Lakes are water bodies that play an essential role as water sources for humanity, as they provide a wide range of ecosystem services. Therefore, this study aimed to evaluate Lake Pomacochas, a high Andean lake in the north of Peru. A variety of parameters were studied, including physicochemical parameters such as temperature (T°C), dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), turbidity, total dissolved solids (TDS), biochemical oxygen demand (BOD), alkalinity, and chlorides hardness; the concentrations of nitrates, nitrites, sulfates, and ammonium; elements such as aluminum (Al), calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), and boron (B); as well as metals and metalloids such as zinc (Zn), cadmium (Cd), copper (Cu), lead (Pb), and arsenic (As). In addition, pH, Zn, and Cu were evaluated at the sediment level. It is important to note that all parameters evaluated in the water matrix showed significant differences in the seasonal period and depth levels. In comparison, the parameters evaluated at the sediment level had no significant differences between the seasonal period and sampling points. As for the seasonal period, the variables that were higher for the dry season were electrical conductivity, total dissolved solids, and lead while that for the wet season were biochemical oxygen demand, zinc, magnesium, turbidity, calcium, dissolved oxygen, temperature, and potential hydrogen. At the depth levels, parameters such as total dissolved solids, lead, and arsenic had similar behavior for the three depths evaluated. According to national standards, latent contamination by cadmium and lead was found in the lake water from the ecological risk assessment. However, by international standards, all sampling stations showed a high level of contamination by cadmium, lead, zinc, copper, and arsenic, which represents a potential risk for the development of socioeconomic activities in the lake. At the same time, the evaluation of sediments did not present any potential risk.
Anthropic activity affects the hydrogeomorphological quality of fluvial systems. River and valley classifications are fundamental preliminary steps in determining their ecological status, and their prioritization is essential for the proper planning and management of soil and water resources. Given the importance of the High Andean livestock micro-watershed (HAL-MWs) ecosystems in Peru, an integrated methodological framework is presented for morphometric prioritization that uses a Principal Component Analysis (PCA) and Weighted Sum Approach (WSA), geomorphological fluvial classifications (channel, slope, and valley), and hydrogeomorphological evaluations using the Hydrogeomorphological Index (IHG). Of six HAL-MWs studied in Leimebamba and Molinopampa (Amazonas region), the PCWSA hybrid model identified the San Antonio HAL-MW as a top priority, needing the rapid adoption of appropriate conservation practices. Thirty-nine types of river course were identified, by combining 13 types of valley and 11 types of riverbed. The total assessment of the IHG indicated that 7.6% (21.8 km), 14.5% (41.6 km), 27.9% (80.0 km), and 50.0% (143.2 km) of the basin lengths have “Poor”, “Moderate”, “Good”, and “Very good” quality rankings, respectively. The increase in the artificial use of river channels and flood plains is closely linked to the decrease in hydrogeomorphological quality.
Los bosques de ribera en áreas tropicales poseen una gran diversidad y heterogeneidad, al estar constituidos por árboles con una distribución irregular, lo que provoca que las comunidades arbóreas difieran a lo largo del río. En la presente investigación, se estudió la vegetación de ribera existente a lo largo de la cuenca del río Utcubamba, situado en un valle interandino tropical en el departamento de Amazonas, nororiente del Perú. Se realizaron inventarios florísticos en 43 puntos de muestreo a lo largo del cauce principal y principales tributarios del río, desde su nacimiento hasta su desembocadura. Se registraron 230 especies de plantas vasculares pertenecientes a 76 familias. Las formaciones arbóreas más comunes colectadas fueron de Alnus acuminata, Salix humboldtiana y Tessaria integrifolia, mientras que las arbustivas resultaron ser Phragmites australis y Gynerium sagittatum. Asimismo, se evaluó la calidad del bosque de galería en cada punto de muestreo mediante el uso del índice QBR-And, mostrándose en la cuenca una calidad decreciente desde el tramo alto al bajo, y superior en los tributarios, en ambos casos motivado por actividades humanas de origen agropecuario principalmente.
Enzymatic electrochemical biosensors play an important role in the agri-food sector due to the need to develop sustainable, low-cost, and easy-to-use analytical devices. Such biosensors can be used to monitor pathogens, endocrine disruptors, and pesticides, such as carbaryl, widely used in many crops. The use of renewable carbon (RC) sources, provided from biomass pyrolysis has been often applied in the fabrication of such sensors. This material is a great candidate for biosensor fabrication due to the presence of surface functional groups, porosity, and moderate surface area. This work describes the functionalization of RC material through an acid treatment with a sulfonitric solution HNO3/H2SO4 (1:3) and the resulting material was characterized by scanning electron microscopy. The obtained RC functionalized (RCF) and the acetylcholinesterase enzyme (AChE) were applied in the construction of the electrochemical biosensor on glassy carbon (GC) electrode and used to detect carbaryl in apple samples. The GC/RCF/AChE biosensor was able to detect the carbaryl pesticide from 5.0 to 30.0 nmol L−1, displaying a LOD of 4.5 nmol L−1. The detection of carbaryl in apple samples presented recoveries between 102.5 to 118.6% through the standard addition method. The proposed biosensor is a promising renewable tool for food safety.
Actualmente el agua es un recurso conflictivo ya sea para su consumo o por su contaminación, siendo este último uno de los principales problemas al que se enfrentan hoy en día las ciudades. En ese sentido el presente estudio buscó determinar la influencia de los efluentes residuales de la ciudad de Chachapoyas en la calidad del agua de la quebrada Santa Lucía y el río Sonche a través de parámetros fisicoquímicos, microbiológicos y el uso de índices como el de contaminación mineralógica (ICOMI). Se establecieron cinco puntos de muestreo, realizándose la colecta de muestras en los meses de agosto y diciembre del 2015. Los resultados fueron contrastados con los Estándares de Calidad Ambiental para aguas del Perú, y a partir de estos se obtuvo que los parámetros microbiológicos no cumplen con ninguna de las categorías analizadas. Además, el índice ICOMI, reflejó un mayor grado de contaminación en los dos puntos de muestreo de la quebrada Santa Lucía, seguido del punto ubicado en el río Sonche después de la afluencia de dicha quebrada. Finalmente, quedó evidenciado la influencia negativa que las aguas residuales de la ciudad de Chachapoyas tienen sobre la red hidrográfica adyacente, tanto directa como indirectamente, principalmente a nivel microbiológico, lo que queda reflejado en que en las estaciones de muestreo establecidas en el río Sonche, el punto que resultó con mayores concentraciones en relación a los parámetros bacteriológicos y fisicoquímicos fue el ubicado después de la confluencia con la quebrada Santa Lucía, para ambos meses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.