PhD Thesis Presentation - Integrated Low-cost Sensor Network Framework for Quantifying Regional Ozone Dynamics and Source Contributions in Complex Environments

Increasing surface ozone (O₃) pollution poses growing threats to human health, ecosystems, and the climate, while its complex photochemistry complicates the quantification and control. Low-cost sensor networks (LCSNs) enable rapid, flexible, and high-density deployment, providing a scalable and complementary approach to traditional O₃ monitoring and mechanistic research. However, key challenges remain in ensuring the reliability of LCSNs across diverse environments and translating high-resolution sensor observations into quantitative insights into O₃ sources, transport pathways, and dominant drivers. This thesis developed an integrated LCSN-based framework that combines sensor observations, quality control and calibration procedures, chemical transport simulations, Lagrangian air trajectory tools, and interpretable machine learning to investigate regional O₃ dynamics and source contributions. The framework was applied through rapid ad-hoc deployment across the environmentally heterogeneous urban clusters of the emission-intensive Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and sustained regional monitoring over the remote, high-altitude Tibetan Plateau (TP) with complex terrain, atmospheric circulation, and extreme environmental conditions.

The results demonstrate that well-calibrated LCSNs can operate reliably across contrasting deployment scenarios, while providing a observational basis for investigating the sources and formation mechanisms of O₃ pollution. In the GBA, the November 2022 O₃ pollution episode was dominated by local photochemical production, while regional transport contributed approximately 20 ppb to O₃ concentrations. Sea-land breeze circulation and anticyclonic conditions facilitated south-to-north transport among urban clusters, highlighting the redistribution of O₃ through regional atmospheric circulation. On the TP, background O₃ accounted for 39.25% of observed surface O₃, while long-range anthropogenic transport (31.62%) and stratospheric intrusion (16.04%) represented the dominant dynamic enhancement pathways; local photochemical production contributed only 13.09% due to limited precursor availability. Major anthropogenic influences originated from the Indo-Gangetic Plain and were transported across the Himalayas through large-scale circulation and orographic lifting. Two dominant west–east transport corridors were identified: a northern pathway (Ngari–Nagqu–Lhasa–Nyingchi/Chamdo) and a southern pathway (Ngari–Shigatse–Lhasa–Nyingchi/Chamdo), with southwestern Ngari serving as a major entry region and Lhasa acting as a key convergence zone. Boundary-layer dynamics was the dominant driver during polluted periods, whereas solar radiation dominated during non-polluted periods, with surface O₃ regulated by nonlinear interactions among these factors.

The developed framework transforms sensor monitoring into an integrated analytical paradigm for characterizing O₃ dynamics, source contributions, transport pathways, and dominant drivers. The findings underscore the importance of coordinated regional management and context-specific O₃ mitigation strategies. Methodologically, this study provides a transferable approach to O₃ assessment worldwide, particularly in data-sparse and resource-constrained regions.

Keywords: sensor network; integrated framework; O3; quantitative contributions; potential source