Investigating the influence of synoptic-scale meteorology on air quality using self-organizing maps and generalized additive modelling

摘要: Abstract The influence of synoptic-scale circulations on air quality is an area increasing interest to management in regards future climate change. This study presents analysis where the range expected circulation patterns over region Melbourne, Australia are determined and linked regional quality. A self-organizing map (SOM) has been applied daily mean sea level pressure (MSLP) reanalysis obtain twenty large-scale synoptic Australian region. time series occurrence archetypes was then employed within framework a generalized additive model (GAM) identify links between observed changes pollutant concentrations. GAM estimated shifts concentration under each type after controlling for long-term trends, seasonality, weekly emissions, spatial variation, temporal persistence. Results found overall explanatory power models be rather modest with 5.1% day-to-day variation O3, 4.7% PM10, 7.1% NO2 being explained. indicates that features not primary driver Nonetheless, further partial residual plots identified despite response at aggregate level, individual categories had differential effects pollutants. In particular, O3 were 20% higher than average when conditions resulted northeasterly gradient wind Melbourne area. For PM10 maximum increases up occurred strong anticyclonic system centered directly sum, unified approach SOM provided complementary suite tools capable identifying entire particular quantifying how they local