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Industrial energy management is critical to ensuring efficient energy usage, market viability, and greenhouse gas emission reductions. In this study, the aim is to investigate energy management practices in paper and pulp industries (PPI) of Bangladesh. The study identifies several barriers to adopt energy management practices; "Lack of governmental attention", "Inadequate staff awareness" and "limited access to capital" are identified as the major constraints. In addition, HVAC systems and compressed air systems present higher barriers compared to electrical motor and pump systems while looking at the barriers by technology areas. On the other hand, "Owner's demand", "Commitment from the top management" and "Pressure from the customers and different non-Governmental organization" are found to be the dominant drivers of energy management in the studied PPI. Energy management practices can enhance the energy efficiency approximately by 4–5 % according to the study. Furthermore, this study reveals that the majority of PPIs are unaware of the energy service companies (ESCO) with the lack of a standardized system for energy audit, as well as a lack of trust and information, appearing to be the obstacles behind this. • Energy management practices in paper and pulp industries of Bangladesh are shown. • Barriers and drivers to energy management practices in paper and pulp industry are presented. • Barriers to energy efficiency measures by technology area are discussed. • Barriers to consult energy service companies (ESCOs) are presented. [ABSTRACT FROM AUTHOR]

• We study the relationship between GVC embedding and carbon emission density. • A mediation effect model was established to test the mechanism. • There is a U-shaped relationship between urban GVC embedding and carbon emission density. To achieve its carbon peak and neutrality plan, whether China's global value chain (GVC) embedding has a carbon emission reduction effect is a question worthy of attention. This paper measures the GVC embedding degree of 218 Chinese cities from 2000 to 2016, and constructs a panel data model to investigate the impact and its mechanism of GVC embedding on carbon emission intensity. This study finds that there is a significant U-shaped relationship between GVC embedding and carbon emission intensity, and a series of robustness test results support this conclusion. Export scale, energy consumption structure and technological innovation play a mediation role in the impact path of GVC embedding on carbon emission intensity. Based on this, this paper proposes that while participating in GVC, China needs to actively utilize the emission reduction effect of GVC, promote the transformation of export mode to high quality, reduce the use and dependence on high-carbon resources such as coal, and encourage companies to innovate. [ABSTRACT FROM AUTHOR]

This work aimed at solving the environmental problem of the hottest greenhouse gas reduction. The paper identifies the energy electricity demand, proposes solutions, and calculates the greenhouse gases emitted in each of the interconnected networks available in Cameroon. For a total production estimated at 1292 MW, the country's electricity production depends heavily on hydropower plants (57%), thermal power plants (42%), and only 1% of biomass. Specifically, biomass would contribute to 40% of the supply of the demand if it is sufficiently exploited. Hydroelectricity needs transmission for long distances. The electricity demand in the median economic scenario is the basis of this study. GHGs were calculated using the tool MESSAGE. The results of this study show that it will be possible, without taking into account the fact that biomass is clean energy, to avoid 462 kt of CO 2 eq and 14 kt of CO 2 eq for South Interconnected Network and East Interconnected Network respectively. The amounts of CH 4 , SO 2 , and NO x are not statistically significant. This study takes into account the main existing energy sources in the country. The specificity of this study is to treat the three interconnected networks of the country separately. The use of biomass in local power plants was proposed to reduce dependence on fossil fuels. This study shows that to reduce the GHG emission and the loss of electricity due to its transmission in the country, it is better to use biomass instead of fossil fuels for the production of electricity in Cameroon. [Display omitted] • Electricity demand of the country was identified. • The quantity of GHG emitted from electricity generation in Cameroon was estimated. • Biomass power plants were introduced in the electricity mix of the country to promote local production. • Local realities were taken into account and dependence of imported fossil fuels was reduced. • Biomass instead of fossil fuels was to avoid emission of 462 kt of CO 2 eq. [ABSTRACT FROM AUTHOR]

Challenges and future perspectives of desalination integration are presented. [Display omitted] • Different optimized models for desalination technologies integration are summarized. • The control strategies of RES-desalination for reducing environmental are discussed. • Impact of desalination process innovation on energy saving and emission reduction. In the present framework, desalination, as an energy-intensive industry, has garnered increased attention due to the imperative need for reducing energy consumption. In this paper, various challenges in the integration and optimal design of desalination processes have been presented. The energy consumption, energy supply method, water production method and improvement measures of various desalination are studied in detail, of which energy consumption is a major aspect. This article summarizes the integration modes of different desalination technologies. Low integration density, inadequate energy utilization and unsystematic theory guidance have been the focus of research. Operational strategies and optimal design methods for the integration of renewable energy and desalination technologies are studied in detail. The integration of renewable energy emerges as a pivotal trend, contributing significantly to the reduction of carbon footprints and costs. Additionally, the significance of recently developed desalination processes, such as pre-treatment process, equipment enhancements and advanced materials have been discussed. Furthermore, various unresolved issues in de integration desalination technologies system have been investigated in the paper along with the possible solutions to address the reported open issues. By exploring the integration of desalination technologies, the paper aims to provide valuable insights for enhancing the efficiency of commercial desalination plants. [ABSTRACT FROM AUTHOR]

Electricity is fundamental for supporting economic development in emerging economies. Power generation from clean energy sources may help to meet societal needs such as increasing electricity demand while complying with contemporary global challenges (e.g. climate change). This paper aims at qualitatively describing the development of clean energy technologies in Mexico by using a multi-perspective analytical framework. By integrating a meta-theoretical framework for national energy transitions and core concepts from policy mixes for sustainability transitions literature, a series of stylised facts are developed to qualitatively describe the evolution of clean energy technologies in Mexico from 1879 to 2021. Interactive governance theory is used as an analytical framework to synthesise these storylines by highlighting the role and interactions among technologies, actors, and policy instruments in governance processes. The case study revealed that the ever-growing electricity demand in Mexico have called for exploring different available energy sources and technologies over time. Diminishing oil and gas domestic reserves, increasing concerns around environmental issues, and worldwide agreements on greenhouse gas emission reductions have been the main drivers for clean energy and energy efficiency development in Mexico. However, different barriers to a clean energy transition in Mexico have been identified and discussed in this study: (1) access to a vast oil and gas resources in the past reinforced the position of fossil-fuel incumbent regimes, displacing clean energy technological niches; (2) lack of investment in clean energy research, development, and innovation; (3) policy paradigms have shifted based on (dynamic) societal needs and socio-political interests in favour of fossil fuel power generation. To overcome these barriers and allow a transition towards a clean energy electricity system in Mexico, multiple policy instruments have been identified and discussed. • The paper describes the evolution of clean energy technologies in Mexico. • A multi-perspective analytical framework is used to create micro-logics. • The interactive governance approach is used to synthesise these micro-logics. • Barriers and drivers for a clean energy transition in Mexico are discussed. • Energy policy mixes towards a clean energy transition are discussed. [ABSTRACT FROM AUTHOR]

