The dynamics of phosphorus (P) in sediments is complex because it is impacted by biogeochemical and physical processes. Among other processes, phosphate that is released by mineralization of organic matter (biogeochemistry) can adsorb to iron oxides, precipitate as apatite (calcium phosphate mineral), or adsorb to calcium carbonate ($CaCO_3$). Adsorption to iron oxides occurs in the oxic zone, while phosphate is released again when iron oxides are reduced in the anoxic zone of the sediment. The last two processes (authigenic apatite formation and P adsorption to $CaCO_3$) can play an important role in the long-term removal of P.
In this exercise, you will make a very simple model of P dynamics in sediments. Assume that P is only exchanging between two pools: dissolved phosphate\footnote{Dissolved phosphate has four species: $H_3PO_4$, $H_2PO_4^-$, $HPO_4^{2-}$ and $PO_4^{3-}$. The speciation depends on pH. At ambient pH, temperature and salinity assumed in this exercise, $H_2PO_4^-$ is the dominant species.} ($H_2PO_4^{-}$), and the phosphate adsorbed to $CaCO_3$ ($P_{ads}$, solid phase). The other processes involved in P dynamics will be ignored.
Assuming an unlimited availability of $CaCO_3$, consider that adsorption and desorption of phosphate can be represented by the following reversible reaction: $$P_{ads} \leftrightarrow H_2 PO_4^{-} + H^+.$$
Due to sediment compaction, the sediment porosity $[m^3~liquid~m^{-3}~bulk]$ declines exponentially with depth from 0.9 at the surface to 0.6 at depth. The coefficient describing the rate of this attenuation is $porcoef = 0.5~cm^{-1}$. Although this variation in porosity influences the advective velocity, we will ignore this in our model.
Use the R-package marelac to estimate the molecular diffusion coefficient of phosphate assuming a temperature of $20~^\circ$C and a salinity of 35. Assume constant $pH$ of 7. At this $pH$, temperature and salinity, the most abundant phosphate species is $H_2PO_4^{-}$. The diffusion coefficient needs to be corrected for tortuosity, as explained in the lectures.
For the P dynamics, assume:
The P:C ratio in the organic matter is according to Redfield: 1 mole of P per 106 moles of C.
There is no deposition of adsorbed phosphate from the water-column.
Phosphate adsorption to $CaCO_3$ is described by first-order kinetics with respect to $H_2PO_4^{-}$ (rate constant $r_{ads}$). This is a reasonable assumption if the concentration of $CaCO_3$ in the sediment is so high that it never becomes limiting.
Later, perform a sensitivity analysis assuming that the value of $r_{ads}$ varies between 0 and $5\times 10^{-3}~d^{-1}$.
Phosphate desorption from $CaCO_3$ is described by first-order kinetics with respect to $P_{ads}$. The corresponding rate constant is $r_{des} = 1\times 10^{-5}~d^{-1}$.
Add P dynamics to the template markdown file for early diagenesis RTM_porous1D.Rmd.\footnote{You can obtain this file from Rstudio: File $\rightarrow$ new File $\rightarrow$ Rmarkdown $\rightarrow$ from template $\rightarrow$ RTM_porous1D. Save this file under a different name. Do not forget to change the heading of this file.} You can use the description for the carbon diagenesis in the template as a basis for the present exercise. There is no need to remove the DIC state variable from the model. However, you can ignore the posibility that DIC may be removed or added to the system due to precipitation or dissolution of $CaCO_3$.
Use m, mol, and d to create the units used in the model. Convert all input parameters into these units (e.g., POC deposition flux, bioturbation mixing coefficient, diffusion coefficient).
First add dissolved phosphate as a state variable, and make sure that the model can be solved with only this species added. Then add the adsorbed phosphate and implement the dynamics.
Make sure to return from the model function ordinary output variables that will be needed when creating the P budget and interpreting the results:
Run three simulations, with the adsorption rate constant set to 0, $1\times 10^{-3}$, and $5\times 10^{-3}~d^{-1}$.
Plot the results and try to understand what happens. Plot in separate R-chunks the depth profiles of concentrations, process rates and the quotient. This will help you better understand and interpret the results. Discuss with the teachers to check your understanding.
Check the sensitivity of your model to the depth of the sediment column in which you model the P dynamics. That is, run your model with the depth of the sediment column set to $60~cm$ (initial), $100~cm$ and $200~cm$ (the easiest way to do this is to simply change the global variable Length
and re-run the model). Try to understand what happens and why. Discuss your ideas with the teachers.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.