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Multi-objective Optimization of Emission Parameters for Air Pollution Models

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Air Pollution Modeling and its Application XXI

Abstract

Optimization algorithms for control of industrial emission parameters with environmental and economic criteria are considered. Combination of the vector relaxation with external penalty function methods is used for multi-objective optimization. The optimization algorithms are developed for air quality management in decision support information systems and to generate some necessary emission scenarios in integrated air pollution models too.

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References

  1. Afshartous D, Guan Y, Mehrotra A (2009) US coast guard air station location with respect to distress calls: a spatial statistics and optimization based methodology. Eur J Oper Res 196:1086–1096

    Article  Google Scholar 

  2. Arrow KJ, Hurwicz L, Uzawa H (1958) Studies in linear and non-linear. Programming. Stanford University Press, Stanford

    Google Scholar 

  3. Bejko IV, Nochvai VI (2008) Modeling and optimization of emission processes parameters in urban atmosphere. J “Math comput model”. Series: Physics and mathematic – Kamyanets-Podilsky, vol 1, pp 25–32 (in Ukrainian)

    Google Scholar 

  4. Carnevale C, Pisoni E, Volta M (2008) A multi-objective nonlinear optimization approach to designing effective air quality control policies. Automatica 44:1632–1641

    Article  Google Scholar 

  5. Hakami A, Odman MT, Russell AG (2004) Non-linearity in atmospheric response: a direct sensitivity analysis approach. J Geophys Res 109:D15303

    Article  Google Scholar 

  6. Holnicki P (2006) On the real-time emission control – case study application. Control Cybern 235:351–367

    Google Scholar 

  7. Holnicki P, Sokolowski J, Zochowski A (1987) Diferential stability of solutions to air quality control problems in urban area. Appl Math 32(3):240–253

    Google Scholar 

  8. Ismael A, Vaz F, Ferreira EC (2009) Air pollution control with semi–infinite programming. Appl Math Model 33:1957–1969

    Article  Google Scholar 

  9. Izmailov AF (2006) Sensitivity in optimization, Moscow (in Russian)

    Google Scholar 

  10. Makowski M (2008) Multi-objective decision support including sensitivity analysis. International Institute for Applied Systems Analysis, Laxenburg, pp 21–22

    Google Scholar 

  11. Mallet V, Sportisse B (2005) A comprehensive study of ozone sensitivity with respect to emissions over Europe with a chemistry-transport model. J Geophys Res 110(D22)

    Google Scholar 

  12. Marchuk GI (1986) Mathematical models in environmental problems. Elsevier, Amsterdam

    Google Scholar 

  13. Seibert P, Frank A (2004) Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode. Atmos Chem Phys 4:51–63. doi:10.5194/acp-4-51-2

    Article  CAS  Google Scholar 

  14. Shavrina AV, Sosonkin MG, Veles AA et al (2008) Integrated modeling of surface and tropospheric ozone for Kyiv city. In: Barnes I, Kharytonov MM (eds) Simulation and assessment of chemical processes in a multiphase environment, vol 25, NATO science for peace and security series C: environmental security. Springer, Dordrecht, pp 345–357

    Chapter  Google Scholar 

  15. Tong D, Muller N, Kan H, Mendelsohn R (2009) Using air quality modeling to study source-receptor relationships between nitrogen oxides emissions and ozone exposures over the United States. Environ Int Nov 35(8):1109–17

    Article  CAS  Google Scholar 

  16. Zhang Y, Bischof C, Easter R, Wu P (2005) Sensitivity analysis of photochemical indicators for O3 chemistry using automatic differentiation. J Atmos Chem 51:1–41

    Article  CAS  Google Scholar 

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Correspondence to Volodymyr Nochvai .

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Nochvai, V. (2011). Multi-objective Optimization of Emission Parameters for Air Pollution Models. In: Steyn, D., Trini Castelli, S. (eds) Air Pollution Modeling and its Application XXI. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1359-8_115

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