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The pulp and paper industry is a high energy consuming and polluting sector, and carbon emissions emitted from this sector are worthy of attention. This article, based upon an analysis of China’s Pulp and Paper Industry (CPPI), provides estimates of each of the following: carbon emissions from energy consumption, pre-treatment sector, combustion of condensed black liquor, and methane emitted from incomplete aerobic digestion during sewage treatment of CPPI. During the study period (2005–2012), total CO 2 emissions ranged from 126.0 Mt to 155.4 Mt. Energy consumption was estimated to be the largest source of carbon emissions, however, due to the application of the local emission inventory rather than the IPCC inventory, energy consumption decreased by 4.7%, a lower percentage than was calculated in a previous study. According to this study’s estimation, the emissions caused by the recovery of biomass energy contributed 26–29% of the total CO 2 emissions. CH 4 generated from sewage treatment accounted for 9–11% of the total carbon emissions. The CO 2 intensity dropped during the study period, which reflected the improvement of energy efficiency in the pulp and paper industry. The outcome of this study provides not only detailed information about CPPI’s carbon emissions, but also a calculation framework for studying carbon emissions from pulp and paper sector in the other regions. It suggests that the local carbon emissions inventory should be used for estimating carbon emissions and to reduce the fossil fuel energy, increase energy recovery from biomass, and that promoting cleaner production is essential to achieve a low carbon development of the pulp and paper industry. [ABSTRACT FROM AUTHOR]

The objective of this paper is to explore how environmental protection expenditures (EPE) affect innovation and investigate the potential causal relationship between the two variables. The novelty and main contribution of our paper to the literature stems from the fact that we look at total environmental protection expenditures from both the public and private sectors, and distinguishing between corporations and households in the private sectors. We also consider both inputs and outputs of innovation and address potential endogeneity issues in this relationship, which are both lacking in the current literature. Using a panel of EU countries over the period 2006–2020, this study generally finds a positive impact of EPE on innovation after controlling for the effects of trade, credit, education and inflation on innovation, and using the System GMM estimator to treat endogeneity. Moreover, EPE from the government sector drives the bulk of this positive impact. The core results are robust to alternative measures of innovation, alternative estimation techniques that address endogeneity (i.e., the Lewbel 2SLS, Mundlak, and Hausman-Taylor estimators) and the moderation effects of Climate Change Performance (CCPI). This study also provides a useful guide to policy makers engaged in environmental planning. • We evaluate the impact of environmental protection expenditures (EPE) on innovation in mainly EU countries. • We use longitudinal dataset for the group of EU countries over the period 2006–2020. • We find a positive impact of EPE on innovation. • The results are robust for observable heterogeneity, alternative measures of innovation and estimation techniques. • This study provides a useful guide to policy makers engaged in environmental planning. [ABSTRACT FROM AUTHOR]

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation's energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events. [Display omitted] • A systematic summer droughts generating capacity assessment framework is developed. • Capacity derating models for various generation technologies are presented. • The impacts of summer droughts on generating fleet in PJM and SERC are studied. • Impact of extreme summer drought on usable capacity of generators is significant. [ABSTRACT FROM AUTHOR]

Reducing the dependence on traditional energy sources and shifting towards the utilization of renewable energy sources (RES) of energy in the maritime sector is imperative for reducing greenhouse gas emissions. Inherently, RES sources like solar and wind are intermittent and variable, resulting in inconsistent power availability and hence leading to energy supply fluctuations and potential shortages. In this respect, an efficient control strategy to maintain system stability and address intermittency effectively is essential. This work considers a hybrid marine microgrid with various energy sources like photovoltaics (PV), wind energy conversion system (WECS), marine biodiesel generator, Archimedes wave power generation, solid oxide fuel cell, and batteries. A 2-degree of freedom (2DOF) structure is designed and implemented with the tilt-integral-derivative filter (TIDN) to address frequency variations. Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. The stability of the proposed microgrid system is assessed under various combinations of RES availabilities, including real-time data from WECS and PV. The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. Simulation results obtained show that the AOA-based 2DOF-TIDN control strategy achieves shorter settling times in mitigating the changes of marine microgrid systems under different dynamic conditions as compared to the other algorithms. Finally, the controller being proposed in this paper was tested for robustness with parameter deviations of +25%, −20%, and − 40% from the nominal values, and proved to be the proposed 2DOF-TIDN controller parameters demonstrate significant robustness in effectively managing the uncertainties and parametric variations. • Maritime Microgrid system is designed for investigations with RE & storage units. • PV, Wind, MBG, AWPG, SOFC, and battery storage units are considered. • 2DOF-TIDN controller is developed to mitigate the changes in the system. • The AOA method is proposed for optimal gains of the 2DOF-TIDN under uncertainties. • Sensitivity analysis, Time delay analysis, and stability analysis are performed [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs. • We generate climate change-informed load and renewable energy production profiles. • We extend a design-and-dispatch problem to a two-stage stochastic program. • Cases with high variation in annual renewable output show the methodology's value. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Comparing alternative fuels with potential for low-carbon intensities. • Technical process design and economic assessment of hydrogen and CO 2 -based fuels. • Environmental life-cycle assessment considering the full carbon cycle. • Identification of methodological challenges in carbon accounting of CO 2 -fuels. Abstract The deployment of low-emission alternative fuels is crucial to decarbonise the transport sector. A number of alternatives like hydrogen or dimethyl ether/methanol synthesised using CO 2 as feedstock for fuel production (hereafter refer to "CO 2 -based fuels") have been proposed to combat climate change. However, the decarbonisation potential of CO 2 -based fuels is under debate because CO 2 is re-emitted to the atmosphere when the fuel is combusted; and the majority of hydrogen still relies on fossil resources, which makes its prospects of being a low-carbon fuel dependent on its manufacturing process. First, this paper investigates the relative economic and environmental performance of hydrogen (produced from conventional steam methane reforming and produced via electrolysis using renewable energy), and CO 2 -based fuels (dimethyl ether and methanol), considering the full carbon cycle. The results reveal that hydrogen produced from steam methane reforming is the most economical option and that hydrogen produced via electrolysis using renewables has the best environmental profile. Whereas the idea of CO 2 -based fuels has recently gained much interest, it has for the foreseeable future rather limited practical relevance since there is no favourable combination of cost and environmental performance. This will only change in the long run and requires that CO 2 is of non-fossil origin, i.e. from biomass combustion or captured from air. Second, this paper address unresolved methodological issues in the assessment of CO 2 -based fuels, such as the possible allocation of emissions to the different sectors involved. The outcomes indicate that implementing different allocation approaches substantially influences the carbon footprint of CO 2 -based fuels. To avoid allocation issues, expanding the boundaries including the entire system and is therefore recommended. [ABSTRACT FROM AUTHOR]

Highlights • Experiments on the absorption process in common absorbers are presented. • Absorption mass fluxes obtained by using different heat and mass transfer intensification techniques are identified. • The use of additives provides the highest mass transfer enhancements in comparison to the other techniques. • Mechanisms for mass transfer enhancement by using nanofluids are discussed. Abstract The absorption cooling/heating system is an old technology that has been relegated by the more efficient mechanical vapour compression systems. However, if they were driven by residual heat or solar thermal energy, advanced absorption technologies for cooling or heating could supply current demand and have a much lesser impact on the environment. With the cost of electricity rising and the climate change more and more in evidence, it would be a positive move towards energy saving. Since the absorber is recognized the key component of the absorption system due to the complex heat and mass transfer process that take place there, the improvement of the absorption process would mean reducing the absorber and desorber sizes to make them more compact, or reducing the system driving temperature for low grade temperature applications. The objective of this paper is to identify, summarize, and review the experimental studies dealing with the enhancement of vapour absorption processes in absorbers by means of passive techniques i.e. advanced surface designs and the use of additives and nanofluids. This review also includes an exhaustive and detailed scrutiny on absorption processes in falling film, spray and bubble mode absorbers for different working fluids, evidencing the experimenting techniques, operating conditions, and latest advances in terms of heat and mass transfer enhancement in absorbers. Finally, the paper contains suggestions for future work to be carried out to obtain mass transfer enhancement in absorbers and absorption cooling/heating systems. [ABSTRACT FROM AUTHOR]

