Meteorological driven changes on air quality over Portugal: a KZ filter application

The Kolmogorov–Zurbenko (KZ) filter method is a tool to improve air quality management, since it determines meteorological effects on air quality concentrations and separates out those effects in order to examine underlying trends. Air quality in Portugal is exceeding the legislated particulate matter (PM10), nitrogen oxides (NO2) and ozone (O3) levels; accordingly, measures to reduce pollutant emissions have been designed. The primary objective of this work is to investigate the influence of meteorology on O3, NO2 and PM10 levels and the long-term air quality trends. Air quality and meteorological datasets were explored for the period 2002–2012 through the decomposition of time-series using the Kolmogorov–Zurbenko (KZ) filter. To determine the best meteorological predictors for the air quality data, a stepwise regression analysis of the filtered time-series was applied. The KZ filter application revealed that the short-term component has the highest contribution to the total variance of the original air quality data (≈64%–PM10; ≈52%–O3; ≈54%–NO2) followed by the seasonal component. The long-term component exhibits the influence of the emission control regulations implemented in each study region. The statistical analysis of the air quality and the meteorological data indicated that O3 has a statistically significant relationship with temperature in most of the components. The results also indicate that emission control strategies are primary regulators for NO2 and PM10 levels. Therefore, to establish an accurate strategy to improve air quality further, it will be essential to include meteorological effects. This study highlights that the KZ filter is a useful tool to support the design and implementation of adequate air quality strategies and for the investigation of the interactions between the emissions, the meteorological conditions and the air quality levels, to improve air quality management in these two urban areas.