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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]

To better qualify the ability of nuclear power to contribute to the net-zero emissions transition, the nuclear power sector needs to understand its sensitivity to hydro-climatic and anthropogenic stresses at the local level. While current approaches based on statistical modelling can be used to assess climate change impacts on electricity networks at a global or national level, they are limited when extrapolated to regulatory thresholds at a local level. As part of a series of two papers aimed at assessing the impact of climate change on site-specific nuclear power outages, this paper presents a modelling chain for estimating hydro-climatic-policy scenarios for nuclear power generation. The second one will implement the modelling chain in context of climate change, based on downscaled IPCC scenarios, and applies the method to two contrasted French nuclear power plants. The modelling framework (power outages modelling bias of +7.0 %) appears as a strong basis for investigating the impact of climate change on nuclear power outages in terms of frequency and magnitude. Such work could inform on the evolving sensitivity of the nuclear fleet to support the energy grid, to potentially optimize its management, and to define water-energy nexus levers to better anticipate the effects of climate change. • Transferable methodology to evaluate the power outages for a nuclear power plant under a hydro-climatic policy scenario. • Improved understanding of nuclear plant sensitivity, considering local constraints. • Ability to assess cumulative sensitivity of current or planned nuclear fleet. [ABSTRACT FROM AUTHOR]

Climate change leads to the frequent occurrence of natural disasters. It has had a severe impact on agricultural economic growth in China. Based on data in China from 2004 to 2020, this paper uses a fixed-effect model to discuss the effects of natural disasters on agricultural economic growth. The empirical results are as follows. (1) Natural disasters negatively affect agricultural economic growth. The regression coefficient of natural disasters on agricultural economic growth is −0.1183. (2) The inhibition of agricultural economic growth by natural disasters is more prominent in areas with low government attention and average agricultural production conditions. (3) The mechanism analysis shows that natural disasters inhibit agricultural economic growth through channels that cause the spread of diseases and pests. (4) Expanding the scale of agricultural insurance can prevent the impact of natural disasters on agricultural economic growth. This research provides policy recommendations for preventing the negative impacts of natural disasters. Agricultural producers should raise awareness of disaster management and improve the accuracy of disaster warning mechanisms. • This paper measures the level of natural disasters in China. • This paper expands the application field of functional data analysis methods. • This paper examines the mechanism of natural disasters affecting agricultural economic growth. • This paper provides policy suggestions for ensuring agricultural economic growth. [ABSTRACT FROM AUTHOR]

Preventing the impact of natural disasters on urban-rural income inequality helps to achieve shared prosperity. This paper uses the functional entropy weight method to calculate the level of natural disasters from 2004 to 2020. Then, this paper discusses the impact of natural disasters on the urban-rural income gap. The empirical results are as follows. (1) Natural disasters have expanded the urban-rural income gap. The regression coefficient is 0.2663, which is significant at the 1% level. (2) In areas with a high proportion of the rural population, the impact of natural disasters is more prominent. (3) Mechanism analysis indicates that natural disasters have widened the urban-rural income gap by restraining rural investment and agricultural production. Finally, this paper suggests strengthening investment in the agricultural sector to mitigate the negative impact of natural disasters. • This paper uses the functional entropy weight method to calculate the level of natural disasters. • This paper quantitatively measures the impact of natural disasters on the urban-rural income gap. • This paper examines the mechanism of the impact of natural disasters on the urban-rural income gap. • This paper provides policy suggestions for narrowing the urban-rural income gap. [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]

CO 2 capture, utilization, and storage (CCUS) are critical technical measures to effectively mitigate the global climate change problem. However, most of the existing research has focused on the capture end and lacks in-depth analysis of subsequent processes such as compression, leading to limitations in the improvement of system economics. Therefore, a novel CCS system for a 300 MW coal-fired power plant was proposed in this paper with two strategies: (1) a CCS system integrating CO 2 refrigeration cycle (CFPP-CCS-CRC); and (2) a CCS co-generation plant integrating CO 2 refrigeration cycle (CHP-CCS-CRC). The proposed systems' performance was comparatively evaluated by applying energy, exergy, and economic (3E) analyses. The results demonstrated that at different CO 2 capture percentages (13.1 %∼72.9 %), the CHP-CCS-CRC system has improved energy utilization efficiency by 1.2 %∼5.6 % and exergy efficiency by 7.7 %∼25.8 %, compared to the conventional CCUS system (CFPP-CCS). In particular, at a percentage of 13.1 %, the combined energy consumption of the CHP-CCS-CRC system was 0.39 GJ/tCO 2 , a 79 % reduction compared to 1.87 GJ/tCO 2 of the CFPP-CCS system, which resulted in a static payback period of less than 2 years. In general, the newly proposed system features more adequate energy utilization, lower operating costs, and higher economic efficiency. [Display omitted] • A novel CCUS system coupled with CO 2 refrigeration were proposed. • The performance of the proposed systems is comparatively evaluated by 3E analysis. • The energy consumption of the proposed CCUS systems is reduced by 29.24 %–79 %. • The exergy efficiency of the proposed CCUS systems is reduced by 7.7 %–25.8 %. • The static payback period for the proposed systems is reduced to less than 2 years. [ABSTRACT FROM AUTHOR]

Abstract Giving policy advice related to climate mitigation requires insights that take both sectoral and technology effects (and their interactions) into account. This paper develops a novel soft-linking method for bridging the gap between sectoral top-down and technology rich bottom-up models. A unique feature of the approach is the explicit modelling of energy service demand in the top-down model, which creates a direct correspondence to the energy service production in the bottom-up model. This correspondence allows us, unlike previous work, to capture the macroeconomic impact of energy system investment flows. The paper illustrates the full-scale application of the method in the Danish IntERACT model, considering the unilateral introduction of coal carbon capture and storage in the Danish concrete sector. The policy leads to a reduction in the Danish concrete production, and in turn, a carbon leakage effect of 88%. Results also underscores the importance of accounting for the macroeconomic impact of energy system investment flows, as this is the source of approximately half of the policy-induced reduction in macroeconomic activity. Highlights • Introduces energy service demands in a computable general equilibrium model. • Identifies a highly consistent method for soft linking a top-down and a bottom-up model. • Highlights the full scale implementation of the method in the Danish IntERACT model. • Demonstrates the impact of energy system investments on the macro economy. • Shows that climate mitigation technologies may lead to significant carbon leakage. [ABSTRACT FROM AUTHOR]

