analysis lies in the tourism attractiveness factors examined, and the results can help shape tourism development policies in balance with structural policies such as energy and environment. [ABSTRACT FROM AUTHOR]

As the manufacturing industry is the foundation of the national economy, many countries have made concerted efforts to promote the transition upgrading of manufacturing enterprises from political, industrial, and academic circles. This study employed content analysis to explore the transition upgrading factors for manufacturing enterprises from an energy source perspective. With the help of FsQCA (Fuzzy-sets qualitative comparative analysis), which can mine multivariate combination relationships using a small number of samples, this study quantitatively calculated the transition paths and energy source combinations of manufacturing enterprises. Three transition upgrading paths were proposed, including an innovation-oriented path, a business-oriented path, and an efficiency-oriented path. The results indicate that manufacturing enterprises can realize transition upgrading based on three key methods, including innovation resources and innovation activities, strategic layout, and production operation + network relationship (peripheral). Such a finding validated the rationality of the theoretical path design and improved the research depth and precision. Multiple case analyses of Huawei, Haier, and Lenovo reveal that manufacturing enterprises used three ways to promote transition upgrading: the joint action of innovation activities and innovation resources; the uni-directional causal effect of strategic layout adjustment to increase market value; and the coordination and matching role of network relations dominated by production and operation. We conclude that this study provides an effective decision-making basis and management reference for manufacturing enterprises, so that enterprises can choose an appropriate energy accumulation method and scientifically realize the transition upgrading. [ABSTRACT FROM AUTHOR]

This research aims to predict the cost and energy consumption associated with pocket and groove machining using the hybrid particle swarm optimization-artificial neurons network (PSO-ANN) algorithm and the response surface method (RSM). A parametric study was conducted to determine the best predictions by adjusting the swarm population size (pop) and the number of neurons (n) in the hidden layer. The results showed that machining strategies and sequences can have a significant impact on energy consumption, reaching a difference of 99.25% between the minimum and maximum values. The cost (C tot) and energy consumption (E tot) values with the PSO-ANN algorithm increased significantly by 99.99% and 92.41%, respectively, compared to the RSM model. The minimum mean square error values for E tot and C tot with the PSO-ANN models are 3.0499 × 10−5 and 4.6296 × 10−10, respectively. This study highlights the potential of the hybrid PSO-ANN algorithm for multi-criteria prediction and highlights the potential for improved machining of 2017A alloy. [ABSTRACT FROM AUTHOR]

In contemporary times, developed economies are adopting environmentally friendly initiatives such as green finance and energy efficiency. However, the factors affecting energy efficiency are widely explored, and green finance remains overlooked in the empirical literature. The present research examines the drivers of sustainable green finance in OECD economies during 2004–2021. The study uses several panel diagnostic tests and validates the mixed integration order of the variables. Still, the long-run equilibrium relationship is valid between financial inclusion, energy efficiency, human capital, foreign trade, composite risk, and green finance. Using panel autoregressive distributed lag model, the study found that financial inclusion, energy efficiency, foreign trade, and composite risk significantly improve green finance in the long run. However, only energy efficiency is effective in the short run. On the other hand, human capital exhibits a significant adverse influence on green finance. The long-run results are robust due to the significant estimates offered by panel dynamic ordinary least square. Besides, there exist one-way and two-way causal associations between variables. The study recommends improving the financial sector performance to enhance financial inclusivity, increase investment in the energy efficiency sector, and encourage trade in environmentally friendly initiatives. [ABSTRACT FROM AUTHOR]

A novel performance seeking control) method based on Beetle Antennae Search algorithm is proposed to improve the real-time performance of performance seeking control. The Beetle Antennae Search imitates the function of antennae of beetle. The Beetle Antennae Search has better real-time performance because of the objective function only calculated twice in Beetle Antennae Search at each iteration. Moreover, the Beetle Antennae Search has global search ability. The performance seeking control simulations based on Beetle Antennae Search, Genetic Algorithm and particle swarm optimization are carried out. The simulations show that the Beetle Antennae Search has much better real-time performance than the conventional probability-based algorithms Genetic Algorithm and particle swarm optimization. The simulations also show that these three probability-based algorithms can get better engine performance, such as more thrust, less specific fuel consumption and less turbine inlet temperature. [ABSTRACT FROM AUTHOR]

