Will "Air Eutrophication" Increase the Risk of Ecological Threat to Public Health?

Enhanced inhibitory efficiency against toxic bloom forming Raphidiopsis raciborskii by Streptomyces sp. HY through triple algicidal modes: Direct and indirect attacks combined with bioflocculation

Raphidiopsis raciborskii (R. raciborskii) forms harmful cyanobacterial blooms globally, and poses a great threat to the safety of drinking water and public health. There is a great need to develop eco-friendly biological alternative measures to mitigate mass blooms of R. raciborskii. However, previous rare studies on algicidal microorganisms against R. raciborskii restricted this aim. Recently, an algicidal bacterium Streptomyces sp. HY (designated HY) was identified with flavones producing ability, and could remove up to 98.73 % of R. raciborskii biomass within 48 h by directly attacking the cyanobacterium and release of algicidal substances (i.e., flavonoids) with a inoculum ratio of 5 %. Algicidal rate of HY was enhanced by 88.05 %, 89.33 % under dark and light, and full-light conditions respectively, when compared with the dark condition. Its algicidal substances were stable in a broad range of temperature (-80-55 °C) and pH (3-11) conditions, and all treated groups exhibited ≈ 100 % algicidal rate at day 3. HY treatment disrupted the photosynthesis system and triggered serious oxidative stress resulting in severe morphological injury. Thereby, HY treatment significantly affected expression levels of several essential genes (i.e., psbA, psaB, rbcL, ftsZ, recA, grpE), and simultaneously inhibited the biosynthesis and release of cylindrospermopsin. Yet, HY treatment didn't show any toxicity to zebrafish test embryos. Such results indicate that HY is a promising algicidal candidate strain to control global R. raciborskii blooms, and holds great promises for an effective biological measure to sustain water safety.

Emerging contaminants: A One Health perspective

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

Analyzing MC-LR distribution characteristics in natural lakes by a novel fluorescence technology

The death of aquatic and terrestrial organisms caused by cyanobacterial blooms has been a topic of considerable concern since the 19th century. Microcystin-LR (MC-LR) produced by cyanobacterial blooms threaten natural ecosystems and human health. Therefore, establishing an effective monitoring and early warning system to detect MC-LR in water bodies is crucial. However, rapidly and intuitively assessing the distribution traits of MC-LR in lakes is a challenging task due to the complexities and expenses associated with conventional detection methods. To overcome these technical limitations, we introduce a novel and effective method for evaluating the distribution of MC-LR in lakes. This method is achieved by using a fluorescence probe (BAD) technology, marking the first application of this technology in evaluating the distribution of MC-LR in natural lake environments. The probe BAD is endowed with unique functions through clever functionalization modification. Experimental results exhibit that BAD has different fluorescence signals at various lake sampling points. The correlation analysis of fluorescence data and physicochemical indicators determines that the fluorescence data of the probe exhibit good correlation with MC-LR, implying that BAD is capable of detecting MC-LR in lakes. Moreover, the introduction of fluorescence technology to achieve the intuitive distribution of MC-LR in the entire plateau lake. This study provides a new method for evaluating the distribution of MC-LR in plateau lakes. It opens a new avenue for exploring the relationship between cyanobacterial blooms and MC-LR in natural waters.

Ultrahigh-porosity Ranunculus-like MgO adsorbent coupled with predictive deep belief networks: A transformative method for phosphorus treatment

Phosphorus is a nonrenewable material with a finite supply on Earth; however, due to the rapid growth of the manufacturing industry, phosphorus contamination has become a global concern. Therefore, this study highlights the remarkable potential of ranunculus-like MgO (MO4-MO6) as superior adsorbents for phosphate removal and recovery. Furthermore, MO6 stands out with an impressive adsorption capacity of 596.88 mg/g and a high efficacy across a wide pH range (2-10) under varying coexisting ion concentrations. MO6 outperforms the top current adsorbents for phosphate removal. The process follows Pseudo-second-order and Langmuir models, indicating chemical interactions between the phosphate species and homogeneous MO6 monolayer. MO6 maintains 80 % removal and 96 % recovery after five cycles and adheres to the WHO and EUWFD regulations for residual elements in water. FT-IR and XPS analyses further reveal the underlying mechanisms, including ion exchange, electrostatic, and acid-base interactions. Ten machine learning (ML) models were applied to simultaneously predict multi-criteria (sorption capacity, removal efficiency, final pH, and Mg leakage) affected by 15 diverse environmental conditions. Traditional ML models and deep neural networks have poor accuracy, particularly for removal efficiency. However, a breakthrough was achieved by the developed deep belief network (DBN) with unparalleled performance (MAE = 1.3289, RMSE = 5.2552, R2 = 0.9926) across all output features, surpassing all current studies using thousands of data points for only one output factor. These captivating MO6 and DBN models also have immense potential for effectively applying in the real water test with error < 5 %, opening immense horizons for transformative methods, particularly in phosphate removal and recovery.

Opposite response of constructed wetland performance in nitrogen and phosphorus removal to short and long terms of operation

Constructed wetlands (CWs) have been widely used for treating polluted water since the 1950s, with applications in over 50 countries worldwide. Most studies investigating the pollutant removal efficiency of these wetlands have focused on differences among wetland designs, operation strategies, and environmental conditions. However, there still remains a gap in understanding the variation in wetland pollutant removal efficiency over different time scales. Therefore, the main aim of the study is to address this gap by conducting a global meta-analysis to estimate the variation in nitrogen (N) and phosphorus (P) removal by wetland in short- and long-term pollutant treatment. The findings of this study indicated that the total efficiencies of N and P removal increased during short-term wetland operation but decreased during long-term operation. However, for surface flow CWs specifically, the efficiencies of N and P removal increased during short-term operation and remained stable during long-term operation. Moreover, the study discovered that wetland N removal efficiency was influenced by seasons, with an increase in spring and summer and a decrease in autumn and winter. Conversely, there was no significant seasonal effect on P removal efficiency. Additionally, high hydraulic load impaired wetland N and P removal efficiency during long-term operation. This study offers a critical review of the role of wetlands in wastewater treatment and provides valuable reference data for the design and selection of CWs types during wastewater treatment in the aspect of sustainability.

Sustainable bioremediation technologies for algal toxins and their ecological significance

The emergence of algal toxins in water ecosystems poses a significant ecological and human health concern. These toxins, produced by various algal species, can lead to harmful algal blooms, and have far-reaching consequences on biodiversity, food chains, and water quality. This review explores the types and sources of algal toxins, their ecological impacts, and the associated human health risks. Additionally, the review delves into the potential of bioremediation strategies to mitigate the effects of algal toxins. It discusses the role of microorganisms, enzymes, and algal-bacterial interactions in toxin removal, along with engineering approaches such as advanced oxidation processes and adsorbent utilization. Microbes and enzymes have been studied for their environmentally friendly and biocompatible properties, which make them useful for controlling or removing harmful algae and their toxins. The challenges and limitations of bioremediation are examined, along with case studies highlighting successful toxin control efforts. Finally, the review outlines future prospects, emerging technologies, and the need for continued research to effectively address the complex issue of algal toxins and their ecological significance.