Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Modeling of carbon sequestration and productivity for maize and oats crops using artificial neural network(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11-25) Aguilar Chavez, Fernanda; Valiente-Banuet, Juan Ignacio; emipsanchez; Clarke Crespo, Emilio; González Viejo, Claudia; School of Engineering and Sciences; Campus QuerétaroClimate change presents a critical challenge to global food security, especially as the global population continues to rise. A major driver of this phenomenon is the accumulation of greenhouse gases, particularly CO₂, which intensifies Earth's warming. Key contributors to elevated CO₂ levels include fossil fuel combustion and agricultural activities. However, agricultural systems have the potential to mitigate this effect by capturing atmospheric CO₂. Notably, few models account for the net CO₂ flux in agricultural systems, which is critical for understanding their true carbon sequestration potential. This study introduces a machine learning-based approach to model CO₂ sequestration and productivity in two forage crops, a variety of maize (Zea mays) and oats (Avena sativa), under diverse environmental conditions. The model leverages critical variables such as degree days, NDVI, and water balance. Using an artificial neural network (ANN), the study achieved robust predictive accuracy for both crops, with determination coefficients (R) of 0.95 for maize and 0.96 for oats, and low mean squared errors (MSE = 0.02). These results highlight the model’s high performance and reliability, offering a valuable tool for predicting carbon sequestration and productivity in forage crops while addressing a key gap in net CO₂ flux modeling.
- Technical and economic evaluation for two process alternatives of CO2 mineralization technology using electric arc furnace slag as raw material(Instituto Tecnológico y de Estudios Superiores de Monterrey) Martínez García, Diana Edith; Montesinos Castellanos, Alejandro; Campus Monterrey; Montesinos Castellanos, AlejandroCarbon dioxide is the major recognized cause of climate change because of its greenhouse properties and continuous accumulation in the atmosphere. It has become attractive for industries that emits great amounts of CO2 emissions to the atmosphere the application of Carbon Dioxide Utilization (CDU) technologies in their processes. In this thesis, technical, economic and environmental aspects are presented to conceptualize two pilot plants that utilize two waste materials, one being the Electric Arc Furnace (EAF) slag produced during steel making and two the CO2 removed in a Direct Reduction (DR) plant to produce either Light Weight Aggregate (LWA) for the construction industry or Precipitated Calcium Carbonate (PCC) for the chemical industry. The objective of the research reported was to evaluate the feasibility for the implementation of the CDU processes in an integrated steelmaking facility which includes a Direct Reduction plant.