The study inspects the seven sectors of the Association of Southeast Asian Nations (ASEAN) economies to explore the impact of consumption of clean energy, green bonds, and green economic advancement on environmental, social, and governance (ESG) practices to attain sustainable development goals (SDGs). The ESG aspects are individually explored from 2011 to 2020. It is observed that the key determinants of ESG practices are green economic advancement, clean energy, and green financing. Moreover, these determinants positively and significantly track the ASEAN economies toward attaining SDGs. The determinants play a vital role in sustainable advancement even when explored individually using different regression models. The linkages between the explanatory and outcome variables remain consistent after controlling other variables like climate regulatory quality, foreign direct investment, and gross domestic product. The study provides solid implications for stakeholders, environmental activists, and governments of ASEAN economies. The findings also infer sustainable business practices via creating an association between ESG practices, green economy, clean energy, and green financing. [ABSTRACT FROM AUTHOR]

In recent years, the global business landscpae has witnessed a paradigm shift toward sustainable and responsible corporate practices. This transition has been particulalrly pronounced in the energy sector where companies are increasingly recongzing the importance of Non-Financial Reporting Initiatives (NFRI) in shaping their operational strategies. The current study endeavors to delive into the intricate relationship between NFRI and the Weighted Average Cost of Capital (WACC) for energy companies in Pakistan. The current study relied on Partial Least Square Structural Equation Modeling (PLS-SEM) technique to extract useful information about the study topic. The data collected for the period 1999 to 2020 from World Development Indicators. The findings of the study revealed that energy consuption factors are responsiblee for around 31.32% variations in WACC, while economic factors contribute 43.98% variations. The financial factors showed to have 35.72% variations in the WACC. The findings of current study revealed to implement policies fostering sustainable energy practices, robust economic growth, and prudent financial management to positively influence the Weighted Average Cost of Capital (WACC) for enhanced business competitiveness and investment attractiveness. [ABSTRACT FROM AUTHOR]

This study explores the optimization of kinetic facades to promote environmental sustainability in building designs, addressing the critical issues of high energy consumption and CO2 emissions prevalent in the construction sector. The focus is on achieving an intricate balance between maximizing natural daylight and minimizing solar radiation using innovative kinetic facade designs. Parametric modeling tools are utilized in the design process to experiment with various facade configurations. The effectiveness of these designs is then validated using both digital and physical prototypes, with their adaptability to diverse climatic conditions evaluated through dynamic simulations. A key component of the study is the application of the Wallacei plugin for Grasshopper, which assists in multi-objective optimization to determine the most effective facade aperture ratios. The results demonstrates a substantial reduction in solar radiation levels, with a 70% decrease on the first floor and a 76% decrease on the seventh floor, achieved by optimizing aperture ratios. The study concludes that optimizing kinetic facades significantly improves building performance compared to traditional glass facades, offering an effective balance between daylight enhancement and solar radiation reduction, influenced by seasonal changes. It also emphasizes the importance of factors such as building height and the surrounding environment in facade design. Overall, the findings highlight kinetic facades as a viable solution for improving building efficiency and occupant comfort, suggesting a promising avenue for advancements in architectural design and construction. [ABSTRACT FROM AUTHOR]

