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Highlights: • We consider the driving effect of green low-carbon behavior in our model. • We propose three green low-carbon behavior systems: GG, PG, PMG. • We get the growth welfare effect and the knowledge diffusion effect. Abstract This paper establishes a new endogenous growth model driven by green low-carbon behavior, optimizes the model and three systems with green low-carbon behavior in order to obtain the comprehensive effects of the empirical and policy of the three policies that have been set. This paper consists of three parts: green low-carbon behavior endogenous growth model, three green low-carbon behavior systems, empirical and policy effects. In the green low-carbon behavior endogenous growth model, we have built a new endogenous growth model, which is based on the existing endogenous growth model, considering the effects and influences of green low-carbon behavior. The model divides the economic system in green low-carbon behavior pattern into three modules: the production module, the household module and the R&D module. In the production module, we consider the number of knowledge diffusion in the intermediate goods and use the number of knowledge diffusion to explain the transmission of green low-carbon behavior. We consider environmental quality, capital, labor and emission input in the production function of the intermediate goods in a specific sector. Then we get the first-order conditions of intermediate producers based on the profit function of intermediate producers. In the household module, we consider consumption, environmental quality and carbon emissions in the representative household utility, and use Hamilton function in order to obtain the optimum conditions for the representative household with respect to consumption and physical capital. In the R&D module, we obtain the characteristics of the balanced growth path in a stable state. In the second part, we propose three green low-carbon behavior systems. Through the optimization of government budget, welfare function and the nine optimization solutions of the new model in green low-carbon behavior pattern, we compare the government's green low-carbon behavior (GG), private green low-carbon behavior motivated by the government (PMG) and private green low-carbon behavior motivated by anarchy (PG). Finally, we draw the conclusion that PMG is an optimal system to achieve the highest growth rate and welfare level. In the part of empirical and policy effects, we propose three green low-carbon parameters that policymakers need to consider and then the numerical simulations are conducted based on data from the United States and China. Then we compare the results obtained from the two countries' numerical simulation, and get the comprehensive effects of green low-carbon behavior: growth welfare effect and knowledge diffusion effect. [ABSTRACT FROM AUTHOR]

[Display omitted] • Robust low-carbon planning method is proposed for the SMGUS in steelmaking plant. • Decarbonizing steel plant through renewable energy, hydrogen, energy storage & CCUS. • Planning under different market conditions and CO 2 reduction routes are discussed. • Considering uncertainties promotes the deployment of flexibly adjustable equipment. • CCUS is the key for decarbonization of steel plant before massive use of renewables. Decarbonization of the steelmaking industry is imperative in achieving the carbon neutrality target. This paper proposes a two-stage low carbon robust planning method for the steel mill gas utilization system (SMGUS), which is the major CO 2 emission source of the conventional blast furnace route based-steelmaking plant. The planning aims to find the optimal installed capacities and relevant deployment time of multiple low-carbon technologies, such as renewable energy, energy storage, hydrogen energy and carbon capture & utilization, so that the demand of steel production can be met in an economically competitive and environmentally friendly way. Case studies are carried out on the low-carbon planning of a steelmaking plant with annual production of 1.5 million tons of crude steel, in which different carbon market conditions and CO 2 reduction routes are considered. The results show that the low carbon planning can reduce the CO 2 emissions to 1.22 tons per ton of steel by 2045–2050 through the proper deployment of the low carbon technologies. The CO 2 emissions can be further reduced to 0.31 tons per ton of steel if the BF-BOF process is replaced by H2-DRI and EAF technologies. This paper presents an effective planning method for the decarbonization of steelmaking plant. [ABSTRACT FROM AUTHOR]

• Lab synthesis of various adsorbents for adsorption-based PCC. • Bench and pilot-scale experimental studies of adsorption-based PCC. • Molecular simulation of adsorbents for post-combustion carbon capture. • Process modelling\simulation and techno-economic analysis of adsorption-based PCC. • Achievements, challenges and future prospect in adsorption-based PCC. Adsorption-based post-combustion carbon capture is a promising emerging technology for capturing CO 2 emissions from fossil-fueled power plants due to the ease of adsorbent regeneration in comparison with solvent-based technologies. To increase its competitiveness, research efforts have focused on the development of new adsorbent materials and processes. This paper presents a state-of-the-art review of such efforts, focusing on lab synthesis and characterization of adsorbent materials, (carbon capture) experimental studies, molecular simulation, process modelling\simulation and techno-economic analysis. Most experimental studies on adsorption-based post-combustion capture are at bench scale. Just a few experimental studies are at pilot scale. There are currently no commercial deployment of adsorption-based post-combustion capture technology. This review paper points out challenges encountered in these experimental investigations utilizing different adsorbent materials, limiting its commercial deployment. These gaps in experimental investigations need further research especially in the chemical modification of the adsorbent materials to increase the adsorption capacity. Molecular simulation of adsorbents and process modelling\simulation of carbon capture processes are cost-effective and time efficient approaches for the assessment of adsorbents' CO 2 capture performance. The review also highlighted the need for more research in the model development of adsorbent materials at molecular scale and the model development of adsorption-based post-combustion process adopting new reactor configurations to further reduce the cost of CO 2 capture. [ABSTRACT FROM AUTHOR]