This paper explore the benefits of a bottom-up spatially enabled engineering building-based energy framework in identifying neighbourhoods, and community’s building aggregated areas with spatial patterns. We argue that an area-based approach allows more houses to be targeted in places where local area characteristics show inefficient elements, and may therefore potentially capture a greater number of households per unit of cost, compared to the existing self-referral methods. We propose a spatial method to show the extent of building envelopes, heating systems and temperature controls. Heating controls, which are not recorded in the United Kingdom Homes Energy Efficiency Database (HEED), but we believe would be considered good practice to maintain balanced temperatures around the house, and also potentially reduce the complexity in modelling the thermal zones. Additionally, heating controls are seen as compulsory in new building regulations, an eligible measure in Green Deal and Energy Company Obligations, and in the United Kingdom Department of Energy and Climate Change (DECC) heat strategy. This paper has taught us that the emerging picture surrounding local energy modelling and that, for example, singularities such as group heating and district heating (decentralised energy supply) have a great impact on final energy consumption calculations. [ABSTRACT FROM AUTHOR]

In light of the global energy and climate crises, integration of low-carbon technologies into energy systems is being considered to mitigate the high energy costs and carbon footprint. The wide range of available capacities, efficiencies, and investment costs of these technologies and their different possible operating schedules can unlock several pathways towards decarbonisation. This paper presents an optimisation framework for a public healthcare facility to determine the optimal operation schedule of the site's energy system. A detailed techno-economic analysis of low-carbon power generation, conversion, and energy storage technologies that can be incorporated into the system based on real historical data was carried out for different scenarios. The results reveal that a heat pump with a capacity of 1800 kW can replace gas boilers on-site to meet the heat demand while recovering the investment in 5 years and providing an operating and carbon cost saving of 22.47% compared to the base case. The analysis shows that a more electrified mode of operation is favoured during high gas prices, thus making electrical energy storage more attractive than thermal energy storage. While handling real data, the optimisation algorithm was sensitised to discriminate conventional energy supplies from clean energy sources by considering their carbon impact so that it minimises energy bills in a smart and eco-friendly way. The optimisation algorithm and the subsequent techno-economic analysis provide a comprehensive framework to decision-makers for facilitating energy investment decisions. The framework can be used based on the short and long term goals of the energy system, visualising the evolution of financial benefits over equipment lifetime, and understanding the environmental impacts of integrating renewable energy. • Heat pumps are the most favourable decarbonisation technology for the hospital. • The moderate variations in energy demand limit the scope of energy storage. • Fuel price surcharge favours EES over TES and reduces payback period of retrofits. • PVT's savings scale linearly with roof space until 3 times the available capacity. • Monetising the carbon footprint shortens the DPP of clean retrofit technologies. [ABSTRACT FROM AUTHOR]

Negative emissions systems differ from net-zero systems by deploying significantly more negative emission technologies. The emerging literature on negative emission power systems assumes straight transition pathways from the present systems to final negative emissions systems. Such straight transition paths are unlikely, as deployment of negative emission technologies such as direct air capture might occur via crash course to respond to climate crises and utilities are investing towards net-zero systems instead of negative emissions systems. In this paper, to inform policymakers of the different outcomes of planning for negative emissions systems at different timelines, we quantify the value of planning for a negative emissions power system beginning now versus after achieving a net-zero emissions system in 2050. We apply a macro-scale capacity expansion planning model to the Eastern Interconnection power system to quantify the technological deployments and cost consequences of these two decarbonization pathways to reach a negative emission power system. We find advanced planning for a negative emissions system favors more deployment of storage technologies, which increases system flexibility and allows for better utilization of renewable generation to reduce investments in other technologies, including transmission lines. This change in distribution of investments across technologies leads to small annual cost saving of $6 billion, or 1%. We also find that further delay in planning for a negative emission system after reaching net-zero by 5, 10, and 15 years could significantly increase total system cost by 29%, 35%, and 41% respectively due to higher deployment of negative emission technologies. Our results indicate that, given small annual cost saving from advanced planning for a negative emission power system, economically utilities are on the right path in planning for a net-zero power system by 2050. However, planning should not be delayed further after reaching net-zero to avoid missing cumulative emission targets or significant cost consequences. • We compare negative emissions Eastern power system planned now versus after net-zero. • Advanced planning increases system flexibility by increasing storage deployments. • Advanced planning reduces investments in non-storage technologies. • Advanced planning reduces total annual system cost by $6 billion (1%) across scenarios. • Delayed planning for a negative emission system after net-zero incurs significant costs. [ABSTRACT FROM AUTHOR]

The future of energy flexibility in microgrids (MGs) is steering towards a highly granular control of the end-user customers. This calls for more highly accurate uncertainty forecasting and optimal management of risk and flexibility options. This paper presents a novel data-driven model to optimize the operation of MGs based on a risk-averse flexi-intelligent energy management system (RFEMS), considering the rising challenge of global climate change. It considers the presence of renewables, a diesel generator, and flexibility resources (FRs) containing a demand response program (DRP), distributed electric vehicles (EVs), and electric springs (ESs). In the first phase, the proposed model, by means of a novel hybrid deep-learning (DL) model, forecasts uncertain parameters associated with wind and solar generations, load demand, and day-ahead energy market price. The architecture of the proposed hybrid forecasting model is composed of several stacked restricted Boltzmann machines and a cascade neural network. In the second phase, the MG operator (MGO), based on the obtained uncertainty forecasting results, in the context of a hybrid risk-controlling model, optimizes the MG operation using the provided demand-side flexibility. The proposed optimization problem is linearized stochastic programming with robust concepts, subject to AC optimal power flow constraints, MG flexibility restrictions, and operating limits of local resources. Finally, the efficiency of the proposed RFEMS by using real German datasets on a 33-bus test MG is analyzed. Numerical results demonstrate the superior performance of the proposed forecasting model over several hybrid DL models. In particular, the root mean square error (RMSE) index for wind, solar, load, and price forecasting is improved by 53.35%, 73.24%, 80.24%, and 58.1%, respectively. Further analysis of the proposed RFEMS reveals that operating indices in two 33-bus and 69-bus test networks are significantly improved. It paves pathways to risk-averse, flexible, and economic operation of smart active distribution networks. [Display omitted] • A data-driven model is proposed to optimize microgrids' operation. • A hybrid deep-learning model is proposed to forecast uncertain parameters. • Uncertain parameters include wind and solar generations, load, and energy price. • The forecasting is composed of Boltzmann machines and cascade neural network • Hybrid stochastic/robust optimization is proposed to handle uncertainty. [ABSTRACT FROM AUTHOR]

