Search

Approximately 172 million rural households in China in 2022, will still rely on traditional biofuels instead of electricity. This study explores the feasibility of achieving rural electrification in China utilization various Energy origins and assesses its potential impact on climate change mitigation. To do so, we employ the Regional Energy Model (REM) to formulate hypotheses for rural power distribution. Covering the era from 2020 until 2050. We evaluate consequences in terms of greenhouse gas discharges, principal energy consumption, associated expenses by comparing these possibilities with a Business- as -Usual (BU) scenario. Our findings reveal that diesel-based arrangements tend to produce 'the maximum Carbon Dioxide (CO2) emissions, trailed by network-based solutions. Electrification focused on renewable energy-driven applications has the potential to reduce total CO2 emissions by up to 97 % and primary energy consumption by 43 % in 2050 compared to the BU scenario. We also find that electrification through decentralized diesel systems tends to be the priciest choice. Rural electrification utilizing renewable energy emerges as a cost-effective choice when the majority of end-use applications rely on renewable energy sources. However, it becomes less economical than network expansions when electric end-user appliances are predominant. In summary, this study investigates the viability of renewable energy for rural power distribution and its role in climate change abatement in rural China, offering policy suggestions. • Analyzes six energy-based scenarios for China's rural electrification until 2050. • Evaluates GHG emissions, energy use, and costs impacts with regional energy model. • Provides policy insights and uncertainties for China's sustainability goals. • An oil price and distance-based analysis also is done with extra 6 scenarios. [ABSTRACT FROM AUTHOR]

The building sector is critical in climate change mitigation by reducing its energy consumption. At the same time, warming climate requires adaptation measures from buildings, making it necessary to study the future thermal energy demand of buildings. This paper studies the impact of climate change on the thermal energy demand of buildings in a heating dominated climate of Finland, under "representative concentration pathway" (RCP) climate scenarios in near- (2030), medium- (2050) and long-term (2080) horizon. Additionally, the impact of the thermal performance level of the buildings is investigated. The thermal energy demand calculation is based on overarching standards from the European "energy performance of buildings" directive. The weather scenarios present both typical and extreme weather years, applied through morphing and future weather data from the Finnish Meteorological Institute. The results show that annual thermal energy demand in Finland in 2080 can decrease up to 74.6 kWh/m 2. In addition, the decrease in heating demand will be higher than the increase in cooling demand. Cooling can become the dominant peak in long-term evaluations, especially in South Finland (Vantaa) with passive buildings under RCP8.5 climate scenario. Renovation is the most efficient action to decrease energy intensity, the earliest it is done the better. [Display omitted] • Thermal energy demand of detached houses in Finland is studied under RCP climate scenarios. • Thermal energy demand is expected to decrease in Finland in long-term. • RCP scenario affects when the highest average annual thermal energy change occurs. • Cooling can become the dominant thermal peak demand source for passive buildings. • Renovating building to newer standards remains beneficial, though less with time. [ABSTRACT FROM AUTHOR]

More than 130 countries and regions have put forward various climate goals, which makes carbon-oriented energy system planning a heated topic. However, these planning studies do not consider the carbon fixation role played by forest carbon sinks (FCSs). To take advantage of the carbon fixation role of FCSs, this paper will develop a carbon-cycle integrated energy hub (CC-EH) model to quantify the economic advantages of FCSs in planning a zero-carbon energy system, where energy flow and carbon flow are both analyzed. A total planning and operating costs minimization with the constraints of CO 2 emissions is proposed as a mixed integer nonlinear programming (MINLP) optimization model and the overall problem is solved based on commercial solver. The proposed model is validated by case studies on six medium to large-size cities in different geographical locations in China. Results indicate that the typical cities in China can fulfill their carbon-neutral commitments by 2060. Throughout the entire planning period, FCSs can offset up to 55.31 % of the total carbon dioxide emissions from urban energy systems. Besides, FCSs achieved by forestation will help the energy system to reduce up to 36 % of the planning cost compared to the case without using FCSs. [Display omitted] • Forest carbon sink (FCS) is modeled considering CO 2 absorption and biomass growth. • FCS is applied to planning through a carbon-cycle integrated energy hub (CC-EH) model. • Coupling of energy system operation and FCS process on an hourly scale is realized. • A power function is introduced to characterize the transition path, and determine the optimal capacity of the CC-EH. • Typical cities in China are taken for case studies to analyze the impact of FCSs on the carbon neutral. [ABSTRACT FROM AUTHOR]

With the galloping progress of the changing climates all around the world, Machine Learning (ML) approaches have been prevalently studied in many types of research in this area. ML is a robust tool for acquiring perspectives from data. In this paper, we elaborate on climate change mitigation issues and ML approaches leveraged to solve these issues and aid in the improvement and function of sustainable energy systems. ML has been employed in multiple applications and many scopes of climate subjects such as ecosystems, agriculture, buildings and cities, industry, and transportation. So, a Systematic Literature Review (SLR) is applied to explore and evaluate findings from related research. In this paper, we propose a novel taxonomy of Deep Learning (DL) method applications for climate change mitigation, a comprehensive analysis that has not been conducted before. We evaluated these methods based on critical parameters such as accuracy, scalability, and interpretability and quantitatively compared their results. This analysis provides new insights into the effectiveness and reliability of DL methods in addressing climate change challenges. We classified climate change ML methods into six key customizable groups: ecosystems, industry, buildings and cities, transportation, agriculture, and hybrid applications. Afterward, state-of-the-art research on ML mechanisms and applications for climate change mitigation issues has been highlighted. In addition, many problems and issues related to ML implementation for climate change have been mapped, which are predicted to stimulate more researchers to manage the future disastrous effects of climate change. Based on the findings, most of the papers utilized Python as the most common simulation environment 38.5 % of the time. In addition, most of the methods were analyzed and evaluated in terms of some parameters, namely accuracy, latency, adaptability, and scalability, respectively. Lastly, classification is the most frequent ML task within climate change mitigation, accounting for 40 % of the total. Furthermore, Convolutional Neural Networks (CNNs) are the most widely utilized approach for a variety of applications. • Touching on a comprehensive survey of the present challenges related to DL approaches for climate change mitigation applications. • Proposing a systematic overview of the existing methods for climate change mitigation in studied research. • Assessing each area with customized DL approaches with various aspects like benefits, limitations, datasets, security involvement, and simulation stings. • Outlining the pivotal sides that drive the referred methods to improve in future studies. • Illustrating the descriptions of particular climate change mitigation utilized in different research. [ABSTRACT FROM AUTHOR]

Energy poverty is a key dimension of multidimensional poverty and a major challenge for climate action. This study examines how climate policies affect energy poverty, especially the role of carbon tax revenue recycling in coordinating climate mitigation and energy poverty alleviation. Using an integrated Climate-Economy-Energy Poverty (RICE-EP) model that incorporates inequality aspects of energy poverty, the study analyzes the effects of climate policies on household energy consumption. The study simulates various scenarios of climate actions and carbon tax revenue recycling and finds that: i) Carbon tax revenue recycling can simultaneously advance climate change mitigation and energy poverty reduction goals, it can promote climate mitigation and enhance equity by lowering the abatement costs borne by low-income populations; ii) However, the interactions between stringent climate targets and energy affordability are complex. Modeling suggests that even optimal revenue recycling fails to prevent exacerbated energy poverty among disadvantaged groups under ambitious 2 °C climate targets; iii) Analysis indicates that an emissions reduction rate approaching 43 %, enabled by a carbon tax calibrated to incentivize an equitable transition, could maximize alleviation of energy poverty by directing subsidy support to low-income groups. The study methodology and findings offer valuable, actionable insights into coordinating equitable climate and economic policies. • An integrated Climate-Economy-Energy Poverty (RICE-EP) model has been developed. • Carbon tax revenue recycling alleviate energy poverty and reduce emission. • Achieving the 2 °C warming target will exacerbate energy poverty. • Developed countries should bear more emission reduction responsibilities. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emission mitigation and climate change adaptation in urban communities are urgent. There is enormous potential to improve the GHG inventory at the community level. This research aims to develop a community-scale GHG emission inventory and improve its accuracy and consistency through a bottom-up approach. This study covers direct and indirect emissions categorized into three scopes and selects the Honjo Waseda community in Japan as a case study community. Energy consumption from different sectors (the residential and commercial, transport, and waste management sectors) is evaluated and calculated through Residential Energy Estimation based on the Daily Activities (REEDA) database, National Census, and first-hand field data. The outcome revealed that the residential and commercial sector emissions rank highest in the total GHG emissions of the community, with a value of 39 %. Translated into the scope concept, the emissions under scopes 2 and 3 account for 39 % and 61 %, respectively. Furthermore, a sensitivity analysis of the implementation of green technologies to reduce GHG emissions is also conducted. Mechanical biological treatment (MBT) implementation could yield the largest emission reduction (18 %–22 %), followed by implementing electric vehicles, ultralightweight vehicles, photovoltaic systems, and ground heat utilization. [Display omitted] • GHG emission mitigation and climate change adaptation of urban communities are urgent. • Evaluate GHG emission at community level from scope 1–3 through a bottom-up approach. • Develop models for evaluating emissions from residential and commercial transport, and waste management sectors. • Propose scenarios and evaluate sensitivity analysis on green technologies implementation. [ABSTRACT FROM AUTHOR]