As part of its energy transition strategy, China has set ambitious targets for increasing the contribution of renewable energy and, in particular, of wind power. However, the Chinese power sector has not undergone the necessary reforms to facilitate the integration and absorption of a larger share of variable renewable energy. This is evident from the difficulties in absorbing wind power from already commissioned wind farms and the resultant curtailment of wind power. Pumped storage hydroelectricity (PSH) is a flexible power source that can facilitate higher penetration levels of wind power as well as complement China’s growing nuclear power capacity. However, regulatory policy constraints have restricted the effective utilization of existing PSH capacity and discouraged investment in new PSH capacity. This paper examines these constraints and assesses the likely impact of new policies designed to address them. Finally, policy recommendations and concluding remarks are provided. This paper contributes to the literature on renewable energy integration from a new perspective. The lessons from China are relevant to other countries going through the energy transition. [ABSTRACT FROM AUTHOR]

This paper shows a new advanced control approach for operations in hybrid systems equipped with solid oxide fuel cell technology. This new tool, which combines feed-forward and standard proportional–integral techniques, controls the system during load changes avoiding failures and stress conditions detrimental to component life. This approach was selected to combine simplicity and good control performance. Moreover, the new approach presented in this paper eliminates the need for mass flow rate meters and other expensive probes, as usually required for a commercial plant. Compared to previous works, better performance is achieved in controlling fuel cell temperature (maximum gradient significantly lower than 3 K/min), reducing the pressure gap between cathode and anode sides (at least a 30% decrease during transient operations), and generating a higher safe margin (at least a 10% increase) for the Steam-to-Carbon Ratio. This new control system was developed and optimized using a hybrid system transient model implemented, validated and tested within previous works. The plant, comprising the coupling of a tubular solid oxide fuel cell stack with a microturbine, is equipped with a bypass valve able to connect the compressor outlet with the turbine inlet duct for rotational speed control. Following model development and tuning activities, several operative conditions were considered to show the new control system increased performance compared to previous tools (the same hybrid system model was used with the new control approach). Special attention was devoted to electrical load steps and ramps considering significant changes in ambient conditions. [ABSTRACT FROM AUTHOR]

Multiple geographically dispersed data center buildings have been increasingly positioned in renewable-rich areas due to their high energy consumption. This paper proposes an optimal multi-energy portfolio for zero carbon data center buildings in the presence of proactive demand response programs. In the data center buildings, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via multi-energy conversion and storage devices, which are modeled as 100% renewable energy hubs for zero carbon multi-energy supplies. In order to exploit the hub-internal operational dispatchability and flexibility, a comprehensive energy consumption model of data center buildings is proposed to facilitate the demand response in terms of available serves, while the variable speed pumped storage (VSPS) is modeled to capture its dynamic operational characteristics. The energy‑carbon production, conversion, storage, and consumption are formulated as an energy‑carbon matrix, which are solved via a two-stage method to obtain the optimal portfolio. Case studies on southwest China data center buildings are implemented to demonstrate the effectiveness and superiority of the proposed methodology on cost-effective accommodation of RESs. Simulations results show that the system portfolio cost can be reduced by at most 17.8% with a higher operational flexibility. • A cost-effective data center building is proposed to accommodate zero carbon targets. • Hydro-solar-wind 100% renewables are formulated for multi-energy supplies. • VSPS and data center energy consumption are modeled to exploit inherent flexibility. • The energy-carbon production, conversion, storage, and consumption are optimized. [ABSTRACT FROM AUTHOR]

• Presenting a set of mathematical models for green flowshop scheduling problems. • Considering common carbon reduction policies and their corresponding scenarios. • Providing analysis of models and insights to design a framework for green flowshops. • Industries can use our cost-effective strategies to meet limits mandated by government. • Government can explore our integrated framework to gauge impacts of carbon policies. In this paper we consider, from an environmental policy-maker perspective, how carbon reduction policies impact the economic competitiveness of the manufacturing sector. Specifically, we focus on flowshop scheduling – which typically aims to minimize makespan for purely economic objectives – and consider how three common carbon reduction policies – namely, taxes on emissions, baselines on emissions, and emissions trading schemes – can create competitive green flowshops that balance minimization of makespan and carbon emissions. The goal is to enable policy-makers to understand how to set policies and control parameters to achieve environmental objectives while ensuring global economic competitiveness of industry. We initially present a set of mixed-integer linear programming (MILP) models for flowshop scheduling problems operating in a regulated environment in which each carbon reduction policy is adopted. We then introduce a bi-objective scheduling framework for the corresponding problem to obtain alternative solutions under each policy. These models and their computational results however, are not the main focus of the study, but are presented as a means to demonstrate how green policies co-exist with economic objectives, with policy-makers in control of the balance. To this end, based on financial data from Australia's carbon emissions profile, we provide a policy-oriented analysis of the models, and some managerial insights into the effect of scheduling strategies on carbon emissions under different reduction policies. These insights offer support to both environmental policy-makers and corporate production and sustainability managers to determine whether it is technically feasible and profitable to replace traditional scheduling strategies with environmentally friendly scheduling strategies. [ABSTRACT FROM AUTHOR]

