Unveiling the Power of Stochastic Methods: Advancements in Air Pollution Sensitivity Analysis of the Digital Twin
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Published:2023-06-26
Issue:7
Volume:14
Page:1078
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ISSN:2073-4433
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Container-title:Atmosphere
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language:en
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Short-container-title:Atmosphere
Author:
Todorov Venelin12ORCID, Dimov Ivan1
Affiliation:
1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G̃. Bonchev Str. Bl. 25A, 1113 Sofia, Bulgaria 2. Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Acad. G̃. Bonchev Str. Bl. 8, 1113 Sofia, Bulgaria
Abstract
Thorough examination of various aspects related to the distribution of air pollutants in a specific region and the factors contributing to high concentrations is essential, as these elevated levels can be detrimental. To accomplish this, the development and improvement of a digital twin that encompasses all relevant physical processes in the atmosphere is necessary. This tool, known as DIGITAL AIR, has been created, and it is now necessary to extend it with precise sensitivity analysis. DIGITAL AIR is gaining popularity due to its effectiveness in addressing complex problems that arise in intricate environments; this motivates our further investigations. In this paper, we focus on the preparation and further investigation of DIGITAL AIR through sensitivity analysis with improved stochastic approaches for investigating high-level air pollutants. We discuss and test the utilization of this digital tool in tackling the issue. The unified Danish Eulerian model (UNI-DEM) plays a crucial role within DIGITAL AIR. This mathematical model, UNI-DEM, is highly versatile and can be applied to various studies concerning the adverse effects caused by elevated air pollution levels.
Funder
Operational Programme “Science and Education for Smart Growth” Bulgarian National Science Fund BNSF
Subject
Atmospheric Science,Environmental Science (miscellaneous)
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