The increase in computer numerical control machine efficiency highly contributes to environmental emission reduction and energy-savings. Path and trajectory optimizations are used to improve machine efficiency in a coverage motion such as pocket milling, polishing, inspection, gluing, and additive manufacturing. Several studies have proposed coverage motion optimization in improving machine efficiency for time and energy consumption. Ensuring the smoothness and satisfaction of the machine constraints in coverage motion is necessary. This paper proposes a multi-objective path and trajectory optimization to obtain a trade-off between time and energy consumption for coverage motion. Jerk limited acceleration profiles describe the trajectory where velocity profiles generated for each linear segment attain desirable velocities. The energy model of an industrial two-axis feed drive system is used in finding solutions to the optimization problem. The non-dominated sorting genetic algorithm II generates a Pareto front for trade-off time and energy consumption solutions. Simulation results of the proposed method are validated through experiments using the industrial two-axis feed drive system. Experimental results show the effectiveness of the proposed approach where time reduction and energy savings are 10.05% and 2.10%, respectively. In addition, the optimized path has a lower maximum error of 76.6% compared to the constantly commanded velocity optimized path. • A method of simultaneous trajectory generation and path optimization is proposed. • Jerk limited acceleration profiles describe the trajectory. • The NSGA II is used to find the trade-off between time and energy consumption. • The best trade-off solution achieves time reduction and energy savings of 10.05% and 2.10%. • Optimized path motion with variable velocities reduces maximum error by 76.6%. [ABSTRACT FROM AUTHOR]

[Display omitted] • Difference in working principle of Solar Thermoelectric Generators (STEGs) and PV-TEG Hybrid Generators is discussed. • Design parameter optimization of TEG only system is not same as that for STEG and PV-TEG hybrid system. • Enhancement in the concentration ratio improves TEGs efficiency, leading to increased conversion efficiency of the hybrid system. • Micro-channel heat pipe significantly reduces the number of TEG used, thus, reducing the overall cost of the system. With the continuously increasing demand for energy, reduction in greenhouse gas emission for daily energy usage is a challenging task. Solar energy based technologies possess the potential to address this challenge since sun is a renewable and abundant source that does not produce any emissions. It would be additional benefit if in the process of using such technologies, wasted heat energy is also converted into electrical energy. Thus, integration of thermoelectric and photovoltaic hybrid systems offers the flexibility to exploit solar spectrum across full wavelength. Thermoelectric Generator (TEG) when integrated with solar electricity conversion technologies result in fabrication of (i) solar thermoelectric generators (STEGs) and (ii) photovoltaic-thermoelectric (PV-TEG) hybrid devices with enhanced efficiency. Improvements in the conversion efficiencies of these technologies would aid in making solar energy at par with conventional forms of energy generation. This paper reviews the prospect of integrating TEG with solar electricity conversion technologies by examining the recent efforts in the field. In particular, the difference in the working of these two type of devices have been focussed on. This review presents in-depth analysis of the state-of-the-art methods used to achieve optimum performance. Moreover, various applications are stated and PV efficiency and losses are discussed along with possible resolutions. Furthermore, recent advancements in these device technologies have been compiled and cost and commercialization aspects have been focussed on. The review aids as a guide to select appropriate procedure of optimizing the performance in these devices as per requirements and specific application. [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 customers of textile wet processing plants have committed to reduce their greenhouse gas emissions from outsourced manufacturing activities. The textile brands directly use specific energy consumption values to analyze and set steep, time-bound emission intensity reduction targets for the energy intensive textile wet processing plants. However, the direct use of specific energy consumption values to evaluate energy savings can be misleading. In this paper, the authors propose a methodological framework to systematically evaluate energy performance and monitor energy savings in the textile wet processing plants. Further, the approach was extended to analyze the energy performance monitoring practices and identify energy conservation measures. The proposed framework was developed based on thorough analysis of the manufacturing process of textile wet processing plants and the principles of ISO 50001. A textile wet processing plant was chosen as a case study for illustrating the effectiveness of the framework using multiple regression method. Bottom up approach for benchmarking was used and yet significantly simplified by the introduction of an innovative parameter "program mix factor" and thereby evaluate "equivalent specific energy consumption". The predicted values for specific energy consumption were found to be within a close error range of ±10 % of the actual data. The proposed methodological framework is therefore innovative, simple and yet comprehensive to conduct internal benchmarking in textile wet processing plants. The textile brands are suggested to use equivalent specific energy consumption instead of specific energy consumption for energy performance monitoring of their textile wet processing plant suppliers. The authors also conducted a survey in fifteen textile wet processing plants to assess the prevailing energy monitoring practices. The results of the survey suggests that only 20 % of the plants are practicing basic level energy performance monitoring, while the remaining 80 % are at minimal level. • Textile wet processing plants were analyzed to identify the parameters required to normalize specific energy consumption • A simplified methodological framework was developed for the textile wet processing plants and the textile brands • The framework serves as a useful tool to evaluate, monitor the realistic energy performance & identify conservation measures • The textile brands are suggested to use equivalent specific energy consumption to monitor energy performance • The study identified the low levels of energy monitoring practices in textile wet processing plants in South Asian countries [ABSTRACT FROM AUTHOR]

The Allam cycle is a novel oxy-fuel power system that has the potential to achieve efficient negative carbon emissions. Compressed carbon energy storage (CCES) technology could improve the stability of power plants. A biomass gasification Allam cycle combined with the CCES system is proposed and evaluated in this research. The energy efficiency of the Allam-CCES cycle during the charge and discharge time is 36.43 % and 39.45 %, respectively. The round trip efficiency (RTE) of the CCES system is 62.04 %. The exergy destruction of the Allam-CCES system is 317.02 MW. Economic analysis shows that the proposed system has a net present value of 447347.97 k$, implying benefits in economic performance. The total cost rate of the Allam-CCES system is 6959.63 $/h. The influence of the storage pressure on the CCES system is evaluated. The RTE drops from 64.55 % to 61.12 % as the high storage pressure rises. The variation of RTE has a crest when the low storage pressure is near critical pressure. The highest RTE is 90.71 % in the research range of low storage pressure. This paper could provide information on biomass gasification Allam cycle integrated with CCES technology, and offer insights to realize efficient and economic carbon emissions reduction. • Compressed CO 2 energy storage is integrated with biomass gasification Allam cycle. • Thermodynamic and economic performance of the system is assessed. • The effects of energy storage pressure on the system performance are discussed. • The power efficiency during the charge and discharge time is 36.43 % and 39.45 %. • The net present value of the system is 447347.97 k$. [ABSTRACT FROM AUTHOR]