• The first 2D combined CH4-assisted SOEC and F-T synthesis model is developed. • A novel strategy towards low-carbon fuel generation is proposed. • Parametric studies are conducted with performance determining factors discussed. • The distribution of generated carbon-contained fuels (from C 1 to C 5+) is studied. CH 4 -assisted solid oxide electrolyzer cells (SOECs) can co-electrolyze H 2 O and CO 2 effectively for simultaneous energy storage and CO 2 utilization. Compared with conventional SOECs, CH 4 -assisted SOECs consume less electricity because CH 4 in the anode provides part of the energy for electrolysis. As syngas (CO and H 2 mixture) is generated from the co-electrolysis process, it is necessary to study its utilization through the subsequent processes, such as Fischer-Tropsch (F-T) synthesis to produce more value-added products. An F-T reactor can convert syngas into hydrocarbons, and thus it is very suitable for the utilization of syngas. In this paper, the combined CH 4 -assisted SOEC and F-T synthesis system is numerically studied. Validated 2D models for CH 4 -assisted SOEC and F-T processes are adopted for parametric studies. It is found that the cathode inlet H 2 O/CO 2 ratio in the SOEC significantly affects the production components through the F-T process. Other operating parameters such as the operating temperature and applied voltage of the SOEC are found to greatly affect the productions of the system. This model is important for understanding and design optimization of the combined fuel-assisted SOEC and F-T synthesis system to achieve economical hydrocarbon generation. [ABSTRACT FROM AUTHOR]

• A high spatial resolution CO 2 emissions inventory of 280 Chinese cities was compiled. • Three methods were compared to evaluate the carbon efficiency of Chinese cities. • The best and worst-performing cities were consistent regardless of different methods. • Top-ranking cities were located in the coastal regions of China. • Lagging-behind cities were located in the central and western regions of China. Comprehensive and accurate city-level carbon dioxide emissions inventory is key to success in China's pursuit of low-carbon development. Based on a high-resolution gridded data, this paper evaluates and benchmarks the carbon emissions efficiency of 280 Chinese cities using three different methods, i.e., composite index, data envelopment analysis and stochastic frontier analysis. The comparative analysis reveals that the average carbon emissions efficiency of Chinese cities is about 70–90%, with only 9 efficient cities (3%). Although the ranking of intermediate cities varies greatly according to the method employed, the most and least carbon-efficient cities remain consistent. While the best-performing cities are found in the coastal regions, the worst-performing cities are located in the central and western regions, which suggests an imbalanced low-carbon development in China. Guided by the results, local governments are encouraged to compete and learn from similar ranking benchmarks in a new regime of "Top Runner City". Finally, the scores of carbon emissions efficiency can provide a scientific basis for the bottom-up allocation of carbon emissions rights to boost the development of the nationwide carbon market in China. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We incorporate a variety of principles and indicators into an improved ZSG-DEA model. • We conduct a multi-criteria allocation of China's CEA by 2030 to provincial shares. • We measure the total and per capita space for carbon emissions by province. • All provinces reach the DEA frontier with different CEA ranging from 4.21 to 16.77 Gt. • Differentiated provincial reduction policies are the key to achieving China's INDCs. Abstract Accelerating global warming has suggested the importance of controlling greenhouse gas emissions associated with human activities. In striving to fulfill the Paris Agreement, China has announced its Intended Nationally Determined Contributions (INDCs) aimed at reducing its carbon dioxide (CO 2) emission intensity by 60–65% in 2030 against the level of 2005. However, China's INDCs cannot be fulfilled without formulating appropriate schemes for the allocation of carbon emission allowance (CEA) at sub-national scales. To help close the gap in our knowledge, this paper starts with measuring the overall CEA of China by 2030, and then proposes a science-based scheme for CEA allocation by developing an improved zero sum gains-data envelopment analysis (ZSG-DEA) model. It demonstrates that the final CEA of some northern provinces can be cut down as compared to their initial shares and, conversely, most southern provinces experience an increase in their CEA. Comparing the final share of CEA by province with current carbon emissions, we observe that provinces with abundant energy reserves, such as Shanxi, Inner Mongolia and Shaanxi, tend to be operating in a state of overshoot in terms of space for carbon emissions (SCE). In contrast, there remains SCE when it comes to Guangdong, Hunan, Fujian, etc. The remaining provinces, such as Heilongjiang, Hebei and Ningxia, are close to the break-even point. In view of the differing SCE of individual provinces, common but differentiated policies for CO 2 emission control would be the key to achieving China's INDCs. The research findings lay a scientific basis for the Chinese government to make its INDCs come true through inter-provincial collaboration on emission reduction, but also serve as a reference for fueling further scientific discussions and development of schemes for the allocation of responsibility for carbon emissions at multiple scales within and beyond China. [ABSTRACT FROM AUTHOR]

