UC Riverside

Air pollution has been a significant problem in California’s South Coast Air Basin for many years due to the region’s unique topography, high anthropogenic emissions, weather patterns, and population density. Fine particulate matter and ozone are the two most concerning pollutants causing serious public health risks.Chemical transport models and machine learning approaches enable an effective way to study air pollution. By looking at a large domain, scientists gain insights into the transport of precursor substances in heavily polluted areas. The methods facilitate the examination of ozone’s response to emissions and meteorological factors. The main objectives are: (1) to enhance the prediction of ozone levels in the South Coast Air Basin, (2) to investigate the role of meteorology in ozone formation, and (3) to determine the most critical factors influencing ozone exceedance hours. The results showed that ozone has a strong relationship with meteorology, in which wind speed and wind direction contribute mainly to the transport and mixing of precursors, while temperature can directly contribute to ozone formation. Climate-related increases in temperature would therefore be expected to increase future ozone levels in the absence of emission changes. Control strategies from the Air Quality Management District have improved the air quality in general. However, it did not ensure the air quality also got better for minority groups. Many polluted areas are associated with industries, shipping activities, and warehouses that mostly affect the underrepresented communities. These communities frequently face social exclusion, yet there has been limited attention and research dedicated to understanding and addressing their specific needs and challenges. Air pollution research often used crowdsourced data which generally reflected a higher socioeconomic status population. A data-driven approach powered by low-cost sensors showed underrepresented groups suffered higher indoor PM2.5 due to high frequent indoor emissions from cooking, cleaning, or dusting without sufficient filtration or air exchange rate, which can be concluded that ambient and indoor PM2.5 exposures for disproportionately impacted groups cannot be generalized in population-wide. Personal exposure studies showed that people spent over 90% of their time staying indoors, emphasizing the crucial role of indoor air quality in impacting human health to a greater extent.