Abstract Addressing environmental concerns alongside economic development and energy transitions is a challenge for all countries and effective policy making requires approaches that can balance all these concerns. In this paper, combining a range of modeling methodologies is proposed as a way of addressing these questions in an integrated manner. The choice of models to be used would depend on the specific characteristics of the system and region being studied. One possible combination of models is discusses in this paper for the specific case of India. The Integrated Modeling Framework (IMF) proposed combines three modeling approaches – i) index decomposition to estimate impacts of structural changes in the economy, ii) constrained optimization to estimate least cost fuel options for the power sector, iii) input-output analysis to estimate economic impacts. The model results indicate that the mode of investment for climate change mitigation is a significant determinant of the impact on economic growth, incomes, and income distribution in India. In some scenarios, higher investments in green energy negatively affects low income households significantly more as compared to other households. The paper also demonstrates how the IMF can be used to determine the reasons for and therefore alleviate the negative impacts. Highlights • An Integrated Modeling Framework (IMF) combining three modeling methods is presented. • IMF built for India, but applicable for other developing countries also. • IMF useful to study balance between energy, environment, economy, and equity. • Negative trade-off between equity and renewable energy transition in some scenarios. • IMF useful for identifying ways to alleviate the negative trade-off. [ABSTRACT FROM AUTHOR]

Abstract Global climate change is a significant environmental problem. A major trigger of climate change is the excess carbon emissions. Based on 44 scenarios in the second generation of new dry cement technology systems, this paper establishes IPSO-BP model to forecast the carbon emissions peak of China's cement industry for 2016–2050 years. The results indicate that China's cement industry only implements capacity reduction plans and the second generation of new dry cement technology systems, so that carbon emissions can reach the peak before 2030. It is up to 19 years ahead of the carbon emissions peak of the basic scenario and the carbon emissions peak is reduced by 38 Mt. Moreover, this paper analyzes the technical combination of the earliest carbon emissions and the lowest carbon emissions. As for the earliest carbon emissions technical combination, China's cement industry carbon emissions will peak at 789.95 Mt in 2021. According to the lowest carbon emissions technical combination, China's cement industry carbon emissions will peak at 742.37 Mt in 2025. Accordingly, the conclusions will be helpful for making carbon emissions reduction policies for China's cement industry. Highlights • Carbon emission levels were reviewed from industrial output and technologies. • The prediction model of carbon emissions was built with improved PSO and BPNN model. • The scenarios were set to analyze carbon emission peak in China's cement industry. • Importance of technique and capacity reduction in China's cement industry is defined. • The best carbon emission peak plan for China's cement industry is discussed. [ABSTRACT FROM AUTHOR]

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage; solar, wind, hydro, green hydrogen, etc.; renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. • The nexus between energy transition, energy poverty and their impacts are investigated. • Influence of climate change, COVID-19, geo-politics, and energy infrastructure on energy transition. • Exhaustive prospects and recommendations are rendered. • Requirement for inclusive investigations and recognition of energy poverty. [ABSTRACT FROM AUTHOR]

Understanding carbon emissions across income levels is vital to limiting global warming to below 1.5 °C and 2 °C, as the Paris Agreement outlines. Unequal emission patterns can affect global remaining carbon budgets, necessitating differentiated strategies. This paper introduces a unique perspective to forecasting carbon emissions and determining the remaining carbon budget relative to income levels and associated socioeconomic factors. Leveraging Pearson correlation analysis and Bayesian-optimised Artificial Neural Network methods, the study examines emissions and carbon budgets of thirty countries, representing 82 % of global carbon emissions in 2022, under a business-as-usual scenario across various income levels. Findings reveal distinct patterns, with high-income countries experiencing declining emissions while middle- and low-income countries anticipate increases. High-income countries are projected to deplete their 2.0 °C budgets later than middle- and low-income countries, with an estimated depletion around 2052 and 2046–2048, respectively. Proposed mitigation and adaptation strategies tailored to income levels include investment in advanced technologies for high-income countries, promoting energy efficiency and renewable energy transition for middle-income countries, and expanding clean energy access for low-income countries. This study advocates the importance of integrating income levels and socioeconomic factors into climate policymaking, offering insights for policymakers, environmentalists, and businesses to tailor interventions and promote equitable climate action. [Display omitted] • Bayesian-optimised ANN methods are used for forecasting across income level. • Forecasted carbon emissions are evaluated against Paris Agreement targets. • High-income nations' future emissions decline; lower-income nations' emissions rise. • Lower-income nations need immediate action due to shorter carbon budget periods. • Mitigation and adaptation strategies are proposed for various income levels. [ABSTRACT FROM AUTHOR]

Combining cost-optimal solutions to reach nearly zero energy buildings (NZEBs) in compliance with European policies is an ongoing challenge. Energy consumption can be reduced evaluating different configurations at the design stage and implementing the most appropriate solutions according to the building and the location. This paper develops a simulation-based optimization framework of cost-optimal choices and energy efficiency measures for new buildings. It combines energy and cost simulations using a sequential search technique to find the most effective combination of energy efficiency and renewable energy measures starting from a base configuration. The model is applied to a residential building prototype, taking into consideration hourly climatic data, construction methods, cost data and energy consumption. A cost database and a library of potential measures, related to envelope, appliances and systems, have been established and used within the optimization process. The potential impact of climate change on the estimated cooling loads has been included in the calculations. The paper shows the feasibility of European requirements for new NZEBs located in different cities. It describes how to best achieve the NZEB design at the lowest cost in 14 locations across Europe. Results highlight how the cost-optimal measures vary with climate and how in each location final selected options differ. Insulation and building tightness appear essential in colder climates, while efficient appliances and lighting are key measures in warmer locations. A key finding of the research is that a source energy reduction of 90% and beyond is feasible for new constructions in all locations. Results also show how efficient lighting and appliances considerably impact the building energy performance. The importance of integrating renewables and energy efficiency measures is confirmed as crucial to reach the NZEBs target. [ABSTRACT FROM AUTHOR]

Wind power and pumped storage combined system (WPCS), as an entity integrates multiple energy sources, can provide a reliable overall power supply by optimizing the management of available resources, helping to combat the serious climate change challenges. In order to address the participation of combination system in multiple market operations and multiple uncertainties, this paper proposes a joint declaration strategy for WPCS to participate in the electricity market (EM) and frequency regulation market (FRM). Firstly, the trading mechanism is developed for WPCS to collaborate in power markets. Secondly, a joint declaration and dispatching strategy decision-making model of WPCS is constructed, and the uncertainty of market prices and wind power output in the model is processed by using the information gap decision theory-distribution robust optimization (IGDT-DRO) technique. Finally, simulations implemented on an actual WPCS are delivered to show that: 1) WPCS achieved an expected profit by 8.79% and decrease deviation penalty costs by 58.81% through multi energy complementary operation. 2) Compared with the single market, WPCS can increase the expected profit by 77.5% in the joint declaration of multi-markets.3) IGDT-DRO technology can simultaneously manage the uncertainty of both price and electricity. When the sample size increases tenfold, the runtime increases by less than 40%, which has advantages in data-driven and stable runtime. [Display omitted] • A synergistic trading mode of electric energy and frequency regulation markets is designed. • A declaration-dispatching strategy for wind power and pumped storage participating in EM andFRM is constructed. • The IGDT-DRO technique is used to deal with the uncertainty of market price and wind power generation. • The characteristics of IGDT-DRO model in data-driven feature, non-conservative result and stable run time have been proved. [ABSTRACT FROM AUTHOR]

