Real-time cyanobacteria/algal monitoring is a valuable tool for early detection of harmful algal blooms, water treatment efficacy evaluation, and assists tailored water quality risk assessments by considering taxonomy and cell counts. This review evaluates and proposes a synergistic approach using neural network image recognition and microscopic imaging devices by first evaluating published literature for both imaging microscopes and image recognition. Quantitative phase imaging was considered the most promising of the investigated imaging techniques due to the provision of enhanced information relative to alternatives. This information provides significant value to image recognition neural networks, such as the convolutional neural networks discussed within this review. Considering published literature, a cyanobacteria monitoring system and corresponding image processing workflow using in situ sample collection buoys and on-shore sample processing was proposed. This system can be implemented using commercially available equipment to facilitate accurate, real-time water quality monitoring. Graphical abstract

Algal blooms consisting of potentially toxic cyanobacteria are a growing source water management challenge faced by water utilities globally. Commercially available sonication devices are designed to mitigate this challenge by targeting cyanobacteria-specific cellular features and aim to inhibit cyanobacterial growth within water bodies. There is limited available literature evaluating this technology; therefore, a sonication trial was conducted in a drinking water reservoir within regional Victoria, Australia across an 18-month period using one device. The trial reservoir, referred to as Reservoir C, is the final reservoir in a local network of reservoirs managed by a regional water utility. Sonicator efficacy was evaluated through qualitative and quantitative analysis of algal and cyanobacterial trends within Reservoir C and surrounding reservoirs using field data collected across three years preceding the trial and during the 18-month duration of the trial. Qualitative assessment revealed a slight increase in eukaryotic algal growth within Reservoir C following device installation, which is likely due to local environmental factors such as rainfall-driven nutrient influx. Post-sonication quantities of cyanobacteria remained relatively consistent, which may indicate that the device was able to counteract favorable phytoplankton growth conditions. Qualitative assessments also revealed minimal prevalence variations of the dominant cyanobacterial species within the reservoir following trial initiation. Since the dominant species were potential toxin producers, there is no strong evidence that sonication altered Reservoir C’s water risk profiles during this trial. Statistical analysis of samples collected within the reservoir and from the intake pipe to the associated treatment plant supported qualitative observations and revealed a significant elevation in eukaryotic algal cell counts during bloom and non-bloom periods post-installation. Corresponding cyanobacteria biovolumes and cell counts revealed that no significant changes occurred, excluding a significant decrease in bloom season cell counts measured within the treatment plant intake pipe and a significant increase in non-bloom season biovolumes and cell counts as measured within the reservoir. One technical disruption occurred during the trial; however, this had no notable impacts on cyanobacterial prevalence. Acknowledging the limitations of the experimental conditions, data and observations from this trial indicate there is no strong evidence that sonication significantly reduced cyanobacteria occurrence within Reservoir C.

Applications of advanced oxidation processes (AOPs) in water and wastewater treatment have been the subject of growing interest throughout the last decade. Although UV/hydrogen peroxide (UV‐H2O2) is the most established technology among the UV‐AOPs, UV‐chlorine (UV‐Cl) is emerging as a reliable and potentially more cost‐effective alternative. Recent studies have indicated that UV‐Cl processes may be more efficient and economically favourable for the degradation of some chemicals of emerging concern from contaminated water. Moreover, in terms of the formation of disinfection by‐products (DBPs), UV‐H2O2 seems to have no superiority over UV‐Cl. This said, more investigation in the assessment of genotoxicity and cytotoxicity of DBPs is required. Additionally, more pilot‐scale and full‐scale studies are required to establish UV‐Cl as a reliable alternative to UV‐ H2O2. This paper compares UV‐Cl and UV‐H2O2 AOPs for the degradation of intractable chemicals from water and wastewater based on the practical considerations of efficiency, cost, DBP formation, kinetics and sensitivity to water matrix variability. Finally, various modelling approaches to UV‐Cl have been reviewed. This review showed that UV‐Cl is superior to UV‐H2O2 in terms of degradation efficiency and cost effectiveness and can be a robust alternative in many UV‐AOPs applications.