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Analysis of Vertical Structural Characteristics of a Spring Ozone Pollution Episode in the Pearl River Delta Based on UAV and Lidar
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DOI：10.1029/2025JD045856.png)
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Abstract
En 中文
Ozone concentrations have exhibited upward trends in major urban agglomerations globally, posing dual challenges as both an air pollutant and a greenhouse gas with climate forcing effects. Growing evidence indicates that climate change is driving ozone exceedance events into colder seasons, as illustrated by a springtime ozone pollution episode observed in a subtropical region. However, understanding of the vertical structure of such events remains insufficient, mainly because traditional surface monitoring and single-platform observations lack the spatiotemporal resolution needed for three-dimensional characterization. We studied a spring ozone pollution episode in the Pearl River Delta, serving as a representative case of emerging early season ozone pollution. We employed an integrated observational approach combining Unmanned Aerial Vehicles (UAVs), ozone LiDAR, wind profiler LiDAR, and ground-based measurements to comprehensively characterize the vertical structure and evolution of the pollution episode. Our analysis identified four distinct spatiotemporal evolution stages (onset, peak, persistence, and dissipation) under varying synoptic conditions. During polluted periods, suppressed turbulent kinetic energy and aerosol-enhanced thermal stability acted synergistically within the boundary layer, creating a self-amplifying process that trapped ozone. In contrast, clean episodes exhibited more vigorous mid-level turbulence that improved vertical mixing. Chemically, clean conditions were mainly limited by volatile organic compounds (VOCs) (VOCs/NOx <3.7), while pollution episodes revealed significant vertical heterogeneity, transitioning from strongly nitrogen oxides (NOx)-limited regimes (VOCs/NOx >8.0) near the surface to transitional and VOC-limited sensitivities at higher altitudes.
Keywords:
ozone pollution
vertical structure
pearl river delta
multi-platform observations
boundary layer dynamics
ozone formation sensitivity
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3.4
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288
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