An optimization model that incorporates all combinatorically feasible inter-plant collaboration networks is developed using P-graph. It has been theoretically proven that time-sliced-based energy planning optimization has positive impacts and is capable of achieving carbon emissions reduction goals and minimizing costs simultaneously. However, as the number of entities increased, an exponential growth in possible combinatorial feasible coalitions is anticipated. Therefore, an extension of the P-graph optimization tool that is capable of generating all possible outcomes in multi-period P2P energy trading – PEP (P-graph for energy planning) is developed. The PEP software can be effectively used in modelling complex process networks graphically and solving optimization problems with the combined advantages of combinatorial algorithms and mathematical programming. In this paper, a systematic framework for implementing P2P energy trading using PEP software is proposed and demonstrated using a real-life case study. [Display omitted] • An optimization tool – PEP software is developed to model P2P energy trading scheme. • The software is capable of generating all possible financial outcomes effectively. • Optimal coalition structure is chosen based on the highest cost savings. • Marginal contribution analysis is done to ensure fair profit distribution. • The sample case study showed that entities can reduce electricity bills by 6.75 %. [ABSTRACT FROM AUTHOR]

To improve space/energy utilization and meet various households' needs, a high efficient and multifunction concentrated solar-air heat pump system(MC-SA-HP) is proposed in this paper. The concentrator is used to lift the energy density and unit generation of photovoltaic panel, and its three-dimensional feature could realize the layered utilization of space by placing the air source evaporator in the spare part below. By different operating strategies, the system could provide heating, electricity, and cooling. Through testing, MC-SA-HP obtained mean electrical generation and efficiency of 146W and 14.6%, condensing heat of 2114W, COP th and COP PVT of 3.7 and 4.4. Compared with the system using flat-panel photovoltaic, it could improve the electrical generation by 71.8%, heating capacity by 5.9%, total output by 12.6%, overall efficiency of 9.5%, COP PVT by 7.3%, and exergy efficiency of 36.1%. In the cooling mode during experiment, the water temperature drops from 14.6 to 2.6 °C, generating 1.51 × 107 J cooling capacity, and an average COP c of 2.3. The multifunction feature increases the attractiveness and feasibility of this novel system. After calculation, the high-efficient and compact MC-SA-HP system shows great effect on cost and emission reduction, which could help to better cope with climate change and achieve the goal of carbon peak and carbon neutrality. [ABSTRACT FROM AUTHOR]

Reducing the shipping sector's contribution to climate change requires urgent emission reductions this decade. Both weather routing and wind propulsion offer immediate solutions, where combining sails with efficient routing amplifies the performance of each technology. However, while large emission savings are theoretically available, the impact of stochastic uncertainty from wind forecasts is unknown. Here, we present a novel approach that exploits fuel consumption calculations from over a thousand departures across three routes to characterise stochastic uncertainty. We show that routes with ideal wind conditions and long voyage times are most sensitive to uncertain forecast inputs, reducing savings from Flettner rotors and weather routing by up to 44% when a priori weather routing strategies are used. This paper further shows how an adaptive weather routing strategy can be used as an accurate prediction tool to reduce uncertainty on all routes investigated, reliably amplifying carbon savings from Flettner rotors by between 1.16 and 2.48 times typical great circle route savings. Overall, this paper provides greater assurance around the previously estimated carbon savings that serves to strengthen confidence in a wind-assisted decarbonisation strategy and its potential to provide essential emission reductions this decade. • We develop an a priori strategy to quantify stochastic uncertainty. • We discuss stochastic uncertainty when weather routing ships with wind propulsion. • We identify characteristics of routes that display high sensitivity to uncertainty. • We develop an adaptive strategy to reduce the impact of forecast uncertainty. • We discuss weather routing and wind propulsion as a decarbonisation strategy. [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]

Heavy-Duty Vehicles (HDVs) pose a significant challenge in meeting emissions reduction targets. However, studies on estimating emissions from Irish HDV fleet are rare. This paper estimates fuel consumption and CO 2 emissions from tractor-trailers that occupy nearly half of Ireland's HDV fleet using the European Commission recommended VECTO tool. To improve the estimation accuracy, driving cycles specific to Irish road conditions were developed utilising real naturalistic driving data from trucks. The Irish driving cycles significantly differ from the VECTO inbuilt driving cycles in percentage time spent in different gears, fuel consumption, and CO 2 emissions. CO 2 emissions estimated with Irish driving cycles range from 733 to 1961 g/km, while with VECTO driving cycles, the values ranged from 728 to 1865 g/km. Further, the study evaluated the sensitivity towards payload, road gradient, and idling percentages. The study insights would provide an essential evidence base for policymakers in Ireland. [Display omitted] • Developed Irish urban, regional, and freeway driving cycles. • Employed the VECTO tool to assess CO 2 emissions from Irish heavy-duty vehicle fleet. • Focused on tractor-trailers with a major share in the Irish fleet. • Evaluated the effect of idling, gradient, and payload on CO 2 emissions. • Fuel consumption is underestimated by up to 7.1% when the road gradient is ignored. [ABSTRACT FROM AUTHOR]

In this paper, the energy, exergy, economic, environmental, steady-state, and process performance modeling/analysis of hybrid renewable energy (RE) based multigeneration system is presented. Beyond the design/performance analysis of an innovative hybrid RE system, this study is novel as it proposes a new methodology for determining the overall process energy and exergy efficiency of multigeneration systems. This novel method integrates EnergPLAN simulation program with EES and Matlab. It considers both the steady-state and the process performance of the modeled system on hourly timesteps in order to determine the overall efficiencies. Based on the proposed new method, it is observed that the overall process thermodynamic efficiencies of a hybrid renewable energy-based multigeneration system are different from its steady-state efficiencies. The overall energy and exergy efficiencies reduce from 81.01% and 52.52% (in steady-state condition) to 58.6% and 39.33% (when considering a one-year process performance). The integration of the hot water production with the multigeneration system enhanced the overall thermodynamic efficiencies in steady-state conditions. The Kalina system produces a total work output of 1171 kW with a thermal and exergy efficiency of 12.23% and 52% respectively while the wind turbine system produces 1297 kW of electricity in steady-state condition and it has the same thermal/exergy efficiency (72%). The economic analysis showed that the Levelized cost of electricity (LCOE) of the geothermal energy-based Kalina system is 0.0103 $/kWh. The greenhouse gas emission reduction analysis showed that the proposed system will save between 1,411,480 kg/yr and 3,518,760 kg/yr of greenhouse gases from being emitted into the atmosphere yearly. The multigeneration system designed in this study will produce electricity, hydrogen, hot water, cooling effect, and freshwater. Also, battery electric vehicle charging is integrated with process performance analysis of the multigeneration system. [Display omitted] • A novel methodology for multigeneration systems' steady-state and process performance evaluation. • Modeling and analysis of a geothermal-wind hybrid comprehensive energy systems. • The overall energy and exergy efficiencies are 81.01% and 52.52% in steady-state condition. • Also, the overall energy/exergy efficiencies are 58.6% and 39.33% based on a one-year process performance. [ABSTRACT FROM AUTHOR]

