Microcystis abundance is predictable through ambient bacterial communities: A data-oriented approach.

The number of cyanobacterial harmful algal blooms (cyanoHABs) has increased, leading to the widespread development of prediction models for cyanoHABs. Although bacteria interact closely with cyanobacteria and directly affect cyanoHABs occurrence, related modeling studies have rarely utilized microbial community data compared to environmental data such as water quality. In this study, we built a machine learning model, the multilayer perceptron (MLP), for the prediction of Microcystis dynamics using both bacterial community and weekly water quality data from the Daechung Reservoir and Nakdong River, South Korea.

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters.

Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters. Therefore, this study investigated the loss of seventy MPs on eight different syringe filters by employing Random Forest, a machine learning algorithm.

Boosted micropollutant removal over urchin-like structured hydroxyapatite-incorporated nickel magnetite catalyst via peroxydisulfate activation.

In this work, urchin-like structured hydroxyapatite-incorporated nickel magnetite (NiFeO/UHdA) microspheres were developed for the efficient removal of micropollutants (MPs) via peroxydisulfate (PDS) activation. The prepared NiFeO/UHdA degraded 99.0 % of sulfamethoxazole (SMX) after 15 min in 2 mM PDS, having a first-order kinetic rate constant of 0.

Multifunctional Scatterometer System for Measuring Physical Oceanographic Parameters Using Range-Doppler FMCW Radar.

A multifunctional scatterometer system and optimized radar signal processing for simultaneous observation of various physical oceanographic parameters are described in this paper. Existing observation methods with microwave remote sensing techniques generally use several separate systems such as scatterometer, altimeter, and Doppler radar for sea surface monitoring, which are inefficient in system operation and cross-analysis of each observation data. To improve this point, we integrated separate measurement functions into a single observation system by adding a measurement function of Doppler frequency to the existing system.

Drivers shaping episodic and gradual changes in phytoplankton community succession: Taxonomic versus functional groups.

Describing temporal changes in phytoplankton communities is complicated owing to (i) multivariate environmental drivers, (ii) inter-specific relationships, and (iii) various species. With long-term research data from the lower Nakdong River from 1993 to 2016, we examined the temporal changes at two scales-episodic (from weekly to monthly) and long-term (yearly)-and screened the potential environmental drivers. Phytoplankton community component patterns were modeled with the drivers as covariates, using multivariate autoregressive state-space (MARSS) models, to assess their response to environmental drivers and biotic interactions.

Effect of HRT and external resistances on power generation of sidestream microbial fuel cell with CNT-coated SSM anode treating actual fermentation filtrate of municipal sludge.

A microbial fuel cell (MFC) with multiwall carbon nanotube (CNT) coated stainless steel mesh (SSM) coated anode (S-MFC) was operated with a filtrate generated by the fermentation of municipal primary sludge. The S-MFC's maximum power density (MPD: 69.8-164.

Multi-barrier approach for removing organic micropollutants using mobile water treatment systems.

The diversity of organic micropollutants (OMPs) in aquatic environments has been increasing rapidly during the last decade. Therefore, it is important to monitor and attenuate emerging contaminants before they can negatively affect the aquatic environment. However, due to the diversity and complexity of OMPs, there are limitations to using a single method for treating a combination of these pollutants.

An Ultrasonic Multi-Beam Concentration Meter with a Neuro-Fuzzy Algorithm for Water Treatment Plants.

Ultrasonic concentration meters have widely been used at water purification, sewage treatment and waste water treatment plants to sort and transfer high concentration sludges and to control the amount of chemical dosage. When an unusual substance is contained in the sludge, however, the attenuation of ultrasonic waves could be increased or not be transmitted to the receiver. In this case, the value measured by a concentration meter is higher than the actual density value or vibration.

Evaluation of dams and weirs operating for water resource management of the Geum River.

As part of the Four Major Rivers Restoration Project, 16 multi-functional weirs have recently been constructed in each river system in Korea. The Project has pursued ecological approaches through constructing artificial weirs in waterways to ensure sufficient flow even in the dry seasons, improving agricultural reservoirs to supply environmental flow for the rivers, and thereby enhancing the water quality of the rivers. However, these anthropogenic activities have been accompanying a significant change in the riverine environment.