1. University of Notre Dame
Agent-based simulations of biocomplexity: Effects of adsorption to natural organic mobility through soils
Leilani Arthurs and Patricia Maurice
Civil Engineering and Geological Sciences
Gregory Madey, Xiaorong Xiang, Yingping Huang, and Ryan Kennedy
Computer Science and Engineering
University of Notre Dame

2. Natural Organic Matter (NOM)
Ubiquitous in aqueous and terrestrial environments
Breakdown product of decaying plant material
Controls many biogeochemical processes
Polydisperse mixture
Molecular weight controls NOM reactivity

3. Figure from Cabaniss et al. (2000)

4. Development of NOM Simulator
Complex interactions of NOM through porous media results in emergent behaviors amenable to a “biocomplexity” approach.
Design and use an agent-based stochastic model for NOM interactions.
We focus specifically on how NOM molecular weight affects adsorption to mineral surfaces and mobility through soil.
Additional research by Cabaniss et al. focuses on higher order biogeochemical reactions.

5. The NOM Simulator Design
Java language, J2EE architecture
Swarm and Repast software
WEB interface
Can be used interactively as part of a collaboratory
Allows for data mining

6. Low surface coverages: adsorbed fraction mimics initial
Higher surface coverages: preferential adsorption of intermediate to high molecular weight components
Kinetic data show that smaller molecules adsorb fast, gradually replaced by larger molecules
Zhou et al. (2001)

7. Adsorption & Desorption Probabilities to Fit Batch Data
High MW adsorbs slowly and desorbs slowly.
Low MW adsorbs fast and desorbs fast.

8. NOM Input Distribution
1. Example of WEB interface:
2. Initial Molecular Distribution:
(Equation Cabaniss et al. 2000)

9. Zhou et al. showed that average MW in solution decreased over time, indicating replacement of fast adsorbing small molecules by larger molecules.
The NOM Simulator captures this behavior for batch adsorption example.

10. Probability equations optimized from batch experiments applied to flow model (column experiment).
Flow simulation will be compared to future laboratory column experiments.

11. Visualization of Simulation
Settings
Legend

12. Visualization Capture 1

13. Visualization Capture 2

14. Visualization Capture 3

15. Visualization Capture 4

16. Results and Conclusions
Developed an agent-based stochastic model for NOM adsorption.
The simulator is accessible through the WEB.
Promotes the use of a “collaboratory” for geographically separated interdisciplinary scientists.
Allows users to set/refine parameters and equations.

17. Acknowledgements Dr. Steve Cabaniss (University of New Mexico)
Center for Environmental Science and Technology and Environmental Molecular Science Institute at the University of Notre Dame
National Science Foundation (EMSI, ITR)
PPG Industries