Computational Chemical Optimization of Nitrogen in Agricultural Fertilizers

Overview

My name is Carlos Sanchez, I go to Bakersfield High School which is located in the Kern high school district and my project is the computational optimization of Nitrogen found in agricultural fertilizers. I had always had an affinity for the scientific method, and more recently computational models. So I thought of how computational models can assist with scientific design. My family has always been affiliated with agriculture and a huge part of agriculture is fertilizers and cultivation, so all of these interests came together to form my project, after I asked one question. How can the science behind nitrogen based fertilizers be optimized through the use of computational modeling? Nitrogen-based fertilizers are essential to modern agriculture, however, the chemical processes that occur in soil 2-4 days after application can lead to losses through volatilization, leaching, and denitrification, which can lead to a reduced crop yield and contamination of groundwater. So, understanding and optimizing these short-term nitrogen dynamics is critical to improving fertilizer efficiency and minimizing environmental impact. This project aims to develop a computational model to simulate short-term soil nitrogen transformations using a system of coupled ordinary differential equations (ODEs) and test how individual reactions influence the overall system utilizing normalized sensitivity. The model models important processes, such as urea hydrolysis, ammonia, ammonium equilibrium, nitrification , plant assimilation, volatilization, leaching, and denitrification. By focusing specifically on the initial post-application phase, the simulation evaluates how reaction kinetics and rate parameters influence nitrogen loss and availability during the period when up to 40% of total nitrogen content can be lost. Independent variables include nitrogen form, concentration, and reaction rate constants, while dependent variables measure nitrogen availability and cumulative losses over time. Controlled environmental parameters such as moisture and PH are incorporated within the modeling framework to maintain consistency across simulations. To evaluate model performance, simulation outputs are compared with findings reported in peer-reviewed scientific literature and with established agricultural systems models such as APSIM and DSSAT. Additionally the model is built in computational chemical programs such as COPASI to further build a proper Chemical reaction network. This comparison evaluates the model’s ability to replicate known nitrogen transformation trends and short-term loss patterns. By analyzing the sensitivity of nitrogen loss pathways to individual reaction parameters, this study provides insight into which chemical processes exert the greatest control over short-term fertilizer efficiency. These findings contribute to a deeper mechanistic understanding of nitrogen dynamics and highlight potential targets for improving fertilizer application strategies.

Competition history

• CSEF 2026 Chemistry (Senior Division) · Entry S-05-02

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