Authors:

Faarza Khan

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About Paper:

In recent decades, air pollution levels have increased to alarming levels. In order to tackle this problem, it is important to understand the dynamics of air pollution and invent better models to understand the complex chemistry of air pollution to adopt science-based mitigation strategies and improve air quality. This study aims to incorporate stable isotopes into air quality models to enable us to better understand the causes of air pollution and provide meaningful solutions. It is believed that human activities are the primary cause of air pollution. However, a change in the chemistry of compounds present naturally in the atmosphere is also a possible cause of the increase in air pollution. The MusicBox simulator shall be used to study the behaviors of the chemical species in the atmosphere. The data from the simulator shall enable us to predict the isotope variation of N species in air pollutants and compare it to observations. We shall use Machine Learning models in addition to Monte Carlo techniques to study how changes in chemistry lead to the partitioning of 14N and 15N into products and reactants. By the end of the study, we shall be able to use the Machine Learning models to learn how 15N affects the NOx compounds and contributes to air pollution. This study shall contribute significantly to understanding the dynamics of air pollution which shall prove beneficial in developing mechanisms to bring down air pollution levels and hence, improve air quality.

Source:

Purdue University / 2023

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Co-authors:

Faarza Khan