Environmental Modelling & Software 24 (2009) 938–939
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TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data Y.Q. Wang a, *, X.Y. Zhang a, Roland R. Draxler b a
Laboratory of Atmospheric Chemistry, Centre for Atmosphere Watch and Services, Chinese Academy of Meteorological Sciences, 46 Zhong-Guan-Cun South Avenue, Beijing 100081, China NOAA Air Resources Laboratory, Silver Spring, MD, USA
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 November 2008 Received in revised form 9 January 2009 Accepted 9 January 2009 Available online 20 February 2009
Statistical analysis of air mass back trajectories combined with long-term ambient air pollution measurements are useful tools for source identification. Using these methods, the geographic information system (GIS) based software, TrajStat, was developed to view, query, and cluster the trajectories and compute the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses when measurement data are included. Ó 2009 Published by Elsevier Ltd.
Keywords: Trajectory statistics GIS Clustering PSCF CWT
Software availability Program name: TrajStat – Trajectory Statistics. Developer: Yaqiang Wang. Contact address:
[email protected] Year first available: 2008. Software required: MS Windows with Microsoft .NET Framework 2.0 installed. Program language: Visual Basic. Program size: 9.3 MB. Availability: http://www.arl.noaa.gov/ready/hysplit4.html Cost: Free of charge 1. Software description Identification of pollutant sources using ambient air quality data is essential for air pollution management. Air mass back trajectory statistical analyses, such as clustering (Harris and Kahl, 1990; Sirois and Bottenheim, 1995), potential source contribution function (PSCF) (Ashbaugh et al., 1985) and concentration weighted trajectory (CWT) (Hsu et al., 2003; Seibert et al., 1994), are frequently
* Corresponding author. Tel.: þ86 10 58995237; fax: þ86 10 62176414. E-mail address:
[email protected] (Y.Q. Wang). 1364-8152/$ – see front matter Ó 2009 Published by Elsevier Ltd. doi:10.1016/j.envsoft.2009.01.004
used to point out the direction and sources of air pollution at a receptor site. For air trajectory calculation, the software programs of HYSPLIT (Draxler and Hess, 1998) and FLEXTRA (Stohl, 1999) have been widely used. Recently, METEX (Zeng et al., 2008) was developed with an emphasis on flexibility and ease-of-use. For air mass trajectory visualization and statistical analysis applications, a new software application called TrajStat was developed in which clustering, PSCF and CWT methods were included and a geographic information systems (GIS) technique built from the open-source GIS component MapWindowGIS ActiveX control (MapWindow open source team, 2007) was used for spatial data management, visualization and analyses. The HYSPLIT model is used to calculate trajectories, which are loaded into the system as an external process. The trajectory files with three-dimensional endpoint data could be converted to the ESRI ‘‘PolylineZ’’ shape file format. In this type of shape file the x, y and z properties of each point are defined by its longitude, latitude and air pressure along the trajectory. The trajectories can be shown in various spatial patterns. For instance, using only the level (x, y) or height (z) coordinates, each trajectory can be shown as a twodimensional figure. When combined height with longitude and latitude values, the three-dimensional trajectories can be plotted. The long-term measurement data could be assigned to their corresponding trajectories. A query function was developed to identify the trajectories to which a user can distinguish the polluted
Y.Q. Wang et al. / Environmental Modelling & Software 24 (2009) 938–939
trajectories with high measurement concentration from a large number of trajectories and then the pollutant pathway could be roughly estimated. Euclidean distance or angle distance (Sirois and Bottenheim, 1995) can be selected as the cluster model. A reasonable maximum cluster number can be decided through visual inspection and comparison of the mean-trajectory maps. The mean pollutant concentration for each cluster can be computed using the cluster statistics function. Pollutant pathways could then be associated with the high concentration clusters. After calculating the PSCF and CWT value, an arbitrary weight function (Polissar et al., 1999) is applied to reduce the uncertainty of cells with few endpoints. Then the potential source regions with high PSCF or CWT value could be identified. Additional functions will be considered for future upgrades such as applying confidence intervals and smoothing functions for CWT (Seibert et al., 1994) and adding the RTWC (Stohl, 1996) analysis function.
Acknowledgements This study was supported by grants from the Fund of CAMS (2008Z004) and National Basic Research Program of China (2006CB403700).
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