Mathematical Modeling of Photochemical and Chemical Interactions in Photochemical Smog Formation
2025
Luis Américo Carrasco-Venegas | Luz Genara Castañeda-Pérez | Daril Giovanni Martínez-Hilario | Juan Taumaturgo Medina-Collana | José Vulfrano González-Fernández | Cesar Gutiérrez-Cuba | Héctor Ricardo Cuba-Torre | Alex Pilco-Nuñez | Carlos Alejandro Ancieta-Dextre | Oscar Juan Rodriguez-Taranco
Atmospheric pollution results from toxic gases in low concentrations, originating from natural processes and human activities. These gases interact with each other in the presence of solar radiation, forming much more complex compounds that contribute to the formation of photochemical smog. This study presents a mathematical model to estimate the daily concentrations of primary and secondary pollutants, assuming that spatial variation is not considered within a control volume. The model includes nitrogen oxides, ozone, hydrocarbons, aldehydes, alcohols, and other gases, which are related through 52 chemical and photochemical reactions with rate constants that depend on factors such as the time of day and temperature. The model formulation results in 31 ordinary differential equations that are solved using a variable-step algorithm in MATLAB R2019a. Two scenarios are simulated: the &ldquo:closed-box&rdquo: model (CBM), where there are no inflows or outflows of gaseous flux, and the &ldquo:open-box&rdquo: model (OBM), which includes inflows and outflows within the control volume. The OBM is particularly useful for predicting concentrations during thermal inversion episodes. The results show that several pollutants reach their maximum concentrations at midday, suggesting an increase in the formation of secondary pollutants under high solar radiation, especially in the closed-box model. In the open-box model, concentration peaks shift toward the afternoon. To compare both models, the closed-box system conditions are considered, incorporating airflow into the open-box model without accounting for pollutants transported by this flow. The complex nonlinear dynamics observed in the pollutants highlight the combined influence of solar radiation, temperature, and emission rates on air quality. This study underscores the usefulness of mathematical models in developing effective mitigation strategies and assessing environmental and public health impacts.
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