The consumption of drinking water containing aluminum levels that exceed regulatory limits (e.g., the WHO’s guideline value of 0.1–0.2 mg/L) may be associated with the potential risk of developing Alzheimer’s disease. However, according to the analyses conducted, it was observed that the scientific evidence on this topic is still limited and contradictory within the scientific community. A bibliometric analysis of 390 articles published between 1979 and 2023 and a systematic review of 20 original articles found that interest in this topic has been decreasing in recent years. The most recent studies focus on the relationship between aluminum and Alzheimer’s disease, suggesting that exposure to high levels of aluminum in drinking water may increase the risk of developing this disease and other neurodegenerative disorders. Nevertheless, other studies have concluded that there is no clear causal relationship between aluminum and Alzheimer’s disease. These studies suggest that other factors, such as age, genetics, or exposure to other toxins, may play a more significant role in the development of this condition. More comprehensive studies with improved methodological quality are needed to better understand the relationship between aluminum and Alzheimer’s disease and to establish a definitive conclusion on this subject. Of the 20 articles systematically reviewed, 12 (60%) reported a positive association between aluminum exposure in drinking water and increased risk of Alzheimer’s disease, while 8 (40%) found no significant association. Five studies (25%) were large-scale epidemiological investigations with robust methodologies. However, the current evidence remains insufficient to establish a definitive causal relationship, highlighting the need for more conclusive research in this area

Arsenic (III) exposure, often from contaminated water, can have severe health repercussions. Chronic exposure to this toxic compound is linked to increased risks of various health issues. Various technologies exist for arsenic (III) removal from contaminated water sources. This work synthesized ZnO-CuO nanocomposites through ultrasound-assisted coprecipitation, generating abundant hydroxylated sites via the deposition of ZnO nanoparticles onto CuO sheets for enhanced arsenic (III) adsorption. Structural characterization verified the formation of phase-pure heterostructures with emergent properties. Batch studies demonstrated exceptional 85.63% As(III) removal at pH 5, where binding with prevalent neutral H₃AsO₃ occurred through inner-sphere complexation with protonated groups. However, competing anions decreased removal through site blocking. Favorable pseudo-second order chemisorption kinetics and the 64.77 mg/g maximum Langmuir capacity revealed rapid multilayer uptake, enabled by intrinsic synergies upon nanoscale mixing of Zn/Cu oxides. The straightforward, energy-efficient ultrasonic production route makes this material promising for real-world water treatment integration.

This article describes an affordable method for the synthesis of MnMoO₄ nanoflowers through the microwave synthesis approach. By manipulating the reaction parameters like solvent, pH, microwave power, and irradiation duration along this pathway, various nanostructures can be acquired. The synthesized nanoflowers were analyzed by using a powder X-ray diffractometer (XRD), field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and UV–vis diffuse reflectance spectroscopy (UV–DRS) to determine their crystalline nature, morphological and functional group, and optical properties, respectively. X-ray photoelectron spectroscopy (XPS) was performed for the examination of elemental composition and chemical states by qualitative and quantitative analysis. The results of the investigations demonstrated that the MnMoO₄ nanostructures with good crystallinity and distinct shape were formed successfully. The synthesized MnMoO₄ nanoflowers were tested for their efficiency as a photocatalyst in the degradation studies of methylene blue (MB) as model organic contaminants in an aqueous medium under visible light, which showed their photocatalytic activity with a degradation of 85%. Through the band position calculations using the electronegative value of MnMoO₄, the photocatalytic mechanism of the nanostructures was proposed. The results indicated that the effective charge separation, and transfer mechanisms, in addition to the flower-like shape, were responsible for the photocatalytic performance. The stability of the recovered photocatalyst was examined through its recyclability in the degradation of MB. Leveraging MnMoO₄’s photocatalytic properties, future studies may focus on scaling up these processes for practical and large-scale environmental remediation.