This paper assesses the separation of CO 2 from ambient air from a technical and economic standpoint. Reducing CO 2 emissions and their sequestration from the atmosphere is vital to counteract ongoing climate change. The most promising technological options for CO 2 separation are first identified by reviewing the literature and comparing the most important technical and economic parameters. The results point to amines/imines as adsorbing agents to separate CO 2 from ambient air. A system layout is then designed and a technical analysis conducted by solving mass and energy balances for each component. An economic analysis is then performed by applying a specifically-developed model. The total energy demand of the system discussed here is calculated as 3.65 GJ/t CO2 . This high energy demand mainly derives from the system-specific implementation of two compressors that compress air/CO 2 and overcome the pressure losses. The second-law efficiency calculated ranges of 7.52–11.83 %, depending on the option of heat integration. The costs of avoiding CO 2 emissions vary between $ 824 and 1333/t CO2 , depending on the energy source applied. The results of this work present higher values for energy demand and costs compared to other values stated in literature. The reasons for this deviation are often insufficient and overoptimistic assumptions in other literature on the one hand, but also relate to the specific system design investigated in this paper on the other. Further case studies reveal that enormous land requirements and investments would be needed to reduce potential CO 2 quantities in the atmosphere to contemporary levels. A comparison between CO 2 removal from the atmosphere and carbon capture and storage technology for coal power plants shows that this technology is not yet able to economically compete with carbon capture and storage. Furthermore, the impact of CO 2 separation on the production costs of industrial commodities like cement and steel demonstrates that CO 2 removal from the atmosphere is not yet a viable alternative to solving the climate change problem. In the long-term, CO 2 separation from ambient air may still play an important role in the sequestration of CO 2 from diluted and dispersed sources, as the technology has the potential for significant further development and optimization. [ABSTRACT FROM AUTHOR]

The scientific and policy relevance of the water-energy nexus in the power system is expected to increase in the future due to climate changes. The operation of the power system is constrained by the availability of water resources, which are necessary for hydropower generation and cooling thermal power plants. At the same time, water availability for non-energy purposes is affected by the power system requirements. In order to analyse this complex interdependency, this paper proposes an interdisciplinary modelling framework including the link of a hydrological model (LISFLOOD) and a power system model (Dispa-SET) within the WATERFLEX project, which aims at assessing the potential of hydropower as a source of flexibility to the European power system, as well as analysing the water-energy nexus against the background of the European Union initiatives towards a low-carbon energy system. Specifically, this paper focuses on the power system model used in WATERFLEX, which encompasses a medium-term hydrothermal coordination model (Dispa-SET MTHC) and a unit commitment and dispatch model (Dispa-SET UCD). The proposed approach is applied to the Greek power system to analyse the implications of different hydrological historical scenarios on the power system operation and economics, as well as the effect of the power system operation on the water availability. For this case study, this paper quantifies the generation costs, the environmental impacts, the water consumptions and withdrawals, as well as the water stress at different power plant locations throughout a year. [ABSTRACT FROM AUTHOR]

The life cycle assessment (LCA) methodology is increasingly used to ensure environmental sustainability of emerging biofuels. However, LCA studies are usually not performed at the process design stage, when it would be more efficient to identify and control environmental aspects. Moreover, the long-term economic profitability of biofuels depends on future energy and climate policies, which are usually not considered in techno-economic feasibility studies. This paper combines the LCA method and a TIMES energy system model, to offer a simultaneous assessment of potential environmental impacts and market penetration under different energy and climate policy scenarios of emerging energy pathways. This combined approach is applied to butanol produced from pre-hydrolysate in a Canadian Kraft dissolving pulp mill. Indeed, the integration of biorefinery processes into existing pulp and paper mills has been identified as a promising avenue to maintain mills activities. It could increase and diversify revenues, keep the forestry-based communities alive, and potentially mitigate climate change by replacing fossil-based fuels or products. Results show that (1) the energy efficiency of the butanol production process is a critical aspect to consider in future design and implementation steps in order to make butanol a competitive fuel among all other alternative fuels, (2) with a 50% internal heat recovery, butanol has a role to play in the transportation sector under climate policy scenarios, and may have a lower carbon footprint than gasoline as estimated by a 2010 US EPA study, and (3) higher supply costs for feedstock might undermine the competitiveness of butanol on the medium term (2030), but probably not on the long-term (2050). This combination of assessment methods is replicable to analyze any types of emerging energy pathways in Canada and in other countries, and to help designing more sustainable forest biorefinery processes in other countries with important forest sector. [ABSTRACT FROM AUTHOR]

This paper presents new metrics to measure the effect of thermal mass on the energy required to heat and cool buildings. Previous studies have been flawed as they have not considered the interaction between intermittent occupancy and thermal mass, which has a significant impact on overall energy use. However, existing parameters do not adequately capture these effects, so the new metrics developed in this paper are used to analyse the impact of thermal mass in hot climates with active cooling, and cold climates with active heating. The results agree with existing literature that high thermal mass structures are likely to be effective in hot climates; however, in cold climates the drawbacks of high thermal mass likely outweigh the advantages, and high thermal mass can cause an increase in energy use. This finding has implications for the design of buildings in cold climates, and contradicts the commonly-held assumption that high thermal mass is correlated with low energy use. The new metrics (transient energy ratio and effective U -value) provide a generalisable method to quantify these effects. They are further used here to analyse the dynamic performance of heavily insulated buildings and show that high thermal mass often leads to higher energy use in cold climates. [ABSTRACT FROM AUTHOR]

In order to slow climate change, economies need to quickly move away from finite energy sources and towards using low-carbon energy systems. However, the integration of non-dispatchable wind and solar sources comes with additional costs and can make the energy market unusual and unpredictable. Specifically, the presence of variable renewable energy sources makes it harder to accurately forecast energy demand. This paper is a first step in presenting a novel approach to overcoming the inherent variability of photovoltaics (PV) by combining them with a run-off-river (ROR) power plant. A mixed integer mathematical model has been developed and applied to simulate the operation of a PV–ROR hybrid energy source coupled with the national power system. Simulations demonstrate various configurations of parameters and their impact on the objective function which was to maximize the volume of energy from PV and hydropower used to cover energy demand, while ensuring that neither energy deficits nor energy surpluses exceed 5% of energy demand. Our analysis indicates that an ROR power plant with relatively small pondage is capable of subsidizing the varying energy output of the PV system. Besides conducting a simulation and optimization, this paper suggests an approach to smoothing the energy exchange with the grid based on fixed volumes of energy which should be delivered during daylight and nighttime hours. [ABSTRACT FROM AUTHOR]

• This paper systematically reviews the research progress of RS technology applied to various stages of PV system development. • We conclude that RS plays a significant role in PV potential assessment, large-scale data analysis and PV health monitoring. • We discuss future challenges and opportunities for RS technology in PV applications for advancing the research in this area. Developing solar photovoltaic (PV) systems is an effective way to address the problems of limited fossil fuel reserves, soaring world energy demand and global climate change. The earth observation information provides a promising perspective for estimating the PV energy potential and understanding the status of the PV system development, which is critical for making scientifically sound and cost-optimal sustainable planning strategies. Remote sensing (RS), a versatile technology that captures surface information at various temporal and spatial scales, is now widely applied in different fields of the PV development. However, despite the rapid growth of related research, there is still a lack of comprehensive review on the application of RS to different stages (i.e., planning, site selection, installation, maintenance, etc.) of the PV system development. This paper systematically reviews the research progress of RS technology applied throughout various stages of the PV system development. The reviewed literatures are organized as four major parts: i) PV potential estimation, ii) PV array detection, iii) PV fault monitoring and diagnosis, and iv) other cross-cutting areas where RS can facilitate PV development. We conclude that RS technology can bridge the gap caused by the traditional methods in effective assessment of resource potential, large-scale data analysis and PV health monitoring, which can provide strong support in assisting the planning, management, and decision-making of PV systems. Finally, we discuss future challenges and opportunities for RS technology in PV applications for advancing the research in this area. [ABSTRACT FROM AUTHOR]

