Prediction of maximum algal productivity in membrane bioreactors with a light-dependent growth model

Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Phytoplankton is the essential primary producer in fresh surface water ecosystems. However, excessive phytoplankton growth due to eutrophication significantly threatens ecologic, economic, and public health. Therefore, phytoplankton identification and quantification are essential to understanding the productivity and health of freshwater ecosystems as well as the impacts of phytoplankton overgrowth (such as Cyanobacterial blooms) on public health. Microscopy is the gold standard for phytoplankton assessment but is time-consuming, has low throughput, and requires rich experience in phytoplankton morphology. Quantitative polymerase chain reaction (qPCR) is accurate and straightforward with high throughput. In addition, qPCR does not require expertise in phytoplankton morphology. Therefore, qPCR can be a useful alternative for molecular identification and enumeration of phytoplankton. Nonetheless, a comprehensive study is missing which evaluates and compares the feasibility of using qPCR and microscopy to assess phytoplankton in fresh water. This study 1) compared the performance of qPCR and microscopy in identifying and quantifying phytoplankton and 2) evaluated qPCR as a molecular tool to assess phytoplankton and indicate eutrophication. We assessed phytoplankton using both qPCR and microscopy in twelve large freshwater rivers across the United States from early summer to late fall in 2017, 2018, and 2019. qPCR- and microscope-based phytoplankton abundance had a significant positive linear correlation (adjusted R2 = 0.836, p-value < 0.001). Phytoplankton abundance had limited temporal variation within each sampling season and over the three years studied. The sampling sites in the midcontinent rivers had higher phytoplankton abundance than those in the eastern and western rivers. For instance, the concentration (geometric mean) of Bacillariophyta, Cyanobacteria, Chlorophyta, and Dinoflagellates at the sampling sites in the midcontinent rivers was approximately three times that at the sampling sites in the western rivers and approximately 18 times that at the sampling sites in the eastern rivers. Welch's analysis of variance indicates that phytoplankton abundance at the sampling sites in the midcontinent rivers was significantly higher than that at the sampling sites in the eastern rivers (p-value = 0.013) but was comparable to that at the sampling sites in the western rivers (p-value = 0.095). The higher phytoplankton abundance at the sampling sites in the midcontinent rivers was presumably because these rivers were more eutrophic. Indeed, low phytoplankton abundance occurred in oligotrophic or low trophic sites, whereas eutrophic sites had greater phytoplankton abundance. This study demonstrates that qPCR-based phytoplankton abundance can be a useful numerical indicator of the trophic conditions and water quality in freshwater rivers.

Recent Developments on the Performance of Algal Bioreactors for CO2 Removal: Focusing on the Light Intensity and Photoperiods

This work presents recent developments of algal bioreactors used for CO₂ removal and the factors affecting the reactor performance. The main focus of the study is on light intensity and photoperiods. The role of algae in CO₂ removal, types of algal species used in bioreactors and conventional types of bioreactors including tubular bioreactor, vertical airlift reactor, bubble column reactor, flat panel or plate reactor, stirred tank reactor and specific type bioreactors such as hollow fibre membrane and disk photobioreactors etc. are discussed in details with respect to utilization of light. The effects of light intensity, light incident, photoinhibition, light provision arrangements and photoperiod on the performance of algal bioreactors for CO₂ removal are also discussed. Efficient operation of algal photobioreactors cannot be achieved without the improvement in the utilization of incident light intensity and photoperiods. The readers may find this article has a much broader significance as algae is not only limited to removal or sequestration of CO₂ but also it is used in a number of commercial applications including in energy (biofuel), nutritional and food sectors.

Optimization and Scale-Up of Fermentation Processes Driven by Models

In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

Solids retention time dependent, tunable diatom hierarchical micro/nanostructures and their effect on nutrient removal

The hierarchical three-dimensional (3D) micro/nanostructures of diatoms make them a promising biomaterial for fabricating nanomaterials, producing bioactive pharmaceuticals or nutraceuticals, and removing micropollutants. For diatom production in a continuous flow system, little is known how bioreactor operating parameters, especially solids retention time (SRT), affect the 3D structures of diatoms. This study demonstrated that tunable diatom micro/nanostructures could be produced by varying the SRT of membrane bioreactors (MBRs). A diatom strain (Stephanodiscus hantzschii) was cultivated in two identical MBRs with a fixed hydraulic retention time (HRT) of 24 h and staged SRTs from 5, to 10, and to 20 d. As SRTs increased from 5 to 20 d, important characteristics of diatom micro/nanostructures showed linear decreases: the diameters of foramina on the areola layer decreased from 170 ± 10 to 130 ± 12 nm, the numbers of nanopores per cribrum layer decreased from 20 ± 3 to 12 ± 2, and the specific surface areas of the diatoms decreased from 36.01 ± 1.27 to 12.67 ± 2.45 m²·g^-1. However, the average diatom heights increased from 2.9 ± 0.3 to 3.9 ± 0.4 µm, while diatom cell diameter (5 µm) and nanopore size (20 nm) remained unchanged. The silicon content of diatoms also linearly increased with SRT. The decrease in diatom porosity and increase in silicon content were probably due to the reduced diatom growth rates (likely resulting in less pores) at increasing SRTs, which also facilitated silica deposition as the overall diatom population stayed longer in the MBRs. As the SRTs increased from 5 to 10, and to 20 d, the nitrate (NO₃^-) removal efficiency decreased from 75% to 70%, and to 60%, respectively, whereas phosphorus (P) removal efficiency increased from 74% to 80%, and to 90%, respectively. The opposite trends in efficiencies were because NO₃^--N was removed by cellular uptake and biomass waste whereas P was mainly removed through diatom-assisted chemical precipitation.