Highlights • A stochastic programming approach is proposed to model TS and ESS sizing simultaneously. • The model considers DSM and renewable energy curtailment policies with various limits. • The effect of TS on total cost, sizes, locations of ESS are discussed. • We find that TS is noteworthy to analyze for power systems with renewable targets. Abstract Increasing the share of renewable energy sources in electricity generation helps address concerns about carbon emissions, global warming and energy security (i.e. dependence on fossil fuels). However, integrating intermittent and variable energy sources into the grid imposes new challenges for power system reliability and stability. To use these clean sources in electricity generation without endangering power systems, utilities can implement various control mechanisms, such as energy storage systems, demand side management, renewable energy curtailment and transmission switching. This paper introduces a two-stage stochastic programming model that co-optimizes transmission switching operations, and transmission and storage investments subject to limitations on load shedding and curtailment amounts. We discuss the effect of transmission switching on the total investment and operational costs, siting and sizing decisions of energy storage systems, and load shedding and renewable energy curtailment in a power system with high renewable penetration. An extensive computational study on the IEEE 24-bus power system with wind and solar as available renewable sources demonstrates that the total cost and total capacity of energy storage systems can be decreased up to 17% and 50%, respectively, when transmission switching is incorporated into the power system. [ABSTRACT FROM AUTHOR]

Highlights • The flexible resources for integrating wind power are analyzed from the cost perspective. • The balancing cost when using coal-fired generation could reach $4/MWhw. • The cost of DSM for integrating wind power can be very low. • The EES will prevail coal-fired generation when its capital cost drops below 400$/kWh. Abstract The inherent stochastic nature of wind power requires additional flexibility during power system operation. Traditionally, conventional generation is the only option to provide the required flexibility. However, the provision of the flexibility from the conventional generation such as coal-fired generating units comes at the cost of significantly additional fuel consumption and carbon emissions. Fortunately, with the development of the technologies, energy storage and customer demand response would be able to compete with the conventional generation in providing the flexibility. Give that power systems should deploy the most economic resources for provision of the required operational flexibility, this paper presents a detailed analysis of the economic characteristics of these key flexibility options. The concept of “balancing cost” is proposed to represent the cost of utilizing the flexible resources to integrate the variable wind power. The key indicators are proposed respectively for the different flexible resources to measure the balancing cost. Moreover, the optimization models are developed to evaluate the indicators to find out the balancing costs when utilizing different flexible resources. The results illustrate that exploiting the potential of flexibility from demand side management is the preferred option for integrating variable wind power when the penetration level is below 10%, preventing additional fuel consumption and carbon emissions. However, it may require 8% of the customer demand to be flexible and available. Moreover, although energy storage is currently relatively expensive, it is likely to prevail over conventional generation by 2025 to 2030, when the capital cost of energy storage is projected to drop to approximately $400/kWh or lower. [ABSTRACT FROM AUTHOR]

China’s commitment to the UNFCCC to peak its emissions by 2030, or sooner, signaled a long anticipated shift in China’s model of development with far reaching consequences. Cities in China, and particularly the residential sector in cities, will be charged with making significant reductions in emissions growth even as rates of urbanization continue to climb. Focusing on Beijing and Shanghai, this paper carries out a measures-based economic analysis of low carbon investment opportunities in the residential sector. Results find significant opportunity: between 2015 and 2030, BAU levels of CO 2 emissions could be reduced by 10.2% in Beijing and 6.8% in Shanghai with the adoption of economically attractive low carbon measures. While these headline results underline the case for low carbon investment in the residential sectors of these megacities in China, a closer analysis provides insights for understanding the economics of decarbonisation in cities more generally. [ABSTRACT FROM AUTHOR]

• Shrinking cities tend to be less energy efficient than their growing counterparts. • Shrinking cities need to consider the environmental effects of shrinkage. • Urban compactness is negatively associated with residential CO 2 emissions. • Intra-city polycentricity is negatively correlated with gas-related CO 2 emissions. This paper analyzes the relationship between urban form, shrinking cities, and residential carbon emissions, based on information collected for prefectural-level and above Chinese cities for the years of 2005, 2010, and 2015. After controlling for a number of urban form and socioeconomic variables (e.g., size, compactness, and polycentricity), this paper pays attention to residential carbon emissions in 'shrinking cities', which have experienced population loss and are a recent urban phenomenon in China. Everything else being equal, shrinking cities tend to be associated with less energy efficient than their growing counterparts, suggesting that these cities may not only be 'battling' with shrinking populations and economies but also need to consider the environmental issues. [ABSTRACT FROM AUTHOR]

• The average carbon reduction performance increases year by year. • The policy has an immediate impact on CO 2 reduction in demonstration cities. • The policy has follow-up impact on carbon emission reduction. • Less thermal power and more research investment are the paths to policy effect. The Energy-saving and Emission Reduction Demonstration City (ESERD) Policy brings more favorable development conditions and opportunities for the cities selected, but the carbon reduction effect of the energy-saving policy is not clear which needs to be quantified and evaluated. By measuring the Total Factor/Energy Carbon Performance Index (TCPI /ECPI) of 286 prefecture-level cities in China from 2003 to 2019 and by constructing a quasi-natural experiment, this paper contributes in three aspects. (1) we are committed to a method of calculating the energy consumption and carbon emission of prefecture-level cities in China; (2) we provide evidence to the CO 2 reduction effect of the ESERD policy in a more comprehensive way; (3) we probe the paths of the policy effects. The main findings are: (1) TCPI and ECPI has been rising since 2011, the eastern cities have more outstanding achievement while the performance of the western region has been at a relatively high level during the time period of the study, and the performance of cities have diverged in recent years. (2) The policy's contribution to the demonstration cities' carbon reduction performance is significant, immediate and far-reaching, a lower share of electricity consumption due to indirectly reducing the use of coal, and higher investment in scientific research for improving the technology level of industrial development are both paths to achieve carbon emission reduction in the demonstration cities. [ABSTRACT FROM AUTHOR]