• Multi-modal energy system planning approach to support political decision makers. • Energy sector coupling enables efficient transition pathway to achieve climate goals. • Main drivers: electrification of heat and mobility sectors and use of synthetic fuels. • High impact of the electricity exchange on the operation and costs of the system. In order to reach the goals of the United Nations Framework Convention on Climate Change, a stepwise reduction of energy related greenhouse gas emissions as well as an increase in the share of renewable energies is necessary. For a successful realization of these changes in energy supply, an integrated view of multiple energy sectors is necessary. The coupling of different energy sectors is seen as an option to achieve the climate goals in a cost-effective way. In this paper, a methodical approach for multi-modal energy system planning and technology impact evaluation is presented. A key feature of the model is a coupled consideration of the sectors electricity, heat, fuel and mobility. The modeling framework enables system planners to optimally plan future investments in a detailed transition pathway of the energy system of a country, considering politically defined climate goals. Based on these calculations, in-depth analyses of energy markets as well as electrical transmission and distribution grids can be performed using the presented optimization models. Energy demands, conversion and storage technologies in households, the Commerce, Trade and Services (CTS) area and the industry are modeled employing a bottom-up modeling approach. The results for the optimal planning of the German energy system until 2050 show that the combination of an increased share of renewable energies and the direct electrification of heat and mobility sectors together with the use of synthetic fuels are the main drivers to achieve the climate goals in a cost-efficient way. [ABSTRACT FROM AUTHOR]

• FuturES framework optimises electricity scenarios with high renewables penetration. • Reservoir and concentrating solar power modelled based on storage value. • Feasible scenarios created with 81–100% renewables by 2050. • Long-term energy storage helps to achieve low electricity costs. Although electricity supply is still dominated by fossil fuels, it is expected that renewable sources will have a much larger contribution in the future due to the need to mitigate climate change. Therefore, this paper presents a new framework for developing Future Electricity Scenarios (FuturES) with high penetration of renewables. A multi-period linear programming model has been created for power-system expansion planning. This has been coupled with an economic dispatch model, PowerGAMA, to evaluate the technical and economic feasibility of the developed scenarios while matching supply and demand. Application of FuturES is demonstrated through the case of Chile which has ambitious plans to supply electricity using only renewable sources. Four cost-optimal scenarios have been developed for the year 2050 using FuturES: two Business as usual (BAU) and two Renewable electricity (RE) scenarios. The BAU scenarios are unconstrained in terms of the technology type and can include all 11 options considered. The RE scenarios aim to have only renewables in the mix, including storage. The results show that both BAU scenarios have a levelised cost of electricity (LCOE) lower than, or equal to, today's costs ($72.7–77.3 vs $77.6/MWh) and include 81–90% of renewables. The RE scenarios are slightly more expensive than today's costs ($81–87/MWh). The cumulative investment for the BAU scenarios is $123-$145 bn, compared to $147-$157 bn for the RE. The annual investment across the scenarios is estimated at $4.0 ± 0.4 bn. Both RE scenarios show sufficient flexibility in matching supply and demand, despite solar photovoltaics and wind power contributing around half of the total supply. Therefore, the FuturES framework is a powerful tool for aiding the design of cost-efficient power systems with high penetration of renewables. [ABSTRACT FROM AUTHOR]

Schematic illustration of the double-layer PDRC coating. [Display omitted] • The idea of introducing masking layer for double-layer PDRC coating is proposed. • PDRC coating achieves high solar reflectivity (94.0%) at a thin thickness. • The PDRC coating reduces the indoor temperature of container room by 5.0 °C. • The prepared PDRC coating can realize large-scale long-time outdoor applications. The realization of spontaneous sub-ambient cooling in daytime typically requires the solar reflectance and thermal emittance of passive daytime radiative cooling (PDRC) material to be > 90%. Toward real-world applications, however, to achieve high optical performance and excellent durability, PDRC coating is often cost-prohibitive due to its high thickness (500 μm or higher). To solve the contradiction between high optical performance and thin thickness of PDRC coating, the idea of introducing masking layer for PDRC coating is proposed in this paper to prepare the water-based double-layer PDRC coating and explore its long-term outdoor application potential. The PDRC coating can achieve high solar reflectance (94.0%) and "atmospheric transparent spectrum window" emittance (93.0%), while the thickness and cost are only 40% and 60% of existing water-based PDRC coating. The PDRC coating shows efficient cooling performance when applied as the external coating of large temporary buildings, with maximum temperature reduction of 20.8 °C and 5.0 °C on the roof/indoor, which are equal to or greater than recorded values. The 150-day large-scale outdoor application shows that the coating has excellent durability, which offers a reference for the long-term outdoor application of PDRC coating. The application of the PDRC coating on rooftops of containers can achieve a cooling energy savings of up to 15.3% compared to conventional steel roofs, translating to an annual energy savings of 413.2 MJ and a reduction of approximately 114 kg in carbon dioxide emissions, which provide compelling evidence for the ability of PDRC coating to mitigate carbon emissions and address global climate change. [ABSTRACT FROM AUTHOR]

With the rising threat of climate change, green hydrogen is increasingly seen as the high-capacity energy storage and transport medium of the future. This creates an opportunity for low- and middle-income countries to leverage their high renewable energy potential to produce, use, and export low-cost green hydrogen, creating environmental and economic development benefits. While identifying ideal locations for green hydrogen production is critical for countries when defining their green hydrogen strategies, there has been a paucity of adequate geospatial planning approaches suitable to low- and middle-income countries. It is essential for these countries to identify green hydrogen production sites which match demand to expected use cases such that their strategies are economically sustainable. This paper therefore develops a novel geospatial cost modelling method to optimize the location of green hydrogen production across different use cases, with a focus on suitability to low- and middle-income countries. This method is applied in Kenya to investigate the potential hydrogen supply chain for three use cases: ammonia-based fertilizer, freight transport, and export. We find hydrogen production costs of €3.7–9.9/kg H 2 are currently achievable across Kenya, depending on the production location chosen. The cheapest production locations are identified to the south and south-east of Lake Turkana. We show that ammonia produced in Kenya can be cost-competitive given the current energy crisis and that Kenya could export hydrogen to Rotterdam with costs of €7/kg H 2 , undercutting current market prices regardless of the carrier medium. With expected techno-economic improvements, hydrogen production costs across Kenya could drop to €1.8–3.0/kg H 2 by 2030. [Display omitted] • We develop a novel GIS method to identify least-cost green hydrogen production locations. • This is applied in Kenya for ammonia, freight transport, and export use cases. • Hydrogen production costs of €3.7–9.9/kg H 2 are currently achievable in Kenya. • The cheapest production locations are to the south/south-east of Lake Turkana. • Kenya could export hydrogen and undercut current market prices with any carrier. [ABSTRACT FROM AUTHOR]

The allowance mechanism is one of the core and sensitive aspects in the design of a carbon emissions trading scheme and affects the compliance cost for each entity covered under the scheme. By examining China’s allowance mechanism from two aspects-allowance allocation and allowance distribution, this paper compares China’s carbon trading pilots with the EU Emissions Trading Scheme and California Cap-and-Trade Program. The comparison identifies the unique features in allowance mechanism and particular issues that affect the efficiency of the pilots. The paper also recommends courses of action to strengthen China’s existing pilots and to build valuable experiences for the establishment of the national cap-and-trade system in China. [ABSTRACT FROM AUTHOR]

To achieve the targets in the Paris Climate Change Agreement, carbon capture, utilization and storage (CCUS) will be one of the critical carbon mitigation technologies. For China, the biggest carbon emitter with coal-dominated energy structure, CCUS is expected to play more and more important roles for carbon emissions reduction. This paper looks at a method for designing a pipeline network system for large-scale CO2 capture, utilization, and storage (CCUS) in China. On the basis of performing a moderately significant literature review of past papers and models dating back to the early 2000’s, a updated multi-stage mixed integer programming (MIP) model for carbon source and sink matching (SSM) in ChinaCCUS DSS (Decision Support System) is developed. The Jing-Jin-Ji (Beijing–Tianjin–Hebei) region suffering from increasingly serious air pollution is chose as a case study to address the SSM issue with application of the updated model. The modeling results show that around 2200 km pipeline with investment of around $1.6 billion needed to be built to transport the cumulative sequestrated emissions of 1620 Mt CO 2 in the planning period of 2020–2050. Compared to the single-stage programming, the multi-stage programming could result to better pipeline connectivity. [ABSTRACT FROM AUTHOR]

