Site-specific calculation of corn bioethanol carbon footprint with Life Cycle Assessment
The agricultural stage is a hotspot in the carbon footprint (CF) of the production of corn bioethanol and, within this stage, the production and use of nitrogen fertilisers is the sub process that has the greatest incidence. The current research project aims to incorporate the environmental impacts in the analysis of optimum nitrogen fertiliser rates, in addition to the agricultural and economic outputs that have been widely used in previous studies. We seek to obtain functions that describe the CF at different nitrogen rates, topographic positions and climatic conditions, incorporating them as objective functions in multiobjective optimization procedures. In order to achieve this aim, the first step is to quantify the corn bioethanol CF with Life Cycle Assessment (LCA) methodology, for fertilisation and yield data at a site-specific scale. On-farm research trials were conducted in 18 corn fields where agricultural producers applied up to 6 levels of strip nitrogen fertilisation, through an elevation gradient, in 5 crop seasons distributed over 12 years, in the centre-south region of Córdoba province, Argentina. The corn transportation and its industrial process were considered as fixed subsystems for this research. The LCA methodology follows the ISO 14067:2018 standard and the Intergovernmental Panel on Climate Change (IPCC) guidelines (2019). The R software was used to process the large datasets. A bioethanol corn CF map at a site-specific scale was achieved. As opposed to a single CF value per field, assessing the CF at a site-specific scale allows us to explore the within-field variability caused by different input rates, its interaction with environmental factors and crop yields. Spatial and temporal statistical analysis is needed to understand the relation between nitrogen fertilisation and corn bioethanol CF. Furthermore, we expect to consider the function that best represents this relation in the definition of optimum site-specific nitrogen rate.
| Main Authors: | , , , , , |
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| Format: | info:ar-repo/semantics/documento de conferencia biblioteca |
| Language: | eng |
| Published: |
Harper Adams University
2023-09
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| Subjects: | Maíz, Huella de Carbono, Huella Ecológica, Etanol, Bioetanol, Aplicación de Abonos, Gestión de Nutrientes en Función de la Ubicación, Agricultura de Precisión, Maize, Carbon Footprint, Ecological Footprint, Ethanol, Bioethanol, Fertilizer Application, Site-specific Nutrient Management, Precision Agriculture, Análisis de Ciclo de Vida, Life Cycle Assessment, |
| Online Access: | http://hdl.handle.net/20.500.12123/17404 |
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| Summary: | The agricultural stage is a hotspot in the carbon footprint (CF) of the production of corn bioethanol and, within this stage, the production and use of nitrogen fertilisers is the sub process that has the greatest incidence. The current research project aims to incorporate the environmental impacts in the analysis of optimum nitrogen fertiliser rates, in addition to the agricultural and economic outputs that have been widely used in previous studies. We seek to obtain functions that describe the CF at different nitrogen rates, topographic positions and climatic conditions, incorporating them as objective functions in multiobjective optimization procedures. In order to achieve this aim, the first step is to quantify the corn bioethanol CF with Life Cycle Assessment (LCA) methodology, for fertilisation and yield data at a site-specific scale. On-farm research trials were conducted in 18 corn fields where agricultural producers applied up to 6 levels of strip nitrogen fertilisation, through an elevation gradient, in 5 crop seasons distributed over 12 years, in the centre-south region of Córdoba province, Argentina. The corn transportation and its industrial process were considered as fixed subsystems for this research. The LCA methodology follows the ISO 14067:2018 standard and the Intergovernmental Panel on Climate Change (IPCC) guidelines (2019). The R software was used to process the large datasets. A bioethanol corn CF map at a site-specific scale was achieved. As opposed to a single CF value per field, assessing the CF at a site-specific scale allows us to explore the within-field variability caused by different input rates, its interaction with environmental factors and crop yields. Spatial and temporal statistical analysis is needed to understand the relation between nitrogen fertilisation and corn bioethanol CF. Furthermore,
we expect to consider the function that best represents this relation in the definition of optimum site-specific nitrogen rate. |
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