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Reactive blue 49 was removed from aqueous solution by biosorption using powder waste sludge composed of Saccharomyces cerevisiae from the beer-brewing industry. The effect of initial pH, temperature and the biosorption thermodynamics, equilibrium, kinetics was investigated in this study. It was found that the biosorption capacity was at maximum at initial pH 3, that the effect of temperature on biosorption of reactive blue 49 was only slight in relation to the large biosorption capacity (25°C, 361 mg g(-1)) according as the biosorption capacity decreased only 43 mg g(-1) at the temperature increased from 25 to 50°C. The biosorption was spontaneous, exothermic in nature and the dye molecules movements decreased slightly in random at the solid/liquid interface during the biosorption of dye on biosorbents. The biosorption equilibrium data could be described by Freundich isotherm model. The biosorption rates were found to be consistent with a pseudo-second-order kinetics model. The functional group interaction analysis between waste beer yeast sludge and reactive blue 49 by the aid of Fourier transform infrared (abbr. FTIR) spectroscopy indicated that amino components involved in protein participated in the biosorption process, which may be achieved by the mutual electrostatic adsorption process between the positively charged amino groups in waste beer yeast sludge with negatively charged sulfonic groups in reactive blue 49.

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Water quality sampling and monitoring are fundamental to water environmental protection. The purpose of this study was to develop a water quality sampling and multi-parameter monitoring system mounted on a multi-rotor unmanned aerial vehicle (UAV). The system consisted of the UAV, water sampling and multi-parameter detection device, and path planning algorithm. The water sampling device was composed of a rotating drum, a direct current (DC) reduction motor, water suction hose, high-pressure isolation pump, sampling bottles, and microcontroller. The multi-parameter detection device consisted of sensors for potential of hydrogen (pH), turbidity, total dissolved solids (TDS), and a microcontroller. The flight path of the UAV was optimized using the proposed layered hybrid improved particle swarm optimization (LHIPSO) and rapidly-exploring random trees (RRT) obstacle avoidance path planning algorithm, in order to improve the sampling efficiency. Simulation experiments were conducted that compared the LHIPSO algorithm with the particle swarm optimization (PSO) algorithm and the dynamic adjustment (DAPSO) algorithm. The simulation results showed that the LHIPSO algorithm had improved global optimization capability and stability compared to the other algorithms, validating the effectiveness of the proposed algorithm. Field experiments were conducted at an aquaculture fish farm, and the device achieved real-time monitoring of three water quality parameters (pH, TDS, turbidity) at depths of 1 m and 2 m. A rapid analysis of three parameters (ammonia nitrogen, nitrite, dissolved oxygen) was performed in the laboratory on the collected water samples, and validated the feasibility of this study.