Urban areas have key roles in climate mitigation, including increasing renewable energy penetration in smart energy systems. The potential of urban areas in limiting global warming, however, is not quantified. This research work develops a new framework to analyse urban emissions and land use efficiency scenarios with coupling to the transient climate response to cumulative carbon dioxide emissions. Two new parameters that quantify contributions to and avoidance of increments of global warming from urban areas are formulated and applied to twelve scenario combinations. The results for 465 urban areas indicate that a green-growth scenario with lower ambition in reducing urban emissions can lead up to a 0.13 °C additional increment of global warming in 2050 based on the best estimate of the transient climate response to cumulative carbon dioxide emissions. Those of the most ambitious urban emissions scenario with green-growth and renewable energy are limited to 0.06 °C. When combined with the most ambitious land use efficiency scenario for 135 urban areas, it is possible to avoid more than double or 2.09 times additional increments of global warming in comparison to other integrated urban scenarios. The mean and 5–95th percentile range of the results are compared based on 10,000 Monte Carlo simulations. Informing on the urgency to ensure ambitious mitigation action in urban areas can support a climate future that remains within critical thresholds and tipping elements of the planet. [Display omitted] • A new framework couples urban scenarios and increments of additional global warming. • Cumulative urban emissions of 465 urban areas can be 291.04 GtCO 2 eq in 30 years. • A green-growth oriented renewable energy scenario can avoid up to 0.09 °C in 2050. • Cumulative sequestration penalties of 135 urban areas are up to 2.01 GtCO 2 in 30 years. • Joint ambitious mitigation and land use efficiency in this case averts 0.039 ± 0.016 °C. [ABSTRACT FROM AUTHOR]

Decarbonizing the EU's district heating is crucial for meeting climate goals and securing a sustainable energy future. Currently, district heating suffers from inefficiency, high operating temperatures, significant distribution losses, and reliance on fossil fuels. Literature highlights strategies for reducing emissions, including integrating low-carbon heat sources, lowering supply temperatures, and employing efficient technologies like heat pumps and combined heat and power (CHP). However, the individual effectiveness of these strategies in reducing emissions within existing networks remains unassessed. This study addresses the gap by applying a comprehensive model that evaluates energy and emissions across the district heating supply chain, coupled with a derivative-based sensitivity analysis. We apply this methodology to the national-level district heating systems of Sweden, France, Germany, and Poland. Results indicate that the impact of decarbonization strategies on district heating emissions varies significantly by the system's characteristics, i.e., the energy mix in power and district heating supply and the presence of CHP plants. Primarily, incorporating more low-carbon heat sources emerges as the most effective method for emission reduction across nearly all examined countries. A 1 % increase in the share of low-carbon heat sources can potentially cut emissions by 0.8–1.3 kg CO 2 e per GJ of heat. In countries like Sweden and France, where the power generation already relies heavily on low-carbon resources, technologies which convert electricity to heat—such as heat pumps and electric boilers—rank as the second most effective approach. In contrast, for countries like Germany and Poland, with their moderate to low use of low-carbon power, reducing distribution losses and decreasing heat demand prove more effective, with emission reductions ranging between 0.8-1.3 and 0.7–1.2 kg CO 2 e per GJ in these countries, respectively. Additionally, cutting down power generation in fossil fuel-based CHP plants significantly reduces emissions in these regions. While green hydrogen and carbon capture and storage (CCS) also contribute to emission reductions, a 1 % increase in green hydrogen's share might decrease emissions by just 0.3–0.5 kg CO 2 e per GJ of heat, highlighting their lower effectiveness compared to the aforementioned strategies. These insights hold value for both district heating operators and for technology suppliers seeking decarbonization pathways. This is also true for policymakers focused on climate change mitigation, guiding the distribution of subsidies and R&D investments. • Creation of a framework to evaluate the effectiveness of strategies to reduce emissions in district heating. • Application of the method to the national-level systems of Sweden, France, Germany, and Poland. • Effectiveness of strategies varies significantly by the system's characteristics. • Identification of most effective strategies by country and policy recommendations. [ABSTRACT FROM AUTHOR]

Achieving decarbonisation of the heating sector is a major challenge, especially in Ireland, which has the lowest proportion of renewable heat in Europe. In economically pursuing ambitious and equitable climate targets, Ireland's Climate Action Plan 2023 set a goal of reaching 2.5 TWh of district heating by 2030, starting from a limited existing capacity. This pioneering study explores supply sources and heat density demand cohorts to develop a model to understand district heating in a low-deployment region, using Ireland as a case study. We also conduct a sensitivity analysis considering different connection rates. Our research demonstrates that district heating is pivotal in achieving optimal decarbonisation pathways. Incorporating district heating reduces marginal CO 2 emission prices by 13%–25%. Additionally, with feasible growth limits applied, total savings for the energy system are anticipated to reach €17.2 billion by 2050. This reduction of emissions in the building sector, facilitated by district heating, allows for greater emissions allowances in other sectors and reduces reliance on electricity while meeting climate targets. These insights highlight the need for spatial energy policies and deepen our understanding of integrating district heating within an energy system optimisation model. • District heating in Ireland can reduce marginal CO 2 emission prices by 13%–25%. • District heating can cumulatively save €17.2 billion compared to no district heating. • Regional energy policy is needed to align with cost-optimal pathways. • Regional supply and demand quantified sensitivity analysis strengthens insights. [ABSTRACT FROM AUTHOR]

Energy system and computable general equilibrium (CGE) models play vital roles in climate change mitigation studies. These models have advantages and disadvantages, and attempts have been made to integrate them. This study aimed to describe the method for integrating energy system and CGE models and demonstrate the new model that captures the strengths of both models. The method developed in this study ensured the detailed convergence of the energy system by exchanging the results iteratively. We demonstrated the model integration by adopting the method to MESSAGEix-GLOBIOM and AIM/Hub and estimating a mitigation scenario that limits the temperature rise to below 2 °C under the middle-of-the-road socioeconomic projection in Shared Socioeconomic Pathways. As a result of the integration, the index showing the difference between the two models proposed in this study decreased from 1.0 to 0.066. Therefore, we confirmed that these models estimated consistent scenarios. The diagnostic indicators showed that compared to its counterpart CGE model, the newly-developed model was characterized by a higher contribution of demand-side reductions, a lesser alteration in the primary energy supply composition, and lower abatement costs. Given the convergence and advantages of the integrated framework, the proposed method is useful for further application to mitigation studies. • Proposed a new method to integrate energy system models and CGE models. • Integrated MESSAGEix-GLOBIOM and AIM/Hub using the newly proposed method. • AIM/Hub provided multi-sectoral and goods representation. • MESSAGEix-GLOBIOM enabled estimates in consideration of detailed technologies. • Integrated model was characterized by demand-side effort and lower abatement costs. [ABSTRACT FROM AUTHOR]

Net-zero energy system configurations can be met in numerous ways, implying diverse economic effects. However, what is usually ignored in techno-economic and economy-wide analysis are the distinct social-political drivers and barriers, which might constrain certain elements of future energy systems. We thus apply a model ensemble that defines social-political storylines which constrain feasible net-zero configurations of the European energy system. Using these configurations in a macroeconomic general equilibrium model allows us to explore economy-wide effects and ultimately the cost-effectiveness of different systems. We find that social-political storylines provide valuable boundary conditions for feasible net-zero designs of the energy system and that the costliest energy sector configuration in fact leads to the highest European-wide welfare levels. This result originates in indirect effects, particularly positive employment effects, covered by the macroeconomic model. However, adverse public budget effects on the transition to net-zero energy may limit the willingness of policymakers who focus on shorter time-horizons to foster such a development. Our results highlight the relevance of considering the interaction of energy system-changes with labor, emission allowance and capital markets, as well as considering long-term perspectives. • Model ensemble covers social, technological and economic factors of net-zero energy. • Costliest system is associated with highest welfare due to economy-wide feedbacks. • Public budget effects show how fiscal space for supporting the transition changes. • Economic model allows for consistently contextualizing the costs of mitigation. [ABSTRACT FROM AUTHOR]

