Estimación de emisiones y modelización del comportamiento ambiental de los gases de efecto invernadero para un relleno sanitario

The study addressed the problem of greenhouse gas (GHG) emissions at the La Cortada Landfill (RSLC) in Pamplona, ​​Norte de Santander. Since its creation in 2006, this landfill has received a significant amount of waste daily, contributing to the constant release of GHGs. The main objective was to estimate GHG emissions, understand their trajectories and model their dispersion in the environment. To achieve this, specialized tools such as LandGEM, Hysplit and Aermod were used, satellite images from the OLI sensor on board the Landsat 8 satellite were selected in periods between August and October from 2016 to 2020. An empirical methane estimation model was also applied. (estimated CH4), which relates land surface temperature (LST) to methane concentrations measured in the field between 2021-2023 (observed CH4). The results showed that measurements using satellite images gave lower values ​​than those obtained in the field (0.007 mg/m3 per year, annual average of Estimated CH4) and (0.05 mg/m3 per year, annual average of observed CH4). In conclusion, The RSLC represented a significant source of GHGs, and this estimation approach based on satellite imagery and field measurements validated the importance of addressing these emissions to promote more sustainable solid waste disposal practices and protect air quality and regional well-being. , likewise allows arguing the implementation of biogas capture systems in the landfill to reduce methane (CH4) emissions, and the exploration so that this resource can be used as a source of renewable energy to produce heat or electricity, which would contribute to sustainability and emissions reduction. El estudio abordó el problema de las emisiones de gases de efecto invernadero (GEI) en el Relleno Sanitario La Cortada (RSLC) de Pamplona, ​​Norte de Santander, desde su creación en 2006, este vertedero ha recibido una cantidad significativa de residuos diariamente, contribuyendo a la liberación constante de GEI. El objetivo principal fue estimar las emisiones de GEI, comprender sus trayectorias y modelar su dispersión en el entorno. Para lograrlo, se utilizaron herramientas especializadas como LandGEM, Hysplit y Aermod, se seleccionaron imágenes satelitales del sensor OLI a bordo del satélite Landsat 8 en períodos entre agosto y octubre de los años 2016 al 2020. También se aplicó un modelo empírico de estimación de metano (CH4 estimado), que relaciona la temperatura superficial terrestre (LST) con las concentraciones de