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  • Author or Editor: S-Å Gustafson x
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S-Å Gustafson, K. O. Kortanek, and J. R. Sweigart


A technique is proposed for objection interpolation of the air quality distribution over a region in terms of sparse measurement data. Empirical information provided by the latter is effectively combined with knowledge of atmospheric dispersion functions of the type commonly used in source-oriented air quality models, to provide improved estimates of the concentration distribution over an extended region. However, the technique is not primarily source-oriented since, in contrast to the real source distribution of a source-oriented model, it utilizes fictitious or pseudò sources that are estimated in terms of the measured air quality data. This involves the use of interpolation functions that are computed using numerical optimization techniques based on the method of least squares. Due to the large number of different “weather” states that affect the atmospheric dispersion of pollution, considerable computation is required, although the bulk of this can be done in advance, so that the final interpolation from the measured values only requires very simple calculation. Thus the proposed method has the potential for application on a real-time basis.

In addition to the mathematical formulation of the problem, this preliminary study includes some numerical experiments, using a current multiple source EPA air quality model, to illustrate the technique that is proposed.

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C. P. Weaver, X.-Z. Liang, J. Zhu, P. J. Adams, P. Amar, J. Avise, M. Caughey, J. Chen, R. C. Cohen, E. Cooter, J. P. Dawson, R. Gilliam, A. Gilliland, A. H. Goldstein, A. Grambsch, D. Grano, A. Guenther, W. I. Gustafson, R. A. Harley, S. He, B. Hemming, C. Hogrefe, H.-C. Huang, S. W. Hunt, D.J. Jacob, P. L. Kinney, K. Kunkel, J.-F. Lamarque, B. Lamb, N. K. Larkin, L. R. Leung, K.-J. Liao, J.-T. Lin, B. H. Lynn, K. Manomaiphiboon, C. Mass, D. McKenzie, L. J. Mickley, S. M. O'neill, C. Nolte, S. N. Pandis, P. N. Racherla, C. Rosenzweig, A. G. Russell, E. Salathé, A. L. Steiner, E. Tagaris, Z. Tao, S. Tonse, C. Wiedinmyer, A. Williams, D. A. Winner, J.-H. Woo, S. WU, and D. J. Wuebbles

This paper provides a synthesis of results that have emerged from recent modeling studies of the potential sensitivity of U.S. regional ozone (O3) concentrations to global climate change (ca. 2050). This research has been carried out under the auspices of an ongoing U.S. Environmental Protection Agency (EPA) assessment effort to increase scientific understanding of the multiple complex interactions among climate, emissions, atmospheric chemistry, and air quality. The ultimate goal is to enhance the ability of air quality managers to consider global change in their decisions through improved characterization of the potential effects of global change on air quality, including O3 The results discussed here are interim, representing the first phase of the EPA assessment. The aim in this first phase was to consider the effects of climate change alone on air quality, without accompanying changes in anthropogenic emissions of precursor pollutants. Across all of the modeling experiments carried out by the different groups, simulated global climate change causes increases of a few to several parts per billion (ppb) in summertime mean maximum daily 8-h average O3 concentrations over substantial regions of the country. The different modeling experiments in general do not, however, simulate the same regional patterns of change. These differences seem to result largely from variations in the simulated patterns of changes in key meteorological drivers, such as temperature and surface insolation. How isoprene nitrate chemistry is represented in the different modeling systems is an additional critical factor in the simulated O3 response to climate change.

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