South East Europe is the region in a part of Europe with approximately 65.5 million inhabitants, making up 8.9% of Europe’s total population. The countries concerned have distinct geographical features, various climates and significant differences in gross domestic product per capita, so the integration of their energy systems is considered to be a challenging task. Large differences between energy mixes, still largely dominated by fossil-fuel consumption, make this task even more demanding. This paper presents the transition steps to a 100% renewable energy system which need to be carried out until the year 2050 in order to achieve zero carbon energy society. Novelty of this paper compared to other papers with similar research goals is the assumed sustainable use of biomass in the 100% renewable energy system of the region considered. It is important to emphasize here that only the sustainable use of biomass can be considered carbon-neutral. The resulting biomass consumption of the model was 725.94 PJ for the entire region, which is in line with the biomass potential of the region. Modelling the zero-carbon energy system was carried out using the smart energy system concept, together with its main integration pillars, i.e. power-to-heat and power-to-gas technologies. The resulting power generation mix shows that a wide variety of energy sources need to be utilized and no single energy source has more than a 30% share, which also increases the security of supply. Wind turbines and photovoltaics are the main technologies with shares of 28.9% and 22.5%, followed by hydro power, concentrated solar power, biomass (mainly used in cogeneration units) and geothermal energy sources. To keep the biomass consumption within the sustainability limits, there is a need for some type of synthetic fuel in the transportation sector. Nevertheless, achieving 100% renewable energy system also promises to be financially beneficial, as the total calculated annual socio-economic cost of the region is approximately 20 billion euros lower in the year 2050 than in the base year. Finally, energy efficiency measures will play an important role in the transition to the zero-carbon energy society: the model shows that primary energy supply will be 50.9% lower than in the base year. [ABSTRACT FROM AUTHOR]

Transformation of the energy sector’s power generation mix is needed to contain global mean temperature rise to no more than 2 °C above the pre-industrial level. Because the power sector is also a dominant direct and indirect consumer of water, it is vital to understand current and likely future trends in power sector water consumption. In this paper, we use an input-output based hybrid approach to study the direct and indirect impacts on water consumption from power mix adjustment in the world’s seven largest emitting economies under multiple cost-effective mitigation pathways toward the 2 °C target. Although different pathways exist, we discovered generally increases in water consumption of power sector under the long-term 2 °C target compared with no-climate-policy pathways, especially for China and India. Fulfilling the Intended National Determined Contributions (INDCs) could decouple direct water consumption and electricity output for most regions but may result in increases of indirect water consumption in China. This paper suggests that in the light of geographically uneven water scarcity, more comprehensive evaluation of both the direct and indirect water demands of the power sector is demanded when considering climate policies relevant to significant structural and technological adjustments in power sector. [ABSTRACT FROM AUTHOR]

At any particular moment, the energy security of an energy system is at risk from events, both external and internal, that can affect its operation. By analyzing these risks, the state of the system’s energy security can be determined. If the method is generic, it can be applied to any energy system and the entities that support its operation. Despite the potential benefits of such a method, a review of the literature shows that existing methods of analysis focus on, for example, limited parts of the system or specific types of energy. To address this shortcoming, this paper presents a method for analyzing the risks to the energy security of any entity in an energy system. The method, derived from work at the National Institute for Statistics and Technology (NIST), determines the risks to an entity using the well-known properties of events (rate-of-occurrence and expected stress) and entities (flows, time-to-recover, and stress-tolerance). The paper demonstrates how the method can be applied using both qualitative and quantitative data to measure, analyze, and potentially improve a system’s energy security. Several examples are included. [ABSTRACT FROM AUTHOR]

With important implications for global climate change mitigation, the development of a cap-and-trade emission trading scheme (ETS) in China is embedded in distinctive political, economic, and institutional contexts and has been attracting increasing attention in recent years. To offer a clear perspective on current research progress, this paper systematically reviews the recent literature on China’s ETS from three main aspects: mechanism design, policy and regional linkages, as well as impact assessment. The current research consensuses are summarized based upon detailed literature analyses and commentaries, and together with observations of international experience and China’s actual condition, the paper provides policy proposals for the development of China’s national ETS during 2016–2020. Finally, several important controversies in the current literature are discussed with regard to the practical demands of China’s ETS development. Five pressing topics that need to be further studied in the coming years are highlighted, including cap setting, allowance allocation among sectors and enterprises, carbon pricing, policy package and unified carbon market construction, as well as ex-ante and ex-post impact assessments. [ABSTRACT FROM AUTHOR]

• Developing countries face the dual challenges of industrialising and 'catching up' while mitigating CO 2 emissions. • Medium- and high-technology manufacturing is associated with lower emissions than low-technology manufacturing, with differences varying by the income levels of countries. • A shift to more technology-intensive manufacturing could be one aspect of environmentally sustainable industrialisation in developing countries. Industrialisation is an important engine of growth and 'catch up', but also associated with harmful carbon dioxide emissions and hence with climate change. This poses a challenge for sustainable industrial development, particularly for late industrialisers on how to industrialise while also mitigating carbon dioxide emissions. This paper investigates the effect of technology intensity across manufacturing industries on carbon dioxide emissions: are medium- and high-technology manufacturing industries less emissions-intensive than low-technology manufacturing industries in developing countries? The paper analyses this relationship for a panel of 68 developing and emerging economies over the period 1990–2016, by adapting the environmental Kuznets curve and the stochastic effect by regression on population, affluence and technology approaches. Using two alternative measures of emissions and estimating generalised method of moments model, the results show that medium- and high-technology manufacturing industries are associated with lower carbon dioxide emissions than low-technology manufacturing industries. The results also show that these differences vary by the income levels of countries. These findings have important policy implications, suggesting that a shift towards more technology-intensive manufacturing production processes may be a more environmentally sustainable industrialisation path for developing countries. [ABSTRACT FROM AUTHOR]

Highlights • Yield per hectare of sweet sorghum are influence by temperature and precipitation. • Xinjiang and Inner Mongolia are suitable for planting sweet sorghum. • The 2020 and 2050 biofuel goal can be satisfied by certain scenarios in this paper. • Climate change and land-use change are critical to energy crop development plan. Abstract Biofuel from energy crops will play an important role in supplying carbon-neutral fuel for the transport sector. However, there are large uncertainties regarding energy crop development and the energy crop potential and distribution need to be evaluated more comprehensively and systematically. In this study, we propose an integrated approach using the AquaCrop model, a geographic information system approach, and a scenario analysis and we conduct a land availability assessment with multiple factors including climate change, land use, soil, topography, regional crop management, and technological improvement to shed light on the potential production, distribution, and temporal-spatial variation of land suitable for sweet sorghum production in China. We evaluate a full range of spatial scales from 1-km resolution to a national assessment in four representative concentration pathways from 2010 to 2100. The results show that most provinces can plant sweet sorghum. The most suitable provinces for sweet sorghum production are Xinjiang, Heilongjiang, Jilin, Inner Mongolia, Yunnan, and Sichuan. The biofuel potential of sweet sorghum in high-slope farmland (0.30–0.73 EJ) and marginal land (11.98–15.18 EJ) can satisfy the biofuel goal in 2020 (0.12 EJ) and 2050 (6.70–8.60 EJ). Climate change and land-use change are critical factors influencing for the current implementation and long-term planning of energy crops in China. [ABSTRACT FROM AUTHOR]

