Illustrating the benefit of using hourly monitoring data on secondary inorganic aerosol and its precursors for model evaluation
Abstract. Secondary inorganic aerosol, most notably ammonium nitrate and ammonium sulphate, is an important contributor to ambient particulate mass and provides a means for long range transport of acidifying components. The modelling of the formation and fate of these components is challenging. Especially, the formation of the semi-volatile ammonium nitrate is strongly dependent on ambient conditions and the precursor concentrations. For the first time an hourly artefact free data set from the MARGA instrument is available for the period of a full year (1 August 2007 to 1 August 2008) at Cabauw, the Netherlands. This data set is used to verify the results of the LOTOS-EUROS model. The comparison showed that the model underestimates the SIA levels. Closer inspection revealed that base line values appear well estimated for ammonium and sulphate and that the underestimation predominantly takes place at the peak concentrations. For nitrate the variability towards high concentrations is much better captured, however, a systematic relative underestimation was found. The model is able to reproduce many features of the intra-day variability observed for SIA. Although the model captures the seasonal and average diurnal variation of the SIA components, the modelled variability for the nitrate precursor gas nitric acid is much too large. It was found that the thermodynamic equilibrium module produces a too stable ammonium nitrate in winter and during night time in summer, whereas during the daytime in summer it is too unstable. We recommend to improve the model by verification of the equilibrium module, inclusion of coarse mode nitrate and to address the processes concerning SIA formation combined with a detailed analysis of the data set at hand. The benefit of the hourly data with both particulate and gas phase concentrations is illustrated and a continuation of these measurements may prove to be very useful in future model evaluation and improvement studies. Based on our findings we propose to implement a monitoring strategy using three levels of detail within the Netherlands.