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Abstract In this work, a novel hydrogen production process (Integrated Chemical Looping Water Splitting “ICLWS”) has been developed. The modelled process has been optimised via heat integration between the main process units. The effects of the key process variables (i.e. the oxygen carrier-to-fuel ratio, steam flow rate and discharged gas temperature) on the behaviour of the reducer and oxidiser reactors were investigated. The thermal and exergy efficiencies of the process were studied and compared against a conventional steam-methane reforming (SMR) process. Finally, the economic feasibility of the process was evaluated based on the corresponding CAPEX, OPEX and first-year plant cost per kg of the hydrogen produced. The thermal efficiency of the ICLWS process was improved by 31.1% compared to the baseline (Chemical Looping Water Splitting without heat integration) process. The hydrogen efficiency and the effective efficiencies were also higher by 11.7% and 11.9%, respectively compared to the SMR process. The sensitivity analysis showed that the oxygen carrier–to-methane and -steam ratios enhanced the discharged gas and solid conversions from both the reducer and oxidiser. Unlike for the oxidiser, the temperature of the discharged gas and solids from the reducer had an impact on the gas and solid conversion. The economic evaluation of the process indicated hydrogen production costs of $1.41 and $1.62 per kilogram of hydrogen produced for Fe-based oxygen carriers supported by ZrO2 and MgAl2O4, respectively - 14% and 1.2% lower for the SMR process H2 production costs respectively.

The effect of osmotic pressure on erythritol and mannitol production by an osmophilic yeast strain of Yarrowia lipolytica CICC 1675 using glycerol as the sole carbon source was investigated. Appropriately high osmotic pressure was found to enhance erythritol production and inhibit mannitol formation. A novel two-stage osmotic pressure control fed-batch strategy based on the kinetic analysis was developed for higher erythritol yield and productivity. During the first 96 h, the osmotic pressure was maintained at 4.25 osmol/kg by feeding glycerol to reduce the inhibition of cell growth. After 132 h, the osmotic pressure was controlled at 4.94 osmol/kg to maintain a high dp(ery)/dt. Maximum erythritol yield of 194.3g/L was obtained with 0.95 g/L/h productivity, which were 25.7% and 2.2%, respectively, improvement over the best results in one-stage fed-batch fermentation. This is the first report that a novel osmotic pressure control fed-batch strategy significantly enhanced erythritol production.

Abstract In this study, we propose a novel integrated approach incorporating super-efficiency slack-based measure with undesirable outputs, difference-in-difference and propensity score matching difference-in-difference to explore the effects of carbon trading mechanism on green development efficiency in terms of impact direction, impact degree and impact mode. Taking the provincial data of China from 1999 to 2017 as an example, the empirical results show that China's green development efficiencies have upward, downward and U-shaped trends. Carbon trading mechanism, research and development intensity, and pollution control investment have a positive effect on green development efficiency. However, population capital, urbanization and degree of openness have a negative effect on green development efficiency.

AbstractBased on Cointegration Analysis and the state space model, this paper empirically analyzes the Yangtze River Delta energy consumption and economic growth based on 1990-2008 data. The results show: According to the cointegration analysis, the Yangtze River Delta economic growth and energy consumption exists long-term equilibrium .the current period of economic growth has been influenced by this period energy consumption and the amount of the previous period of economic growth, and the economic growth have the ability of 29.98% of the autorepair capacity. in all,we can conclude three enlightenment.

An analysis of electricity market reforms already taken place in the UK, Norway, Alberta (Canada) and California (USA) leads to our overall conclusion that the introduction of a competitive generation market, of itself, has failed to deliver reliable service at low and stable prices. The market reform failures are attributed to market power abuse by few dominant sellers (especially at times of transmission congestion), poor market design that invites strategic bidding by suppliers, the lack of customer response to price spikes, capacity shortage caused by demand growth not matched by new capacity, and thin trading of forward and futures contracts that are critical for price discovery and risk management. The paper then explains why an electricity market reform can easily fail to deliver the promised gains of better service at lower and more stable prices. The policy implication is that an electric market reform can be extremely risky, and may lead to a disastrous outcome. Thus, it is imprudent to implement such a reform in countries with limited sites for newgeneration and no indigenous fuels (e.g., Israel and Hong Kong). These countries should therefore consider introducing performance-based regulation that can immediately benefit electricity consumers in terms of lower prices, more stable prices, improved reliability, more choices, while encouraging the electric sector to pursue efficient operation and investment. r 2003 Elsevier Science Ltd. All rights reserved.

