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The research assessed waste-based briquettes consumption compared to conventional fuels in the Andes. Laboratory tests were conducted together with on-field analysis in Colquencha (Bolivia). The laboratory study shows that the performances of briquettes are better in terms of PM2.5 (933.4 ± 50.8 mg kg−1) and CO emissions (22.89 ± 2.40 g kg−1) compared to animal dung (6265.7 ± 1273.5 mgPM2.5 kg−1 and 48.10 ± 12.50 gCO kg−1), although the boiling time increased due to the lower fuel consumption rate and firepower compared to shrubs. The social survey organized with 150 Bolivian citizens suggested that low-income households are not able to pay for an alternative fuel: about 40% would pay less than 4 USD per month, while methane use for cooking is positively correlated with the income level (r = 0.244, p < 0.05). On field analysis suggested that local cookstoves are not appropriate for briquettes combustion since indoor air pollution overcomes 30 ppm of CO and 10 mgPM2.5 m-3. On balance, local small manufactures can be the main target for selling waste-based briquettes to reduce shrubs and wood consumption. However, briquettes production costs seem not yet competitive to natural easy-to-obtain fuels (i.e., animal dung). The research encourages the use of cellulosic and biomass waste-based briquettes in the Andean area for cooking, heating, or manufacturing and strongly advises policy-makers to introduce economic incentives for the recovery of secondary raw materials. • Analysis of waste-based briquettes use in Andean areas were conducted. • Laboratory analysis, social surveys, and on field evaluations are the methods. • Briquettes can be employed for reducing about 30% of the conventional fuels. • The research encourages the employment of waste-based briquettes in the Andes. • Incentives to briquettes production and consumption should be introduced. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the higher regularity and asymptotic behavior for the 2-D magnetic Prandtl model in the Prandtl-Hartmann regime. Due to the degeneracy of horizontal velocity near boundary, the higher regularity of solution is a tricky problem. By constructing suitable approximated system and establishing closed energy estimate for a good quantity (called "quotient" in [19]), our first result is to solve this higher regularity problem. Furthermore, we show the global well-posedness and global-in- x asymptotic behavior when the initial data is small perturbation of the classical Hartmann layer in Sobolev space. By using the energy method to establish closed estimate for the quotient, we overcome the difficulty arising from the degeneracy of horizontal velocity near boundary. Due to the damping effect, we also point out that this global solution will converge to the equilibrium state (called Hartmann layer) with exponent decay rate. [ABSTRACT FROM AUTHOR]

In controlled environment agriculture spaces, the conditions fluctuate between photoperiod and dark period, with crops growing continuously. As crops grow, their impact on the energy demand and energy use, often estimated using a building performance simulation tool, becomes more prominent. In this paper, a dynamic crop model integrated into a building performance simulation tool is proposed to estimate the yield and heat gain/loss from crops by combining a growth model and an energy balance model of the crops. The developed growth model is an adjusted version of a greenhouse lettuce growth model modified for high-density controlled environment agriculture applications by calibrating the sensitive parameters for several indoor environment conditions (temperature, lighting, etc.) using an experimental growth dataset. The yield, the energy demand and the energy use were assessed for a case study modelled in TRNSYS. The results obtained using the greenhouse and developed growth models were compared to those generated with the experimental growth dataset. Depending on the indoor environment conditions, the difference in specific energy use estimated using the experimental growth dataset and the developed model varied between 0.1% and 3.5%, indicating that the model led to an acceptable level of accuracy. The dynamic crop model estimates yield and heat gain/loss from crops for various indoor environment conditions, which are essential for carrying out energy, financial, and environmental analyses. • Existing crop growth model overestimates growth in controlled agriculture spaces. • A calibrated grey-box mechanistic crop model is proposed. • Crop growth and dynamic heat exchanges are integrated to a building simulation tool. • The model is applicable to various indoor environment conditions. • This approach supports analyses that balance both yield and energy consumption. [ABSTRACT FROM AUTHOR]

