Phosphorus removal and recovery from domestic wastewater is urgent nowadays. A novel process of nutrients removal coupled with phosphorus recovery from domestic sewage was proposed and optimization of induced crystallization reaction was performed in this study. The results showed that 92.3% of phosphorus recovery via induced Hydroxyapatite crystallization was achieved at the optimum process parameters: reaction time of 80 min, seed crystal loads of 60 g/L, pH of 8.5, Ca/P mole ratio of 2.0 and 4.0 L/min aeration rate when the PO43--P concentration was 10 mg/L in the influent, displaying an excellent phosphorus recovery performance. Importantly, it was found that the effect of reaction temperature on induced Hydroxyapatite crystallization was slight, thus favoring practical application of phosphorus recovery method described in this study. From these results, the proposed method of induced HAP crystallization to recover phosphorus combined with nutrients removal can be an economical and effective technology, probably favoring the water pollution control and phosphate rock recycle.

Dye wastewater is one of typically non-biodegradable industrial effluents. A new process linking Fenton’s oxidation with biological oxidation proposed in this study was investigated to degrade the organic substances from real dye wastewater. During the combination process, the Fenton’s oxidation process can reduce the organic load and enhance biodegradability of dye wastewater, which is followed by biological aerated filter (BAF) system to further remove organic substances in terms of discharge requirement. The results showed that 97.6% of chemical oxygen demand (COD) removal by the combination process was achieved at the optimum process parameters: pH of 3.5, H2O2 of 2.0 mL/L, Fe(II) of 500 mg/L, 2.0 h treatment time in the Fenton’s oxidation process and hydraulic retention time (HRT) of 5 h in the BAF system. Under these conditions, COD concentration of effluent was 72.6 mg/L whereas 3020 mg/L in the influent, thus meeting the requirement of treated dye wastewater discharge performed by Chinese government (less than 100 mg/L). These results obtained here suggest that the new process combining Fenton’s oxidation with biological oxidation may provide an economical and effective alternative for treatment of non-biodegradable industrial wastewater.

Azo dye wastewater treatment is urgent necessary nowadays. Electrochemical technologies commonly enable more efficient degradation of recalcitrant organic contaminants than biological methods, but those rely greatly on the energy consumption. A novel process of biofilm coupled with electrolysis, i.e., bioelectrochemical system (BES), for methyl orange (MO) dye wastewater treatment was proposed and optimization of main influence factors was performed in this study. The results showed that BES had a positive effect on enhancement of color removal of MO wastewater and 81.9% of color removal efficiency was achieved at the optimum process parameters: applied voltage of 2.0 V, initial MO concentration of 20 mg/L, glucose loads of 0.5 g/L and pH of 8.0 when the hydraulic retention time (HRT) was maintained at 3 d, displaying an excellent color removal performance. Importantly, a wide range of effective pH, ranging from 6 to 9, was found, thus greatly favoring the practical application of BES described here. The absence of a peak at 463 nm showed that the azo bond of MO was almost completely cleaved after degradation in BES. From these results, the proposed method of biodegradation combined with electrochemical technique can be an effective technology for dye wastewater treatment and may hopefully be also applied for treatment of other recalcitrant compounds in water and wastewater.

Accurate information about the vehicle state such as sideslip angle is critical for both advanced assisted driving systems and driverless driving. These vehicle states are used for active safety control and motion planning of the vehicle. Since these state parameters cannot be directly measured by onboard sensors, this paper proposes an adaptive estimation scheme in case of unknown measurement noise. Firstly, an estimation method based on the bicycle model is established using a square-root cubature Kalman filter (SQCKF), and secondly, the expectation maximization (EM) approach is used to dynamically update the statistic parameters of measurement noise and integrate it into SQCKF to form a new expectation maximization square-root cubature Kalman filter (EMSQCKF) algorithm. Simulations and experiments show that EMSQCKF has higher estimation accuracy under different driving conditions compared to the unscented Kalman filter.