The optimized design of outdoor environment is of utmost importance due to its impact on human health, urban livability and energy consumption inside buildings. The outdoor thermal comfort and its ...spatiotemporal variations were assessed using Universal Thermal Climate Index (UTCI). Annual and seasonal UTCI were calculated using the daily dataset collected from 591 stations in China between 1966 and 2016. A REOF-cluster-EOF hybrid model was developed to optimize regionalization and assess regional-scale variations for UTCI. The results showed the following: (1) UTCI values decreased due to the increase of the latitude in China except for the Qinghai-Tibet Plateau. 69.5% of the total area of China experienced “no thermal stress” conditions in summer, whereas it was only 7.7% in winter. Additionally, the outdoor environment in summer had a wider “thermal comfort zone” than that in other seasons. (2) China was divided into a small number of regions with coherent UTCI changes using REOF analysis and K-means clustering algorithm. Eight homogeneous regions were obtained for annual UTCI. From spring to winter, the numbers of homogeneous regions were eight, nine, ten and seven, respectively. (3) Using EOF analysis, dominant patterns of UTCI in each region were extracted by the first two EOF modes, which accounted for >60% of the total variance. In the first mode, the significant upward trends of UTCI were detected in each region, suggesting the stronger outdoor heat stress. In the second mode, UTCI showed fluctuation between the cold and warm periods with different turning points between regions. Overall, the outdoor thermal comfort seemed to be improved more in high-latitude regions than that in low-latitude regions.
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•A REOF-cluster-EOF hybrid model was proposed to examine regional-scale variations.•The thermal comfort zone was the largest in summer and the smallest in winter.•Annual and seasonal UTCI exhibited the significant warming trend in each region.•UTCI fluctuated between cold and warm periods with different turning points.•The outdoor thermal comfort seemed to be improved more in high-latitude regions.
The integration of distributed generation (DG) sources can cause significant impacts on distribution networks, particularly the changes in magnitudes and directions of short circuit currents that may ...lead to false tripping or fail to trip over-current protection relays in the system. It is expensive and technically challenging to redesign/reconfigure and/or to replace the original protection system for a distribution network. If not appropriately handled, this issue can be a big hurdle before the wide use of DG. Based on the impact analysis of the number of DGs, their locations and capacities upon short circuit currents, this paper presents an optimal DG placement method to maximize the penetration level of DG in distribution networks without changing the original relay protection schemes. Genetic algorithm is used to find the optimal locations and sizes of DG in distribution networks. Simulation studies have been carried out on a three-feeder test distribution network and a widely used 33-node test system to show the effectiveness of the proposed method.
Mg-based materials are one of the most promising hydrogen storage candidates due to their high hydrogen storage capacity, environmental benignity, and high Clarke number characteristics. However, the ...limited thermodynamics and kinetic properties pose major challenges for their engineering applications. Herein, we review the recent progress in improving their thermodynamics and kinetics, with an emphasis on the models and the influence of various parameters in the calculated models. Subsequently, the impact of alloying, composite, and nano-crystallization on both thermodynamics and dynamics are discussed in detail. In particular, the correlation between various modification strategies and the hydrogen capacity, dehydrogenation enthalpy and temperature, hydriding/dehydriding rates are summarized. In addition, the mechanism of hydrogen storage processes of Mg-based materials is discussed from the aspect of classical kinetic theories and microscope hydrogen transferring behavior. This review concludes with an outlook on the remaining challenge issues and prospects.
Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction ...accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.
The satellite record since 1979 shows downward trends in Arctic sea ice extent in all months, which are smallest in winter and largest in September. Previous studies have linked changes in winter ...atmospheric circulation, anomalously cold extremes and large snowfalls in mid-latitudes to rapid decline of Arctic sea ice in the preceding autumn. Using observational analyses, we show that the winter atmospheric circulation change and cold extremes are also associated with winter sea ice reduction through an apparently distinct mechanism from those related to autumn sea ice loss. Associated with winter sea ice reduction, a high-pressure anomaly prevails over the subarctic, which in part results from fewer cyclones owing to a weakened gradient in sea surface temperature and lower baroclinicity over sparse sea ice. The results suggest that the winter atmospheric circulation at high northern latitudes associated with Arctic sea ice loss, especially in the winter, favors the occurrence of cold winter extremes at middle latitudes of the northern continents.
•An infiltration model for short-duration and high-intensity rainfall was proposed.•The model, derived from Richards’ equation, had good accuracy and adaptability.•The model simulate a range to cover ...observed infiltration rate fluctuation.
Many infiltration models have been proposed to simulate infiltration process. Different initial soil conditions and non-uniform initial water content can lead to infiltration simulation errors, especially for short-duration rainfall (SHR). Few infiltration models are specifically derived to eliminate the errors caused by the complex initial soil conditions. We present a simple analytical infiltration model for SHR infiltration simulation, i.e., Short-duration Infiltration Process model (SHIP model). The infiltration simulated by 5 models (i.e., SHIP (high) model, SHIP (middle) model, SHIP (low) model, Philip model and Parlange model) were compared based on numerical experiments and soil column experiments. In numerical experiments, SHIP (middle) and Parlange models had robust solutions for SHR infiltration simulation of 12 typical soils under different initial soil conditions. The absolute values of percent bias were less than 12% and the values of Nash and Sutcliffe efficiency were greater than 0.83. Additionally, in soil column experiments, infiltration rate fluctuated in a range because of non-uniform initial water content. SHIP (high) and SHIP (low) models can simulate an infiltration range, which successfully covered the fluctuation range of the observed infiltration rate. According to the robustness of solutions and the coverage of fluctuation range of infiltration rate, SHIP model can be integrated into hydrologic models to simulate SHR infiltration process and benefit the flood forecast.
