Air Quality Project as a Multidisciplinary Method of Innovative Learning: Measurements in Guadalajara, México During 2022

Air quality is not typically covered in undergraduate studies, particularly in Chemical Engineering programs, despite its critical importance in addressing environmental challenges. This project provided two undergraduate students with the opportunity to engage in multidisciplinary research, helping them develop a broader understanding of air pollution and its impacts. Air pollution is a pressing issue that negatively affects human health, especially in urban areas where exposure to high concentrations of particulate matter (PM) in ambient air is a serious concern. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{P M}_{\mathbf{2}. 5}$</tex> (particles with a diameter of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2. 5}$</tex> micrometers or less) and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{1}$</tex> are particularly hazardous, as they can penetrate deep into the lungs and even enter the bloodstream, leading to significant health risks such as respiratory and cardiovascular diseases. Traditionally, air quality has been monitored using automatic stations, which, while effective, are costly and cover only limited areas. Recently, the use of low-cost sensors has gained attention as a more flexible and affordable alternative, allowing for the identification of localized areas with high pollution, or “microenvironments.” This six-month study, conducted by two Chemical Engineering students, involved the installation of 14 low-cost PM monitors on the roofs of vehicles to analyze PM concentrations throughout the Guadalajara Metropolitan Area, Mexico, in 2022. The students gained valuable skills in data analysis, environmental monitoring, programming, and scientific writing. Moreover, they wrote code in Python, using ChatGPT as a generative AI tool, with the aim of producing high-quality graphs to analyze the big data sets collected. The study found that PM concentrations were highest in the city center, where the daily average reached <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$79 \mu ~\mathrm{g} / \mathrm{m}^{3}$</tex>, likely due to heavy vehicular traffic. In the southern part of the city, PM concentrations peaked at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$94.5 \mu ~\mathrm{g} / \mathrm{m}^{3}$</tex>, potentially linked to traditional brick manufacturing. These findings highlight the importance of identifying specific pollution sources to improve air quality in urban settings.