Authors:

Anusha Waseem

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

Air pollution is increasingly becoming a major global concern as the quality of our air continues to degrade. To address this issue, it is crucial to improve our understanding of air pollution and our ability to predict it accurately. This study proposes a new approach by incorporating stable isotopes into models that simulate the chemical reactions causing air pollution.To accomplish this, we have developed a simulation mechanism that captures the different reactions and substances involved in air pollution. The simulation, utilizing a specialized software known as the Music-Box simulator, generates datasets that capture the complicated interactions among pollution sources and their collective influence on air quality.We have also introduced a special kind of isotope, called 15N, into the model to track its behavior. By using advanced mathematical models, we explore how pollution sources are connected and how this affects the distribution of the 15N isotope.To validate the approach, a comparison is made between the simulations and real-world observations of specific compounds.This study aims to provide a better understanding of how certain isotopes behave during the chemical processes that cause air pollution. Additionally, we will evaluate how well machine learning models can predict air quality indicators.By combining simulation and machine learning, we hope to expand our knowledge of air pollution dynamics and contribute to the development of effective strategies to reduce air pollution.

Source:

Purdue University / 2023

Topics:

No topics listed

Co-authors:

Anusha Waseem