Effects of side-stream operation on the mainstream biological phosphorus metabolic pathway for phosphorus recovery: Simulation by an extended ASM2d model.

An extended activated sludge model (E-ASM2d) was established by including the metabolic processes of double-layer extracellular polymeric substances (EPS) and glycogen-accumulating organisms (GAOs) into the existing ASM2d model for describing and predicting the metabolic processes of the side-stream phosphorus (P) recovery reactor. A sensitivity analysis of model parameters on SPO4(soluble phosphate), XLEPS (loosely-bound EPS), XTEPS (tightly-bound EPS), COD, and SNH4 (soluble ammonia nitrogen) outputs was conducted for identifying influential parameters. The predicted effluent values of COD, ammonia nitrogen (NH4), and P corresponded well with actual measured values and all the model performance coefficient values for COD, NH4, and P were higher than 0.65, implying the E-ASM2d model could accurately simulate the metabolic processes of the side-stream P recovery process under different COD:P ratio conditions. The variations in the mainstream biological P metabolic pathway under different COD:P conditions were investigated by the E-ASM2d model. At COD:P ratios of 30, 20, and 10, the values of fPP,TEPS (fraction of XTEPS in polyphosphate metabolic process) increased from 0.092, 0.094, and 0.096 in the initial phase to 0.107, 0.124, and 0.187 in the side-stream phase, respectively, demonstrating that the fraction of P removal by tightly-bound EPS was improved by the side-stream operation.

Development of a double-layer EPS-ASM2d model to illustrate the effect on mainstream biological phosphorus system in side-stream phosphorus recovery process.

In order to deeply investigate the influences of side-stream phosphorus (P) recovery operation on mainstream biological P removal system, an improved activated sludge model no. 2 (ASM2d) was established to illuminate the metabolic processes of P in a side-stream P recovery reactor. The improved ASM2d (named D-EPS-ASM2d) was established by extending of the P metabolic processes of double-layer extracellular polymeric substances (EPS) into conventional ASM2d model. The predicted effluent concentrations of COD, NH4, and TP by the D-EPS-ASM2d had good fits with measured values in the side-stream P recovery process. Comparing with conventional ASM2d, the likelihood values of D-EPS-ASM2d related to COD, NH4, and TP effluents were increased from 0.694, 0.837 and 0.762 to 0.868, 0.904 and 0.920, respectively, implying the simulation performances of D-EPS-ASM2d on nutrient removal processes were significantly improved. Besides, the calibrated values of fPP,TEPS was 0.09, 0.102 and 0.123 as side-stream volume (SSV) increasing from 0.3 to 0.9, implying the fraction of P removal by tightly-bound EPS was enhanced with the increase of SSV.

Study on the treatment of sudden cadmium pollution in surface water by a polymer enhanced ultrafiltration process.

The removal of cadmium(ii) pollution in surface water by a polymer enhanced ultrafiltration (PEUF) process was investigated. Three water soluble polymers, chitosan (CTS), polyvinyl alcohol (PVA) and polyacrylate sodium (PAAS), were selected for this study. Of the three polymers, PAAS had strong interactions with Cd2+, and the PEUF achieved a high removal of Cd2+; therefore, PAAS was used as a complexing agent for the simulated cadmium pollution experiment. Experiments were performed as a function of the aqueous pH, polymer/Cd2+ ratio (P/M), ionic strength and humic acid. Under optimum experimental conditions, the Cd2+ removal rate reached 100%. pH was the main factor affecting removal of Cd2+, which decreased to 60% at a pH of 4. The Cd2+ removal was found to decrease as NaCl and HA were added. The analysis showed that the mechanism of NaCl could be a compressed electric double layer, while the mechanism of HA and H+ was competitive complexation. Finally, UF membrane fouling, the dissociation of PAAS-Cd and the regeneration of PAAS were investigated. The results showed that the higher P/M was, the lower the pH, the higher the HA concentration, and the more serious the UF membrane fouling were. The dissociation rate of PAAS-Cd reached 99.8% at a pH of 2.5. When the P/M was 5, the removal rate of Cd reached 99.6% with the addition of 20% new PAAS in the regenerate. This result showed that the PEUF process could be a promising method for removing Cd pollution in surface water.

