Assessing spatial heterogeneity of nutrient loads in a large shallow lake using a lattice Boltzmann water quality model.

Nutrient loads in lakes are spatially heterogeneous, but current spatial analysis method are mainly zonal, making them subjective and uncertain. This study proposes a high-resolution model for assessing spatial differences in nutrient loads based on the lattice Boltzmann method. The model was applied to Dongping Lake in China. Firstly, the contribution rates of four influencing factors, including water transfer, inflow, wind, and internal load, were calculated at different locations in the lake. Then, their proportionate contributions during different intervals to the whole lake area were calculated. Finally, the cumulative load could be calculated for any location within the lake. The validation showed that the model simulated hydrodynamics and water quality well, with relative errors between the simulated and measured water quality data smaller than 0.45. Wind increased the nutrient loads in most parts of the lake. The loads tended to accumulate in the east central area where high-frequency circulation patterns were present. Overall, the proposed water quality model based on the lattice Boltzmann method was able to simulate seven indexes. Therefore, this model represents a useful tool for thoroughly assessing nutrient load distributions in large shallow lakes and could help refine lake restoration management.

Hydraulic conditions control the abundance of antibiotic resistance genes and their potential host microorganisms in a frequently regulated river-lake system.

Antibiotic resistance genes (ARGs) are a growing problem that is widespread in river-lake ecosystems, where they pose a threat to the aquatic environment's health and public safety. These systems serve as critical nodes in water management, as they facilitate the equitable allocation of water resources through long-term and frequent water diversions. However, hydrological disturbances associated with water-regulation practices can influence the dynamics of their potential host microorganisms and associated resistance genes. Consequently, identifying the key ARGs and their resistance mechanisms in heavily regulated waters is vital for safeguarding human health and that of river-lake ecosystems. In this study, we examined the impact of water-regulation factors on ARGs and their hosts within a river-lake continuum using 16S rRNA and metagenomic sequencing. We found that a significant increase in ARG abundance during regulation periods (p < 0.05), especially in the aquatic environment. Key resistance genes were macB, tetA, evgS, novA, and msbA, with increased efflux pinpointed as their principal resistance mechanism. Network analysis identified Flavobacteriales, Acinetobacter, Pseudomonas, Burkholderiaceae, and Erythrobacter as key potential host microorganisms, which showed increased abundance within the water column during regulation periods (p < 0.05). Flow velocity and water depth both drove the host microorganisms and critical ARGs. Our findings underscore the importance of monitoring and mitigating the antibiotic resistance risk during water transfers in river-lake systems, thereby supporting informed management and conservation strategies.

Meta-analysis to identify inhibition mechanisms for the effects of submerged plants on algae.

Submerged plants inhibit algae through shading effects, nutrient competition, allelopathy, and combinations of these mechanisms. However, it is unclear which mechanism is dominant, and how the inhibition intensity results from the traits of the plant and algae. In this study, we performed meta-analysis to quantitatively identify the dominant mechanisms, evaluate the relationship between inhibition intensity and the species and functional traits of the submerged plants or algae, and reveal the influences of external environmental factors. We found that allelopathy caused stronger inhibition than the shading effect and nutrient competition and dominated the combined mechanisms. Although the leaf shapes of the submerged plants influenced light availability, this did not change the degree of algae suppression. Algal species, properties (toxic or nontoxic) and external environmental factors (e.g., lab/mesocosm experiments, co-/filtrate/extract culture, presence or absence of interspecific competition) potentially influenced inhibition strength. Cyanobacteria and Bacillariophyta were more strongly inhibited than Chlorophyta, and toxic Cyanobacteria more than non-toxic Cyanobacteria. Algae inhibition by submerged plants was species-dependent. Ceratophyllum, Vallisneria, and Potamogeton strongly inhibited Microcystis, and can potentially prevent or mitigate harmful algal blooms of this species. However, the most common submerged plant species inhibited mixed algae communities to some extent. The results from lab experiments and mesocosm experiments both confirmed the inhibition of algae by submerged plants, but more evidence from mesocosm experiments is needed to elucidate the inhibition mechanism in complex ecosystems. Submerged plants in co-cultures inhibited algae more strongly than in extract and filtrate cultures. Complex interspecific competition may strengthen or weaken algae inhibition, but the response of this inhibition to complex biological mechanisms needs to be further explored. Our meta-analysis provides insights into which mechanisms contributed most to the inhibition effect and a scientific basis for selecting suitable submerged plant species and controlling external conditions to prevent algal blooms in future ecological restoration of lakes.

