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In the European Union, increasing attention is already being paid not only to the development of renewable energy sources, but also to the establishment of solutions to achieve local energy self-sufficiency while increasing the role of citizens in managing the energy they generate. This approach is expected both to have a positive impact on the environment and the reduction of greenhouse gas emissions, and to enhance energy security—both in economic and civic terms by, i.a., combating energy poverty. The development of local energy communities promoted in the EU is supported i.a. by energy cooperatives. These contribute to the efficient harnessing of renewable energy potential in rural and urban-rural areas, and have been developing in Poland for several years now. In their previous studies, the authors of this research paper attempted to verify the generation (number, type and capacity of installed sources) and consumption (energy demand) configurations in which an energy cooperative would be a viable solution for prosumers who might establish it. However, over the past few years, the conditions for prosumers and the method of their accounting with the electricity seller have changed radically in Poland (shift from net metering to net billing). This situation has opened up space for further research and encouraged the authors to revisit the problem of analyzing the viability of establishing energy cooperatives in relation to the rules of operation of individual prosumers. This research was carried out for three scenarios, and the horizon of the analyses conducted and described extends to 2045. The comparative analysis included energy consumers without their own generation sources, prosumers with a photovoltaic generation installation covered by the net billing model, as well as a scenario involving prosumers' cooperation within an energy cooperative, which by law is settled in the net metering model. Conclusions from the research and simulations made it possible to confirm the claim that, despite changes in the rules of prosumer billing, developing energy independence in the energy community formula results in a significant reduction in the cost of purchasing electricity (even several times lower purchase costs in the timeframe analyzed) and can lead to a reduction in the payback time of investments in generation sources even by a factor of two. The results presented in this research paper open up space for further research. The outcomes allow us to assume that energy cooperatives—in the organizational and institutional model in Poland—are a good tool for reducing the phenomenon of energy poverty on a local scale. [ABSTRACT FROM AUTHOR]

The need for sustainable integrated energy systems to mitigate environmental impact is hindered by challenges in fluctuating demand, trading reliability, and trustworthiness. This paper proposes an innovative approach to tackle these challenges by introducing a blockchain-based integrated energy system trading model with smart contracts. It is intricately linked with the operation of carbon capture and storage (CCS) technology and power-to-gas (P2G) equipment. The CCS-P2G-coupled operation principle is first outlined, followed by the presentation of a comprehensive system model. The peer-to-peer (P2P) energy trading algorithm is enhanced using the Bloom filtering technique. Leveraging smart contracts, a distributed energy trading mechanism is employed, resulting in a meticulously constructed integrated energy system trading model for CCS-P2G-coupled operation. The proposed model is rigorously evaluated for energy trading efficiency and system performance, revealing significant improvements compared to prior studies and showcasing substantial cumulative benefits. Three operation scenarios are examined, with experimental results highlighting the model's superior carbon emission reduction capacity. This study introduces an innovative paradigm for trading and managing integrated energy systems, holding potential implications for the sustainable development and decarbonization transition of future energy systems. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor scheduling flexibility and insufficient carbon emission reduction capacity of the current integrated energy system, this paper proposes an optimization scheduling model of integrated energy demand response that combines source-load synergy with reward and punishment stepped carbon trading mechanism. Firstly, the integrated energy system operation architecture including electricity-heat-cooling energy was constructed to harmonize the energy generation side and consumption side and effectively improve the multi-energy complementary capability of the system. Secondly, the reward and punishment stepped carbon trading mechanism is established by combining the initial carbon quota allocation method and the actual carbon emission calculation theory, so that environmental friendliness and economic sustainability are effectively improved. Finally, to minimize the system operating cost, an integrated demand response optimal dispatch model that considers the characteristics of electric, thermal and cooling loads is constructed to determine the optimal dispatch scheme for the integrated energy system. The results of the calculation example indicate that the proposed integrated demand response model has the function of peak reduction and valley correction, energy conservation and carbon reduction, and provides a feasible solution for the integrated energy system optimal scheduling. [ABSTRACT FROM AUTHOR]

According to the latest energy efficiency European directive (EED 2023/1791/EU), the expected energy renovation rate of at least 3% of the buildings' floor area each year towards nearly zero-energy buildings (nZEBs) is extended to include public buildings not only of the central government (as per the first EED 2012/27/EU) but also of regional and local authorities. This poses a great challenge, especially for Municipalities that often manage large building stocks with high energy demands. In response to this challenge, this paper presents the application of the so-called "typology approach" for conducting public buildings' energy renovation plans at the local level. A computational survey is initially introduced to decide the optimal set of building-stock clustering criteria among all possible combinations, involving the minimization of the RMSE index regarding the primary energy consumption of each building. For a representative building from each identified typology, the key performance indicators (KPIs) are computed for alternative energy-upgrading scenarios. Exploiting the IMPULSE Interreg-MED project tools, the KPIs from each representative building are at first extrapolated to all buildings of the examined stock and, finally, a gradual energy renovation plan is automatically produced based on user-defined decision parameters including the required annual renovation rate. The methodology is applied for the case of the Municipality of Hersonissos in Greece. For the specific 44-buildings' stock it was found that the optimal clustering set included four criteria, building use, construction year, heating, and a cooling system, leading to 15 building typologies. Finally, assuming a 7% renovation rate per year, a 12-year gradual renovation (nZEB transformation) plan is obtained foreseeing an 85% CO2 emissions' reduction. [ABSTRACT FROM AUTHOR]

With the increasing demand for sustainable urban development, smart cities have emerged as a promising solution for optimizing energy usage, reducing emissions, and enhancing the quality of life for citizens. In this context, the combined use of key performance indicators (KPIs) and data analytics has gained significant attention as a powerful tool for promoting energy efficiency and emissions reduction in urban areas. This paper presents a comprehensive conceptual framework in which a series of KPIs are proposed to serve as essential metrics for guiding, monitoring, and assessing energy efficiency and emissions reduction levels in smart cities. Some of the included KPIs in the analysis are 'annual energy consumption per person', 'reduction in greenhouse gas emissions', 'public transport use', and 'adoption of renewable energy'. By incorporating these KPIs, city planners and policymakers can gain valuable insights into the effectiveness of sustainability initiatives. Furthermore, the paper explores how the integration of KPIs with data analytics can be used for monitoring and assessing the overall performance of the city in terms of energy efficiency, emissions reduction, and the enhancement of urban living conditions. Visualization tools, such as radar plots, and time series analysis forecasting methods allow data to be processed and patterns to be identified, enabling informed decision-making and efficient resource allocation. Real-life case studies of ongoing smart city projects are presented in the paper, which also provides a KPI comparison among different European cities, as well as models to forecast the evolution of KPIs related to energy usage and emissions reduction in different European cities. [ABSTRACT FROM AUTHOR]

