Presencia de microplásticos en la ciénaga Guartinaja, complejo cenagoso del Bajo Sinú

Microplastic pollution in freshwater ecosystems is attracting the attention of researchers around the world. These materials have the ability to persist in the environment for long periods of time, generating accumulations that can last for thousands of years, becoming an emerging pollutant that req...

Full description

Autores:
Begambre González, Fernando José
Cifuentes Montt, Valentina
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2023
Institución:
Universidad de Córdoba
Repositorio:
Repositorio Institucional Unicórdoba
Idioma:
spa
OAI Identifier:
oai:repositorio.unicordoba.edu.co:ucordoba/7596
Acceso en línea:
https://repositorio.unicordoba.edu.co/handle/ucordoba/7596
Palabra clave:
Microplásticos
Contaminación
Superficies de predicción
IDW
Spline
Natural neighbor
Microplastics
Contamination
Prediction surfaces
IDW
Spline
Natural neighbor
Rights
openAccess
License
Copyright Universidad de Córdoba, 2023
Description
Summary:Microplastic pollution in freshwater ecosystems is attracting the attention of researchers around the world. These materials have the ability to persist in the environment for long periods of time, generating accumulations that can last for thousands of years, becoming an emerging pollutant that requires study. The objective of this research was to evaluate the presence of microplastics in the water of the Ciénaga Guartinaja through field sampling and laboratory methods. For this, water samples were taken at 20 selected points distributed randomly throughout the Ciénaga. The microplastics were extracted by the filtration method, the particles were counted and classified by visual inspection. In total, a concentration of 13.39 Mps/L was found with an average for the swamp of 0.669 MPs/L, fibers were the most found form of microplastics followed by microspheres, films, foams, and fragments. With the data obtained, three interpolation methods (IDW, Spline and Natural Neighbor) were evaluated to generate concentration prediction surfaces, which would allow visualizing and analyzing spatial patterns of the variable in question.