This study examines the relationship between climate risk and stock crash risk and the moderating effect of greenhouse gas emission trading scheme (ETS). Numerous studies have tested stock price crash risk measured by the negative skewness of return distributions in the areas of internal governance mechanism. While interest in environmental performance for sustainable growth of firms has increased, there are no studies on the effect of climate risk on stock crash risk. Thus, we find that climate risk (a firm's greenhouse gas emissions and energy consumption) increases stock crash risk, and the positive effect of climate risk on stock crash risk is weakened after introduction of the emission trading scheme. This study theoretically extends the literature on the empirical determinants of stock crash risk, and practically provides investors with proven information about whether climate risk is worth considering during investment decisions. Furthermore, at the level of government policy, we can suggest that a monitoring system is needed to mitigate potential information asymmetry problems in firm with high climate risk. [ABSTRACT FROM AUTHOR]

Climate change as a global challenge requires collective responses from stakeholders in society. As the main source of energy consumption generating greenhouse gases (e.g., CO2), firms increasingly share their problems and experiences regarding energy saving in interfirm knowledge communities. By distinguishing knowledge sharing from free‐riding, we investigate how firms that participate in an interfirm knowledge community for energy saving improve their energy efficiency. We use a unique panel dataset collected between 2001 and 2011 from the Energy Saving through Partnership program in South Korea. Our findings show that, within the community for energy saving, firms that share their knowledge through presenting their best practices improve energy efficiency to a greater extent (approximately 11.8–14.8%) than free‐riders. Our results suggest that the improvement in knowledge‐sharing firms' energy efficiency is attributed to relevant and tailored feedback gained from other participants. Further, we find that the understanding and activeness of other participants, which determine the quality and quantity of feedback respectively, significantly affect knowledge‐sharing firms' energy efficiency. Overall, our analysis has implications for firms on how they can contribute to a collective response to climate change through their collaborative activities in an interfirm knowledge community. [ABSTRACT FROM AUTHOR]

Although some studies have posited that sectoral growth could influence environmental pollution through energy consumption, the issue has not been explicitly and empirically investigated in the carbon-neutrality literature. Hence, this analysis fills the gap in the extant literature by employing the interaction models to ascertain the moderating role of energy consumption on the environmental impacts of the industrial, agricultural, financial, and service sectors in Malaysia. It also analyzes the marginal effects of sectoral growth on environmental pollution (i.e., ecological footprint and carbon emissions) at various levels of energy consumption. The Autoregressive Distributed lag technique utilized in this study found that the variables are cointegrated. The empirical estimations reveal that energy consumption plays a harmful moderating role on the impacts of the industrial and financial sectors on environmental pollution but does not aggravate the environmental impacts of the agricultural and service sectors. Besides, the marginal effects of the industrial and financial sectors on environmental pollution increase as the level of energy consumption rises in Malaysia. Based on the findings, this study highlights the policy implications and options. [ABSTRACT FROM AUTHOR]

We study a long‐term service agreement (LTSA) between an original equipment manufacturer (OEM) of a conventional power generator and a utility firm in the electricity supply chain. The OEM offers the LTSA to the utility firm, which specifies the service fee and the maintenance interval. The utility firm dynamically chooses among different resources (conventional, renewable, or emergency) to meet energy demand. An LTSA contracts on a generator's long‐term production schedule (i.e., the usage time and number of starts). We first characterize that the conventional generator's optimal operating mode (i.e., on or off) follows a two‐threshold policy, which shows a hysteresis phenomenon. Then, the optimal production from different resources can be obtained by minimizing the utility firm's cost of the current period. We prove that the OEM's optimal LTSA design on the maintenance interval and service fee can be solved sequentially, and capture the trade‐off between the service margin and the usage of conventional generator. Our numerical results show that the utility firm starts the conventional generator less often as the maintenance service fee of a start increases and the minimum conventional output decreases. The OEM has incentives to reduce the minimum output to make the conventional generator more flexible, but such improvement may not benefit the utility firm. Finally, increasing renewable penetration leads to more frequent cycling of the conventional generator and less conventional output. With more renewable generation and less conventional and emergency generation, higher renewable penetration reduces the utility firm's cost, the OEM's profit, and the total emission. [ABSTRACT FROM AUTHOR]