Formulating energy policies at national, European, and global levels is extremely challenging. The move away from fossil fuels is associated with a variety of technological, economic, and social implications, each of which is subject to dynamic changes and societal scrutiny and can hardly be predicted with certainty. Therefore, a fact-based assessment for the path to a sustainable green energy future is sought out in this paper, using the road-based mobility sector of the Federal Republic of Germany as an example. The analysis performed in this paper is built on publicly accessible, reputable sources like DESTATIS and EUROSTAT. In addition, some very simple calculations were made, e.g., on the potential for wind and photovoltaic energy within Germany. Such an analysis needs to start with the overall energy consumption of any one country. A basic assumption of the paper is that the energy system of the future will be based to a large extent on electricity and its storage in chemical energy. It is assumed that, in addition to hydrogen, liquid energy sources will play a significant role due to the simplicity of their logistics and the subsequent implications on cost. Examples of green, electricity-based fuels with great potential are methanol, methane, and ammonia. Additionally, biomass plays an important role, either for direct use as a fuel or as a source of non-fossil carbon. Today, biofuels, i.e., biodiesel and bioethanol, deliver the largest contribution to climate protection in the EU transport sector. The main goal—the reduction of greenhouse gas emissions—often collides with geopolitical circumstances or national political necessities. This includes, for example, the current world market situation and its national impacts caused by the Russian attack on Ukraine. The prospect for a green, sustainable, and defossilized energy supply are discussed in this context. The paper concludes that a defossilized world energy supply and trade based on renewable electricity and its derivatives, eHydrogen and refuels, and on biomass, is feasible. [ABSTRACT FROM AUTHOR]

The global aluminium industry faces a serious challenge in reducing greenhouse gas emissions as the demand for aluminium continues to increase. The aluminium industry has a responsibility to streamline its energy consumption, especially in the production process. There have been many studies discussing energy consumption performance in the industry. However, most of them only discuss energy saving partially, without involving energy consumption with various items produced. This paper proposes an energy savings measurement in the manufacturing industry. An energy baseline consumed per unit volume has been developed using the equivalent volume method with an energy management control system (EMCS). The study takes a case example from the automotive--aluminium component industry. The steps taken in the study are: examining the production process, converting the production volume to equivalent, calculating the energy consumption ratio, developing an energy baseline, simulating the savings performance, and then proposing an EMCS with key performance indicators (KPI) for sustainability. The results show that the development of a baseline using the ratio of energy and an equivalent volume of production gives a better data correlation with an R² value close to one. From the baseline, the bestdemonstrated performance (BDP) can be used as a reference to set energy goals. Furthermore, the data and the deviant deleted have the same baseline value. They differ in energy reduction goal percentages. The practical application of this study is not only in the manufacturing industry but in other industries as well, such as building management. This study contributes to energy savings achieved with EMCS. [ABSTRACT FROM AUTHOR]

Over the last decade, a constantly growing trend of the popularization of self-service automated stores has been observed. Vending machines have been expanded into fully automated stores, the offer of which is comparable to small, conventional stores. One of the basic reasons for the popularization of modern automated stores is the reduction in a store's energy consumption while ensuring a comparable range of products offered. The research into possibilities of reducing greenhouse gases emission is important in terms of the environment and climate protection. The research presented in the paper concerns the development of a model for determining electricity consumption, operating costs and CO2 emission of an automated store designed and developed by Delfin company. In the developed model, the potential location of the store, prevailing climatic conditions and expected product sales are taken into account. Estimated energy demand for the store is the information of key importance for the potential investors and the manufacturer of the automated store. It is worth emphasizing that the average annual electrical energy consumption evaluated for a grocery store of an area of 70 m2 amounted to approximately 38.4 MWh, while for an automated store of an area of 9 m2 and a comparable product range, the electricity consumption was approximately 10.1 MWh, i.e., 74% smaller. [ABSTRACT FROM AUTHOR]

In South Africa, there has been a rapid adoption of solar power, particularly inverter-based solar sources, in low-voltage (LV) networks due to factors such as load shedding, rising electricity costs and greenhouse gas emissions reduction. In residential LV networks, the alignment between solar supply and energy demand is less precise, necessitating larger battery storage systems to effectively utilize solar energy. Residential areas experience peak energy demand in the morning and evening when solar irradiance is limited. As a result, substantial energy storage is important to fully utilize the potential of solar energy. However, increasing inverter-based, customer-generated power creates an imbalance in the utility supply. This is because utility LV supply transformers have three phases, while individual customers have single-phase connections and no load balancing control mechanism. This supply imbalance adversely affects the overall power quality, causing energy losses, damage to devices and other issues. To address these problems, the paper proposes a smart control approach to minimize power imbalances within utility LV supply transformers. The controller uses customer battery storage in residential areas to balance the utility transformer phases. A laboratory model was built to simulate a three-phase low-voltage network with single-phase customers, both with and without a smart controller. The results show that closely monitoring and controlling individual inverters through a central controller can significantly improve the balance of the supply network. [ABSTRACT FROM AUTHOR]

As one of the effective and crucial ways to achieve the energy saving and emission reduction of loaders, hybrid technology has attracted the attention of many scholars and manufacturers. Selecting an appropriate energy management strategy (EMS) is essential to reduce fuel consumption and emissions for hybrid loaders (HLs). In this paper, firstly, the application status of drivetrain configuration of HLs is presented. Then, the working condition characteristics of loaders are analyzed. On the basis of this, the configurations of HLs are classified, and the features and research status of each configuration are described. Next, taking the energy consumption optimization of HLs as the object, the implementation principle and research progress of the proposed rule strategy and optimization strategy are compared and analyzed, and the differences of existing EMSs and future development challenges are summarized. Finally, combining the advantages of intelligent control and optimal control, the future prospective development direction of EMSs for HLs is considered. The conclusions of the paper can be identified in two points: firstly, although the existing EMSs can effectively optimize the energy consumption of HLs, the dependence of the strategy on the mechanism model and the vehicle parameters can reduce the applicability of the strategy to heterogeneous HLs and the robustness to a complex working condition. Secondly, combining the advantages of intelligent control and optimal control, designing an intelligent EMS not depending on the vehicle analytical model will provide a new method for solving the energy consumption optimization problem of HL. [ABSTRACT FROM AUTHOR]

With the increase in energy demand and carbon emission requirements, energy management and CO2 emission reduction on the user side are significant for integrated energy system (IES) scheduling. This paper constructs a two-stage optimal dispatching model combining active/passive demand response (DR) and reward and punishment ladder-type carbon trading. In the first stage, the electricity/gas load was optimized by adding a logistics function to the active DR model. A passive DR model is built based on the optimized electric load and the heat/cooling–electricity ratio of the cogeneration unit to optimize the heat/cooling load. In the second stage, a multi-objective IES model based on the optimized load and reward and punishment ladder carbon trading was solved by the golden eagle multi-objective optimization (MOGEO). Analyzing the scheduling results from different scenarios, the active/passive DR model can reduce the load peak-to-valley difference and improve user satisfaction and grid revenue. At the same time, the combination of reward and punishment ladder carbon trading makes the system gain more carbon revenue, reduces system operating costs and carbon emissions, and improves energy utilization. [ABSTRACT FROM AUTHOR]