• "Transition to sustainable multi-building energy systems can reduce greenhouse gas emissions by synergising the multiple renewable energy sources with specific structural characteristics and occupancy constraints of buildings." • "To ensuring energy flexibility and resilience, optimization strategies for multi-building energy systems vary significantly with the climatic context and potentials for integrating energy storage technologies, highlighting the necessity for adaptable designs considering future energy demands and the expansion of district-level systems." • "There is a pressing need for more user-friendly multi-building energy system simulation tools to facilitate effective long-term planning and to optimize the design and management of energy flows among multiple buildings, ensuring maximum efficiency and sustainability. The transition to clean and sustainable energy systems in the building sector is vital to reduce global greenhouse gas emissions. In this regard, shifting the focus from single buildings to clusters of buildings, such as at the district level, can provide more effective sustainable solutions. In this study, the term Multi Building Energy Systems (MBES) was introduced to represent various scales, from local communities to districts and larger urban areas. This approach reflects a more inclusive understanding of sustainability potentials for large-scale building blocks that goes beyond traditional boundaries. Such systems encompass the aggregated energy impacts of multiple buildings whether physically proximate or connected via smart grid technologies that enable two-way energy and information flows. This paper comprehensively reviewed case studies on MBES that have achieved zero-energy, nearly-zero-energy, and positive-energy performance. The literature review, facilitated by a combination of database searches and snowball search techniques, has yielded 67 relevant case studies. The findings revealed diverse pathways towards achieving optimal renewable energy production depending on the location and the climate. Integration of renewable energy sources and energy storage systems is pivotal in achieving economies of scale, reducing operational costs, and enhancing resilience and reliability of energy supply at the neighbourhood scale. Total energy use and emissions reduction could be achieved by considering the architectural features of the building stocks. The study highlighted the need for adaptive strategies in MBES implementation to address challenges such as power grid overloads and the complexities of spatial arrangement, to meet current demands, while ensuring long-term energy resilience and sustainability in evolving urban landscapes. The limited adoption of MBES simulation software suggests a need for accessible tailored software. Future research should focus on developing advanced personalised energy management and control strategies, while continuously assessing emerging technologies for improving MBES performance. [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]

[Display omitted] • Sustainability of a thermochemical-biochemical pathway for biofuel production. • Different types of biomass feedstock in potential biorefinery locations included. • Greenhouse Gas emissions reduction in the range of 60–86%. • Up to 68% Greenhouse Gas emissions reduction in 2050 compared to 2022. • Up to 83% decrease in non-renewables consumption in 2050 compared to 2022. This paper aims to carry out an integrated Life Cycle Assessment (LCA) to evaluate the environmental performance of a novel thermochemical-biochemical biomass-to-liquid pathway for sustainable aviation and maritime biofuel production. Five scenarios are defined, considering different types of biomass feedstock and biorefinery locations, in different geographically dispersed European countries. The results indicate that the replacement of conventional aviation and maritime fuels with sustainable biofuels could reduce Greenhouse Gases (GHG) by 60–86%, based on feedstock type. When the renewable share in the electricity mix reaches 100% (in 2050), the GHG emissions will experience a great decrease (26% − 68%), compared to 2022 levels. The non-renewable energy consumption will also decrease (by 56% − 83%), with results strongly affected by the electricity mix of the European country considered. This study demonstrates that the deployment of biomass-to-jet/marine fuel pathways could favor the industrial adoption of circular economy strategies for transport biofuels production. [ABSTRACT FROM AUTHOR]

• Advanced clean coal technologies and CCS could provide promising solutions for reducing CO 2 emissions up to 45% in comparison to BAU by 2050. • Coal demand changes to 1100-1400 Mt in 2030 and 1132-2200 Mt in 2050 under alternate future scenarios • CO 2 emissions from coal changes to 45-69% in 2030 and 34-67% of the total emissions in 2050 under alternate future scenarios. • Mitigation measures first decarbonize the power sector due to availability of flexible choices. Simultaneously it decarbonizes the other economic sectors. • Analysis shows that energy security and deep GHG emission mitigation is possible. Rapid shift from traditional energy intensive pathways is required to pace-up economic growth before exhausting remaining carbon budget under 2 °C global stabilization target. Within this larger context, in this paper we have used AIM/End-use, a bottom-up, techno-economic model to analyze India's energy security and greenhouse gas (GHG) emissions from the year 2000 to 2050 with a focus on possibilities of coal continuance in India. Our analysis shows that by adopting advanced coal technologies and carbon dioxide capture and sequestration (CCS) options, up to 45% CO 2 emission reduction can be achieved over business-as-usual scenario (BAU) by 2050. This is possible even when coal use would increase to nearly 2200 Mt in 2050 as against 870 Mt in 2017-18. Without CCS, coal use could peak at 1200 Mt with 22% CO 2 reduction over BAU in 2050 but in that case nuclear and renewable energy would become pivotal in meeting energy demand. The paper concludes that a win-win integration of energy security and deep GHG emission mitigation is possible through a large-scale integration of advanced coal technologies and CCS in Indian energy systems. We have also provided a brief PESTLE analysis for finding the enabling environment necessary for achieving the results discussed in various scenarios. [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]

As climate warming intensifies, reducing greenhouse gas emissions has become a national consensus for many countries. Green finance plays an important role in promoting energy efficiency and lowering such emissions, but there is scant literature that analyzes the impacts and mechanisms of green finance on energy efficiency. Based on China's provincial panel data from 2010 to 2018, this research measures the green finance index using the panel entropy weighting method and systematically evaluates the relationship between green finance and energy efficiency using the fixed-effects model. The results show the following. (1) Green finance significantly contributes to energy efficiency and remains the same after a series of robustness tests such as endogeneity treatment, replacement of explanatory and interpreted variables, and replacement of regression models. (2) Green technology innovation and energy structure optimization are the transmission mechanism of green finance for energy efficiency, which means that green finance improves energy efficiency by promoting green technology innovation and energy structure optimization. (3) There is regional heterogeneity, temporal heterogeneity, and industry heterogeneity in the impact of green finance on energy efficiency. The positive effects of green finance on energy efficiency are more pronounced in resource-dependent regions, regions with irrational industrial structure, north regions, industrial sectors, and after 2013. The conclusions of this paper offer some policy recommendations, including promoting the development of green finance, building a cooperation platform for green finance and technological innovation, enhancing the depth and breadth of renewable energy utilization, and building differentiated green finance strategies according to local conditions. [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]