The implementation of Increase in Block Pricing (IBP) policy is premised on the assumption that consumers adjust their behavior to save energy in response to electricity price increases. However, consumers often lack a comprehensive understanding of the pricing schedules, leading to inaccurate consumption predictions. This study utilizes monthly electricity billing data from the administrative records of urban residential consumers of the Electricity Company of Ghana Limited to estimate the causal effect of IBP policy schedules on electricity consumption. To achieve this, we employed the Regression Kink (RK) design identification strategy to explore the kink structure of the policy function. This paper finds an inelastic causal relationship between IBP policy and electricity consumption. The results show a treatment effect of 0.41 KWh with an associated p-value of 0.473 at a robust 95 % confidence interval. Thus, IBP policy has no causal effect on electricity consumption at the 50 KWh lower block threshold. Notably, electricity consumers do not respond significantly to price increments, rendering IBP policy ineffective in achieving energy saving at the lower block threshold. This research contributes to a deeper understanding of the effectiveness of IBP policy in promoting energy savings and informs researchers, policymakers, and stakeholders in the energy sector. Results can be used to develop evidence-based policies that contribute to energy conservation and climate change mitigation. • Increase in block pricing (IBP) is used to encourage energy conservation. • We estimate the causal effect of the IBP policy on electricity consumption. • We use monthly electricity billing data from the Electricity Company of Ghana. • Despite expectations, we find that IBP policy is ineffective in achieving energy conservation objectives. [ABSTRACT FROM AUTHOR]

Achieving net zero emissions is a crucial challenge in the global climate change policy. It requires a substantial reduction in unabated fossil fuel use, the deployment of renewable energy sources, and the development of carbon capture, utilisation and storage technologies. The aim of this study was to investigate and compare two CO 2 capture retrofits for natural gas combined cycle (NGCC). First one, amine absorption, is already mature and characterised as commercial technology, whereas second one, calcium looping is a promising method but still under pilot studies. Energy required for capture process yields net efficiency penalty, which in conducted research totalled 8.4% points for amine unit and 7.4–15.5% points in calcium-looping units. The economic evaluation was performed to analyse the impact of both concepts on their profitability. Moreover, the climate change mitigation potential was assessed and indicated that carbon capture can lower the emissivity of a conventional power plant by 82–87% or even contribute to achieving negative emissions when biofuels are used. Carbon dioxide capture is one of the key elements of ongoing energy transition and its integration with NGCC power units could be determined as essential for maintaining energy security with net zero emissions. • The work provides the comparison between amine scrubbing and calcium-looping CO 2 capture for Natural Gas Combined Cycle. • CCS retrofit causes a net efficiency penalty between 7.4 and 15.5%p for analysed configurations. • Calcium-looping retrofit placed after the gas turbine yield lower SPECCA and higher unit power due to new steam cycle. • Using biogas as a feedstock to calciner of calcium-looping unit leads to negative CO 2 emissions. • Amine scrubbing retrofit has much lower CAPEX and OPEX than CaL units, yet they reach higher ΔNPV within 25 years. [ABSTRACT FROM AUTHOR]

During the last decades, several studies have shown that heat pumps are a promising solution to reach the European Union targets on climate change mitigation, since they satisfy the energy needs for heating, cooling and hot water production employing a single device and using a significant share of renewable energy. However, the full exploitation of the energy-saving potential of heat pumps is a difficult task for designers to achieve, as several factors, such as the variability of outdoor climatic conditions, the control logic of the system and the system configuration, influence the energy performance. High Coefficient of Performance (COP) and low environmental impact make Ground Source Heat Pump (GSHP) systems one of the most suitable technologies for the heating and cooling services, to promote the decarbonization of the building sector, especially in urban areas. The objective of this study is to assess a range of strategies for heat pump systems to achieve optimal performance that can be fully utilized. To do this, the authors analyse the performance of a 'positive' office building, located in Swansea University Bay, which is already featured with renewable energy technologies for electricity and heat generation: an integrated photovoltaic roof to generate electricity and a wall-photovoltaic thermal system. The current configuration ('baseline scenario') of the building-plant system was modelled in TRNSYS 17 environment and the influence of different parameters on the energy performances was studied. To complement the already high use of renewables the authors propose an alternative scenario for the Active Office Building integrating the use of geothermal heat pumps with the existing systems. By comparing the two scenarios on an energy and environmental point of view, it was possible to assess an 11% decrease in primary energy consumption, leading to a corresponding 11% reduction in greenhouse gas (GHG) emissions. [Display omitted] • GSHP are a promising solution to achieve EU energy goals, since they supply heating and cooling with a high share of RES. • The work proposed suggests optimization measures for buildings to increase efficiency. • A Positive Office Building, equipped with renewable technologies has been modelled with TRNSYS 17. • A technoeconomic and environmental analysis has been performed to assess the benefits of the adoption of a GSHP. • The proposed scenario has shown an energy saving of 11% and a reduction of GHG emissions with respect to the baseline one. [ABSTRACT FROM AUTHOR]

Deep decarbonization scenarios indicate a decline in fossil oil usage in the coming decades, meaning that oil refineries must adapt. This work evaluates the refining sector in deep decarbonization pathways using Brazil as a case study. BLUES – a national integrated assessment model – is employed to investigate the evolution of the sector in mitigation scenarios until 2050. The production of feedstocks for the petrochemical industry, of fuels for the aviation and maritime sectors, and biomass co-processing are analyzed. These strategies may bring resilience to the sector. The potential for avoiding emissions in refineries' operations is also explored. Findings show that the refining sector operates at 70% and 74% of its nameplate capacity in decarbonization scenarios. These results are used as the starting point for a detailed analysis of Brazilian refineries. Results show that the employment of refineries' assets for purposes aligned with decarbonization targets, along with emissions mitigation in the sector, reduces risks of carbon lock-in and of asset stranding. To our knowledge, this is the first study that evaluates emissions mitigation in the refining sector and also uses an integrated assessment model to investigate oil refining repurposing and co-processing options in the context of decarbonization. • The refining sector is evaluated using an integrated assessment model for Brazil. • A comparison is made between business- as -usual and decarbonization scenarios. • Opportunities for refineries' assets and mitigation measures are explored. • Opportunities for refineries depend on their location and type of processing units. • Risks of carbon lock-in and asset stranding can be reduced. [ABSTRACT FROM AUTHOR]

Increasing energy demand and the industrialization of communities have been the leading causes of climate change. As a result, natural disasters have increased blackouts in power systems. Climate change mitigation should be a global goal of communities. Since natural disaster occurrence has risen recently, rapid system restoration after natural disasters is essential. Mitigation of global warming is inextricably linked to the mechanisms and architecture of energy systems. Energy resilience is a multi-dimensional solution to this problem. In this research, resilient strategies for dealing with natural disasters have been examined. Implementing distributed energy resources (DERs), smart distribution networks, and defining load priority based on consumers' preferences have made a viable solution to the post-disaster operation. Previous efforts cared more about the generation and transmission sectors. This study focused on active distribution systems (ADSs) because distribution systems, as a vital part of energy systems, have not sufficiently contributed to crisis management. A framework for resilience enhancement to smartening conventional distribution systems against natural disasters has been proposed. Three-stage socio-technical optimization was investigated, including optimal allocation of battery storage systems (BESSs), intentional islanding, and optimal power flow (OPF) in MATLAB and DIgSILENT. This optimization presents a decision-making tool for distribution system operators to quickly prepare the system against natural disasters. By applying eight scenarios in the proposed system, in the best scenario (CS4), the recovered power value (RPV) has increased from 38% to more than 99% (more than 61% increase in the resilience index). The amount of supplied load increased from 56% to 92%. Furthermore, prioritizing crucial consumers and reconfiguration are two primary crisis management tools. This approach creates a solid ground for avoiding the social consequences of natural disasters like electrocution and power outages of priority consumers. Failure to apply these two techniques would result in a 21% reduction in the RPV. • Determining load priorities based on consumers' preference. • Optimal placement of batteries considering cost and load priority. • Intentional islanding of the system to enhance resilience. • In the best scenario (CS4), recovered power value (RPV) has increased to 99.35%. • Failure to apply load priority and reconfiguration has reduced RPV to 77.85% (CS5). [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the decoupling status and mitigation potential of CO2 emissions from China's transport sector over the period 1991–2015. Firstly, this paper utilizes the Log-Mean Divisia Index (LMDI) technique to identify influencing factors, which govern CO2 emissions from China's transport sector. Over the study period, the CO2 coefficient effect (Δ C c f t ) was the main factor for decreasing CO2 emissions. However, the economic growth effect (Δ C g t ) was the main factor for increasing CO2 emissions. Then, the decoupling indicator is also constructed based on the above influencing factors, which can be utilized to reflect the dependence degree of economic development on CO2 emissions from China's transport sector. During 1991–2015, the CO2 emissions from China's transport sector presented expansive coupling (EC) with economic development. Weak decoupling (WD) only appeared in the sub-period 1991–1995. The CO 2 emissions only presented 3 decoupling grades in all sub-period and the period 1991–2015: Ⅱ, Ⅲ, and Ⅳ. Furthermore, the above influencing factors are also used to establish a theoretical mitigation model, which is used to reflect the mitigation potential of CO2 emissions from China's transport sector. Finally, the occurrence of CO2 mitigation only appeared in 3 sub-periods: 1991–1995, 2005–2010, and 2010–2015. • The LMDI technique is used to identify influencing factors. • The decoupling indicator is constructed based on the influencing factors. • The influencing factors are used to establish a theoretical mitigation model. [ABSTRACT FROM AUTHOR]