Direct carbon solid oxide fuel cell (DC-SOFC) is a promising energy conversion device for power generation using solid carbon fuel. In this paper, a 2D model is developed for a tubular DC-SOFC for CO and electricity co-generation. Parametric simulations are conducted to understand the physical/chemical processes in the DC-SOFC. Good performance of DC-SOFC is observed even at a large distance between the carbon bed and the porous anode, indicating the feasibility of large-scale DC-SOFC applications. The DC-SOFC performance is found to decrease with decreasing temperature due to the decreased Boudouard reaction kinetics. It’s also found that the molar fraction of CO at the anode can be well controlled by adjusting the operating conditions, enabling DC-SOFC for electricity and CO cogeneration. Another finding is that the current density in the DC-SOFC increases slightly along the cell length, which is different from the H 2 -fueled SOFC. In addition, the anode-supported configuration is found to be beneficial in improving the electrical output of the DC-SOFC but is unfavorable for CO generation. A small D ce and a high potential are recommended to improve CO generation from the DC-SOFC. The model can be used for design optimization of DC-SOFC at a system level. [ABSTRACT FROM AUTHOR]

Lithium-ion storage capacitors were assembled using graphene/tantalum carbide/tantalum wire electrodes and carbon hollow spheres as electrolyte. The graphene/tantalum carbide layers were prepared by electron-assisted hot filament chemical vapor deposition; the carbon hollow spheres were synthesized by hydrothermal reaction and pyrolysis treatment. The specific capacitance of the capacitor was 593 F g −1 at a current density of 10 A g −1 . The capacitor showed excellent cycling stability, retaining 91.2% of its initial capacitance after 8000 cycles. Moreover, the capacitor provided a high specific energy density of 132 W h kg −1 at a high power density of 3.17 kW kg −1 . The high energy density is attributed to the widened operation window ranging from 0 to 3.0 V. The graphene layer of the electrode and carbon hollow spheres in electrolyte synergistic affect influence on the electrochemical performance of the capacitor are discussed. In addition, the use of a low-cost lithium salt, lithium chloride, is also featured in this paper. [ABSTRACT FROM AUTHOR]

Climate change present a range of equity issues for human being, but operating the equity principle within emission allocation scheme to various parties has raised multiple challenges. Although more than 40 schemes have been suggested in the literatures, there is little consistency in the way that baselines, scope, coverage and other key parameters have been compared or discussed. In this paper, we reviewed 41 schemes used in the literature so far and compared the cumulative allowances of main countries under various schemes in a consistent framework. Two cases are considered, i.e. only energy and industry related CO 2 and all Kyoto GHGs. Besides the allowances, carbon Gini coefficient in the global perspective and the reduction tradeoffs between country groups are further quantitatively discussed. It is demonstrated that the full ranges of countries’ allowances are quite large resulting from different equity considerations and implement methods behind different effort-sharing schemes. However, absolute mitigations are always required in developed countries in order to realize the 2 °C target, regardless of schemes. [ABSTRACT FROM AUTHOR]

The prioritized purpose of this dissertation is to put forward a scientific and plausible interval of carbon price benchmark on the unified carbon trading market, of which will be scheduled to be established in the year of 2016. A model named EMD–GARCH that integrated Empirical Mode Decomposition (EMD) with Generalized Autoregressive Conditionally Heteroskedastic (GARCH) together is presented here in order to forecast the carbon price of the five pilots (Shenzhen, Shanghai, Beijing, Guangdong, and Tianjin) in 2016 so as to provide exogenous data for later analysis. For further study, a recursive dynamic Computable General Equilibrium (CGE) model will be structured to explore the impacts on China’s macroeconomics, environmental quality, and energy demand respectively under 8 different simulation scenarios, which are being designed in terms of the aforementioned calculated carbon price outcome. The simulation results illustrate that the unified carbon price policy will exert a comprehensive effect on China in various perspectives that we discussed in this paper. Moreover, regarding the carbon price scenarios, the price level by itself generates a different degree of impacts in improving the environmental quality, decreasing the energy demand, and increasing the macroeconomic growth. Consequently, based on the analysis of those three approaches mix in this study, we suggest the alternative interval of carbon price benchmark in the national unified carbon trading market with a lower bound of 30 yuan/tCO 2 to an upper bound of 50 yuan/tCO 2 . [ABSTRACT FROM AUTHOR]

This paper provides a review on three streams of life cycle studies that have been frequently applied to evaluate the environmental impacts of building construction with a major focus on whether they can be used for decision making. The three streams are Life Cycle Assessment (LCA), Life Cycle Energy Assessment (LCEA) and Life Cycle Carbon Emissions Assessment (LCCO 2 A). They were compared against their evaluation objectives, methodologies, and findings. Although they share similar objectives in evaluating the environmental impacts over the life cycle of building construction, they show some differences in the major focuses of evaluation and methodologies employed. Generally, it has been revealed that quite consistent results can be derived from the three streams with regard to the relative contribution of different phases of life cycle. However, discrepancies occur among the findings obtained from the three streams when different compositions of fuel mixes are used in power generation, or when the overall impacts are not contributed mostly by greenhouse gases emissions. The use of different functional units in different studies also makes it difficult to compare results with benchmarks or results from previous studies. Besides, there are drawbacks in boundary scoping, methodology framework, data inventory and practices which impair their usefulness as a decision making support tool for sustainable building designs. [ABSTRACT FROM AUTHOR]