This paper explores the effects of various parameters on the triticale straw cutting process and the subsequent biomass yield. The impact of blade angle (α), rake angle (β), and the distance between the blade and counter-blade (g) were examined in relation to the shaft torque (T d) on the cutting knife drum, the energy consumption (E c), and the required power (P) for processing straw. Heterogeneity among straw samples was taken into account to ensure accurate calibration of responses. An analysis of variance (ANOVA) was employed to investigate the interactions between input variables and recorded responses, leading to the identification of optimal cutting parameters (α = 35° and β = 0°) that minimise T d , E c , and P. Additionally, the components of the recorded torque T d , including cutting torque (T c) and friction torque (T f), were analysed. Parameter f was used to ascertain the percentage of T f in T d , enabling an optimisation process that confirmed the experimental results and pinpointed the parameter values that resulted in the least energy-intensive process. • ANOVA analysis of influence of process settings on the cutting process results. • The knife blade angle has the most significant influence on energy consumption. • The distance between blade and counter-blade has less influence on energy consumption. • The share of friction torque in the cutting torque facilitated numerical optimisation. • Lower energy consumption of cutting improves energy balance of biofuel production. [ABSTRACT FROM AUTHOR]

Supercritical water oxidation (SCWO) has been regarded as a new and efficient technology for the harmless treatment and energy utilization of organic wastes, resulting in the quickly homogeneous oxidation between organics and oxidizers and the former being wholly degraded into small environment-friendly green molecules such as H 2 O and N 2 and inorganic salts. This paper systematically analyzed the influencing behavior and mechanisms of the reaction factors, such as temperature, pressure, residence time, oxidant type, oxidation coefficient, and the concentration and pH values of the raw material, on the treatment effect of organic wastes. For most organic wastes, the SCWO conditions at 550 °C with a residence time of 1min and an oxidation coefficient of 100% can meet the removal rate of more than 99%. To further enhance the degradation rate of organics, the principles, implementation cases, and related equipment components of general enhancement technologies of supercritical water oxidation were discussed, such as fractional oxygen injection, auxiliary fuel co-oxidation, and hydrothermal flame-assisted degradation. This paper proposes a novel supercritical flame-assisted oxidation process in which the reactor performs preheating, corrosion protection, and desalination functions. The use of additive-enhanced oxidation, segmented oxidation, and supercritical hydrothermal flame-assisted oxidation has achieved good results in the complicated treatment process of brutal degradation of organic matter. Figure Schematics of supercritical water oxidation flowchart and focused process enhancement perspectives. [Display omitted] [ABSTRACT FROM AUTHOR]

Combined heat and power (CHP) plants fueled by biomass can collect and utilize waste straw resources in a productive way. This paper considers the impact of regional factors on biomass energy potential and the energy needs of the population, so as to study the differences in construction of biomass CHP plants and the collection scope of raw materials, and proposes evaluating suitability for biomass energy development based on scope of resource collection. Taking five counties in China as its study areas, this paper assesses biomass energy potential. A topology system of biomass CHP plants has been reasonably established in different counties through ArcGIS, the required installed capacity has been calculated according to the number of persons served by such plants. Finally, the collection length and corresponding value range of raw materials of CHP plants along roads has been obtained based on biomass energy potential and energy demand. The result shows that the differences in area, straw yield and biomass fuelization rate depending on regions have a great impact on biomass energy potential, while the residue-to-product ratio of straw and biomass calorific value have less of an impact. When the biomass energy per capita of a region reaches 9.75GJ/person, it is suitable for biomass energy development. The installed capacity in the biomass CHP plant system of each study area is mostly within the scope of 3–59 MW, and the collection length of corresponding biomass resources of such plants along roads is mostly within the scope of 5.09–25.23 km. • Assessment of biomass energy potential based on regional biomass differences. • Suitability for biomass energy development based on scope of resource collection. • Strategies for biomass plant system construction in different regions are proposed. [ABSTRACT FROM AUTHOR]

Economic transformation and development serve as effective strategies for resource-based regions to avoid the "resource curse." By optimizing industrial structure and enhancing energy efficiency through government macro-regulation, these regions can achieve sustainable and environment-friendly growth. The general equilibrium model is widely employed to assess the effectiveness of economic transformation and development. In this study, we constructed a provincial social accounting matrix based on macro data from Shanxi, China, to examine the impact of different environmental protection tax rates on the macro economy, industrial structure, and energy consumption. The findings reveal that the implementation of environmental protection tax has successfully optimized the industrial structure and improved energy utilization efficiency. However, it has also led to a slight decline in total output. Hence, it is imperative to establish a more balanced and reasonable environmental protection tax rate to further promote economic transformation and development in resource-based areas. Consequently, this paper puts forth policy recommendations aimed at achieving a harmonious balance between ecological preservation and economic progress in resource-based regions, ultimately enhancing the overall quality of economic development in such areas. • Economic transformation and development are effective ways for resource-based regions to avoid the "resource curse". • This paper is based on macro data from Shanxi, and constructs a provincial social accounting matrix to study the impact of different environmental protection tax rates on macroeconomic, industrial structure, and energy consumption. • Setting a reasonable environmental protection tax rate can promote the economic transformation and development of resource-based areas [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