Highlights • Climate-sensitivity of load is asymmetric; high demand is more sensitive than moderate demand. • Dew point temperature is the key predictor of high- and moderate-intensity demands. • Residential high-intensity demand is more sensitive to precipitation than moderate demand. • Higher wind speeds decrease both the high- and moderate-intensity end-use demands. • Moderate intensity demand is more price-sensitive than high intensity demand. Abstract Climatic variations significantly influence the shape of end-use electricity demand curves. Although the climate sensitivity of end-use electricity demand is well-established, projecting medium- and long-term future demand remains a significant challenge—mostly due to a multitude of uncertainties involved in the modeling process. In this paper, we leveraged a state-of-the-art Bayesian approach to develop rigorously validated regional prediction models of the climate–demand nexus conditioned on the intensity level of demand. The prediction models were developed for the residential and commercial sectors for the top eight energy-intensive states in the U.S. A key contribution of this work was to illustrate the asymmetry in the sensitivity of load to climate. More specifically, our results demonstrated a greater sensitivity of the high-intensity end-use demand to climate variability as compared to the moderate-intensity end-use demand. In addition, our results helped identify mean dew point temperature as the key predictor of the climate-sensitive portion of both residential and commercial electricity demands, irrespective of the demand intensity levels. Wind speed was identified as the second most important predictor of the high-intensity (i.e., ≥ 3rd quartile) end-use demand, while electricity price was found to be the key predictor of the moderate-intensity (i.e., <3rd quartile) end-use demand. The influence of precipitation on the residential and commercial sectors' moderate end-use demand was found to be more variable. Precipitation was found to influence the commercial sector's electricity demand more significantly compared to the residential sector's demand. [ABSTRACT FROM AUTHOR]

Highlights • Taiwanese building energy conservation index (ENVLOAD) was converted to OTTV. • New models for energy efficient envelope were proposed as an adaption to the changing climate. • Coefficients of the OTTV model should be changed to reflect climate change. • Thermal insulation is gaining more concern while climate change proceeds. • Altering method of OTTV and setting new criteria in response to future climate was proposed. Abstract Changes in the climate system affect a building's energy consumption. Many countries have implemented building energy consumption indices to regulate the newly built buildings from excessive energy use. However, those indices were developed based on previous climate datasets and were incapable of responding to the changing climate. To stabilize the energy uses of future buildings as those under today's climate, regular updates of the evaluation index are mandatory to take climatic variations into consideration. This study firstly discussed the limitations in responding to future climate of current practicing building envelope energy conservation index in Taiwan. Secondly, we proposed a new index, the overall thermal transfer value (OTTV), based on the simulation results and tried to convert existing baseline criteria for the new OTTV. An approach on how to alter the OTTV index in response to the climate change was proposed. We found that because of the warming climate, the coefficient of the OTTV equation has to be changed over times to accurately respond to the changing climate. The approach presented in this paper provides a method on how to formulate a climate responsive index in pursuit of a better energy efficient building in the future. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of buildings is a key strategy in responding to climate change and resource challenges associated with the use of fossil fuel derived energy. The characteristics of the building envelope play a decisive role in determining building operation energy. Transparent Insulation Materials (TIMs) add to the strategies that may be used to sustain these improvements: they can reduce heat loss by providing high thermal resistance while effectively transmitting solar energy and contributing to the luminous environment. In this review, key types of TIMs and their characterisation in terms of both thermal and optical behaviours are introduced as well as the benefits that may be realised through their application to buildings. Relatively few studies exist regarding the performance of window systems incorporating TIMs. To provide a clear picture of how to accurately predict the performance of TIM integrated window systems, this paper also explores the literature around window systems incorporating complex interstitial structures, as these share many of the same characteristics as TIMs. The experimental and numerical methods used to evaluate the thermal and optical characteristics of complex window systems are summarised and this body of research provides potential methods for tackling similar questions posed in relation to the performance of window systems with TIMs. Finally, this review introduces a method that permits the prediction of the combined thermal and daylight behaviour of spaces served by TIM integrated window systems. The results from using this methodology show that using TIMs over a conventional window system offers a range of benefits to the occupants of buildings. Thus, this review offers a workflow that may be used to assess and analyse the benefit of applying TIMs for building energy saving and daylight comfort in buildings subjected to varying climate conditions. [ABSTRACT FROM AUTHOR]

It is becoming widely recognized that our society must transition to low-carbon energy systems to combat global climate change, and renewable energy sources are needed to provide energy security in a world with limited fossil-fuel resources. While many clean power-generation solutions have been proposed and are being developed, our ability to transition to a low-carbon society is prevented by the present lack of clean and renewable energy carriers that can replace the crucial roles that fossil fuels play, due to their abundance, convenience and performance, in global energy trade and transportation. Any future low-carbon energy carriers that aim to displace or supplement fossil fuels must have high energy densities for convenient trade and storage, and should be consumable within efficient high-power-density engines for transportation, heavy machinery, and other off-grid energy applications. Hydrogen and batteries have been widely studied but they are not suitable for use as international energy-trading commodities and they cannot provide the energy density and safety demanded by society. Metal fuels, produced using low-carbon recycling systems powered by clean primary energy, such as solar and wind, promise energy densities that are competitive to fossil fuels with low, or even negative, net carbon dioxide emissions. To date, however, few practical high-power-density end-use devices for generating heat or power from metal fuels have been proposed. This paper proposes a novel concept for power generation in which metal fuels are burned with air in a combustor to provide clean, high-grade heat. The metal-fuel combustion heat can be used directly for industrial or residential heating and can also power external-combustion engines, operating on the Rankine or Stirling cycles, or thermo-electric generators over a wide range of power levels. A design concept is proposed for a metal-fuelled combustor that is based upon extensive experimental and theoretical studies of stabilized and propagating metal flames performed at McGill University. This paper also reviews the fundamental and applied aspects of metal-fuel combustion in order to provide the framework needed to assess any potential metal engine technologies. The energy and power densities of the proposed metal-fuelled zero-carbon heat engines are predicted to be close to current fossil-fuelled internal-combustion engines, making them an attractive technology for a future low-carbon society. [ABSTRACT FROM AUTHOR]

• A novel decarbonization concept applied to offshore natural gas wells benefiting CCUS technology. • A comprehensive CFD model considers real gas EOS and the behaviours of gas, droplets, liquid film. • Compatible with pure CO 2 and CH 4 -CO 2 models to study condensation and separation characteristics. • The maximum CO 2 condensation amount under high pressure and low temperature is 10.33 ton/h. • The maximum CO 2 capture capacity is 4.43 ton/h with high heterogeneous droplet mass concentration. Carbon capture, utilisation and storage (CCUS) is of unique significance for building a green and resilient energy system, and it is also a key solution to tackle the climate challenge. The concept of supersonic decarburization, a joint product of non-equilibrium condensation and swirling separation, can contribute to CCUS technology in a clean way. In this paper, a numerical model is established and validated to investigate the complex physical phenomena of supersonic decarbonization in a high-pressure environment based on the real gas equation of state. The model is compatible with the pure CO 2 model and CH 4 -CO 2 model. Through the simulation of the supersonic nozzle and supersonic separator, the condensation and separation performance of supersonic decarbonization technology was evaluated. For the condensation performance of carbon dioxide, the results show that higher pressure makes it much easier to achieve the condensation process. When the pressure is supercritical, the decrease of inlet temperature or the increase of inlet mole fraction of CO 2 leads to a higher liquid fraction. For separation performance, when the mass concentration of inlet heterogeneous droplets increases from 0.1 kg/m3 to 7.5 kg/m3, the carbon separation amount increases from 3.33 ton/h to 4.43 ton/h, while the exergy loss of condensed CO 2 drops from 436.57 kJ/kg to 329.56 kJ/kg. It demonstrates that the decarburization process is easier, and exergy required for condensation decreases when the concentration of the foreign core is larger. This new concept is beneficial to CCUS technology and can be applied to carbon capture in offshore natural gas processing. [ABSTRACT FROM AUTHOR]

