Skip to main content

Advertisement

Log in

A Linear-Programming-Based Strategy for Bioremediation of Oil-Polluted Marine Environments

  • Published:
Environmental Modeling & Assessment Aims and scope Submit manuscript

Abstract

A linear programming problem is considered with the aim to determine the optimal discharge point and the optimal discharge rate of a nutrient to be released to a marine environment polluted with oil. The objective is to minimize the total discharge of nutrient into the system provided that the concentrations of nutrient will reach critical values sufficient to eliminate oil residuals in certain affected zones through bioremediation. An initial boundary-value 3D problem for the advection–diffusion equation and its adjoint problems are considered to model, estimate, and control the dispersion of nutrient in a limited region. It is shown that the advection–diffusion problem is well posed, and its solution satisfies the mass balance equation. In each oil-polluted zone, the mean concentration of nutrient is determined by means of an integral formula in which the adjoint model solution serves as a weight function. Critical values of these mean concentrations are used as the constraints of linear programming problem. Some additional constraints are posed in order to limit not only the local discharge of the nutrient, but also the mean concentration of this substance in the whole region. Both constraints serve for environmental protection. The ability of the new method is demonstrated by numerical experiments on the remediation in oil-polluted channel using three control zones. The experiments show that the optimal discharge rate can always be got with a simple combination of step functions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Alvarez-Vázquez, L. J., García-Chan, N., Martínez, A., Vázquez-Méndez, M. E., & Vilar, M. A. (2010). Optimal control in wastewater management: a multi-objective study. Communications in Applied and Industrial Mathematics, 1(2), 62–77.

    Google Scholar 

  2. Boufadel, M. C., Suidan, M. T., & Venosa, A. D. (2006). Tracer studies in laboratory beach simulating tidal influences. Journal of Environmental Engineering, 132(6), 616–623.

    Article  CAS  Google Scholar 

  3. Boufadel, M. C., Suidan, M. T., & Venosa, A. D. (2007). Tracer studies in a laboratory beach subjected to waves. Journal of Environmental Engineering, 133(7), 722–732.

    Article  CAS  Google Scholar 

  4. Bragg, J. R., Prince, R. C., Harner, E. J., & Atlas, R. M. (1994). Effectiveness of bioremediation for the Exxon Valdez oil spill. Nature, 368, 413–418.

    Article  CAS  Google Scholar 

  5. Coulon, F., McKew, B. A., Osborn, A. M., McGenity, T. J., & Timmis, K. N. (2006). Effects of temperature and biostimulation on oil-degrading microbial communities in temperate estuarine waters. Environmental Microbiology, 9(1), 177–186.

    Article  Google Scholar 

  6. Crank, J., & Nicolson, P. (1947). A practical method for numerical evaluation of solutions of partial differential equations of the heat conduction type. Proceedings of the Cambridge Philological Society, 43, 50–67.

    Article  Google Scholar 

  7. Dang, Q. A., Ehrhardt, M., Tran, G. L., & Le, D. (2012). Mathematical modeling and numerical algorithms for simulation of oil pollution. Environmental Modeling and Assessment, 17(3), 275–288.

    Google Scholar 

  8. Dantzig, G. B., Orden, A., & Wolfe, P. (1955). Generalized simplex method for minimizing a linear from under linear inequality constraints. Pacific Journal of Mathematics, 5, 183–195.

    Article  Google Scholar 

  9. Dieudonné, J. (1969). Foundations of modern analysis. New York: Academic.

    Google Scholar 

  10. Folland, G. B. (1999). Real analysis: Modern techniques and their applications. New York: Wiley-Interscience (Pure and applied mathematics).

  11. Hadamard, J. (1923). Lectures on Cauchy’s problem in linear partial differential equations. New Haven: Yale University Press.

    Google Scholar 

  12. Hadley, G. (1962). Linear programming. USA: Addison-Wesley.

    Google Scholar 

  13. Hinze, M., Yan, N. N., & Zhou, Z. J. (2009). Variational discretization for optimal control governed by convection dominated diffusion equations. Journal of Computational Mathematics, 27(2–3), 237–253.

    Google Scholar 

  14. Hongfei, F. (2010). A characteristic finite element method for optimal control problems governed by convection–diffusion equations. Journal of Computational and Applied Mathematics, 235(3), 825–836.

