Integrated Modeling of Composition-Resolved Source Apportionment and Dynamic Projection for Ozone Pollution in Datong

Growing ozone (O₃) pollution in industrial cities urgently requires in-depth mechanistic research. This study utilized multi-year observational data from Datong City, China, from 2020 to 2024, integrating time trend diagnostics, correlation dynamics analysis, Environmental Protection Agency Positive Matrix Factorization 5.0 (EPA PMF 5.0) model simulations, and a grey prediction model (GM (1,1)) projection method to reveal the coupling mechanisms among O₃ precursors. Key breakthroughs include the following: (1) A ratio of volatile organic compounds (VOCs) to nitrogen oxides (NO_x) of 1.5 clearly distinguishes between NO_x-constrained (winter) and VOC-sensitive (summer) modes, a conclusion validated by the strong negative correlation between O₃ and NO_x (r = -0.80, <i>p</i> < 0.01) and the dominant role of NO titration. (2) Aromatic compounds (toluene, xylene) used as solvents in industrial emissions, despite accounting for only 7.9% of VOC mass, drove 37.1% of ozone formation potential (OFP), while petrochemical and paint production (accounting for 12.2% of VOC mass) contributed only 0.3% of OFP. (3) Quantitative analysis of OFP using PMF identified natural gas/fuel gas use and leakage (accounting for 34.9% of OFP) and solvent use (accounting for 37.1% of OFP) as key control targets. (4) The GM (1,1) model predicts that, despite a decrease in VOC concentrations (-15.7%) and an increase in NO_x concentrations (+2.4%), O₃ concentrations will rise to 169.7 μg m^-3 by 2025 (an increase of 7.4% compared to 2024), indicating an improvement in photochemical efficiency. We have established an activity-oriented prioritization framework targeting high-OFP species from key sources. This provides a scientific basis for precise O₃ emission reductions consistent with China's 15th Five-Year Plan for synergistic pollution/carbon governance.