An environmental degradation due to consumption of fossil fuel based high grade energy releasing greenhouse gases is a pressing issue around the world. The use of low-grade heat from renewable energy sources using organic Rankine cycle is an attractive solution to reduce of emission of greenhouse gases and protect the environment. This paper investigates the potential of a new single rotor expander-compressor device in a combined Vapor Compression Refrigeration (VCR) cycle and an organic Rankine cycle (ORC). The numerical model of combined ORC-VCR is developed and validated. The thermal performance of combined cycle has been evaluated under the influence of evaporation temperature of ORC (62.75 °C–89.7 °C) and VCR (−20 °C–5 °C), condensation temperature of ORC (20 °C–45 °C) and rotor speed (500–3000 rpm) at a constant hot source (water) temperature of 95 °C. The maximum cooling effect, heat-to-cooling efficiency, and exergy efficiency achieved are found to be 5.38 kW, 56% and 63% when the evaporation temperature of ORC and VCR is 62.75 °C and −5 °C, and condensation temperature of ORC is 20.5 °C. Moreover, cooling effect increases linearly with the rotor speed, however, the heat-to-cooling efficiency and exergy efficiency are not affected by the rotor speed. • ORC- VCR is a promising technology for harnessing renewable heat sources. • Assessment of a new single rotor expander-compressor to couple ORC-VCR. • Heat-to-cooling efficiency reached 56%. • Overall exergy efficiency reached 63%. [ABSTRACT FROM AUTHOR]

Enhanced coalbed methane (ECBM) is an effective development technology to improve energy utilisation and reduce greenhouse gas emissions by injecting N 2 /CO 2 into coal seams. The process involves the adsorption, desorption, and diffusion of N 2 /CO 2 in multi-scale coal pores. This results in gas storage and transport characteristics limited by the coal's structural distribution of nanoscale pores (≤100 nm). Thus, studying N 2 /CO 2 storage and diffusive transport characteristics in pores at different scales is vital for efficiently implementing N 2 /CO 2 -ECBM. This paper performed low-pressure adsorption with N 2 /CO 2 (LPA-N 2 /CO 2) to evaluate coal samples' isothermal adsorption characteristics and pore structure, revealing the dual filling-adsorption mechanism of N 2 /CO 2 in coal. A new coal pore classification method was proposed. Pores (≤50 nm) in coal-N 2 or coal-CO 2 adsorption systems were classified as inaccessible pores (<0.364 nm or < 0.33 nm), filling pores (0.364–1.65 nm or 0.33–1.36 nm), transition pores (1.65–2 nm or 1.36–1.60 nm), and adsorption pores (>2 nm or > 1.60 nm). Combining the experimental results to construct micropore and mesopore models, molecular dynamics were applied to simulate the loading and migration processes of N 2 /CO 2 in the pore models. Filling, transition, and adsorption pores completed loading gas within 0.1–1 MPa, 1–5 MPa and 5–10 MPa in that order, visualising the gas filling-adsorption process in coal. Then, the adsorption capacity of N 2 was controlled by the pore size and adsorption pressure, while CO 2 was mainly influenced by adsorption pressure. [Display omitted] • The filling-adsorption mechanism of N 2 /CO 2 in different coal pores is revealed. • A new pore classification method for coal-N 2 and coal-CO 2 systems is proposed. • The pressure stage for loading gas in various types of pores is defined. • Visualisation of gas filling-adsorption process in coal by simulation is realised. [ABSTRACT FROM AUTHOR]

In 2007 was settled the first minimum energy performance standards for air conditioners in Brazil. After more than 14 years since the first regulations and looking upon future perspectives, this paper presents a review of regulatory developments in the country and an assessment based on scenario simulation to verify potential impacts of new minimum energy performance standards for air conditioners. The methodology employed is a bottom-up approach designed to estimate the energy consumption of air conditioners. A spreadsheet-based computational tool was developed to perform sensitivity analysis of key parameters such as ownership rate, average temperature and cooling degree days. The results show a significant energy savings potential that could be captured through a minimum energy performance standards revision. For the scenarios simulated these savings potential would reach up to 417 TWh, with respective greenhouse gases emissions reduction that would be 249 million tons, over the period from 2023 to 2040. An economic analysis of minimum energy performance standards impact is also provided and indicate that even in conditions that involve higher costs and discount rates, new more restrictive minimum energy performance standards allow capturing significant benefits for the society as a whole and for consumers individually. Reviewing the minimum energy performance standards is a critical and urgent issue for Brazil and the methodology presented in this paper can be useful in the process of decision-making related to new regulatory developments. • More restrictive MEPS for air conditioners is urgently needed in Brazil. • The synergy between the CGIEE, Procel and PBE/INMETRO should be improved. • The methodology presented in the paper can support the process of MEPS revisions. • Energy, economic and environmental benefits of more stringent MEPS can be very significant. [ABSTRACT FROM AUTHOR]

Improving energy performance has been recognized as an effective measure to promote the energy saving and emission reduction and to realize the sustainable development. Methods of improving energy performance towards sustainable manufacturing are numerous and scattered, resulting in insufficiency from the perspective of overall strategies and system integration. After the intensive selection of advanced literatures, about 166 research papers directly related to energy performance improvement are analyzed. A comprehensive review and analysis from multi-perspectives of energy monitoring, evaluation, optimization and benchmarking are performed, which is conducive to understand the energy consumption pattern and take effective energy-saving measures. This paper establishes a framework of energy performance integrated method, and four energy management methods and their energy models in energy monitoring, evaluation, optimization and benchmarking phase are analyzed and summarized. Besides, the proposed framework analyzes potential applications and key advantages, and some challenges and potential opportunities for energy performance improvement methods are discussed. This study will provide a significant foundation for energy-efficient production through various methods application. • Performing a review on methods of improving energy performance. • Constructing a framework of methods of improving energy performance. • Summarizing advances in energy monitoring, evaluation, optimization and benchmarking. • Discussing challenges and opportunities of improving energy performance. [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]

Human activities are closely related to energy consumption and carbon emissions. Nevertheless, in the context of energy transition and carbon emission reduction policies, the impact of population migration on energy consumption and carbon emissions is still unclear. Based on the panel data of 30 provincial regions in China from 2000 to 2019, this paper uses the spatial Durbin model to perform a spatial econometric investigation on this issue. In particular, this study innovatively embeds two spatial weight matrices, an economic gravity weight matrix and a population migration weight matrix, into the spatial Durbin model to capture the spatial spillover effects of population migration. The results show that population migration has obvious adverse impacts on the provinces with net outward population migration. Specifically, on the one hand, population migration increases energy consumption and energy poverty, but energy poverty is more severe in provinces with net outward population migration. On the other hand, population migration increases the carbon emissions and carbon reduction barriers of the provinces with net outward population migration and has no significant impact on the carbon emissions and carbon reduction barriers of the provinces with net inward population migration. Besides, the results of heterogeneity analysis show that population migration causes gaps in the energy structure among regions and even triggers the carbon transfer to provinces with net outward population migration. On the whole, the research results of this paper all prove that population migration increases the carbon reduction barriers in the provinces with net outward population migration. These empirical insights enrich the relevant theoretical achievements of the impact of population migration on energy consumption and carbon emissions and have a high reference value for formulating more reasonable regional energy transition and carbon emission reduction policies. • The spatial spillover effects of population migration on energy consumption and carbon emissions are explored. • The spatial Durbin model is used in this paper. • The spatial Durbin model is embedded with the economic gravity weight matrix and the population migration weight matrix. • Population migration has obvious adverse impacts on the provinces with net outward population migration [ABSTRACT FROM AUTHOR]