The deployment of geothermal energy systems can significantly contribute to climate change mitigation and play a part in the transition to a low carbon society. This study proposes a framework for identifying the shallow geothermal energy potential of new individual and district heating (DH) systems. The model accounts for thermal interference between neighbouring wells and borehole heat exchangers, where the main criteria for analysis are ground temperature, thermal conductivity, heat flow, and heat capacity. The paper presents a cost-effective area method for the identification of potential new DH areas, while considering the cost competitiveness of the heat supplied. Economic potential is determined based on the cost-effectiveness of the competing technologies, separately for urban and rural areas. The results show that although 54% of technical DH potential in Slovenia remains untapped, the future of shallow geothermal energy systems lies predominantly in individual systems, which have proven to be the most cost efficient solution on locations with favourable geological or hydro-geological conditions. Where possible, shallow geothermal energy can contribute from 2% to 25% of energy for heat production in analysed existing fossil fuel based DH systems, thus making shallow geothermal energy suitable for supplying base load power in an economical manner. • Study of shallow geothermal energy exploitation in individual and new DH systems. • Ground-source heat pumps are examined at a grid cell size resolution of 100 m. • Cost-effective area model is introduced, which identifies new DH areas. • Out of 5 TWh/a technical potential for new DH, only 0.95 TWh/a is economically viable. • Temperature plume plays a key role in analyses of potential. [ABSTRACT FROM AUTHOR]

Geothermal energy can play a vital role in the mitigation of climate change due to its CO 2 -neutral, renewable and non-fluctuating character. Because of the expensive preparation of the geothermal wells, the thermal water should be utilized with the highest efficiency. Therefore, the wells are often exploited in combined heat and power concepts. Consequently, the power plant operates in part load most of the time. However, this high portion of part load operation is often not fully considered in the design stage of the plant, due to a lack of suitable simulation models. Therefore, the purpose of this paper is to compare several approaches to simulate the part load behavior of the geothermal Kalina power plant in Unterhaching (Germany) and to validate them with operational data. Simulation approaches to calculate the isentropic efficiency of the turbine and the heat transfer coefficients of the heat exchangers are studied and compared on component level. An investigation of different combinations of these component models then follows. The results show that a detailed correlation to model the isentropic efficiency of the turbine is necessary to achieve sufficient accuracy. Furthermore, modeling plate heat exchangers with a power law approach for the heat transfer coefficient appears promising. • Operational data of a Kalina power plant is given. • Comparison of modeling approaches by means of the annual produced electricity. • Plate heat exchanger modeling with a power law approach yields sufficient results. • A correlation for the isentropic efficiency of the turbine is suggested. • A correlation of the turbine isentropic efficiency is needed to model in off-design. [ABSTRACT FROM AUTHOR]

Abstract Currently, the economic performance of rooftop photovoltaics (PVs) is predominantly evaluated using the levelized cost of electricity approach. Some researchers have argued that rooftop PVs should be viewed as an investment, where performance is evaluated using relevant investment analysis methods. This article argues that the proper economic value and climate mitigation potential of rooftop PVs can be assessed only if the market mechanisms and characteristics of the underlying building stock are understood better. This paper utilises a customer-driven investment model to examine the feasible market potential of rooftop PVs in an urban environment. The economic returns of PV installations are calculated for 89,000 buildings separately and by comparing them to the underlying spatial property returns, the profitability and adoption years of rooftop PVs for in different locations are estimated. Implications for CO2 emissions and the impact of the net metering (NM) policy on the rate of adoption are calculated. The results imply that even in Finland rooftop solar PVs are already profitable for a third of the residential building stock and will be profitable for a fourth of the commercial building stock by 2025. Finally, the NM could increase substantially the diffusion rate of solar PVs in the coming years. Highlights • Real estate economics provides a new perspective to estimate the diffusion of rooftop PVs. • In the Helsinki Metropolitan Area, rooftop PVs are already profitable for a third of the residential building stock. • A fourth of the commercial building stock will be profitable by 2025. • Net metering (NM) could increase the diffusion of rooftop PVs rapidly. • The benefits of implementing NM seem to outweigh the costs of implementation. [ABSTRACT FROM AUTHOR]

Abstract Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. Highlights • Comparison of technology representation and techno-economic parameters of 15 IAMs. • Structural differences in representing technology in IAMs are identified. • Methods of projecting techno-economic parameters differ across IAMs. • Strict harmonization of techno-economic parameters across models is difficult. • Recommendation to publish techno-economic parameters and technology representation. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a new approach to incorporate climate damages in the BAU emissions baselines. The shared socio-economic pathways framework is used to inform country-level changes in the mean surface temperature for the climate projections associated with each scenario. The temperature changes are used to calculate the economic damages using empirical estimates of climate effects on GDP growth. Finally, an energy system model is used under the original socio-economic assumptions and the climate-damaged assumptions, illustrating the indirect effect of climate change in a country-level energy system. Mexico was chosen to exemplify this method. The results show a reduction of energy access and a slow down of technological transition in the energy sector under climate-damaged projections. It is concluded that greenhouse gas mitigation goals should be re-calibrated under cost-benefit analysis that takes into account the damages associated with future climates consistent with the baseline. Thus, the nationally determined contributions that state the emission goals of many countries could be closer to limit the temperature to 1.5 Celsius above pre-industrial levels. Highlights • Climate change impacts on energy systems are assessed via climatically-damaged GDP. • New business as usual scenarios are computed accounting for its associated climates. • Under new BAU, energy production and society's welfare decreases. • Greenhouse gases mitigation goals should be re-calibrated under new BAU. • The recalibration could enable accomplishment of Paris Agreement. [ABSTRACT FROM AUTHOR]

Abstract Japan is the sixth largest greenhouse gas emitter in 2016 and plays an important role to attain the long-term climate goals of the Paris Agreement. One of the key policy issues in Japan's energy and environmental policy arena is the energy system transition to achieve 80% emissions reduction in 2050, a current policy goal set in 2016. To contribute to the ongoing policy debate, this paper focuses on energy-related CO 2 emissions and analyzes such decarbonization scenarios that are consistent with the government goals. We employ six energy-economic and integrated assessment models to reveal decarbonization challenges in the energy system. The modeling results show that Japan's mitigation scenarios are characterized by high marginal costs of abatement. They also suggest that the industrial sector is likely to have a large final energy share and significant residual emissions under the 80% reduction scenario, though it is generally thought that the transport sector would have large decarbonization challenges. The present findings imply that not only energy policy but also industrial policy may be relevant to the long-term environmental target. Given the high marginal costs exceeding those of negative emissions technologies that could place a cost ceiling, further model development would be crucial. Highlights • We analyze the energy system scenarios to achieve 80% reduction in carbon dioxide emissions by 2050. • We employ six integrated assessment models to reveal decarbonization challenges in the energy system. • The model results show that the industrial sector has a large final energy share and significant residual carbon dioxide emissions under the 80% reduction scenario. • We also show that Japan's mitigation scenarios are accompanied with high marginal costs of abatement. [ABSTRACT FROM AUTHOR]