In order to comprehensively evaluate the water resources carrying capacity in Xiong’an New Area, a system dynamics (SD) model was established to evaluate the regional water resources carrying ...capacity, for which several scenarios were designed: the original development scenario, the accelerated industrialization scenario, the environmental governance scenario, and the optimization development scenario. The results show that, compared with the original development scenario, the water resources carrying capacity in Xiong’an New Area can be improved in other scenarios, but a water supply and demand gap will be generated due to the lack of groundwater overdraft and a water transfer project. In 2026, under the accelerated industrialization scenario, the population carrying capacity will be 2.652 million, and the water supply and demand gap will be 1.13 × 108 m3; under the environmental governance scenario, the population carrying capacity will be 2.36 million, and the water supply and demand gap will be 0.44 × 108 m3; under the optimal development scenario, the population carrying capacity will be 2.654 million, and since the supply of water resources will be greater than the demand, there will not be a gap between supply and demand, making it the most feasible scenario to effectively alleviate the tension between industry restructuring, environmental management, and water resources development and utilization. The findings of this study can provide reference and decision support for optimizing regional water resources allocation and enhancing water resources carrying capacity in Xiong’an New Area.
Guangdong Province in China.
Water shortages due to the spatially uneven distribution of water resources have become the main obstacle to the sustainable development of regional society and the ...economy. To alleviate this problem, this study developed a framework including prediction, optimization, and decision-making models to allocate available water resources among the different sectors of the cities in the region. The framework was advantageous in efficiently predicting future water demand and supply for multiple cities, quantitatively reflecting the level of the spatial equilibrium of water allocation (SEWA) through coupling coordination degree (CCD), and achieving a higher level of SEWA rather than just the equitable water distribution.
The results indicated that: (i) by 2030, the deficit of water supply and demand of Guangdong Province would be further aggravated, with a water shortage rate of 4.18%; (ii) by optimal water allocation, the water shortage rate of Guangdong Province decreased to 1.56% and the level of SEWA improved significantly from moderate equilibrium to good equilibrium; and (iii) from 2018 to 2030, key water-saving sectors in different cities were identified, while the industrial sector had a higher water-saving intensity than other water use sectors. This study could provide references for integrated water allocation strategies to realize the coordinated development of socioeconomic and environmental systems in other regions of the world.
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•A spatial equilibrium-based allocation framework of regional water allocation was developed.•An efficient approach was proposed to predict future water supply and demand for multiple cities.•The framework can achieve a higher level of water resources spatial equilibrium.
Exploring inexpensive and high-performance nonprecious metal catalysts (NPMCs) to replace the rare and expensive Pt-based catalyst for the oxygen reduction reaction (ORR) is crucial for future ...low-temperature fuel cell devices. Herein, we developed a new type of highly efficient 3D porous Fe/N/C electrocatalyst through a simple pyrolysis approach. Our systematic study revealed that the pyrolysis temperature, the surface area, and the Fe content in the catalysts largely affect the ORR performance of the Fe/N/C catalysts, and the optimized parameters have been identified. The optimized Fe/N/C catalyst, with an interconnected hollow and open structure, exhibits one of the highest ORR activity, stability and selectivity in both alkaline and acidic conditions. In 0.1 M KOH, compared to the commercial Pt/C catalyst, the 3D porous Fe/N/C catalyst exhibits ∼6 times better activity (e.g., 1.91 mA cm–2 for Fe/N/C vs 0.32 mA cm–2 for Pt/C, at 0.9 V) and excellent stability (e.g., no any decay for Fe/N/C vs 35 mV negative half-wave potential shift for Pt/C, after 10000 cycles test). In 0.5 M H2SO4, this catalyst also exhibits comparable activity and better stability comparing to Pt/C catalyst. More importantly, in both alkaline and acidic media (RRDE environment), the as-synthesized Fe/N/C catalyst shows much better stability and methanol tolerance than those of the state-of-the-art commercial Pt/C catalyst. All these make the 3D porous Fe/N/C nanostructure an excellent candidate for non-precious-metal ORR catalyst in metal–air batteries and fuel cells.
In this paper we respond to calls for an institution-based perspective on strategy. With its emphasis upon mimetic, coercive, and normative isomorphism, institutional theory has earned a ...deterministic reputation and seems an unlikely foundation on which to construct a theory of strategy. However, a second movement in institutional theory is emerging that gives greater emphasis to creativity and agency. We develop this approach by highlighting co-evolutionary processes that are shaping the varieties of capitalism (VoC) in Asia. To do so, we examine the extent to which the VoC model can be fruitfully applied in the Asian context. In the spirit of the second movement of institutional theory, we describe three processes in which firm strategy collectively and intentionally feeds back to shape institutions: (1) filling institutional voids, (2) retarding institutional innovation, and (3) deploying institutional escape. We outline the key contributions contained in the articles of this Special Issue and discuss a research agenda generated by the VoC perspective.
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