| ABSTRACT |
Ground-level ozone (GLO) is a major air pollutant that can adversely affect human health and the environment. This study aims to develop spatial extreme ozone maps for Peninsular Malaysia using cyclic non-stationary Generalized Extreme Value (GEV) and max-stable models. Weekly maximum GLO concentration data collected from air quality monitoring stations will be analysed to identify extreme ozone events and their spatial dependence. The cyclic non-stationary GEV model will be used to capture seasonal patterns in ozone extremes, while max-stable models, including Smith, Schlather, and Brown¿Resnick models, will be applied to investigate spatial dependence. The best-fitting model will be selected based on appropriate statistical criteria. Finally, spatial maps of ozone return levels will be generated to identify areas at risk of extreme ozone concentrations. The findings are expected to provide valuable information for understanding the spatial patterns of extreme ozone events and supporting air quality management in Peninsular Malaysia.
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