Abstract
In this paper, various modifications of the Latin Hypercube Sampling algorithm have been used in order to evaluate the sensitivity of an environmental model output results for some dangerous air pollutants with respect to the emission levels and some chemical reaction rates. The environmental security importance is growing rapidly, becoming at present a significant topic of interest all over the world. Respectively, the environmental modeling has very high priority in various scientific fields. By identifying the major chemical reactions that affect the behavior of the system, specialists in various fields of application will be able to obtain valuable information about improving the model, which in turn will increase the reliability and sustainability of forecasts.
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Acknowledgments
This work is supported by the Bulgarian National Science Fund under Project DN 12/5/2017 “Efficient Stochastic Methods and Algorithms for Large-Scale Problems”. V. Todorov is also supported by the Bulgarian National Science Fund under Young Scientists Project KP-06-M32/2/2019 “Advanced Stochastic and Deterministic Approaches for Large-Scale Problems of Computational Mathematics” and by the National Scientific Program “Information and Communication Technologies for a Single Digital Market in Science, Education, and Security (ICT in SES)”, contract No DO1-205/2018, financed by the Ministry of Education and Science in Bulgaria. The work of I. Dimov is also supported by the Project KP-06-Russia/2017 “New Highly Efficient Stochastic Simulation Methods and Applications”, funded by the Bulgarian National Science Fund.
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Ostromsky, T., Todorov, V., Dimov, I., Georgieva, R., Zlatev, Z., Poryazov, S. (2022). Sensitivity Study of Large-Scale Air Pollution Model Based on Modifications of the Latin Hypercube Sampling Method. In: Lirkov, I., Margenov, S. (eds) Large-Scale Scientific Computing. LSSC 2021. Lecture Notes in Computer Science, vol 13127. Springer, Cham. https://doi.org/10.1007/978-3-030-97549-4_18
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