Given the need to rein in the rise in the global average temperature, decarbonizing the electricity sector, which accounts for nearly 50% of global greenhouse gas (GHG) emissions, is crucial. The suitability of nuclear power as a base-load technology and its relatively negligible GHG emissions raised expectations of a nuclear renaissance, until the Fukushima disaster brought discussions about nuclear power’s potential to a standstill. However, completely ruling out nuclear may not be sustainable owing to the realities of rising energy demand, climate change considerations, and the need for reliable base-load supply technology, especially in the case of fast growing economies in the Association of South East Asian Nations (ASEAN). The Fukushima disaster was a wake-up call for both governments and the nuclear industry. Led by the International Atomic Energy Agency, the more advanced economies conducted stringent reviews of safety standards and emergency response procedures in the event of a catastrophe. Meanwhile the industry responded with strong commitments towards “Fukushima proof” designs, alongside other advancements towards “safer” fission power. In the ASEAN context, we argue in this paper that in addition to the economic advantage, nuclear power can help address the twin objectives of energy security and mitigating climate change effects. In ASEAN, there is still a strong momentum towards nuclear power development due to strategic considerations. In this paper, we reviewed in a holistic approach the various factors influencing decision making on nuclear power. Using ASEAN as a case study, we argue that nuclear power remains an important option and should be taken up rapidly if decarbonizing electricity generation is a grave concern. We also provide some recommendations towards the “safer nuclear” for ASEAN at the end of this paper. [ABSTRACT FROM AUTHOR]

Household fuel-use (HFU) patterns are strongly associated with multiple effects, including air quality, human health, and regional climate change. This paper presents the results from the first Chinese Environmental Exposure-Related Human Activity Patterns Survey (CEERHAPS), carried out among 91,121 households located in 9108 villages, 636 towns, and 159 counties in 31 provinces. Face-to-face interviews were conducted with each participant to obtain information about the type of fuels used for cooking and heating. The main objectives of this paper were to investigate HFU for cooking and heating in China, to validate the World Health Organization (WHO) model, and to help inform local evaluation models. In China, gas and biomass fuels, the dominant energy fuels for cooking, are used by 44.8% and 32.1% of households, respectively. Approximately 34.1% of families have no household heating during the cold season, and 16.7%, 15.6% and 12.8% of households rely on coal, electricity, and biomass, respectively, for household heating when no central heating was available. The proportion of households using solid fuels has generally decreased during the last two decades. Considerable spatial variation was evident in the HFU patterns for both cooking and heating. The data revealed that the predominant fuel for cooking was biomass (47.6%) in rural populations, whereas urban households were more likely to cook with gas (65.8%). In terms of heating, coal (21.4%) and biomass (19.0%) were the main fuels used in rural households, while electricity (23.6%) and coal (10.5%) were more commonly used in urban areas. The overall HFU results for cooking from this study were comparable to those predicted using the WHO model. We also developed models at the provincial level to estimate HFU for cooking and heating in China; it is expected that the model, if confirmed by future studies, could be used for future research on household air pollution, domestic human exposure and burden of disease. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions are currently at the crux of political, environmental, technological, and cultural discussions due to climate change. A drastic reduction of GHG emissions is needed in order to mitigate potentially catastrophic climate change impacts. Thus, thoroughly understanding emission sources is imperative. A disaggregated analysis of Canada’s future GHG emission projections has not yet been conducted. The objectives in this paper are to assess disaggregated GHG emissions in Canada for the years 2014, 2030, and 2050, and analyze the results through Sankey diagrams. Emissions are calculated using a bottom-up multi-regional accounting-based Long-range Energy Alternative Planning systems model. Each major economic sector in Canada is analyzed including the electricity generation, residential, commercial and institutional, industrial, transportation, and agriculture sectors. The emissions released in these sectors are traced to the resources and end-uses responsible. Results are presented for Canada and for provinces individually. GHG emissions contained in exported resources are evaluated. Results show that Canada’s business-as-usual GHG emissions will grow from 732 million tonnes in 2014 to 780 and 798 million tonnes in 2030 and 2050, respectively. Canada exports more emissions contained in resources than it emits. Per capita emissions intensity will fall by 14% between 2014 and 2050. Results are compared to climate targets and key areas of GHG mitigation potential are identified. Alberta’s oil and gas sector and Ontario’s transportation sector are the two single largest sectoral sources of emissions by 2050. This research can help policy makers, innovators, and the public better understand GHG emissions, which can lead to more effective GHG mitigation. [ABSTRACT FROM AUTHOR]

Trade-related CO 2 emissions are an important component in global emissions. Understanding the role of international trade in emissions is of direct relevance to global and national emission reductions, particularly for major exporters and importers. In the literature, the issue has seldom been studied using index decomposition analysis (IDA), which is a popular tool in assessing growth in national-level CO 2 emissions. In this paper, based on a multi-region I-O analysis, we introduce three inter-linked IDA models to quantify the impacts of trade on the production-based emissions, the consumption-based emissions, and the emission balance of economies, respectively. A salient feature of the models, when applied together, is that they can help to assess the role of trade and the emission performance of economies from multiple perspectives. We discuss the relevant methodological issues as well as the advantages and limitations of the models. We then apply the models to evaluate the impact of international trade on changes in global CO 2 emissions from 1995 to 2009. It is found that while the growing trade volume drove up the total emissions, changes in the emission intensity and goods composition related to trade led to some degree of emission mitigation, particularly after 2005. [ABSTRACT FROM AUTHOR]

Security of supply and progressively climate change are guiding countries' energy policy worldwide. Iceland is a paradigmatic example of gaining energy independence and decarbonizing the power sector while meeting its growing demand. In this paper, we focus on some of the main generation and transmission expansion alternatives that the country is considering for the next decade in an environment dominated by an increasing demand and a generation mix with virtually zero variable cost. We assess the medium- to long-term dimensions of security of supply as determinants of the system configuration and resources utilization. Based on a stochastic hydrothermal scheduling model that includes DC power flows and generation expansion decisions, our analysis indicates that hydro, geothermal and wind renewable resources are more competitive than fossil fuels, while demand flexibility can also contribute to gain security of supply at comparable costs. In addition, our methodology incorporates a detailed bilateral contracting structure typically used by Icelandic generators and consumers to agree on power prices and negotiated curtailments. The modeling and security evaluation could be of interest in other countries and regions where inflexible thermal generation and hydro resources create a market characterized by prices that are close to zero during long periods, but spike when resources are scarce. [ABSTRACT FROM AUTHOR]

In an effort to address climate change, in 2013 China launched the world’s largest government-driven carbon emission reduction programme, the National Low Carbon Industrial Parks Pilot Programme (LCIPPP). This paper analyses this newly developed pilot program. To deepen our understanding of the causes and the impact of industrial park CO 2 emissions, we use the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and data from 20 pilot industrial parks involved in the LCIPPP for the period 2012–2016. This study quantitatively evaluates the effect of CO 2 emissions on output, energy structure, energy intensity, industrial structure, R&D intensity, and population change in different regions and nationally through an elasticity coefficient method. The results confirm that an increase in output and energy intensity is a dominant contributor to the growth of CO 2 emissions whereas an increase of the share of tertiary industry and R&D intensity has significant effects on reducing CO 2 emissions. The elasticity of energy intensity and renewable energy consumption on CO 2 emissions in the eastern region of China is the highest, indicating that using renewable energy to reduce CO 2 emissions for the industrial parks is more effective in the eastern region as compared to the central and western regions of the country. The elasticity of population is significantly negative in both the central and western areas while it is positive in eastern part of China, thereby illustrating that promoting labour intensive industries will be an effective way to reduce CO 2 emissions for the industrial parks in China’s central and western regions. Our study reveals that differentiated low carbon development pathways should be adopted. Concrete policy implications for reducing CO 2 emissions are also provided. [ABSTRACT FROM AUTHOR]