This paper demonstrates a theoretical and experimental study on a universal vibro-impact system with bidirectional drift. With a dedicated experimental rig that is able to verify numerical simulations, the system has revealed various bifurcations from a piecewise-smooth dynamical model involving impact and dry friction. This experimental rig with a two-sided constraint is designed with adjustable configurations which can be used for experimental testing of versatile piecewise-smooth dynamical systems, e.g., the impact oscillator, the drifting oscillator and the capsule system. It is able to be customised to alter different system parameters, such as friction, number of constraints, mass ratio, impact gap and constraint stiffness, for developing and testing various control strategies. In this paper we particularly studied several types of bifurcations from our preliminary experimental results and discussed the dynamical responses of the system under different excitation frequencies and amplitudes. It was found that with a higher excitation frequency and amplitude, the vibro-impact dynamics on both ends of the constraints could result in a large amount of uncertainties, thus bi-stable and chaotic motions are likely to be observed. While being unstable, the system runs with a relatively high energy efficiency in this configuration. [Display omitted] • An experimental rig with a two-sided constraint and bidirectional drift is studied. • The rig is designed with adjustable configurations for testing versatile systems. • System parameters are identified and verified by numerical simulations. • Grazing and sliding bifurcations, bi-stability and chaotic motions are studied. • Control parameters that cause instability may lead to high energy efficiency. [ABSTRACT FROM AUTHOR]

Latching control is a phase optimization control mechanism for improving the energy conversion efficiency of a wave energy converter (WEC). This paper, for the first time, extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed in this paper by integrating conventional tuned mass dampers (TMD) and the latching mechanism. First, the theoretical models of WEC and TMD are compared. Second, the mathematical model of an LMD installed on a single-degree-of-freedom structure is established, and three latching control strategies with different latching time instants, latching durations, unlatching time instants, and required information feedback are tested. Subsequently, the performance of the LMD is evaluated through the comparison with the detuned and optimally tuned TMDs. The characteristics of the latching control force are analyzed in terms of phase, component, energy dissipation, and damping enhancement effect. Lastly, the feasibility and effectiveness of the proposed LMD with three different latching strategies are proven. The latching control can reduce the stiffness component and increase the damping component of the control force, thereby optimizing the phase lag between the control force and the structural response. The proposed latching mechanism and strategies for vibration control can provide an innovative solution to improve the effectiveness of high-frequency detuned dampers, facilitate the design of long-period dampers, and develop adaptive semi-active dampers in the future. [ABSTRACT FROM AUTHOR]

China's coastal region is the major geographical unit for the future development of China's industrial sector. The transformation of basic structure to high-class development in China's coastal places is a significant tool for promoting the changes related to quality, power and efficiency in regional economic development. In the 21st century, environmental and energy issues have increased worldwide, and challenges related to environmental pollution, energy crises, and ecological imbalances have emerged. To climate change and energy utilization, the sustainable progress of clean energy is the new route of future energy development. Based on China's non-polluting energy growth process in the last ten years, this article explores China's clean/green energy policies and economic growth development plans. Clean energy utilization is crucial for sustainable development in the context of high-quality economic growth and climate change. However, the monetary evolution and carbon emission are not investigated whole from the clean energy aspects. Using Wind energy sources as the acceptable variable, this paper employs threshold regression and impulse functions to assess the energy consumption and economic growth on carbon emission in 30 Chinese provinces over the 2000 to 2020 period. The Deep Belief Network (DBN) model predicts wind energy utilization and efficiency. The results show that economic development and carbon emissions are connected. Further, growth influences promote the offset of carbon emissions. Green innovation alters the nexus of carbon emissions, and China's economy reduces carbon usage. It provides the decision-making policies for clean energy development. • China's Coastal region is the major geographical unit for the future development of China's industrial. • In high-quality economic growth and climate change, clean energy use is vital for sustainable development. • The utilization of wind energy and it's efficiency is predicted using Deep Belief Network (DBN) model. • Empirical results link economic growth with carbon emissions, showing growth promotes emissions offset. • Green innovation changes the economic growth-carbon link, aiding China's carbon reduction efforts. [ABSTRACT FROM AUTHOR]

