ALBERT

Description: This work evaluates particle size–composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using micro-orifice uniform deposit impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO42−, NO3−, NH4+, Na+, Cl−, Mg2+, Ca2+, and K+ are compared to CMAQ model output for discrete sampling periods between 2002 and 2005. The observation sites were predominantly in remote areas (e.g., National Parks) in the USA and Canada, and measurements were typically made for a period of roughly 1 month. For SO42− and NH4+, model performance was consistent across the USA and Canadian sites, with the model slightly overestimating the peak particle diameter and underestimating the peak particle concentration compared to the observations. Na+ and Mg2+ size distributions were generally well represented at coastal sites, indicating reasonable simulation of emissions from sea spray. CMAQ is able to simulate the displacement of Cl− in aged sea spray aerosol, though the extent of Cl− depletion relative to Na+ is often underpredicted. The model performance for NO3− exhibited much more site-to-site variability than that of SO42− and NH4+, with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and accumulation modes resulted in differences in daily averages of up to 1 μg m−3 (10 %), while the difference in seasonal and annual model performance compared to observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE), Chemical Speciation Network (CSN), and Air Quality System (AQS) networks was very small. Two updates to the CMAQ aerosol model – changes to the assumed size and mode width of emitted particles and the implementation of gravitational settling – resulted in small improvements in modeled size distributions.

Description: Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-salt particles from the coastal surf zone is known to be elevated compared to that from the open ocean. Despite the importance of sea-salt emissions and chemical processing, the US EPA's Community Multiscale Air Quality (CMAQ) model has traditionally treated coarse sea-salt particles as chemically inert and has not accounted for enhanced surf-zone emissions. In this article, updates to CMAQ are described that enhance sea-salt emissions from the coastal surf zone and allow dynamic transfer of HNO3, H2SO4, HCl, and NH3 between coarse particles and the gas phase. Predictions of updated CMAQ models and the previous release version, CMAQv4.6, are evaluated using observations from three coastal sites during the Bay Regional Atmospheric Chemistry Experiment (BRACE) in Tampa, FL in May 2002. Model updates improve predictions of NO3−, SO42−, NH4+, Na+, and Cl− concentrations at these sites with only a 8% increase in run time. In particular, the chemically interactive coarse particle mode dramatically improves predictions of nitrate concentration and size distributions as well as the fraction of total nitrate in the particle phase. Also, the surf-zone emission parameterization improves predictions of total sodium and chloride concentration. Results of a separate study indicate that the model updates reduce the mean absolute error of nitrate predictions at coastal CASTNET and SEARCH sites in the eastern US. Although the new model features improve performance relative to CMAQv4.6, some persistent differences exist between observations and predictions. Modeled sodium concentration is biased low and causes under-prediction of coarse particle nitrate. Also, CMAQ over-predicts geometric mean diameter and standard deviation of particle modes at the BRACE sites. These over-predictions may cause too rapid particle dry deposition and partially explain the low bias in sodium predictions. Despite these shortcomings, the updates to CMAQ enable more realistic simulations of chemical processes in environments where marine air mixes with urban pollution. The model updates described in this article are included in the public release of CMAQv4.7 (http://www.cmaq-model.org).

Description: This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N2O5 parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM2.5) is dominated by overpredictions of unspeciated PM2.5 (PMother) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.