Energy consumption is one of the most important variables that have an impact on the environment. One of the nations in the world with the highest per capita electrical energy usage is the Kingdom of Saudi Arabia. Many attempts are being made in Kingdom of Saudi Arabia to lower energy consumption and electricity consumption to achieve sustainability. In this work, the data on the energy consumption of two mosques in Hail City were analyzed, and the opportunities for energy conservation and the use of solar energy were studied to make mosques sustainable. Annual energy use intensity was determined to be 100 and 121 kWh/m2 for the Al-Khashil and Al-Jamil mosques, respectively. While Al-Khashil's mosque envelope is insulated, energy efficiency measures implemented to the walls, roof, and windows of Al-Jamil's mosque resulted in reductions in energy consumption of 27%, 13%, and 6%, respectively. The most effective energy efficiency option is a heating, ventilation, and air conditioning system with a high energy efficiency ratio, which can reduce cooling demand by more than 30%. If the condition of Saudi Building Code 601 is met, then it has the potential to cut energy usage by 35.4% and 63.3% for Al-Khashil and Al-Jamil, respectively. Due to coronavirus disease 2019, Al-Khashil's electricity usage was reduced by 58,737 kWh, or 39.9%, in 2020 compared to 2019. When using data from RETScreen and ATLAS, there were inconsistencies of up to 28%, but for DesignBuilder, the findings were the closest to the billing data. The mosques Al-Khashil and Al-Jamil have a combined yearly photovoltaic energy output from the suggested systems of around 135.93 MWh and 33.98 MWh, respectively. For the mosques, Al-Khashil and Al-Jamil, the yearly yield factor and capacity factor were both 1887.9 kWh/kWp/year and 21.9%, respectively. The annual greenhouse gas emission reductions from photovoltaic systems for Al-Khashil and Al-Jamil were 102.9 tCO2 and 25.72 tCO2, respectively. Concerning economics, the following results were obtained: The levelized cost of energy of photovoltaic systems is 0.0901 SR/kWh (0.024 $/kWh); the net present value and internal rate of return for photovoltaic systems are not suitable as a result of the current prices and the system applied in the Kingdom of Saudi Arabia. If the electricity produced from photovoltaic systems is injected into the grid at a rate of 0.32 SR/kWh, which is comparable to the SEC tariff for the mosque or government sector, then the simple payback time is 5.14 years. [ABSTRACT FROM AUTHOR]

Background.: U.S. households produce a significant amount of greenhouse gas emissions, indicating a potential to reduce their carbon footprints from changing food, energy, and water (FEW) consumption patterns. Behavioral change to FEW consumption is needed, but difficult to achieve. Interactive and engaging approaches like serious games could be a way to increase awareness of possible measures, leading to more sustainable behavior at a household level. This study looks into the experiences and effects of a digital game for homeowners with the potential to reduce FEW resource consumption impacts. Intervention.: In this study, we developed and implemented a digital game to explore its potential to raise awareness of the consumption and conservation of FEW resources and the efficacy of conservation messages. This study aims to measure learning outcomes from game participation and to assess the suitability of the game for informing resource conservation actions. Methods.: We tested a proof-of-concept of a digital four-player game, called HomeRUN, with 28 homeowners. The data collected include homeowners' values and preferences with regard to FEW resources. The patterns of game actions are analyzed with an emphasis on the effectiveness of conservation messaging in informing household consumption behavior. Results.: About 65% of the respondents agree that they gained a better understanding of the greenhouse gas emission impacts of FEW resource consumption after playing the game. Over 57% of the respondents agree that the game experience would influence their future consumption behavior, while a quarter of the respondents are unsure. Overall, we demonstrate the HomeRUN game has potential as a tool for informing conservation efforts at a household level. [ABSTRACT FROM AUTHOR]

