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Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

The paper comprises a systematic experimental investigation into the influence of AC test source parameters on the leakage current pulses, voltage fluctuations and flashover voltages of polluted insulators. The test techniques include both salt-and clean-fog methods, while the test insulators comprise long-rod and cap and pin strings of different lengths as well as support columns.

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.

Recent geomorphic evidence from the inner shelf and shoreface to the east of Long Island's barrier island system indicates that reworking of glacial outwash deposits at the inner shelf-shoreface transition, as sea level rises, may be supplying much of the sediment needed to maintain barrier islands to the west. A conceptual model describing sediment dispersal from outwash source areas was developed from this hypothesis. It was reasoned that outwash sediments ranging from silts to coarse gravels would be subject to differential transport paths across and along the shoreface upon reworking. Coarser grain sizes would move onshore toward the intertidal beach, whereas finer sediments would move offshore. Sand of intermediate grain size would be concentrated in the surf zone an move alongshore in wave-generated longshore currents. To test this model, 400 samples from the beach and shoreface of Long Island were analyzed for grain-size frequency distribution and each grain-size class was examined for frequency of occurrence in the cross-shore and alongshore directions. On a spatially averaged basis, grain-size classes displayed peak abundance in specific zones across the shoreface as predicted by the model, but alongshore trends could not be recognized among the "noisy" data. Therefore, empirical orthogonal functions (EOF) were used to examine uncorrelated (orthogonal) modes of variability in the occurrence of each grain-size class in the alongshore direction. The first function, representing more than 60% of the variability among the data, showed that grain sizes subject to longshore transport in the surf zone i crease in frequency in the alongshore direction relative to coarser grain sizes. Results also show that peak concentrations of coarse sediments correspond to zones subject to frequent overwashing. It is concluded that EOF analysis of individual grain-size classes holds promise for extracting trends from noisy data sets. End_of_Article - Last_Page 318------------

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

Energy is consumed at every stage of the cycle of water production, distribution, end use, and recycled water treatment. Understanding the nexus of energy and water may help to minimize energy and water consumption and reduce environmental emissions. However, the interlinkages between water and energy have not received adequate attention. To address this gap, this paper disaggregates and quantifies the energy consumption of the entire water cycle process in Beijing. The results of this study show that total energy consumption by water production, treatment and distribution, end use, and recycled water reuse amounts to 55.6 billion kWh of electricity in 2015, or about 33% of the total urban energy usage. While water supply amount increased by only 10% from 2005 to 2015, the related energy consumption increased by 215% due to water supply structural change. The Beijing municipal government plans to implement many water saving measures in the area from 2016 to 2020, however, these policies will increase energy consumption by 74 million kWh in Beijing. This study responds to the urgent need for research on the synergies between energy and water. In order to achieve the goal of low-energy water utilization in the future, water and energy should be integrated in planning and management.

Paper mill sludge (PMS) is a residual biomass that is generated at paper mills in large quantities. Currently, PMS is commonly disposed in landfills, which causes environmental issues through chemical leaching and greenhouse gas production. In this research, we are exploring the potential of fast pyrolysis process for converting PMS into useful bio-oil and biochar products. We demonstrate that by subjecting PMS to a combination of acid hydrolysis and torrefaction pre-treatment processes it is possible to alter the physicochemical properties and composition of the feedstock material. Fast pyrolysis of pretreated PMS produced bio-oil with significantly higher selectivity to levoglucosenone and significantly reduced the amount of ketone, aldehyde, and organic acid components. Pretreatment of PMS with combined 4% mass fraction phosphoric acid hydrolysis and 220 °C torrefaction processed prior to fast pyrolysis resulted in a 17 times increase of relative selectivity towards levoglucosenone in bio-oil product along with a reduction of acids, ketones, and aldehydes combined from 21 % to 11 %. Biochar, produced in higher yield, has characteristics that potentially make the solid byproduct ideal for soil amendment agent or sorbent material. This work reveals a promising process system to convert PMS waste into useful bio-based products. More in-depth research is required to gather more data information for assessing the economic and sustainability aspects of the process.

Abstract This paper presents a novel multi-time-stage input–output-based modeling framework for simulating the dynamics of bioenergy supply chains. One of the key assumptions used in the model is that the production level at the next time-stage of each segment of the energy supply chain adjusts to the output surplus or deficit relative to targets at the current time period. Furthermore, unlike conventional input–output models, the technology matrix in this approach need not be square, and thus can include coefficients denoting flows of environmental goods, such as natural resources or pollutants. Introducing a feedback control term enables the system to regulate the dynamics, thus extending the model further. This is an important feature since the uncontrolled dynamic model exhibits oscillatory or unstable behavior under some conditions; in principle, the control term allows such undesirable characteristics to be suppressed. Numerical simulations of a simple, two-sector case study are given to illustrate dynamic behavior under different scenarios. Although the case study uses only a hypothetical system, preliminary comparisons are made between the simulation results and some broad trends seen in real bioenergy systems. Finally, some of the main policy implications of the model are discussed based on the general dynamic characteristics seen in the case study. In particular, insights from control theory can be used to develop policy interventions to impart desirable dynamic characteristics to nascent or emerging biofuel supply chains. These interventions can be used to guide the growth of bioenergy supplies along final demand trajectories with minimal fluctuation and no instability.

To meet the increasing challenges on global warming and customer demands, the current hierarchical structure of electric power grid is undergoing a rapid change by focusing on high efficiency, reliability and flexibility. To address such challenges, the new concept of smart grid with a sophisticated communication infrastructure has emerged. While power grid systems are based on traditional information architectures at present, the evolving smart grid has a strong need on communication connections among a huge amount of distributed elements, such as generators, substations, monitoring sensors and customers. However, the power industry is facing dilemma that communication resources are limited due to the lack of wireless spectrum resources and the restrictions of wired applications. This paper firstly provides the architecture of the wide-area monitoring system for smart grid by applying a spectrum sensing and sharing technique of cognitive radio, based on an overview of the current communication technologies. Afterwards, the paper presents the feasible application of cognitive communication architecture on the existing power quality monitoring system by combining long-term and short-term monitoring approaches.