Brazil has an energy system with a hydrothermal characteristic that interconnects consumers and generators covering 98% of the demand for energy supplies. Most of the plants are concentrated in the southeast region, where the largest consumers and the largest population concentration are located. The expansion of this system, considering the hydroelectric contributions, will occur exploring the potentials located in the Amazon region. This analysis paper shows that the variations imposed by climate changes on some climatological variables create significant uncertainties about the power generation forecasts of the hydroelectric power plants to be installed in the Amazon, thus compromising the financial economic feasibility of these enterprises and also possibly compromising the expansion plans of the Brazilian energy system. The methodological approach uses information from various climate change scenarios and compares those with historical hydrological patterns and generation information. By exploring the characteristics of a large-scale hydrothermal system with high dependence on water resources, this paper provides valuable insights on how energy policy would address hydroelectric vulnerabilities and climate change. This analysis is focused on the Brazilian case but reveals important issues related to systems with hydro thermal characteristics. [ABSTRACT FROM AUTHOR]

Natural gas (NG), as one fossil fuel with multiple applications, plays a major role in Europe. However, to face global climate change and accelerate the transition to a sustainable society, fossil fuels, such as NG have to be replaced in the long term. The aim of this paper is to evaluate the technical and economic aspects of emerging technology concepts for the production of renewable methane from biomass. Biochemical and thermochemical concepts are considered within the scope of this paper. To evaluate the different conversion technologies an adapted AHP (analytic hierarchy process) was developed, based on two methods AHP and utility value analysis. In total, 99 alternatives (bio- and thermochemical conversion) were evaluated. From the multi-criteria analysis, no single technology pathway was given preference. However, the choice of substrate was found to be a critical factor in comparing the technology options. Within biochemical conversion, organic waste alternatives were favoured, for the thermochemical conversion, residual forest wood. The goal, a comprehensive comparison of two different conversion pathways on a multi-criteria scale, was achieved, and has thus provided added value for the bioeconomy and biorefinery in research and policy aspects. Further, the methodology is expandable and transferable to other criteria and technologies. [ABSTRACT FROM AUTHOR]

This paper delves into the potential impact of a changing climate on the energy performance of European buildings. Research aims to provide a comprehensive evaluation of current energy requirements focusing on the envelope, considering existing regulations in national policies. Energy simulations are conducted at 94 locations across the European Union to cover the climatic variability and Koppen climate classification. The research analyzes future climate scenarios for the years 2030, 2050, and 2070, using three different Representative Concentration Pathways (RCP 2.6, 4.5, 8.5). According to a comprehensive analysis of heating, cooling, and overall energy performance, climate plays a significant role in buildings' energy balance. In moderately cool climate countries, the demand for air conditioning is projected to decrease in the years ahead. Conversely, in countries with a warm climate, there is a projected increase in the overall energy demand. Consequently, a revision of current energy regulations should be a priority. Providing insights into the relation between building design, energy efficiency, and climate change, the research identifies policy adjustments to ensure buildings can effectively respond to changing climatic conditions. A holistic and dynamic approach can support building design accounting for long-term impacts of climate change to create resilient and energy-efficient structures. • National building energy regulations of European Member States do not tackle climate change. • Over next decades, a decrease in heating demand is forecasted across all climate zones. • There is potential for a future considerable increase of cooling demand in Europe. • A reduction in total building energy demand in colder climates and an increase in warmer climates can be expected. • Revise national energy regulations, especially in warmer zones, to curb the expected rise in Europe's total energy demand. [ABSTRACT FROM AUTHOR]

Fifth-generation district heating and cooling (5GDHC) systems have the potential to provide simultaneous heating and cooling, allowing for energy exchange between users with different needs. However, their viability in mild climates with a higher share of cooling demand remains unclear. In this paper, we propose a framework for assessing the engineering, economic and environmental performance of a 5GDHC system compared to a state-of-the-art business-as-usual solution and demonstrate it through a practical case study for a university campus in Melbourne, Australia. When accessible heat sources and sinks are available, the 5GDHC system provides a cost-effective solution, with annual cost savings between 9 and 29 % and GHG emissions reduction between 25 and 58 % compared to an already advanced business-as-usual system. Additionally, by using peak off-peak tariffs and an hourly emission factor for the electricity consumed, we demonstrate the 5GDHC operational flexibility in pursuing different objectives, such as minimising cost or emissions, respectively. The results suggest that 5GDHC systems are an economically and environmentally viable solution in milder climates, and a successful implementation of 5GDHC in Australia can create new market opportunities and pave the way for its adoption in other countries with similar climatic conditions and no established history of district heating systems. • 5GDHC systems are analysed in a new context with a milder climate. • A multi-dimensional assessment framework is proposed. • The framework is demonstrated through a practical case study in Melbourne, Australia. • Flexibility is assessed through varying electricity tariffs and emission factors. • The strong performance of the 5GDHC system offers insights into similar contexts. [ABSTRACT FROM AUTHOR]

In this paper we describe a novel methodology for forecasting in the Swedish–Norwegian el-certificate market, which is a variant of a tradable green certificate scheme. For the forecasting, the el-certificate market is integrated in the electricity-market model EMPS, which has weekly to hourly time-step length, whereas the planning horizon can be several years. Strategies for the certificate inventory are calculated by stochastic dynamic programming, whereas penalty-rates for non-compliance during the annual settlement of certificates are determined endogenously. In the paper the methodology is described, and we show the performance of the model under different cases that can occur in the el-certificate market. The general results correspond to theoretical findings in previous studies for tradable green certificate markets, in particular that price-scenarios spread out in such a way that the unconditional expected value of certificates is relatively stable throughout the planning period. In addition the presented methodologies allows to assess the actual dynamics of the certificate price due to climatic uncertainty. Finally, special cases are indentified where the certificate price becomes excessively high respectively zero, due the design-specific dynamics of the penalty rate. [ABSTRACT FROM AUTHOR]

Accurate forecasting of peak electricity load has long been an active area of research in electricity markets, and power systems planning and operation. Unanticipated climate-induced surges in peak load can lead to supply shortages causing frequent brownouts and blackouts, and large-scale socioeconomic impacts. In this paper, the climate sensitivity of daily peak load is characterized by leveraging advanced statistical machine learning algorithms. More specifically, a rigorously tested and validated predictive model based on the Bayesian additive regression trees algorithm is proposed. Results from this study revealed that maximum daily temperature followed by mean dew point temperature are the most important predictors of the climate-sensitive portion of daily peak load. Among the non-climatic predictors, electricity price was found to have a strong positive association with the daily peak load. Economic growth was observed to have an inverse association with the daily peak load. While the proposed framework is established for the state of Texas, one of the most energy-intensive states with geographic and demographic susceptibility to climatic change, the methodology can be extended to other states/regions. The model can also be used to make short-term predictions of the climate-sensitive portion of daily peak load. • Maximum temperature is the most important predictor of climate-sensitive peak load. • Dew point temperature significantly influences peak load both during summer and winter. • Maximum sustained wind speed lowers daily peak load. • Electricity price has a strong positive association with peak load. • Economic growth of the state is inversely associated with peak load. [ABSTRACT FROM AUTHOR]