The wastewater sector accounts for up to 7 and 10% of anthropogenic CH 4 and N 2 O emissions, respectively. Nowadays wastewater treatment plants are going through a paradigm shift to approach a net-zero carbon condition. Numerous ongoing measures have taken place to identify the sources of greenhouse gases and minimize the carbon footprint. This paper systematically reviews all known practices leading towards net-zero carbon wastewater treatment. The greenhouse gas emissions from the wastewater sector are identified and carbon footprint quantification tools, such as reliable models and emission factors are compared. The direct process emissions can contribute to over 60% of the carbon footprint in wastewater treatment plants, while around 30% of the carbon footprint is due to energy-related indirect emissions. Therefore, greenhouse gas mitigation via process optimization and energy usage in wastewater treatment plants are comprehensively described. The implantation of novel nitrogen removal processes can reduce both greenhouse gas emissions and energy consumption. Other techniques such as source separation systems can potentially allow mitigation of N 2 O emissions by 60% while avoiding energy-intensive nitrogen fertilizer production. Nutrient recovery methods are another approach which offer negative value for the net carbon footprint. Recovering N 2 O for energy production is a promising method which can lead to both direct and indirect carbon footprint reductions. Ultimately, to achieve full decarbonization any remaining emissions need to be offset, including carbon footprint of chemicals usage and transportation. [Display omitted] • Wastewater sector is going through a paradigm shift towards decarbonization • GHG emission hotspots are identified and emission factors are reviewed • WWTPs may be responsible for approximately 5% of total GHG emissions • Direct emissions can contribute to >60% of the carbon footprint in WWTPs • Process modifications and energy optimization play key roles towards net-zero WWTPs [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]

Urbanization is the primary driver of changes in total energy consumption and the transformation of energy consumption structure. Fossil fuel combustion in energy consumption is the main contributor to carbon emissions. Therefore, urbanization is closely related to energy consumption and carbon emission. China's urbanization level has reached a tipping point, meanwhile, China has accelerated the pace of energy consumption and structural transformation in response to climate change. Understanding the interactions among energy consumption, carbon emissions and urbanization is crucial for promoting coordinated development of energy environment and urbanization in China. Based on panel data of 30 provinces in China from 2003 to 2019, this paper investigates the effects of urbanization on the aggregate effect, composition effect of energy consumption and carbon emissions using econometric models such as fixed-effects model and panel threshold model. The empirical results show that: (1) The relationship between urbanization and total energy consumption exhibits an inverted U-shaped curve relationship. The decarbonization of energy consumption structure is significantly negatively impacted by urbanization, although the effect is significantly weakened when the urbanization rate exceeds 60.35%. In contrast, urbanization has a significant positive effect on total carbon emissions, although this effect is significantly attenuated when the urbanization rate exceeds 66.20%. (2) As of 2020, 17 provinces in China still have urbanization rates below 60.35%, indicating that they are at a stage where urbanization is having a significant negative impact on the decarbonization of energy consumption structure. Similarly, 20 provinces have urbanization rates below 60.30%, indicating that they are at a stage where urbanization is still significantly contributing to carbon emissions. Therefore, continued urbanization will still have a significant impact on decarbonization of energy consumption structure and carbon emission reduction. (3) Heterogeneity analysis revealed that when the urbanization rate exceeds 51.54%, the role of total energy consumption on carbon emission decreases, while the role of energy consumption structure increases. Additionally, beyond a threshold of per capital regional GDP and education social fixed asset investment, decoupling of urbanization and carbon emission can be promoted. Furthermore, urbanization can have a significant negative impact on carbon emissions after local fiscal resource tax increases to a certain level. • We constructed an index for decarbonizing the energy mix. • We applied the panel threshold regression method to our analysis. • We found that urbanization has a negative effect on the decarbonization of the energy mix. • We discovered that urbanization has a positive effect on carbon emissions. [ABSTRACT FROM AUTHOR]

• The hotel system of a cruise ship was modelled by using a building simulation tool. • The modelled annual energy use was 55 MWh/passenger, with 20% for the hotel system. • Various energy efficiency measures were evaluated for the hotel system. • Heat pumps gave the largest energy savings with a 38% reduction. • Using a hot water storage tank could eliminate use of auxiliary boilers in ports. In light of climate change, the shipping industry is committed to reducing its greenhouse gas emissions. When transitioning from fossil fuels to low-carbon fuels, it is crucial to also reduce the ships' energy need. For cruise ships, the hotel system is a major energy consumer and the focus of this paper. This study aims to investigate the energy use of an existing fossil-fuelled cruise ship operating in a Nordic climate, and evaluate the effectiveness of various passive and active energy-saving measures. For this purpose, a dynamic energy model of the hotel system was developed in the building simulation tool IDA Indoor Climate and Energy (IDA ICE), including a customised weather file. Validation of the model was achieved through comparison with literature and some operational data from the actual cruise ship. Simulation results showed a total annual energy use of 55 MWh/passenger, with the hotel system accounting for 20%. The passive measures, such as increased insulation and improved windows, each resulted in less than a 1% reduction in the hotel's annual energy use. Larger energy savings were achieved by using heat pumps (38%), improved ventilation system (8–24%), and heating setback in port and during the night (5%). A hot water storage tank, charged with the engines' waste heat during sea operation, could reduce the use of auxiliary boilers, especially in port. A hot water tank of 600 m3 could cover 97% of the heating demand in port, thereby minimising the use of fuel-fired boilers. [ABSTRACT FROM AUTHOR]

Policy-makers are investigating ways to reduce greenhouse gas emissions of the transportation sector. Many government agencies have studied the effects of pavement type and characteristics on fuel consumption. Such models, valid for a particular set of simulation conditions, suggest that rigid pavements perform better than flexible pavements. However, it is unclear how this type of model can be applied at the scale of a realistic road network. This paper proposes a statistical approach to assess the relative importance of pavement type and characteristics on fuel consumption of heavy vehicle traffic by considering the specificities of meteorological conditions, heavy vehicles, and driver behaviours. A case study in Canada showed that the potential advantage of using rigid pavements was offset by cold climate effects and the consideration of a realistic statistical payload distribution. Road roughness accounted on average for 1.1% of total fuel consumption, with an increased value of 1.9% in January. [ABSTRACT FROM AUTHOR]

