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Process monitoring models play an increasingly indispensable role in promptly differentiating faults within the wastewater treatment process to maintain a safe state. The accuracy and time overhead are crucial indicators in judging whether models results are excellent or not. In terms of accuracy, deep learning methods excel, because of their generalized approximation and strong learning capabilities that enable them to infinitely approach an ideal level of monitoring accuracy. Meanwhile, they also have large computational loads that generates significant time overhead, which poses challenges for real-time monitoring of the wastewater treatment process. Hence, a novel process monitoring method called Time-Stacked Broad Learning System (Time-SBLS) is developed to alleviate these concerns in an effective and accurate manner. Time-SBLS leverages the efficiency of the BLS while incorporating the residual mechanism and time lag idea to capture necessary nonlinear features and time correlation associated with the fault detection accuracy better. Furthermore, another advantage of Time-SBLS is its inherited efficiency from BLS regarding time overhead, which is minimized by utilizing the pseudo-inverse technique to calculate weight parameters. Experimental findings on the Benchmark platform reveal that Time-SBLS offers considerable advantages in terms of accuracy and network time overhead compared to other state-of-the-art approaches. • Time-SBLS is applied for the first time to the wastewater treatment process. • Time-SBLS model can achieve satisfactory monitoring accuracy. • Time-SBLS overcomes the limitations of some deep learning networks. • Time-SBLS is compatible with accuracy and time overhead simultaneously. [ABSTRACT FROM AUTHOR]

Abstract: Higher contents of and SS in wastewater hamper the anaerobic digestion; necessitating its pretreatment to reduce them. This study reveals optimization of struvite/MAP precipitation protocol followed by anaerobic digestion of pretreated swine wastewater for pollutants removal. Levels of different treatments: stirring speeds, 400 and 160rpm; pH values, 9.0, 9.5, 10.0, 10.5, 11.0 and 11.5; and P:Mg:N ratios, 1:1:1.2, 1:1:1.7, 1:1:2.2, 1:1:2.7, 1:1:4.0 and 1:1:5.0 were evaluated for MAP crystallization. Among various combinations, protocol comprising of initial 10min stirring at 400rpm followed by 160rpm for 30min, pH 10.0, and P:Mg:N ratio 1:1:1.2 rendered the best removal efficiency for , , COD, TC and TOC. Subsequent anaerobic biodegradation revealed superiority of MAP supernatant over raw swine wastewater for methane yield and , , COD, TC and TOC removals. It suggests that struvite precipitation as pretreatment to anaerobic digestion is highly effective and advantageous in wastewater treatment. [Copyright &y& Elsevier]

Abstract: In view of the existing technical problems about treatment of heavy metal pollution, a new organic heavy metal chelator—dipropyl dithiophosphate has been developed. This paper focuses on the mechanism about the laboratory synthesis of dipropyl dithiophosphate and chelate heavy metal, discusses the effects of pH value, added quantity of chelator, reactive time and coexistence of several heavy metal ions on the treatment effectiveness, and compares the stability of chelate complex with conventional neutral precipitation method. The results of the experiment show that, within the scope of pH 3–6, for the wastewater with the concentration of lead, cadmium, copper and mercury being 200mg/L, dipropyl dithiophosphate enjoys a removal rate about these elements up to over 99.9%, and the concentrations of the lead, cadmium, copper and mercury in the wastewater after treatment are less than 1, 0.1, 0.5 and 0.05mg/L, respectively, which meet the limit value of concentration stipulated in the Integrated Wastewater Discharge Standard (GB8978-1996). And the treatment effectiveness are not affected by pH value and coexistent heavy metal ions, which makes up the deficiency that neutral precipitation must be used under the condition of high alkalinity. The optimum quantity of dipropyl dithiophosphate chelator added is 1.2 times as much as stoichiometric amount and the optimum reactive time is 20min for lead, cadmium and copper, and 30min for mercury. Within the scope of pH 3–9, each heavy metal ion release of chelate complex will decrease along with increased pH value. But under any pH conditions, the release of heavy metal ions in hydroxide is far higher than that in chelate complex, therefore reducing the risk of polluting the environment again. [Copyright &y& Elsevier]

Abstract: Three Upflow Anaerobic Sludge Blanket (UASB) reactors were compared for Anammox enrichment using synthetic wastewater with Spherical Plastic (SP) and Bamboo Charcoal (BC) addition, and without carrier (CK). After four months of operation, the Anammox activity occurred in all reactors allowing continuous removal of ammonium and nitrite. Ammonium and nitrite removal efficiencies were all higher than 98% in steady phase with the effluent concentrations below 1mgL−1. The start-up time could be shortened from 117 to 97d in CK and SP reactor to 85d in BC amendment reactor. Quantitative PCR (q-PCR) analyses indicated a significant increase in the number of Anammox bacteria in BC amended reactor as compared with CK and SP during the entire start-up periods. The copy numbers of Anammox of 16SrRNA gene in the reactor with BC amendment could reach up to 6×109 copiesg−1 Volatile Suspended Solids, around 22.5times and 12.3times greater than that in CK and SP reactor, respectively. BC addition could accelerate the start-up of Anammox and significantly increase the Anammox bacteria number. [Copyright &y& Elsevier]