Comprehensive Assessment of Air Quality Dynamics Around Yosemite National Park Using Remote Sensing, GIS, and Computational Analysis During Wildfire Events

Ambreena Javaid; Syeda Haddia Abbas

Authors

Ambreena Javaid Kinnaird College for Women, Lahore, Pakistan
Syeda Haddia Abbas Kinnaird College for Women, Lahore, Pakistan

Keywords:

Air pollution, Wildfire, AODV, Yosemite National Park

Abstract

In recent years, Mariposa County has experienced several significant wildfires, including the catastrophic Rim Fire of 2013. On July 22, 2022, Yosemite National Park faced one of its most devastating wildfires, profoundly affecting Aerosol Optical Depth (AOD) and overall air quality. This study employs an integrated approach using remote sensing, GIS, and advanced computational tools to investigate the impact of these wildfires on air quality, focusing specifically on aerosol pollution dynamics and key atmospheric pollutants. The research leverages satellite data from TROPOMI, MODIS AQUA, and Suomi NPP/VIIRS, along with meteorological inputs from GDAS. Data processing and analysis were performed using Python, MATLAB, and R, with spatial mapping and visualization achieved through ArcMap and Google Earth Engine. The study utilized the MODIS MAIAC algorithm to conduct a detailed examination of AOD fluctuations in the Yosemite region, spanning from July 21 to August 1, 2022. Our comprehensive analysis reveals significant temporal and spatial variations in aerosol pollution during the wildfire. Initial findings indicate a marked increase in AOD with the onset of the wildfire, reflecting severe impacts on atmospheric composition. Pre-fire AOD levels were relatively low at 0.12, but surged to 0.20 at the wildfire's peak, demonstrating a substantial rise in atmospheric aerosol loading. The average AOD throughout the study period was recorded at 0.16, highlighting the wildfire's prolonged effect on air quality. Furthermore, the study identifies elevated concentrations of key pollutants, including NO₂, SO₂, CO, HCHO, and O₃, during the wildfire event. The integration of data from various satellite sources and the application of machine learning models provided a more nuanced understanding of pollution patterns. The HYSPLIT model was also employed to track the distribution of air masses and contaminants, revealing significant northwestward transport. This research advances our understanding of the intricate relationships between wildfires, aerosol pollution, and air quality in Yosemite National Park. The findings offer critical insights for public health preparedness, the development of resilience strategies against wildfires, and the formulation of effective mitigation measures in fire-prone regions like Yosemite.

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