This paper presents the extension of industry modelling within the REMIND integrated assessment model to industry subsectors, and the projection of future industry subsector activity and energy demand for different baseline scenarios for use with the REMIND model. The industry sector is the largest greenhouse gas-emitting energy demand sector and considered a mitigation bottleneck. At the same time, industry subsectors are heterogeneous and face distinct emission mitigation challenges. By extending the multi-region, general equilibrium integrated assessment model REMIND to an explicit representation of four industry subsectors (cement, chemicals, steel, and other industry production), along with subsector-specific carbon capture and sequestration (CCS), we are able to investigate industry emission mitigation strategies in the context of the entire energyeconomy- climate system, covering mitigation options ranging from reduced demand for industrial goods, over fuel switching and electrification, to endogenous energy efficiency increases and carbon capture.We also present the derivation of both activity and final energy demand trajectories for the industry subsectors for the use with the REMIND model in baseline scenarios, based on short-term the continuation of historic trends and long-term global convergence. The system allows for selective variation of specific subsector activity and final energy demand across scenarios and regions to create consistent scenarios for a wide range of socioeconomic drivers and scenario story lines, like the shared socioeconomic pathways (SSPs). [ABSTRACT FROM AUTHOR]

The goal of reaching the peak of carbon in the construction industry is urgent. However, the research on the feasibility of realizing this goal and the implementation of relevant policies in China is relatively superficial. In view of the historical data of energy consumption and building CO2 emission from 1995 to 2019, this paper establishes a BP neural network model for predicting building CO2 emissions. Moreover, the influencing factors, such as population, GDP, and total construction output, are introduced as the parameters in the model. Through the scenario analysis method explores the practical path to accomplish the peak of building CO2 emissions. When using traditional prediction methods to predict building carbon emissions, the long prediction cycle will increase the possibility of significant errors. Therefore, this paper constructs the calculation model of building carbon emission and forecasts the future carbon emission value through the BP neural network to avoid the error caused by the nonlinear relationship between influencing factors and predicted value. It will effectively predict the feasibility of the carbon peak and the carbon-neutral target set by government, and provide a useful predictive tool for adjusting the new energy structure and formulating related emission reduction policies. [ABSTRACT FROM AUTHOR]

To address the current problem of high energy consumption in data centers, this paper proposes a data center heat pipe air-conditioning system based on the latent heat of water evaporation, which uses the latent heat of water evaporation for cooling by creating a low pressure environment to evaporate large amounts of water. In order to verify the effect of the system, a heat pipe test bench based on the latent heat of water evaporation was designed and built. Compared with the traditional heat pipe in the data center for heat dissipation, the performance and economy of the water evaporation latent heat pipe system designed in this paper are analyzed experimentally. A multi-physics coupled model of water evaporation latent heat pipe air-conditioning based on COMSOL Multiphysics was established to simulate and study the temperature field and velocity field distribution of water evaporation latent heat pipe air-conditioning system in data centers. The research shows that: -- Under the designed test conditions, compared with the traditional heat pipe system, the water evaporation latent heat pipe air conditioner can conduct 2540 kJ more heat in one day in an outdoor environment of 24 °C. -- At an ambient temperature of 3 5°C and an indoor temperature of 25.8 °C, the cooling capacity of the heat pipe in the data center water evaporation latent heat pipe air-conditioning system is twice the cooling capacity of the air conditioner, and the heat pipe can work efficiently regardless of the outdoor ambient temperature. -- The energy-saving effect of the latent heat pipe of water evaporation in the data center has a significant effect on air conditioners with an energy efficiency rating (EER) lower than 2.5-4.4. It can improve the energy efficiency of level 5 with an EER of 2.5 to level 2 with an EER of 3.22, greatly reducing the power consumption of the data center air-conditioning system. When the EER of the air conditioner exceeds 4.4, the coefficient of performance of the data center water evaporation latent heat pipe air-conditioning system will be lower than that of the air conditioner itself. [ABSTRACT FROM AUTHOR]

The process of Land Consolidation (LC) is deemed an important instrument of rural development in many countries, where it contributes to the economic development and viability of their rural areas. This paper aims to analyze three areas of Castilla y León in Northwestern Spain, all having similar agronomic features. The above areas have recently undergone LC processes. This research proves LC can contribute to reducing greenhouse gases (GHG) using the rationalization introduced in the layout of the agrarian exploitations. For this purpose, this paper analyzes the effects of LC actions on the size, shape, and level of scattering of the owners affected and compares the energy consumption in every journey from the exploitation to each plot, as well as the number of row-end turnings within the plots. GHG reductions present significant differences depending on the LC technique carried out, the size of the area consolidated, and the different degrees of intensification of agricultural exploitations. Through the three LC projects analyzed, a reduction in GHG emissions of 23.60% in SA1, 11.46% in SA2, and 9.85% in SA3 would have been obtained. In total, 1067.34 t CO2 of GHG emissions would have been mitigated. In the light of the results obtained, LC can be considered an efficient process in the strategy of GHG reduction, all in line with the current commitments derived from the Paris Agreement. It is also necessary to continue to research the structure and importance of the consumption of fossil fuels in farming and its possible link to emission reduction policies. [ABSTRACT FROM AUTHOR]

The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

Internal Combustion Engines (ICE) are experiencing a transition era in which research and innovation are mainly pushed by environmental issues: emission reduction and fuel saving are indispensable requirements of the new technologies, otherwise the end of ICE is proposed in Europe. Modifications, in reality, are under discussion by 2026 but the environmental issues are anyway welcomed. In the transportation sector, today dominated by ICEs, it appears that the reduction in the propulsion power, hybridization at various degrees, and exhaust post-treatment improvements will guarantee technological solutions able to support the transition in the next couple of decades toward full electric propulsion. Waste Heat Recovery (WHR) is a very interesting opportunity since almost two-thirds of fuel energy is not converted into mechanically useful energy. Moreover, the integration with other thermal streams on board (cooling and lubricating mediums, EGR cooling) can add further value to the recovery opportunity as well as the concept of managing the engine thermal management which can produce a sensible contribution that is appreciated mainly during urban driving. A huge scientific effort is underway, and a great expectation is perceptible. More generally, the technological options that can achieve a reduction in overall fuel consumption and, thus, the improvement of global engine efficiency, are the most valuable when they can be introduced without massive changes to the engine layout. This happens in all the energy applications in which ICEs are involved since the recovery unit can be introduced in the exhaust line. The mechanical energy recovered can be easily transformed into electrical energy, so represents an interesting integration with the hybrid propulsion powertrains. In this paper, a review of the most important technologies referred to the WHR is presented, outlining advantages and drawbacks, and setting up the presently available technologies referred to the transportation sector. [ABSTRACT FROM AUTHOR]

