Ground-level ozone (O3) is one of the most worrisome air pollutants regarding environmental and health impacts. There is a need for a deeper understanding of its spatial and temporal dynamics. Models are needed to provide continuous temporal and spatial coverage in ozone concentration data with a fine resolution. However, the simultaneous influence of each determinant of ozone dynamics, their spatial and temporal variations, and their interaction make the resulting dynamics of O3 concentrations difficult to understand. This study aimed to i) identify different classes of temporal dynamics of O3 at daily and 9 km2 resolution over a long-term period of 12 years, ii) identify the potential determinants of these dynamics and, iii) explore the spatial distribution of the potential classes of temporal dynamics on a spatial continuum and over about 1000 km2. Thus, 126 time series of 12-year daily ozone concentrations were classified using dynamic time warping (DTW) and hierarchical clustering (study area centered on Besançon, eastern France). The different temporal dynamics obtained differed on elevation, ozone levels, proportions of urbanized and vegetated surfaces. We identified different daily ozone temporal dynamics, spatially structured, that overlapped areas called urban, suburban and rural. Urbanization, elevation and vegetation acted as determinants simultaneously. Individually, elevation and vegetated surface were positively correlated with O3 concentrations (r = 0.84 and r = 0.41, respectively), while the proportion of urbanized area was negatively correlated with O3 (r = -0.39). An increasing ozone concentration gradient was observed from urban to rural areas and was reinforced by the elevation gradient. Rural areas were both subject to higher ozone levels (p < 0.001), least monitoring and lower predictability. We identified main determinants of the temporal dynamics of ozone concentrations. The joint influence of determinants was also synthesized. This study proposed a systematic, and reproducible way to build exposure area mapping.
Keywords: Exposure areas; Land use; Ozone; Spatial and temporal dynamics.
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