The influence of synoptic-scale circulations on air quality is an area of increasing interest to air quality management in regards to future climate change. This study presents an analysis where the dominant synoptic ‘types’ over the region of Melbourne, Australia are determined and linked to regional air quality. First, a self-organising map (SOM) is used to generate a time series of synoptic charts that classify the annual daily circulation affecting Melbourne into 20 different synoptic types. SOM results are then employed within the framework of a generalized additive model (GAM) to identify links between synoptic-scale circulations and observed changes air pollutant concentrations. The GAMs estimate shifts in pollutant concentrations under each synoptic type after controlling for long-term trends, seasonality, weekly emissions, spatial variation, and temporal persistence. Results showed the aggregate impact of synoptic circulations in the models to be quite modest as only 5.1% of the daily variance in O3, 4.7% in PM10, and 7.1% in NO2 were explained by shifts in synoptic circulations. Further analysis of the partial residual plots identified that despite a modest response at the aggregate level, individual synoptic categories had differential effects on air pollutants. In particular, increases of up to 40% in NO2 and PM10 and 30% in O3 occur when a synoptic conditions result in a north-easterly gradient wind over the Melbourne area. Additionally, NO2 and PM10 levels also showed increases of up to 40% when a strong high pressure system was centered directly over the Melbourne area. In sum, the unified approach of SOM and GAM proved to be a complementary suite of tools capable of identifying the entire range synoptic circulation patterns over a particular region and quantifying how they influence local air quality.
Keywords: air pollution, generalized additive models, self-organizing maps, and synoptic meteorology.