In accordance with the Paris Agreement, many nations have set out a global framework to stabilise and prevent greenhouse gas (GHG) emissions to mitigate climate change. This study reviewed the literature on the GHG protection and control (GHGPC) impacts of overburden fractures in relation to coal mining. Different factors, such as geological conditions, mining conditions, and gas extraction methods, were compared because they influence GHGPC. Carbon emissions, coal mining safety, and environmental protection are crucial parameters. GHGPC can (1) improve the safety and efficiency of mining, (2) reduce GHG emissions, and (3) generate clean gas resources. During mining, cracks appear in overburden strata, causing GHG emissions. Various techniques, including scanning electron microscopy, nuclear magnetic resonance, two-dimensional and three-dimensional physical similarity simulations, permeability testing, and numerical simulations, have been adopted to determine the macroscopic and microscopic features of overburden fractures. Finally, the extraction method of GHG was optimised through field practice, namely, roadway, borehole, and pipe extraction, were analysed, and the comprehensive GHG extraction method was preferred to achieve superior management results. This paper reviewed studies that examine the development of fractures to elucidate the significance of GHGPC. Moreover, this article provides new insights into the achievement of the "dual carbon strategy" with particular reference to coal mining; it also summarises the holistic life cycle of gas management in terms of overburden activity, gas transport patterns, reservoir characteristics and typical technologies. It also summarises the holistic life span of GHGPC management in terms of overburden activity, GHG transport patterns, reservoir characteristics, and typical technologies. Finally, the authors discuss and conclude the article with proposed methods for future research directions. • The role of GHGPC in carbon neutrality was talked about from various aspects. • Technologies for GHG transport, extraction, and utilisation were elaborated. • GHG extraction technologies in coal mining were introduced. • New energy supply and the dual carbon strategy in coal mining were described. [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]

Abstract: This paper reviewed the history of the evolution of low-carbon development strategies and the establishment of low-carbon targets in China, over the past 30 years. The climate policy development in China has been classified into four stages and the key strategies of the Chinese government adopted towards low-carbon development were analysed. The results showed the changing view of the government regarding the climate issue, was the underlying reason for the establishment of low-carbon development targets, whilst a low-carbon economy is now receiving increasing attention in the governance of China. Some recommendations for future improvement were given at the end of the paper. [Copyright &y& Elsevier]

Abstract: This paper will summarise the European Strategy for Energy and Climate Change. In current international negotiations Europe has proposed a 20% reduction in GHG (greenhouse gases) in the developed countries by 2020 or 30% should there be an international agreement in the domain. However it is important to define measures to achieve the targets. One of the principal tools is to improve energy efficiency under the energy efficiency action plan, which will help to achieve a 20% energy saving by 2020. On the other hand, the amount of energy from renewable sources consumed in Europe will have to rise from its current level of 8.5%–20% by 2020. These are ambitious but achievable targets. Nonetheless, these can only be achieved through strong investment in areas of the knowledge triangle which strengthens research and innovation in the energy sector in Europe. The paper covers European Energy and Climate Change Policy, the European Strategic Energy Technology plan, the consequences of the Lisbon Treaty, European and national Road maps to a low carbon economy, the Energy Efficiency Plan for 2011 and finishes with a brief consideration of the EU’s energy infrastructure priorities. [Copyright &y& Elsevier]

Seasonal climate variations affect electricity demand, which in turn affects month-to-month electricity planning and operations. Electricity system planning at the monthly timescale can be improved by adapting climate forecasts to estimate electricity demand and utilizing energy models to estimate monthly electricity generation and associated operational costs. The objective of this paper is to develop and test a computationally efficient model that can support seasonal planning while preserving key aspects of system operation over hourly and daily timeframes. To do so, an energy system optimization model is repurposed for seasonal planning using features drawn from a unit commitment model. Different scenarios utilizing a well-known test system are used to evaluate the errors associated with both the repurposed energy system model and an imperfect load forecast. The results show that the energy system optimization model using an imperfect load forecast produces differences in monthly cost and generation levels that are less than 2% compared with a unit commitment model using a perfect load forecast. The enhanced energy system optimization model can be solved approximately 100 times faster than the unit commitment model, making it a suitable tool for future work aimed at evaluating seasonal electricity generation and demand under uncertainty. • An energy system optimization model is repurposed for seasonal planning. • Results are compared with a unit commitment model under two demand forecasts. • The enhanced energy system model can generate results nearly 100 times faster. • This model performance makes it possible to do seasonal planning under uncertainty. [ABSTRACT FROM AUTHOR]

Abstract In recent years, the use of renewable energies has been promoted in most of developed countries due to the climate change threat. In this scenario, the importance of geothermal installations has increased. This paper focuses on a heat exchanger present on a geothermal installation. The main aim is to achieve an accurate prediction system using the previous readings of some of the sensors located along the heat exchanger. Different time series modeling techniques were applied obtaining satisfactory results in the prediction of the heat exchanger state during one year. This prediction is made 1 h, 3 h and 6 h in advance. Also, a strong correlation between the sensor readings is concluded, offering the possibility to dispense some of them. Highlights • The performance prediction of a geothermal heat exchanger can improve its efficiency. • From real measurements, the system is modeled with intelligent techniques. • The models predict the state of the installation up to 6 h in advance. • A strong correlation between different sensors is concluded. [ABSTRACT FROM AUTHOR]

Abstract Due to the growing concerns about global climate change and energy dependence, many countries have introduced regulations targeting the energy efficiency of the residential sector. However, whether these policies have been effective in reducing the total residential consumption of energy is still unclear. In this paper, we analyze the impact of residential energy efficiency policies on household energy consumption across Europe for the period 1980–2016. We examine the electricity and non-electricity energy consumption separately, as these are generally used for different purposes (appliances and heating) by households and are subject to different energy efficiency policies. We focus on two distinct types of regulations – mandatory energy efficiency labels for household appliances and building standards. After controlling for county-specific effects and changes in income, energy prices, demography and climate conditions over our sample period, our results offer compelling evidence that both the energy labeling requirements for appliances and the stricter building codes lead up to lower residential energy consumption. According to our estimation results, we should expect a 0.24% reduction in residential electricity use after governments introduce a mandatory disclosure of energy labels for an appliance group that represent ten percent of households' electricity use. Similarly, given that U-values proxy the thermal quality of the new dwellings, we find that a 0.1 unit decrease in the U-value requirement triggers a lasting 0.28% annual decrease in residential non-electricity energy consumption. These results can help policymakers to shape future regulations targeted on reducing our energy use in the years to come. Highlights • We analyze the impact of energy efficiency policies on households' energy demand. • Electricity demand decreases after the introduction of energy labeling policy. • Stricter building standards lead to a reduction in residential energy demand. • The effects are stronger with higher construction and appliance ownership rates. [ABSTRACT FROM AUTHOR]