Sustainable economic development involves both improving the socio-economic quality of life in the present and improving environmental conditions for future generations. The main objective of the study was to investigate the impact of the determinant macroeconomic variables, including economic complexity, construction, energy consumption, and housing sector expenditures, on environmental changes in Iran over the period 1991 to 2019; using the autoregressive distributed lag (ARDL) model. The results show that at the macro level, an increase in the economic complexity index can reduce pollution in both the short and long term. The effects of further expansion of the housing sector and household energy consumption on pollution are positive and significant in both the short and long run. The error correction model (ECM = 0.65) shows that 65% of the imbalances in each period are corrected in the next period. Based on the obtained results, it is recommended to take serious measures to improve the structure of production and increase the country's economic complexity index; in other words, to produce goods with higher knowledge and technology and apply policies to improve the level of household energy consumption leading to air pollution reduction. Jel: Q40, Q48, Q50, Q52 [ABSTRACT FROM AUTHOR]

Multi-omic data mining has the potential to revolutionize synthetic biology especially in non-model organisms that have not been extensively studied. However, tangible engineering direction from computational analysis remains elusive due to the interpretability of large datasets and the difficulty in analysis for non-experts. New omics data are generated faster than our ability to use and analyse results effectively, resulting in strain development that proceeds through classic methods of trial-and-error without insight into complex cell dynamics. Here we introduce a user-friendly, interactive website hosting multi-omics data. Importantly, this new platform allows non-experts to explore questions in an industrially important chassis whose cellular dynamics are still largely unknown. The web platform contains a complete KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis derived from principal components analysis, an interactive bio-cluster heatmap analysis of genes, and the Halomonas TD1.0 genome-scale metabolic (GEM) model. As a case study of the effectiveness of this platform, we applied unsupervised machine learning to determine key differences between Halomonas bluephagenesis TD1.0 cultivated under varied conditions. Specifically, cell motility and flagella apparatus are identified to drive energy expenditure usage at different osmolarities, and predictions were verified experimentally using microscopy and fluorescence labelled flagella staining. As more omics projects are completed, this landing page will facilitate exploration and targeted engineering efforts of the robust, industrial chassis H bluephagenesis for researchers without extensive bioinformatics background. [ABSTRACT FROM AUTHOR]

Due to difficulties in accessing detailed energy modelling and usage data that are required to estimate energy needs that are responsive to local circumstances, we propose an equivalence scale approach to the determination of required energy consumption. Our method requires the estimation of energy equivalence scales that are used to rescale reference household energy consumption and, thus, yield household-specific energy requirements. We apply the method using readily available income and expenditure data, finding that estimated required energy is well above actual energy expenditure for low- and middle-income households, which is consistent with an expectation that basic energy needs for poor households may not be met. The proposed approach is general enough to incorporate other features that might be deemed relevant and available in other settings, and, therefore, can be used to examine the affordability component of SDG 7, undertake energy poverty analysis or design appropriate policies. [ABSTRACT FROM AUTHOR]

Climate and energy policies use to be embedded in joint packages with seeming coherent goals on which the electricity sector is targeted. However, the complexity of power systems is rarely fully apprehended while setting up such packages, particularly when technical externalities from variable renewable energies (VRE) become widespread and different sources of flexibility need to be considered. We use a detailed power system model subject to a combination of RE goals and CO2 caps to seize their interplays and propose a methodology to rank the resulting equilibriums in terms of environmental effectiveness and economic efficiency. We show that: only modest levels of VRE develop without subsidies regardless the level of the CO2 cap; technical externalities create trade-offs between VRE penetration and environmental effectiveness; new flexibility technologies may correct or exacerbate these externalities, impacting effectiveness, costs, and coherence of such packages, requiring a sensitive target hierarchization and fine-tuning of such instruments. [ABSTRACT FROM AUTHOR]

