This study used pilot-scale high-rate algae ponds to assess algal–bacteria biomass productivity and wastewater nutrient removal as well as the impact of mechanical and hydrothermal pretreatments on biomass disintegration, methane production kinetics, and anaerobic digestion (AD) energy balance. Mechanical pretreatment had a minor effect on biomass disintegration and methane production. By contrast, hydrothermal pretreatment significantly reduced particle size and increased the solubilized organic matter content by 3.5 times. The methane yield and production rate increased by 20–55% and 20–85%, respectively, with the highest values achieved after pretreatment at 121 °C for 60 min. While the 1st-order and pseudo-1st-order reaction equation models fitted methane production from untreated biomass best (R2 > 0.993), the modified Gompertz sigmoidal-type model provided a superior fit for hydrothermally pretreated algae (R2 ≥ 0.99). The AD energy balance revealed that hydrothermal pretreatment improved the total energy output by 25–40%, with the highest values for volume-specific and mass-specific total energy outputs reaching 0.23 kW per digester m3 and 2.3 MW per ton of biomass volatile solids. Additionally, net energy recovery (energy output per biomass HHV) increased from 20% for untreated algae to 32–34% for hydrothermally pretreated algae, resulting in net energy ratio and net energy efficiency of 2.14 and 68%, respectively.

E. coli O157:H7 is a foodborne pathogen that constitutes a global threat to human health. However, the quantification of this pathogen in food and environmental samples may be problematic at the low cell numbers commonly encountered in environmental samples. In this study, we used recombinase polymerase amplification (RPA) for the detection of E. coli O157:H7, real-time quantitative PCR (qPCR) for quantification, and droplet digital PCR (ddPCR) for absolute and accurate quantification of E. coli O157:H7 from spiked and environmental samples. Primer and probe sets were used for the detection of stx1 and stx2 using RPA. Genes encoding for stx1, stx2, eae, and rfbE were used to quantify E. coli O157:H7 in the water samples. Furthermore, duplex ddPCR assays were used to quantify the pathogens in these samples. Duplex assay set 1 used stx1 and rfbE genes, while assay set 2 used stx2 and eae genes. Droplet digital PCR was used for the absolute quantification of E. coli O15:H7 in comparison with qPCR for the spiked and environmental samples. The RPA results were compared to those from qPCR and ddPCR in order to assess the efficiency of the RPA compared with the PCR methods. The assays were further applied to the dairy lagoon effluent (DLE) and the high rate algae pond (HRAP) effluent, which were fed with diluted DLE. The RPA detected was <10 CFU/mL, while ddPCR showed quantification from 1 to 10(4) CFU/mL with a high reproducibility. In addition, quantification by qPCR was from 10(3) to 10(7) CFU/mL of the wastewater samples. Therefore, the RPA assay has potential as a point of care tool for the detection of E. coli O157:H7 from different environmental sources, followed by quantification of the target concentrations.

The feasibility of generating a lipid-containing algal-bacterial polyculture biomass in municipal primary wastewater and enhancing biomethanation of lipid-extracted algal residues (LEA) through hydrothermal pretreatment and co-digestion with sewage sludge (SS) was investigated. In high-rate algal ponds, the polyculture of native algal and bacteria species demonstrated a monthly average net and gross biomass productivity of 30 +/- 3 and 36 +/- 3 gAFDW m(-2) day(-1) (summer season). The algal community was dominated by Micractinium sp. followed by Scenedesmus sp., Chlorella sp., pennate diatoms and Chlamydomonas sp. The polyculture metabolic activities resulted in average reductions of wastewater volatile suspended solids (VSS), carbonaceous soluble biochemical oxygen demand (csBOD(5)) and total nitrogen (N-total) of 63 +/- 18%, 98 +/- 1% and 76 +/- 21%, respectively. Harvested biomass contained nearly 23% lipid content and an extracted blend of fatty acidmethyl esters satisfied the ASTM D6751 standard for biodiesel. Anaerobic digestion of lipid extracted algal residues (LEA) demonstrated long lagphase inmethane production of 17 days and ultimatemethane yield of 296 +/- 2 mL/gVS (or similar to 50% of theoretical), likely because to its limited biodegradability and toxicity due to presence of the residual solvent (hexane). Hydrothermal pretreatment increased the ultimatemethane yield and production rate by 15-30% but did not mitigate solvent toxicity effects completely leading to less substantial improvement in energy output of 5-20% and diminished Net Energy Ratio (NER < 1). In contrast, co-digestion of LEA with sewage sludge (10% to 90% ratio) was found to minimize solvent toxicity and improve methane yield enhancing the energy output similar to 4-fold, compared to using LEA as a single substrate, and advancing NER to 4.2. (c) 2018 Elsevier B. V. All rights reserved.