In the global effort to reduce CO 2 emissions, the concurrent enhancement of pollutant degradation and reductions in fossil fuel consumption are pivotal aspects of microalgae-mediated wastewater treatment. Clarifying the degradation mechanisms of bacteria and microalgae during pollutant treatment, as well as regulatory biolipid production, could enhance process sustainability. The synergistic and inhibitory relationships between microalgae and bacteria are introduced in this paper. The different stimulators that can regulate microalgal biolipid accumulation are also reviewed. Wastewater treatment technologies that utilize microalgae and bacteria in laboratories and open ponds are described to outline their application in treating heavy metal-containing wastewater, animal husbandry wastewater, pharmaceutical wastewater, and textile dye wastewater. Finally, the major requirements to scale up the cascade utilization of biomass and energy recovery are summarized to improve the development of biological wastewater treatment. [Display omitted] • The synergistic and antagonistic interactions between bacteria and microalgae are summarized. • Different stimulators that could regulate microalgal biolipid accumulation are also reviewed. • Wastewater treatment technologies that utilize microalgae and bacteria in the laboratory and open ponds are described. • The trends in microalgae-bacterial consortium in multistage energy production are proposed. [ABSTRACT FROM AUTHOR]

A cloud computing environment processes user workloads or tasks by exploiting its high performance computational, storage, of reducing and network resources. The virtual machines in the cloud environment are allocated to tasks with the aim of reducing overall execution time. The use of high performance resources incurs monetary costs, as well as high power consumption. The heuristic based approaches implemented for scheduling tasks are unable to cope with the complexity of optimizing multiple parameters. In this paper, we propose a multi-objective grey-wolf optimization based algorithm for scheduling tasks on cloud platforms. The proposed algorithm targets to minimize schedule length (overall execution time), energy consumption, and monetary cost required for executing tasks. For optimization, the algorithm incorporates steps that are performed iteratively for mimicking the behavior of grey wolves attacking their prey. It uses discrete values for positioning wolves for encircling and attacking the prey. The assignment of tasks to virtual machines is performed using the solution found after multi-objective optimization that incorporates weighted sorting for arranging solutions. Our experimentation performed using the CloudSim framework shows that the proposed algorithm outperforms other algorithms with performance improvement ranging from 3.98% to 16.07%, while considering the schedule length, monetary cost, and energy consumption. • For cloud computing environments, we present a novel task scheduling approach, termed as GWOTS. • Using the proposed approach, the schedule length, monetary cost, and energy consumption are optimized. • The GWOTS algorithm uses multi-objective optimization and incorporates weighted sorting for arranging solutions. • The proposed GWOTS algorithm outperforms other state-of-the-art algorithms by producing optimized schedules. [ABSTRACT FROM AUTHOR]

This paper proposes a novel dual-functional nonlinear metastructure for amplitude-robust simultaneous vibration suppression and energy harvesting, consisting of combined bistable and monostable cubic-hardening nonlinear electromechanical resonators that are alternately arranged on a host structure. The proposed design can effectively achieve wide bandgap even at high acceleration levels, suppress the undesired resonance transmission peaks outside the bandgap that are deemed as inevitable troubles in conventional linear metastructures, and generate power across a broad bandwidth at low frequencies. It is shown experimentally that the fabricated nonlinear prototype suppresses the unwanted resonance peaks by up to 70.5% while widening the bandgap by 52%, compared to the linear counterpart. A distributed-parameter electromechanically coupled model is established to verify the experimental measurements. Analytical expressions for the dynamic and electrical responses are explicitly derived using the harmonic balance method, based on which the interplay between several key parameters and their influences on the performance of the system are investigated, including the cubic nonlinear stiffness, mass ratio, load resistance, and electromechanical coupling strength. The findings provide a valuable guideline for accurately assessing the dual capabilities and facilitate efficient optimization of the next-generation nonlinear metastructure system. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

