An assessment of the ability of three-dimensional air quality models with current thermodynamic equilibrium models to predict aerosol NO3?

摘要

The partitioning of total nitrate (TNO3) and total ammonium (TNH4) between gas and aerosol phases is studied with two thermodynamic equilibrium models, ISORROPIA and the aerosol inorganics model (AIM), and three data sets: high time resolution measurement data from the 1999 Atlanta Supersite Experiment (summer case) and the 2002 Pittsburgh Air Quality Study (PAQS) Supersite Experiment (winter case), and 12-hour measurement data from the Clinton site, North Carolina, in 1999. At the Atlanta site, both models reproduced a large percentage of the observed aerosol NH4 + and HNO3 (NH4 +: >94% and HNO3: >86%) within a factor of 1.5, whereas neither model reproduced a majority of observed aerosol NO3 ~- and NH3 (NO3 ~-: <48% and NH3: <51%) within a factor of 2. At the Pittsburgh site, both models reproduced more than 76% of observed NO3 ~- within a factor of 2. At the Clinton site, both models performed a little better on aerosol NO3 ~- (47?C58% within a factor of 1.5) than at the Atlanta site but worse than at the Pittsburgh site. Sensitivity test of thermodynamic models with Gaussian random errors indicates that in many cases, measurement errors in SO4 2~- and TNH4 can explain a major fraction of the discrepancies between the equilibrium model predictions and observations in partitioning of TNO3. Comparison of predictions of the three-dimensional (3-D) Community Multiscale Air Quality (CMAQ) model with the observations over the continental United States indicates that the performance of the 3-D model for NO3 ~-, HNO3, NH4 +, and NH3 strongly depends on its performance for TNO3, TNH4, and SO4 2~-. Tests show that errors associated with SO4 2~- and TNH4 predictions of the 3-D model can result in the thermodynamic model calculation replicating only 47% and 60% of base case NO3 ~- within a factor of 2 for summer and winter cases, respectively. It was found that errors in TNH4 are more critical than errors in SO4 2~- to prediction of NO3 ~-.