Abstract The paper aims to discuss the adaptation of a brazilian social housing project to the Passive House standard, by defining the thermal envelope construction fabric for different climates of southern Brazil, from a base line according to the Brazilian performance standard. The study was developed in 4 steps, where a numerical model was set up and runned in a transient regime, using EnergyPlus® software. In the first step, the thermal and energy performance of the reference base model was assessed. In the second step, a sensitivity analysis was performed, varying the thermal envelope parameters of the building case study, in order to satisfy the minimum performance of the classification level A, according to the Brazilian Energy Efficiency Regulation (RTQ-R). In a third step, the external envelope of the building was optimised, through a multi-objective evolutionary algorithm. In a last step, the numerical model defined according to the Passive House standard was optimised, in order to obtain optimal solutions. Thermal and energy performance and economic viability of the solutions were analysed. Solutions attending to RTQ-R presented additional investment between 26% and 27% and solutions attending to Passive House standard presented additional costs of 39% and 42% for the three bioclimatic zones. Highlights • An optimisation methodology for Passive House design is presented. • An evolutionary multi-objective algorithm is used for thermal building simulation. • Different bioclimatic zones in Brazil are investigated. • Energy performance and thermal comfort of the buildings are significantly improved. • The Passive social interest housing is economically viable for bioclimatic zone 2. [ABSTRACT FROM AUTHOR]

Abstract Ejector cooling with hydrocarbon as alternative refrigerant promises great application potential in hot climate regions. In order to unleash the potential of these sustainable cooling systems, it is essential to design high-performance hydrocarbon ejectors. In this paper, a computational fluid dynamic (CFD) simulation approach is proposed for detailed ejector modeling. The NIST real gas model is used to incorporate thermophysical properties of actual refrigerants for accurate ejector performance prediction. A hydrocarbon ejector performance is analyzed according to different operating and geometric conditions, where a linear relationship between the expansion ratio and the compression ratio is obtained for Pentane with an accuracy of 0.5%. A set of Pareto Frontier performance curves are also recommended for designing and operating energy-efficient hydrocarbon ejector cooling systems. Our results show that a small area ratio leads to a high ejector compression ratio, which is desired in hot climate applications. The other geometric design parameters have minor effects on the ejector performance. This work also indicates that ejectors with a converging-area chamber can achieve better overall performance compared to conventional ejectors. Highlights • Designing high-performance hydrocarbon ejectors for cooling in hot climate regions. • Axisymmetric CFD simulation of ejector with NIST real gas thermophysical properties. • Pentane ejector having a linear relation between its expansion ratio and compression ratio. • Ejector with converging-area chamber performing better than ejector with constant-area section. • Pareto Frontier performance curves recommended for future hydrocarbon ejector cooling applications. [ABSTRACT FROM AUTHOR]

Abstract This paper presents an evaluation of energy supply strategies for Egypt's power sector and identifies prospects to meet rising electricity demand while addressing energy security and low-carbon development issues. We apply the TIMES energy system model to examine Egypt's energy policy goals as reflected in Egypt's Vision 2030 , and specifically: (a) targeted power generation based on renewable energy under two different scenarios; (b) targeted carbon dioxide (CO 2) emissions' mitigation toward low-carbon society development; and (c) constraints on natural gas production for power generation. The quantitative results from the model suggest a need for diversification from predominantly natural gas to a mix of renewable and conventional energy sources in order to improve energy security, reduce dependency on fossil fuels, and reduce carbon dioxide emissions, with the level of diversification changing with different policy options. Although total energy system cost is projected to increase the effects on fossil-fuel dependency, diversity of energy supply-mix, marginal electricity generation price, and GHG mitigation indicate that it may be wise to target promotion of renewable energy for power generation and develop a low-carbon society. Highlights • Egypt energy strategies call for GHG reductions and diversified energy portfolios. • Egypt can diversify from natural gas to a mix-supply to improve energy security. • Enhanced promotion of renewables would reduce fossil fuel dependency by 42% by 2050. • The long-term cost of pursuing renewable technologies is not significantly higher. [ABSTRACT FROM AUTHOR]

Abstract In recognition of the impact of the refrigeration sector on climate change, global commitments are achieved to replace hydrofluorocarbon substances with more planet-friendly alternatives. In this regard, countries with high ambient temperatures (HAT) face additional problems in identifying suitable alternatives due to the impact of such temperatures on energy performance in vapor compression systems. This paper presents an experimental analysis using R134a and two lower global warming potential (GWP) mixtures in a small capacity vapor compression refrigeration system for HAT environments. The range of evaporating and condensing conditions was selected to simulate a refrigeration system working at HAT conditions. The experimental operating results show that although R450A values are acceptable, R513A shows better adaptation to the refrigeration system in terms of pressure ratio, discharge temperature, and mass flow rate. Then, attending to experimental energetic results, R450A energy performance (quantified by COP) and cooling capacity are lower than R513A and R134a. TEWI analysis of a small refrigeration unit shows CO 2 equivalent emission saving when using R450A in the different condensation conditions. However, taking into account the variation of cooling capacity, R513A system results in the lowest TEWI when normalizing per unit of delivered cooling capacity. Highlights • R450A and R513A are analyzed as drop-in replacements to R134a. • Selected middle condensing temperatures are 40, 50 and 60 °C. • R513A and R450A shows proper adaptation to R134a system. • R513A energy performance is comparable to R134a at most conditions. • Normalized TEWI gives better results for R513A. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the integration of renewable electricity into the UK system in 2020. The purpose is to find the optimal wind generation that can be integrated based on total cost of supply. Using EnergyPLAN model and the Department of Energy and Climate Change (DECC) energy projections as inputs, this paper simulates the total cost of electricity supply with various levels of wind generation considering two systems: a reference and an alternative system. The results show that 80 TWh of wind electricity is most preferable in both systems, saving up to 0.9% of total cost when compared to a conventional system without wind electricity production. The alternative system, with decentralized generation and active demand management, brings relatively more cost saving, and higher wind utilisation, compared to the reference case. The sensitivity analysis with alternative fuel and capital costs again confirms the superiority of the alternative over the reference system. [Copyright &y& Elsevier]

