ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-9-2577-2009 Technical note: a new method for the Lagrangian tracking of pollution plumes from source to receptor using gridded model output Owen R. C. 1 2 Honrath R. E. 1 2 3 Department of Geological and Mining Engineering and Sciences, Michigan Technological University, USA Department of Civil and Environmental Engineering, Michigan Technological University, Houghton, Michigan, USA Atmospheric Sciences Program, Michigan Technological University, USA 08 04 2009 9 7 2577 2595 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.net/9/2577/2009/acp-9-2577-2009.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/9/2577/2009/acp-9-2577-2009.pdf

Lagrangian particle dispersion models (LPDMs) are powerful and popular tools used for the analysis of atmospheric trace gas measurements. However, it can be difficult to determine the transport pathway of emissions from their source to a receptor using the standard gridded model output, particularly during complex meteorological scenarios. In this paper we present a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (e.g., concentration) and backward (e.g., residence time) LPDM simulations. By comparing the pathway determined from this method with particle trajectories from both the forward and backward models, we show that this method successfully restores much of the Lagrangian information that is lost when the data are gridded. A sample analysis is presented, demonstrating that the source-to-receptor pathway determined from this method is more accurate and easier to use than existing methods using standard LPDM products (gridded fields of, e.g., concentrations and residence time). As demonstrated in an evaluation and an example application, the method requires agreement between the transport described by the forward and backward simulations and thus provides a means to assess the quality and reversibility of the simulation. Finally, we discuss the potential for combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor. Based on the advantages presented here, this new method can complement or even replace many of the standard uses of backward LPDM simulations.

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