    Article  Google Scholar 

  15. Kreyszig, E. (1978). Introductory functional analysis with applications. New York: J. Wiley.

  16. Kreyszig, E. (2006). Advanced engineering mathematics. New Jersey: Wiley.

    Google Scholar 

  17. Ladousse, A., & Tramier, B. (1991). Results of 12 years of research in spilled oil bioremediation: Inipol EAP22. In Proceedings of the 1991 International Oil Spill Conference (pp. 577–582). Washington: American Petroleum Institute.

    Google Scholar 

  18. Liu, F., Zhang, Y. H., & Hu, F. (2005). Adjoint method for assessment and reduction of chemical risk in open spaces. Environmental Modelling and Assessment, 10(4), 331–339.

    Article  Google Scholar 

  19. Marchuk G. I. (1974). Numerical solution of problems of the dynamics of atmosphere and ocean. Leningrad, Gigrometeoizdat (in Russian).

  20. Marchuk, G. I. (1986). Mathematical models in environmental problems. New York: Elsevier.

    Google Scholar 

  21. Marchuk, G. I. (1995). Adjoint equations and analysis of complex systems. Dordrecht: Kluwer.

    Google Scholar 

  22. Marchuk, G. I., & Skiba, Y. N. (1990). Role of adjoint functions in studying the sensitivity of a model of the thermal interaction of the atmosphere and ocean to variations in input data. Izvestiya, Atmospheric and Oceanic Physics, 26, 335–342.

    Google Scholar 

  23. Mehrotra, S. (1992). On the implementation of a primal–dual interior point method. SIAM Journal on Optimization, 2, 575–601.

    Article  Google Scholar 

  24. Mills, M. A., Bonner, J. S., Simon, M. A., McDonald, T. J., & Autenrieth, R. L. (1997). Bioremediation of a controlled oil release in a wetland. In Proceedings of the 24th Arctic and Marine Oilspill (AMOP) Program Technical Seminar. Environment Canada, Ottawa, Ontario, Canada, 609–616.

  25. Parra-Guevara, D., & Skiba, Y. N. (2007). A variational model for the remediation of aquatic systems polluted by biofilms. International Journal of Applied Mathematics, 20(7), 1005–1026.

    Google Scholar 

  26. Parra-Guevara, D., Skiba, Y. N., & Arellano, F. N. (2011). Optimal assessment of discharge parameters for bioremediation of oil-polluted aquatic systems. International Journal of Applied Mathematics, 24(5), 731–752.

    Google Scholar 

  27. Parra-Guevara, D., Skiba, Y. N., & Pérez-Sesma, A. (2010). A linear programming model for controlling air pollution. International Journal of Applied Mathematics, 23(3), 549–569.

    Google Scholar 

  28. Prince, R. C., Bare, R. E., Garrett, R. M., Grossman, M. J., Haith, C. E., Keim, L. G., Lee, K., Holtom, G. J., Lambert, P., Sergy, G. A., Owens, E. H., & Guénette, C. C. (1999). Bioremediation of a marine oil spill in the Arctic. In B. C. Alleman & A. Leeson (Eds.), In situ bioremediation of petroleum hydrocarbon and other organic compounds (pp. 227–232). Columbus: Battle Press.

    Google Scholar 

  29. Prince, R. C., & Bragg, J. R. (1997). Shoreline bioremediation following the Exxon Valdez oil spill in Alaska. Bioremediation Journal, 1, 97–104.

    Article  Google Scholar 

  30. Prince, R. C., Clark, J. R., Lindstrom, J. E., Butler, E. L., Brown, E. J., Winter, G., Grossman, M. J., Parrish, R. R., Bare, R. E., Braddock, J. F., Steinhauer, W. G., Douglas, G. S., Kennedy, J. M., Barter, P. J., Bragg, J. R., Harner, E. J., & Atlas, R. M. (1994). Bioremediation of the Exxon Valdez oil spill: monitoring safety and efficacy. In R. E. Hinchee, B. C. Alleman, R. E. Hoeppel, & R. N. Miller (Eds.), Hydrocarbon remediation (pp. 107–124). Boca Raton: Lewis.

