Modeling the link between carbon emissions and ocean acidification using a Lotka-Volterra dynamical system

We study the possibility that the dynamics of carbon emissions and aragonite saturation in sea water can be modeled with a non-linear coupled system of two Ordinary Differential Equations. In total, there are seven parameters plus two initial conditions that we fit in order to adjust experimental data. For the fitting, we use two independent methods: Genetic Algorithms and Monte Carlo Markov Chains, both useful at fitting in high-dimensional parameter spaces. The data for the carbon emissions we deal with is obtained from several sources dedicated to monitoring the changes in these emissions over time. We calculated aragonite saturation using a combination of carbon chemistry measures from two stations. Our findings show that with this combination of ODEs and the fitting methods chosen, these two phenomena can be reproduced within an 8% error.