Abstract The adoption of electric vehicles (EVs) is an important way to reduce air pollution and greenhouse gas emissions. The city of Shenzhen, in southern China, has focused on developing policies to encourage EV implementation over the past decade and now has the most EVs of any city in the world, including the largest e‐bus and e‐taxi fleets. This paper reviews Shenzhen's innovative incentive policies and business models with respect to the potential for other cities and regions to learn from the city's experiences. Subsidies for the purchase and use of EVs, the construction of charging facilities, and the provision of services followed an inverse U‐shaped trend that initially rose to encourage early adoption before decreasing as the market matured. Additional incentives included preferential vehicle licensing, parking privileges, and road access. Furthermore, the city adopted a business model that incentivized cooperation between third‐party financial institutions, EV manufacturers, and charging facility operators to reduce the initial financial burden and risk of EV adoption by pooling purchasing power through leasing and vehicle sharing while disassociating vehicle and battery maintenance. Although Shenzhen's experience has unique aspects that cannot easily be replicated, such as a strong financial position of the government, it offers two important lessons for other cities around the globe: (a) incentivize the whole EV value chain in order to avoid bottlenecks and (b) use innovative business models that mobilize both public and private resources by distributing both risks and rewards. This article is categorized under: Energy and Transport > Economics and Policy Energy and Transport > Economics and Policy Energy Research and Innovation > Climate and Environment
In recent years, the mine tunneling method and the new Austrian tunneling method have been considered the main theories of tunneling approaches in China. It is difficult for the traditional technique to overcome the large deformation problems imposed by complex geological conditions of mountain soft rock tunneling. Hence, the compensation excavation method has been proposed to solve this issue under the consideration that all damage in tunneling originates from the excavation. It uses supportive strategies to counteract the excavation effects successfully. This paper provides an overview of the fundamental ideas of the compensation excavation method, methodologies, and field applications. The scientific validity and feasibility of the compensation excavation method were investigated through the practical engineering study of the Muzhailing and Changning tunnels.
In this article, we present data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media using Koopman operators. Different from the case of autonomous dynamical systems, the Koopman operator family of nonautonomous dynamical systems significantly depend on a time pair. In order to effectively estimate the time-dependent Koopman operators, a moving time window is used to decompose the snapshot data, and the extended dynamic mode decomposition method is applied to computing the Koopman operators in each local temporal domain. Many physical properties in multiscale media often vary in very different scales. In order to capture multiscale information well, the dimension of collected data may be high. To accurately construct the models of dynamical systems in multiscale media, we use high spatial dimension of observation data. It is challenging to compute the Koopman operators using the very high dimensional data. Thus, the strategy of reduced-order modeling is proposed to treat the difficulty. The proposed reduced-order modeling includes two stages: offline stage and online stage. In offline stage, a block-wise low rank decomposition is used to reduce the spatial dimension of initial snapshot data. For the nonautonomous dynamical systems, real-time observation data may be required to update the Koopman operators. The online reduced-order modeling is proposed to correct the offline reduced-order modeling. Three methods are developed for the online reduced-order modeling: fully online, semi-online and adaptive online. The adaptive online method automatically selects the fully online or semi-online and can achieve a good trade-off between modeling accuracy and efficiency.
Abstract This work presents a new reactive transport framework that combines a powerful geochemistry engine with advanced numerical methods for flow and transport in subsurface fractured porous media. Specifically, the PhreeqcRM interface (developed by the USGS) is used to take advantage of a large library of equilibrium and kinetic aqueous and fluid-rock reactions, which has been validated by numerous experiments and benchmark studies. Fluid flow is modeled by the Mixed Hybrid Finite Element (FE) method, which provides smooth velocity fields even in highly heterogenous formations with discrete fractures. A multilinear Discontinuous Galerkin FE method is used to solve the multicomponent transport problem. This method is locally mass conserving and its second order convergence significantly reduces numerical dispersion. In terms of thermodynamics, the aqueous phase is considered as a compressible fluid and its properties are derived from a Cubic Plus Association (CPA) equation of state. The new simulator is validated against several benchmark problems (involving, e.g., Fickian and Nernst-Planck diffusion, isotope fractionation, advection-dispersion transport, and rock-fluid reactions) before demonstrating the expanded capabilities offered by the underlying FE foundation, such as high computational efficiency, parallelizability, low numerical dispersion, unstructured 3D gridding, and discrete fraction modeling.
Abstract Oxygen evolution reaction catalysts capable of working efficiently in acidic media are highly demanded for the commercialization of proton exchange membrane water electrolysis. Herein, we report a Zn-doped RuO 2 nanowire array electrocatalyst with outstanding catalytic performance for the oxygen evolution reaction under acidic conditions. Overpotentials as low as 173, 304, and 373 mV are achieved at 10, 500, and 1000 mA cm −2 , respectively, with robust stability reaching to 1000 h at 10 mA cm −2 . Experimental and theoretical investigations establish a clear synergistic effect of Zn dopants and oxygen vacancies on regulating the binding configurations of oxygenated adsorbates on the active centers, which then enables an alternative Ru−Zn dual-site oxide path of the reaction. Due to the change of reaction pathways, the energy barrier of rate-determining step is reduced, and the over-oxidation of Ru active sites is alleviated. As a result, the catalytic activity and stability are significantly enhanced.
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