Hydroponic and pot experiments were conducted to examine the effects of Fenton reagent on paddy rice plant growing in arsenic-contaminated soils. Fenton reagent significantly reduced arsenic phytotoxicity, uptake by the plants and accumulation in rice grain. This is attributed to oxidation of As 3+ to As 5+ by hydroxyl radicals and immobilization of arsenate by reacting with precipitating Fe 3+ to form practically insoluble compounds. Although this process enhanced the formation of Feenriched coatings on root surface, it appears that root plaque had limited effects on inhibiting As uptake since most of the young roots were not covered by iron plaque. It is more likely that As immobilization in the bulk soils play a major role in reducing As flux towards rhizosphere. The findings have implications for understanding As behavior in paddy field receiving rainwater-borne hydrogen peroxide and developing cost-effective techniques for reducing As level in rice grain produced from As-contaminated soils.

To improve the energy-efficiency of transport systems, it is necessary to investigate electric trains with on-board hybrid energy storage devices (HESDs), which are applied to assist the traction and recover the regenerative energy. In this paper, a time-based mixed-integer linear programming (MILP) model is proposed to obtain the energy-saving operation for electric trains with different constraints of on-board HESDs, such as their capacity, initial state of charge (SOC), and level of degradation. The proposed integrated power flow model based on the train longitudinal dynamics, power split of on-board HESDs, and line impedance is discretized and linearized, aiming to minimize the net energy consumption (NEC). The results reveal that on-board HESDs with a higher capacity does not necessarily lead to a higher energy-saving rate; a lower or excessive initial SOC could undermine the energy-saving potential; considering the long-term train operation, the degradation of the Li-ion battery will influence the energy-saving operation for electric trains, as well as result in an energy-saving rate that ranges from 41.57% to 31.90%. The practical data from Guangzhou Metro Line 7 were applied in the simulations, which enhanced the practicality and effectiveness of the proposed method.

Electric vehicles (EV) are growing fast in recent years with the widespread concern about carbon neutrality. The development of charging infrastructures needs to be in phase with EV both in terms of quantity and charging time to decrease the range anxiety of EV users and resource waste. This paper proposed a multistage and dynamic layout optimization model based on mixed integer linear programming (MILP) for EV charging stations (CSs) to minimize the total social costs (TSC) consisting of the detour cost of EV users and the construction, relocation, and operating cost of CSs. The charging satisfaction coefficient and M/M/S/K model of queuing theory has been introduced to determine the desirable charging supply. The spatial-temporal distribution of charging demand was modeled based on the behavior analysis of travelers and over the discrete-time intervals for a day. Comparison studies based on the Sioux Falls network reveal that TSC with a multistage optimization strategy will drop 8.79% from that with a one-time optimization strategy. Charging service quality, relocation cost, and road network scales have a significant impact on the optimization results according to the sensitivity analysis.

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In modern rail transportation, energy-efficient train control (EETC) is concerned with the optimal train speed trajectory or control strategies to achieve the minimum energy cost under various operation and traction constraints. This paper proposes an EETC model based on convex optimization so that the model can be rapidly solved by convex optimization algorithms. The high computational efficiency and robustness of the convex model can be verified by comparing the results achieved by the method proposed by this paper and other mainstream mathematical programming methods including mixed-integer linear programming (MILP) and Radau pseudospectral method (RPM). Based on the characteristics of convex optimization, the proposed method boasts more significant advantages over its counterparts in terms of computational efficiency in the promising online applications for automatic train control systems of various types of rail transportation.