Energy storage is an important technical means to increase the consumption of renewable energy and reduce greenhouse gas emissions. Electrochemical energy storage, represented by lithium-ion batteries, has a promising developmental prospect. The performance of lithium-ion batteries continues to decline in the process of application, and the differences between batteries are increasing. Therefore, accurate estimation of the state of health (SOH) of batteries is the key to the safe and efficient operation of energy storage systems. In this paper, the electrochemical impedance spectroscopy (EIS) characteristics of Li-ion batteries under different states of charge and health were studied. Three groups of Li-ion battery impedance module values under different frequencies were selected as characteristic parameters, and the SOH estimation model of Li-ion batteries was built by using the support vector regression (SVR) algorithm. The results show that: the model with the second group of frequency-point combinations as characteristic parameters takes into account both accuracy and efficiency; the cumulative time of the characteristic frequency test and SOH evaluation of lithium-ion batteries is less than 10 s; and this technology has good engineering application value. [ABSTRACT FROM AUTHOR]

Purpose: This article determines the volume of greenhouse gases emitted by a range of industrial manufacturing sectors in order to give direction to public emission reduction programmes and increasing the impacts of the latter. Design/methodology/approach: To this end, it applies a classification of industrial manufacturing sectors based on their greenhouse gas emissions profiles. By making use of economic data on the consumption of energy sources and a conversion process, we obtain an estimation of greenhouse gas emissions, and consequently a profile of the direct/indirect emissions, concentration of emissions, total emissions and electrification level of each sector. Finally, this allowed us to segment the sectors into four groups. Findings: By grouping the sectors into four segments we reveal a series of group-specific characteristics, which serves as a basis for corresponding greenhouse gas reduction programmes. Special attention should be given to the segment that features a large amount of emissions concentrated in a relatively low number of firms and a low level of electrification, while making a disproportional use of public funds as compared to the volume of their emissions. Research limitations/implications: This research followed an aggregate (macro) approach, which limits the possibilities to interpret the results from a NACE level towards individual companies pertaining to a specific sector. This applies also to the use of average values for conversion factors. Take note also that some big emitter sectors, such as extractive industries and petroleum refining industries, are not included in the study. Practical implications: Public programmes should consider different approaches to reducing greenhouse gas emissions based on sectoral segmentation. General recommendations are proposed for each of the identified segments. Social implications: Improved public programmes can foster the reduction of greenhouse gas emissions and the United Nation's Sustainable Development Goals 7 and 12. Originality/value: The methodology proposed in this paper allows pointing out sectors where return on investments in greenhouse gas reduction would be highest. [ABSTRACT FROM AUTHOR]

In coastal cities, a large amount of cold energy is released into the nearby seawater during the process of regasification of liquefied natural gas (LNG) at the receiving terminal, and meanwhile, a large amount of exported and/or imported foods need to be frozen by bulk cold energy near the sea. In this paper, a new multistage cold energy recovery/utilization system is investigated to link the LNG cold energy directly to supply the coastal cold store. This design uses a realistic case in Ningbo LNG receiving station in China, and for the very first time considers how to utilize the LNG cold energy in an efficient manner regarding the technical, economic, and environmental benefits. A three‐stage LNG cold energy utilization system is designed and evaluated by considering different temperatures, pressures, and heat exchange parameters. Compared to conventional electric‐driven cold stores, the proposed multistage cold energy recovery/utilization system has a much cheaper capital cost during the initial investment stage, and also avoids the utility power consumption during the daily operation period. In the case study, from Ningbo LNG receiving station to a 10 MW class cold store, the proposed multienergy system can save the energy of 20.05 kilotons of standard coal, and the carbon emission reduction is up to 1.49 × 108 kg per year. [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]

Southern Africa has a huge potential for renewable energy sources such as hydro, solar, wind, biomass, and geothermal. However, electricity access remains a key policy issue for most member states, with a global average access to electricity of only 54% in 2019. This low electrification rate is a strong motivation for member states to increase renewable energy use and improve access to electricity for all. The goal of this paper was to present a literature review of methodologies, energy plans, and government programs that have been implemented by the Southern African Development Community member states to address the region's low average electrification rate and greenhouse gas emission reduction targets. The study presents the most commonly used methodologies for the integration of renewable energies into electrical systems, considering the main grid and distributed generation systems. LCOE minimization methodologies and software options, such as GIS, HOMER, LEAP, and EnergyPLAN, are the most common among the identified studies. The traditional method of electrifying by expanding the grid has not contributed to the eradication of energy poverty in rural areas. Therefore, to improve electricity access in Southern Africa, it is essential to consider off-grid solutions based on renewable energy sources. [ABSTRACT FROM AUTHOR]

Using energy more efficiently is one of the easiest ways to save money, reduce greenhouse gas emissions, and meet growing energy demands. Electricity consumption control is an emergent topic worldwide. The passive house idea is not new, but it is still actual and is discussed by researchers. This paper brings to the reader's attention the combined use of fuzzy and fractional control methods to increase the performance of electricity consumption control, taking into account the current challenges in the energy field, together with a method for the automatic definition of fuzzy rules. In comparison with the no-control case, a 20% reduction in consumption is achieved with the present proposal. In the case of another control method, a 15% reduction was possible using Shakeri's team's method. The simulation of the proposed passive house control proves that it could ensure efficient electricity consumption that can be translated into electricity cost savings between 10 and 50 percent. [ABSTRACT FROM AUTHOR]

The European Commission introduced a package of measures to accelerate the shift to low-carbon energy transition in Europe. In 2014, EU member states agreed to reduce greenhouse gas emissions by at least 40% by 2030 compared to 1990 levels. The binding greenhouse gas emission targets for Member States from 2021 to 2030 for the transport, buildings, agriculture, waste, and land-use and forestry sectors were established. EU Member States should decide on their own how to meet the agreed upon 2030 target and implement climate-change-mitigation measures. All EU MSs have committed to prepare national energy and climate plans based on regulation on the governance of the energy union and climate action (EU)2018/1999, agreed as part of the Clean Energy for All Europeans package approved in 2019. The national plans outline how the EU Member States intend to implement the GHG reduction target by increasing their in energy efficiency, use of renewables, greenhouse-gas-emission reductions, interconnections, and research and innovation. This paper analyzes the energy and climate plans of the Baltic States and systematizes the main climate-change-mitigation policies in the energy sector targeting the household sector. The background of energy and climate planning is provided from a theoretical point of view, encompassing regional, local, and national energy and climate plans. The diffusion levels of renewables in the Baltic States were determined and the energy-climatic-friendly policies followed, by them, they were identified. [ABSTRACT FROM AUTHOR]

Many developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government's five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China's long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced. [ABSTRACT FROM AUTHOR]

