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H 2 is an important commodity chemical that can also be used as an alternative fuel. The way how H 2 is currently produced and distributed, however, is not compatible with this usage. This is primarily due to the high costs associated with storing and delivering H 2 from the centralized production facilities to the end-use sites like H 2 stations that will be distributed throughout a region. Here, we propose a methodology for configuring the distributed H 2 production system that minimizes the overall cost in delivering H 2 to demand sites while meeting the safety requirements. The methodology also takes into account changes in costs with respect to production volume by applying the concept of economy of scale. The proposed methodology is applied to a hypothetical case involving H 2 supply to three stations. The results demonstrate significant reduction in the overall cost when adopting the optimal solution found by our methodology compared to the traditional, centralized production system. Insights on the cost structures associated with producing and delivering H 2 are provided, as well as specific improvements required to make H 2 affordable at the level defined by the international society. • A new methodology for configuring sizes and layout of distributed H 2 production system. • Comparative analysis between the centralized and distributed H 2 production system. • Costs of various H 2 production technologies and sensitivity analyses of key parameters. [ABSTRACT FROM AUTHOR]

Biological H 2 production is one of the alternative technologies for producing H 2 in a renewable and sustainable fashion. The technology often relies on the [FeFe] hydrogenase enzyme for catalyzing the H 2 production reaction from protons and electrons as it is highly efficient. The high O 2 sensitivity of the enzyme have been one of the key obstacles for implementing the technology, but recent findings showed the feasibility of improving O 2 tolerance via protein engineering. In this study, we investigated the changes in the O 2 tolerance and aerobic H 2 production activity of an [FeFe] hydrogenase by replacing methionines on the surface with leucines. None of the mutations were detrimental to protein folding, and a few were able to exert either positive or negative influence on the O 2 tolerance of the enzyme. We combined the mutation exhibiting the highest improvement in O 2 tolerance with the rest of the Met – Leu replacements; however, the results indicated non-synergistic impact on the tolerance. Combinations with the other types of mutations that have been reported previously also failed to further improve the O 2 tolerance of the hydrogenase. These results provide new insights on how mutagenesis affects the enzyme's functional properties, as well as the molecular mechanism(s) behind the tolerance. • A novel mutation that enhances the O 2 tolerance of the [FeFe] hydrogenase. • Analysis of the combinatorial mutagenesis' influence on the key functional properties. • Protein engineering work employing both in silico and experimental methods. [ABSTRACT FROM AUTHOR]

Abstract: We perform the first long-term (>1 year) continuous adjoint simulations with a global atmospheric chemistry–transport model focusing on population exposure to fine particulate matter (PM2.5) and associated risk of early death. Sensitivities relevant to intercontinental and high-altitude PM pollution are calculated with particular application to aircraft emissions. Specifically, the sensitivities of premature mortality risk in different regions to NO x , SO x , CO, VOC and primary PM2.5 emissions as a function of location are computed. We apply the resultant sensitivity matrices to aircraft emissions, finding that NO x emissions are responsible for 93% of population exposure to aircraft-attributable PM2.5. Aircraft NO x accounts for all of aircraft-attributable nitrate exposure (as expected) and 53% of aircraft-attributable sulfate exposure due to the strong “oxidative coupling” between aircraft NO x emissions and non-aviation SO2 emissions in terms of sulfate formation. Of the health risk-weighted human PM2.5 exposure attributable to aviation, 73% occurs in Asia, followed by 18% in Europe. 95% of the air quality impacts of aircraft emissions in the US are incurred outside the US. We also assess the impact of uncertainty or changes in (non-aviation) ammonia emissions on aviation-attributable PM2.5 exposure by calculating second-order sensitivities. We note the potential application of the sensitivity matrices as a rapid policy analysis tool in aviation environmental policy contexts. [Copyright &y& Elsevier]