Abstract: In previous papers the authors demonstrated that significant energy savings can be achieved in air-conditioning through the use of a hybrid plant in which a vapor-compression inverse cycle is integrated with an air dehumidification system working with hygroscopic solution and hydrophobic membrane. The advantage of this system lies in the fact that the refrigeration device operates at a higher evaporation temperature than that of a traditional system, in which dehumidification is achieved through condensation. In the proposed hybrid system the supplied air is simultaneously cooled and dehumidified in an air–solution membrane contactor. The LiCl solution is cooled by means of a vapor-compression inverse cycle. The solution is regenerated in another membrane contactor by exploiting the exhaust air and the heat rejected by the condenser. The paper reports a study of the steady-state behavior of the system in summer climatic conditions on varying some significant climatic parameters, such as the latent load of the conditioned space and the outdoor and indoor relative humidity. The performances of the hybrid system are compared with those of a traditional direct-expansion air-conditioning plant. Results of the simulations reveal that energy saving may exceed 60% when the latent load in the conditioned environment is high. [Copyright &y& Elsevier]

Abstract: This paper is concerned with modeling possible future paths for Lebanon’s electricity future and evaluating them. The baseline scenario (BS) reflects the business-as-usual state of affairs and thus describes the most likely evolution of the power sector in the absence of any climate change-related or other policies. Two alternative scenarios are examined in contrast to the BS; the renewable energy scenario (RES) and the natural gas scenario (NGS). Using the Long range Energy Alternatives Planning System (LEAP) software we conduct a full-fledged scenario analysis and examine the technical, economic, and environmental implications of all scenarios. From an economic standpoint as well as from an environmental perspective both alternative scenarios are superior to the baseline. Hence, the results of the simulation show that the alternative scenarios are more environmentally and economically attractive than the BS. They would help Lebanon meet its social, environmental, and economic development goals, while at the same time providing other unquantifiable benefits that are discussed further in the paper. Anticipated barriers to the shift in energy mix from conventional sources to renewable energy sources are also presented and discussed [Copyright &y& Elsevier]

Abstract The aim of this paper is to evaluate and compare the techno-economic performance of grid-connected photovoltaic (PV) power systems for a rooftop solar PV building containing 14 families in five climate zones in China. The techno-economic performance of grid-connected PV system in the five regions was evaluated using the HOMER software. Monthly average electric production, economic and environmental considerations, and sensitivity analyses were all considered. The results show that the pollutants from grid-only, grid/PV, and grid/PV/battery systems come mainly in the form of CO 2 emissions. In addition, this study concludes that grid/PV systems are technically, economically and environmentally feasible for all five climate zones. The excess electricity, NPC, and COE values of the grid/PV systems for all five climate zones increased with PV penetration increased, whereas the CO 2 emissions for these climate zones decreased due to the increasing PV sizes. For the grid/PV systems of five climate zones, Kunming is the most economical with the least NPC ($113,382) and COE ($0.073/kWh). The lowest CO 2 (38,975 kg/yr), SO 2 (35.4 kg/yr), and NO x (165 kg/yr) emissions of grid/PV systems occurred in Kunming. From an economic and environmental perspective, Kunming, with its mild climate conditions, may be especially suitable for grid/PV power generation. Highlights • The techno-economic performance of grid/PV system is evaluated using HOMER in five climate zones. • The grid/PV systems are feasible in five climate zones, China. • Kunming is the most economical with the least NPC ($113,382) and COE ($0.073/kWh). • Kunming may be especially suitable for grid/PV power generation. • The grid/PV system is a better choice for all five regions than the other studied systems. [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 Major nuclear accidents are typically low-probability–high-consequence events. This paper focuses on weather and sea-level events that might affect the safety of nuclear power plants (NPPs). Flooding risks at Finnish NPP sites have been re-evaluated based on investigations of long-term changes and short-term variations in sea level, which has led to improvements in the protection against extremely high sea water level. Climate change projections indicated that 1000-year return levels of high enthalpy of the air would increase by 13–27% by 2100. However, no clear future trends were projected for the all-year-round probabilities of freezing rain at the NPP sites. Simulations of the spread of hypothetical radioactive releases during two sea-breeze cases, using weather input data at a remarkably high spatial resolution, demonstrated the impacts of coastal meteorological phenomena on atmospheric dispersion. Overviews of various single and combined weather and marine events that could possibly affect normal NPP operation highlighted the need to broaden the scope of future research. Special attention was focused on various aspects of uncertainty. According to the results, a more extreme weather or marine event corresponded to a larger uncertainty in its probability of occurrence in the changing climate. Highlights • Safe production of nuclear energy requires appraisal of weather and sea-level risks. • Changing climate affects the occurrence of extreme weather and sea-level events. • Land uplift will moderate the increase of flooding risks on the Finnish coast. • Progress in data and methods reveals new potential hazards such as meteotsunamis. • High-resolution meteorological data is vital as input for dispersion modelling. [ABSTRACT FROM AUTHOR]

Abstract This paper performs a multi-model comparison to assess strategies for adaptation to climate change impacts in hydropower generation in Brazil under two Representative Concentration Pathways. The approach used allows for evaluating the interactions between climate change mitigation and adaptation strategies under low and high impact scenarios through 2050. Climate change impact projections of sixteen General Circulation Models indicate that a global high emissions trajectory scenario would likely yield more severe impacts on hydropower generation than a mitigation scenario. Adaptation modeling suggests that climate change impacts can be compensated by a wide range of alternatives, whose optimality will depend on the level of mitigation effort pursued. Our results show that climate change impacts would lead to even higher emissions in the absence of climate change mitigation policies. On the other hand, mitigation strategies to pursue lower emissions are maintained under climate change impacts, meaning that mitigation strategies are robust when faced with adaptation challenges. Mitigation efforts could yield a more diverse and less carbon intensive mix of technological options for adaptation. When analyzing investment costs to adapt to climate change impacts, in some cases mitigation can lead to a lower total investment level. Highlights • Climate change impacts on hydropower are assessed for sixteen models and two scenarios. • Interactions between climate change mitigation and adaptation are analyzed. • Adaptation/mitigation strategies from six different energy models are compared. • Adaptation and mitigation investment costs are assessed and compared. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the relationship among carbon dioxide emissions, economic growth and electricity consumption in the presence of two other variables which are trade openness and annual average temperature. The study uses data of four selected North- African countries over the period 1971–2014. We use the Autoregressive Distributed Lag Cointegration approach (ARDL) known as the Bounds approach. The obtained results confirm the existence of long run equilibrium among the studied variables. The long run analysis reveals that economic growth and electricity consumption are the main cause of environment degradation, while the increased temperature over the year leads to increase electricity consumption in Egypt and Morocco. On the other hand, the analysis of short run causalities confirms the growth hypothesis in these two countries. Furthermore, the feedback relationship between economic growth and electricity consumption has been confirmed in Tunisia. These findings imply that environmental and economic corrective measures have to be adopted to achieve green growth and sustainable development. Highlights • The economic growth in North-Africa region is accompanied by an increased electricity use. • Energy consumption and economic growth are the main sources of CO2 emissions. • Climate change appears to be a significant factor that determines electricity consumption in the region. • North- African countries should investing in renewable energy field to achieve sustainable development. [ABSTRACT FROM AUTHOR]