Unraveling the rate-limiting step in microorganisms' mediation of denitrification and phosphorus absorption/transport processes in a highly regulated river-lake system.

River-lake ecosystems are indispensable hubs for water transfers and flow regulation engineering, which have frequent and complex artificial hydrological regulation processes, and the water quality is often unstable. Microorganisms usually affect these systems by driving the nutrient cycling process. Thus, understanding the key biochemical rate-limiting steps under highly regulated conditions was critical for the water quality stability of river-lake ecosystems. This study investigated how the key microorganisms and genes involving nitrogen and phosphorus cycling contributed to the stability of water by combining 16S rRNA and metagenomic sequencing using the Dongping river-lake system as the case study. The results showed that nitrogen and phosphorus concentrations were significantly lower in lake zones than in river inflow and outflow zones (p < 0.05). Pseudomonas, Acinetobacter, and Microbacterium were the key microorganisms associated with nitrate and phosphate removal. These microorganisms contributed to key genes that promote denitrification (nirB/narG/narH/nasA) and phosphorus absorption and transport (pstA/pstB/pstC/pstS). Partial least squares path modeling (PLS-PM) revealed that environmental factors (especially flow velocity and COD concentration) have a significant negative effect on the key microbial abundance (p < 0.001). Our study provides theoretical support for the effective management and protection of water transfer and the regulation function of the river-lake system.

Microbial abundance and community in constructed wetlands planted with Phragmites australis and Typha orientalis in winter.

NOVELTY STATEMENT: The microbial abundance and communities were characterized in CWs with different plant species during winter. Better removal efficiency with high microbial abundance and diversified microbial community were found in CWs planted with Phragmites australis. This study confirmed that in winter, withered plants in CWs can effectively remove NH4+-N and COD by affecting microbial abundance and community structure.

Essential factors of an integrated moving bed biofilm reactor-membrane bioreactor: Adhesion characteristics and microbial community of the biofilm.

This work aims at revealing the adhesion characteristics and microbial community of the biofilm in an integrated moving bed biofilm reactor-membrane bioreactor, and further evaluating their variations over time. With multiple methods, the adhesion characteristics and microbial community of the biofilm on the carriers were comprehensively illuminated, which showed their dynamic variation along with the operational time. Results indicated that: (1) the roughness of biofilm on the carriers increased very quickly to a maximum value at the start-up stage, then, decreased to become a flat curve, which indicated a layer of smooth biofilm formed on the surface; (2) the tightly-bound protein and polysaccharide was the most important factor influencing the stability of biofilm; (3) the development of biofilm could be divided into three stages, and Gammaproteobacteria were the most dominant microbial species in class level at the last stage, which occupied the largest ratio (51.48%) among all microbes.

A new insight into resource recovery of excess sewage sludge: feasibility of extracting mixed amino acids as an environment-friendly corrosion inhibitor for industrial pickling.

The work mainly presented a laboratory-scale investigation on an effective process to extract a value-added product from municipal excess sludge. The functional groups in the hydrolysate were characterized with Fourier transform infrared spectrum, and the contained amino acids were measured by means of an automatic amino acid analyzer. The corrosion-inhibition characteristics of the hydrolysate were determined with weight-loss measurement, electrochemical polarization and scanning electron microscopy. Results indicated that the hydrolysate contained 15 kinds of amino acid, and their adsorption on the surface could effectively inhibit the corrosion reaction of the steel from the acid medium. Polarization curves indicated that the obtained hydrolysate was a mixed-type inhibitor, but mainly restricted metal dissolution on the anode. The adsorption accorded well with the Langmuir adsorption isotherm, involved an increase in entropy, and was a spontaneous, exothermic process.