Synergy of In-Situ and Remote Sensing Observations for Understanding Ozone Variability and Low-Level Jet Dynamics

Abstract

Several decades of regulations on anthropogenic emissions has shown that poor air quality is not only driven by chemical reactions but also by the mesoscale dynamics affecting the area. In recent years more emphasis has been placed on the concomitant factors of atmospheric composition that lead to poor air quality. What is currently needed to improve out understanding of air quality episode is the quantification of dispersion and entrainment of pollutants into the surface layer. This dissertation discusses the complex interplay between atmospheric dynamics and atmospheric chemistry with a focus on the United States Mid-Atlantic Nocturnal Low-Level Jet. This work elucidates the vertically resolved evolution of the typical Mid-Atlantic NLLJ and demonstrates how these phenomena can contribute to the formation, transport, and accumulation of ozone and ozone-precursors in the region. A detailed case study of an ozone exceedance event on May 20, 2021, in Maryland demonstrates how the confluence of long-range transport of pollutants and NLLJ-induced downmixing lead to ozone exceedances in rural communities with significant deviation from their typical ozone trends. Subsequently, a supervised machine-learning approach was developed to automate the isolation and characterization of NLLJs from high-resolution wind profile data. This effort has produced the first vertically resolved high-resolution temporal evolution of the typical Mid-Atlantic NLLJ in addition to statistics of maximum wind speeds, height of maximum, and duration of event. Furthermore, this work underscores the importance of integrating multiple observation platforms and techniques—including surface monitoring, balloon-borne sondes, lidars, and radar wind profilers—to elucidate how mesoscale phenomena contribute to the air quality. This dissertation concludes with recommendations for enhancing observational networks and refining analytical methodologies to improve our understanding of boundary layer dynamics and their implications for pollutant dispersion.