Climate change mitigation requires the reduction of greenhouse gas (GHG) emissions. The majority of the discussions on climate change policy focus exclusively on the reduction of carbon dioxide (CO 2 ) emissions but ignore other important GHGs such as methane. This paper investigates the optimal choice of policy instruments under the joint consideration of CO 2 and methane in a dynamic setting with asymmetric information and pollutant correlations. We develop a dynamic programming model with two state variables and calibrate it to the global warming case. The results show that it is optimal to levy tax on both CO 2 and methane. A mixed strategy that implements a tax on CO 2 and a quota on methane is the second-ranked choice. [ABSTRACT FROM AUTHOR]

A passenger transport model, Asia-pacific Integrated Model (AIM)/Transport, incorporating travelers’ mode of choice and transport technological details was developed in this study. This AIM/Transport was coupled with the AIM/Computable General Equilibrium (AIM/CGE) to capture interactive mechanisms between the transport sector, energy consumption, greenhouse gas (GHG) emissions, and the macro-economy. This paper presents the model structure and mathematical formulation of AIM/Transport, and explains how it was integrated with the CGE model by an iterative algorithm, taking into consideration the feedback between AIM/Transport and AIM/CGE. A numerical simulation proved that the integration of AIM/CGE and AIM/Transport can achieve a convergence after 13 iterations. A business-as-usual (BaU) scenario and a mitigation scenario were created to test the robustness of the model integration and how the mitigation potential and cost would be modified by coupling AIM/Transport. The key finding was that the carbon price and mitigation cost were modified with the coupled CGE-Transport model. [ABSTRACT FROM AUTHOR]

This paper discusses the economic impacts of climate change, including those on ecosystems, and whether a new backstop technology should be used under conditions of strict temperature targets. Using the dynamic integrated climate-economy (DICE) model, we developed a new model to calculate the optimal path by considering new backstop technologies, such as CO 2 capture and storage (CCS). We identify the effects of parameter changes based on the resulting differences in CO 2 leakage and sites, and we analyse the feasibility of CCS. In addition, we focus on ocean acidification and consider the impact on economic activity. As a result, when CCS is assumed to carry a risk of CO 2 leakage and acidification is considered to result in a decrease in utility, we find that CCS can only delay the effects of climate change, but its use is necessary to achieve strict targets, such as a 1.5 °C limit. This observation suggests that if the target temperature is too tight, we might end up employing a technology that sacrifices the ecosystem too greatly. [ABSTRACT FROM AUTHOR]

Reducing local and global emissions is one of the drivers behind the promotion of renewable energy technologies (RETs). Some RET projects (e.g. solar, marine power, and some biomass and wind) usually require supplemental income from carbon credits in order to make them economically viable. This paper presents the mathematical development of nodal marginal CO 2 emission metrics for hydrothermal systems. These metrics are obtained from optimal power flow and hydrothermal dispatch models considering hydro uncertainty. The proposed model allows a more accurate assessment of the emission reduction effect of RET projects and the provision of efficient carbon signals to the system. Modeling of hydro reservoirs and intertemporal constraints also allows incorporating the emission mitigation potential of water storage. The concepts of marginal CO 2 emissions for hydrothermal systems are first exemplified using a small test system, and then simulations on a real hydrothermal system illustrate how these metrics can inform investment and operational decisions. Theoretical and simulation results show that transmission and hydro storage constraints neglect may provide wrong signals for RET investors, missing the incentives to install in areas where the potential for emissions reduction is higher (where renewable energy displaces a larger amount of coal or diesel). Policy makers can use the proposed model to assess the cost-effectiveness of emission reduction policies. [ABSTRACT FROM AUTHOR]

The incidence of climate change policy is of great interests to economists, policy makers, producers and consumers. Using the daily market data for a 65-month period of 01/01/2011–05/31/2016, this empirical paper documents that the California Independent System Operator’s day-ahead prices have a CO 2 premium approximately equal to natural-gas-fired generation’s marginal cost of CO 2 emissions. This finding prevails in the six time-of-day periods developed to match the pricing periods used by the state’s local distribution companies and the bilateral trading of wholesale electricity in the Western Interconnection, a large electricity grid serving the western portion of North America and a Mexican state. Our findings suggest that the California cap-and-trade (C&T) program is effective in internalizing CO 2 emission costs of the in-state natural-gas-fired generation. However, the program’s economic efficiency is compromised by the unintended consequence of power laundering under inter-regional trading of wholesale electricity. While the program encourages the Pacific Northwest’s hydro export that displaces California’s natural-gas-fired generation, it also induces output increases by non-California coal- and natural-gas-fired generators in the Western Interconnection. Hence, reducing the overall CO 2 emissions in the Western Interconnection requires expanding the program’s geographic scope to meaningfully address the global warming problem. [ABSTRACT FROM AUTHOR]

Decarbonising electricity systems is essential for mitigating climate change. Future systems will likely incorporate higher penetrations of intermittent renewable and inflexible nuclear power. This will significantly impact on system operations, particularly the requirements for flexibility in terms of reserves and the cost of such services. This paper estimates the interrelated changes in wholesale electricity and reserve prices using two novel methods. Firstly, it simulates the short run marginal cost of generation using a unit commitment model with post-processing to achieve realistic prices. It also introduces a new reserve price model, which mimics actual operation by first calculating the day ahead schedules and then letting deviations from schedule drive reserve prices. The UK is used as a case study to compare these models with traditional methods from the literature. The model gives good agreement with and historic prices in 2015. In a 2035 scenario, increased renewables penetration reduces mean electricity prices, and leads to price spikes due to expensive plants being brought online briefly to cope with net load variations. Contrary to views previously held in literature, a renewable intensive scenario does not lead to a higher reserve price than a fossil fuel intensive scenario. Demand response technology is shown to offer sizeable economic benefits when maintaining system balance. More broadly, this framework can be used to evaluate the economics of providing reserve services by aggregating decentralised energy resources such as heat pumps, micro-CHP and electric vehicles. [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) is a low-carbon technology aiming to prevent carbon dioxide (CO 2 ) generated in large industrial facilities (e.g. power plants) from entering the atmosphere, thus mitigating human-caused climate change. CCS is deemed to be one of the most promising approaches to reduce industrial CO 2 emissions on a global scale, in addition to energy efficiency enhancement and increased use of renewables. This paper presents a mathematical programming model for multi-period planning of power plant retrofits with carbon capture (CC) technologies. The model allows for energy penalties due to CC retrofits and the need for compensatory power generation, as well as variations in technological parameters (such as electricity costs) over time. Furthermore, the model is formulated as a mixed integer linear programme (MILP), for which global optimality is guaranteed if a solution exists. Two case studies on carbon-constrained energy sector planning are presented to illustrate the proposed approach. Further analysis is carried out to examine the effect of the cost limit on the total increase in power generation cost. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [ABSTRACT FROM AUTHOR]

Many international organizations have called for an increased usage of renewable energy as a means to reduce CO 2 emissions and address climate change. This paper uses a large panel data set of 93 countries and recently developed panel estimation techniques to answer the question by how much does increasing non-fossil fuels in electricity generation reduce the subsequent carbon dioxide emissions. For the full sample, we find long-run displacement elasticities for non-fossil fuel consumption per capita of approximately −0.38; however, for the share of non-fossil fuels used in electricity generation, those long-run displacement elasticities are −0.82. Thus, a one percent increase of the share of non-fossil fuel electricity generation reduces CO 2 emissions per capita from electricity generation by about 0.82%. Long-run share displacement elasticities for non-OECD countries are substantially higher than those for OECD countries (approximately −0.98 to −0.54). These results have a number of policy implications. Our results are important in establishing that a very rapid increase in the share of non-fossil fuels used in electricity generation is needed in order to have a meaningful impact on per capita CO 2 emissions from electricity generation. [ABSTRACT FROM AUTHOR]