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Reaction Count
3. RESULTS AND DISCUSSION
Using this agent-based model (ABM), we can simulate many aspects of NOM
behavior, including elemental and functional group composition, size distribution,
bioavailability to microbes, metal complexation and reactive transport. In addition, we can
examine how specific environmental factors can affect these behaviors- for example, how
differences in precursors lead to differences in bioavailability, or how exposure to sunlight
affects metal complexation.
One advantage of the ABM is that we can simulate the evolution of humic
substances from specific precursor molecules and observe not only changes in bulk
properties (%C, MW n , etc.) but also the reactions leading to these changes. For example,
Figure 1 shows how the production of –COOH groups lags the photolysis of conjugated
alkenes in a simulation of protein and lignin fragments exposed to sunlight.
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Figure 1. Surface water incubation of biopolymers: Reaction counts per 50 hour interval for
C=C oxidation to diol (squares, right Y axis), alcohol oxidation to aldehyde or ketone (X),
aldehyde oxidation to -COOH (circles).
Metal complexation is simulated a priori (without calibration on NOM) by combining
the AlphaStep output (molecular structure data) with a quantitative structure-property
relationship (QSPR) to predict a metal binding K’ for each molecule in the assemblage.
These K’ values can then be used to calculate binding in solution of known NOM content
(Fig. 2). The results are semi-quantitative, which is quite remarkable given that the model
is not calibrated using any NOM complexation data.
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