To ensure the safety of aircraft operation, the current regional passenger aircraft maintains a large distance from the preceding aircraft in actual operation, which result in reducing the operation efficiency of airports and airspace, and increasing pollutant emissions. To address these issues, in this paper, two aircraft types are selected in which the CRJ-900 encounters the trailing wake vortices of the A380 in front. An improved strip model is developed to build the CRJ-900 overall response wake encounter value. First, the safety of the CRJ-900 longitudinal and lateral wake encounters in different flight stages is analyzed. Second, we calculate the critical safety separation and its impact on air transport efficiency. Third, we use the LTO model to measure the reduction of aircraft fuel consumption and pollutant emissions. The results demonstrated that the medium-sized aircraft CRJ-900 has the potential to reduce the wake separation when following the super-heavy A380 aircraft. In terms of the critical safety separation calculated by the safety index, the operating efficiency of airports and airspace could be effectively improved, allowing the reduction of pollutant emissions during aircraft take-off and landing. During the takeoff, level flight, and landing phase, the results are summarized as follows: when the CRJ-900 is 13km away from the A380, the maximum lift variation is 11334N, 8157N, and 7366N; the maximum rolling moment variation is 43836N•M, 35274 N•M, and 28487 N•M; the maximum value of the rolling moment coefficient (RMC) is 0.0171, 0.0160, and 0.0130; when the RMC critical value is 0.031, the maximum safe separation for different flight stages is 11960m, which is 1040m shorter than the existing separation; when the RMC critical value is 0.05, the maximum safe separation distance of each stage is 10083m, a reduction of 2917m compared with the existing separation; when the RMC threshold is 0.07, the maximum safe separation of different flight stages is 9021m, a reduction of 3979m compared to the existing separation; when the RMC value is between 0.031-0.07, the fuel consumption can be reduced by 7.9%–12.8%, and the pollutant emission can be reduced by 9.1%–12.8%. [ABSTRACT FROM AUTHOR]

To achieve the carbon neutrality goal, the industrial parks with heavy multi-energy consumption are gradually promoting green and low-carbon transitions. This transition is a long-term dynamic evolution process, which is affected by the strategies of different stakeholders and unpredictable events. It will lead to the industrial parks blindly promoting carbon emission reduction tasks. Therefore, it is necessary to analyze the stakeholders' strategy evolution trajectories based on the evolutionary game theory under changing scenarios to provide correct policy guidance for their carbon emission reduction process. In this paper, firstly, an evolutionary game model of carbon emission reduction in industrial parks is constructed, including an energy supplier, an industrial park operator, and the government. Secondly, the dynamic behavior characteristics of different stakeholders and the factors affecting the stability of the strategy equilibrium are analyzed thoroughly. Finally, different scenarios are formulated to simulate and analyze industrial parks' long-term dynamic evolutionary game law of carbon emission reduction. Furthermore, discussions and suggestions are provided to guide industrial parks' future carbon emission reduction transitions. [ABSTRACT FROM AUTHOR]

China's climate and environmental problems remained prominent. Energy transition was the key to improve climate and pollution, and it was at a critical period. Previous studies mostly focused on the impact of climate policies on the reduction of air pollutants and the environmental health impacts of individual sector or pathway policies. Thus, focusing on the synergistic abatement of CO 2 and air pollutants and health effects of energy transition in carbon neutrality was significant for building beautiful and healthy China. LEAP-HEA model was constructed to project energy demand, CO 2 and air pollutants, and assess energy transition's environmental health effects from 2020 to 2060. LMDI model was adopted to decompose the abatement contribution. Synergistic assessment index was used to estimate the coordinated abatement effects. Cost-effectiveness of energy transition and regional heterogeneity of PM 2.5 toxicity were not considered. The results indicated: (1) energy demand would decrease and structure would be optimized significantly under deep energy transition scenario. (2) Deep energy transition could promote earlier realization of carbon neutrality. It would contribute significantly to CO 2 and air pollutants abatement with strong synergistic effects. (3) Energy transition would reduce health risks with large economic benefits. Recommendations were proposed based on the conclusions. The framework of LEAP-HEA model. [Display omitted] • The synergistic abatement and health effect of energy transition were explored. • The models of LEAP, LMDI, exposure-response and the data of 2020 were used. • Energy transition would have significant synergistic abatement and health effect. • The paper has significance for promoting carbon neutrality and healthy China. [ABSTRACT FROM AUTHOR]

Cities have emerged as critical and challenging places for promoting the green and low-carbon transformation of the economy and society in the context of the "dual carbon" targets. Meanwhile, fiscal policy is also an indispensable component of the public policy framework supporting the green and low-carbon transformation. This paper uses the pilot project of "Comprehensive Demonstration Cities for Energy Conservation and Emission Reduction Fiscal Policies" ("ECER-CD" policy) implemented in China since 2011 as a quasi-natural experiment. This research theoretically analyzes and empirically tests the energy conservation and emission reduction effects of fiscal policies supporting green and low-carbon transformation utilizing methodologies such as time-varying DID and multiple periods and multiple groups of DID. The study finds that the pilot cities effectively reverse the behavioural bias of local governments and promote energy conservation and emission reduction efforts. This conclusion holds after undergoing robustness tests such as parallel trend analysis and heterogeneity treatment effects. The effectiveness of the pilot policy is attributed to the upgrade of industrial structure, improvement of energy efficiency, and the effects of green technology innovation. However, cities' geographic location and resource dependency can interfere with the effective implementation of policies. This paper also further explores the environmental dividends and economic consequences of the policy and finds that the pilot cities have certain environmental dividends and do not significantly restrain economic and social development. This study broadens the research perspective on fiscal policies in energy conservation and emission reduction and clarifies the pathways through which fiscal policies promoting green, low-carbon transformation drive energy conservation and emission reduction in cities. Moreover, it also improves the use of the Difference-in-Differences method in evaluating policy effects in scenarios such as the overlapping implementation of pilot policies and policy withdrawal. Finally, this paper proposes policy recommendations to provide more empirical evidence for China to accelerate the green and low-carbon transformation of the economy and society. [ABSTRACT FROM AUTHOR]

The paper presents an assessment of thermal energy consumption for heating in 10 buildings made in the OWT-67N prefabricated large-panel technology from 1983 to 1986. The work covers the years 2002–2020 in three periods: before and after thermal modernization and after the use of an innovative weather prediction heating system control in buildings. The analysis made it possible to assess the impact of carrying out a deep thermal modernization, and then installing a modern forecast regulation system in terms of reducing heat energy consumption for central heating purposes, as well as reducing greenhouse gas emissions, such as CO2, SOx, NOx, CO and benzo(a)pyrene, into the atmosphere. The implementation of deep thermal modernization in buildings allowed for savings of 19.8–35% of thermal energy consumption for heating. The use of additional regulation based on prediction saved from 4.8 to 23.5%, except for one building BU10, where there was an increase in final energy consumption by 2.1%. Replacing the weather regulation in heating stations with the forecast regulation additionally reduced the emission of pollutants by 11.1%, compared to the reduction of pollutants achieved as a result of the thermal modernization of buildings alone, amounting to an average of 29.7%. [ABSTRACT FROM AUTHOR]

