Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis

The Deviation Closeness Analysis (DCA) quantifies the disparities between approximated and the invariant curves, using advanced Model Reduction Techniques (MRTs). The MRTs, Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM) are focusing on assessing the closenes...

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Main Authors: Muhammad Yaseen, Faisal Sultan, Muhammad Sohail, Yasser Elmasry
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Ain Shams Engineering Journal
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Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924005197
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author Muhammad Yaseen
Faisal Sultan
Muhammad Sohail
Yasser Elmasry
author_facet Muhammad Yaseen
Faisal Sultan
Muhammad Sohail
Yasser Elmasry
author_sort Muhammad Yaseen
collection DOAJ
description The Deviation Closeness Analysis (DCA) quantifies the disparities between approximated and the invariant curves, using advanced Model Reduction Techniques (MRTs). The MRTs, Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM) are focusing on assessing the closeness between model predictions and actual data points applied to Nitrogen Oxides (NOx) and Ozone (O3) simulation in the atmosphere, crucial for air quality regulation and smog formation. The novel contribution in this article is to perform the comparative analysis between the reduced model predictions and actual data points through DCA for NOx and O3 within complex reaction mechanisms impacting the ozone layer. Further, Local sensitivity analysis identifies influence of species and parameters in given chemical model. Findings indicate achievable invariant regions and influential parameters for NOx and O3, presented through simulations and tabular comparisons.
format Article
id doaj-art-5a5f347c0d344f0291f64fe64bd237d8
institution Kabale University
issn 2090-4479
language English
publishDate 2024-12-01
publisher Elsevier
record_format Article
series Ain Shams Engineering Journal
spelling doaj-art-5a5f347c0d344f0291f64fe64bd237d82024-12-18T08:48:30ZengElsevierAin Shams Engineering Journal2090-44792024-12-011512103138Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness AnalysisMuhammad Yaseen0Faisal Sultan1Muhammad Sohail2Yasser Elmasry3Institute of Mathematics, Khwaja Fareed University of Engineering and Information Technology, PakistanInstitute of Mathematics, Khwaja Fareed University of Engineering and Information Technology, Pakistan; Corresponding author.Institute of Mathematics, Khwaja Fareed University of Engineering and Information Technology, Pakistan; Composite Materials Scientific Research Center of Azerbaijan State University of Economics (UNEC), 194 Murtaza Mukhtarov Street, Baku AZ1065, AzerbaijanDepartment of Mathematics, College of Science, King Khalid University, P.O. Box 9004, Abha 61466, Saudi ArabiaThe Deviation Closeness Analysis (DCA) quantifies the disparities between approximated and the invariant curves, using advanced Model Reduction Techniques (MRTs). The MRTs, Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM) are focusing on assessing the closeness between model predictions and actual data points applied to Nitrogen Oxides (NOx) and Ozone (O3) simulation in the atmosphere, crucial for air quality regulation and smog formation. The novel contribution in this article is to perform the comparative analysis between the reduced model predictions and actual data points through DCA for NOx and O3 within complex reaction mechanisms impacting the ozone layer. Further, Local sensitivity analysis identifies influence of species and parameters in given chemical model. Findings indicate achievable invariant regions and influential parameters for NOx and O3, presented through simulations and tabular comparisons.http://www.sciencedirect.com/science/article/pii/S2090447924005197Chemical kineticModel reduction techniquesSlow invariant manifoldSensitivity analysisDeviation-Closeness Analysis
spellingShingle Muhammad Yaseen
Faisal Sultan
Muhammad Sohail
Yasser Elmasry
Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
Ain Shams Engineering Journal
Chemical kinetic
Model reduction techniques
Slow invariant manifold
Sensitivity analysis
Deviation-Closeness Analysis
title Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
title_full Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
title_fullStr Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
title_full_unstemmed Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
title_short Advanced quantitative analysis of nitrogen oxides and ozone: Integrating model reduction techniques with Deviation-Closeness Analysis
title_sort advanced quantitative analysis of nitrogen oxides and ozone integrating model reduction techniques with deviation closeness analysis
topic Chemical kinetic
Model reduction techniques
Slow invariant manifold
Sensitivity analysis
Deviation-Closeness Analysis
url http://www.sciencedirect.com/science/article/pii/S2090447924005197
work_keys_str_mv AT muhammadyaseen advancedquantitativeanalysisofnitrogenoxidesandozoneintegratingmodelreductiontechniqueswithdeviationclosenessanalysis
AT faisalsultan advancedquantitativeanalysisofnitrogenoxidesandozoneintegratingmodelreductiontechniqueswithdeviationclosenessanalysis
AT muhammadsohail advancedquantitativeanalysisofnitrogenoxidesandozoneintegratingmodelreductiontechniqueswithdeviationclosenessanalysis
AT yasserelmasry advancedquantitativeanalysisofnitrogenoxidesandozoneintegratingmodelreductiontechniqueswithdeviationclosenessanalysis