A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines. This work aims to develop and test, a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools. This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes. It also allows furthering the design and assessment of air pollution control measures for a specific area. To evaluate its performance and suitability, the system was applied to the Macau Special Administrative Region (SAR), China, one of the most densely populated areas on earth, during a winter period when this area is affected by high levels of Particulate Matter (PM). Although the developed system tends to underestimate the PM concentrations, it revealed a good performance in reproducing the temporal and spatial air pollution patterns. Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated. The tested urban atmospheric emission reduction scenarios have shown air quality improvements, indicating that emission reduction measures at urban level should focus on the domestic sector. However, it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macau SAR. The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.
Keywords: High-resolution emission inventory; Particulate matter; Population exposure; Urban areas.
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