Abstract: During the last few decades, energy planning has focused on meeting domestic demand at lower total costs. However, global warming and the shared recognition of it have transformed the problem of energy planning into a more complex task with a greater number of issues to be considered. Since the key issue is to reduce greenhouse effects, governments around the world have begun to make investments in renewable energy systems (e.g., hydro, wind, solar, and/or biomass power). The relatively high costs of renewable energy systems and the uncertain outlook of their rate of diffusion in the market make it difficult to heavily rely on them. The uncertain variations in production cost over time are especially challenging. To handle uncertainties, the concept of the learning rate was adopted in this study so as to compute the costs of energy systems in the future and Monte Carlo simulation was performed. The aim of this study was to optimize plans of conventional and prospective renewable energy systems with respect to production cost. The production cost included capital, fixed, variable, and external costs. For the case study, the energy situation in South Korea was used. The results of the case study where the proposed methodology was applied could provide useful insights economically and strategies of sustainable energy management for ambiguous environments. [Copyright &y& Elsevier]

Abstract: This paper studies economics of renewable energy systems with consideration of future prospects on costs and uncertain external conditions that may affect competitiveness in the power plant market. The concept of learning curve is adopted to compute estimates on the costs of installing and operating renewable energy systems in the future; fuel costs and carbon price are modeled as scenario-dependent variables to analyze their impact on total costs under different scenarios. The proposed approach allows evaluation and comparison of total costs necessary in implementing renewable energy plans under varying technological, and/or economical conditions that face uncertainty at present. Moreover, analyzing the evaluation results further with techniques like sensitivity analysis can identify factors central to reducing the total costs. As an illustrative case-study, the Korean government’s renewable energy plan has been evaluated accordingly, under three different scenarios defined by International Energy Agency (IEA). The evaluation results indicate minor changes in total costs of achieving the plan among three scenarios, mainly due to counterbalancing between the price of fossil fuels and carbon price. Further analyses revealed factors central to lowering the total costs necessary in implementing the plan—hybridization between renewable energy systems, reduction of biomass production costs via technological innovation, increasing learning rates by focusing on R&D and international cooperation. [Copyright &y& Elsevier]

Abstract: In this paper, a new approach has been proposed that allows a robust optimization of sustainable energy planning over a period of years. It is based on the modified energy flow optimization model (EFOM) and minimizes total costs in planning capacities of power plants and CCS to be added, stripped or retrofitted. In the process, it reduces risks due to a high volatility in fuel prices; it also provides robustness against infeasibility with respect to meeting the required emission level by adopting a penalty constant that corresponds to the price level of emission allowances. In this manner, the proposed methodology enables decision makers to determine the optimal capacities of power plants and/or CCS, as well as volumes of emissions trading in the future that will meet the required emission level and satisfy energy demand from various user-sections with minimum costs and maximum robustness. They can also gain valuable insights on the effects that the price of emission allowances has on the competitiveness of RES and CCS technologies; it may be used in, for example, setting appropriate subsidies and tax policies for promoting greater use of these technologies. The proposed methodology is applied to a case based on directions and volumes of energy flows in South Korea during the year 2008. [Copyright &y& Elsevier]

Abstract: The modification of the electrical characteristics of field-effect transistors (FETs) with channels composed of n- or p-type silicon nanowires (SiNWs) by oxygen plasma treatment is investigated in this study. The SiNWs obtained from silicon bulk wafers are <111> surface-oriented and their doping concentrations are ∼1021 and ∼1017 cm−3 for the n- and p-type SiNWs, respectively. After the back-gate SiNWFETs were subjected to oxygen plasma treatment, the magnitude of the drain current of the n-type SiNWs was decreased, whereas that of the p-type SiNWs was increased, while the gate-dependent characteristics of both of types of SiNWs were improved. The changes in the electrical characteristics are due to the adsorption of oxygen ions on the surface of the SiNWs. To verify the effect of the oxygen ions, the SiNWFETs were kept in a vacuum for 24h whereupon their electrical characteristics tended to revert to their inherent state. [Copyright &y& Elsevier]