The world is currently facing urgent climate and environmental issues, such as global warming, ecosystem collapse, and energy shortages. In this context, this study selected data from 2000 to 2021 and employed the Method of Moment Quantile Regression (MMQR) to thoroughly investigate the impact of renewable energy consumption, economic complexity, and geopolitical risks on the ecological footprint of the Group of Twenty (G20) countries. The results indicate that in countries with lower quantiles, renewable energy consumption significantly reduces the ecological footprint, whereas its effect is not prominent in countries with higher quantiles. Economic complexity has a negative impact on the ecological footprint, and this impact becomes stronger as the quantile of the ecological footprint rises. Additionally, economic complexity moderates the effect of renewable energy on the ecological footprint. Geopolitical risks facilitate the growth of the ecological footprint. Likewise, robustness tests such as DOLS, FMOLS, and quantile regression confirm these estimates in the same framework. This study has conducted a profound analysis of global environmental issues, offering innovative perspectives and recommendations for achieving goals related to sustainable energy utilization, mitigating climate change, and improving the ecological environment. The findings of this research will guide policymakers in G20 countries to adopt more effective environmental protection measures, thereby contributing to the construction of a sustainable future. • This paper investigates the factors influencing the ecological footprint of G20 countries. • The study utilized a novel Method of Moment Quantile Regression to explore nexus among the study variables. • Renewable energy consumption has no significant effect on the ecological footprint in higher quantiles. • Economic complexity moderates the effect of renewable energy on the ecological footprint. • Geopolitical risks exhibit a unidirectional causality with the ecological footprint. [ABSTRACT FROM AUTHOR]

Spacecraft devices have strict restrictions on weight and volume for high fuel efficiency and endurance requirements. In this paper, a method for designing an ultrathin passive vibration isolator based on multi-layer plain-woven wire mesh is proposed. The isolator is structurally inspired by O-type wire rope isolators, and the wire mesh is pre-compressed to buckling for lower stiffness and higher stability. The isolator stiffness in the post-buckling process is analyzed by simplifying the single wire as a strut. The motion equation of the strut is constructed and calculated by the fourth-order Runge–Kutta method and the shooting method. The morphology and stiffness variation of the wire mesh during pre-compression process and repeated compression process are analyzed, and the structural compaction ratio is calculated. This computational method has been experimentally validated and proven to be effective. To prevent collisions between the protected objects and the base during the shock process, the system is simplified and described using a single-degree-of-freedom (SDOF) system with displacement restrictors. The system's motion equation is formulated and solved using the central difference method. Subsequently, the maximum compression displacement of the isolator is determined through the calculation. A wire mesh isolator with a thickness of less than 10 mm is fabricated for a specific application. Experimental results confirm that the isolation efficiency surpasses 65%, and the isolator is capable of withstanding a peak acceleration of 60 g while maintaining a shock acceleration magnification below 1.2. • A method for designing vibration isolators composed of the wire mesh is proposed. • The isolator stability performance is enforced by pre-compressing the wire mesh. • The morphology and stiffness variation of the wire mesh are calculated. • The shock displacement amplitude is calculated using the central difference method. [ABSTRACT FROM AUTHOR]

Accurate road slope information is of paramount importance for optimizing vehicle control and enhancing energy efficiency. In the context of heavy-duty vehicles (HDVs), the precise estimation of road slope presents a formidable challenge. This challenge is rooted in the coupling between vehicle mass and road slope, the robustness of road slope estimation methods across diverse driving styles, and the generalizability of algorithms to real-world road scenarios. To address these challenges, this paper proposes an innovative road slope estimation scheme that comprehensively considers the influences of multiple source factors in a real-world HDV transportation scenario. Firstly, in order to solve the problem of road slope estimation error under complex road types and different driving styles, a complex road slope estimation method based on the nonlinear predictive filter (NPF) combined with the Cubature Kalman filter (CKF) is constructed. To eliminate the problem of vehicle power fluctuation in special traffic scenarios, we propose a special scenario road slope estimation method based on the combination of a low-pass filter (LPF) and the NPF_CKF algorithm. To address the error problem when using low-cost Inertial Measurement Unit (IMU) sensors, we designed a Kalman filter (KF)-based multi-sensor fusion correction method. Finally, we conduct real-world experiments on complex roads at the test site to verify the accuracy of the proposed estimation method and its insensitivity to model parameters. The robustness and applicability of the proposed method are also verified in free-driving experiments conducted in real-world road scenarios. [ABSTRACT FROM AUTHOR]

