ACPD Atmospheric Chemistry and Physics Discussions ACPD 1680-7375 Copernicus GmbH Göttingen, Germany 10.5194/acpd-11-19953-2011 Observation and modeling of the evolution of Texas power plant plumes Zhou W. 1 Cohan D. S. 1 Pinder R. W. 2 Neuman J. A. 3 4 Holloway J. S. 3 4 Peischl J. 3 4 Ryerson T. B. 3 Nowak J. B. 3 4 Flocke F. M. 5 Zheng W. 5 Department of Civil and Environmental Engineering, Rice University, Houston, Texas Office of Research and Development, US Environmental Protection Agency, North Carolina, USA Chemical Sciences Division, Earth System Research Laboratory, NOAA, Boulder, Colorado, USA Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA National Center for Atmospheric Research, Boulder, Colorado, USA 13 07 2011 11 7 19953 19993 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys-discuss.net/11/19953/2011/acpd-11-19953-2011.html The full text article is available as a PDF file from http://www.atmos-chem-phys-discuss.net/11/19953/2011/acpd-11-19953-2011.pdf

During the second Texas Air Quality Study 2006 (TexAQS II), a full range of pollutants was measured by aircraft in eastern Texas during successive transects of power plant plumes (PPPs). A regional photochemical model is applied to simulate the physical and chemical evolution of the plumes. The observations reveal that SO<sub>2</sub> and NO<sub>y</sub> were rapidly removed from PPPs on a cloudy day but not on the cloud-free days, indicating efficient aqueous processing of these compounds in clouds. The model reasonably represents observed NO<sub>x</sub> oxidation and PAN formation in the plumes, but fails to capture the rapid loss of SO<sub>2</sub> (0.37 h<sup>−1</sup>) and NO<sub>y</sub> (0.24 h<sup>−1</sup>) in some plumes on the cloudy day. Adjustments to the cloud liquid water content (QC) and the default metal concentrations in the cloud module could explain some of the SO<sub>2</sub> loss. However, NO<sub>y</sub> in the model was insensitive to QC. These findings highlight cloud processing as a major challenge to atmospheric models. Model-based estimates of ozone production efficiency (OPE) in PPPs are 20–50 % lower than observation-based estimates. Possible explanations for this discrepancy include the observed rapid NO<sub>y</sub> loss which biases high some observation-based OPE estimates, and the model's under-prediction of isoprene emissions.

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