This paper studies forecasting the use of renewable energies in the water and wastewater industry. Different methods have been proposed to show energy recovery techniques and the use of renewable energy in wastewater treatment. The results indicate that increasing the carbon tax to more than 30 USD per ton of CO2 could reduce emissions from all fossil-fuel power plant types by 30%. • Providing a new assessment approach in applying renewable energy in the water and wastewater industry • Measuring the potential of using renewable energy in the water and wastewater industry • Investigating the use of renewable energy to reduce greenhouse gas emissions and air pollution control by wastewater treatment [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas emissions and energy cost in the building sector largely relies on effective energy management. Yet, when it comes to heating or cooling, energy savings may translate to uncomfortable conditions for the building users. To ensure thermal comfort with a minimal energy consumption, in this paper we propose a modular methodology that dynamically schedules the operating hours of the heating/cooling system of the building using thermal comfort forecasts. To decide on the time and mode of operation, our approach utilizes indoor air temperature and relative humidity forecasting models, as well as a data-driven algorithm that predicts thermal comfort level based on said forecasts and employs pre-heating/cooling when necessary. Our empirical evaluation, conducted in the Casal Mira-sol culture center of Sant Cugat, Spain, suggests that our approach can improve the satisfaction of the building users, while achieving significant energy savings. • A method to handle heating and cooling systems based on thermal comfort forecasts. • Optimization of the HVAC operation using indoor temperature and humidity forecasts. • A dynamic algorithm that simulates thermal comfort to pre-heat/cool the building. • Demonstration of the approach through an application to a public building in Spain. [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]

India ranks third globally in overall greenhouse gas (GHG) emissions, with power and transportation first and third, respectively, in terms of India's sectoral GHG contributions. Motivated by India's Nationally Determined Contribution goals and stated intent to drive renewables growth and vehicle electrification, this paper explores the connections between India's power and road transportation sectors by investigating the benefits of flexible electric vehicle (EV) charging on a set of hypothetical 2037 Indian power grid infrastructures. Using two production cost models, one simulating optimal unit commitment and hourly dispatch of available generation, the other simulating subhourly real-time dispatch operations, we examine the impact of flexible and inflexible EV charging regimes and vehicle-to-grid integration on generation profiles, peak load shaving, energy storage utilization, and overall emissions. Our techno-economic analysis shows that a number of future grid infrastructure scenarios, despite not specifically accounting for EV growth scenarios, may meet annual and hourly peak demand when combined with flexible EV charging; in contrast, inflexible EV charging, particularly during the early morning, will lead to substantial need for additional generation capacity. Coupled sectoral decarbonization remains tied to the grid generation mix, highlighting the need for continued policy focus on decarbonization of the rapidly growing power sector. • Flexible charging, grid decarbonization policies critical for EV adoption benefits. • Scenario analysis highlights pathways to efficiency gains + emissions reductions. • We quantify net CO 2 emissions from power + road transport with increasing EV load. • V2G reduces unserved reserves, prevents price spikes during extreme power outages. [ABSTRACT FROM AUTHOR]

Forecasting the short-term future energy demand in buildings and districts is a vital component towards the optimization of energy use and consequently the reduction in greenhouse gas emissions. This paper explores artificial intelligence approaches applied to estimate the future heating load in a district heating system. A distinction is made within thisd work between a prediction and forecasting based approach; a comparison is then accomplished by applying each method with prominent Machine Learning and Deep Learning based algorithms to estimate the future heating demand over 6 h and 24 h ahead. This analysis used available data from a Canadian district heating system in Quebec and actual weather forecasts obtained from Canadian meteorological services. All models within this work applied a grid search in order to calibrate their respective hyperparameters. Results of this work indicated that the prediction-based approach (with forecasted inputs) obtained a higher accuracy than the forecasting approach. All the machine learning models obtained good accuracy with errors not exceeding 16% CV(RMSE) and closer to 10% CV(RMSE) for the top performing models. Furthermore, the LSTM and XGBoost were consistently among the top performing algorithms and provided good performance over a variety of hyperparameters. The biggest difference between the two algorithms was the computational times; it was observed that the XGBoost was significantly faster to train. • Artificial Intelligence models are investigated to forecast district heating demand. • Prediction and forecasting based approaches are compared. • Model performance is estimated using accuracy, training time and stability. • The prediction approach using forecasted inputs shows slightly better results. • LSTM and XGBoost models outperform other techniques with an error of 11%. [ABSTRACT FROM AUTHOR]

• The model has a high accuracy of MAPE < 14% and MAE < 0.16 cc/s. • Data analysis is used to improve the prediction accuracy of the model. • The model has good applicability and popularization value. Due to the increasingly severe environmental issues caused by transportation, energy conservation and emission reduction have become one of the most important research directions in the field of transportation. As the key tool for estimating transient fuel consumption, fuel consumption models are crucial for quantifying the energy consumption of automobiles and achieving energy conservation and emission reduction. However, most existing fuel consumption models suffer from problems such as a complex structure, difficult-to-determine model coefficients, and difficult-to-measure input parameters. Therefore, it is necessary to propose a high-precision fuel consumption model with good applicability and easy implementation. The model proposed in this paper adopted a structure of steady-state estimation and transient correction and used support vector regression to predict fuel consumption. First, the engine torque was fitted based on the steady-state data, and the steady-state module was established. Then, based on data analysis using the Gaussian mixture model, the transient motion was divided into three driving conditions, and the transient module was obtained by transient correction for different driving conditions. Ultimately, the performance of the model was validated. The results show that the mean absolute percentage error of the new model is less than 14%, and the mean absolute error is less than 0.16 cc/s, which is a significant improvement compared with other classic models, indicating that the new model has a high prediction accuracy. In addition, the new model takes the most common engine speed, vehicle speed, and acceleration as inputs, making it easy to use and has good applicability and popularization value. [ABSTRACT FROM AUTHOR]

[Display omitted] • Firewood biomass has traditionally been used to generate energy by burning. • Pathways to anaerobic digestion, enzyme hydrolysis and microbial fuel cells were analyzed. • Circular economy preserves the value of its by-products by reducing time. • Anaerobic digestion and microbial fuel cells help to achieve biomass use with sustainability. • Alternative fuels raise the demand for energy throughout the world. In recent years, biofuel or biogas have become the primary source of bio-energy, providing an alternative to conventionally used energy that can meet the growing energy demand for people all over the world while reducing greenhouse gas emissions. Enzyme hydrolysis in bioethanol production is a critical step in obtaining sugars fermented during the final fermentation process. More efficient enzymes are being researched to provide a more cost-effective technique during enzymatic hydrolysis. The exploitation of microbial catabolic biochemical reactions to produce electric energy can be used for complex renewable biomasses and organic wastes in microbial fuel cells. In hydrolysis methods, a variety of diverse enzyme strategies are used to promote efficient bioethanol production from various lignocellulosic biomasses like agricultural wastes, wood feedstocks, and sea algae. This paper investigates the most recent enzyme hydrolysis pathways, microbial fermentation, microbial fuel cells, and anaerobic digestion in the manufacture of bioethanol/bioenergy from lignocellulose biomass. [ABSTRACT FROM AUTHOR]

