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In this study, we investigated the influence of overall financial development and its components on energy consumption using the panel data of 120 countries and the generalized method of moments (GMM). By dividing the sample into developed and developing countries, we further examined the national differences of the impact of financial development on energy consumption. The empirical results indicate that the overall financial development significantly positively impacts energy consumption from a worldwide perspective, and its two components (financial institution and the financial market) have the same effect. The analysis of national differences indicates that the financial development also positively impacts energy consumption in developing countries but with no obvious effect in developed countries. The results also suggest that financial development cannot be used to restrain the increase in energy consumption from the global perspective, and policymakers in developing countries must balance the relationship between the development of the financial sector and energy consumption.

Understanding the system of connections between societal contexts and policy outcomes in municipal governments provides important insights into how community sustainability happens, and why it happens differently in various communities. A growing body of research in recent years has focused on understanding the socio-economic characteristics of communities and cities that are recognized as policy leaders in sustainability. In this paper, we expand the focus beyond the leaders in sustainability as we apply a selection of socio-demographic influences of community sustainability to a large sample of U.S. communities using community classification analytics to identity a range of community types and levels of engagement with sustainability. Our typology presents an integrated and comprehensive perspective on the structure of community sustainability in the United States, highlighting key points of comparison between human capital factors such as population size and density, affluence, home ownership, and adoption of sustainability policy. The analysis provides new insights not only about community leaders in sustainability, but also communities with the civic and social capacity to do more, and the challenges that may inhibit sustainability efforts in others.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

Abstract:While the need to update EPA benefit-cost analysis to reflect the most recent science is broadly acknowledged, little work has been done examining how well ex ante BCAs estimate the actual benefits and costs of regulations. This paper adds to the existing literature on ex post cost analyses by examining EPA’s analysis of the 1998 Locomotive Emission Standards. Due to data limitations and minimal ability to construct a reasonable counterfactual for each component of the cost analysis, the assessment relies mainly on industry expert opinion, augmented with ex post information from publicly available data sources when possible. The paper finds that the total cost of bringing line-haul locomotives into compliance with the 1998 Locomotive Emission Standards rule remains uncertain. Even though the initial per-unit locomotive compliance costs were higher than predicted by EPA, total costs also depend on the number of locomotives affected by the regulation. Over 2000–2009, the number of newly built line-haul locomotives was higher but the number of remanufactured line-haul locomotives was lower than EPA’s estimate.

ABSTRACTA novel design for a high temperature SOFC, based on lamellar electrode-electrolyte segments obtained by solidification of an oxidic eutectic melt on an electrolyte substrate is presented. Such “composite” electrodes contain NiO or MnO - 8Y-ZrO2 lamellae, which after reduction / oxidation yield electrode-electrolyte lamellae with 1–2 μm width and a vertical dimension of> 100 μm, depending upon the amount of eutectic melt solidified on a polycrystalline substrate. The nucleation of the eutectic on a polycrystalline substrate followed by a semi-directional crystallization of the two phases yields a gradient of 3-phase boundaries over the height of such an electrode, with the number of 3-phase boundaries increasing towards the substrate.

Abstract One approach to creating physics-based reduced-order models (ROMs) of battery-cell dynamics requires first generating linearized Laplace-domain transfer functions of all cell internal electrochemical variables of interest. Then, the resulting infinite-dimensional transfer functions can be reduced by various means in order to find an approximate low-dimensional model. These methods include Pade approximation or the Discrete-Time Realization algorithm. In a previous article, Lee and colleagues developed a transfer function of the electrolyte concentration for a porous-electrode pseudo-two-dimensional lithium-ion cell model. Their approach used separation of variables and Sturm–Liouville theory to compute an infinite-series solution to the transfer function, which they then truncated to a finite number of terms for reasons of practicality. Here, we instead use a variation-of-parameters approach to arrive at a different representation of the identical solution that does not require a series expansion. The primary benefits of the new approach are speed of computation of the transfer function and the removal of the requirement to approximate the transfer function by truncating the number of terms evaluated. Results show that the speedup of the new method can be more than 3800.

In developing an algal treatment system, selenium (Se) removal efficiency by Chlorella vulgaris was evaluated under various conditions such as Se concentration, algal density, temperature and pH. A maximum removal efficiency plateau of ∼90% was observed between 1000-3000 μg Se/L while the tolerance of Se toxicity was found at 6000 μg Se/L. C. vulgaris of 0.75 g DW/L showed the highest removal efficiency (84%), and volatilization was dominant below 1.37 g DW/L. Se volatilization was two times higher at 25 °C than at 20 °C in the first 24 h. Moreover, the highest removal efficiency (77%) was obtained at pH 8.0, compared to 66.5% at pH 6.5 and 40% at pH 10.0. To prevent ecotoxicity, Se laden algae were further burned to ashes or filtered out by Anodonta woodiana. After burning, biomass Se was reduced by 99%, with organo-Se entirely converted into inorganic Se, lowering Se bioavailability. A. woodiana removed 54% of Se in 24 h, leading to Se bioaccumulation in soft tissues, which may serve as dietary Se supplements for human health. Our results suggest the cleanup of Se-contaminated water from either agricultural runoff or industrial discharge could be achieved using an algal treatment system with minimum potential ecotoxicity.

Exploring the sensitivity of rural households’ livelihood strategies to livelihood capital is of great significance for improving rural households’ livelihood levels. This paper selects 23 livelihood capital measurement indicators and conducts an in-depth survey of rural households. In addition, the entropy method and a weighted comprehensive model are used to explore the basic characteristics of rural households’ livelihood capital in the upper reaches of the Min River, China, in 2017. Furthermore, econometric models are used to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital. As indicated from the research, the livelihood capital levels of different types of rural households in the study area are not equivalent. The types of rural households with different livelihood strategies can be ordered in terms of quantity as follows: non-agricultural type > non-agricultural dominant type > agricultural dominant type > pure agricultural type. Livelihood strategies have different sensitivities to different livelihood capital measurement indicators. Among these indicators, cash income, the number of relatives and friends available for financial assistance, and the number of civil servants have positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. However, the average age of laborers, area of cultivated land and gardens, number of livestock and poultry, and present value of production tools have negative effects. These evaluation results can provide a scientific decision-making basis for the formulation of poverty alleviation policies by relevant government departments.