Digital economy is a great route to promote the efficient utilization of natural resources and promote sustainability due to its high-tech, rapid growth, extensive penetration, deep integration and other characteristics. Existing study on the influencing factors of the digital economy is not deep enough and lacks the analysis on the relationship structure of factors influencing the digital economy, which is not conducive for an overall grasp of the digital economy. To correctly understand how to better develop the digital economy, this paper studies its influencing factors and the relationships between them. Based on the time-series data of China from 2002 to 2018, grey correlation analysis was applied to calculate the correlation between these influencing factors and the digital economy, and determine the major influencing factors of digital economy development in China. The Granger causality test and a review of existing research were used to judge the interrelationship of various factors. The interpretative structure model was utilized to determine the relationship structure of the main factors affecting the development of China’s digital economy. The results show that the number of digital talents, state of the technology market, and degree of digitalization are direct influencing factors of the digital economy. The results help to better understand the development of the digital economy and will enable the implementation of policies to improve towards more sustainable cities.

Mining and using depletable fossil fuel usually result in severe environmental problem such as climate change in the global scale and acid rain in the regional level. To improve sustainable development, it is important to substitute fossil fuel with renewable and clean energy sources. In this study we employ a partial equilibrium, price endogenous mathematical programming model to analyze how bioenergy development in Taiwan can (1) enhance domestic energy production, (2) reduce the carbon dioxide (CO 2 ) and sulfur dioxide (SO 2 ) emissions, and (3) protect the environment. The results show that the ethanol expands with an increase in gasoline price, but SO 2 emission reduction would shrink because of a reduction in renewable electricity generation. Conversely, up to 10.4% of Taiwan’s annual SO 2 emission can be reduced in the face of higher coal and emission prices. A tradeoff between CO 2 and SO 2 emission reductions is perceived during the switch of production of liquid and nonliquid bioenergy. Policy implications such as technology selection, market operation, and government subsidy are also discussed.

Abstract Background Gap models are individual-based models for forests. They simulate dynamic multispecies assemblages over multiple tree-generations and predict forest responses to altered environmental conditions. Their development emphases designation of the significant biological and ecological processes at appropriate time/space scales. Conceptually, they are with consistent with A.G. Tansley’s original definition of “the ecosystem”. Results An example microscale application inspects feedbacks among terrestrial vegetation change, air-quality changes from the vegetation’s release of volatile organic compounds (VOC), and climate change effects on ecosystem production of VOC’s. Gap models can allocate canopy photosynthate to the individual trees whose leaves form the vertical leaf-area profiles. VOC release depends strongly on leaf physiology by species of these trees. Leaf-level VOC emissions increase with climate-warming. Species composition change lowers the abundance of VOC-emitting taxa. In interactions among ecosystem functions and biosphere/atmosphere exchanges, community composition responses can outweigh physiological responses. This contradicts previous studies that emphasize the warming-induced impacts on leaf function. As a mesoscale example, the changes in climate (warming) on forests including pest-insect dynamics demonstrates changes on the both the tree and the insect populations. This is but one of many cases that involve using a gap model to simulate changes in spatial units typical of sampling plots and scaling these to landscape and regional levels. As this is the typical application scale for gap models, other examples are identified. The insect/climate-change can be scaled to regional consequences by simulating survey plots across a continental or subcontinental zone. Forest inventories at these scales are often conducted using independent survey plots distributed across a region. Model construction that mimics this sample design avoids the difficulties in modelling spatial interactions, but we also discuss simulation at these scales with contagion effects. Conclusions At the global-scale, successful simulations to date have used functional types of plants, rather than tree species. In a final application, the fine-scale predictions of a gap model are compared with data from micrometeorological eddy-covariance towers and then scaled-up to produce maps of global patterns of evapotranspiration, net primary production, gross primary production and respiration. New active-remote-sensing instruments provide opportunities to test these global predictions.