Eco-innovations are being recognized as fundamental means to foster sustainable development, as well as to create new business opportunities. Nowadays, the eco-innovation concept is gaining ground within both academic and practitioner studies with the attempt to better understand the main dynamics underlying its nature and guide policymakers and companies in supporting its development. This paper contributes to the extant literature on eco-innovation by providing a comprehensive overview of the evolution of a specific type of eco-innovations that are playing a crucial role in the current socio-economic agenda, namely low-carbon energy technologies. Accordingly, we focus our attention on the related patenting activity of different countries and organizations over time, as well as on influencing policy initiatives and events. Hence, we collected 131,661 patents granted at the United States Patent and Trademark Office (U.S.PTO.) between 1971 and 2010, and belonging to the “Nuclear power generation”, “Alternative energy production”, and “Energy conservation” technological classes, as indicated by the International Patent Classification (IPC) Green Inventory. Our findings report the development trends of low-carbon energy technologies, as well as identify major related environmental programs, historical events, and private sector initiatives explaining those trends, hence revealing how these different circumstances have significantly influenced their development over time. [ABSTRACT FROM AUTHOR]

• A multi-regional input–output model is applied for empirical analysis. • Relationships between rebound effects and consumption patterns are investigated. • The rebound risks are measured from three perspectives. • Repressing the direct rebound effect can counteract the total rebound effect. Improving energy efficiency is considered to be essential to carbon emission reduction. However, it may not be as effective as expected due to the rebound effect. This paper attempts to investigate the carbon rebound effects and rebound risks in households. For this purpose, a comprehensive analysis framework incorporating elastic estimates, environmentally extended multi-regional input–output model and re-spending model, were built. Three rebound risk indicators were then constructed, following which a simulation of direct and indirect carbon rebound effects was conducted for urban households in China. By comparing the estimation results of the four re-spending scenarios, we found these households' carbon rebound effect to be significant. The empirical results further indicate significant differences in the rebound risk among different provinces. Overall, Xinjiang, Qinghai and Ningxia are the provinces most vulnerable to the rebound effect. These findings point to the necessity of the government adopting other measures besides energy efficiency policies, with regional differences taken into account, in order to curb the carbon rebound effect. [ABSTRACT FROM AUTHOR]

Carbon emission allowances are issued to limit the carbon emission by enterprises, but some unforeseen variables may cause their demand unpredictable. Together with the high volatility of carbon price dynamic, management of carbon asset is of great significance and difficulty for those enterprises with heavy carbon consumption. To cope with the demand and price uncertainty of carbon emission right, carbon derivative provides a feasible solution for those enterprises. This paper proposes applying the carbon option for carbon management. For better applying this tool, carbon option is evaluated through a geometric Brownian motion model with regime-switching. Based on the value estimation and analysis of carbon option, decision making and strategy design for carbon asset management are achieved by the quantitative results of option pricing and digital detection during the operation. Development of the modeling and algorithm for carbon option pricing is the main theoretical contribution, also it enriches the theory of real option property of carbon. Moreover, it provides a detailed schema and an inspiring case study of applying the options for carbon asset management and facilitating the decision-making digitally in line with the market information constantly updated, and it is applicable and believed to optimize the risk control for all enterprises with carbon-consumption. • Carbon option is priced and applied for digital decision-making of the transactions. [ABSTRACT FROM AUTHOR]

• The first to examine the herding behavior in China's eight carbon markets. • Beijing, Shanghai, Chongqing, Fujian four carbon markets exist herding behavior. • There is no herding behavior in China's overall carbon market. • Herding intensity is positively correlated with carbon market volatility. This paper introduces a modified cross-sectional absolute deviation approach to measure the existence of herding behavior and herding asymmetry, and uses the runs test to measure the herding intensity in China's carbon markets. It is the first study to examine the existence of herding behavior in China's carbon markets. The empirical results show that no herding behavior exists in China's overall carbon market. As for herding asymmetry, no herding behavior exists in both up and down markets and in the markets with high and low trading volumes, as well as in the markets with high volatility. Among China's eight carbon markets, herding behavior exists in Beijing, Shanghai, Chongqing, and Fujian, in which Chongqing has the highest herding intensity, while Guangdong, Hubei, Shenzhen, and Tianjin have no herding behavior. The herding behavior is prone to the occurrence when carbon price continuously rises or falls with high volatility. When the carbon market is highly volatile with a large transaction volume, the herding intensity is high. Herding intensity is positively correlated with market volatility. Finally, we propose policy implications to mitigate herding behavior. [ABSTRACT FROM AUTHOR]