Abstract Energy scenarios provide guidance to energy policy, not least by presenting decarbonisation pathways for climate change mitigation. We review such scenarios for the example of Germany 2050, with a focus on the decarbonisation of heat generation and road transport. In this context, we characterize the role of renewable electricity and contrast two rivalling narratives: direct and indirect electrification. On the one hand, electricity directly provides heat and transport, using electric heat pumps, electric heaters, and battery electric vehicles. On the other hand, electricity, heat, and transport are indirectly linked, using gas heat pumps, gas heaters, fuel cell electric vehicles, and internal combustion engine vehicles, in combination with power-to-gas and power-to-liquid processes. To reach climate policy targets, our findings imply that energy stakeholders must (1) plan for the significant additional demand for renewable electricity for heat and road transport, (2) pave the way for system-friendly direct heat electrification, (3) be aware of technological uncertainties in the transport sector, (4) clarify the vision for decarbonisation, particularly for road transport, and (5) use holistic and more comparable scenario frameworks. Highlights • In the scenarios reviewed, GHG emission reduction targets drive electrification. • If targets are met by 2050, 40–100% of heat and car transport will be electrified. • The electricity consumption of heat and transport will increase to 400–800 TWh. • Heat generation, at least in the building sector, favours direct electrification. • Preferable electrification paths and technologies for road transport are unclear. [ABSTRACT FROM AUTHOR]

Abstract High-temperature heat pumps (HTHPs) based on vapour compression can be used for industrial low-grade waste heat valorisation, which can aid in mitigating climate change. Currently, the performance of HTHPs operating at high-temperatures lifts is limited; therefore, advanced configurations become an opportunity for their utilisation. This paper presents an HTHP cascade with configurations of internal heat exchangers (IHXs) that uses low GWP refrigerants in both high-stage (HS) (HCFO-1233zd(E), HFO-1336mzz(Z), HCFO-1224yd(Z), and pentane) and low-stage (LS) (HFO-1234yf, HFO-1234ze(E), butane, isobutane, and propane) cycles. Prior to the analysis and presentation of results, an optimisation of the operating conditions is performed based on intermediate temperature and IHX effectiveness in both stage cycles. Results indicate that butane and isobutane appear to be the most convenient working LS fluids from the point of view of coefficient of performance (COP). The highest system performance is obtained using pentane and HFO-1336mzz(Z) in the HS cycle. Compared to third-generation refrigerants (HFC-245fa/HFC-134a), a slight COP improvement is obtained using HCFO-1233zd(E), and HCFO-1224yd(Z). A comparable or even lower volumetric flow rate at the HS compression suction is also observed. The use of pentane/butane achieved maximum COP (3.15), which is a 13% improvement compared to COP obtained when HFC-245fa/HFC-134a is employed. Highlights • A high-temperature heat pump cascade with the IHXs is proposed and optimised. • Synthetic and natural refrigerants with low GWPs are proposed for both stages. • The higher effectiveness of both IHXs in similar proportions increases total COP. • Pentane/butane presents maximum COP and minimum HCFO-1224yd(Z)/HFO-1234yf. • A few refrigerant pairs are comparable with HFC-245fa/HFC-134a in the stages of V ˙ s u c . [ABSTRACT FROM AUTHOR]

Abstract The five Nordic countries of Denmark, Finland, Iceland, Norway and Sweden have aggressive climate and energy policies in place and are largely on track in their decarbonisation of electricity, heat, and buildings. Transportation and mobility, however, remains a pressing challenge. This study asks: what are the greatest national and regional transport challenges facing Nordic countries? To provide an answer, the authors conducted 227 semi-structured interviews with participants from 201 institutions across seventeen cities within the Nordic region. Those interviewed represent a diverse array of stakeholders involved with transport technology, policy and practice. Although respondents identified 44 distinct transport challenges, the fossil fuel intensity of transport was by far the most frequently mentioned by more than two-fifths (42%) of the expert sample. Five other challenges were also mentioned the most frequently by respondents: long travel distances (17%), the state of public transport infrastructure (16%), congestion (15%), population density (10%), and electrification of transport (10%). Interestingly, items such as costs and affordability, energy or transport efficiency, consumer knowledge and awareness, and automobile accidents were mentioned by only 3% (or less). The article concludes by what this heterogeneity and prioritization of challenges means for future Nordic research and policy. Highlights • The five Nordic countries have not made substantial progress in decarbonizing transportation and mobility. • What are the greatest national and regional transport challenges facing Nordic countries? • Fossil fuel intensity of transport was by far the most frequently mentioned challenge among expert interviews. • Long travel distance, infrastructure and congestion were depicted as challenges. • Population density and electrification of transport were also mentioned as challenges. [ABSTRACT FROM AUTHOR]

Regionalized Negative Emission Technology (NET) portfolios can sustainably support climate change mitigation. However, current studies focus on individual technologies that may be unsustainable on the large scale. The existing studies also do not consider multiple environmental footprints, technological readiness, and ecological discount rates, which are critical for addressing the future environmental damages of climate change. This study addresses these research gaps by using mixed integer linear programming to develop a multi-footprint, multi-period, optimization model for NET portfolios. The model is illustrated with a case study in the Southeast Asian region until 2100. The results show varying portfolios, with the net present value ranging from USD 516–2783 B, and the negative emissions from 30.42 to 79.56 Gt CO 2. The cheaper, technologically ready options like afforestation and biochar are selected earlier in the portfolio, while the initially expensive, emerging technologies like enhanced weathering and direct air capture come later. Land and water are the limiting resources. Both carbon value discounting and using a high initial carbon price support the early deployment of NETs for climate change mitigation. The model currently does not consider synergistic/antagonistic interactions between NETs, multi-objective optimization, and parametric uncertainties, which can be included in future works. [Display omitted] • A multi-footprint, multi-period, MILP model is developed for NETs portfolio optimization. • The model maximizes the net present value of the portfolio. • Economic and carbon value discount rates are applied. • Different scenarios result in different NET portfolio configurations. • Results show how NET portfolios under resource constraints perform in a discounted carbon market. [ABSTRACT FROM AUTHOR]

This paper examines the social costs and benefits of potential configurations of electric vehicle deployment, including and excluding vehicle-to-grid. To fully explore the benefits and costs of different electric vehicle pathways, four different scenarios are devised with both today's and 2030 electricity grid in Denmark. These scenarios combine different levels of electric vehicle implementation and communication ability, i.e. smart charging or full bi-directionality, and then paired with different levels of future renewable energy implementation. Then, the societal costs of all scenarios are calculated, including carbon and health externalities to find the least-cost mix of electric vehicles for society. The most cost-effective penetration of electric vehicles in the near future is found to be 27%, increasing to 75% by 2030. This would equate to a $34 billion reduction to societal costs in 2030, a decrease of 30% compared to business as usual. This represents a projected annual savings per vehicle of $1200 in 2030. However, current vehicle capital cost differences, a lack of willingness to pay for electric vehicles, and consumer discount rates are substantial barriers to electric vehicle deployment in Denmark in the near term. [ABSTRACT FROM AUTHOR]

Local climate action is not only a domain of large cities, but also smaller urban areas that increasingly address climate change mitigation in their policy. The Danish municipality of Helsingør can achieve a substantial CO 2 emissions reduction by transforming its heat supply and deploying heat savings. In this paper, we model the heating system of Helsingør, assess it from a simple socio- and private-economic perspective, develop future scenarios, and conduct an iterative process to derive a cost-optimal mix between district heating, individual heating and heat savings. The results show that in 2030 it is cost-optimal to reduce the heating demand by 20–39% by implementing heat savings, to deploy 32%–41% of district heating and to reduce heating-related CO 2 emissions by up to 95% in comparison to current emissions. In 2050, the cost-optimal share of district heating in Helsingør increases to between 38 and 44%. The resulting average heating costs and CO 2 emissions are found to be sensitive to biomass and electricity price. Although the findings of the study are mainly applicable for Helsingør, the combined use of the Least Cost Tool and modelling with energyPRO is useful in planning of heating and/or cooling supply for different demand configurations, geographical region and scale. [ABSTRACT FROM AUTHOR]