In today's world, where economic development and environmental sustainability are becoming increasingly important aspects of national strategy, attention to the impact of different economic sectors on climate change is becoming an integral part of scientific research. This article focuses on analyzing the impact of primary and secondary economic sectors development on carbon dioxide (CO 2) emissions at the sub-national level in Russia from 2005 to 2019. The aim of the study is to provide an in-depth understanding of the relationships between the dynamics of these sectors and CO 2 emission levels in different regions of the country. Weighted regression and panel data methods were applied to better identify the patterns of the impact. The results show that the size of population and electricity consumption have the highest impact on CO 2 emissions. So that, the expansion of nuclear and gas generation capacity, as well as significant improvement of energy efficiency, are of crucial importance to reduce the emissions. Other sectors have a heterogeneous impact and requires more differential approaches, considering the specifics of regions. Taking into account the significant differences between the Russian constituent entities, this paper emphasizes the low informativeness of assessments at the national level and their inadequacy in terms of improving the efficiency of domestic management, including decarbonization policies. • The impact of considered economic sectors on CO 2 emissions were analyzed in 80 Russian constituent entities in 2005–2019. • Weighted regression and panel data methods were used to catch the specifics of Federal districts and constituent entities. • Population size and electricity consumption have the highest impact on CO 2 emissions. • Increasing energy efficiency and modernization of energy facilities are the most promising solutions to reduce the emissions. [ABSTRACT FROM AUTHOR]

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction. • There exist differences in carbon quota allocation among provinces in the future. • There are changes in the initial and optimal carbon quotas obtained by each province. • The role of carbon emissions between regions is changing over time. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies. [Display omitted] • Enrich the view of renewable energy's indirect impact on carbon emissions. • Renewable energy's carbon emission reductions go beyond replacing fossil fuels. • Constructed a mediating effect model between renewable energy and carbon emissions. • Renewable energy can promote or inhibit carbon emissions through various pathways. • Research helps develop more effective renewable energy sustainability strategies. [ABSTRACT FROM AUTHOR]

The existence of various pollutants in water environment contributes to global pollution and poses significant threats to humans, wildlife, and other living beings. The emergence of an effective, realistic, cost-effective, and environmentally acceptable technique to treat wastewater generated from different sectors is critical for reducing pollutant accumulation in the environment. The electrochemical advanced oxidation method is a productive technology for treating hazardous effluents because of its potential benefits such as lack of secondary pollutant and high oxidation efficiency. Recent researches on advanced oxidation processes (AOPs) in the period of 2018–2022 are highlighted in this paper. This review emphasizes on recent advances in electro-oxidation (EO), ozone oxidation, sonolysis, radiation, electro-Fenton (EF), photolysis and photocatalysis targeted at treating pharmaceuticals, dyes and pesticides polluted effluents. In the first half of the review, the concept of the AOPs are discussed briefly. Later, the influence of increasing current density, pH, electrode, electrolyte and initial concentration of effluents on degradation are discussed. Lastly, previously reported designs of electrochemical reactors, as well as data on intermediates generated and energy consumption during the electro oxidation and Fenton processes are discussed. According to the literature study, the electro-oxidation technique is more appropriate for organic compounds, whilst the electro-Fenton technique appear to be more appropriate for more complex molecules. [ABSTRACT FROM AUTHOR]

[Display omitted] • Adaptive kinetic energy reallocation mechanism utilizes a pre-programmable and variable frequency-up converter to manipulate the kinetic energy transfer. • Kinetic energy reallocation enhances system response and stabilizes the power generation. • The power ratio is reduced by up to 42 % and the maximum power is 1.48 mW under single pendulum excitation. Energy harvesting technology has become a crucial way to accomplish battery-free wireless sensor networks. Although the output power of the wearable energy harvester has been significantly improved, the bandwidth of the energy harvester is still a key issue that hinders the applications of the energy harvester since the output power could dramatically fluctuate within a small excitation range. In this paper, adaptive kinetic energy reallocation (AKER) mechanism is proposed to stabilize the output power of the wearable energy harvester. In contrast to potential energy-based method, the AKER utilizes a pre-programmable and variable frequency-up converter to manipulate the kinetic energy transfer. Thus, the kinetic energy is adaptively controlled to enhance system response such that the output power can be stabilized. A mathematical model is built to predict the system performance and assess the feasibility of AKER mechanism. To validate the AKER, a prototype is fabricated and tested under single pendulum and simulated limb swinging excitations. Both the theoretical and experimental results show that the AKER can effectively stabilize the output power for all the excitation conditions. Compared with conventional energy harvester, the AKER can reduce the power ratio by up to 42 % and generate maximum power of 1.48 mW under single pendulum excitation. Moreover, under simulated limb swinging excitation, the AKER cuts down the power ratio decrease by 46 % and the maximum power reaches 1.47 mW. Based on these results, the AKER demonstrates great advantage in improving the output power stability and provides a novel method to enhance the bandwidth of the energy harvester. [ABSTRACT FROM AUTHOR]