China's food industry is a large energy consumer and carbon emitter due to its huge scale, so it cannot be ignored if China wants to achieve the goals of energy conservation, emission reduction, and clean production. It is necessary to conduct an in‐depth analysis of the energy environment efficiency of the industry. This paper measures the total‐factor energy environment efficiency (TFEEE) of China's food industry and calculates its energy‐saving and CO2 emission‐reduction potential. A method that combines the slacks‐based measure (SBM) model with meta‐frontier technology is adopted, which considers the heterogeneity of production between regions while dealing with the undesirable output (CO2 emissions). This method is used to calculate the energy environment efficiency of each province based on the group frontier (GTFEEE) and the meta‐frontier (MTFEEE). Through the difference between these two efficiencies, the energy‐saving potential is further decomposed into energy saving from management efficiency improvement and energy saving from technology catch‐up. The results show that, overall, the energy environment efficiency of China's food industry is low, and there are obvious technology gaps between regions. In 2013, the energy‐saving potential of China's food industry reached 49.28 million tce, accounting for 60.7% of the industry's energy consumption that year. Among them, 76% came from the improvement of management efficiency. And the CO2 emission‐reduction potential was 154.6 million tons. Finally, targeted energy saving and emission reduction recommendations were put forward. [ABSTRACT FROM AUTHOR]

In order to facilitate the carbon emission reduction to mitigate climate change, this paper proposes a coordinated multi-stage planning strategy for the transmission-level integrated electricity-gas-heating system. The strategy coordinates installations of gas-fired generation plants, renewable energy plants, gas wells, power-to-gas plants, transmission lines and pipelines, considering retirements of coal-fired generation plants. It can help facilitate carbon emission reduction of the electricity system as well as the integrated energy system. The objective is to minimize the total present value of the investment and the operation economic cost, with consideration of constraints from each sub-system and carbon emission restriction. In the case studies, the proposed planning strategy is verified to be able to obtain the installation plan of the related facilities. With which the system can reduce the proportion of fossil fuel energy utilization and increase renewable energy utilization. Hence, carbon emission reduction is achieved. In addition, it has demonstrated that integrating the multi-energy systems can help reduce the economic cost in the planning result. • Multi-stage planning strategy of the integrated energy system is proposed. • Energy conversions among different sub-systems are considered. • An aggregated model of district heating system is adopted. • Capability of carbon emission reduction is verified. • Contributions from flexibility of gas and heating systems are demonstrated. [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]

The current work aims to analyze the existing situation in Romania compared to other EU countries, regarding bovines herds, given that this species is one of the ones that causes the highest level of greenhouse gases, with a direct effect on the environment and global warming. This is the reason why the subject has become a priority not only at the community level, but also worldwide. Through the Common Agricultural Policy, important funds have been allocated at the level of the European Union, which will continue to be allocated, not only for the reduction of climate change, but also for the adaptation of the states of the world to these existing climate changes at the global level. Given the path in which animal husbandry influences sustainable development, through the study we have followed both the effective changes, but also the obtained productions, with a direct impact on consumption. It was found that both at the community level, as well as at the national level, there was a decrease in bovines herds in in the period 2016-2020, the reasons being primarily of an economic nature, but equally important being the social and environmental ones. The analysis was carried out starting from the data published by the National Institute of Statistics and Eurostat, data that were then processed and analyzed with the help of statistical methods. Based on these, the conclusions were formulated that show us that in Romania the number of bovines herds decreased by 11% in the period 2016-2021. At the European Union level, Romania ranks 10th in terms of bovines herds and 20th in terms of density/100 ha. Although there are advances in terms of applied technologies or more productive breeds, at the global level the objectives pursued by the reduction of greenhouse gas emissions have not been influenced by these advances, which makes the activity of raising bovines to be considered one with effects negative effects on the environment, but also high consumption of energy and water, which in turn have a negative impact on climate change. [ABSTRACT FROM AUTHOR]

The call for green shipping is increasing, and the reduction of greenhouse gas emissions from ships becomes more and more important. Traditional ship energy efficiency monitoring is based on the noon reports, which are susceptible to human error and have a time delay. Many ship energy efficiency monitoring systems have been designed and developed, but they usually cannot send data to the shore in time. In order to identify abnormal fuel consumption in time, this paper realizes a big data collection system for ship energy efficiency monitoring based on the BeiDou System. The system installed on two sister container ships has already collected a lot of data. Big data analysis methods, such as principal component analysis (PCA) and correlation analysis, are applied in the system to realize data visualization and analysis. Using PCA, it turns out that the shaft power of the main engine is related to a certain ship speed, which is also affected by load and weather conditions, and is the biggest factor in determining fuel consumption. To realize the assessment of hull fouling and the optimization of ship trim, a useful physics-based analysis is proposed. The analysis shows that the fouling of ship body greatly increases its resistance. Our analysis method can also find the best trim under specific loading condition. All these points are important for reducing fuel consumption and improving ship efficiency. [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]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

In the twenty-first century, there has been an increase in energy demand and waste production, due to the rising population of the world. One good approach for satisfying the energy demand and overcoming the waste management issues is to convert waste to energy. Additionally, using waste biomass as the feedstock of waste-to-energy (WtE) conversion methods makes them renewable and green and also helps the environmental challenges and reduces the emission of greenhouse gases (GHGs). Gasification is a thermochemical WtE route, which can produce hydrogen-rich gaseous biofuel called synthetic gas (syngas), from wastes. In this paper, different aspects of gasification process are reviewed with greater focus on catalyst usage. Syngas processing steps, which increase the quality and H 2 content of the syngas to form bio-hydrogen, are discussed. Solid oxide fuel cell (SOFC) technology is one of the most promising techniques of renewable energy production due to their environmental cleanness characteristics and high efficiencies. Thus, one of the best ways to exploit the energy content of the bio-hydrogen product of gasification is to employ it in a SOFC. Therefore, waste biomass gasification process can be integrated with SOFCs to build high efficiency systems for production of clean and renewable energy from waste, which are called integrated gasification fuel cell (IGFC) systems. These systems provide the opportunity of further upgrading of syngas inside the SOFC. In this paper, we are going to briefly discuss fuel cell technology (especially SOFCs) and review SOFC applications from the aspect of integration with gasification process (IGFC system). Finally, the impacts and issues of gasification process and SOFC technology are considered. • Different concepts related to waste and waste management are discussed. • Waste-to-Energy conversion methods, are presented. • Gasification process is discussed in detail with focus on its catalyst usage. • Syngas processing for bio-hydrogen production is considered. • Integrated gasification solid oxide fuel cells are considered as an efficient system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