The energy environmental Kuznets curve is effectively an environmental Kuznets curve augmented by adding one or more energy-related variables. We suggest that the energy Kuznets curve (EKC) can be estimated separately from the conventional environmental Kuznets curve as a quadratic function of income. It is demonstrated that the environmental Kuznets curve implies and is implied by the EKC. The empirical results show consistently that both the environmental and EKC are valid for developed (high income) countries but not so for developing (low income) countries where the relations are positive and monotonic. The importance of considering energy consumption in conjunction with the environmental Kuznets curve is that economic growth on its own does not put an end to environmental degradation unless the underlying country is on the downward-sloping sections of both the environmental and EKC. [ABSTRACT FROM AUTHOR]

This research aims to examine the influence of chairperson/CEO demographic characteristics on the level of cooperatives' the environmental performance of Vietnamese cooperatives, based on Upper Echelon Theory. To measure environmental performance levels, this study uses energy consumption levels (electricity) to test the hypotheses. A sample of 1,508 cooperatives (from 2014 to 2016) has been used to carry out the OLS regression model, controlling for year and industry fixed effects. This study shows that the relationship between a chairperson's educational level and electricity consumption is negative and significant (decreasing energy consumption). A similar finding is also found with CEO duality, which supports the negative nexus with electricity used. In addition, no significant association was found between chairperson/CEO gender and energy consumption level, whereas the relationship with a chairpersons' age is positive. Drawing from Upper Echelon Theory, the current research provides novel insights into the relationships between chairpersons/CEOs' characteristics and the cooperatives' environmental performance. From practical implication, since cooperatives are a relatively common type of business in the rural areas of Vietnam and environmental protection is quite essential, it is necessary for cooperatives to choose suitable chairpersons/CEO based on their demographic characteristics. JEL: G30, K32, M14 [ABSTRACT FROM AUTHOR]

This work focuses on vibration alleviation and energy harvesting in a dynamical system of a spring-pendulum. The structure of the pendulum is modified using an independent electromagnetic harvesting system. The harvesting depends on the oscillation of a magnet in a coil. An endeavor has been made to get both the energy harvesting and mitigation of vibration efficacy of the harvester. The governing kinematics equations are derived using Lagrange's equations and are solved asymptotically using the multiple scales method to achieve the intended outcome as new and precise results. The resonance states are classified, and the influence of various parameters of the studied system is analyzed. Fixed points at steady states are categorized into stable and unstable. The time behavior of the solutions, the modified amplitudes, and phases are examined and interpreted in the light of their graphical plots. Zones of stability and instability are concerned, in which the system's behavior is stable for a wide range of used parameters. This model has become essential in recent times as it uses control sensors in industrial applications, buildings, infrastructure, automobiles, and transportation. [ABSTRACT FROM AUTHOR]

The United States has long recognized the potential of improved energy efficiency to profitably reduce energy consumption in manufacturing. The Department of Energy (DOE) has also recognized the potential and initiated several programs to enhance energy efficiency in manufacturing. Despite the attention, studies point out that many energy‐efficiency opportunities remain unexploited. Increasingly, scholars have emphasized that behavioral factors could facilitate the uptake of energy‐efficiency practices. Accordingly, we adopt a behavioral perspective and investigate whether precision (a hitherto unexplored behavioral factor) affects the adoption of energy‐efficiency practices. Specifically, we examine whether the implementation of energy‐efficiency practices depends on whether the costs and savings associated with such practices are presented as precise (e.g., $20,431) or round (e.g., $20,400) numbers. First, we explore the impact of precision with econometric analysis using data on energy‐efficiency recommendations made by the DOE to small‐ and medium‐sized manufacturing firms. Our econometric analysis indicates that energy‐efficiency recommendations with precise cost and precise saving exhibit higher adoption rates as compared to other recommendations. Next, we use individual interactions with managers and laboratory experiments with managers and students to replicate and isolate the precision effects. Then, we elicit the mechanism by which precision affects the adoption of energy‐efficiency initiatives. We find that credibility serves as a key mechanism that drives the precision effect. Our findings suggest that credibility‐enhancing cues such as precision can be leveraged to increase the uptake of energy efficiency and possibly other process improvement practices. [ABSTRACT FROM AUTHOR]