Deregulation is widely considered a driver of competition and reduction of market inefficiency and can lead to innovation. We deepen the literature and policy understanding of this narrative by extending it to negative emission technologies while we strengthen the findings of previous studies by accounting for input research and development (R&D) expenditure with heterogeneity analyses. The authors adopt the staggered difference-in-difference (SDID) design to 25 OECD countries for the period 1985–2015 to examine the influence of deregulation on innovation in the electricity industry with an emphasis on negative emission technologies. The empirical results show that while electricity deregulation is generally associated with increased innovation, only intense market deregulation can promote innovation in carbon capture and storage (CCS). This benefit is more observed in European Union OECD countries and those with high output innovation performance. The results also show that when implemented after market deregulation, solar PV and Wind power Feed-in tariffs effectively promote renewable energy innovation. The results suggest that electricity deregulation is a compelling market tool to promote climate change mitigation since the competitive market it creates supports the advancement of CCS and renewable energy innovation. We recommend a deregulation process to accommodate an effective market model designed to incentivize the promotion of funding for negative emission technologies. • We study the effect of deregulation (PMR) on innovation in the electricity industry. • The staggered DID method is applied to electricity deregulation and innovation. • Electricity deregulation can promote negative emission technology such as CCS. • Renewables feed-in tariffs effectively promote innovation in post-deregulation. • The results have implications for both developed and developing economies. [ABSTRACT FROM AUTHOR]

Global climate change and energy crises have increasingly impeded the sustainable development of society and economy. With an accelerated process of urbanization and improved standards of living, China has become the largest carbon emitter in the world and therefore has great responsibility and great potential to mitigate global carbon emissions. Accordingly, as the largest source of emissions in China, Chinese buildings should also decrease carbon emissions towards this goal. However, until now, there has been no clear and comprehensive understanding of the carbon emissions in this sector. To fill this gap, we survey the current and future situation. Firstly, we estimate the controlled ceiling of building carbon emission, splitting from the overall reduction goal in China. Then we develop a comprehensive carbon-calculating methodology, the China Building Carbon Emissions Model, using a bottom-up approach, and assess the building carbon emissions based on official statistics. On the basis of that, scenario analysis is used to predict the future trend of carbon emissions in China's building sector. According to our analysis, it is critical to simultaneously control floor space, energy consumption and energy structure to limit the growth of carbon emissions in the building sector. Finally, some relative policy suggestions are also discussed. [ABSTRACT FROM AUTHOR]

The industry sector is a major energy consumer and GHG emitter. Effective climate change mitigation strategies will require a significant reduction of industrial emissions. To better understand the variations in the projected industrial pathways for both baseline and mitigation scenarios, we compare key input and structure assumptions used in energy-models in relation to the modeled sectors' mitigation potential. It is shown that although all models show in the short term similar trends in a baseline scenario, where industrial energy demand increases steadily, after 2050 energy demand spans a wide range across the models (between 203 and 451 EJ/yr). In Non-OECD countries, the sectors energy intensity is projected to decline relatively rapidly but in the 2010–2050 period this is offset by economic growth. The ability to switch to alternative fuels to mitigate GHG emissions differs across models with technologically detailed models being less flexible in switching from fossil fuels to electricity. This highlights the importance of understanding economy-wide mitigation responses and costs and is therefore an area for improvements. By looking at the cement sector in more detail, we show that analyzing each industrial sub-sector separately can improve the interpretation and accuracy of outcomes, and provide insights in the feasibility of GHG abatement. [ABSTRACT FROM AUTHOR]

Limiting global warming well below 2 °C requires substantial increase in the installation of low-carbon electricity generation technologies (EGTs). EGTs however require several critical materials and materials associated with considerable energy, water and CO 2 emissions. This paper assesses the implications of materials and energy efficiencies for climate change mitigation potential of global energy transition scenarios (GETS). The analysis is carried out using a dynamic material flow-stock model for 21 materials and 15 scenarios combining GETS developed by international organizations including International Energy Agency (IEA) and Greenpeace (GP), materials scenarios, and energy, water, and emissions intensities scenarios. Materials related CO 2 emissions are expected to constitute between 4% and 14% the emissions reported in the IEA Sustainable Development scenario, while expected to be between 10% and 28% in GP Advanced Revolution scenario. Increasing material efficiency and reducing emissions intensities (driven by increasing energy efficiency, renewable technologies in energy supply mix, and recycling) reduce cumulative emissions by 73.2% and 26.3% respectively, while both reduce emissions by 79.5%. Increasing materials efficiency in EGT, energy and water efficiency in mining activities mainly for iron, aluminium, and nickel, and recycling, combined with careful selection of EGTs are significant to realize the full potential of GETS in climate change mitigation. • Materials and energy efficiencies implications for climate change mitigation potential of energy scenarios are assessed. • Dynamic material flow-stock model for 21 materials and 15 combined materials and energy scenarios are used. • Materials related CO 2 emissions constitute between 4% and 14% of emissions reported in IEA Sustainable Development scenario. • Increasing material efficiency and reducing emission intensities reduce cumulative emissions by 79.5%. • Increasing materials efficiency and recycling, and careful selection of EGT are significant for climate change mitigation. [ABSTRACT FROM AUTHOR]

Energy markets are critical avenues for achieving the goal of climate action. Nevertheless, effective green policies by the government may significantly influence the demand and supply side of the market differently. Using the time-varying parameter vector autoregression (TVP-VAR) and panel autoregressive distributed lag (PARDL), this study examines the role of institutional enforcement of environmental taxes and government spending on environmental protection on the returns and risk connectedness of energy stocks of 12 countries. The results show that networks of energy stocks primarily influence the returns and risk of each country's energy stock. The analysis further reveals that institutional enforcement of environmental fiscal laws reduces the long-run total returns connectedness of the energy market only through the net transmitting markets. The opposite is observed in net receiving markets. On the other hand, the risk spillover of energy markets increases with enforcing environmental protection spending only through the net receiving markets in the long run. A detailed analysis of the net receiving markets demonstrates that, depending on the period and the instruments employed, the impact of enforcing environmental fiscal laws on risk spillover of these markets is heterogeneous. The results of this study emphasize the policy implications for investors and climate change. • Returns and risk of energy stocks are mostly network-driven. • Enforcing environmental fiscal stance reduces returns shocks in net transmitting markets. • Risk shocks are amplified in net receiving markets by enforcing government spending on environmental protection. [ABSTRACT FROM AUTHOR]

Shale gas is becoming a top priority for future global energy consumption and climate change mitigation, and deep and ultradeep shale gas extraction cannot overlook the influence of the geothermal environment. This paper experimentally investigated the tensile behavior and acoustic emission (AE) characteristics of anisotropic shale under geothermal environment of 25–200 °C. The results indicate that the tensile strength and absorbed energy of all specimens decreased with increasing temperature, and minimum values occurred in specimens with a layer inclination of 90° at each temperature. The evolution of tensile strength and absorbed energy versus the layer inclination did not vary with increasing temperature, exhibiting an inverted-V shape. Anisotropic failure mode of specimens with layer inclinations of 30°, 45° and 60° was influenced by the increasing temperature, but central tensile fracturing in specimens with layer inclinations of 0° and 90° was temperature-independent. With increasing temperature, the cumulative AE hits of specimens showed a highly obvious step-up trend, and anisotropic crack initiation stress levels obtained via the AE definition significantly varied. Finally, microstructure response, fracture length and fracture location and proportion of fracture types were discussed, and potential applications and challenges of geothermal environment in hydraulic fracturing of deep shale reservoirs were proposed. • Tensile behavior and AE characteristics of shale under the geothermal environment were investigated by Brazilian test. • Anisotropic tensile properties and AE activities of shale specimens versus the geothermal temperature were summarized. • Anisotropic failure behavior of shale specimens versus the geothermal temperature was concluded and discussed. • Potential applications of geothermal environment in hydraulic fracturing of deep shale reservoirs were proposed. [ABSTRACT FROM AUTHOR]

In the EU, COVID-19 and associated policy responses led to economy-wide disruptions and shifts in services demand, with considerable energy-system implications. The European Commission's response paved the way towards enhancing climate ambition through the European Green Deal. Understanding the interactions among environmental, social, and economic dimensions in climate action post-COVID thus emerged as a key challenge. This study disaggregates the implications of climate ambition, speed of economic recovery from COVID-19, and behavioural changes due to pandemic-related measures and/or environmental concerns for EU transition dynamics, over the next decade. It soft-links two large-scale energy-economy models, EU-TIMES and NEMESIS, to shed light on opportunities and challenges related to delivering on the EU's 2030 climate targets. Results indicate that half the effort required to reach the updated 55% emissions reduction target should come from electricity decarbonisation, followed by transport. Alongside a post-COVID return to normal, the European Green Deal may lead to increased carbon prices and fossil-fuel rebounds, but these risks may be mitigated by certain behavioural changes, gains from which in transport energy use would outweigh associated consumption increases in the residential sector. Finally, the EU recovery mechanism could deliver about half the required investments needed to deliver on the 2030 ambition. • This study soft-links an energy system model and a macroeconometric model for the EU. • Electricity decarbonisation can make up half the effort to −55% followed by transport. • Investments as part of EU green recovery could finance about half of what is required. • The pandemic is unlikely to heavily impact the EU's long-term emissions trajectory. • Work- and travel-related behaviour changes could considerably reduce investment needs. [ABSTRACT FROM AUTHOR]

