Scenarios Analysis of Stratospheric Ozone Concentrations – Box Modeling and Statistical Inference

This study uses a method that combines box models and statistical inference to deeply explore the interaction between stratospheric ozone concentration and nitrogen oxides (NOx) and chlorine compounds (ClOx). Ordinary differential equations written in MATLAB were used to simulate chemical reactions in the atmosphere. Based on these results, evaluate qualitatively the effects of NOx and ClOx on ozone concentration by further multiple linear regression analysis using VIF for multicollinearity detection and AIC for model selection. Results show that NO2 and N2O5 have significant effects on the variations of O3, while Cl is related to the content of another species. The developed fast simulator can quickly process complex chemical reaction equations and meteorological data to predict future ozone concentration changes. The research not only enhances understanding of atmospheric chemical dynamics but also helps inform environmental policy.

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Publication Details

Journal
International Journal of Computer Science and Information Technology
Published
2024-08-12
DOI
https://doi.org/10.62051/ijcsit.v3n3.26
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
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article

Scenarios Analysis of Stratospheric Ozone Concentrations – Box Modeling and Statistical Inference

Jiang Chen
International Journal of Computer Science and Information Technology
Air Quality Monitoring and Forecasting
article

Scenarios Analysis of Stratospheric Ozone Concentrations – Box Modeling and Statistical Inference

Jiang Chen
article en

Abstract

This study uses a method that combines box models and statistical inference to deeply explore the interaction between stratospheric ozone concentration and nitrogen oxides (NOx) and chlorine compounds (ClOx). Ordinary differential equations written in MATLAB were used to simulate chemical reactions in the atmosphere. Based on these results, evaluate qualitatively the effects of NOx and ClOx on ozone concentration by further multiple linear regression analysis using VIF for multicollinearity detection and AIC for model selection. Results show that NO2 and N2O5 have significant effects on the variations of O3, while Cl is related to the content of another species. The developed fast simulator can quickly process complex chemical reaction equations and meteorological data to predict future ozone concentration changes. The research not only enhances understanding of atmospheric chemical dynamics but also helps inform environmental policy.

International Journal of Computer Science and Information TechnologyVol. 3(3)
Nanjing Foreign Language School (CN)
Openalex Percentile: Top 88%
Air Quality Monitoring and Forecasting
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Scenarios Analysis of Stratospheric Ozone Concentrations – Box Modeling and Statistical Inference — Jiang Chen · International Journal of Computer Science and Information Technology (2024) | TGRS Research Map | TGRS