Evaluation of model simulated atmospheric constituents with observations in the factor projected space: CMAQ simulations of SEARCH measurements |
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| Authors: | Amit Marmur Wei Liu Yuhang Wang Armistead G Russell Eric S Edgerton |
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| Institution: | 1. Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA 30332, United States;2. Georgia Institute of Technology, School of Civil and Environmental Engineering, Atlanta, GA 30332, United States;3. Atmospheric Research and Analysis, Inc., Cary, NC 27513, United States;4. ENVIRON International Corporation, Novato, CA 94998, United States;1. Department of Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD 20742, USA;2. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA;3. NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA;4. NASA Langley Research Center, Hampton, VA 23681, USA;5. National Center for Atmospheric Research, Boulder, CO 80305, USA;6. Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80303, USA;7. Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA;8. Institut für Ionenphysik und Angewandte Physik, Universität Innsbruck, Innsbruck, Austria;1. School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;2. School of Chemical and Biomolecular Engineering, Georgia Institute Technology, Atlanta, GA 30332, USA;3. Center for Climate Systems Research, Columbia University, New York, NY 10025, USA;4. NASA Goddard Institute for Space Studies, New York, NY 10025, USA;5. Northeast States for Coordinated Air Use Management, Boston, MA 02111, USA;6. School of Earth & Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA;1. Department of Environmental Engineering, School of City Construction, Hebei University of Engineering, Handan, Hebei 056038, China;2. Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN 37996, USA;3. Department of Environmental Science, Beijing University of Technology, Beijing 100124, China;1. College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, China;2. Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA;3. Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA;4. Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA;5. Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA;1. School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA;2. School of Energy and Environment, Southeast University, Nanjing, China |
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| Abstract: | Two-year CMAQ simulations of gases and aerosols over the southeast are evaluated using SEARCH observations for 2000 and 2001, both by direct comparison to observations and by projecting both datasets to the factor space using the Positive Matrix Factorization (PMF) model. Model performance for secondary species (sulfate, ozone) is generally better than for primary species (EC, CO). Nitrate concentrations are overestimated, mainly due to wintertime over-partitioning to the particulate phase. Projecting both observed and simulated constituents to the factor space using PMF, four common factors are resolved for each surface site (two urban sites and two rural sites). The resolved factors include (1) secondary sulfate, (2) secondary nitrate, (3) a fresh motor vehicle factor characterized by EC, OC, CO, NO and NOy, and (4) a mixed factor characterized by EC, OC, and CO. Performance for the sulfate and nitrate factors follow that of the corresponding driving species, while the motor vehicle and “mixed” factors exhibit performance corresponding to that of primary species. Comparing observations and CMAQ simulations in the projected space allow for an evaluation of the co-variability between species, an indicator of source impacts. The fact that similar factors were resolved by PMF from both the observations and the CMAQ simulations suggests that temporal processes related to emissions from specific source categories, as well as the subsequent dispersion and reactivity, are well captured by the CMAQ model. The ability to identify additional factors can be enhanced by adding tracer species in CMAQ simulations. |
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