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JOURNAL OF GEOPHYSICAL RESEARCH,
VOL. 110,
D13308,
23 PP., 2005
doi:10.1029/2004JD004918
Multiscale Air Quality Simulation Platform (MAQSIP): Initial applications and performance for tropospheric ozone and particulate matter
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Georgia Institute of Technology, Atlanta, Georgia, USA
Baron Advanced Meteorological Systems, Raleigh, North Carolina, USA
Baron Advanced Meteorological Systems, Raleigh, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Baron Advanced Meteorological Systems, Raleigh, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, North Carolina, USA
The performance of the Multiscale Air Quality Simulation Platform (MAQSIP) in simulating the regional distributions of tropospheric ozone and particulate matter (PM) is evaluated through comparisons of model results from three-dimensional simulations against available surface and aircraft measurements. These applications indicate that the model captures the dynamic range of observations and the spatial trends represented in measurements. Some discrepancies also exist, however, and they are discussed in the context of model formulation, input data specification and assumptions, and variability and bias in measurements. The daily normalized bias (within ±20%) and normalized gross errors (<25%) for predicted surface level O3 over an entire summer season are within the suggested performance criteria for management evaluation studies and are comparable to, if not smaller than, those reported previously for other regional O3 models. Comparisons of modeled PM composition with speciated fine particle concentration measurements show that the model is able to capture the spatial variability in fine PM mass as well as in the inorganic component fractions. Both measurements and model results show that in the summertime in the eastern U.S., SO4 2− is a relatively large component of fine PM mass; in contrast, NO3 − is a significant fraction in the western U.S. in the wintertime case studied. The ability of the model to simulate the observed visibility indices (extinction coefficient and deciview) are evaluated through comparisons of model estimates using both a detailed Mie theory-based calculation (based on predicted aerosol size and number distributions) and an empirical mass reconstruction algorithm. Both modeled and observed data show that among the various aerosol components, in the eastern U.S. SO4 2− contributes the largest fraction to the aerosol extinction (35–85%), while organic mass contributes up to 20–25%. In contrast, in the western U.S., SO4 2− and NO3 − have comparable contributions (20–50%) to the observed aerosol extinction. Comparisons with limited observational aircraft data, however, show moderate to poor correlation with measurements in the free troposphere. While these discrepancies can be attributed in part to model initialization and lateral boundary conditions specification, there is a need for further evaluation of the representation of boundary layer-free troposphere exchange mechanisms as well as the chemical mechanisms currently used in the model for representing chemistry in the free troposphere.
Received 16 April 2004; accepted 11 April 2005; published 15 July 2005.
Citation: (2005), Multiscale Air Quality Simulation Platform (MAQSIP): Initial applications and performance for tropospheric ozone and particulate matter, J. Geophys. Res., 110, D13308, doi:10.1029/2004JD004918.
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