Energy Internet (EI) is typically characterized by digitalization and clean energy that seeks to revolutionize the energy system and reduce carbon emissions. Even though several scholars conclude that EI accelerates the clean energy transition of energy system, since the controversial relationship between digitalization and energy consumption in academia, current studies on the carbon emission reduction advantages of the EI are still in dispute. This paper employs the effect of EI's construction on the carbon emission peak goal of China's energy system based on the system dynamics model and different scenarios. The simulation results find that: (1) the construction of the EI could enable China's energy system to meet the carbon reduction commitment in 2028, with a carbon emission peak of 11.61 billion tons; (2) As digitalization and clean energy become more extensively employed, rising energy demand is satisfied by the manner of consuming low-carbon electricity energy. This is thought to be the primary factor that could promote China to achieve the carbon peak goal earlier than expected; (3) The advancement of digitalization has further promoted the decoupling of China's economic growth from carbon emissions. It is projected that China's energy system will still achieve the carbon peak goal by 2030 when the expected annual GDP growth rate is increased to 6.32%, 5.75%, and 4.6% for the years 2020–2025, 2026–2030, and 2031–2035, respectively. These findings might provide a new perspective for quantitative research on the environmental outcomes of the EI and the relationship between environmental improvement and economic growth. [ABSTRACT FROM AUTHOR]

Taiwan's per capita carbon emissions ranks first in Asia. Whether Taiwan's current "2025 Non-Nuclear Homeland" energy transition policy can achieve the goal of greenhouse gas reduction is an issue that needs to be studied urgently. On the basis of studying the status quo of energy supply and demand and carbon emissions in Taiwan, this paper first uses an econometric model to predict Taiwan's energy demand from 2021 to 2030, and then uses a Markov chain model to predict its energy structure changes and CO 2 emission trends under different scenarios, and evaluates the impact of its energy transition policies on carbon emission reduction goals. On this basis, by comparing the carbon trading markets on both sides of the Taiwan strait, the feasibility of and obstacles to the cross-strait cooperation in the carbon trading market are discussed in depth, and the opportunities for future cross-strait cooperation in the carbon trading market are proposed innovatively. The empirical results of this paper show that the carbon emissions in 2025 under the energy transition policy will be reduced by 59.8–61.1 million tons compared with those without planning constraints, but compared with the carbon reduction target (a reduction of 124.8–133 million tons), there is still a long way to go. The contribution potential of the annual carbon emission reduction target is only 45.9%–47.9%, and the contribution potential in 2030 is 57.2%–60.1%. The current "2025 Non-Nuclear Homeland" policy is not in line with Taiwan's current reality, and it is difficult to achieve the expected carbon reduction goal. In order to realize the energy transition in Taiwan in the future, it is necessary to make overall planning of energy policies, explore the cross-strait power cooperation model, and gradually try to build a cross-strait carbon trading market. [ABSTRACT FROM AUTHOR]

The optimization of energy consumption in buildings' HVAC systems plays a crucial role in reducing greenhouse gas emissions worldwide. In new and deeply-renovated buildings, characterized by modulating terminal units and aiming at the maximum exploitation of renewables, an accurate hydraulic balance of the distribution network may become critical, resulting in a significant increase of pumping energy consumptions and a deterioration of indoor thermal comfort conditions. In the present paper, we compare the performance of traditional manual balancing valves and new pressure independent control valves (PICVs), used to balance the hydronic loop of HVAC systems. To perform this analysis, a new MATLAB-Simulink model has been specifically developed to simulate the behavior of PICVs and has been used in an application case study. The efficiency of manual and pressure independent control valves is evaluated numerically by simulating a multi-zone distribution network under variable operating conditions and considering different control strategies of the circulating pump. Results show that in off-design conditions, when some of the branches of the hydraulic network are closed, traditional manual balancing valves are not able to guarantee the nominal mass flow rate in the remaining loops. On the contrary, no significant variations of water mass flow rate are observed when PICVs are adopted, even in partial load conditions. Despite their additional cost, PICVs allow to ensure better indoor thermal comfort sensations for individuals, avoiding under/over-heating of rooms and, moreover, yield a decrease of the pump electric consumption with respect to traditional manual balancing valves. In addition, based on the obtained results, general rules concerning the adoption of PICVs are provided, depending on the extension of the hydraulic loop and the adopted pump control logic. The reported results highlight the role that PICVs can play to ensure energy savings in HVAC systems without penalizing users' indoor comfort conditions. [ABSTRACT FROM AUTHOR]

• The data requirements of quota methods are summarized, and a city-scale database containing 670 credible government office buildings is established. • By comparing the processes, the results and applicability, the selection basis of quota methods under different conditions is refined. • A flow chart of the formulation process and method selection of city-level building energy consumption quotas is constructed. • It is proposed that special attention should be paid to the outliers, and the characteristics of outliers in Chongqing are summarized. Energy consumption quota policies are effective management measures to promote energy conservation and emission reduction in China. Cities need to choose an appropriate method to formulate local energy consumption quota standards. This paper is based on the data of 670 government office buildings in Chongqing and the selected quantile method (QM), quota-level method (QLM) and multiple linear regression (MLR) method, which are widely used in the formulation of city-level energy quotas. By comparing their interpretability, evaluation, consistency and stability, the application conditions and applicability of each method are summarized. MLR has the strongest explanatory power but the highest requirements for the technology and information dimensions. The QLM is more explanatory and stable than the QM and is more suitable for the initial stage of energy quota management. When using the QLM, we should consider scientific classifications and reasonable quota levels. Special attention should be given to "outliers" with abnormal evaluations of the quota results. The outliers in Chongqing are characterized as buildings that have been used for more than 10 years and have an area of less than 5000 m2. Finally, this paper constructed a flow chart of the formulation process and method selection to help policymakers better understand how to choose the most appropriate method and identify inefficient buildings. [ABSTRACT FROM AUTHOR]

• Earlier phase-out of coal is not the best answer to achieve energy transition. • The 2050 plan and historical RES investments maxima are not enough to reach climate neutrality. • What is the effect of regional RES limits over Nationwide RES limits. • Where will be the states in Germany having major RES deployment. • Myopic optimization reveals new challenges for energy policy. This paper will introduce the open-source model MyPyPSA-Ger, a myopic optimization model developed to represent the German energy system with a detailed mapping of the electricity sector, on a highly disaggregated level, spatially and temporally, with regional differences and investment limitations. Furthermore, this paper will give new outlooks on the German federal government 2050 emissions goals of the electricity sector to become greenhouse gas neutral by proposing new CO 2 allowance strategies. Moreover, the regional differences in Germany will be discussed, their role and impact on the energy transition, and which regions and states will drive the renewable energy utilization forward. Following a scenario-based analysis, the results point out the major keystones of the energy transition path from 2020 to 2050. Solar, onshore wind, and gas-fired power plants will play a fundamental role in the future electricity systems. Biomass, run of river, and offshore wind technologies will be utilized in the system as base-load generation technologies. Solar and onshore wind will be installed almost everywhere in Germany. However, due to the nature of Germany's weather and geographical features, the southern and northern regions will play a more important role in the energy transition. Higher CO 2 allowance costs will help achieve the 1.5-degree-target of the electricity system and will allow for a rapid transition. Moreover, the more expensive, and the earlier the CO 2 tax is applied to the system, the less it will cost for the energy transition, and the more emissions will be saved throughout the transition period. An earlier phase-out of coal power plants is not necessary with high CO 2 taxes, due to the change in power plant's unit commitment, as they prioritize gas before coal power plants. Having moderate to low CO 2 allowance cost or no clear transition policy will be more expensive and the CO 2 budget will be exceeded. Nonetheless, even with no policy, renewables still dominate the energy mix of the future. However, maintaining the maximum historical installation rates of both national and regional levels, with the current emissions reduction strategy, will not be enough to reach the level of climate-neutral electricity system. Therefore, national and regional installation requirements to achieve the federal government emission reduction goals are determined. Energy strategies and decision makers will have to resolve great challenges in order to stay in line with the 1.5-degree-target. [ABSTRACT FROM AUTHOR]

