Modelling agricultural ammonia emissions : impact on particulate matter formation

In March and April 2007, the forecasts delivered in France by the chemical transport model (CTM) CHIMERE, within the operational platform for air quality monitoring and forecasting PREV'AIR, were significantly underestimating PM10 levels in the boundary layer during intense episodes. The origin of such event was first investigated analyzing observations of the PM10 speciation. It was found a lack of ammonium nitrate in the modeled aerosol composition. This was interpreted as a wrong estimate of ammonia emissions. Agriculture is the main source of anthropogenic ammonia emissions. Ammonia reacts with sulfuric and nitric acids to form ammonium sulfate and nitrate aerosols. Under favourable meteorological conditions, ammonium nitrate can contribute to high PM2.5 thus to PM10 concentrations (Walker et al., 2004, Deutsch et al., 2008), which have been linked to a range of adverse health effects (Pope et al., 2009). The estimation of ammonia emissions is associated with large uncertainties and its availability is considered to be the most uncertain factor controlling the model performance in the calculation of secondary nitrate aerosol (Hass et al., 2003, Schaap et al., 2003, Schaap et al., 2004). To improve the existent approach which is not fully satisfying in terms of model performances regarding PM10 in spring, a coupling process has been built between CHIMERE and a mechanistic VOLT'AIR model computing the NH3 Methods volatilization