This paper presents a model of a natural draft wet type cooling tower, which is based on the conservation laws of thermodynamics. The model assesses the cooling abilities of a tower, the evaporation rate, and the amount of required make-up water, all represented as a function of the atmospheric conditions. The purpose of the model is to estimate the effects of extreme weather conditions on the thermodynamic efficiency of a natural draft wet type cooling tower. World climate is changing and average temperatures are anticipated to rise in the near future, thus affecting the electrical energy generation. To that aim, we study the climate change effects on the ability of natural draft wet type cooling towers to reject heat and hence on the electricity generation of thermal power plants. Additionally, we perform cost-based analyses of a cooling tower considering the long-term projections for air temperature increase, and exemplify our model with reference to a location in France. The results show a remarkable drop in the cooling tower efficiency, and, hence, significant electricity generation losses even when a small increase of atmospheric temperature above the cooling tower design temperature occurs. Furthermore, the results of the cost-based analysis show that large electricity losses are expected. However, the performed cost-based analyses, considering climate change projections, show that even with the highest temperature increase, there is no need for additional tower height. In other words, the concrete costs outweigh the generated revenues from the curtailed power as result of insufficient cooling. [ABSTRACT FROM AUTHOR]

Abstract: Heavily (about 99%) depending on imported energy, Taiwan, a country in the subtropics, has limited natural resources. In this regard, biomass energy from (MSW) municipal solid waste incineration plants thus became attractive during the 1990s. The objective of this paper is to present a comprehensive analysis of MSW-to-energy in Taiwan. This paper gave a concise summary of current status of domestic energy consumption & power generation, MSW generation & MSW incineration treatment, and electricity generation from MSW incineration plants since 2000. Based on the electricity generation in 2008 (i.e., 2967 GWh), the environmental benefit of mitigating CO2 emissions and the economic benefit of selling electricity were preliminarily calculated to be around 1.9 × 106 tons and US$ 1.5 × 108, respectively. However, since the heat content of incinerated MSW and the methodologies were used on the recommendation of the (IPCC) Intergovernmental Panel on Climate Change, the net emissions of CO2 equivalent from methane (CH4) & nitrous oxide (N2O) have been estimated to be at around 76,000 and 88,000 tons/year compared to coal and oil, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Coal is the abundant domestic energy resource in India and is projected to remain so in future under a business-as-usual scenario. Using domestic coal mitigates national energy security risks. However coal use exacerbates global climate change. Under a strict climate change regime, coal use is projected to decline in future. However this would increase imports of energy sources like natural gas (NG) and nuclear and consequent energy security risks for India. The paper shows that carbon dioxide (CO2) capture and storage (CCS) can mitigate CO2 emissions from coal-based large point source (LPS) clusters and therefore would play a key role in mitigating both energy security risks for India and global climate change risks. This paper estimates future CO2 emission projections from LPS in India, identifies the potential CO2 storage types at aggregate level and matches the two into the future using Asia-Pacific Integrated Model (AIM/Local model) with a Geographical Information System (GIS) interface. The paper argues that clustering LPS that are close to potential storage sites could provide reasonable economic opportunities for CCS in future if storage sites of different types are further explored and found to have adequate capacity. The paper also indicates possible LPS locations to utilize CCS opportunities economically in future, especially since India is projected to add over 220,000MW of thermal power generation capacity by 2030. [Copyright &y& Elsevier]

Abstract: India''s energy challenges are multi-pronged. They are manifested through growing demand for modern energy carriers, a fossil fuel dominated energy system facing a severe resource crunch, the need for creating access to quality energy for the large section of deprived population, vulnerable energy security, local and global pollution regimes and the need for sustaining economic development. Renewable energy is considered as one of the most promising alternatives. Recognizing this potential, India has been implementing one of the largest renewable energy programmes in the world. Among the renewable energy technologies, bioenergy has a large diverse portfolio including efficient biomass stoves, biogas, biomass combustion and gasification and process heat and liquid fuels. India has also formulated and implemented a number of innovative policies and programmes to promote bioenergy technologies. However, according to some preliminary studies, the success rate is marginal compared to the potential available. This limited success is a clear indicator of the need for a serious reassessment of the bioenergy programme. Further, a realization of the need for adopting a sustainable energy path to address the above challenges will be the guiding force in this reassessment. In this paper an attempt is made to consider the potential of bioenergy to meet the rural energy needs: (1) biomass combustion and gasification for electricity; (2) biomethanation for cooking energy (gas) and electricity; and (3) efficient wood-burning devices for cooking. The paper focuses on analysing the effectiveness of bioenergy in creating this rural energy access and its sustainability in the long run through assessing: the demand for bioenergy and potential that could be created; technologies, status of commercialization and technology transfer and dissemination in India; economic and environmental performance and impacts; bioenergy policies, regulatory measures and barrier analysis. The whole assessment aims at presenting bioenergy as an integral part of a sustainable energy strategy for India. The results show that bioenergy technology (BET) alternatives compare favourably with the conventional ones. The cost comparisons show that the unit costs of BET alternatives are in the range of 15–187% of the conventional alternatives. The climate change benefits in terms of carbon emission reductions are to the tune of 110T C per year provided the available potential of BETs are utilized. [Copyright &y& Elsevier]

Abstract: This paper describes the development of the Energy and Climate Policy and Scenario Evaluation (ECLIPSE) model—a flexible integrated assessment tool for energy and climate change policy and scenario assessment. This tool builds on earlier efforts to link top-down and bottom-up models, and combines a macroeconomic energy demand model and a consumer-budget transport demand model with the technology-rich bottom-up energy and transport system model Energy Research and Investment Strategy (ERIS), and solves the models iteratively. Compared to previous efforts, ECLIPSE includes many new features, such as a more disaggregated production function, improved calibration and parameterization and separate modeling of passenger transport demand. The separate modeling of transportation makes ECLIPSE particularly well-suited to analyzing interactions between the transport sector and the broader energy market and economy. This paper presents results illustrating some features of the integrated model, compares technology deployment results with ECLIPSE and the bottom-up ERIS model, and briefly describes illustrative baseline and greenhouse gas mitigation scenarios to highlight some of the features of the framework outlined in this paper. A number of modeling and policy insights arising from this scenario analysis are discussed. [Copyright &y& Elsevier]

Abstract: Climate change response, including the implementation of the Kyoto targets as the first step, calls for technological innovation of future sustainable energy systems. Based on the Danish case, this paper evaluates the type of technological change necessary. During a period of 30 years, Denmark managed to stabilize primary energy supply, and CO2 emissions decreased by 10%, during a period of 20 years. However, after the introduction of the Kyoto Mechanisms, Denmark has changed its strategy. Instead of continuing the domestic CO2 emission controls, Denmark plans to buy CO2 reductions in other countries. Consequently, the innovative technological development has changed. This paper evaluates the character of such change and makes preliminary recommendations for policies to encourage the use of the Kyoto Mechanisms as an acceleration of the necessary technological innovation. [Copyright &y& Elsevier]

