Work

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

Year: 2024

Type: article

Abstract: 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.

Source: Ain Shams Engineering Journal

DOI: 10.1016/j.asej.2024.103138

Authors: Muhammad Yaseen, Faisal Sultan, Muhammad Sohail, Yasser Elmasry

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $860

Funder: King Khalid University

Awards: G1379669787, G4439699463