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

Abstract

[1] The partitioning of total nitrate (TNO 3 ) and total ammonium (TNH 4 ) 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 NH 4 + and HNO 3 (NH 4 + : >94% and HNO 3 : >86%) within a factor of 1.5, whereas neither model reproduced a majority of observed aerosol NO 3 À and NH 3 (NO 3 À : <48% and NH 3 : <51%) within a factor of 2. At the Pittsburgh site, both models reproduced more than 76% of observed NO 3 À within a factor of 2. At the Clinton site, both models performed a little better on aerosol NO 3 À (47-58% 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 SO 4 2À and TNH 4 can explain a major fraction of the discrepancies between the equilibrium model predictions and observations in partitioning of À within a factor of 2 for summer and winter cases, respectively. It was found that errors in TNH 4 are more critical than errors in SO 4 2À to prediction of NO 3 À .Citation: Yu, S., R. Dennis, S. Roselle, A. Nenes, J. Walker, B. Eder, K. Schere, J. Swall, and W. Robarge (2005), An assessment of the ability of three-dimensional air quality models with current thermodynamic equilibrium models to predict aerosol NO 3 À ,

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

“…Model predictions tend to underestimate the low particle phase nitrate concentrations in summer, especially when temperatures exceed 25 • C. Model predictions for particulate nitrate are usually less than 1 µg m −3 under these conditions, while 2-3 µg m −3 nitrate concentrations are still observed in the ambient air. Similar underpredictions of summertime nitrate have been reported in other regional modeling studies (Appel et al, 2008;Tesche et al, 2006;Yu et al, 2005;Zhang et al, 2014a). Model calculations reflect thermodynamics and kinetic gas-particle transfer for ammonium nitrate in mixed particles, suggesting that some other form of nitrate is present in the real atmosphere, such as organo-nitrates (Day et al, 2010).…”

Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis

“…Although the NMB values for aerosol NO − 3 are less than 60 %, as shown in Table 5a, the poor model performance for NO − 3 (see the scatter plot in Fig. 6a and the correlation of less than 0.40 in Table 5a) is related in part to volatility issues for measurements associated with NO (Yu et al, 2005). Table 5a indicates that both models overestimated the observed mean OC, EC and TC concentrations at the IMPROVE sites by 25.9, 54.9 and 31.9 % for WRF-CMAQ/CAM, respectively, and by 23.8, 52.2 and 29.7 % for WRF-CMAQ/RRTMG, respectively.…”

Inverse modeling and mapping US air quality influences of inorganic PM&lt;sub&gt;2.5&lt;/sub&gt; precursor emissions using the adjoint of GEOS-Chem

“…That the most significant difference between prior and optimized emissions scaling factors for any species considered is for NH 3 emissions is not an artifact of these emissions be- ing ascribed the largest prior uncertainty, as it is true even when each type of emission is assumed a prior uncertainty of 100%, see US have been analyzed in several recent studies (Gilliland et al, 2003Pinder et al, 2006;Stephen and Aneja, 2008) and are cited as a significant source of model uncertainty (Yu et al, 2005;Nowak et al, 2006;Zhang et al, 2008). The inverse modeling efforts of Gilliland et al (2003Gilliland et al ( , 2006 focused on imparting seasonality to the aseasonal National Emissions Inventory (NEI) (EPA, 2001).…”

“…For inorganic PM 2.5 , the key emissions of gas-phase precursors are sulfur dioxide (SO 2 , often considered collectively with SO 2− 4 emissions as SO x ), nitrogen oxides (NO x ) and ammonia (NH 3 ). NH 3 is recognized as being both highly uncertain and influential for aerosol formation and thus a critical factor for improving estimated distributions of nitrate aerosol in the continental US (Park et al, 2004;Yu et al, 2005;Nowak et al, 2006;Park et al, 2006;Liao et al, 2007;Zhang et al, 2008;Wu et al, 2008;Stephen and Aneja, 2008). Previous inverse modeling studies of NH + 4 in the US using a Discrete Kalman filter (Gilliland and Abbitt, 2001) estimated improved monthly emissions scaling factors for total US NH 3 emissions using observations of ammonium wet deposition (Gilliland et al, 2003.…”