    Google Scholar 

  31. Prince, R. C., Lessard, R. R., & Clark, J. R. (2003). Bioremediation of marine oil spills. Oil & Gas Science and Technology, 58(4), 463–468.

    Article  CAS  Google Scholar 

  32. Pudykiewicz, J. (1998). Application of adjoint tracer transport equations for evaluating source parameters. Atmospheric Environment, 32, 3039–3050.

    Article  CAS  Google Scholar 

  33. Ramsay, M. A., Swannell, R. P. J., Shipton, W. A., Duke, N. C., & Hill, R. T. (2000). Effect of bioremediation on the microbial community in oiled mangrove sediments. Marine Pollution Bulletin, 41, 413–419.

    Article  CAS  Google Scholar 

  34. Skiba, Y. N. (1993). Balanced and absolutely stable implicit schemes for the main and adjoint pollutant transport equations in limited area. Review of International Contamination Ambient, 9, 39–51.

    Google Scholar 

  35. Skiba, Y. N. (1996). Dual oil concentration estimates in ecologically sensitive zones. Environmental Monitoring and Assessment, 43, 139–151.

    Article  Google Scholar 

  36. Skiba, Y. N., & Parra-Guevara, D. (2000). Industrial pollution transport. Part I: formulation of the problem and air pollution estimates. Environmental Modeling and Assessment, 5, 169–175.

    Article  Google Scholar 

  37. Swannell, R. P. J., Mitchell, D., Jones, D. M., Petch, S., Head, I. M., Wilis, A., Lee, K., & Lepo, J. E. (1999). Bioremediation of oil-contaminated fine sediment. In Proceedings of the 1999 International Oil Spill Conference (pp. 751–756). Washington: American Petroleum Institute.

    Google Scholar 

  38. Swannell, R. P. J., Mitchell, D., Lethbridge, G., Jones, D., Heath, D., Hagley, M., Jones, M., Petch, S., Milne, R., Croxford, R., & Lee, K. (1999). A field demonstration of the efficacy of bioremediation to treat oiled shorelines following the Sea Empress incident. Environmental Technology, 20, 863–873.

    Article  CAS  Google Scholar 

  39. Venosa, A. D. (1998). Oil spill bioremediation on coastal shorelines: a critique. In S. K. Sikdar & R. I. Irvine (Eds.), Bioremediation: principles and practice, Vol. III. Bioremediation technologies (pp. 259–301). Lancaster: Technomic.

    Google Scholar 

  40. Venosa, A. D., Suidan, M. T., Wrenn, B. A., Strohmeier, K. L., Haines, J. R., Eberhart, B. L., King, D., & Holder, E. (1996). Bioremediation of an experimental oil spill on the shoreline of Delaware Bay. Environmental Science and Technology, 30, 1764–1775.

    Article  CAS  Google Scholar 

  41. Yan, N. N., & Zhou, Z. J. (2009). A priori and a posteriori error analysis of edge stabilization Galerkin method for the optimal control problem governed by convection-dominated diffusion equation. Journal of Computational and Applied Mathematics, 223(1), 198–217.

    Article  Google Scholar 

  42. Yee, E. (2008). Theory for reconstruction of an unknown number of contaminant sources using probabilistic inference. Boundary-Layer Meteorology, 127(3), 359–394.

    Article  Google Scholar 

  43. Zhang, Y. (1996). Solving large-scale linear programs by interior-point methods under the MATLAB environment, Technical Report TR96-01, Department of Mathematics and Statistics, University of Maryland, Baltimore.

  44. Zhu, X., Venosa, A. D., Suidan, M. T., & Lee, K. (2001). Guidelines for the bioremediation of marine shorelines and freshwater wetlands. USA: Environmental Protection Agency.

    Google Scholar 

Download references

Acknowledgments

This work was supported by the projects PAPIIT IN104811-3 (UNAM, México) and PAPIME PE103311 (UNAM, México), and by the grants 14539 and 25170 of National System of Researches (CONACyT, México).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David Parra-Guevara.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Parra-Guevara, D., Skiba, Y.N. A Linear-Programming-Based Strategy for Bioremediation of Oil-Polluted Marine Environments. Environ Model Assess 18, 135–146 (2013). https://doi.org/10.1007/s10666-012-9337-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10666-012-9337-z

Keywords

Navigation