• Region contributed to 50% of global CO 2 emissions and 92% of increase in 1995–2015. • Region was a net exporter of trade-embodied emissions despite high carbon intensity. • Carbon leakage has gradually moved from China and India to other developing nations. • The nations had diverse trends of carbon footprint due to technological differences. • The drivers of changes in regional CO 2 emissions varied across nations and over time. A continuous growth of international trade, especially between developing countries, has greatly increased carbon dioxide (CO 2) emissions associated with energy consumption over the past two decades. Given the more intensified intraregional cooperation and trade within the Belt and Road Initiative (BRI), this study aims to trace the imbalance of CO 2 embodied in trade between nations in BRI and the rest of the world, providing new insights into the drivers of emissions growth by contrasting consumption, production and technological differences-based perspectives. Results indicate that the BRI contributed to over 50% of global carbon footprint and 92% of its increase in 1995–2015. The BRI was a net exporter of trade-embodied emissions, whose technological-adjusted carbon footprint remained remarkably large due to comparatively high carbon intensity. Geographically, carbon leakage has gradually moved from China and India to other BRI countries, especially to Southeast Asia, West Asia and Africa. Technological change was the key driver of emissions reduction, followed by the change in industrial structure. The growth in final demand per capita was the most important driver for the growth of CO 2 emissions in BRI. Improving carbon efficiency remains a critical step for BRI nations to slow down not only emissions growth but also carbon leakage. The paper managed to provide novel insights into the carbon leakage in BRI by contrasting the consumption, production and technological differences-based perspectives, thus being able to better inform policymakers on region-specific low-carbon transition and global climate governance. [ABSTRACT FROM AUTHOR]

• A trading framework is designed enabling the exchange of energy and carbon allowance. • Smart contract is exploited to automate standardised auction procedure. • The bidding/selling prices directly target on reshaping prosumption behaviours. • Results prove that the proposed framework facilitates regional energy balance and carbon saving. Prosumers are active participants in future energy systems who produce and consume energy. However, the emerging role of prosumers brings challenges of tracing carbon emissions behaviours and formulating pricing scheme targeting on individual prosumption behaviours. This paper proposes a novel blockchain-based peer-to-peer trading framework to trade energy and carbon allowance. The bidding/selling prices of prosumers can directly incentivise the reshaping of prosumption behaviours to achieve regional energy balance and carbon emissions mitigation. A decentralised low carbon incentive mechanism is formulated targeting on specific prosumption behaviours. Case studies using the modified IEEE 37-bus test feeder show that the proposed trading framework can export 0.99 kWh of daily energy and save 1465.90 g daily carbon emissions, outperforming the existing centralised trading and aggregator-based trading. [ABSTRACT FROM AUTHOR]

(a) Historical carbon emission mitigation of the residential building sector and (b) emission benchmarks of the future residential building sector in China. • Carbon mitigation of the residential building sector in 2000–2015 is 1.817 (±0.643) BtCO 2. • Residential building will achieve its emission peak in 2037 (±4) at 1.419 (±0.081) BtCO 2. • Floor space per capita and energy intensity are determining in the uncertainty of emission peak. • Future residential building energy benchmark should be controlled at 0.703 (±0.042) Btce. • A benchmark of 1.258 BtCO 2 can achieve the residential buildings' 2030 emission peak goal. Fast-growing carbon emissions from the residential building sector are a hindrance for China to achieve its 2030 emission peak goal. To identify future low carbon roadmaps of residential buildings, this study is the first to assess the historical carbon mitigation and simulate the energy and emission peaks of China's residential building sector using a dynamic emission scenario. It shows that the emission mitigation of the residential building sector during 2000–2015 is 1.817 (±0.643) billion tons of carbon dioxide (BtCO 2), and the normal distribution-based scenario simulation demonstrates that the residential building sector will achieve its carbon emission peak in 2037 (±4) with a peak value of 1.419 (±0.081) BtCO 2. The sensitivity analysis reveals that the impacts of floor space per capita and energy intensity of urban residential buildings are the most significant for the uncertainty of emission peaks. A strict energy demand benchmark of the residential building sector suggests a control at 0.661 billion tons of standard coal equivalent (Btce), and its peaking time is estimated for 2035, which is 5 years ahead of the business-as-usual scenario, with energy savings of 0.042 Btce. For the earliest peaking time, if the residential building sector aims to achieve its emission peak before 2030, the emission peak should be controlled at 1.258 BtCO 2. Overall, this paper can assist the government in more accurate and feasible building emission mitigation strategies. Moreover, the results provide a more powerful decision-making reference in issuing targeted and feasible strategies for future residential building emission mitigation. [ABSTRACT FROM AUTHOR]

• The potential gains and carbon emissions reduction of carbon trading are detected. • Three scenarios of carbon trading schemes are considered and compared. • Sectoral trading may create potential gains of 268.02 trillion yuan in 2006–2015. • Carbon emissions may decrease by 17.17 billion tonnes under sectoral trading scheme. • Sectoral trading decreases industrial carbon intensity by 19.80% during 2015–2020. Carbon trading is an important market tool in driving growth and carbon dioxide emissions reduction in industrial sectors in China. This paper attempts to assess the impacts of carbon trading on economic output and carbon dioxide emissions reduction in China's industrial sectors by employing the data envelopment analysis (DEA) based optimization models, based on three carbon trading schemes, i.e., no trading (NT), sectoral trading (ST), and sectoral-and-temporal trading (STT) during 2006–2015. Comparing with the no-trading scheme, the results indicate that, (1) the ST and STT schemes may create potential gains of 268.02 and 612.26 trillion yuan in the whole industrial during the study period, i.e., the industrial value-added would be increased by 55.17% and 73.76%, respectively; (2) the ST and STT schemes could reduce 17.17 and 19.22 billion tonnes of carbon dioxide emissions, respectively, accounting for 58.30% and 65.25% of emissions reduction in the whole industry; and (3) if carbon trading were adopted in China since 2006, its carbon intensity of industrial sectors would decrease by 34.89%, 47.44% and 19.80% under the ST scheme, and 58.93%, 31.50% and 10.25% under the STT scheme during the11th, 12th and 13th Five-Year Plan periods, respectively. [ABSTRACT FROM AUTHOR]