Abstract: This paper provides an overview of the evolving climate-change strategies put in place by industrialized countries to combat climate change and to comply with their quantitative commitments under the Kyoto Protocol. It links past policy performance with the historical level of greenhouse-gas emissions and with indicators of policy performance, such as energy intensity and carbon intensity, between 1990 and 2000. It presents the emerging new and integrated method of climate-policy formulation and implementation based on a portfolio approach, where a mix of policies and measures are selected to help achieve the required emissions reduction. The paper outlines the portfolios of policy instruments used by the industrialized countries in their evolving climate-change strategies and in their approach to widening the scope and increasing the coverage of those policy instruments to all sectors and all gases. [Copyright &y& Elsevier]

Marine renewable energies can play a key role by reducing the dependency on fossil fuels and, therefore, mitigating climate change. Among them, it is expected that wave energy will experience rapid growth in the upcoming decades. Thus, it is important to know how wave climate will change and how suitable the wave energy converters (WECs) will be to the new wave conditions. This paper aims to evaluate the capability of four different WECs—a WaveRoller type device (WRTD), Atargis, AquaBuoy and RM5—to extract wave energy on the Northwest coast of Spain (NWCS). The analysis was performed using the high-resolution wave data obtained from the Simulating Waves Nearshore (SWAN) model over the near future winters (2026–2045). The energy output (P E), the power load factor (ε), the normalized capture width (NC w) and the operational time (OT) were analyzed. According to these parameters, among the devices that work for intermediate-deep waters, Atargis would be the best option (P E = 1400 ± 56 kW, ε = 55.4 ± 2.2%, NC w = 35.5 ± 4.1% and OT = 84.5 ± 3.3%). The WRTD would also be a good option for shallow nearshore areas with P E = 427 ± 248 kW, ε = 12.8 ± 7.4%, NC w = 48.9 ± 9.6% and OT = 88.7 ± 18.9%. A combination of Atargis and WRTDs is proposed to make up the future wave energy farms on the NWCS. • Dynamical downscaling using SWAN to simulate near-shore wave conditions. • Wave energy converters suitability is analyzed in the context of climate change. • Atargis is the most suitable device to future sea conditions in intermediate waters. • WaveRoller type devices can constitute future wave farms for shallow waters. [ABSTRACT FROM AUTHOR]

The complicated interrelationship between water and energy makes the water-energy dilemma a complex challenge to be tackled, especially considering the tradeoffs among decision-makers at different hierarchical levels and multiple uncertainties derived from climate change, socio-economic development, technical improvement and decision-making preferences. Thus, a water-energy nexus planning framework would be established in this paper to assist optimal decision-making with bi-level programming and multi-uncertainty. By integrating the regional climate model, multiple linear regression, and bi-level interval flexible programming, an integrated prediction optimization model would be developed as the core of the water-energy nexus planning framework. Then it is applied to planning Zhengzhou City over fifteen years. Multiple scenarios based on electricity demand-supply and carbon dioxide emission satisfaction degrees are analyzed leading to the results of (1) compared to the conventional single-level optimization method, the developed model can achieve the hierarchical goals of water saving and economic suitability; (2) renewable energy will be largely developed and its ratio to electricity generation will reach [26.30, 27.51] % under the limited water availability. Overall, the proposed water-energy nexus planning framework can achieve a balanced water-energy dilemma considering bi-level decision-making preferences and multi-uncertainties, which can be applied to planning water-energy nexus systems at a similar scale. • Regional climate model is used for predicting future electricity demands. • The proposed model addresses bi-level and multi-uncertainty. • Water-energy dilemma towards two different hierarchical levels is assessed. • Optimal solutions provide insights for managing similar scale studies. [ABSTRACT FROM AUTHOR]

This paper assesses the potential effects on the U.S. economy if the U.S. retreats from its pledge to reduce greenhouse gas emissions agreed under the Paris Agreement. We assume prior to withdrawal that the U.S. and other nations or regions would introduce climate change policies, such as emissions trading schemes, to meet their emission targets which were agreed in Paris. When the U.S. withdraws from the Paris Agreement, it will not adopt such a policy. We use a modified version of the GTAP-E model to examine the effects on the U.S. economy of its anti-mitigation action in a counterfactual framework. The findings suggest that a retreat from the Paris Agreement would increase the real GDP and real private consumption by 1.13% and 0.78%, respectively, in the U.S. Given such improvements at the macro level, the effects on the U.S. energy sectors from the withdrawal are substantial. Prices of energy would reduce considerably, particularly for coal, natural gas, and consequently the price of electricity (−17.8%). These three energy sectors would also experience considerable expansions when the U.S. withdraws from the Paris Agreement compared to its position if it honored its previously pledged committed targets. [ABSTRACT FROM AUTHOR]

Geoengineering methods based on either direct carbon dioxide removal (CDR) from the atmosphere or solar radiation management (SRM) that curtails solar irradiation are campaigned for as technical solutions that would slow down the global temperature rise and climate change. Except for a few CDR methods, this does not receive much interest from policy-makers as a result of a lack of evidence on net advantages and decision-making challenges related to boundary-crossing effects, not to mention costs. An alternative, third geoengineering approach would be enhanced cooling by thermal radiation from the Earth's surface into space. The so-called atmospheric window, the 8–14 μm bandwidth where the atmosphere is transparent for thermal radiation indeed offers a “window of opportunity” for technology that enables sending out thermal radiation at rates that significantly exceed the natural process. This paper describes work that addresses this, with focus on technical devices that combine materials with the properties required for enhanced long wavelength (LW) thermal radiation heat transfer from Earth to space, through the atmospheric window. One example is a skylight (roof window) developed and tested at our institute, using ZnS windows and HFC-type gas (performing better than CO 2 or NH 3 ). Suggestions for several other system layouts are given. [ABSTRACT FROM AUTHOR]

Wind resource in China is abundant due to its vast land mass and long coastline. Based on wind speed and direction records from wind measurement towers at six onshore sites with different geographical climate conditions in China, statistical assessment of wind characteristics and wind energy potential at height of 70 m corresponding to the hub heights of multi-megawatt wind turbines is presented and discussed in this paper. First of all, the Weibull distribution function is verified to be a reliable model for wind speed prediction and the moment method is proved to be an accurate approach for estimation of the Weibull parameters at all the sites. Moreover, the variations of mean wind speed, the Weibull parameters and wind power density at the six sites are investigated in terms of seasonal, monthly and diurnal time scales. Finally, annual energy outputs at the six sites are determined by taking a commercial wind turbine as an example to evaluate the economic feasibility of wind energy development. The results of this study indicate that the six sites in North China, Northeast China, Central China, coastal regions in East China and Southeast China are in rich wind energy areas which are suitable for wind energy utilization. In particular, among the six sites, Tongliao in North China is the most promising location for wind energy development with the maximum annual energy output of 10.33 GWh. The objective of this study is to provide useful information for wind energy development and an effective approach for wind energy potential assessment. [ABSTRACT FROM AUTHOR]