Due to frequent natural disasters, it is required for the energy systems to be more resilient and affordable. Numerous investigations can be found in the publications that proposed renewable energy systems to deliver power to localities. Nevertheless, researchers have yet to explore the resiliency benefits of renewable energy systems in refugee camps. Therefore, in this study, we modelled the performance of a PV/battery system for hypothetical health care centres located in the Rohingya refugee camp, Bangladesh. A 24-h grid outage was assigned to the REopt software to observe the survival possibility of the system. An optimized mixed-integer linear programming model is used as it considers several practical parameters such as reducing total cost sufficiently robust to handle the simulated outages perfectly. The optimum system consists of a 643 kW PV and a 102 kW battery. The potential life cycle savings of the system are $27,212, and the system can successfully handle a 24-h duration outage. The system also reduces CO 2 emissions by 69% in resilient mode compared to 44% in financial mode. Therefore, it can contribute to climate change mitigation. • First study to address the resiliency benefits of a PV/Battery System in Refugee Camp. • REopt software is used to study and simulate the outage impact in the camp. • The system can successfully handle a 24-h duration outage. • The optimum system consists of a 643 kW PV and a 102 kW battery. • The system also reduces CO 2 emission by 69% in resilient mode. [ABSTRACT FROM AUTHOR]

Renewable energy resources have garnered considerable attention owing to concerns regarding climate change mitigation and sustainability. The performance of renewable energy resources varies based on weather conditions, which is an important consideration in power system planning as renewable energy penetration increases. In this study, a probabilistic approach for the potential estimation of renewable energy resources based on augmented spatial interpolation was proposed. The proposed algorithm was verified using empirical data obtained from wind farms in Jeju Island. Wind power output scenarios were modeled through ordinary kriging and Monte Carlo simulations. Moreover, the point and cause of line overload according to the seasonal wind power output and power demand were analyzed through transmission security analysis, and the frequency and scale of the curtailments were estimated. This can be used to estimate potential renewable energy resources and establish a power system operation plan. Further study includes the development of stable power system operation plans for large-scale renewable energy resource-integrated power systems. [ABSTRACT FROM AUTHOR]

One of the motivations for the removal of subsidies on fossil fuels is that these subsidies lead to the over-consumption of energy, and as a result, undermine environmental quality. Despite the huge opportunities that removal of subsidies on fossil fuels may bring for climate change mitigation, empirical studies for Ghana have failed to appropriately test these links. For this reason, this study employs a multi-region computable general equilibrium (CGE) model to evaluate the welfare and environmental impacts from imported refined oil subsidies removal in Ghana. The simulation experiment shows evidence of welfare losses even if environmental benefits are accounted for. Although the rate of CO 2 emissions appears to increase, there is an overall 1.9% improvement in environmental quality due to the removal of fuel subsidies. The results provided in this study imply that the removal of subsidies on energy should be implemented along with policies aimed at stimulating economic activities. In addition, the study has implications for the so-called ‘green paradox’. [ABSTRACT FROM AUTHOR]

This work evaluates implications of incorporating LCA-GHG (life cycle assessment of GHG emissions) into the optimisation of the power generation mix of Brazil through 2050, under baseline and low-carbon scenarios. Furthermore, this work assesses the impacts of enacting a tax on LCA-GHG emissions as a strategy to mitigate climate change. To this end, a model that integrates regional life cycle data with optimised energy scenarios was developed using the MESSAGE-Brazil integrated model. Following a baseline trend, the power sector in Brazil would increasingly rely on conventional coal technologies. GHG emissions from the power sector in 2050 are expected to increase 15-fold. When enacting a tax on direct-carbon emissions, advanced coal and onshore wind technologies become competitive. GHG emissions peak at 2025 and decrease afterwards, reaching an emission level 40% lower in 2050 than that of 2010. However, if impacts were evaluated through the entire life cycle of power supply systems, LCA-GHG emissions would be 50% higher in 2050 than in 2010. This is due to loads associated with the construction of plant infrastructures and extraction and processing of fossil fuel resources. Thus, taxes might not be as effective in tackling GHG emissions as shown by past studies, if they are only applied to direct emissions. [ABSTRACT FROM AUTHOR]

Climate change mitigation has been a global effort and energy generation is one of the primary sources of GHG emissions. There is a need to transition from fossil-based energy to renewable-based energy. One of the platforms to nourish the work is Eco-Industrial Park (EIP) which it promotes resource efficiency, industrial symbiosis, and circular economy practice. There is a need to explore an optimal configuration of multiple renewable energy (RE) systems in a centralised EIP facility that generates electricity for internal consumption and exports the excess energy to the grid. This model developed a mixed-integer non-linear programming (MINLP) model that considers RE from biogas, biomass, micro-hydro, and solar sources for a centralised water hub. The energy generated is primarily used for the main processes involved in the facility as the excess energy will be supplied to the grid. A case study and two scenarios were assessed, and the results offered simultaneous technical, economic, and environmental benefits, which are in the forms of multiple RE generations, additional yearly profit, and GHG emission avoidance from fossil source. This will further strengthen the envisioned role of EIP as it is also capable of supporting the United Nations Sustainable Development Goal (UNSDG) and RE100 agenda. • A MINLP model to optimise renewable energy generation for Total Site was developed. • The model is a part of a framework to optimise energy, water, and material streams. • The model considers energy generation via solar, micro hydro, biomass, and biogas. • The proposed installation could suffice the core processes energy needs. • Additional profit is up to 39% and GHG emission reduction can be up to 70%. [ABSTRACT FROM AUTHOR]

The Spanish national energy and climate plan (PNIEC) has recently been published, leading the worldwide task of climate change mitigation towards a net zero-carbon economy by 2050. The objective scenario of the PNIEC expects to reach a renewable share in the power system of 74% by 2030. In this context, three contributions are developed: i) providing an analysis of how Spain is facing the energy transition; ii) conceptualizing the link between an hourly energy model (EnergyPLAN) and a yearly integrated assessment model (MEDEAS); and iii) proposing a transparent policy agenda for the Spanish benchmarking in line with the official report. The results clarify the decreasing role such technologies as the combined heat and power facilities, as well as the pressure of biomass in Spain. Coherency in translating common variables in the energy chain of IAMs to the energy model is effectively reflected in the tables as an output of the research. Positive conclusions are found for Spain. The commitment of 74% might well be completed and the Spanish economy could run with a 100% renewable energy system by 2050, with requirements of sixteen and six times more installed capacity of solar-PV and wind onshore, respectively, by 2050 related to 2017. [ABSTRACT FROM AUTHOR]

A dynamic partial equilibrium model, TIMES (​The Integrated MARKAL-EFOM System), is built to optimize the energy system in a post-transition European country, the Czech Republic. The impacts of overall nine scenarios on installed capacity, capital and fuel costs, air quality pollutant emission, emission of CO 2 and environmental and health damage are quantified for a period up to 2050. These scenarios are built around three different price sets of the EUA (EU allowance) to emit greenhouse gasses alongside a policy that retains the ban on brown coal mining in two Czech mines, a policy that will allow the re-opening of mining areas under this ban (i.e. within the territorial ecological limits), and a low natural gas price assumption. We found that the use of up until now dominant brown coal will be significantly reduced in each scenario, although reopening the coal mines will result in its smaller decline. With low EUA price, hard coal will become the dominant fuel in electricity generation, while nuclear will overtake this position with a 51% or even 65% share assuming the central price of EUA, or high EUA price, respectively. The low price of natural gas will result in an increasing gas share from an almost zero share recently up to about 42%. This stimulus does not however appear at all with low EUA price. Neither of these scenarios will achieve the renewable energy sources 2030 targets and only a high EUA price will lead to almost full de-carbonization of the Czech power system, with fossil fuels representing only 16% of the energy mix. The low EUA price will result in an increase in CO 2 emissions, whereas the high EUA price will reduce CO 2 emission by at least 81% compared to the 2015 reference level. Those scenarios that will result in CO 2 emission reduction will also generate ancillary benefits due to reduction in air quality emissions, on average over the entire period, at least at 38€ per t of avoided CO 2 , whereas scenarios that will lead to CO 2 increase will generate ancillary costs at least of 31€ per t CO 2 . [ABSTRACT FROM AUTHOR]

