[Temporal and Spatial Variations in Ozone and Its Causes over Hainan Province from 2015 to 2020]

This study investigated temporal and spatial variations in O₃-8h (defined as the maximum 8 h average result) in Hainan Province from 2015 to 2020 and further analyzed its relationships with precursors and meteorological factors based on a dataset of observations from 32 environmental monitoring stations in Hainan. Basic statistical methods, including the empirical orthogonal function (EOF), climatic tendency rate, and climatic trend coefficient analysis, were used here. The results showed that ρ(O₃-8h) was higher in northern and western Hainan than that in other regions, with the maximum value occurring in Dongfang City (91.5 μg·m^-3). Twelve cities and counties experienced a downward trend from 2015 to 2020, and six cities and counties reached a 95% confidence level. The variation in ρ(O₃-8h) in Hainan Province demonstrated remarkable seasonal changes, which were the largest in the autumn, spring, and winter followed by the smallest in the summer, exhibiting a clear declining trend in all seasons except autumn. In addition, the cumulative variance of the first two eigenvector fields decomposed by EOF was 72.58%, which could well describe the distributed characteristics of ρ(O₃-8h) in Hainan Province. The first mode reflected the consistency of ρ(O₃-8h) variation, and the second mode reflected regional differences. Meanwhile, the change in ρ(O₃-8h) had a good correlation with the precursors and meteorological factors. Among them, the correlation coefficients between ρ(O₃-8h) and ρ(NO₂), precipitation, sunshine duration, average temperature, average wind speed, atmospheric pressure, and total radiation passed the 99% confidence test. The results of multiple linear regression showed that the variation in regressed ρ(O₃-8h) was consistent with the observed ρ(O₃-8h), and the correlation coefficient between them was 0.853, which passed the 99.9% confidence test. The regression value explained 0.72 variance of the observed value.