Introduction: High Andean lagoons in southern Peru have critical hydrological and ecological functions; however, long-term time series integrating trophic, integral quality, and metal contamination metrics to support adaptive management are lacking. Methods: A total of 1,846 records (2015–2024) from four systems (3,100–4,600 m asl) were analyzed using seven indices (CTSI, TRIX, OWQI, WQIHA, CCME-WQI, HPI, and CD). Temporal trends were assessed by using Mann–Kendall and Theil–Sen slope; spatial heterogeneity using Kruskal–Wallis and Dunn–Bonferroni comparisons; controlling factors using distance-based redundancy analysis (999 permutations); and functional typology using Ward's hierarchical clustering on Z-standardized data. Results: 97% of the series lacked monotonic trends, demonstrating high interannual stability; spatial variance was marked (ε² = 0.73 in CCME-WQI). db-RDA explained 24.6% of the total variability by lake identity, year, and wet-dry period. Four functional archetypes emerged, including a metal-eutrophic hotspot (HPI ≈ 213; CD ≈ 25 µg L⁻¹) and recovering reservoirs with CCME-WQI ≈ 63. CTSI thresholds ≥ 60 combined with HPI ≥ 100 signaled the transition to cyanobacterial dominance. Conclusions: Systems show temporal resilience but strong spatial divergence induced by local pressures; The proposed typology and thresholds provide an operational basis for early warnings and prioritization of remediation actions in high-mountain ecosystems subject to increasing anthropogenic stress.

High Andean lagoons in southern Peru have critical hydrological and ecological functions; however, long-term time series integrating trophic, integral quality, and metal contamination metrics to support adaptive management are lacking. A total of 1846 records (2015–2024) from four systems (3100–4600 m a.s.l.) were analyzed using seven indices assessing trophic status (TSItsr, TRIX), general water quality (OWQI, WQIHA, CCME-WQI), and metal contamination (HPI, CD). Temporal trends were assessed using Mann–Kendall and Theil–Sen slope; spatial heterogeneity using Kruskal–Wallis and Dunn–Bonferroni comparisons; controlling factors using distance-based redundancy analysis (999 permutations); and functional typology using Ward’s hierarchical clustering on Z-standardized data. 93% of the series lacked monotonic trends (52/56 lagoon–stratum × index combinations), demonstrating high interannual stability; spatial variance was marked (ε² = 0.73 in CCME-WQI). Distance-based redundancy analysis (db-RDA) explained 24.6% of total variability, with lake identity as the dominant driver (~45%), followed by temporal change (~8%). Four functional archetypes emerged, including a metal-eutrophic hotspot (HPI ≈ 213; CD ≈ 19) and recovering reservoirs with intermediate water quality indicators. Joint thresholds (TSItsr ≥ 60 + HPI ≥ 100) establish early-warning criteria, with Paucarani (HPI = 213) approaching the critical domain where metal-driven stress may facilitate cyanobacterial dominance. Systems show temporal resilience but strong spatial divergence induced by local pressures. The proposed typology and thresholds provide an operational basis for early warnings and prioritization of remediation actions in high-mountain ecosystems subject to increasing anthropogenic stress.

El objetivo fue construir un modelo de pronóstico de series de tiempo en base a patrones y variables endógenas del consumo del agua potable y adicionalmente determinar la tendencia, estacionalidad, los patrones cíclicos y las características del agua que se consume en la ciudad de Tacna para la obtención de pronósticos. La investigación fue no experimental, correlacional y longitudinal, con información de periodicidad mensual entre enero de 2006 hasta marzo de 2018 registrada mediante análisis documental. La unidad de análisis fueron las unidades económicas de la ciudad de Tacna con servicio de agua potable conectado a la red pública y consumo mensual como variable de interés. La población corresponde a una serie finita de datos mensuales de tamaño N=383 meses. La muestra estuvo constituida por 139 observaciones entre enero 2006-julio 2017 con los que se ha construido el modelo ARIMA en base a la metodología Box-Jenkins y extendida hasta marzo de 2018, para la validación del modelo. La conclusión principal es la obtención del modelo de pronóstico para el consumo de agua de uso poblacional en la ciudad de Tacna ARIMA (0,1,1)(0,1,1)12 con intercepto y cuya formulación matemática empírica es: (LnX) ̂_t=0,000415+0,590a_(t-1)+0,899a_(t-12) con patrones de tendencia y estacionalidad.