Algal-bacteria high-rate ponds represent an energy-efficient wastewater treatment approach and a source for affordable and sustainable biomass feedstock for production of renewable energy through anaerobic digestion (AD). However, there is still a need for more data on wastewater treatment efficiency, biomass productivity and settleability from outdoor treatment facilities, as well as on impact of variability in biomass composition and digestibility on methane yield and energy output. Hydraulic retention time (HRT) and wastewater quality fed into 30 m(2) raceway ponds had a major effect on algal-bacteria polyculture productivity, settleability, phylogenetic and biochemical compositions, digestibility and methane yield. While Micractinium, Scenedesmus, Chlorella, and pennate diatoms were always among the key species observed, the gross productivity and 2-hour settle-ability during summer cultivation varied in the first-stage ponds treating primary wastewater/ from 29 +/- 5 to 54 +/- 12 g(AFDW)/m(2)/d and from 88 +/- 8 to 94 +/- 4% for HRT of 3 and 2 days, respectively. For these conditions, the effluent had csBOD of 3.4 or 3.3 mg/L and N-total (mostly NO3- -N) of 9.2 or 8.2 mg/L, respectively. The second-stage algal ponds (HRT 3 days) showed lower productivity of 16 +/- 6 g(AFDW)/m(2)/d, settleability of 84 +/- 11%, and effluent csBOD 3.7 mg/L and N-total 0.8 mg/L. Biomass composition from different ponds was 34-38% protein, 18-28% total lipids and 6-14% FAME. The methane yield varied about 30% with largest value of 0.34 +/- 0.01 L/gVS and showed a positive correlation with biomass lipid content (R-2 = 0.93). First-order and pseudo-parallel first-order rate kinetic models exhibited a better fit for methane production (most R-2 > 0.993) than the modified Gompertz model. The variation in biomass composition led to significant differences in energy output (varied by about 60%), Net Energy Ratios (ranged from 1.6 to 2.2) and Net Energy Efficiency (from 60% to 70%) when projecting the energy balance for a large-scale continuous AD process with an optimal HRT of 20-30 days.

Dynamics of seasonal microbial community compositions in algae cultivation ponds are complex. However, there is very limited knowledge on bacterial communities that may play significant roles with algae in the bioconversion of manure nutrients to animal feed. In this study, water samples were collected during winter, spring, summer, and fall from the dairy lagoon effluent (DLE), high rate algae ponds (HRAP) that were fed with diluted DLE, and municipal waste water treatment plant (WWTP) effluent which was included as a comparison system for the analysis of total bacteria, Cyanobacteria, and microalgae communities using MiSeq Illumina sequencing targeting the 16S V4 rDNA region. The main objective was to examine dynamics in microbial community composition in the HRAP used for the production of algal biomass. DNA was extracted from the different sample types using three commercially available DNA extraction kits; MoBio Power water extraction kit, Zymo fungi/bacterial extraction kit, and MP Biomedicals FastDNA SPIN Kit. Permutational analysis of variance (PERMANOVA) using distance matrices on each variable showed significant differences (P=0.001) in beta-diversity based on sample source. Environmental variables such as hydraulic retention time (HRT; P<0.031), total N (P<0.002), total inorganic N (P<0.002), total P (P<0.002), alkalinity (P<0.002), pH (P<0.022), total suspended solid (TSS; P<0.003), and volatile suspended solids (VSS; P<0.002) significantly affected microbial communities in DLE, HRAP, and WWTP. Of the operational taxonomic units (OTUs) identified to phyla level, the dominant classes of bacteria identified were: Cyanobacteria, Alpha-, Beta-, Gamma-, Epsilon-, and Delta-proteobacteria, Bacteroidetes, Firmicutes, and Planctomycetes. Our data suggest that microbial communities were significantly affected in HRAP by different environmental variables, and care must be taken in extraction procedures when evaluating specific groups of microbial communities for specific functions.