The International Maritime Organization has set a goal to achieve a 50% reduction of total annual greenhouse gas emission related to the international shipping by 2050 compared to the 2008 baseline emissions. Malaysia government has taken an initiative to investigate the assessment (cost-effectiveness) of this International Maritime Organization's short-term measure on Malaysian-registered domestic ships although this measure is only for international merchant ship. To achieve this, this paper collected the ship's data from the shipowners from 25 sample ships. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times. Based on cost-efficiency analysis, it creates for the purpose of compliance with the operational carbon intensity indicator. It found that even if it is possible to bring an asset back into service, it may not be possible to do so in a manner that generates a profit or complies with applicable regulations. In these situations, it may be more prudent to scrap the asset rather than run the risk of having it become a stranded asset. This is especially true for older tankers. Alternatives with lengthy payback periods are not desirable for the domestic tanker fleet that is already in operation. [Display omitted] • International Maritime Organization cut greenhouse gas emissions. • This report collects shipowner data from 25 sample ships. • Low engine power limitation can increase sailing times. • It found that reactivating an asset may not be profitable or compliant. • Instead of risking stranding, it may be better to scrap the asset. [ABSTRACT FROM AUTHOR]

The signatory countries of the Paris Agreement must submit their updated Intended National Determined Contributions (INDCs) to the UNFCCC secretariat every five years. In Colombia, this activity was historically carried out with a wide set of diverse non-interconnected sector-specific models. Given the complexity of GHG emissions reporting and the evaluation of mitigation actions on a national scale, the need for a centralized platform was evident. Such approach would allow the integration and analysis of potential interactions among sectors, as well as to guarantee the homogeneity of assumptions and input parameters. In this paper, we describe the construction of an integrated bottom-up LEAP model tailored to the Colombian case, which covers all IPCC sectors. An integrated model facilitates capturing synergies and intersectoral interactions within the national GHG emissions system. Hence, policies addressing one sector and influencing others are identified and correctly assessed. Thus, 44 mitigation policies and mitigation actions were included in the model, in this way, identifying the sectors directly and being indirectly affected by them. The mitigation scenario developed in this paper reaches a reduction of 28% of GHG emissions compared with the reference scenario. The importance of including non-energy sectors is evident in the Colombian case, as GHG emission reductions are mainly driven by AFOLU. The first section describes the GHG emissions context in Colombia. Next, we describe the model structure, main input parameters, assumptions, considerations, and used LEAP functionalities. Results are presented from a GHG emissions accounting and energy demand perspective. The model allows for the correct estimate of the scope and potential of mitigation actions by considering indirect, unintended emissions reductions in all IPCC categories, as well as synergies with all mitigation actions included in the mitigation scenario. Moreover, the structure of the model is suitable for testing potential emission trajectories, facilitating its adoption by official entities and its application in climate policymaking. [ABSTRACT FROM AUTHOR]

Although there have been international frameworks for limiting global warming, however, sustainable actions are not on the same track in terms of speed and scale due to the lack of an explicit pathway. A large strand of the literature has examined the emissions-mitigating effect of R&D expenditure and biofuel energy consumption but in a linear framework and disregarded the factors that cause non-linearity. In that respect, this study aims to offer a new perspective on the asymmetric response of greenhouse gas emissions to government energy R&D expenditure and biofuel use in the United States over the 1981–2020 period using a nonlinear time series approach. The results confirm the asymmetrical relationships between government energy R&D, biofuel use, and greenhouse gas emissions. In the long run, a positive shock in energy R&D expenditure reduces greenhouse gas emissions, while a negative shock increases them. More importantly, the reducing effect of positive shock is more dominant than the enhancing effect of negative shock in energy R&D. Similarly, it is shown that the reducing effect of a positive shock on ethanol consumption on greenhouse gas emissions is stronger than the increasing effect of a negative shock. After the estimations, this paper presents two critical implications, political and practical. (i) The government's energy R&D expenditures and biofuels have an important role in the fight against climate change and the clean energy transformation process. (ii) Researchers should also consider asymmetric effects when examining energy technologies, renewable energy, and environmental issues. • Examines the greenhouse gas emissions response to government energy R&D expenditures and bioethanol consumption in the US. • Follows an asymmetric and non-linear method. • Confirms the asymmetrical relationships between energy R&D, bioethanol, and greenhouse gas emissions. • Provides implications for environmental quality and the clean energy transition. [ABSTRACT FROM AUTHOR]

Almost all countries have committed to develop Nationally Determined Contributions (NDC) to reduce GHG emissions. They determine the level of GHG mitigation that, as a nation, they will commit to reducing. Zimbabwe has ambitious and laudable GHG mitigation targets. Compared to a coal-based future, emissions will be reduced by 33% per capita by 2030. If historical climate conditions continue, it can do this at low or negative cost if suitable sources of climate financing are in place. The NDC plots a positive future. However, much of Zimbabwe's NDC mitigation center on hydropower generation and other measures that are dangerously vulnerable to climate change. Should the climate change in accordance with recent projections, these investments will be at risk, severely constraining electricity supply and causing high degrees of economic damage. This paper uses the Open-Source energy Modelling SYStem (OSeMOSYS) to consider two adaptation pathways that address this vulnerability. In the first, the country turns to a historically accessible option, namely the deployment of coal. In so doing, the electrical system is made more resilient, but emissions ramp up. The second pathway 'climate proofs' the power sector by boosting solar and wind capacity, using hydropower to provide balance for these new renewable resources, and introducing significant energy efficiency measures. This second pathway would require a set of extra accompanying investments and changes to the power market rules, but allows for both system resilience and NDC targets to be met. The paper shows that Zimbabwe's low emissions growth can be made resilient, and while this path promises strong benefits, it also requires strong commitment and political will. From this paper insights are drawn and requirements for future analysis are made. Two critical insights are that: (i) NDCs that focus on mitigation should include resilience in their design. If they do not, they can introduce deep vulnerability; (ii) a departure from historical electricity market structures appears to hold potential for strong environmental, cost and reliability gains. [ABSTRACT FROM AUTHOR]