• Biogenic feedstock is not sufficient to replace overall energy demand of aviation. • Non-biogenic feedstock is constrained by low capacities for renewably sourced energy. • Costs of the renewable aviation fuels are determined by feedstock and energy costs. • Synthetic kerosenes are options on a shorter, hydrogen rather on a longer timespan. The air transport sector's contribution to anthropogenic climate forcing is estimated at around 4 %. In this respect, alternative fuels are considered as a key measure to reduce greenhouse gas emissions within the air transport system and thus to reduce the contribution of commercial aviation to anthropogenic climate change. Nevertheless, so far the usage-shares of alternative fuels are below 1 %. Thus, the goal of this paper is to analyse a broad selection of aviation fuel options for their greenhouse gas reduction potential based on a set of nine assessment criteria. The fuel options studied are blended synthetic kerosene and neat synthetic kerosene fuels, three alcohols (methanol, ethanol and butanol) and three gases (methane, ammonia and hydrogen). For these fuels a multi-criteria assessment based on a five-step ordinal scale is performed. The assessment results show that the availability of some biogenic feedstock is not sufficient to replace the present overall energy demand of aviation; while the availability of non-biogenic fuels might increase in the near- to mid-term. In general, alternative kerosene-like fuel options are mainly constrained by lacking production capacities, while alcohols and gases considered are constrained by aircraft modifications or development of new aircraft types. All discussed fuel options have the potential to mitigate greenhouse gas emissions of commercial aviation substantially also from a life cycle perspective. Within the next decade, especially alternative kerosene-like options with (intermediate) products experiencing demand from other sectors, such as FT-SPK or AtJ-SPK, show a high development potential. The same holds for hydrogen provided that a hydrogen fueled aircraft will be brought successfully to the market. [ABSTRACT FROM AUTHOR]

[Display omitted] • Advances in the design for biorefineries toward carbon-neutrality. • Application of decision-making tools and artificial intelligence in the design of a biorefinery. • IoT concept in biorefinery design for the valorization of biomass. • Future works in the integration of Industry 5.0 for carbon emission reduction. The increase in worldwide demand for energy is driven by the rapid increase in population and exponential economic development. This resulted in the fast depletion of fossil fuel supplies and unprecedented levels of greenhouse gas in the atmosphere. To valorize biomass into different bioproducts, one of the popular and carbon–neutral alternatives is biorefineries. This system is an appropriate technology in the circular economy model. Various research highlighted the role of biorefineries as a centerpiece in the carbon–neutral ecosystem of technologies of the circular economy model. To fully realize this, various improvements and challenges need to be addressed. This paper presents a critical and timely review of the challenges and future direction of biorefineries as an alternative carbon–neutral energy source. [ABSTRACT FROM AUTHOR]

In order to realize the effective use of energy and promote the full consumption of renewable energy, the microgrid integrated by distributed resources has the potential of resource sharing as independent stakeholders. While, the traditional multi-microgrid interconnection ignores the information privacy of each microgrid, moreover, the cooperation strategy often cannot achieve a fair and reasonable distribution of benefits. Based on this, this paper firstly establishes a microgrid model for the coordination of three energy forms of electricity, heat, and gas. Secondly, considering the actual situation involving uncertainties on both sides of the source and load, robust interval optimization is used to achieve better robustness. Then, combined with the increasingly important low-carbon operation goal, a combined heat and power (CHP) model integrating power to gas (P2G) and carbon capture systems (CCS) is constructed, and the goal of emission reduction is achieved through the carbon trading operation mechanism. Finally, based on the Nash bargaining theory, a multi-microgrid Peer-to-Peer(P2P) low-carbon economic operation model is established, and the alternating direction method of multipliers (ADMM) with good convergence and privacy is used to decomposed the original problem into two sub-problems to solve. • Proposed a kind of multi-microgrid P2P Nash bargaining operation strategy using ADMM algorithm. • Using robust interval optimization to explain double-sided uncertainty of source-load. • Using CHP with P2G and CCS in microgrid to realize energy saving and emission reduction. [ABSTRACT FROM AUTHOR]

• The IES cloud-edge collaborative distributed dispatching architecture is proposed. • Based on PJ-ADMM, the IES distributed optimal solution method is proposed. • Considering privacy protection in IESs, subproblems can be solved in parallel. • Compared with centralized methods, the proposed method shows higher solution efficiency. • The impact of demand response on IES operation and carbon trading is analyzed. To reduce carbon emissions and improve the energy efficiency of energy systems, integrated energy systems (IESs) have been promoted in recent years. However, the data of different energy networks cannot be fully shared. The data privacy protection is attracting more attention in demand side. It is difficult for centralized dispatching strategies, which must obtain all the data of energy systems during optimization, to be applied. To solve these issues, a cloud-edge collaborative distributed optimal dispatching strategy for electric-gas IESs is proposed in this paper. The centralized IES scheduling problem is reasonably divided into multiple subproblems. Considering information barrier, the cloud computing centers are separately set in different energy networks to solve energy flow optimization subproblems. Considering prosumer privacy protection, edge computing units are separately set in energy hubs to deal with cost and carbon emissions minimization of regional integrated energy systems (RIESs). Based on the proximal Jacobian alternating direction method of multipliers, the common optimization variables interactive iteration and parallel solution of multiple dispatching models are developed. The simulation results show that the proposed distributed optimization method can achieve the same accuracy as the centralized optimization method and improve problem-solving efficiency in general. [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]

• The shadow price of energy and CO2 of 36 industrial sectors in China was estimated. • The cost-saving benefits of EQT and ETS in China was evaluated. • Industries can gain higher cost-savings under trans-province and inter-industry EQT. • Industries with a high energy demand can gain higher cost-savings in EQT. • EQT can gain higher cost-savings than ETS under the same environmental targets. In response to the severity of its environmental problems, China is fully promoting the construction of a national energy quota trading (EQT) market and a national carbon emission trading scheme (ETS). However, there is currently a lack of studies comparing the cost savings of EQT and ETS from the perspective of different industries in different provinces under the same environmental regulation. To fill this gap, this paper first estimates the shadow price of energy and CO2 in 30 Chinese provinces' 38 industrial sectors using provincial-industrial level data from 2005 to 2016 based on the duality theory of non-radial directional distance function. Thus, at the methodological level, this study also overcomes the shortcomings of the DEA method used in most previous studies, that is, it is not appropriate for the cross-industry and cross-province heterogeneity characteristics of the research target. It then evaluates the cost savings of EQT and ETS by simulating actual trade scenarios. We find that the single EQT market obtains greater cost-saving benefits than the mixed market and the single ETS market with the same environmental target. We suggest that the energy consumption units should choose the trading market based on their energy-saving and emissions reduction costs, which is more conducive to achieving the set environmental goals and obtaining cost savings, taking into account different regional industry structures, natural resources, and environmental regulation intensity. [Display omitted] [ABSTRACT FROM AUTHOR]