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Electrochemical conversion of CO2 into liquid fuels such as ethanol, powered by renewable electricity, is an efficient strategy for CO2 utilization to produce high value-added products. In this work, we discovered that the primary C2+ product could be switched from gaseous ethylene to liquid ethanol by directly increasing the CO2 pressure when Cu2O@Cu with a hollow sphere morphology was adopted as the catalyst. The faradaic efficiency (FE) of ethanol reached as high as 36.6% at a low overpotential of −1.0 V vs. Ag/AgCl (−0.48 V vs. RHE) at 100 bar, which was 4.6 times higher than that of 1 bar. Moreover, faster kinetics and lower overpotential for ethanol formation were obtained at high CO2 pressures. In situ Raman spectroscopy studies at different pressures in combination with density functional theory calculations demonstrated that the *CO surface coverage was increased significantly at increased CO2 pressure, which is responsible for facilitating ethanol formation during the electrochemical CO2RR. This study provides a novel and promising strategy for the selective production of ethanol on Cu-based catalysts by facilely adjusting the CO2 pressure. [ABSTRACT FROM AUTHOR]

Urban road facilities are typically shared by heterogeneous traffic, such as cars, buses, and bicycles. This paper investigates the car and bicycle traffic at the network level by extending the 3D-MFD model to the car-bicycle network. Statistical 3D-MFDs for the car-bicycle traffic are proposed and empirically estimated for three selected networks in Shanghai. Simulation-based 3D-MFDs are used to determine the network bicycle capacity and validate statistical 3D-MFDs. Estimation results quantify negative marginal effects of car and bicycle density on network car speeds, and confirm the negative effect of bi-modal speed difference on bicycle traffic. When looking into the predicted results of 3D-MFDs, the maximum bi-modal production changes with the accumulation of bicycles, indicating car-bicycle interactions within the network. Few empirical observations are in the optimum operation regime, which indicate the potential of improving the multi-modal networks. Findings of this study can benefit network designs and traffic operations, such as adjusting separation types, implementing stricter bicycle management, and extending bicycle priority in certain areas. [ABSTRACT FROM AUTHOR]

Dynamic congestion pricing has attracted increasing attentions during the recent years. Nevertheless, limited research has been conducted to address the dynamic tolling scheme at the network level, such as to cooperatively manage two alternative networks with heterogeneous properties, e.g., the two-layer network consisting of both expressway and arterial network in the urban areas Recently, the macroscopic fundamental diagram (MFD) developed by both field experiments and simulation tests illustrates a unimodal low-scatter relationship between the mean flow and density network widely, providing the network traffic state is roughly homogeneous. It reveals traffic flow properties at an aggregated level and sheds light on dynamic traffic management of a large network. This paper proposes a bilevel programming toll model, incorporating MFD to solve the unbalanced flow distribution problem within the two-layer transportation networks. The upper level model aims at minimizing the total travel time, while the lower level focuses on the MFD-based traffic assignment, which extends the link-based traffic assignment to network wide level. Genetic algorithm (GA) and the method of successive average were adopted for solving the proposed model, on which an online experimental platform was established using VISSIM, MATLAB, and Visual Studio software packages. The results of numerical studies demonstrate that the total travel time is decreased by imposing the dynamic toll, while the total travel time savings significantly outweigh the toll paid. Consequently, the proposed dynamic toll scheme is believed to be effective from both traffic and economic points of view., 1. Introduction Congestion pricing has been regarded as an effective traffic demand management policy that has been applied in many cities, among which Singapore was the first one to impose [...]

Operational performance optimization of signalized intersections is one of the most important tasks for traffic engineers and researchers. To compensate for the limitations of practical implementation, simulation software packages have been widely used to evaluate different optimization strategies and thus to improve the efficiency of the intersections as well as the entire network. However, for the existing optimization studies on signalized intersections, the relationships among various optimization measures and the combination of strategies have not been fully investigated. In this paper, uniform design experimentation was introduced to combine different optimization measures into strategies and achieve the minimum time cost in model construction. VISSIM software package was then calibrated and used to evaluate various optimization strategies and identify the one with the best measurement of performance, namely, control delay at the signalized intersection. By taking a representative congested intersection in Shanghai as a case study, the optimal strategy was identified to reduce the overall control delay by 27.3%, which further verified the modeling capability of the proposed method., 1. Introduction Optimizing operation at signalized intersections has long been an issue for congestion mitigation in urban areas. Microsimulation packages, such as VISSIM, TSIS/CORSIM, AIMSUN, and PARAMICS, were developed and [...]

With the increasing popularity of smart phones, Parking Reservation System (PRS) becomes practical to reduce the travel time in cruising for vacant spaces. The aim of this study is to assess the impact of PRS explicitly. This paper was started with analyzing the processes of cruising for vacant spaces and making parking reservation decisions. The vehicles were divided into two categories: the intelligent vehicles and the regular ones. Only the intelligent vehicles have the ability to make a parking reservation beforehand, while the regular ones have to cruise for vacant spaces. All involved components were treated as different agents, including vehicles, parking lots, network, and management center. Based on this, agent-based simulation was introduced to evaluate the performances of the scenarios with different penetration rates. The simulation results indicate the average travel time increases with the improvement of the penetration rates for the regular vehicles. The assessment method presented in this study would assist in promoting the performances of PRS in urban areas., 1. Introduction The shortage of parking spaces is one of the major ignored transportation issues in urban areas [1,2], mainly because the situation gained less attention than the roadway planning [...]