Purification effect and microbial community structure of bio filter on rural dispersed sewage.

Taking rural dispersed sewage for research objects, the treatment effect and microbial community structure characteristics of a bio filter (BF) reactor was studied. At fixed time and location, the removal efficiencies of common pollutants were investigated. By using high-throughput sequencing method, the heterogeneities of microbial community structure in fillers and plant roots were analyzed. The results showed that the average annual removal rates of CODCr, NH3-N, TN, and TP by the BF were 83.10 %, 65.67 %, 60.25 %, and 80.32 % respectively, and the effluent could reach the first grade of the water pollutant discharge standard of rural sewage treatment facility (DB51/2626-2019). During the sewage treatment process, Scindapsus could effectively establish complex and stable microbial communities, and could better degrade pollutants, especially nitrogen removal. The dominant microbial communities were more than 11 phyla and 19 classes. At the genus level, the dominant bacteria included Nitrospira, Arthrobacter, Rhodoplanes, etc.

Optimization pilot scale study on ammonia nitrogen removal by bio filter.

In order to obtain the optimal conditions for ammonia nitrogen (AN) wastewater treatment by bio filter (BF), the effects of ratio of carbon to nitrogen (C/N), pH, and hydraulic load (HL) on the AN degradation were studied by Response Surface Methodology (RSM). Central Composite Design (CCD) experiments were conducted, and the response of the AN removal rates were fitted to a second-order polynomial model. The analysis of variance showed that the model was accurate and reliable. Through model fitting, the optimal condition for AN removal was: C/N of 18.95, pH of 7.78, and HL of 1.04 d-1. The maximum AN removal rate predicted by the model was 91.90%, accorded with the experimental verification value of 91.37% under the optimal condition. The research provided valuable demonstration for optimizing process parameters on AN removal in BF.

Optimization of Nanofiltration Hollow Fiber Membrane Fabrication Process Based on Response Surface Method.

Layer-by-layer (LBL) self-assembly technology has become a new research hotspot in the fabrication of nanofiltration membranes in recent years. However, there is a lack of a systematic approach for the assessment of influencing factors during the membrane fabrication process. In this study, the process optimization of LBL deposition was performed by a two-step statistical method. The multiple linear regression was performed on the results of single-factor experiments to determine the major influencing factors on membrane performance, including the concentration of Poly (allylamine hydrochloride) (PAH), glutaraldehyde, and the NaCl concentration in PAH solution. The Box-Behnken response surface method was then used to analyze the interactions between the selected factors, while their correlation with the membrane performance was obtained by polynomial fitting. The R2 value of the regression models (0.97 and 0.94) was in good agreement with the adjusted R2 value (0.93 and 0.86), indicating that the quadratic response models were adequate enough to predict the membrane performance. The optimal process parameters were finally determined through dual-response surface analysis to achieve both high membrane permeability of 14.3 LMH·MPa-1 and MgSO4 rejection rate of 90.22%.