Effects of various side stream phosphorus recovery volume on the performance and microbial structures of mainstream biological system.

The effects of three side stream phosphorous recovery volume on the performance and microbial structure of biological phosphorous removal system were investigated. Results showed that the removal of COD and nitrogen had no significant impacts by side stream operation, but the removal of phosphorous were gradually enhanced with the increase in side stream volume (SSV). The secretion of extracellular polymeric substance (EPS) were variously promoted at the stripping period. However, with the increase in SSV, the inhibition on EPS and phosphorus-accumulating organisms (PAOs) phosphorous absorption were severe and the restoration were tougher. The high throughout 16S rRNA gene sequencing revealed the succession of microbial population were significantly effected by side stream operation. The relative abundances of PAOs reduced to 0.17%, 0.09% and 0.07% with 30%, 60% and 90% side stream operations, respectively. At the restoration period, the relative abundance could restore to 95.4%, 65% and 38% initial values, respectively. The relative abundances of glycogen-accumulating organisms were variously enhanced under various SSV conditions. In conclusion, at SSV of 60%, more abundant recovered phosphorous could be obtained and had slighter and reversible effects on activated sludges. The SSV of 60% was the applicable SSV for phosphorous recovery from the biological phosphorus removal system.

La-based-adsorbents for efficient biological phosphorus treatment of wastewater: Synergistically strengthen of chemical and biological removal.

The present work demonstrated the invention of synergistically strengthen of chemical and biological removal of phosphorus (P) in biological wastewater treatment, which was achieved by exposure the bioreactors to different levels of La-based-adsorbents. We fabricated a high-performance La2O2CO3 micro-adsorbent (H-La2O2CO3) and added it into sequencing batch reactors. When activated sludge was exposed to 40 mg/L H-La2O2CO3 for 40 d, effluent total phosphorus (TP) concentration significantly decreased to approximately 0.18 mg/L, with the steady removal efficiency of 96.4%, which is superior to the biological phosphorus removal (BPR). The effect of H-La2O2CO3 dosages on P removal in biological wastewater treatment was also detailedly investigated. The H-La2O2CO3 adsorbent could not only capture P by chemical bonding itself, but also increased protein (PN) contents of extracellular polymeric substances (EPS) and changed the functional group of EPS to chemically adsorb P. Additionally, the results of 16s rDNA molecular analysis revealed that the species richness and microbial diversity varied with the different dosages of adsorbent. Sequence analyses showed that the appropriate concentration of H-La2O2CO3 addition increased the contents of several polyphosphate accumulating organisms (PAOs) at genus level in sludge.

Identification of Genome Sequences of Polyphosphate-Accumulating Organisms by Machine Learning.

In the field of sewage treatment, the identification of polyphosphate-accumulating organisms (PAOs) usually relies on biological experiments. However, biological experiments are not only complicated and time-consuming, but also costly. In recent years, machine learning has been widely used in many fields, but it is seldom used in the water treatment. The present work presented a high accuracy support vector machine (SVM) algorithm to realize the rapid identification and prediction of PAOs. We obtained 6,318 genome sequences of microorganisms from the publicly available microbial genome database for comparative analysis (MBGD). Minimap2 was used to compare the genomes of the obtained microorganisms in pairs, and read the overlap. The SVM model was established using the similarity of the genome sequences. In this SVM model, the average accuracy is 0.9628 ± 0.019 with 10-fold cross-validation. By predicting 2,652 microorganisms, 22 potential PAOs were obtained. Through the analysis of the predicted potential PAOs, most of them could be indirectly verified their phosphorus removal characteristics from previous reports. The SVM model we built shows high prediction accuracy and good stability.