The goal of this paper is to showcase a modelling exercise, conducted for the Republic of Macedonia, a non-Annex I country under UNFCCC and a candidate for EU membership, by making use of MARKAL energy system model. Baseline Scenario and three groups of mitigation scenarios have been developed until 2050, reflecting different types of targets with different levels of ambition regarding CO 2 emissions reduction: (1) EU scenarios – end-year targets compared to 1990 level; (2) QELRC (Quantified Emission Limitation and Reduction Commitment) scenarios – a range of targets over the period 2021–28 and for each subsequent 8-year period, and (3) Baseline deviation scenarios – deviation compared to baseline emission level. The comparative assessment of mitigation scenarios, based on the cumulative emissions, cumulative total system costs and incremental specific reduction cost, has generated a basis for setting the national mitigation contributions and formulating the most appropriate national mitigation action plan. [ABSTRACT FROM AUTHOR]

Developing energy solutions that positively impact issues related to economic growth, the environment and social equity in cities is important. A better understanding of urban energy use, particularly in developing countries, can strengthen energy security, climate change mitigation and local pollution abatement. This study seeks to evaluate the trends in energy use and CO 2 emissions in Bogotá by determining energy flows through input and output analyses. The study establishes a relationship between energy and sustainable development by applying correlation analyses. Bogotá consumes 24% of the electricity produced in the country, generates 96010.1 TJ of the gross energy, and emits CO 2 , NOx and CO (carbon monoxide). Correlation analyses indicate a strong and direct relationship between energy, economic variables and social variables, with the majority of the correlation coefficients exceeding 0.8. Strong positive correlations are particularly observed between energy consumption, the gross domestic product, the human development index and CO 2 emissions. Energy per capita and CO 2 emissions per capita also strongly correlate with the human development index and GINI coefficients. These results demonstrate that energy increasingly influences the development, economic growth and welfare of the city population. Thus, formulating strategies that will improve energy use in cities is important. [ABSTRACT FROM AUTHOR]

We introduce a new method for incorporating short-term temporal variability of both power demand and VRE (variable renewables) into long-term energy-economy models: the RLDC approach. The core of the implementation is a representation of RLDCs (residual load duration curves), which change endogenously depending on the share and mix of VRE. The approach captures major VRE integration challenges and the energy system's response to growing VRE shares without a considerable increase of numerical complexity. The approach also allows for an endogenous representation of power-to-gas storage and the simultaneous optimization of long-term investment and short-term dispatch decisions of non-VRE plants. As an example, we apply the RLDC approach to REMIND-D, a long-term energy-economy model of Germany, which was based on the global model REMIND-R 1.2. Representing variability results in significantly more non-VRE capacity and reduces the generation of VRE in 2050 by about one-third in baseline and ambitious mitigation scenarios. Explicit modeling of variability increases mitigation costs by about one fifth, but power-to-gas storage can alleviate this increase by one third. Implementing the RLDC approach in a long-term energy-economy model would allow improving the robustness and credibility of scenarios results, such as mitigation costs estimates and the role of VRE. [ABSTRACT FROM AUTHOR]

Sustainable energy transition, air pollution reduction and climate change mitigation are the most challenging themes in nowadays energy sector. Microgrids (MGs) are one of the most effective ways to integrate Renewable Energy Sources (RES), and among them PhotoVoltaic (PV)-Storage (ST) configuration is relevantly promising. Focusing the attention on the PV and ST converters primary control, the main needs are to properly regulate voltage and frequency and optimally exploit the energy coming from the sun and manage the ST operation without any communication among the converter controllers. The conventional converter control approach presents several drawbacks and thus a strategy based on Higher Order Sliding Mode (HOSM) is presented in this work. The HOSM converter control strategy is fully analysed defining its control laws and the control schemes. A comparison between the HOSM and conventional control is performed with dedicated simulations on a common benchmark MG in order to highlight the advantages of the proposed strategy. • Decentralized control of islanded photovoltaic-storage microgrids. • Higher-Order sliding model application to microgrids. • Robust control approach for islanded power systems. • Combined results of primary and secondary frequency regulation without communication. [ABSTRACT FROM AUTHOR]

Phasing-out fossil fuels is key to limiting global warming to 1.5 °C. Recent studies indicated huge amounts of unextracted oil resources in deep mitigation scenarios. However, crude oil heterogeneity and related refining yields have been overlooked. The same holds for the impact of carbon dioxide removal (CDR) and sequestration technologies on stranded oil resources, and the pace of crude oil extraction in different world regions in scenarios with and without average global surface temperature overshoot for the 2020–2100 period. This study uses a global Integrated Assessment Model (IAM) to assess the impact of considering such complexities when running full-century and peak budget carbon scenarios. When "turning off" the detailed oil quality module of this IAM, an overproduction of crude oil with a smaller throughput of oil refineries was found, as the model simplified the oil supply-demand balance. "Turning on" the detailed oil module and simulating the energy-land nexus showed that CDR allowed the remaining use of oil in hard-to-abate sectors, while refineries were better adjusted to oil supply. African and Latin American regions produced more oil before 2050 in the full-century-budget scenario than in the peak budget scenario. This has implications for just transition, as these regions usually prefer anticipating rents. • Phasing-out fossil fuels and CDR options are key to limiting global warming. • Crude oil quality matters to estimate stranded oil resources. • Climate ambitions and negative emissions affect just transition. • The distribution of unextracted oil resources differs regionally. • Temperature overshoot allows some developing regions to anticipate oil revenues. [ABSTRACT FROM AUTHOR]

The trend for the decarbonization of the transportation sector, contributing to climate change mitigation, has driven the accelerated deployment of electric buses in cities. However, higher upfront costs, charging infrastructure deployment and operational issues are the main obstacles to their massive adoption. This work develops an optimization model to deal with the charging schedule of a fleet of battery electric buses. This approach aims to minimize the charging costs of electric bus fleets also considering the ageing of the batteries and the participation in vehicle to grid schemes. We developed a case study using real-world data from a small electric bus fleet of eleven electric buses in a medium-size Portuguese city. Further, we performed a sensitivity analysis to assess the possibilities of energy trading with the grid. The results indicate that below a battery replacement cost threshold of 100 €/kWh, it may become economically attractive for public transportation operators to sell back energy to the grid for a given remuneration scheme. Considering battery degradation and energy selling, our study indicates that operation costs could be 38% lower in 2030. The approach presented in this article provides a tool that can be employed by public transportation operators to assist decision making in the electrification of bus systems. • An optimization model to optimize electric bus fleet charging is developed. • The feasibility of V2G schemes considering battery degradation is evaluated. • Sensitivity analysis is performed to assess energy trading possibilities. • Total cost of ownership analysis evaluates the costs related to energy transactions. [ABSTRACT FROM AUTHOR]

One of the main initiatives in the context of global warming brought by the COP26 is global transition to green energy. Bioenergetic utilization of unharnessed renewable resources, such as native rangeland frequently subjected to fires, is a promising alternative to displace fossil fuels. Spartina argentinensis is a native perennial grass that develops in a depressed area of 33,000 km2 in Santa Fe province (Argentine) named "Los Bajos Submeridionales". A life cycle assessment (LCA) was performed analyzing the bioenergetic utilization of S. argentinensis. Two alternative scenarios (AS) were assessed and compared to their business as usual (BAU) counterparts: pellets for i) gasification to deliver electricity to the grid (ASp), contrasted to the Argentinean energy mix (BAUp) and ii) residential heating (ASh) contrasted to natural gas heating (BAUh). Carbon Balance of both AS were negative noticeably lower than BAU and the energy balance was promising considering that the produced energy was higher than that required along the complete system assessed. This is the first LCA of bioenergy from S. argentinensis and according to the results, this biomass resource could collaborate remarkably in climate change mitigation, which is auspicious considering the vast region occupied by this grass and others with similar characteristics. [Display omitted] • Spartina argentinensis can be pelletized without need of an additive. • Pellets can produce syngas for CHP or can be burnt for residential heat. • Renewable energies assessed produce significant lower GHG than fossil counterparts. • Renewable scenarios present high Energy Return on Investment. [ABSTRACT FROM AUTHOR]