• A joint decomposition model based on meta-frontier was proposed. • The effect of scale efficiency was captured based on variable return to scale model. • The catch up effect of carbon emission and energy usage technology was captured. Production-theoretical decomposition analysis (PDA) is widely used to explore the factors related to changes in carbon emissions. However, traditional PDA mainly focuses on scenarios of decision making units (DMUs) with constant returns to scale, and neglects technology heterogeneity among DMUs. Therefore, this paper proposes a joint approach combined PDA and index decomposition analysis (IDA) based on the variable returns to scale (VRS) and the meta-frontier model, and further decomposed the change of carbon emissions into 9 driving factors. Based on above, we investigated the effects of the nine factors on the change of carbon emissions at national, regional and provincial levels in China during the period of 2007–2016. The results indicated that the increase of carbon emissions in China have slowed down since 2012, but the overall situation is not optimistic, especially in the western region. Economic activity played a dominant role in increasing carbon emissions for each region. Carbon emission efficiency and potential carbon factor were also the two important factors related to increase carbon emissions. Conversely, energy intensity, the catch-up effect of pure technical efficiency and scale efficiency on carbon emissions played a positive role in decreasing CO 2 emissions, especially for the eastern region. However, the driving factors related to energy usage, such as the catch-up effect of energy usage scale efficiency and the pure energy usage technical efficiency had trifling and unstable effects on the change of carbon emissions. Based on the above analysis, we propose suggestions to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

• We explore whether each of the 30 Chinese provinces will peak emissions by 2030. • We combine STIRPAT models and scenario analyses to predict emissions trajectories. • 26 provinces are likely to peak emissions under at least one scenario, but 4 are not. • Peaking time and cumulative emissions are considered in seeking optimal peaking path. • Provincial results in aggregate show China may peak in 2028–2040 and 2030 is optimal. China has pledged in its Nationally Determined Contributions (NDCs) that its carbon emissions will peak no later than 2030. However, the varying carbon emissions trajectories of individual provinces make it difficult to determine whether China can fulfill this ambitious goal on time. To bring transparency and clarity to this core issue, this paper explores for the first time whether and how all the 30 Chinese provinces will peak their energy-related emissions in future by developing a set of extended STIRPAT models that investigate the driving forces behind each province and integrating the estimates into scenario analysis for peaking simulation. We observe that, despite continued economic growth, 26 provinces are highly likely to reach peak emissions under at least one scenario, whereas the remaining are not. We find it interesting that the earliest peaking scenarios may not be the best option for those provinces whose cumulative carbon emissions are estimated to be considerably large. To ensure a viable reaching of China's peak emissions, much more attention should be paid to seeking for the most appropriate emissions trajectory to peak at the subnational level with relatively low cumulative value. Provincial results in aggregate show that China may peak emissions in the period 2028–2040, with cumulative emissions ranging from 403,607 Mt CO 2 (corresponding to peaking in 2030) to 456,191 Mt CO 2 (corresponding to peaking in 2038), while 2030 would be the optimal year for the country to peak because of the lowest cumulative carbon emissions. Our findings only provide a deeper understanding of China's potential peaking paths by province, but also assist policy makers in better prediction and evaluation of possible emissions trajectory for other nations and the whole world from a bottom-up perspective, and therefore could be of global significance. [ABSTRACT FROM AUTHOR]

• A new, pseudo-transient re-formulation for rate-based column models. • Seamless integration with a library of pseudo-transient unit operation models. • Application to simulation and optimization of complex carbon capture processes. • Validation of next-generation flowsheet against a rigorous thermodynamic model. • Results reveal economic effect of solvent stability and flue gas composition. Amine scrubbing processes remain an important technology for mitigating the contribution of carbon emissions to global warming and climate change. Like other chemical processes, they can benefit from computer-aided optimization at the design stage, but systematic optimization procedures are rarely employed due to the challenges of simulating the requisite rate-based mass transfer and reaction models. This paper presents a novel approach for the simulation and optimization of rate-based columns, with specific application to the absorber and stripper columns found in (amine-) solvent-based carbon capture processes. The approach is based on pseudo-transient continuation, and the resulting column models are easily incorporated into large-scale process flowsheets with other previously developed pseudo-transient models. We demonstrate that the proposed approach allows for gradient-based optimization of next-generation amine scrubbing processes by considering a complex carbon capture process under three different operating conditions. The results provide general insight into the design of amine scrubbing processes, and shadow prices at the optimal point(s) suggest potential avenues for improving the process economics. The effects of carbon dioxide removal percentage and flue gas composition on process economics are briefly analyzed. [ABSTRACT FROM AUTHOR]