This data package was submitted to a staging environment for testing purposes only. Use of these data for anything other than testing is strongly discouraged.

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  • Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021
  • Heindel, Ruth C; Assistant Professor of Environmental Studies; Kenyon College
  • 2024-12-11
  • Heindel, R.C. 2024. Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021 ver 1. Environmental Data Initiative. https://doi.org/DOI_PLACE_HOLDER (Accessed 2024-12-27).
  • This data package contains modeled air parcel back-trajectories generated using the Stochastic Time-Inverted Lagrangian Transport model (STILT) via the R interface. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, and to connect the geochemistry of deposited dust to air mass trajectories. Back-trajectories are three-dimensional paths of air parcels from a receptor site (the dust collection site) backwards in time and space for the duration of the tracking interval, calculated iteratively using wind fields from high-resolution gridded meteorological data. To calculate a probability of potential pathways, rather than a single back-trajectory, STILT introduces small random perturbations into the wind fields during each time step. For four sites along an urban-rural transect in central Ohio for June-July 2021, we generated weekly footprints of potential sources for the dust deposited at each site. These back-trajectories can be paired with geochemical data to establish a connection between land use and anthropogenic dust composition. This dataset is complete and will not be updated.

  • N: 40.36882      S: 39.94561      E: -82.39015      W: -83.00555
  • edi.1825.1  (Uploaded 2024-12-11)  
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  • Data Entities:
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    3. SciotoAudubonJune15  (438.5 MiB; 0 downloads) 
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    5. SciotoAudubonJune01  (454.9 MiB; 0 downloads) 
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    12. RockyForkJune15  (435.7 MiB; 0 downloads) 
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    14. RockyForkJune01  (471.0 MiB; 0 downloads) 
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    18. RockyForkJuly06  (435.5 MiB; 0 downloads) 
    19. KenyonJune29  (472.1 MiB; 0 downloads) 
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    28. BlendonWoodsJune29  (464.4 MiB; 0 downloads) 
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    35. BlendonWoodsJuly13  (460.5 MiB; 0 downloads) 
    36. BlendonWoodsJuly06  (435.2 MiB; 0 downloads) 
  • This information is released under the Creative Commons license - Attribution - CC BY (https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) is required to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you.
  • DOI PLACE HOLDER

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