A method to assess the inter-annual weather-dependent variability in air pollution concentration and deposition based on weather typing

Abstract

Annual anomalies in air pollutant concentrations, and deposition (bulk and throughfall) of sulphate, nitrate and ammonium, in the Gothenburg region, south-west Sweden, were correlated with optimized linear combinations of the yearly frequency of Lamb Weather Types (LWTs) to determine the extent to which the year-to-year variation in pollution exposure can be partly explained by weather related variability. Air concentrations of urban NO2, CO, PM10, as well as O3 at both an urban and a rural monitoring site, and the deposition of sulphate, nitrate and ammonium for the period 1997–2010 were included in the analysis. Linear detrending of the time series was performed to estimate trend-independent anomalies. These estimated anomalies were subtracted from observed annual values. Then the statistical significance of temporal trends with and without LWT adjustment was tested. For the pollutants studied, the annual anomaly was well correlated with the annual LWT combination (R2 in the range 0.52–0.90). Some negative (annual average [NO2], ammonia bulk deposition) or positive (average urban [O3]) temporal trends became statistically significant (p < 0.05) when the LWT adjustment was applied. In all the cases but one (NH4 throughfall, for which no temporal trend existed) the significance of temporal trends became stronger with LWT adjustment. For nitrate and ammonium, the LWT based adjustment explained a larger fraction of the inter-annual variation for bulk deposition than for throughfall. This is probably linked to the longer time scale of canopy related dry deposition processes influencing throughfall being explained to a lesser extent by LWTs than the meteorological factors controlling bulk deposition. The proposed novel methodology can be used by authorities responsible for air pollution management, and by researchers studying temporal trends in pollution, to evaluate e.g. the relative importance of changes in emissions and weather variability in annual air pollution exposure.