Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.

Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predicting treated greywater quality is of great significance for water reuse. In this work, machine learning models were developed for simulating and predicting linear alkylbenzene sulfonate (LAS) removal using 152-days collected data from a battled oxygenic microalgal-bacteria biofilm reactor (MBBfR).

Microalgal extracellular polymeric substances (EPS) and their roles in cultivation, biomass harvesting, and bioproducts extraction.

Microalgae extracellular polymeric substances (EPS) are complex high-molecular-weight polymers and the physicochemical properties of EPS strongly affect the core features of microalgae cultivation and resource utilization. Revealing the key roles of EPS in microalgae life-cycle processes in an interesting and novelty topic to achieve energy-efficient practical application of microalgae. This review found that EPS showed positive effect in non-gas uptake, extracellular electron transfer, toxicity resistance and heterotrophic symbiosis, but negative impact in gas transfer and light utilization during microalgae cultivation.

Differentiation and quantification of extracellular polymeric substances from microalgae and bacteria in the mixed culture.

Extracellular polymeric substances (EPS) play significant roles in the formation, function, and interactions of microalgal-bacteria consortia. Understanding the key roles of EPS depends on reliable extraction and quantification methods, but differentiating of EPS from microalgae versus bacteria is challenging. In this work, cation exchange resin (CER) and thermal treatments were applied for total EPS extraction from microalgal-bacteria mixed culture (MBMC), flow cytometry combined with SYTOX Green staining was applied to evaluate cell disruption during EPS extraction, and auto-fluorescence-based cell sorting (AFCS) was used to separate microalgae and bacteria in the MBMC.

Mass Flow and Metabolic Pathway of Nonaeration Greywater Treatment in an Oxygenic Microalgal-Bacterial Biofilm.

A symbiotic microalgal-bacterial biofilm can enable efficient carbon (C) and nitrogen (N) removal during aeration-free wastewater treatment. However, the contributions of microalgae and bacteria to C and N removal remain unexplored. Here, we developed a baffled oxygenic microalgal-bacterial biofilm reactor (MBBfR) for the nonaerated treatment of greywater.

Response of antibiotic resistance genes expression and distribution on extracellular polymeric substances and microbial community in membrane biofilm during greywater treatment.

This study evaluated how organic loading affects antibiotic resistance genes (ARGs) expression and distribution in the membrane biofilm. Organic surface loading rate of 4.65 g chemical oxygen demand (COD)/m·d achieved the maximum biofilm thickness, concentration and linear alkylbenzene sulfonate (LAS) removal ratio of 136.

Microbial niches and dynamics of antibiotic resistance genes in a bio-enhanced granular-activated carbon biofilm treating greywater.

Accumulation and transmission of antibiotic resistance genes (ARGs) in greywater treatment systems present risks for its reuse. In this study, a gravity flow self-supplying oxygen (O) bio-enhanced granular activated carbon dynamic biofilm reactor (BhGAC-DBfR) was developed to treat greywater. Maximum removal efficiencies were achieved at saturated/unsaturated ratios (R) of 1:1.

Distribution and dynamics of antibiotic resistance genes in a three-dimensional multifunctional biofilm during greywater treatment.

Antibiotic resistance genes (ARGs) have been identified as serious threats to public health. Despite the widespread in various systems, dynamics of ARGs in three-dimensional multifunctional biofilm (3D-MFB) treating greywater are largely undefined. This work tracked the distributions and dynamics of eight target genes (intI1, korB, sul1, sul2, tetM, ermB, bla and qnrS) in a 3D-MFB during greywater treatment.

pH-dependent microbial niches succession and antibiotic resistance genes distribution in an oxygen-based membrane biofilm reactor treating greywater.

System pH is found to crucially affect biofilm growth and microorganisms' activity in the biofilm-based wastewater treatment system. This study investigated the pH-dependent pollutants removal, microbial niches succession and antibiotic resistance genes (ARGs) accumulation in an oxygen-based membrane biofilm reactor treating greywater. Results indicated that neutral conditions achieved the highest biofilm concentration and living cells, which enabled the highest pollutants removal rates; multifarious functional groups in biofilm enabled pollutants adsorption, which favored its continuous bio-removal.

Removal kinetics of linear alkylbenzene sulfonate in a batch-operated oxygen based membrane biofilm reactor treating greywater: Quantitative differentiation of adsorption and biodegradation.

Oxygen-based membrane biofilm reactor (O-MBfR) is a unique technique for high linear alkylbenzene sulfonate (LAS)-containing greywater (GW) treatment. Despite the efficient removal of LAS, the dynamics of how it is taken up and the quantitative differentiation of adsorption and biodegradation are largely undefined. In this study, we tracked the fate of LAS, chemical oxygen demand and nitrogen in various systems: GW, GW with inactivated sludge (InAS) and GW with activated sludge (AS).

Assessment and optimization of the oxygen based membrane biofilm reactor as a novel technology for source-diverted greywater treatment.

The oxygen based membrane biofilm (O-MBfR) has been proved to be a novel technology in treating greywater (GW) and response surface methodology (RSM) was used to model the removal of chemical oxygen demand (COD) and total nitrogen (TN) with operation parameters COD/TN ratio, system pH and lumen air pressure (LAP). Results indicated that the all target single factors affect GW treatment efficiency, and the regression model with central composite design (CCD) showed good agreement with the experimental results with high R and R2 adj values (all >0.97) for all the target responses.